In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,...In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,we examined the structural characteristics and variability of female bubbling calls among four Cuculus species(Common Cuckoo C.canorus,Oriental Cuckoo C.optatus,Indian Cuckoo C.micropterus,and Lesser Cuckoo C.poliocephalus)breeding in South Korea.Comprehensive acoustic analyses of seven call parameters,using recordings from 2021 to 2023,were conducted to quantify the characteristics of their calls and compare withinand between-individual variability across species.Significant differences were found across all call parameters,with the Common Cuckoo producing the highest number of notes and the Oriental Cuckoo the lowest-frequency calls.Despite these differences,the overall structure of the calls remained acoustically similar,with overlapping characteristics across species.Furthermore,female Common Cuckoos exhibited greater within-individual variability in their calls,while the other species showed higher between-individual variability,which may further complicate species identification based vocalization alone.These findings highlight the complexities of female vocalizations in Cuculus cuckoos and suggest that ecological,social,and evolutionary factors may contribute to this vocal variability.展开更多
Avian brood parasitism is a unique reproductive behavior in which parasitic birds depend on other species to incubate their eggs and raise their offspring.In China,there are 20 species of cuckoos in the family Cuculid...Avian brood parasitism is a unique reproductive behavior in which parasitic birds depend on other species to incubate their eggs and raise their offspring.In China,there are 20 species of cuckoos in the family Cuculidae,order Cuculiformes,of which 17 species are parasitic cuckoos.This makes China one of the countries with the largest number of parasitic cuckoo species worldwide.Understanding the host utilization of cuckoos provides fundamental data for studying the coevolution of cuckoos with their hosts.We collected information on cuckoo hosts from the literature,photographs provided by birdwatchers,and online short video platforms,combined these data with our field observations,and summarized the parasitic cuckoos and their host species in China.A total of 1155 parasitism events were counted,involving 12 parasitic cuckoo species and 87 bird host species.These hosts belonged to 26 families,among which Muscicapidae was the most diverse with 19 species,accounting for 21.8%of the total hosts,followed by the families Phylloscopidae and Leiothrichidae with 8 species each,accounting for 9.2%of the total hosts recorded.The Common Cuckoo(Cuculus canorus)had the largest number of host taxa with 38 species,accounting for 43.7%of the total host species.This study adds 14 host species that have not been reported in China.However,for five species,the Jacobin Cuckoo(Clamator jacobinus),Banded Bay Cuckoo(Cacomantis sonneratii),Violet Cuckoo(Chrysococcyx xanthorhynchus),Common Hawkcuckoo(Hierococcyx varius),and Whistling Hawk-cuckoo(Hierococcyx nisicolor),information regarding host utilization is still lacking.展开更多
Deep learning algorithm is an effective data mining method and has been used in many fields to solve practical problems.However,the deep learning algorithms often contain some hyper-parameters which may be continuous,...Deep learning algorithm is an effective data mining method and has been used in many fields to solve practical problems.However,the deep learning algorithms often contain some hyper-parameters which may be continuous,integer,or mixed,and are often given based on experience but largely affect the effectiveness of activity recognition.In order to adapt to different hyper-parameter optimization problems,our improved Cuckoo Search(CS)algorithm is proposed to optimize the mixed hyper-parameters in deep learning algorithm.The algorithm optimizes the hyper-parameters in the deep learning model robustly,and intelligently selects the combination of integer type and continuous hyper-parameters that make the model optimal.Then,the mixed hyper-parameter in Convolutional Neural Network(CNN),Long-Short-Term Memory(LSTM)and CNN-LSTM are optimized based on the methodology on the smart home activity recognition datasets.Results show that the methodology can improve the performance of the deep learning model and whether we are experienced or not,we can get a better deep learning model using our method.展开更多
This study introduces a hybrid Cuckoo Search-Deep Neural Network(CS-DNN)model for uncertainty quantification and composition optimization of Na_(1/2)Bi_(1/2)TiO_(3)(NBT)-based dielectric energy storage ceramics.Addres...This study introduces a hybrid Cuckoo Search-Deep Neural Network(CS-DNN)model for uncertainty quantification and composition optimization of Na_(1/2)Bi_(1/2)TiO_(3)(NBT)-based dielectric energy storage ceramics.Addressing the limitations of traditional ferroelectric materials—such as hysteresis loss and low breakdown strength under high electric fields—we fabricate(1−x)NBBT8-xBMT solid solutions via chemical modification and systematically investigate their temperature stability and composition-dependent energy storage performance through XRD,SEM,and electrical characterization.The key innovation lies in integrating the CS metaheuristic algorithm with a DNN,overcoming localminima in training and establishing a robust composition-property prediction framework.Our model accurately predicts room-temperature dielectric constant(ε_(r)),maximum dielectric constant(ε_(max)),dielectric loss(tanδ),discharge energy density(W_(rec)),and charge-discharge efficiency(η)from compositional inputs.A Monte Carlo-based uncertainty quantification framework,combined with the 3σ statistical criterion,demonstrates that CSDNN outperforms conventional DNN models in three critical aspects:Higher prediction accuracy(R^(2)=0.9717 vs.0.9382 for ε_(max));Tighter error distribution,satisfying the 99.7% confidence interval under the 3σprinciple;Enhanced robustness,maintaining stable predictions across a 25% composition span in generalization tests.While the model’s generalization is constrained by both the limited experimental dataset(n=45)and the underlying assumptions of MC-based data augmentation,the CS-DNN framework establishes a machine learning-guided paradigm for accelerated discovery of high-temperature dielectric capacitors through its unique capability in quantifying composition-level energy storage uncertainties.展开更多
Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate becau...Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.展开更多
Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a ...Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a two-area power system.Methods Two areas were connected through an AC tie line in parallel with a DC link to stabilize the frequency of oscillations in both areas.The PI parameters were tuned using the cuckoo search algorithm(CSA)to minimize the integral absolute error(IAE).A state matrix was provided,and the stability of the system was verified by calculating the eigenvalues.The frequency response was investigated for load variation,changes in the generator rate constraint,the turbine time constant,and the governor time constant.Results The CSA was compared with particle swarm optimization algorithm(PSO)under identical conditions.The system was modeled based on a state-space mathematical representation and simulated using MATLAB.The results demonstrated the effectiveness of the proposed controller based on both algorithms and,it is clear that CSA is superior to PSO.Conclusion The CSA algorithm smoothens the system response,reduces ripples,decreases overshooting and settling time,and improves the overall system performance under different disturbances.展开更多
Hole-nesting tits Parus spp.have been classified as"unsuitable"hosts for cuckoo parasitism because cuckoos cannot enter a cavity if the entrance is too small.However,Chinese tits could re-ject alien eggs and...Hole-nesting tits Parus spp.have been classified as"unsuitable"hosts for cuckoo parasitism because cuckoos cannot enter a cavity if the entrance is too small.However,Chinese tits could re-ject alien eggs and egg ejection rate increased with the local diversity of parasitic cuckoo species.Antiparasitic behavior among Chinese tits may have evolved due to greater size variation among sympatric cuckoo species.This raises the question of whether differently sized parasitic cuckoos pose different threats to Chinese tits.A green-backed tit Parus monticolus population that is sym-patric with Asian emerald cuckoo Chrysococcyx maculatus(eme-cuckoo,small-sized parasite)and common cuckoo Cuculus canorus(com-cuckoo,large-sized parasite),and a cinereous tit P.cinereus population that is only sympatric with com-cuckoo were chosen as study organisms.We observed behavioral response and recorded alarm calls of the 2 tit species to eme-cuckoo,com-cuckoo,chipmunk Tamias sibiricus(a nest predator)and dove Streptopelia orientalis(a harm-less control),and subsequently played back alarm calls to conspecific incubating females.In dummy experiments,both tit species performed intense response behavior to chipmunk,but rarely responded strongly to the 3 avian species.In playback experiments,both tit species responded strongly to conspecific chipmunk alarm calls,but rarely responded to dove alarm calls.The inten-sity of response of incubating female green-backed tits to eme-cuckoo and com-cuckoo alarm calls were similar to that of chipmunk alarm calls,while the intensity to eme-cuckoo alarm calls was higher than the intensity to dove alarm calls which was similar to that of com-cuckoo alarm calls.In contrast,few female cinereous tits responded to eme-cuckoo and com-cuckoo alarm calls.These findings indicated that the threat level of eme-cuckoo was slightly greater than that of com-cuckoo for sympatric green-backed tits,but not for allopatric cinereous tits.展开更多
The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and co...The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm.展开更多
Although egg color polymorphism has evolved as an effective defensive adaptation to brood parasitism,spatial variations in egg color polymorphism remain poorly characterized.Here,we investigated egg polymorphism in 64...Although egg color polymorphism has evolved as an effective defensive adaptation to brood parasitism,spatial variations in egg color polymorphism remain poorly characterized.Here,we investigated egg polymorphism in 647 host species(68 families and 231 gen era)parasitized by 41 species of Old Word cuckoos(1 family and 11 gen era)across Asia,Europe,Africa,and Australia.The diversity of parasitic cuckoos differs among continents,reflecting the continent-specific intensities of parasitic selection pressure on hosts.Therefore,host egg polymorphism is expected to evolve more frequently on continents with higher cuckoo diversity.We identified egg polymorphism in 24.1%of all host species and 47.6%of all host families.The common cuckoo Cuculus canorus utilized 184 hosts(28.4%of all host species).Hosts of the common cuckoo and of Chrysococcyx species were more likely to have polymorphic eggs than hosts parasitized by other cuckoos.Both the number of host species and the host families targeted by the cuckoo species were positively correlated with the frequency of host egg polymorphism.Most host species and most hosts exhibiting egg color polymorphism were located in Asia and Africa.Host egg polymorphism was observed less frequently in Australia and Europe.Our results also suggested that egg polymorphism tends to occur more frequently in hosts that are utilized by several cuckoo species or by generalist cuckoo species.We suggest that selecti on pressure on hosts from a given contin ent in creases proportionally to the number of cuckoo species,and that this selection pressure may,in turn,favor the evolution of host egg polymorphism.展开更多
The artificial nestbox on an Asian White Birch (Betula platyphylla) (1360 m in elevation) was used by a pair of Yellow-rumped Flycatcher (Ficedula zanthopygia) in Beijing, and five eggs were found in the nest in 2005....The artificial nestbox on an Asian White Birch (Betula platyphylla) (1360 m in elevation) was used by a pair of Yellow-rumped Flycatcher (Ficedula zanthopygia) in Beijing, and five eggs were found in the nest in 2005. One was much larger and was identified as the Oriental Cuckoo’s (Cuculus optatus) egg.展开更多
Background:Thrush species are rarely parasitized by cuckoos,but many have a strong egg recognition ability.To date,there is a limited understanding of the relationship between host egg rejection and cuckoo parasitism ...Background:Thrush species are rarely parasitized by cuckoos,but many have a strong egg recognition ability.To date,there is a limited understanding of the relationship between host egg rejection and cuckoo parasitism rate.Methods:By using egg experiments in the field,we compared egg rejection between two non‑parasitized potential host species and two parasitized hosts of cuckoos in the same region.Results:The White‑bellied Redstart(Luscinia phoenicuroides),a host of the Common Cuckoo(Cuculus canorus),rejected 66.6%of blue model eggs;the Elliot’s Laughingthrush(Trochalopteron elliotii),a host of the Large Hawk Cuckoo(Hierococcyx sparverioides),rejected 25%of blue model eggs and 46.1%of white model eggs;and the Chestnut Thrush(Turdus rubrocanus)and the Chinese Thrush(T.mupinensis),in which cuckoo parasitism has not been recorded,rejected 41.1 and 83.3%of blue model eggs,respectively.There were no significant differences in the egg rejection among them,although the Chinese Thrush showed the highest rate of egg rejection.Conclusions:This study indicates that the egg recognition ability of cuckoo hosts has no correlation with the actual parasitism rate of cuckoos.We suggest that the egg recognition ability of the two potential host species may have been retained from a parasitic history with the cuckoo,while the two common host species have developed their egg rejection abilities due to current parasitism pressure.In addition,our study highlights the importance of the multicuckoo parasite system for better understanding the selection pressure of parasitism on the evolution of host egg recognition abilities.展开更多
Interaction between a parasite and its host could lead to a co-evolutionary arms race. Cuckoo-host system is among the most studied of all brood parasite systems, but the cuckoos of Asia, on the other hand, are much l...Interaction between a parasite and its host could lead to a co-evolutionary arms race. Cuckoo-host system is among the most studied of all brood parasite systems, but the cuckoos of Asia, on the other hand, are much less well known. China has the most abundant cuckoo species in Asia. Many of these co-occur in sympatric areas, posing a potential risk of mis-identification of cuckoo nestlings, especially in Cuculus species. In this study we have provided a practical criterion to identify cuckoo nestlings species in the field and performed molecular phylogeny to confirm our empirical results. These results indicate that two distinct characteristics of cuckoo nestlings, i.e., the gape color pattern and feather traits can be considered as reliable species identification. To our knowledge, this is the first report for species identification of Cuculus nestlings through molecular analysis.展开更多
Generalist avian brood parasites vary considerably in their degree of host specialization(e.g.,number of hosts);some parasitize the nests of just a few host species,whereas others exploit more than 100 species.Several...Generalist avian brood parasites vary considerably in their degree of host specialization(e.g.,number of hosts);some parasitize the nests of just a few host species,whereas others exploit more than 100 species.Several factors,including habitat range,habitat type,and geographic location,have been suggested to account for these variations.However,inter-specific differences in individual attributes,such as personality and plasticity,have rarely been considered as potential factors of such variation,despite their potential relationship to,for example,range expansion.Using cage experiments,we tested the hypothesis that parasitic species exploiting more host species may be more active and exploratory.To this end,we quantified behaviors exhibited by two Cuculus cuckoos(Common Cuckoo C.canorus and Oriental Cuckoo C.optatus)that vary greatly in their number of host species.Specifically,we evaluated exploratory behavior displayed by birds in the cage,such as the number of movements,head-turning,wing-flapping,and stepping.The Common Cuckoo,which has a higher number of host species,tended to exhibit higher levels of exploratory behaviors than the Oriental Cuckoo.Our study showed that the two cuckoo species exhibited different exploratory levels,as predicted by the differences in their number of hosts.Further studies regarding the causality between individual attributes and host specialization with improved experimental methodology would greatly enhance our understanding of the role of individual characteristics in the coevolution of avian brood parasites and their hosts.展开更多
A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones,...A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance.Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems.展开更多
We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to es...We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems.This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy.Experiments are conducted on the Lorenz system and the Chen system.The proposed algorithm is used to estimate the parameters for these two systems.Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.展开更多
Background: Resemblance to raptors such as hawks(Accipiter spp.) is considered to be an adaptive strategy of cuckoos(Cuculus spp.), which has evolved to protect cuckoos against host attacks. However, the effectiveness...Background: Resemblance to raptors such as hawks(Accipiter spp.) is considered to be an adaptive strategy of cuckoos(Cuculus spp.), which has evolved to protect cuckoos against host attacks. However, the effectiveness of the mimicry remains controversial, and is not yet fully studied for highly aggressive hosts.Methods: We evaluated the effectiveness of sparrowhawk(Accipiter nisus) mimicry by common cuckoos(Cuculus canorus) in oriental reed warblers(Acrocephaus orientalis), which are highly aggressive hosts. Using a both the single and the paired dummy experiment, defense behaviors and attack intensities of oriental reed warblers against common cuckoos, sparrowhawks and oriental turtle doves(Streptopelia orientalis) were assessed.Results: Oriental reed warblers exhibit strong nest defense behaviors, and such behaviors do not change with breeding stage(i.e., egg stage and nestling stage). Furthermore, assistance from conspecific helpers may increase attack intensities. However, they were deterred from mobbing overall by the presence of the hawk.Conclusions: Oriental reed warblers are able to distinguish cuckoos from harmless doves. However, they may be deterred from mobbing by the presence of the predatory hawk, suggesting hawk mimicry may be ineffective and does not reduce attacks of cuckoos by highly aggressive hosts.展开更多
This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time ...This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions.展开更多
Nest sanitation is a ubiquitous behavior in birds and functions to remove foreign objects that accidentally have fallen into their nests. In avian brood parasitism, the host’s ability to recognize and reject parasiti...Nest sanitation is a ubiquitous behavior in birds and functions to remove foreign objects that accidentally have fallen into their nests. In avian brood parasitism, the host’s ability to recognize and reject parasitic eggs is a specific anti-parasitic behavior. Previous studies have shown that egg recognition may have evolved from nest sanitation behavior;however, few studies have offered evidence in support of this hypothesis. In the current study, we added one real white egg and one model egg to the nests of common tailorbirds (Orthotomus sutorius), the main host of plaintive cuckoos (Cacomantis merulinus), to explore the relationship between egg recognition ability in hosts and nest sanitation behavior. Results showed that common tailorbirds rejected both non-mimetic blue model eggs and mimetic white model eggs at a similar rate of 100%, but only rejected 16.1% of mimetic real white eggs. The egg rejection behavior of common tailorbirds towards both real and model eggs was consistent. However, when both blue model eggs and real white eggs were simultaneously added to their nests, the probability of rejecting the mimetic real white egg increased to 50%. The addition of blue model eggs not only increased the occurrence of nest sanitation behavior but also increased the ability to recognize and reject parasitic eggs. This suggests that nest sanitation may facilitate egg rejection in common tailorbird hosts.展开更多
Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In...Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In this study, three hybrid multi-step wind speed forecasting models are developed and compared — with each other and with earlier proposed wind speed forecasting models. The three models are based on wavelet decomposition(WD), the Cuckoo search(CS) optimization algorithm, and a wavelet neural network(WNN). They are referred to as CS-WD-ANN(artificial neural network), CS-WNN, and CS-WD-WNN, respectively. Wind speed data from two wind farms located in Shandong, eastern China, are used in this study. The simulation result indicates that CS-WD-WNN outperforms the other two models, with minimum statistical errors. Comparison with earlier models shows that CS-WD-WNN still performs best, with the smallest statistical errors. The employment of the CS optimization algorithm in the models shows improvement compared with the earlier models.展开更多
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by The Ministry of Education(NRF-2020R1I1A2063567)。
文摘In brood-parasitic Cuculus cuckoos,male vocalizations are species-specific and easily distinguishable,whereas female calls are remarkably similar across species,making species identification challenging.In this study,we examined the structural characteristics and variability of female bubbling calls among four Cuculus species(Common Cuckoo C.canorus,Oriental Cuckoo C.optatus,Indian Cuckoo C.micropterus,and Lesser Cuckoo C.poliocephalus)breeding in South Korea.Comprehensive acoustic analyses of seven call parameters,using recordings from 2021 to 2023,were conducted to quantify the characteristics of their calls and compare withinand between-individual variability across species.Significant differences were found across all call parameters,with the Common Cuckoo producing the highest number of notes and the Oriental Cuckoo the lowest-frequency calls.Despite these differences,the overall structure of the calls remained acoustically similar,with overlapping characteristics across species.Furthermore,female Common Cuckoos exhibited greater within-individual variability in their calls,while the other species showed higher between-individual variability,which may further complicate species identification based vocalization alone.These findings highlight the complexities of female vocalizations in Cuculus cuckoos and suggest that ecological,social,and evolutionary factors may contribute to this vocal variability.
基金supported by the National Key R&D Program of China(2023YFF1304600)supported by the National Natural Science Foundation of China(Nos.32160242 to JL,32470513 and 32270526 to W.L.)supported by the 2023 Ningxia Hui Autonomous Region Youth Science and Technology Support Talent Training Project。
文摘Avian brood parasitism is a unique reproductive behavior in which parasitic birds depend on other species to incubate their eggs and raise their offspring.In China,there are 20 species of cuckoos in the family Cuculidae,order Cuculiformes,of which 17 species are parasitic cuckoos.This makes China one of the countries with the largest number of parasitic cuckoo species worldwide.Understanding the host utilization of cuckoos provides fundamental data for studying the coevolution of cuckoos with their hosts.We collected information on cuckoo hosts from the literature,photographs provided by birdwatchers,and online short video platforms,combined these data with our field observations,and summarized the parasitic cuckoos and their host species in China.A total of 1155 parasitism events were counted,involving 12 parasitic cuckoo species and 87 bird host species.These hosts belonged to 26 families,among which Muscicapidae was the most diverse with 19 species,accounting for 21.8%of the total hosts,followed by the families Phylloscopidae and Leiothrichidae with 8 species each,accounting for 9.2%of the total hosts recorded.The Common Cuckoo(Cuculus canorus)had the largest number of host taxa with 38 species,accounting for 43.7%of the total host species.This study adds 14 host species that have not been reported in China.However,for five species,the Jacobin Cuckoo(Clamator jacobinus),Banded Bay Cuckoo(Cacomantis sonneratii),Violet Cuckoo(Chrysococcyx xanthorhynchus),Common Hawkcuckoo(Hierococcyx varius),and Whistling Hawk-cuckoo(Hierococcyx nisicolor),information regarding host utilization is still lacking.
基金Supported by the Anhui Province Sports Health Information Monitoring Technology Engineering Research Center Open Project (KF2023012)。
文摘Deep learning algorithm is an effective data mining method and has been used in many fields to solve practical problems.However,the deep learning algorithms often contain some hyper-parameters which may be continuous,integer,or mixed,and are often given based on experience but largely affect the effectiveness of activity recognition.In order to adapt to different hyper-parameter optimization problems,our improved Cuckoo Search(CS)algorithm is proposed to optimize the mixed hyper-parameters in deep learning algorithm.The algorithm optimizes the hyper-parameters in the deep learning model robustly,and intelligently selects the combination of integer type and continuous hyper-parameters that make the model optimal.Then,the mixed hyper-parameter in Convolutional Neural Network(CNN),Long-Short-Term Memory(LSTM)and CNN-LSTM are optimized based on the methodology on the smart home activity recognition datasets.Results show that the methodology can improve the performance of the deep learning model and whether we are experienced or not,we can get a better deep learning model using our method.
基金supported by the Postgraduate Education Reform and Quality Improvement Project of Henan Province(Grant Nos.YJS2023JD52 and YJS2025GZZ48)the Zhumadian 2023 Major Science and Technology Special Project(Grant No.ZMD SZDZX2023002)+1 种基金2025 Henan Province International Science and Technology Cooperation Project(Cultivation Project,No.252102521011)Research Merit-Based Funding Program for Overseas Educated Personnel in Henan Province(Letter of Henan Human Resources and Social Security Office[2025]No.37).
文摘This study introduces a hybrid Cuckoo Search-Deep Neural Network(CS-DNN)model for uncertainty quantification and composition optimization of Na_(1/2)Bi_(1/2)TiO_(3)(NBT)-based dielectric energy storage ceramics.Addressing the limitations of traditional ferroelectric materials—such as hysteresis loss and low breakdown strength under high electric fields—we fabricate(1−x)NBBT8-xBMT solid solutions via chemical modification and systematically investigate their temperature stability and composition-dependent energy storage performance through XRD,SEM,and electrical characterization.The key innovation lies in integrating the CS metaheuristic algorithm with a DNN,overcoming localminima in training and establishing a robust composition-property prediction framework.Our model accurately predicts room-temperature dielectric constant(ε_(r)),maximum dielectric constant(ε_(max)),dielectric loss(tanδ),discharge energy density(W_(rec)),and charge-discharge efficiency(η)from compositional inputs.A Monte Carlo-based uncertainty quantification framework,combined with the 3σ statistical criterion,demonstrates that CSDNN outperforms conventional DNN models in three critical aspects:Higher prediction accuracy(R^(2)=0.9717 vs.0.9382 for ε_(max));Tighter error distribution,satisfying the 99.7% confidence interval under the 3σprinciple;Enhanced robustness,maintaining stable predictions across a 25% composition span in generalization tests.While the model’s generalization is constrained by both the limited experimental dataset(n=45)and the underlying assumptions of MC-based data augmentation,the CS-DNN framework establishes a machine learning-guided paradigm for accelerated discovery of high-temperature dielectric capacitors through its unique capability in quantifying composition-level energy storage uncertainties.
文摘Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.
基金Supported by the Russian Science Foundation(Agreement 23-41-10001,https://rscf.ru/project/23-41-10001/).
文摘Background Interconnection of different power systems has a major effect on system stability.This study aims to design an optimal load frequency control(LFC)system based on a proportional-integral(PI)controller for a two-area power system.Methods Two areas were connected through an AC tie line in parallel with a DC link to stabilize the frequency of oscillations in both areas.The PI parameters were tuned using the cuckoo search algorithm(CSA)to minimize the integral absolute error(IAE).A state matrix was provided,and the stability of the system was verified by calculating the eigenvalues.The frequency response was investigated for load variation,changes in the generator rate constraint,the turbine time constant,and the governor time constant.Results The CSA was compared with particle swarm optimization algorithm(PSO)under identical conditions.The system was modeled based on a state-space mathematical representation and simulated using MATLAB.The results demonstrated the effectiveness of the proposed controller based on both algorithms and,it is clear that CSA is superior to PSO.Conclusion The CSA algorithm smoothens the system response,reduces ripples,decreases overshooting and settling time,and improves the overall system performance under different disturbances.
基金the National Natural Science Foundation of China(Nos.31770419 and 31470458 to H.W.,31772453 and 31970427 to W.L.)the Open Project Program of Jilin Provincial Key Laboratory of Animal Resource Conservation and Utilization(130028823)+1 种基金the Fundamental Research Funds for the Central Universities(2412018QD009)the Project funded by China Postdoctoral Science Foundation(2018M631854).
文摘Hole-nesting tits Parus spp.have been classified as"unsuitable"hosts for cuckoo parasitism because cuckoos cannot enter a cavity if the entrance is too small.However,Chinese tits could re-ject alien eggs and egg ejection rate increased with the local diversity of parasitic cuckoo species.Antiparasitic behavior among Chinese tits may have evolved due to greater size variation among sympatric cuckoo species.This raises the question of whether differently sized parasitic cuckoos pose different threats to Chinese tits.A green-backed tit Parus monticolus population that is sym-patric with Asian emerald cuckoo Chrysococcyx maculatus(eme-cuckoo,small-sized parasite)and common cuckoo Cuculus canorus(com-cuckoo,large-sized parasite),and a cinereous tit P.cinereus population that is only sympatric with com-cuckoo were chosen as study organisms.We observed behavioral response and recorded alarm calls of the 2 tit species to eme-cuckoo,com-cuckoo,chipmunk Tamias sibiricus(a nest predator)and dove Streptopelia orientalis(a harm-less control),and subsequently played back alarm calls to conspecific incubating females.In dummy experiments,both tit species performed intense response behavior to chipmunk,but rarely responded strongly to the 3 avian species.In playback experiments,both tit species responded strongly to conspecific chipmunk alarm calls,but rarely responded to dove alarm calls.The inten-sity of response of incubating female green-backed tits to eme-cuckoo and com-cuckoo alarm calls were similar to that of chipmunk alarm calls,while the intensity to eme-cuckoo alarm calls was higher than the intensity to dove alarm calls which was similar to that of com-cuckoo alarm calls.In contrast,few female cinereous tits responded to eme-cuckoo and com-cuckoo alarm calls.These findings indicated that the threat level of eme-cuckoo was slightly greater than that of com-cuckoo for sympatric green-backed tits,but not for allopatric cinereous tits.
基金supported by the National Natural Science Foundation of China(51875465)
文摘The present study proposed an enhanced cuckoo search(ECS) algorithm combined with artificial neural network(ANN) as the surrogate model to solve structural reliability problems. In order to enhance the accuracy and convergence rate of the original cuckoo search(CS) algorithm, the main parameters namely, abandon probability of worst nests paand search step sizeα0 are dynamically adjusted via nonlinear control equations. In addition, a global-best guided equation incorporating the information of global best nest is introduced to the ECS to enhance its exploitation. Then, the proposed ECS is linked to the well-trained ANN model for structural reliability analysis. The computational capability of the proposed algorithm is validated using five typical structural reliability problems and an engineering application. The comparison results show the efficiency and accuracy of the proposed algorithm.
基金We thank Laikun Ma,Tongping Su,and Juan Huo for their assistances.
文摘Although egg color polymorphism has evolved as an effective defensive adaptation to brood parasitism,spatial variations in egg color polymorphism remain poorly characterized.Here,we investigated egg polymorphism in 647 host species(68 families and 231 gen era)parasitized by 41 species of Old Word cuckoos(1 family and 11 gen era)across Asia,Europe,Africa,and Australia.The diversity of parasitic cuckoos differs among continents,reflecting the continent-specific intensities of parasitic selection pressure on hosts.Therefore,host egg polymorphism is expected to evolve more frequently on continents with higher cuckoo diversity.We identified egg polymorphism in 24.1%of all host species and 47.6%of all host families.The common cuckoo Cuculus canorus utilized 184 hosts(28.4%of all host species).Hosts of the common cuckoo and of Chrysococcyx species were more likely to have polymorphic eggs than hosts parasitized by other cuckoos.Both the number of host species and the host families targeted by the cuckoo species were positively correlated with the frequency of host egg polymorphism.Most host species and most hosts exhibiting egg color polymorphism were located in Asia and Africa.Host egg polymorphism was observed less frequently in Australia and Europe.Our results also suggested that egg polymorphism tends to occur more frequently in hosts that are utilized by several cuckoo species or by generalist cuckoo species.We suggest that selecti on pressure on hosts from a given contin ent in creases proportionally to the number of cuckoo species,and that this selection pressure may,in turn,favor the evolution of host egg polymorphism.
文摘The artificial nestbox on an Asian White Birch (Betula platyphylla) (1360 m in elevation) was used by a pair of Yellow-rumped Flycatcher (Ficedula zanthopygia) in Beijing, and five eggs were found in the nest in 2005. One was much larger and was identified as the Oriental Cuckoo’s (Cuculus optatus) egg.
基金This work was funded by the National Natural Science Foundation of China(Nos.31772453 and 31970427 to WL and 31472012 to Y‑HS).
文摘Background:Thrush species are rarely parasitized by cuckoos,but many have a strong egg recognition ability.To date,there is a limited understanding of the relationship between host egg rejection and cuckoo parasitism rate.Methods:By using egg experiments in the field,we compared egg rejection between two non‑parasitized potential host species and two parasitized hosts of cuckoos in the same region.Results:The White‑bellied Redstart(Luscinia phoenicuroides),a host of the Common Cuckoo(Cuculus canorus),rejected 66.6%of blue model eggs;the Elliot’s Laughingthrush(Trochalopteron elliotii),a host of the Large Hawk Cuckoo(Hierococcyx sparverioides),rejected 25%of blue model eggs and 46.1%of white model eggs;and the Chestnut Thrush(Turdus rubrocanus)and the Chinese Thrush(T.mupinensis),in which cuckoo parasitism has not been recorded,rejected 41.1 and 83.3%of blue model eggs,respectively.There were no significant differences in the egg rejection among them,although the Chinese Thrush showed the highest rate of egg rejection.Conclusions:This study indicates that the egg recognition ability of cuckoo hosts has no correlation with the actual parasitism rate of cuckoos.We suggest that the egg recognition ability of the two potential host species may have been retained from a parasitic history with the cuckoo,while the two common host species have developed their egg rejection abilities due to current parasitism pressure.In addition,our study highlights the importance of the multicuckoo parasite system for better understanding the selection pressure of parasitism on the evolution of host egg recognition abilities.
基金supported by the National Natural Science Foundation of China (No. 31071938, 31101646)the Key Project of the Chinese Ministry of Education (No. 212136)the Program for New Century Excellent Talents in University(NCET-10-0111)
文摘Interaction between a parasite and its host could lead to a co-evolutionary arms race. Cuckoo-host system is among the most studied of all brood parasite systems, but the cuckoos of Asia, on the other hand, are much less well known. China has the most abundant cuckoo species in Asia. Many of these co-occur in sympatric areas, posing a potential risk of mis-identification of cuckoo nestlings, especially in Cuculus species. In this study we have provided a practical criterion to identify cuckoo nestlings species in the field and performed molecular phylogeny to confirm our empirical results. These results indicate that two distinct characteristics of cuckoo nestlings, i.e., the gape color pattern and feather traits can be considered as reliable species identification. To our knowledge, this is the first report for species identification of Cuculus nestlings through molecular analysis.
基金supported by the National Research Foundation of Korea(NRF2017R1D1A1B03030329,NRF-2019K2A9A2A06022677)。
文摘Generalist avian brood parasites vary considerably in their degree of host specialization(e.g.,number of hosts);some parasitize the nests of just a few host species,whereas others exploit more than 100 species.Several factors,including habitat range,habitat type,and geographic location,have been suggested to account for these variations.However,inter-specific differences in individual attributes,such as personality and plasticity,have rarely been considered as potential factors of such variation,despite their potential relationship to,for example,range expansion.Using cage experiments,we tested the hypothesis that parasitic species exploiting more host species may be more active and exploratory.To this end,we quantified behaviors exhibited by two Cuculus cuckoos(Common Cuckoo C.canorus and Oriental Cuckoo C.optatus)that vary greatly in their number of host species.Specifically,we evaluated exploratory behavior displayed by birds in the cage,such as the number of movements,head-turning,wing-flapping,and stepping.The Common Cuckoo,which has a higher number of host species,tended to exhibit higher levels of exploratory behaviors than the Oriental Cuckoo.Our study showed that the two cuckoo species exhibited different exploratory levels,as predicted by the differences in their number of hosts.Further studies regarding the causality between individual attributes and host specialization with improved experimental methodology would greatly enhance our understanding of the role of individual characteristics in the coevolution of avian brood parasites and their hosts.
基金supported in part by the National Key Research and Development Program of China(2017YFB0306400)in part by the National Natural Science Foundation of China(61573089,71472080,71301066)Liaoning Province Dr.Research Foundation of China(20175032)
文摘A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance.Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60473042,60573067 and 60803102)
文摘We study the parameter estimation of a nonlinear chaotic system,which can be essentially formulated as a multidimensional optimization problem.In this paper,an orthogonal learning cuckoo search algorithm is used to estimate the parameters of chaotic systems.This algorithm can combine the stochastic exploration of the cuckoo search and the exploitation capability of the orthogonal learning strategy.Experiments are conducted on the Lorenz system and the Chen system.The proposed algorithm is used to estimate the parameters for these two systems.Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to the particle swarm optimization and the genetic algorithm when considering the quality of the solutions obtained.
基金supported by the National Natural Science Foundation of China(Nos.31672303 to CY,31472013 and 31772453 to WL)
文摘Background: Resemblance to raptors such as hawks(Accipiter spp.) is considered to be an adaptive strategy of cuckoos(Cuculus spp.), which has evolved to protect cuckoos against host attacks. However, the effectiveness of the mimicry remains controversial, and is not yet fully studied for highly aggressive hosts.Methods: We evaluated the effectiveness of sparrowhawk(Accipiter nisus) mimicry by common cuckoos(Cuculus canorus) in oriental reed warblers(Acrocephaus orientalis), which are highly aggressive hosts. Using a both the single and the paired dummy experiment, defense behaviors and attack intensities of oriental reed warblers against common cuckoos, sparrowhawks and oriental turtle doves(Streptopelia orientalis) were assessed.Results: Oriental reed warblers exhibit strong nest defense behaviors, and such behaviors do not change with breeding stage(i.e., egg stage and nestling stage). Furthermore, assistance from conspecific helpers may increase attack intensities. However, they were deterred from mobbing overall by the presence of the hawk.Conclusions: Oriental reed warblers are able to distinguish cuckoos from harmless doves. However, they may be deterred from mobbing by the presence of the predatory hawk, suggesting hawk mimicry may be ineffective and does not reduce attacks of cuckoos by highly aggressive hosts.
基金the National Natural Science Foundation of China(No.61571146)the Fundamental Research Funds for the Central Universities of China(No.HEUCFP201769)
文摘This paper formulates a new framework to estimate the target position by adopting cuckoo search(CS)positioning algorithm. Addressing the nonlinear optimization problem is a crucial spot in the location system of time difference of arrival(TDOA). With the application of the Levy flight mechanism, the preferential selection mechanism and the elimination mechanism, the proposed approach prevents positioning results from falling into local optimum. These intelligent mechanisms are useful to ensure the population diversity and improve the convergence speed. Simulation results demonstrate that the cuckoo localization algorithm has higher locating precision and better performance than the conventional methods. Compared with particle swarm optimization(PSO) algorithm and Newton iteration algorithm, the proposed method can obtain the Cram′er-Rao lower bound(CRLB) and quickly achieve the global optimal solutions.
基金supported by the National Natural Science Foundation of China(31672303 to C.C.Y.,and 31472013,31772453 and 31970427 to W.L.)
文摘Nest sanitation is a ubiquitous behavior in birds and functions to remove foreign objects that accidentally have fallen into their nests. In avian brood parasitism, the host’s ability to recognize and reject parasitic eggs is a specific anti-parasitic behavior. Previous studies have shown that egg recognition may have evolved from nest sanitation behavior;however, few studies have offered evidence in support of this hypothesis. In the current study, we added one real white egg and one model egg to the nests of common tailorbirds (Orthotomus sutorius), the main host of plaintive cuckoos (Cacomantis merulinus), to explore the relationship between egg recognition ability in hosts and nest sanitation behavior. Results showed that common tailorbirds rejected both non-mimetic blue model eggs and mimetic white model eggs at a similar rate of 100%, but only rejected 16.1% of mimetic real white eggs. The egg rejection behavior of common tailorbirds towards both real and model eggs was consistent. However, when both blue model eggs and real white eggs were simultaneously added to their nests, the probability of rejecting the mimetic real white egg increased to 50%. The addition of blue model eggs not only increased the occurrence of nest sanitation behavior but also increased the ability to recognize and reject parasitic eggs. This suggests that nest sanitation may facilitate egg rejection in common tailorbird hosts.
基金supported by the National Key Research and Development Program of China [grant number2017YFA0604500]
文摘Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In this study, three hybrid multi-step wind speed forecasting models are developed and compared — with each other and with earlier proposed wind speed forecasting models. The three models are based on wavelet decomposition(WD), the Cuckoo search(CS) optimization algorithm, and a wavelet neural network(WNN). They are referred to as CS-WD-ANN(artificial neural network), CS-WNN, and CS-WD-WNN, respectively. Wind speed data from two wind farms located in Shandong, eastern China, are used in this study. The simulation result indicates that CS-WD-WNN outperforms the other two models, with minimum statistical errors. Comparison with earlier models shows that CS-WD-WNN still performs best, with the smallest statistical errors. The employment of the CS optimization algorithm in the models shows improvement compared with the earlier models.
