Efficient Defense Research Articles

Pseudomonas aeruginosa kills Staphylococcus aureus in a polyphosphate-dependent manner.

Due to their frequent coexistence in many polymicrobial infections, including in patients with cystic fibrosis or burn/chronic wounds, many studies have investigated the mechanistic details of the interaction between the opportunistic pathogens Pseudomonas aeruginosa and Staphylococcus aureus. P. aeruginosa rapidly outcompetes S. aureus under in vitro cocultivation conditions, which is mediated by several of P. aeruginosa's virulence factors. Here, we report that polyphosphate (polyP), an efficient stress defense system and virulence factor in P. aeruginosa, plays a role in the pathogen's ability to inhibit and kill S. aureus in a contact-independent manner. We show that P. aeruginosa cells characterized by low polyP levels are less detrimental to S. aureus growth and survival while the Gram-positive pathogen is significantly more compromised by the presence of P. aeruginosa cells that produce high levels of polyP. The polyP-dependent phenotype of P. aeruginosa-mediated killing of S. aureus could at least in part be direct, as polyP was detected in the spent media and causes significant damage to the S. aureus cell envelope. However, more likely is that polyP's effects are indirect through modulating the production of one of P. aeruginosa's virulence factors, pyocyanin. We show that pyocyanin production in P. aeruginosa occurs polyP-dependently and harms S. aureus through membrane damage and potentially the generation of reactive oxygen species, resulting in the increased expression of antioxidant enzymes. In summary, our study adds a new component to the list of biomolecules that the Gram-negative pathogen P. aeruginosa generates to compete with S. aureus for resources.IMPORTANCEHow do interactions between microorganisms shape the course of polymicrobial infections? Previous studies have provided evidence that the two opportunistic pathogens Pseudomonas aeruginosa and Staphylococcus aureus generate molecules that modulate their interaction with potentially significant impact on disease outcomes. Our study identified the biopolymer polyphosphate (polyP) as a new effector molecule that impacts P. aeruginosa's interaction with S. aureus. We show that P. aeruginosa kills S. aureus in a polyP-dependent manner, which occurs primarily through the polyP-dependent production of the P. aeruginosa virulence factor pyocyanin. Our findings add a new role for polyP to an already extensive list of functions. A more in-depth understanding of how polyP influences interspecies interactions is critical, as targeting polyP synthesis in bacteria such as P. aeruginosa may have a significant impact on other microorganisms and potentially result in dynamic changes in the microbial composition.

SecureVision: Advanced Cybersecurity Deepfake Detection with Big Data Analytics

SecureVision is an advanced and trustworthy deepfake detection system created to tackle the growing threat of ‘deepfake’ movies that tamper with media, undermine public trust, and jeopardize cybersecurity. We present a novel approach that combines big data analytics with state-of-the-art deep learning algorithms to detect altered information in both audio and visual domains. One of SecureVision’s primary innovations is the use of multi-modal analysis, which improves detection capabilities by concurrently analyzing many media forms and strengthening resistance against advanced deepfake techniques. The system’s efficacy is further enhanced by its capacity to manage large datasets and integrate self-supervised learning, which guarantees its flexibility in the ever-changing field of digital deception. In the end, this study helps to protect digital integrity by providing a proactive, scalable, and efficient defense against the ubiquitous threat of deepfakes, thereby establishing a new benchmark for privacy and security measures in the digital era.

Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance.

Sunflower (Helianthus annuus) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. Verticillium dahliae is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to V. dahliae across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with V. dahliae resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by V. dahliae. This study also reveals the polygenic architecture of V. dahliae resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector.

High internal phase emulsions stabilized by fluorescent phycocyanin for improved stability and bioaccessibility of β-carotene.

High internal phase emulsions (HIPE) are distinguished from ordinary emulsions by higher oil-phase percentage and better storage stability. Recently, HIPE stabilized with protein-based particles has received more attention. However, organic precipitation, chemical cross-linking and thermal denaturation are often needed to stabilize emulsions with natural proteins, and there is an urgent need to reduce the pollution of organic reagents. HIPE loaded with β-carotene stabilized by phycocyanin was prepared under mild conditions. It demonstrated strong stability in terms of temperature and storage, as evidenced by its 94.17% retention rate and 81.06% bioavailability. This stability was ascribed to the efficient defense against heat and UV rays, which was probably associated with the oil-droplet environment and interfacial protection of phycocyanin. It is speculated that the possible main interaction site between phycocyaninand sorbitol exists near amino acids 110 to 120 of the B chain. The hydrogen bond and hydrophobic interaction between them make the phycocyanin fully adsorbed on the oil-water interface when sorbitol is stable, forming a strong oil-water structure, which increases the stability of the emulsion. The outstanding fluorescence characteristics provide a feasible alternative for fluorescent emulsions to distribute and trace active compounds in vitro. HIPE loaded with β-carotene might have potential as a 3D printing material for edible functional foods. © 2024 Society of Chemical Industry.

Advanced technology based on Poly(deep eutectic solvent) core–shell nanomaterials enriched with Fructus Choerospondias phenols for efficient defense against UVB-induced ferroptosis

Plant phenolic compounds serve as significant natural antioxidants. However, traditional preparation methods face sustainability challenges. In this study, we synthesized a novel deep eutectic solvent (DES) modified core–shell nanomaterial composed of betaine, ethylene glycol and dopamine hydrochloride based on the spatial arrangement formed by the abundant weak interaction forces in the poly(deep eutectic solvent) (PDES). Utilizing the PDES magnetic nanomaterial and combined with ultrasound-assisted matrix solid phase dispersion (UA-MSPD), it was able to efficiently enrich Fructus Choerospondias phenols (FCP) up to 61.468 ± 0.405 mg/g. Density functional theory (DFT) was used to analyze the adsorption mechanism between the material and the target compounds, which involved weak interactions of electrostatics, hydrogen bonds, and π-π stacking, while maintaining the activity of phenols without destroying the molecular structure. Remarkably, the adsorption efficiency of the material remained above 80 % after six repetitions, indicating excellent reusability. FCPs were identified and analyzed using ultra-performance liquid chromatography-tandem triple quadrupole mass spectrometry (UPLC-Q-TOF-MS). The FCP prepared by Fe3O4@SiO2@PDES exhibited superior in vitro antioxidant performance, achieving enrichment and purification in one step. Cell experiment results showed that FCP could scavenge ROS, regulate cytokines, and reduce ferroptosis caused by ultraviolet radiation, making FCP have therapeutic value in practical applications. The technology opens up a new way for the green and sustainable production and enrichment of plant phenolic compounds for anti-aging treatment.

Categorical-Parallel Adversarial Defense for Perception Models on Single-Board Embedded Unmanned Vehicles

Significant advancements in robustness against input perturbations have been realized for deep neural networks (DNNs) through the application of adversarial training techniques. However, implementing these methods for perception tasks in unmanned vehicles, such as object detection and semantic segmentation, particularly on real-time single-board computing devices, encounters two primary challenges: the time-intensive nature of training large-scale models and performance degradation due to weight quantization in real-time deployments. To address these challenges, we propose Ca-PAT, an efficient and effective adversarial training framework designed to mitigate perturbations. Ca-PAT represents a novel approach by integrating quantization effects into adversarial defense strategies specifically for unmanned vehicle perception models on single-board computing platforms. Notably, Ca-PAT introduces an innovative categorical-parallel adversarial training mechanism for efficient defense in large-scale models, coupled with an alternate-direction optimization framework to minimize the adverse impacts of weight quantization. We conducted extensive experiments on various perception tasks using the Imagenet-te dataset and data collected from physical unmanned vehicle platforms. The results demonstrate that the Ca-PAT defense framework significantly outperforms state-of-the-art baselines, achieving substantial improvements in robustness across a range of perturbation scenarios.

Design of a cybersecurity defense system based on big data and artificial intelligence

With the development of big data and artificial intelligence technologies, hacker attack techniques and capabilities have continuously improved, and the methods of network attacks have diversified. Without cybersecurity, there is no national security. Therefore, cybersecurity has become a focal point of attention. To comprehensively enhance the network security defense capabilities of computer operating systems, aligning with the rapid development trends of big data and artificial intelligence technologies, this study focuses on constructing an efficient, stable, and practical cybersecurity defense system. This system deeply integrates advanced technologies of big data analysis and artificial intelligence, thoroughly analyzing the current status of network information security in computer operating systems and closely aligning with the practical needs of design and production. The aim is to provide highly valuable reference solutions for the field of cybersecurity defense.

Preliminary phytochemical and biological activity screening of Sargassum lapazeanum

Algae are exposed to substantial stress. In response, these organisms have developed efficient defense systems, such as protective secondary metabolite synthesis, making algae a primary source of bioactive compounds with a wide spectrum of biological activities. Thus, algae show potential for use in treatments of thrombotic, infectious, and chronic degenerative diseases. Therefore, the objective of this study was to evaluate the phytochemical compounds and pharmacological activity of an extract obtained from Sargassum lapazeanum. Algae were collected in the intertidal zone of Tarabillas beach (Bahía de La Paz, BCS). The biological activities of an ethanolic extract and its fractions were evaluated using chromatographic techniques. In addition, a bioautographic assay of hemolytic activity was conducted, and phytochemical profiles and acute toxicity in Artemia franciscana were evaluated. The relationships among the main extract components were also determined. The ethanolic extract exhibited significant antioxidant and hemolytic activity, which was mainly attributed to its content of anthrones, anthraquinones, and unsaturated triterpenes. Its toxicological activity reached an LC50 value of 225.1 μg mL-1, which was mainly attributed to alkaloids, flavonoids, anthrones, and saponins. The results suggest that Sargassum lapazeanum, which is endemic to the Gulf of California, has great pharmacological potential with biomedical applications.

Metabolomics analysis of bahia grass (Paspalum notatum) inoculated with arbuscular mycorrhizal fungi exposed to soil Cd stress

Heavy metals can adversely affect the growth and metabolic processes of plant. Arbuscular mycorrhizal (AM) fungi, which colonize the roots of most plants, may change the uptake and resistance to heavy metals by altering plant metabolism. But few published papers focused on how AM fungi enhanced plant tolerance to heavy metals at the metabolomics level. Therefore, our study incorporated LC-MS technology to explore the molecular mechanism by which AM fungi improved cadmium (Cd) tolerance of Bahia grass (Paspalum notatum) at the metabolomic scale. The results showed that AM fungi increased growth of Bahia grass, and enhanced its uptake and tolerance of Cd. Infection with AM fungi significantly raised the levels of both primary metabolites (amino acid, carbohydrate, organic acid, etc.) and secondary metabolites (such as terpenoids, phenolic compounds, and alkaloids), which in turn improved the photosynthesis efficiency, osmoregulation, and antioxidation defense of the plant, thereby enhancing the Cd tolerance of Bahia grass. Furthermore, under high concentration of Cd, both TCA cycle and lipid metabolism were generally suppressed, and AM fungi inoculation alleviated the effects and normalized the TCA cycle and lipid metabolism. In all, the metabolic alterations identified here provided insights into the mechanisms by which AM fungi enhanced plant tolerance to heavy metals.

The Multifaceted Role of Tissue-Resident Memory T Cells

Regionalized immune surveillance relies on the concerted efforts of diverse memory T cell populations. Of these, tissue-resident memory T (TRM) cells are strategically positioned in barrier tissues, where they enable efficient frontline defense against infections and cancer. However, the long-term persistence of these cells has been implicated in a variety of immune-mediated pathologies. Consequently, modulating TRM cell populations represents an attractive strategy for novel vaccination and therapeutic interventions against tissue-based diseases. Here, we provide an updated overview of TRM cell heterogeneity and function across tissues and disease states. We discuss mechanisms of TRM cell–mediated immune protection and their potential contributions to autoimmune disorders. Finally, we examine how TRM cell responses might be durably boosted or dampened for therapeutic gain.

Algal consortia as the flexible bio-system for wastewater treatment: Effect of different light intensities on photosynthetic performance, anti-oxidative system and biodiesel production of consortia

Competence of microalgae consortia-1 (Chlorococcum humicola and Tetradesmus sp.) and consortia-2 (Chlorococcum humicola, Scenedesmus vacuolatus and Tetradesmus sp.) was analyzed by examining their adaptability potential in wastewater under different light intensities (20 W/m2 and 40 W/m2). The results depicted highest decline in nutrients and metal concentration (40–90%) at light intensity of 40 W/m2 by consortia-1 and consortia-2 treated with wastewater (50%, 100%). The result of metal remediation was further confirmed by fourier transform infrared spectroscopy (FTIR) which reflected occurrence of different functional groups in selected consortia. Moreover, light intensity of 40 W/m2 induced neutral-lipid accumulation (1750 cm−1) in consortia-1 as depicted in FTIR spectra. The maximum active photosystem-II reaction center (79.75%), quantum yield (26.17%) and performance index (195.8%) revealed that light intensity (40 W/m2) and wastewater augmented functioning of photosystem-II in consortia-1 than consortia-2. Further, consortia-2 appeared more sensitive to oxidative stress as the concentration of oxidative stress markers (5.73–6.39 folds) was amplified after treatment with wastewater at light intensity of 40 W/m2. The prodigious tolerance potential towards different light intensities and wastewater concentration of consortia-1 may be attributed to increased activity of ascorbic acid (1.16 folds), proline (1.32 folds), cysteine (2.80 folds), superoxide dismutase (3.44 folds), catalase (2.52 folds) and glutathione reductase (1.90 folds). However, abundance of saturated fatty acid (41.34%) together with high cetane number (59.07) indicated that consortia 2 can produce excellent quality biofuel at 20 W/m2 while consortia-2 at 40 W/m2. Overall, consortia 1 appeared competent in terms of photosynthetic performance, remediation efficiency and antioxidant defense mechanism under 20 W/m2 and 40 W/m2 while consortia-2 showed quality biodiesel production at 20 W/m2. Thus, algal consortia based on photosynthetic performance and defense responses along with excellent biodiesel quality under different light intensity and wastewater concentration can serve as the promising biosystem for biomass and bioenergy production.

Stress-related transcriptomic changes associated with GFP transgene expression and active transgene silencing in plants

Plants respond to biotic and abiotic stress by activating and interacting with multiple defense pathways, allowing for an efficient global defense response. RNA silencing is a conserved mechanism of regulation of gene expression directed by small RNAs important in acquired plant immunity and especially virus and transgene repression. Several RNA silencing pathways in plants are crucial to control developmental processes and provide protection against abiotic and biotic stresses as well as invasive nucleic acids such as viruses and transposable elements. Various notable studies have shed light on the genes, small RNAs, and mechanisms involved in plant RNA silencing. However, published research on the potential interactions between RNA silencing and other plant stress responses is limited. In the present study, we tested the hypothesis that spreading and maintenance of systemic post-transcriptional gene silencing (PTGS) of a GFP transgene are associated with transcriptional changes that pertain to non-RNA silencing-based stress responses. To this end, we analyzed the structure and function of the photosynthetic apparatus and conducted whole transcriptome analysis in a transgenic line of Nicotiana benthamiana that spontaneously initiates transgene silencing, at different stages of systemic GFP-PTGS. In vivo analysis of chlorophyll a fluorescence yield and expression levels of key photosynthetic genes indicates that photosynthetic activity remains unaffected by systemic GFP-PTGS. However, transcriptomic analysis reveals that spreading and maintenance of GFP-PTGS are associated with transcriptional reprogramming of genes that are involved in abiotic stress responses and pattern- or effector-triggered immunity-based stress responses. These findings suggest that systemic PTGS may affect non-RNA-silencing-based defense pathways in N. benthamiana, providing new insights into the complex interplay between different plant stress responses.

A generic approach for network defense strategies generation based on evolutionary game theory

The generation of optimal defense strategies in dynamic adversarial environments is crucial for cybersecurity. Recently, defense approaches based on evolutionary game theory have gained significant achievements. However, they would fail when facing complex networks and sophisticated attack strategies, due to the fatal drawbacks of defense strategy generation considering atomic attacks only. To relieve this issue, a generic approach for generating defense strategies using evolutionary game theory is proposed in this paper. Initially, a novel payoff quantification method for network attack-defense games based on attack graphs is designed. Innovatively, two factors concerning the decision-maker's degree of irrationality (DI) and the level of environmental security (LES) are introduced into the replicator dynamics equation to model the impacts on equilibrium solutions. Noting that Active Directory (AD) domain service is one of the most used and representative information security management system in Windows domains, from which attack graphs and paths can be plainly extracted and analyzed. Therefore, it is necessary and imperative to anchor AD to unfold the theoretical analyses and experiments validation based on a real environment. Case studies on a real-world AD network demonstrate that the proposed approach is effective and can generate stable and efficient defense strategies.

The Role of Plant Ubiquitin-like Modifiers in the Formation of Salt Stress Tolerance.

The climate-driven challenges facing Earth necessitate a comprehensive understanding of the mechanisms facilitating plant resilience to environmental stressors. This review delves into the crucial role of ubiquitin-like modifiers, particularly focusing on ATG8-mediated autophagy, in bolstering plant tolerance to salt stress. Synthesising recent research, we unveil the multifaceted contributions of ATG8 to plant adaptation mechanisms amidst salt stress conditions, including stomatal regulation, photosynthetic efficiency, osmotic adjustment, and antioxidant defence. Furthermore, we elucidate the interconnectedness of autophagy with key phytohormone signalling pathways, advocating for further exploration into their molecular mechanisms. Our findings underscore the significance of understanding molecular mechanisms underlying ubiquitin-based protein degradation systems and autophagy in salt stress tolerance, offering valuable insights for designing innovative strategies to improve crop productivity and ensure global food security amidst increasing soil salinisation. By harnessing the potential of autophagy and other molecular mechanisms, we can foster sustainable agricultural practices and develop stress-tolerant crops resilient to salt stress.

Plant, pest and predator interplay: tomato trichomes effects on Tetranychus urticae (Koch) and the predatory mite Typhlodromus (Anthoseius) recki Wainstein.

Trichomes are well-known efficient plant defense mechanisms to limit arthropod herbivory, especially in Solanaceae. The present study aims to evaluate the impact of trichome types on the development, survival and dispersal of Tetranychus urticae, and the phytoseiid predatory mite Typhlodromus (Anthoseius) recki. Six Solanum lycopersicum cultivars and two wild Solanum species, S. cheesmaniae and S. peruvianum, presenting contrasting densities and types of trichomes, were considered. Cultivars and species were characterized by counting each trichome type on leaves, petioles and stems. Mites stuck on petiole and stem and alive mites on the leaflet used for mite release and in the whole plant were counted three weeks after T. urticae plant infestation. Tetranychus urticae settlement and dispersal were differently affected by trichomes. Trichome types V and VI did not affect settlement and dispersal, whereas trichome types I and IV on the petiole had the highest impacton mites. Trichomes on leaves slightly affected mite establishment, there appears to be a repellent effect of trichome types I and IV. The low densities of both T. urticae and its predator detected for the cv. Lancaster could not be clearly associated to the trichome types here considered. The predator did not seem to be affected by plant characteristics, but rather by T. urticae numbers on the plant. The trichome traits unfavorable to T. urticae, did not affect the predator which showed high efficiency to control this pest on all the plant genotypes considered, but at a favorable predator:prey ratio (1:1). Altogether, these results are encouraging for the use of T. (A.) recki as a biological control agent of T. urticae regardless of the trichome structure of the tomato cultivars, but other conditions should be tested to conclude on practical implementations.

A novel framework of DDoS attack detection in network using hybrid heuristic deep learning approaches with attention mechanism

The “Distributed Denial of Service (DDoS)” threats have become a tool for the hackers, cyber swindlers, and cyber terrorists. Despite the high amount of conventional mitigation mechanisms that are present nowadays, the DDoS threats continue to enhance in severity, volume, and frequency. The DDoS attack has highly affected the availability of the networks for the previous years and still, there is no efficient defense technique against it. Moreover, the new and complex DDoS attacks are increasing on a daily basis but the traditional DDoS attack detection techniques cannot react to these threats. On the other hand, the hackers are employing very innovative strategies to initiate the threats. But, the traditional methods can become effective and reliable when combined with the deep learning-aided approaches. To solve these certain issues, a framework detection mechanism for DDoS attacks utilizes an attention-aided deep learning methodology. The primary thing is the acquisition of data from standard data online sources. Further, from the garnered data, the significant features are drawn out from the “Deep Weighted Restricted Boltzmann Machine (RBM)” using a “Deep Belief Network (DBN)”, in which the parameters are tuned by employing the recommended Enhanced Gannet Optimization Algorithm (EGOA). This feature extraction operation increases the network performance rate and also diminishes the dimensionality issues. Lastly, the acquired features are transferred to the model of “Attention and Cascaded Recurrent Neural Network (RNN) with Residual Long Short Term Memory (LSTM) (ACRNN-RLSTM)” blocks for the DDoS threat detection purpose. This designed network precisely identifies the complex and new attacks, thus it increases the trustworthiness of the network. In the end, the performance of the approach is contrasted with other traditional algorithms. Hence, the simulation outcomes are obtained that prove the system’s efficiency. Also, the outcomes displayed that the designed system overcame the conventional threat detection techniques.

Efficient dual defense: PDA-Cu coating for simultaneous corrosion resistance and antibacterial protection of Mg alloys

The corrosion problem of Mg alloys remains a significant barrier to their technical applications. Particularly challenging is meeting specific functional requirements while enhancing corrosion resistance. Here, a novel metal organic composite coating (PDA-Cu) has been developed, exhibiting excellent corrosion resistance, strong bonding strength, and potent antibacterial properties. In 3.5 wt% NaCl solution, the corrosion rate of PDA-Cu alloy was significantly lower than that of bare Mg alloy, about 1/360; it had a strong inhibition rate (100%) and high binding strength (23.75 N). Importantly, the composite coating maintains consistency across various substrates and forms, proving its adaptability and expanding its potential applications.

The 2023 Merger Guidelines and The Role of Economics

Relying heavily on legal analysis, the 2023 Merger Guidelines argue for a fundamental shift in antitrust enforcement that places more emphasis on protecting competitors and less on protecting the beneficiaries of competition. It is up to courts, not economists, to ascertain whether this interpretation of antitrust law is correct. But economists can and should analyze the likely economic effects. Evidence that antitrust enforcement has permitted some markets to be overly concentrated justifies the tightening of horizontal merger enforcement that is signaled by these guidelines. Evaluating the elimination of double marginalization from vertical mergers as a part of an efficiency defense rather than as a primary economic effect reflects a fundamental misunderstanding of the economics of vertical mergers. At a minimum, these guidelines will further damage the reputation of the DOJ and FTC among competition policy enforcers in other countries. A potentially more serious cost will be if foreign competition authorities use these guidelines to justify enforcing their own laws to protect inefficient domestic firms against foreign competition.

Improving Robustness of Intent Detection Under Adversarial Attacks: A Geometric Constraint Perspective.

Deep neural networks (DNNs)-based natural language processing (NLP) systems are vulnerable to being fooled by adversarial examples presented in recent studies. Intent detection tasks in dialog systems are no exception, however, relatively few works have been attempted on the defense side. The combination of linear classifier and softmax is widely used in most defense methods for other NLP tasks. Unfortunately, it does not encourage the model to learn well-separated feature representations. Thus, it is easy to induce adversarial examples. In this article, we propose a simple, yet efficient defense method from the geometric constraint perspective. Specifically, we first propose an M-similarity metric to shrink variances of intraclass features. Intuitively, better geometric conditions of feature space can bring lower misclassification probability (MP). Therefore, we derive the optimal geometric constraints of anchors within each category from the overall MP (OMP) with theoretical guarantees. Due to the nonconvex characteristic of the optimal geometric condition, it is hard to satisfy the traditional optimization process. To this end, we regard such geometric constraints as manifold optimization processes in the Stiefel manifold, thus naturally avoiding the above challenges. Experimental results demonstrate that our method can significantly improve robustness compared with baselines, while retaining the excellent performance on normal examples.

Larval gregariousness in Papilionidae is more prevalent outside the tropics

Abstract Larval gregariousness, reported for 20 of the 127 families of Lepidoptera, may enhance thermoregulation, feeding efficiency, and antipredator defence. In the swallowtail family (Papilionidae), which is distributed worldwide yet mainly in the tropics, larval gregariousness has independently evolved at least six times. Here we evaluated in Papilionidae whether gregarious species are mostly distributed in temperate regions, where enhanced thermoregulation should be more beneficial because of the colder climate and greater climatic variations, compared to the tropics. We found data for 198 of the c. 560 species of Papilionidae. Results showed that larval gregariousness was significantly more prevalent in temperate regions. This pattern was statistically significant even when the analysis accounted for phylogenetic relatedness, which also influenced the occurrence of gregariousness. Thus, the shared evolutionary history of Papilionidae species explains in part the global distribution pattern of larval gregariousness. Nonetheless, this macroecological pattern of distribution of larval gregariousness in swallowtail species could have resulted from the ecological benefits concerning thermoregulation that are associated with group living.