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In this paper, we develop an integral reinforcement learning (IRL)‐based trajectory tracking control (TTC) scheme via firefly optimized neural networks for partially unknown multiplayer nonlinear systems. Under the developed TTC scheme, IRL is proved to be equivalent to the classical policy iteration, which guarantees the convergence of the IRL algorithm. By implementing the IRL method, the requirement of the drift dynamics is obviated. The TTC policy for each player is obtained by solving the coupled Hamilton–Jacobi equation with a critic neural network, whose weight vector is tuned by the firefly algorithm. The tracking error of the closed‐loop system is guaranteed to be stable via the Lyapunov's direct method. Simulation results illustrate the effectiveness and superiority of the present IRL‐based TTC scheme, and show that the success rate of system operation is increased by introducing the firefly algorithm. [ABSTRACT FROM AUTHOR]

Al2O3-SiC-C (ASC) castables containing spherical asphalt are widely utilized in high-temperature metallurgical furnaces because of their good abrasive resistance and slag resistance; however, the release of hazardous benzopyrene during the pyrosis process in spherical asphalt is detrimental to the environment and to the health of furnace workers. Herein, nontoxic nano carbon black (CB) was selected as the carbon source for ASC castables, and the effects of the CB amount and sintering atmosphere on the properties of ASC castables were investigated in this work. The results show that on increasing CB from 0.5% to 2%, the cold strength of the samples after firing in the reducing atmosphere increased, the residual strength increased, and the slag penetrated depth decreased; the reasons can be ascribed to nano CB being able to fill the pores to reduce the apparent porosity of the castables. Furthermore, SiC whiskers were formed at elevated temperatures and generated a network structure, which was beneficial in improving their properties. When CB was 1%, the cold modulus of the rupture of the samples after firing in the oxidizing atmosphere and reducing atmosphere were higher (about 20 MPa), the retained strength ratio of the samples pre-fired in the reducing atmosphere was the highest (85.4%), the hot strength at 1400 °C of the samples tested in the oxidized atmosphere was the highest (5.3 MPa), and the slag resistance of the samples measured in the oxidizing atmosphere was the best. The castables heat-treated in the air atmosphere possessed higher hot strength and slag resistance; the reasons can be attributed to the formed SiO2 derived from the oxidation of SiC, which reacted with Al2O3 to form mullite, creating a strengthening effect and decreasing the porosity and increasing the viscosity of slag, thereby improving the hot strength and slag resistance. [ABSTRACT FROM AUTHOR]

Simple Summary: This preliminary study aims to shed light on the behaviour of some predatory entomofauna species found in the snail farms of Sardinia. We observed the interactions between snails and their natural predators in laboratory conditions. This approach enabled us to address a significant gap in the scientific literature by investigating whether specific types of shell damage could be characteristic of certain insect families or species. Heliciculture farms are susceptible to significant biotic issues that can impact snail breeding, among them, the entomofauna predation of snails. Predatory insects can cause damage to snail shells during predation, and sometimes, the specific type of damage may be characteristic of certain insect families or species. Under laboratory conditions, we analysed the predatory activity of the species Silpha tristis Illiger, 1798 (Coleoptera: Silphidae), Ocypus olens (Müller, 1764) (Coleoptera: Staphylinidae), Carabus (Macrothorax) morbillosus constantinus Kraatz, 1899 (Coleoptera: Carabidae), and Lampyris sardiniae Geisthardt, 1987 (Coleoptera: Lampyridae) against the gastropod Cornu aspersum (Müller, 1774) reared on snail farms located in the Sardinian region. The adult and larval stages of each species were tested, except for L. sardiniae, as only the larval stage preys upon snails. This study showed that among all of the species considered, only two insects were able to damage the shell of C. aspersum: C. morbillosus constantinus and O.olens. This may prove valuable in C. aspersum breeding for the recognition of specific lesions, even in the absence of the predator. [ABSTRACT FROM AUTHOR]

Engineering and economics both make extensive use of fractional programming. Because they are highly nonconvex and multimodal, they are regarded as challenging. This paper proposes an enhanced firefly algorithm (HFA) for solving fractional programming . The new population mean center is predicted by using the historical data of the population mean centers and added to the movement equation of fireflies to better guide their search. Numerical experiments are provided to demonstrate the efficiency and robustness of HFA. The results obtained by HFA show that it is always better than those produced by other methods. [ABSTRACT FROM AUTHOR]

Accurately estimating the remaining useful life (RUL) of batteries is crucial for optimizing maintenance, preventing failures, and enhancing reliability, thereby saving costs and resources. This study introduces a hybrid approach for estimating the RUL of a battery based on the firefly algorithm–neural network (FA–NN) model, in which the FA is employed as an optimizer to fine-tune the network weights and hidden layer biases in the NN. The performance of the FA–NN is comprehensively compared against two hybrid models, namely the harmony search algorithm (HSA)–NN and cultural algorithm (CA)–NN, as well as a single model, namely the autoregressive integrated moving average (ARIMA). The comparative analysis is based mean absolute error (MAE) and root mean squared error (RMSE). Findings reveal that the FA–NN outperforms the HSA–NN, CA–NN, and ARIMA in both employed metrics, demonstrating superior predictive capabilities for estimating the RUL of a battery. Specifically, the FA–NN achieved a MAE of 2.5371 and a RMSE of 2.9488 compared with the HSA–NN with a MAE of 22.0583 and RMSE of 34.5154, the CA–NN with a MAE of 9.1189 and RMSE of 22.4646, and the ARIMA with a MAE of 494.6275 and RMSE of 584.3098. Additionally, the FA–NN exhibits significantly smaller maximum errors at 34.3737 compared with the HSA–NN at 490.3125, the CA–NN at 827.0163, and the ARIMA at 1.16e + 03, further emphasizing its robust performance in minimizing prediction inaccuracies. This study offers important insights into battery health management, showing that the proposed method is a promising solution for precise RUL predictions. [ABSTRACT FROM AUTHOR]

Rhabdophis chiwen is currently found so far in Sichuan Province, China, where it predominantly feeds on earthworms and firefly larvae. In this study, we sequenced and analyzed the mitochondrial genome of R. chiwen, which measured 17,646 bp in length and encompassed 37 genes along with two control regions. The base composition revealed percentages of 33.20% A, 25.94% T, 13.27% G, and 27.59% C. Phylogenetic analyses indicate that R. chiwen belongs to the family Colubridae and forms a sister branch with R. tigrinus. This study successfully obtained the first complete mitochondrial genome of R. chiwen, offering crucial genetic data for its evolutionary history and conservation. [ABSTRACT FROM AUTHOR]

The beetle superfamily Elateroidea comprises the most biodiverse bioluminescent insects among terrestrial light-producing animals. Recent exceptional fossils from the Mesozoic era and phylogenomic studies have provided valuable insights into the origin and evolution of bioluminescence in elateroids. However, due to the fragmentary nature of the fossil record, the early evolution of bioluminescence in fireflies (Lampyridae), one of the most charismatic lineages of insects, remains elusive. Here, we report the discovery of the second Mesozoic bioluminescent firefly, Flammarionella hehaikuni Cai, Ballantyne & Kundrata gen. et sp. nov., from the Albian/Cenomanian of northern Myanmar (ca 99 Ma). Based on the available set of diagnostic characters, we interpret the specimen as a female of stem-group Luciolinae. The fossil possesses deeply impressed oval pits on the apices of antennomeres 3–11, representing specialized sensory organs likely involved in olfaction. The light organ near the abdominal apex of Flammarionella resembles that found in extant light-producing lucioline fireflies. The growing fossil record of lampyrids provides direct evidence that the stunning light displays of fireflies were already established by the late Mesozoic. [ABSTRACT FROM AUTHOR]

Firefly algorithm (FA) combined with extreme learning machine (ELM) is developed for spectral interval selection and quantitative analysis of complex samples. The method firstly segments the spectra into a certain number of intervals. Vectors with 1 and 0, which represent the interval selected or not, are used as the inputs of the FA. The RMSEP value predicted by ELM model is used as the fitness function of the FA. The activation function and number of hidden layer nodes of ELM, number of spectral intervals, population number, environmental absorbance, and constant of FA are optimized. The predictive performance of FA‐ELM is compared with full‐spectrum PLS, ELM, genetic algorithm‐ELM (GA‐ELM), and particle swarm optimization‐ELM (PSO‐ELM) by one ultraviolet (UV) spectrum dataset of gasoil and three near‐infrared (NIR) spectral datasets of corn, wheat, and tablet samples. The results show that FA‐ELM has a better performance compared with its competitors in predicting monoaromatics, water, wheat kernel texture, and active pharmaceutical ingredients (APIs) in gasoil, corn, wheat, and tablet samples. [ABSTRACT FROM AUTHOR]

This paper presents a modified metaheuristic algorithm named the modified Firefly algorithm. Any metaheuristic algorithm will have exploration and exploitation steps, and the goal of modification is to maintain a balance between them. The improvement relies on movement equations, alterations to the algorithm's structure by introducing a single loop, and a selection of movement equations at random. Two movement equations are included in the improved method and are randomly selected. This guarantees both regionally and globally focused solution-finding. This prevents the algorithm from getting stuck at a local minimum. Comparing the modified version to the original Firefly method, just one for loop is used, reducing the algorithm's complexity. The algorithm's performance is evaluated with 35 traditional benchmark test functions and 10 CEC2019 test functions. According to the findings, the suggested method performed optimally in 24 traditional benchmark test functions and best in the six remaining benchmark test functions. The improved algorithm produced the best outcomes in seven of the 10 CEC2019 test functions. In contrast, the Firefly algorithm produced optimal results in 18 classical benchmark test functions and the best results in 6 CEC2019 test functions. The proposed algorithm is compared with other variants of the Firefly algorithm for common test functions in the literature. The results show that the proposed algorithm outperforms other variants in most test functions. [ABSTRACT FROM AUTHOR]

The important role of the dynamic structure of firefly luciferase in enzyme functioning is a subject of this literature review. Due to the domain alternation, the optimal configuration of the active site is created for each stage of the luciferin oxidation. The diversity of bioluminescence spectra is explained by the combined emission of several coexisting forms of electronically excited oxyluciferin. The superposition of two or three emitter forms recorded in the bioluminescence spectra indicates that different luciferase conformers coexist in the reaction medium in dynamic equilibrium. The relationship between the thermal stability of the protein globule and the bioluminescence spectra is also discussed [ABSTRACT FROM AUTHOR]

Clustering is one of the most important approaches used to extend the lifetime of Wireless Sensor Networks (WSN). The fundamental metric taken by clustering algorithms is energy enhancement. Moreover, network coverage and load balance are two important approaches that play crucial roles in improving network lifetime and delivery since the former focuses on maximizing the use of all network resources, while the second is based on distributing the load between the nodes to enhance the energy consumption. As the challenge of clustering nodes in an energy-efficient way is an NP-Hard problem, firefly optimization algorithm is used to address this challenge. However, the proposed solutions focus on centralized processing of the algorithm, which makes them unsuitable for large-scale WSN. In this paper, a double firefly based efficient clustering solution is proposed for large-scale WSN which is implemented in a decentralized fashion to improve the lifetime and packet delivery. The first firefly algorithm is used by each node to move to the best initial Cluster Head (CH) by performing a balance of belonging between the clusters, while the second algorithm is used only between the initial CHs to eliminate membership redundancy and optimally construct balanced clusters. The simulation results show that our proposed solution significantly improves the network lifetime as well as the delivery rate. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) facilitates connectivity in businesses and smart homes by integrating embedded technology, wireless sensor networks and data aggregation. Regular monitoring of energy usage in IoT networks is crucial due to the high energy consumption and delays in transmitting data to the Base Station (BS) by the sensor nodes. The most significant challenges in IoT include energy depletion and transmission delays. In this research, the proposed Differential Evolution with Sailfish Optimization (DESFO) model addresses large network handling, achieves maximum convergence rates, and reduces energy consumption. The Differential Evolution (DE) mutation and crossover operators enhance exploration capabilities, while SFO adaptive movement strategies improve the exploitation of the search space. Together, they achieve high convergence rates, prevent falling into local optima, provide iterative control and manage high-dimensional networks effectively. The DESFO method exhibits superior performance when compared to the existing methods, Firefly Optimization and Aquila Optimization (FF-AO), Fixed-Parameter Tractable Approximation Clustering (FPTAC), and Cluster based Reliable Data Aggregation-Sunflower Optimization (CRDA-SFO). The proposed DESFO method yields impressive results, achieving a Packet Delivery Ratio (PDR) of 96.12% at 250 nodes, a Delay of 3ms at 250node, Energy consumption of 12J at 250 respectively. [ABSTRACT FROM AUTHOR]

Image dehazing is said to be an emerging research area in the platform of computer vision and image processing. Due to the cruel fog, air dispersion, and haze around the environment, the hazes images are resulted in different challenges in retrieving the actual information of the original image. On the other hand, the conventional approaches are ensured with the huge computational complexity and also with the distortion of actual images like over-saturation and halos. The recent methods are used for restoring the haze-free images however they are worked with the physical models and along with the learning methods. It is a very challenging task to maintain the detailed details of the image at the time of reducing the fog in the single-image dehazing. With an advanced development deep structured strategy, mostly Convolutional Neural Network (CNN)-aided dehazing approaches are developed for processing the single image dehazing. However, haze residual and slow training of the convergence rate are considered as the two main drawbacks in these conventional dehazing networks. To deal with these problems, the latest approach is proposed for the restoration of haze-free images. The hazy images are gathered from the standard datasets. At first, Adaptive Discrete Wavelet Transform (ADWT) is utilized for decomposing the images, where the ADWT is implemented by Hybrid African Vultures Fire Fly Optimization (HAVFFO). Further, image dehazing is designed by Optimized Residual-Based Deep CNN (OR-Deep CNN), where the hyperparameters of the Residual-Based Deep CNN are optimized by the same HAVFFO. Finally, the restoration of haze-free images is carried out through adaptive inverse DWT. Through the performance analysis, our recommended model is better in quantitative visual and performances on online resources. [ABSTRACT FROM AUTHOR]

Sexual dimorphism arises because of divergent fitness optima between the sexes. Phenotypic divergence between sexes can range from mild to extreme. Fireflies, bioluminescent beetles, present various degrees of sexual dimorphism, with species showing very mild sexual dimorphism to species presenting female-specific neoteny, posing a unique framework to investigate the evolution of sexually dimorphic traits across species. In this work, we present novel assembled genomes of two firefly species, Lamprohiza splendidula and Luciola italica, species with different degrees of sexual dimorphism. We uncover high synteny conservation of the X-chromosome across ~ 180 Mya and find full X-chromosome dosage compensation in our two fireflies, hinting at common mechanism upregulating the single male X-chromosome. Different degrees of sex-biased expressed genes were found across two body parts showing different proportions of expression conservation between species. Interestingly, we do not find X-chromosome enrichment of sex-biased genes, but retrieve autosomal enrichment of sex-biased genes. We further uncover higher nucleotide diversity in the intronic regions of sex-biased genes, hinting at a maintenance of heterozygosity through sexual selection. We identify different levels of sex-biased gene expression divergence including a set of genes showing conserved sex-biased gene expression between species. Divergent and conserved sex-biased genes are good candidates to test their role in the maintenance of sexually dimorphic traits. Sexual dimorphism reflects divergent requirements between the sexes. We explore gene expression between two fireflies that show mild and extreme dimorphism. We uncover conserved and divergent gene expression, including complete dosage compensation. [ABSTRACT FROM AUTHOR]

Disruption of alternative splicing frequently causes or contributes to human diseases and disorders. Consequently, there is a need for efficient and sensitive reporter assays capable of screening chemical libraries for compounds with efficacy in modulating important splicing events. Here, we describe a screening workflow employing dual Nano and Firefly luciferase alternative splicing reporters that affords efficient, sensitive, and linear detection of small molecule responses. Applying this system to a screen of ~95,000 small molecules identified compounds that stimulate or repress the splicing of neuronal microexons, a class of alternative exons often disrupted in autism and activated in neuroendocrine cancers. One of these compounds rescues the splicing of several analyzed microexons in the cerebral cortex of an autism mouse model haploinsufficient for Srrm4, a major activator of brain microexons. We thus describe a broadly applicable high-throughput screening system for identifying candidate splicing therapeutics, and a resource of small molecule modulators of microexons with potential for further development in correcting aberrant splicing patterns linked to human disorders and disease. Here the authors perform a high-throughput screen to identify compounds that stimulate or repress the splicing of neuronal microexons. One of these compounds rescues the splicing of several microexons in the brains of mice haploinsufficient for Srrm4. [ABSTRACT FROM AUTHOR]

Nowadays, technology has shifted the way individuals access news from conventional media sources to social media platforms. The active engagement of people with social media platforms leads them to consume news without confirming its source or legitimacy. This facilitated the dissemination of more manipulated and false information in the form of rumors and fake news. Fake news can affect public opinion and create chaos and panic among the population. Thus, it is essential to employ an advanced methodology to identify fake news with high precision. This research work has proposed the concept of the quantum-inspired firefly algorithm with the ant miner plus algorithm (QFAMP) for more effective fake news detection. The proposed QFAMP algorithm utilizes the attributes of quantum computing (QC), the firefly algorithm (FA), and the ant miner plus algorithm (AMP). Here, the QFA approach ensures the effective exploitation of the firefly agents until the agents are able to search for the brighter firefly. Further, the AMP algorithm utilizes the best ants with higher pheromone concentrations for global exploration, which also avoids the premature convergence of the QFA agents. In addition, the AMP algorithm serves as an efficient data mining variant that is effective for the classification of fake news. The efficacy of the proposed QFAMP algorithm is evaluated for the dataset of FakeNewsNet, which is composed of two sub-categories: BuzzFeed and PolitiFact. The experimental evaluations indicate the effective performance of the proposed algorithm compared to the other techniques. [ABSTRACT FROM AUTHOR]

Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%. [ABSTRACT FROM AUTHOR]

Photinus gabicastanoae sp. nov. is described from the State of Michoacán, which morphologically differs from the known firefly species. In addition, its relationship with P palaciosi (Zaragoza-Caballero, 2012) is discussed. [ABSTRACT FROM AUTHOR]

Simple Summary: The family Lampyridae, commonly known as fireflies, is a cosmopolitan group comprising approximately 100 genera and 2200 species. Oculogryphus Jeng, Engel & Yang, 2007 is a small firefly genus endemic to Asia with only four known species and the phylogenetic position of it remains unresolved. It has been considered enigmatic because of its characteristic morphology intermingling different subfamilies, while its systematic status has never been rigorously tested due to a lack of molecular data. In this study, we obtained a large series of O. chenghoiyanae Yiu & Jeng, 2018 from southeastern China. We successfully sequenced and annotated its complete mitochondrial genome and clarified the systematic status of Oculogryphus. The firefly genus Oculogryphus Jeng, Engel & Yang, 2007 is a rare-species group endemic to Asia. Since its establishment, its position has been controversial but never rigorously tested. To address this perplexing issue, we are the first to present the complete mitochondrial sequence of Oculogryphus, using the material of O. chenghoiyanae Yiu & Jeng, 2018 determined through a comprehensive morphological identification. Our analyses demonstrate that its mitogenome exhibits similar characteristics to that of Stenocladius, including a rearranged gene order between trnC and trnW, and a long intergenic spacer (702 bp) between the two rearranged genes, within which six remnants (29 bp) of trnW were identified. Further, we incorporated this sequence into phylogenetic analyses of Lampyridae based on different molecular markers and datasets using ML and BI analyses. The results consistently place Oculogryphus within the same clade as Stenocladius in all topologies, and the gene rearrangement is a synapomorphy for this clade. It suggests that Oculogryphus should be classified together with Stenocladius in the subfamily Ototretinae at the moment. This study provides molecular evidence confirming the close relationship between Oculogryphus and Stenocladius and discovers a new phylogenetic marker helpful in clarifying the monophyly of Ototretinae, which also sheds a new light on firefly evolution. [ABSTRACT FROM AUTHOR]

This study explores the importance of vegetation (display trees) in shaping the habitat preferences, mating behaviours, and survival strategies of Pteroptyx fireflies in Southeast Asia, especially Malaysia. The research highlights the crucial role of diverse plant species, tree characteristics, and specific plant components in influencing firefly behaviour, emphasising the impact of vegetation composition, structure, and function. The findings underscore the essential role of vegetation in providing resources such as food, shelter, and suitable breeding sites, thereby shaping the distribution and abundance of firefly populations in their natural habitats. Moreover, the study elucidates the significant influence of plant-related chemical compounds and emissions on firefly behaviour and ecosystem dynamics, underscoring the intricate interplay between plant life and insect populations. This comprehensive understanding of the intricate dynamics between fireflies and their vegetation landscape has substantial implications for conservation efforts and the sustainable management of their habitats. [ABSTRACT FROM AUTHOR]

This paper discusses the improved capacity of colour image authentication in media applications and proposes an optimization-based robust watermarking algorithm. The algorithm first uses firefly optimization to compute the optimal embedding strength factor, which is useful for maintaining an effective relationship between robustness and quality. The combination of spatial and transformed domain schemes is then adopted to conceal the multiple marks on the different channels of the carrier media through the optimal strength factor. In order to make image marking safer, it is encrypted before being concealed by the media channel. Extensive experiments analyzed the impact of various results on Kodak and USI-SIPI datasets, demonstrating that the suggested algorithm has improved robustness, excellent quality, and high capacity. Superior to other existing schemes, the proposed algorithm achieves robustness of up to 11% with the improved watermark capacity. [ABSTRACT FROM AUTHOR]

Firefly flashes are well-known visual signals used by these insects to find, identify, and choose mates. However, many firefly species have lost the ability to produce light as adults. These "unlighted" species generally lack developed adult light organs, are diurnal rather than nocturnal, and are believed to use volatile pheromones acting over a distance to locate mates. While cuticular hydrocarbons, which may function in mate recognition at close range, have been examined for a handful of the over 2000 extant firefly species, no volatile pheromone has ever been identified. In this study, using coupled gas chromatography - electroantennographic detection, we detected a single female-emitted compound that elicited antennal responses from wild-caught male winter fireflies, Photinus corruscus. The compound was identified as (1S)-exo-3-hydroxycamphor (hydroxycamphor). In field trials at two sites across the species' eastern North American range, large numbers of male P. corruscus were attracted to synthesized hydroxycamphor, verifying its function as a volatile sex attractant pheromone. Males spent more time in contact with lures treated with synthesized hydroxycamphor than those treated with solvent only in laboratory two-choice assays. Further, using single sensillum recordings, we characterized a pheromone-sensitive odorant receptor neuron in a specific olfactory sensillum on male P. corruscus antennae and demonstrated its sensitivity to hydroxycamphor. Thus, this study has identified the first volatile pheromone and its corresponding sensory neuron for any firefly species, and provides a tool for monitoring P. corruscus populations for conservation and further inquiry into the chemical and cellular bases for sexual communication among fireflies.

Introduction: Use of indocyanine green (ICG) with near‐infrared fluorescence (NIRF) has been demonstrated to be an effective tool for intraoperative assessment of bowel and ureteric vascularity. This study aimed to evaluate the impact of ICG on postsurgical outcomes such as anastomotic bowel leak and uretero‐enteric stricture formation during robot‐assisted cystectomy (RAC) and intracorporeal urinary diversion (ICUD). Methods: We identified 238 patients who underwent RAC at the University of Louisville between September 2012 and August 2021. Patients were divided into two groups based on the utilization of ICG. Demographic, perioperative outcomes, and rate of anastomotic bowel leak were compared. Results: In total, 138 patients were in the ICG group and 100 patients were in the non‐ICG group. More intracorporeal urinary diversions and more simple cystectomies were observed in the ICG group (p < 0.001 and p = 0.015, respectively). The ICG group patients initiated an oral diet sooner than the control group (4.9 vs. 7.1 days, p < 0.001). The mean length of stay of the ICG group was shorter than the non‐ICG group (8.3 vs. 12.8 days, p < 0.001). The rate of postoperative ileus was not significantly different between cohorts. No patients in the ICG group experienced a bowel leak compared with five patients in the non‐ICG group (p = 0.008). Conclusions: In our study, the use of ICG for intraoperative assessment of bowel and ureteric vascularity was associated with earlier bowel recovery and a shorter length of stay. It was also significantly correlated with a lower rate of anastomotic bowel leak. [ABSTRACT FROM AUTHOR]

We have recently witnessed the rapid development of several emerging technologies, including the internet of things, which lead to a high interest in wireless sensor networks. Tiny sensor nodes are now important parts of a large number of complex systems, with numerous applications, including military, environment monitoring, and surveillance and body area sensor networks. A wireless sensor network builds the core part for IoT. Besides this, lifetime maximization is the biggest challenge in the wireless sensor network. Also, In a wireless sensor network, it is difficult to find an optimal node deployment approach that would minimize costs, be robust to node failures, decrease computing overhead and communication, and maintain a high degree of coverage and network connectivity. There is numerous literature addressed this challenge which is discussed in this paper; still there are lot many challenges yet to be addressed. Considering this scenario, in this paper, we propose a scheduled-based node deployment algorithm using Firefly Optimization (FA) to offer a circumstance where we have a group of target points that satisfy p-coverage and sensor nodes that satisfy q-connectivity, with subject to the selection of the optimal number of a sensor node that has the highest energy and minimum distance. The multiple parameters as no. of sensor nodes, distance, survivability factors, coverage, and connectivity of the sensor nodes are considered for designing the fitness function. A comprehensive statistical analysis is done using the simulation results to prove the proposed scheme's efficiency with other existing state-of-the-art methods under various p-coverage and q-connectivity configurations. [ABSTRACT FROM AUTHOR]

Artificial Light at Night (ALAN), particularly the blue lights with short wavelength (450 nm) sourced from LED contributing about 72% of the total ALAN has emerged as a thriving hazard, especially to the nocturnal biotic communities. Fireflies, possessing intrinsic property of bioluminescence are quite vulnerable to the negative impacts of ALAN which threatens the natural courses of their life cycle. The present field-based research highlights the effect of the exposure of differential ALAN intensities on the occurrence of fireflies (Coleoptera: Lampyridae: Luciolinae) for the first time from the Indian subcontinent. Declining effects on the abundance of larvae and adults of three terrestrial firefly species Abscondita chinensis, Abscondita perplexa, and Abscondita terminalis were observed at sites exposed under differential levels of ALAN intensities. Microhabitat occupancy of larvae altered significantly. Availability of larval prey snails increased. The ratio of biomass of the larvae and females represented a deteriorating trend. However, site-specific entomofaunal association did not vary significantly. Cluster analysis reflected the categorization of the study specimens under 3 different assemblages according to the lowest, medium, and highest ranges of ALAN exposure. Principal component analysis indicated that the abundance of adult insects was positively influenced by Sky Quality Meter (SQM) (PC1:0.98) and Naked- eye limiting magnitude (NELM) (PC1:0.97), whereas, the artificial brightness (AB) and total brightness (TB) (PC1: 0.92 for each) had shown negative impacts. The results suggest the scope of utilization of fireflies as a potential bioindicator for light pollution. [ABSTRACT FROM AUTHOR]

Dynamic workloads with varying parameters are delivered to data centers to be scheduled on virtual machines (VMs). These unreliable, inconsistent, shockingly rising workloads with changing resource requisites may cause data center servers to become imbalanced. Consequently, the servers' resource utilization and QoS get degraded which further subsides the energy usage. To meet the requirement for variable on-demand resource provisioning, the current infrastructure must be virtualized to escalate its capability and capacity. Furthermore, because of the existence of competing balancing constraints, load balancing in cloud systems is NP-hard. An efficient load-balancing strategy in coalition with a scheduling technique based on the fusion of the Firefly (FF) and Honeybee algorithm (HA) is implemented to resolve the shortcomings of load balancing. This article proposes an efficient Firefly and Honeybee-based Load Balancing algorithm (FHLBA), to optimize average load, response time, and turnaround time. This methodology not only improvises resource utilization and throughput but also depreciates the makespan, degree of imbalance. It initially executes the FF algorithm to explore potential search space and identify the best feasible mapping of tasks to VMs. Further, the HA technique is applied to eliminate over-usage and under-usage of resources and optimize resource usage as per the workload. The efficacy of the proposed technique is appraised through simulation of the independent and non-preemptive tasks on Cloudsim. A comparison with different mechanisms such as RR, FCFS, SJF, GA, IPSO, IPSO-Firefly, Firefly, OLB, and JAYA is given. The simulation results show the least average load of 0.238 ms, minimum average response time of 13.56 ms, memory usage up to 93%, effective CPU utilization of 98%, a throughput of 73%, and a makespan time of 148 ms, degree of imbalance of 172.01 is achieved with a variable volume of tasks and VMs. [ABSTRACT FROM AUTHOR]

The larvae of some lampyrid beetles are highly specialized predators of snails. They have been observed to climb on the shells of their prey and use this exposed position to bite and inject secretions potentially originating from the midgut. Besides serving the purpose of extra-oral digestion (EOD), injected compounds also seem to have a paralyzing effect. Up to now, the toxins causing this paralyzing activity have not been identified. In the current study, we provide a first compositional analysis of the midgut secretion from lampyrid larvae, with a focus on identifying putative neurotoxins causing the observed paralyzing effect. For this purpose, we utilized a combined proteo-transcriptomic approach to characterize the compounds present in the midgut secretion of larval stages of Lampyris noctiluca. In terms of the absolute numbers of identified compounds, the midgut secretion is dominated by hydrolyzing enzymes comprising peptidases, carboxylesterases, and glycosidases. However, when considering expression levels, a few rather short cysteine-rich peptides exceed all other compounds. Some of these compounds show moderate similarity to putative neurotoxins identified in the venom of other arthropods and could be responsible for paralyzing effects. In addition to these potential toxins, we provide a list of peptides typical of the midgut secretion of L. noctiluca, supplemented by the corresponding precursor sequences. [ABSTRACT FROM AUTHOR]

Many organisations have concentrated on how hyperspectral images allow for the automatic pixel-level classification and segmentation since each pixel's underlying spectrum is abundantly documented. Due to the unpredictable nature of the spectrum and the noise in the hyperspectral data, this task is very challenging and calls for specific solutions. The hyperspectral picture segmentation procedure in this instance makes use of the newly developed Namib Beetle Firefly Optimization (NBFO) method, which was created by combining the Namib Beetle Optimization method (NBOA) and Firefly Algorithm (FAO) for tackling optimisation issues. Therefore, in order to segment the images, the U-Net++ model is used. The DenseNet model, which is likewise trained using the NBFO approach, is then used to classify the segmented images. Utilising hyperspectral image segmentation techniques, the NBFO-driven DenseNet model surpassed the competition, resulting in a True Positive Rate (TPR) of 0.906786, a Positive Rate (FPR) of 0.889466, and a False Pixel Accuracy (FPA) of 0.931562. [ABSTRACT FROM AUTHOR]

This study explores the application and applicability of the Degree-Day Model in forecasting the phenology of fireflies, which serve as important indicators of environmental changes. The model is based on the relationship between temperature and the growth of organisms that rely on external sources of heat. It measures the amount of heat energy that accumulates over time by considering the daily temperature changes and a specific minimum temperature threshold. The accumulation of thermal energy allows for the prediction of important life cycle events in organisms like fireflies, particularly their emergence and peak activity levels, by considering their specific temperature requirements. The model has demonstrated efficacy in firefly phenology research, although with limited applications in only two research studies. In contrast, other animal species have been subjected to more comprehensive investigations, yielding a more precise approach to forecasting important events. Moreover, the model provides valuable information about the environmental parameters that impact the life cycles of fireflies, such as the complex correlation between the accumulation of degree-days and variables like precipitation. This model can be a useful tool for understanding and predicting how variations in temperature affect firefly populations. This helps us gain a better understanding of climate change and its impact on biodiversity. [ABSTRACT FROM AUTHOR]

Within the domain of network intrusion detection, this study conducts a comprehensive evaluation of machine learning models using both aggregated route data and the NSL-KDD dataset. The evaluation encompasses an array of quantitative and qualitative parameters, including crucial Quality of Service (QoS) metrics. A distinctive feature of this research is the application of the Firefly algorithm to fine-tune neural networks, thereby optimizing predictive capabilities. The study consistently highlights the superiority of the proposed Firefly-tuned Neural model, showcasing excellence in precision, recall, F-measure, accuracy, and QoS parameters. It also includes an approach that coordinates the K-means++ algorithm for careful data segmentation and fuzzy logic for the fine-grained assignment of membership degrees. The study highlights how important model selection is to cybersecurity and provides priceless information on the advantages of various algorithms. In conclusion, the amalgamation of route data clustering, Firefly algorithm optimization, and a comprehensive assessment of QoS parameters promises significant advancements in network intrusion detection systems. Future research should explore the real-world adaptability and scalability of these techniques, fortifying network security against evolving threats and intricate environments while simultaneously enhancing QoS. [ABSTRACT FROM AUTHOR]

Drilini are soft-bodied predatory click beetles with incompletely metamorphosed females. Approximately 150 described species are distributed in the Afrotropical, Palaearctic and Oriental realms, with the highest diversity known from sub-Saharan Africa. In this study, we describe Namibdrilus albertalleni gen. et sp. nov. from Namibia which brings the total number of genera in Drilini to 16. The discovery of this unique taxon sheds new light on the diversity and evolution of the enigmatic paedomorphic beetle lineage and is interesting for several reasons. This new species is the only known representative of Drilini that has unidentate mandibles and lacks a hook on the dorsal part of the aedeagal median lobe, two of the few characters heretofore used for the unambiguous identification of members of this group. Furthermore, based on its morphology it belongs to a group of genera (Drilus clade) which heretofore contained only taxa from the Palaearctic Realm. We provide an updated diagnosis of the tribe Drilini, as well as an updated diagnosis and an identification key for the genera of the Drilus clade based on adult males. Further, we explain how to easily recognize adult Drilini from similar-looking soft-bodied elateroids like Elateridae: Omalisinae, Rhagophthalmidae, and Lampyridae: Ototretinae. [ABSTRACT FROM AUTHOR]

Firefly luciferases emit yellow-green light and are pH-sensitive, changing the bioluminescence color to red in the presence of heavy metals, acidic pH and high temperatures. These pH and metal-sensitivities have been recently harnessed for intracellular pH indication and toxic metal biosensing. However, whereas the structure of the pH sensor and the metal binding site, which consists mainly of two salt bridges that close the active site (E311/R337 and H310/E354), has been identified, the specific role of residue H310 in pH and metal sensing is still under debate. The Amydetes vivianii firefly luciferase has one of the lowest pH sensitivities among the group of pH-sensitive firefly luciferases, displaying high bioluminescent activity and special spectral selectivity for cadmium and mercury, which makes it a promising analytical reagent. Using site-directed mutagenesis, we have investigated in detail the role of residue H310 on pH and metal sensitivity in this luciferase. Negatively charged residues at position 310 increase the pH sensitivity and metal sensitivity; H310G considerably increases the size of the cavity, severely impacting the activity, H310R closes the cavity, and H310F considerably decreases both pH and metal sensitivities. However, no substitution completely abolished pH and metal sensitivities. The results indicate that the presence of negatively charged and basic side chains at position 310 is important for pH sensitivity and metals coordination, but not essential, indicating that the remaining side chains of E311 and E354 may still coordinate some metals in this site. Furthermore, a metal binding site search predicted that H310 mutations decrease the affinity mainly for Zn, Ni and Hg but less for Cd, and revealed the possible existence of additional binding sites for Zn, Ni and Hg. [ABSTRACT FROM AUTHOR]

Vision plays a vital biological role in organisms, which depends on the visual pigment molecules (opsin plus chromophore). The expansion or reduction of spectral channels in the organisms is determined by distinct opsin classes and copy numbers resulting from duplication or loss. Within Coleoptera, the superfamily Elateroidea exhibits a great diversity of morphological and physiological characteristics, such as bioluminescence, making this group an important model for opsin studies. While molecular and physiological studies have been conducted in Lampyridae and Elateridae, other families remain unexplored. Here, we reused transcriptome datasets from Elateroidea species, including members of Elateridae, Lampyridae, Phengodidae, Rhagophthalmidae, Cantharidae, and Lycidae, to detect the diversity of putative opsin genes in this superfamily. In addition, we tested the signature of sites under positive selection in both ultraviolet (UV)‐ and long‐wavelength (LW)‐opsin classes. Although the visual system in Elateroidea is considered simple, we observed events of duplication in LW‐ and UV‐opsin, as well as the absence of UV‐opsin in distinct families, such as larval Phengodidae individuals. We detected different copies of LW‐opsins that were highly expressed in the eyes of distinct tribes of fireflies, indicating the possible selection of each copy during the evolution of the sexual mating to avoid spectrum overlapping. In Elateridae, we found that the bioluminescent species had a distinct LW‐opsin copy compared with the non‐bioluminescent species, suggesting events of duplication and loss. The signature of positive selection showed only one residue associated with the chromophore binding site in the Elateroidea, which may produce a bathochromic shift in the wavelength absorption spectra in this family. Overall, this study brings important content and fills gaps regarding opsin evolution in Elateroidea. [ABSTRACT FROM AUTHOR]

Services for AI tasks have garnered a lot of attention as an integral aspect of intelligent services in the new era. However, implementing such a system in a stable and distributed manner, while simultaneously coordinating the use of cloud computing and remote edge devices, is challenging due to the pressing need for energy and computing resources. The primary contribution of this study lies in the development of a distributed co-inference architecture that harnesses the collective intelligence of interconnected agents to optimize traffic flow in real-time. By combining Q-learning with enhanced deep learning, our approach enables traffic signals and routing decisions to adapt dynamically to changing traffic patterns and environmental conditions. The security, responsiveness, and dependability of intelligent systems deployed close to end-users are improved by deploying deep learning systems. Another critical aspect where latency and accuracy in models are traded off is deep learning model optimization. Finding the best offloading policy and model for deep learning services requires an end-to-end decision-making solution that takes into account computation-communication problems. This study presents a holistic network optimization approach for scheduling AI services based on artificial intelligence. By adjusting for differences in computational resources and network congestion, the suggested deep Q-learning technique maximizes the throughput of AI tasks in general. This research introduces a virtual queue for analyzing the system's Lyapunov stability and employs a multi-hop Directed Acyclic Graph (DAG) to explain Q-learning of Reinforcement learning-based co-inference network topology. To optimize the total task processing rate, the study develops an Optimized self-adaptive glow worm swarm optimization method (SA-GSO) based on deep Q-learning. It then proposes a prioritybased data forwarding approach for efficiency. The study concludes by simulating the distributed co-inference system's platform. We attest to the superiority of our idea by comparing it to other standards. [ABSTRACT FROM AUTHOR]

A key component of software quality assurance is software error prediction, which aims to find probable flaws in software systems during the development stage. In this extensive study, we assessed the classification efficiency of four well-known classifiers for software defect prediction: Decision Tree, Multi-Layer Perceptron, Random Forest, and Multi SVM. Additionally, we revised the firefly method and developed a unique multi-objective fitness function that took into account both weighted error and area under the curve (AUC) in order to assess the fitness of the classifiers in feature selection. Using a diverse dataset comprising varying numbers of records, ranging from 500 to 5000, we calculated key performance metrics, including precision, recall, F-measure, classification accuracy, and receiver operating characteristic (ROC) curves. The average metrics for each classifier at 5000 records were as follows: In terms of precision, recall, F-measure, and accuracy, DT attained averages of 0.7974, 0.8133, and 0.8047. Similarly, MLP exhibited an average precision, recall, F-measure, and accuracy of 0.8130, 0.8041, 0.7984, and 0.7953, Random Forest exhibited 0.8138, 0.8047, 0.8172, and 0.7950, while Multi SVM exhibited 0.8032, 0.8117, and 0.8128, respectively. [ABSTRACT FROM AUTHOR]

The use of electric vehicles has raised need for infrastructure for effective charging. Wait periods at charging stations are a problem for both owners and operators of electric vehicles. Owners of electric vehicles are irritated by lengthy wait periods, and charging facilities are underutilised. Wait times at electric car charging stations are decreased using "OptiCharge," a Firefly Algorithm-based solution. Scheduling charging stations makes sense given the Firefly Algorithm's ability to adjust to changing conditions and solve challenging problems. In the present paper, we incorporate dynamic scheduling and waiting time computation mathematically into OptiCharge. Extensive testing and comparative analysis with different optimisation techniques demonstrate that OptiCharge decreases waiting times and enhances charging station performance. The results show how OptiCharge may enhance EV charging and promote intelligent, sustainable transportation. [ABSTRACT FROM AUTHOR]

The predatory firefly Photuris elliptica is common throughout the Atlantic Forest and has been proposed as a biomonitor due to the species' narrow niche and elevational range. However, the species is only known from adults, and a more effective monitoring of its populations hinges on the lack of knowledge on their immature stages. Recent sampling in ferruginous caves and inserted in other lithologies, on sites in the Atlantic Forest and Cerrado, have led to the capture of firefly larvae later reared to adults in the lab. Firefly larvae have been reported in South American caves before; however, they have only been identified to family due to the adult-biased taxonomy of Lampyridae. Here, we provide an updated diagnosis of Photuris elliptica, describe its immature stages for the first time, and update the distribution of the species. The larvae of Photuris elliptica were observed to interact with guano of several bat species, including that of vampire bats. These observations are consistent with the less specialized feeding preferences of photurine larvae, unlike most other firefly taxa, which specialize in gastropods and earthworms. It is yet unclear whether P. elliptica are cave specialists. However, since its occurrence outside caves remains unknown, protecting cave environments must be considered in conservation strategies for this important biomonitor species. [ABSTRACT FROM AUTHOR]

Lakes, as the main sources of surface water, are of great environmental and ecological importance and largely affect the climatic conditions of the surrounding areas. Lake area fluctuations are very effective on plant and animal biodiversity in the areas covered. Hence, accurate and reliable forecasts of ​lake area might provide the awareness of water and climate resources and the survival of various species dependent on area fluctuations. Using machine learning methods, the current study numerically predicted area fluctuations of ​China's largest lake, Qinghai, over 1 to 12 months ahead of lead time. To this end, Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images were used to monitor the monthly changes in the area of ​the lake from 2000 to 2021. Predictive inputs included the MODIS-derived lake area time latency specified by the autocorrelation function. The data was divided into two periods of the train (initial 75%) and test (final 25%), and the input combinations were arranged so that the model in the test period could be used to predict 12 scenarios, including forecast horizons for the next 1 to 12 months. The adaptive neuro-fuzzy inference system (ANFIS) was utilized as a predictive model. The firefly algorithm (FA) was also used to optimize ANFIS and improve its accuracy, as a hybrid model ANFIS-FA. Based on evaluation criteria such as root mean square error (RMSE) (477–594 km2) and R2 (88–92%), the results confirmed the acceptable accuracy of the models in all forecast horizons, even long-term horizons (10 months, 11 months, and 12 months). Based on the normalized RMSE criterion (0.095–0.125), the models' performance was reported to be appropriate. Furthermore, the firefly algorithm improved the prediction accuracy of the ANFIS model by an average of 16.9%. In the inter-month survey, the models had fewer forecast errors in the dry months (February–March) than in the wet months (October–November). Using the current method can provide remarkable information about the future state of lakes, which is very important for managers and planners of water resources, environment, and natural ecosystems. According to the results, the current approach is satisfactory in predicting MODIS-derived fluctuations of Qinghai Lake area and has research value for other lakes. [ABSTRACT FROM AUTHOR]

This research introduces a unified power quality conditioner (UPQC) that integrates solar photovoltaic (PV) system and battery energy systems (SBES) to address power quality (PQ) issues. The reference signals for voltage source converters of UPQC are produced by the Levenberg–Marquardt back propagation (LMBP) trained artificial neural network control (ANNC). This method removes the necessity for conventional dq0, abc complex shifting. Moreover, the optimal choice of parameters for the adaptive neuro-fuzzy inference system (ANFIS) was achieved through the integration of the enhanced harmony search algorithm (EHSA) and the predator-prey-based firefly algorithm (PPFA) in the form of the hybrid metaheuristic algorithm (PPF-EHSA). In addition, the algorithm is employed to optimize the selection of resistance and inductance values for the filters in UPQC. The primary objective of the ANNC with predator-prey-based firefly algorithm and enhanced harmony search algorithm (PPF-EHSA) is to enhance the stability of the DC-link capacitor voltage (DLCV) with reduced settling time amid changes in load, solar irradiation (G), and temperature (T). Moreover, the algorithm seeks to achieve a reduction in total harmonic distortion (THD) and enhance power factor (PF). The method also focuses on mitigating fluctuations such as swell, harmonics, and sag and also unbalances at the grid voltage. The proposed approach is examined through four distinct cases involving various permutations of loads and sun irradiation (G). However, in order to demonstrate the performance of the suggested approach, a comparison is conducted with the ant colony and genetic algorithms, i.e., (ACA) (GA), as well as the standard methods of synchronous reference frame (SRF) and instantaneous active and reactive power theory (p-q). The results clearly demonstrate that the proposed method exhibits a reduced mean square error (MSE) of 0.02107 and a lower total harmonic distortion (THD) of 2.06% compared to alternative methods. [ABSTRACT FROM AUTHOR]

Medical image segmentation is a critical task in medical image analysis, and clustering algorithms can be utilized to achieve this goal. This research work focuses on the segmentation of neuro disorder magnetic resonance images using Otsu, K-means, and FCM coupled with the firefly optimization algorithm. Otsu is a classical thresholding algorithm that relies on a single threshold value to segment the images. K-Means is one of the simplest and most widely used clustering algorithms. It aims to partition data into K clusters, where each data point belongs to the cluster with the nearest mean. Fuzzy C-Means is an extension of K-Means, allowing data points to belong to multiple clusters with varying degrees of membership. In medical image segmentation, FCM was used to classify pixels or voxels into different tissue classes with soft boundaries, accounting for partial volume effects. Firefly Optimization helps in improving the convergence speed of the FCM algorithm. Firefly optimization is good at exploring the solution space and finding global optima. The combination of FCM and Firefly Optimization leads to more accurate clustering results. The performance evaluation was done by Renyi entropy and Shannon entropy, FCM coupled with the firefly optimization was found to exhibit superior results when compared with the Otsu and K-means clustering algorithms. [ABSTRACT FROM AUTHOR]

Adult fireflies exhibit unique flashing courtship signals, emitted by specialized light organs, which develop mostly independently from larval light organs during the pupal stage. The mechanisms of adult light organ development have not been thoroughly studied until now. Here we show that key homeobox transcription factors AlABD-B and AlUNC-4 regulate the development of adult light organs and bioluminescence in the firefly Aquatica leii. Interference with the expression of AlAbd-B and AlUnc-4 genes results in undeveloped or non-luminescent adult light organs. AlABD-B regulates AlUnc-4, and they interact with each other. AlABD-B and AlUNC-4 activate the expression of the luciferase gene AlLuc1 and some peroxins. Four peroxins are involved in the import of AlLUC1 into peroxisomes. Our study provides key insights into the development of adult light organs and flash signal control in fireflies. Adult firefly light organs exhibit flashing signals important for courtship, though how these organs form during development is largely unknown. Here the authors demonstrate that homeobox transcription factors play a patterning role in the development of the adult light organs. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) affects species-specific communication in a wide range of nocturnal species, including fireflies (Lampyridae). Fireflies rely on bioluminescent signals for communicating. In this study, we conducted two manipulative field experiments to evaluate the effect of artificial light at night on the flashing activity of male and female neotropical fireflies during courtship and predation. Our results showed a significant reduction in the flashing activity of both males and females exposed to ALAN during courtship and predation. Remarkably, the effect of ALAN on male flashing activity seems to be independent of female flashing activity. In conclusion, ALAN disrupts bioluminescent intraspecific (courtship) and interspecific (predation) communication, which in turn could influence mating success, thus negatively affecting neotropical firefly populations in the long term. Our findings contribute to understanding the challenges faced by neotropical firefly communities in the presence of ALAN. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of transcription factor binding sites (TFBSs) is a key problem in contemporary biology, which is a critical issue in gene regulation. Identifying a pattern of TFBSs in every DNA sequence, motif discovery reveals the basic regulatory relationship and compassionate the evolutionary system of every species. In this case, recognizing the high-quality (ℓ, d) motif is a great challenge. This problem is addressed in motif discovery and motif finding, using the proposed algorithms, such as Segmentation to Filtration (S2F) and Firefly with FREEZE (FFF), respectively. In this study, the whole DNA sequences are divided into two segments. Segment 1 involves motif discovery and is sliced by base and sub k-mers applying an iterative approach, followed by filtration 1 and 2 techniques, respectively. This approach obtains the top five percent of the best motifs (TOPbk_mer) based on accuracy. In segment 2, the motifs recognized in segment 1 are given as input to the FFF algorithm to identify the TFBs locations. The standard firefly algorithm with two freezing techniques, local and global, is employed to recognize the final motif. The performance of these algorithms is evaluated on the simulated datasets and real datasets such as the Escherichia coli cyclic AMP receptor protein (CRP) dataset, mouse Embryonic Stem Cell (mESC) dataset, and human species ChIP-seq (Chromatin Immuno Precipitation Sequences) dataset. All of these datasets have a running time of the experiment within 3 min, and the sequence numbers (t) hold ranges up to 39,601. It is evident from the results that the two proposed algorithms, S2F and FFF, can identify the high-quality motif, and it is faster than the state-of-the-art PMS and QPMS algorithms. [ABSTRACT FROM AUTHOR]

Buildings are amongst the world's largest energy consumers and simultaneous peaks in demand from networks of buildings can decrease electricity system stability. Current mitigation measures either entail wasteful supply-side over-specification or complex centralised demand-side control. Hence, a simple schema is developed for decentralised, self-organising building-to-building load coordination that requires very little information exchange and no top-down management—analogous to other complex systems with short range interactions, such as coordination between flocks of birds or synchronisation in fireflies. Numerical and experimental results reveal that a high degree of peak flattening can be achieved using surprisingly small load-coordination networks. The optimum reductions achieved by the simple schema can outperform existing techniques, giving substantial peak-reductions as well as being remarkably robust to changes in other system parameters such as the interaction network topology. This not only demonstrates that significant reductions in network peaks are achievable using remarkably simple control systems but also reveals interesting theoretical results and new insights which will be of great interest to the complexity and network science communities. [ABSTRACT FROM AUTHOR]

More than 4700 nominal family-group names (including names for fossils and ichnotaxa) are nomenclaturally available in the order Coleoptera. Since each family-group name is based on the concept of its type genus, we argue that the stability of names used for the classification of beetles depends on accurate nomenclatural data for each type genus. Following a review of taxonomic literature, with a focus on works that potentially contain type species designations, we provide a synthesis of nomenclatural data associated with the type genus of each nomenclaturally available family-group name in Coleoptera. For each type genus the author(s), year of publication, and page number are given as well as its current status (i.e., whether treated as valid or not) and current classification. Information about the type species of each type genus and the type species fixation (i.e., fixed originally or subsequently, and if subsequently, by whom) is also given. The original spelling of the family-group name that is based on each type genus is included, with its author(s), year, and stem. We append a list of nomenclaturally available family-group names presented in a classification scheme. Because of the importance of the Principle of Priority in zoological nomenclature, we provide information on the date of publication of the references cited in this work, when known. Several nomenclatural issues emerged during the course of this work. We therefore appeal to the community of coleopterists to submit applications to the International Commission on Zoological Nomenclature (hence- forth "Commission") in order to permanently resolve some of the problems outlined here. The following changes of authorship for type genera are implemented here (these changes do not affect the concept of each type genus): CHRYSOMELIDAE: Fulcidax Crotch, 1870 (previously credited to "Clavareau, 1913"); CICINDELIDAE: Euprosopus W.S. MacLeay, 1825 (previously credited to "Dejean, 1825"); COCCINELLIDAE: Alesia Reiche, 1848 (previously credited to "Mulsant, 1850"); CURCULIONIDAE: Arachnopus Boisduval, 1835 (previously credited to "Guérin-Méneville, 1838"); ELATERIDAE: Thylacosternus Gemminger, 1869 (previously credited to "Bonvouloir, 1871"); EUCNEMIDAE: Arrhipis Gemminger, 1869 (previously credited to "Bonvouloir, 1871"), Mesogenus Gemminger, 1869 (previously credited to "Bonvouloir, 1871"); LUCANIDAE: Sinodendron Hellwig, 1791 (previously credited to "Hellwig, 1792"); PASSALIDAE: Neleides Harold, 1868 (previously credited to "Kaup, 1869"), Neleus Harold, 1868 (previously credited to "Kaup, 1869"), Pertinax Harold, 1868 (previously credited to "Kaup, 1869"), Petrejus Harold, 1868 (previously credited to "Kaup, 1869"), Undulifer Harold, 1868 (previously credited to "Kaup, 1869"), Vatinius Harold, 1868 (previously credited to "Kaup, 1869"); PTINIDAE: Mezium Leach, 1819 (previously credited to "Curtis, 1828"); PYROCHROIDAE: Agnathus Germar, 1818 (previously credited to "Germar, 1825"); SCARABAEIDAE: Eucranium Dejean, 1833 (previously "Brullé, 1838"). The following changes of type species were implemented following the discovery of older type species fixations (these changes do not pose a threat to nomenclatural stability): BOLBOCERATIDAE: Bolbocerus bocchus Erichson, 1841 for Bolbelasmus Boucomont, 1911 (previously Bolboceras gallicum Mulsant, 1842); BUPRESTIDAE: Stigmodera guerinii Hope, 1843 for Neocuris Saunders, 1868 (previously Anthaxia fortnumi Hope, 1846), Stigmodera peroni Laporte & Gory, 1837 for Curis Laporte & Gory, 1837 (previously Buprestis caloptera Boisduval, 1835); CARABIDAE: Carabus elatus Fabricius, 1801 for Molops Bonelli, 1810 (previously Carabus terricola Herbst, 1784 sensu Fabricius, 1792); CERAMBYCIDAE: Prionus palmatus Fabricius, 1792 for Macrotoma Audinet-Serville, 1832 (previously Prionus serripes Fabricius, 1781); CHRYSOMELIDAE: Donacia equiseti Fabricius, 1798 for Haemonia Dejean, 1821 (previously Donacia zosterae Fabricius, 1801), Eumolpus ruber Latreille, 1807 for Euryope Dalman, 1824 (previously Cryptocephalus rubrifrons Fabricius, 1787), Galeruca affinis Paykull, 1799 for Psylliodes Latreille, 1829 (previously Chrysomela chrysocephala Linnaeus, 1758); COCCINELLIDAE: Dermestes rufus Herbst, 1783 for Coccidula Kugelann, 1798 (previously Chrysomela scutellata Herbst, 1783); CRYPTOPHAGIDAE: Ips caricis G.-A. Olivier, 1790 for Telmatophilus Heer, 1841 (previously Cryptophagus typhae Fallén, 1802), Silpha evanescens Marsham, 1802 for Atomaria Stephens, 1829 (previously Dermestes nigripennis Paykull, 1798); CURCULIONIDAE: Bostrichus cinereus Herbst, 1794 for Crypturgus Erichson, 1836 (previously Bostrichus pusillus Gyllenhal, 1813); DERMESTIDAE: Dermestes trifasciatus Fabricius, 1787 for Attagenus Latreille, 1802 (previously Dermestes pellio Linnaeus, 1758); ELATERIDAE: Elater sulcatus Fabricius, 1777 for Chalcolepidius Eschscholtz, 1829 (previously Chalcolepidius zonatus Eschscholtz, 1829); ENDOMYCHIDAE: Endomychus rufitarsis Chevrolat, 1835 for Epipocus Chevrolat, 1836 (previously Endomychus tibialis Guérin-Méneville, 1834); EROTYLIDAE: Ips humeralis Fabricius, 1787 for Dacne Latreille, 1797 (previously Dermestes bipustulatus Thunberg, 1781); EUCNEMIDAE: Fornax austrocaledonicus Perroud & Montrouzier, 1865 for Mesogenus Gemminger, 1869 (previously Mesogenus mellyi Bonvouloir, 1871); GLAPHYRIDAE: Melolontha serratulae Fabricius, 1792 for Glaphyrus Latreille, 1802 (previously Scarabaeus maurus Linnaeus, 1758); HISTERIDAE: Hister striatus Forster, 1771 for Onthophilus Leach, 1817 (previously Hister sulcatus Moll, 1784); LAMPYRIDAE: Ototreta fornicata E. Olivier, 1900 for Ototreta E. Olivier, 1900 (previously Ototreta weyersi E. Olivier, 1900); LUCANIDAE: Lucanus cancroides Fabricius, 1787 for Lissotes Westwood, 1855 (previously Lissotes menalcas Westwood, 1855); MELANDRYIDAE: Nothus clavipes G.-A. Olivier, 1812 for Nothus G.-A. Olivier, 1812 (previously Nothus praeustus G.-A. Olivier, 1812); MELYRIDAE: Lagria ater Fabricius, 1787 for Enicopus Stephens, 1830 (previously Dermestes hirtus Linnaeus, 1767); NITIDULIDAE: Sphaeridium luteum Fabricius, 1787 for Cychramus Kugelann, 1794 (previously Strongylus quadripunctatus Herbst, 1792); OEDEMERIDAE: Helops laevis Fabricius, 1787 for Ditylus Fischer, 1817 (previously Ditylus helopioides Fischer, 1817 [sic]); PHALACRIDAE: Sphaeridium aeneum Fabricius, 1792 for Olibrus Erichson, 1845 (previously Sphaeridium bicolor Fabricius, 1792); RHIPICERIDAE: Sandalus niger Knoch, 1801 for Sandalus Knoch, 1801 (previously Sandalus petrophya Knoch, 1801); SCARABAEIDAE: Cetonia clathrata G.-A. Olivier, 1792 for Inca Lepeletier & Audinet-Serville, 1828 (previously Cetonia ynca Weber, 1801); Gnathocera vitticollis W. Kirby, 1825 for Gnathocera W. Kirby, 1825 (previously Gnathocera immaculata W. Kirby, 1825); Melolontha villosula Illiger, 1803 for Chasmatopterus Dejean, 1821 (previously Melolontha hirtula Illiger, 1803); STAPHYLINIDAE: Staphylinus politus Linnaeus, 1758 for Philonthus Stephens, 1829 (previously Staphylinus splendens Fabricius, 1792); ZOPHERIDAE: Hispa mutica Linnaeus, 1767 for Orthocerus Latreille, 1797 (previously Tenebrio hirticornis DeGeer, 1775). The discovery of type species fixations that are older than those currently accepted pose a threat to nomenclatural stability (an application to the Commission is necessary to address each problem): CANTHARIDAE: Malthinus Latreille, 1805, Malthodes Kiesenwetter, 1852; CARABIDAE: Bradycellus Erichson, 1837, Chlaenius Bonelli, 1810, Harpalus Latreille, 1802, Lebia Latreille, 1802, Pheropsophus Solier, 1834, Trechus Clairville, 1806; CERAMBYCIDAE: Callichroma Latreille, 1816, Callidium Fabricius, 1775, Cerasphorus Audinet-Serville, 1834, Dorcadion Dalman, 1817, Leptura Linnaeus, 1758, Mesosa Latreille, 1829, Plectromerus Haldeman, 1847; CHRYSOMELIDAE: Amblycerus Thunberg, 1815, Chaetocnema Stephens, 1831, Chlamys Knoch, 1801, Monomacra Chevrolat, 1836, Phratora Chevrolat, 1836, Stylosomus Suffrian, 1847; COLONIDAE: Colon Herbst, 1797; CURCULIONIDAE: Cryphalus Erichson, 1836, Lepyrus Germar, 1817; ELATERIDAE: Adelocera Latreille, 1829, Beliophorus Eschscholtz, 1829; ENDOMYCHIDAE: Amphisternus Germar, 1843, Dapsa Latreille, 1829; GLAPHYRIDAE: Anthypna Eschscholtz, 1818; HISTERIDAE: Hololepta Paykull, 1811, Trypanaeus Eschscholtz, 1829; LEIODIDAE: Anisotoma Panzer, 1796, Camiarus Sharp, 1878, Choleva Latreille, 1797; LYCIDAE: Calopteron Laporte, 1838, Dictyoptera Latreille, 1829; MELOIDAE: Epicauta Dejean, 1834; NITIDULIDAE: Strongylus Herbst, 1792; SCARABAEIDAE: Anisoplia Schönherr, 1817, Anticheira Eschscholtz, 1818, Cyclocephala Dejean, 1821, Glycyphana Burmeister, 1842, Omaloplia Schönherr, 1817, Oniticellus Dejean, 1821, Parachilia Burmeister, 1842, Xylotrupes Hope, 1837; STAPHYLINIDAE: Batrisus Aubé, 1833, Phloeonomus Heer, 1840, Silpha Linnaeus, 1758; TENEBRIONIDAE: Bolitophagus Illiger, 1798, Mycetochara Guérin-Méneville, 1827. Type species are fixed for the following nominal genera: ANTHRIBIDAE: Decataphanes gracilis Labram & Imhoff, 1840 for Decataphanes Labram & Imhoff, 1840; CARABIDAE: Feronia erratica Dejean, 1828 for Loxandrus J.L. LeConte, 1853; CERAMBYCIDAE: Tmesisternus oblongus Boisduval, 1835 for Icthyosoma Boisduval, 1835; CHRYSOMELIDAE: Brachydactyla annulipes Pic, 1913 for Pseudocrioceris Pic, 1916, Cassida viridis Linnaeus, 1758 for Evaspistes Gistel, 1856, Ocnoscelis cyanoptera Erichson, 1847 for Ocnoscelis Erichson, 1847, Promecotheca petelii Guérin-Méneville, 1840 for Promecotheca Guérin- Méneville, 1840; CLERIDAE: Attelabus mollis Linnaeus, 1758 for Dendroplanetes Gistel, 1856; CORYLOPHIDAE: Corylophus marginicollis J.L. LeConte, 1852 for Corylophodes A. Matthews, 1885; CURCULIONIDAE: Hoplorhinus melanocephalus Chevrolat, 1878 for Hoplorhinus Chevrolat, 1878; Sonnetius binarius Casey, 1922 for Sonnetius Casey, 1922; ELATERIDAE: Pyrophorus melanoxanthus Candèze, 1865 for Alampes Champion, 1896; PHYCOSECIDAE: Phycosecis litoralis Pascoe, 1875 for Phycosecis Pascoe, 1875; PTILODACTYLIDAE: Aploglossa sallei Guérin-Méneville, 1849 for Aploglossa Guérin-Méneville, 1849, Colobodera ovata Klug, 1837 for Colobodera Klug, 1837; PTINIDAE: Dryophilus anobioides Chevrolat, 1832 for Dryobia Gistel, 1856; SCARABAEIDAE: Achloa helvola Erichson, 1840 for Achloa Erichson, 1840, Camenta obesa Burmeister, 1855 for Camenta Erichson, 1847, Pinotus talaus Erichson, 1847 for Pinotus Erichson, 1847, Psilonychus ecklonii Burmeister, 1855 for Psilonychus Burmeister, 1855. New replacement name: CERAMBYCIDAE: Basorus Bouchard & Bousquet, nom. nov. for Sobarus Harold, 1879. New status: CARABIDAE: KRYZHANOVSKIANINI Deuve, 2020, stat. nov. is given the rank of tribe instead of subfamily since our classification uses the rank of subfamily for PAUSSINAE rather than family rank; CERAMBYCIDAE: Amymoma Pascoe, 1866, stat. nov. is used as valid over Neoamymoma Marinoni, 1977, Holopterus Blanchard, 1851, stat. nov. is used as valid over Proholopterus Monné, 2012; CURCULIONIDAE: Phytophilus Schönherr, 1835, stat. nov. is used as valid over the unnecessary new replacement name Synophthalmus Lacordaire, 1863; EUCNEMIDAE: Nematodinus Lea, 1919, stat. nov. is used as valid instead of Arrhipis Gemminger, 1869, which is a junior homonym. Details regarding additional nomenclatural issues that still need to be resolved are included in the entry for each of these type genera: BOSTRICHIDAE: Lyctus Fabricius, 1792; BRENTIDAE: Trachelizus Dejean, 1834; BUPRESTIDAE: Pristiptera Dejean, 1833; CANTHARIDAE: Chauliognathus Hentz, 1830, Telephorus Schäffer, 1766; CARABIDAE: Calathus Bonelli, 1810, Cosnania Dejean, 1821, Dicrochile Guérin- Méneville, 1847, Epactius D.H. Schneider, 1791, Merismoderus Westwood, 1847, Polyhirma Chaudoir, 1850, Solenogenys Westwood, 1860, Zabrus Clairville, 1806; CE- RAMBYCIDAE: Ancita J. Thomson, 1864, Compsocerus Audinet-Serville, 1834, Dorca- dodium Gistel, 1856, Glenea Newman, 1842; Hesperophanes Dejean, 1835, Neoclytus J. Thomson, 1860, Phymasterna Laporte, 1840, Tetrops Stephens, 1829, Zygocera Erichson, 1842; CHRYSOMELIDAE: Acanthoscelides Schilsky, 1905, Corynodes Hope, 1841, Edusella Chapuis, 1874; Hemisphaerota Chevrolat, 1836; Physonota Boheman, 1854, Porphyraspis Hope, 1841; CLERIDAE: Dermestoides Schäffer, 1777; COCCINELLIDAE: Hippodamia Chevrolat, 1836, Myzia Mulsant, 1846, Platynaspis L. Redten- bacher, 1843; CURCULIONIDAE: Coeliodes Schönherr, 1837, Cryptoderma Ritsema, 1885, Deporaus Leach, 1819, Epistrophus Kirsch, 1869, Geonemus Schönherr, 1833, Hylastes Erichson, 1836; DYTISCIDAE: Deronectes Sharp, 1882, Platynectes Régimbart, 1879; EUCNEMIDAE: Dirhagus Latreille, 1834; HYBOSORIDAE: Ceratocanthus A. White, 1842; HYDROPHILIDAE: Cyclonotum Erichson, 1837; LAMPYRIDAE: Luciola Laporte, 1833; LEIODIDAE: Ptomaphagus Hellwig, 1795; LUCANIDAE: Leptinopterus Hope, 1838; LYCIDAE: Cladophorus Guérin-Méneville, 1830, Mimolibnetis Kazantsev, 2000; MELOIDAE: Mylabris Fabricius, 1775; NITIDULIDAE: Meligethes Stephens, 1829; PTILODACTYLIDAE: Daemon Laporte, 1838; SCARABAEIDAE: Allidiostoma Arrow, 1940, Heterochelus Burmeister, 1844, Liatongus Reitter, 1892, Lomaptera Gory & Percheron, 1833, Megaceras Hope, 1837, Stenotarsia Burmeister, 1842; STAPHYLINIDAE: Actocharis Fauvel, 1871, Aleochara Gravenhorst, 1802; STENOTRACHELIDAE: Stenotrachelus Berthold, 1827; TENEBRIONIDAE: Cryptochile Latreille, 1828, Heliopates Dejean, 1834, Helops Fabricius, 1775. First Reviser actions deciding the correct original spelling: CARABIDAE: Aristochroodes Marcilhac, 1993 (not Aritochroodes); CERAMBYCIDAE: Dorcadodium Gistel, 1856 (not Dorcadodion), EVODININI Zamoroka, 2022 (not EVODINIINI); CHRYSOMELIDAE: Caryopemon Jekel, 1855 (not Carpopemon), Decarthrocera Laboissière, 1937 (not Decarthrocerina); CICINDELIDAE: Odontocheila Laporte, 1834 (not Odontacheila); CLERIDAE: CORMODINA Bartlett, 2021 (not CORMODIINA), Orthopleura Spinola, 1845 (not Orthoplevra, not Orthopleuva); CURCULIONIDAE: Arachnobas Boisduval, 1835 (not Arachnopus), Palaeocryptorhynchus Poinar, 2009 (not Palaeocryptorhynus); DYTISCIDAE: Ambarticus Yang et al., 2019 and AMBARTICINI Yang et al., 2019 (not Ambraticus, not AMBRATICINI); LAMPYRIDAE: Megalophthalmus G.R. Gray, 1831 (not Megolophthalmus, not Megalopthalmus); SCARABAEIDAE: Mentophilus Laporte, 1840 (not Mintophilus, not Minthophilus), Pseudadoretus dilutellus Semenov, 1889 (not P. ditutellus). While the correct identification of the type species is assumed, in some cases evidence suggests that species were misidentified when they were fixed as the type of a particular nominal genus. Following the requirements of Article 70.3.2 of the International Code of Zoological Nomenclature we hereby fix the following type species (which in each case is the taxonomic species actually involved in the misidentification): ATTELABIDAE: Rhynchites cavifrons Gyllenhal, 1833 for Lasiorhynchites Jekel, 1860; BOSTRICHIDAE: Ligniperda terebrans Pallas, 1772 for Apate Fabricius, 1775; BRENTIDAE: Ceocephalus appendiculatus Boheman, 1833 for Uroptera Berthold, 1827; BUPRESTIDAE: Buprestis undecimmaculata Herbst, 1784 for Ptosima Dejean, 1833; CARABIDAE: Amara lunicollis Schiødte, 1837 for Amara Bonelli, 1810, Buprestis connexus Geoffroy, 1785 for Polistichus Bonelli, 1810, Carabus atrorufus Strøm, 1768 for Patrobus Dejean, 1821, Carabus gigas Creutzer, 1799 for Procerus Dejean, 1821, Carabus teutonus Schrank, 1781 for Stenolophus Dejean, 1821, Carenum bonellii Westwood, 1842 for Carenum Bonelli, 1813, Scarites picipes G.-A. Olivier, 1795 for Acinopus Dejean, 1821, Trigonotoma indica Brullé, 1834 for Trigonotoma Dejean, 1828; CERAMBYCIDAE: Cerambyx lusitanus Linnaeus, 1767 for Exocentrus Dejean, 1835, Clytus supernotatus Say, 1824 for Psenocerus J.L. LeConte, 1852; CICINDELIDAE: Ctenostoma jekelii Chevrolat, 1858 for Ctenostoma Klug, 1821; CURCULIONIDAE: Cnemogonus lecontei Dietz, 1896 for Cnemogonus J.L. LeConte, 1876; Phloeophagus turbatus Schönherr, 1845 for Phloeophagus Schönherr, 1838; GEOTRUPIDAE: Lucanus apterus Laxmann, 1770 for Lethrus Scopoli, 1777; HISTERIDAE: Hister rugiceps Duftschmid, 1805 for Hypocaccus C.G. Thomson, 1867; HYBOSORIDAE: Hybosorus illigeri Reiche, 1853 for Hybosorus W.S. MacLeay, 1819; HYDROPHILIDAE: Hydrophilus melanocephalus G.-A. Olivier, 1793 for Enochrus C.G. Thomson, 1859; MYCETAEIDAE: Dermestes subterraneus Fabricius, 1801 for Mycetaea Stephens, 1829; SCARABAEIDAE: Aulacium carinatum Reiche, 1841 for Mentophilus Laporte, 1840, Phanaeus vindex W.S. MacLeay, 1819 for Phanaeus W.S. MacLeay, 1819, Ptinus germanus Linnaeus, 1767 for Rhyssemus Mulsant, 1842, Scarabaeus latipes Guérin-Méneville, 1838 for Cheiroplatys Hope, 1837; STAPHYLINIDAE: Scydmaenus tarsatus P.W.J. Müller & Kunze, 1822 for Scydmaenus Latreille, 1802. New synonyms: CERAMBYCIDAE: CARILIINI Zamoroka, 2022, syn. nov. of ACMAEOPINI Della Beffa, 1915, DOLOCERINI Özdikmen, 2016, syn. nov. of BRACHYPTEROMINI Sama, 2008, PELOSSINI Tavakilian, 2013, syn. nov. of LYGRINI Sama, 2008, PROHOLOPTERINI Monné, 2012, syn. nov. of HOLOPTERINI Lacordaire, 1868. [ABSTRACT FROM AUTHOR]

Nibong Tebal, Penang is a firefly ecotourism area that has attracted attention from both foreign and local visitors. Ecotourism areas require support and participation from local communities to catalyse their social and economic developments. This study examines the impact of ecotourism activities on the socioeconomic development of the local community in Nibong Tebal. In this regard, community involvement in ecotourism activities and the impact of local community involvement in ecotourism activities are identified and studied. A total of 150 questionnaires was used as a quantitative research method. In addition, an in-depth interview method was also conducted as a qualitative research method. The results of this study show that community involvement in ecotourism activities is driven by various factors that can improve both social and economic developments. Ecotourism activities bring many benefits to the local community such as opening up job opportunities, business avenues and benefits for them to earn some side income. Understanding the benefits that can be obtained is a motivating factor for the community to get involved in this activity. Through this study, it is also possible to improve the existing ecotourism management system by looking at aspects of the level of management knowledge, the needs of other agencies in helping to boost ecotourism activities and improving public facilities that are still below par. Therefore, it is suggested that all stakeholders unite to increase local community cooperation in addition to diversifying the existing ecotourism activities to attract more visitors to this area. [ABSTRACT FROM AUTHOR]

Photinus signaticollis Blanchard, 1846 (Coleoptera: Lampyridae) is a firefly native to South America and recently established in Europe. Since 2016, this firefly has colonized the northeastern part of the Iberian Peninsula and crossed the Pyrenees to reach southern France in 2019. The larvae of this firefly feed on earthworms, so a high density of this species could negatively impact this key group in soil processes and agriculture. The precise extent of colonization, the environmental niche and the potential range expansion in non-native areas are currently unknown. Using species distribution models, we have found the high suitability areas across Europe where P. signaticollis may become established if introduced. Interestingly, using only South American records and associated conditions modelling it can be strongly predicted where the species is currently found in Europe. Despite a few propagules of P. signaticollis detected in very unsuitable areas of Spain were no longer detected after their initial observation, the climatic niche overlap between South America and Europe populations appeared to be very low. In our case, this pattern is more likely to reflect a high unfilled niche rather than a niche expansion or niche shift, because many occupied areas in South America possess a climate not occurring in Europe. Among the considered variables, we furthermore found that only the temperature seasonality appeared to be the same in both native and European areas and relevant in the models, suggesting that it may represent the main limiting factor for establishing this firefly. Implications for insect conservation: The introduction and population expansion of a non-native firefly is a novel event in European communities and the effects are unpredictable: through their interspecific competition with native fireflies and possible interactions with other insects, they could disrupt fragile surface balances, and their feeding on earthworms could potentially affect soil communities and processes. [ABSTRACT FROM AUTHOR]

Simple Summary: Predatory female fireflies of several species in the genus Photuris attract males from other firefly species by responding to their flash signals, and then, the females try to capture and feed on the attracted males. Predatory female Photuris, called "femmes fatales", are considered a serious threat to males of other firefly species; however, there are very few quantitative data on the strength of this menace. We measured the attraction of Photinus palaciosi males to predatory females of Photuris lugubris in the field, as well as the number of prey captured. We observed that females, in general, attract several males of the prey species but capture relatively few; only nine out of 92 (9.8%) observations of predatory females resulted in successful capture. Our observations show that the low hunting success of Photuris females could be explained in part by male behaviors. First, the males attracted behave in a way that we call "cautious" or "hesitant", which could prevent attacks, and second, these males also behave in ways that probably reduce the success of attacks at close distance, such as approaching in flight and "dropping" in the face of an imminent attack. Female Photuris also behave in ways that probably improve their success in attracting and capturing prey, such as perching in or near display areas of their prey species, and partially concealing their own lantern on the substrate to avoid revealing their much larger size and/or to better mimic the responses of Photinus females. Our observations are thus consistent with the idea that predators and prey are engaged in a coevolutionary race of adaptation and counter-adaptation. Photuris female fireflies attract males of different firefly species by responding to their flashing signals; then, they try to capture and feed on them. This aggressive mimicry is considered a major selective pressure on the communication systems of the fireflies of the American continent. The intensity of this selective pressure is a function of its efficiency in prey capture. In this study, the rates of attraction and capture of males of the synchronous firefly Photinus palaciosi by the predatory females of Photuris lugubris are reported. Although the females attract numerous males, their hunting success is low. This result is consistent with the few previous measurements published. In agreement with the predicted coevolutionary race between predator and prey, behaviors consistent with predation avoidance in P. palaciosi and increasing prey encounters and prey deception by P. lugubris were observed. [ABSTRACT FROM AUTHOR]