Golden eagle based improved Att-BiLSTM model for big data classification with hybrid feature extraction and feature selection techniques.

The remarkable development in technology has led to the increase of massive big data. Machine learning processes provide a way for investigators to examine and particularly classify big data. Besides, several machine learning models rely on powerful feature extraction and feature selection techniques for their success. In this paper, a big data classification approach is developed using an optimized deep learning classifier integrated with hybrid feature extraction and feature selection approaches. The proposed technique uses local linear embedding-based kernel principal component analysis and perturbation theory, respectively, to extract more representative data and select the appropriate features from the big data environment. In addition, the feature selection task is fine-tuned by using perturbation theory through heuristic search based on their output accuracy. This feature selection heuristic search method is analysed with five recent heuristic optimization algorithms for deciding the final feature subset. Finally, the data are categorized through an attention-based bidirectional long short-term memory classifier that is optimized with a golden eagle-inspired algorithm. The performance of the proposed model is experimentally verified on publicly accessible datasets. From the experimental outcomes, it is demonstrated that the proposed framework is capable of classifying large datasets with more than 90% accuracy.

Turbulence explains the accelerations of an eagle in natural flight.

Turbulent winds and gusts fluctuate on a wide range of timescales from milliseconds to minutes and longer, a range that overlaps the timescales of avian flight behavior, yet the importance of turbulence to avian behavior is unclear. By combining wind speed data with the measured accelerations of a golden eagle (Aquila chrysaetos) flying in the wild, we find evidence in favor of a linear relationship between the eagle's accelerations and atmospheric turbulence for timescales between about 1/2 and 10 s. These timescales are comparable to those of typical eagle behaviors, corresponding to between about 1 and 25 wingbeats, and to those of turbulent gusts both larger than the eagle's wingspan and smaller than large-scale atmospheric phenomena such as convection cells. The eagle's accelerations exhibit power spectra and intermittent activity characteristic of turbulence and increase in proportion to the turbulence intensity. Intermittency results in accelerations that are occasionally several times stronger than gravity, which the eagle works against to stay aloft. These imprints of turbulence on the bird's movements need to be further explored to understand the energetics of birds and other volant life-forms, to improve our own methods of flying through ceaselessly turbulent environments, and to engage airborne wildlife as distributed probes of the changing conditions in the atmosphere.

Diagnosis and Surgical Treatment of a Renal Cyst Causing Unilateral Lameness in a Golden Eagle (Aquila chrysaetos).

This report describes the diagnosis and treatment of a benign renal cyst in an adult, female golden eagle (Aquila chrysaetos) presented for unilateral leg lameness. A cyst at the cranial division of the left kidney was diagnosed by computed tomography and was suspected of compressing the lumbosacral nerve plexus, resulting in limb lameness. The renal cyst was incompletely excised because the cyst wall was closely adhered to the kidney parenchyma and local blood supply. Fluid analysis and surgical biopsy of the cyst and left kidney confirmed the diagnosis of a benign renal cyst. No evidence of an infectious, inflammatory, or neoplastic etiology was noted. Postoperatively, the eagle's lameness resolved and the bird was ultimately released following recovery. During treatment for the renal cyst, the eagle was concurrently found to have increased serum titers on elementary body agglutination for Chlamydia psittaci and a positive titer for Aspergillus species antibody testing. The bird was administered doxycycline, azithromycin, and voriconazole for treatment of these potential pathogens prior to release. Unfortunately, the eagle was found dead 86 days postrelease due to an unknown cause. To the authors' knowledge, this is the first report of a golden eagle with a benign solitary renal cyst causing unilateral lameness secondary to nerve compression that was resolved with surgical excision.

Postmortem Evaluation of Cardiac Valvular Disease in Bald Eagles (Haliaeetus leucocephalus) and a Golden Eagle (Aquila chrysaetos).

Limited data are available regarding cardiac diseases in birds of prey despite their prevalence in these avian species. Literature regarding valvular lesions in birds of prey is scarce and includes single reports of left atrioventricular valvular endocarditis in an adult, free-ranging, male bald eagle (Haliaeetus leucocephalus) and aortic valvular endocarditis in an adult, free-ranging, female red-tailed hawk (Buteo jamaicensis). The purpose of this study was to evaluate the prevalence, signalment, gross necropsy findings, and histologic lesions of valvular lesions in eagles. In this retrospective study, necropsy reports for 24 free-ranging and captive eagles were evaluated over a 15-year period (July 3, 2006-February 28, 2021). Six (25%; 95% confidence interval: 8.9-58.9) birds, 5 bald eagles and 1 golden eagle (Aquila chrysaetos), met the inclusion criteria. Five (83.3%) of the 6 birds had valvular degeneration, 2 (33.3%) had endocarditis, and Staphylococcus aureus was cultured from 1 (16.7%) of the endocarditis cases. The 6 eagles with valvular lesions were all captive adults. Four of the birds were female (66.7%), and the aortic and left atrioventricular valves were equally affected. Acute or chronic cerebral infarcts were present in all 6 birds. Valvular cardiac disease should be considered as a differential diagnosis in eagles exhibiting respiratory distress, neurologic signs, syncope, or in cases of sudden death.

Age-specific survival rates, causes of death, and allowable take of golden eagles in the western United States.

In the United States, the Bald and Golden Eagle Protection Act prohibits take of golden eagles (Aquila chrysaetos) unless authorized by permit, and stipulates that all permitted take must be sustainable. Golden eagles are unintentionally killed in conjunction with many lawful activities (e.g., electrocution on power poles, collision with wind turbines). Managers who issue permits for incidental take of golden eagles must determine allowable take levels and manage permitted take accordingly. To aid managers in making these decisions in the western United States, we used an integrated population model to obtain estimates of golden eagle vital rates and population size, and then used those estimates in a prescribed take level (PTL) model to estimate the allowable take level. Estimated mean annual survival rates for golden eagles ranged from 0.70 (95% credible interval = 0.66-0.74) for first-year birds to 0.90 (0.88-0.91) for adults. Models suggested a high proportion of adult female golden eagles attempted to breed and breeding pairs fledged a mean of 0.53 (0.39-0.72) young annually. Population size in the coterminous western United States has averaged ~31,800 individuals for several decades, with λ = 1.0 (0.96-1.05). The PTL model estimated a median allowable take limit of ~2227 (708-4182) individuals annually given a management objective of maintaining a stable population. We estimate that take averaged 2572 out of 4373 (59%) deaths annually, based on a representative sample of transmitter-tagged golden eagles. For the subset of golden eagles that were recovered and a cause of death determined, anthropogenic mortality accounted for an average of 74% of deaths after their first year; leading forms of take over all age classes were shooting (~670 per year), collisions (~611), electrocutions (~506), and poisoning (~427). Although observed take overlapped the credible interval of our allowable take estimate and the population overall has been stable, our findings indicate that additional take, unless mitigated for, may not be sustainable. Our analysis demonstrates the utility of the joint application of integrated population and prescribed take level models to management of incidental take of a protected species.

Demographic partitioning of dynamic energy subsidies revealed with an Ornstein-Uhlenbeck space use model.

In populations across many taxa, a large fraction of sexually mature individuals do not breed but are attempting to enter the breeding population. Such individuals, often referred to as "floaters," can play critical roles in the dynamics and stability of these populations and buffer them through periods of high adult mortality. Floaters are difficult to study, however, so we lack data needed to understand their roles in the population ecology and conservation status of many species. Here, we analyzed satellite telemetry data with a newly developed mechanistic space use model based on an Ornstein-Uhlenbeck process to help overcome the paucity of data in studying the differential habitat selection and space use of floater and territorial golden eagles Aquila chrysaetos. Our sample consisted of 49 individuals tracked over complete breeding seasons across 4 years, totaling 104 eagle breeding seasons. Modeling these data mechanistically was required to disentangle key differences in movement and particularly to separate aspects of movement driven by resource selection from those driven by use of a central place. We found that floaters generally had more expansive space use patterns and larger home ranges, as well as evidence that they partition space with territorial individuals seemingly on fine scales through differential habitat and resource selection. Floater and territorial eagle home ranges overlapped markedly, suggesting that floaters use the interstices between territories. Furthermore, floater and territorial eagles differed in how they selected for uplift variables, key components of soaring birds' energy landscape, with territorial eagles apparently better able to find and use thermal uplift. We also found relatively low individual heterogeneity in resource selection, especially among territorial individuals, suggesting a narrow realized niche for breeding individuals, which varied from the level of among-individual variation present during migration. This work furthers our understanding of floaters' potential roles in the population ecology of territorial species and suggests that conserving landscapes occupied by territorial eagles also protects floaters.

Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds.

Human modification of landscapes includes extensive addition of linear features, such as roads and transmission lines. These can alter animal movement and space use and affect the intensity of interactions among species, including predation and competition. Effects of linear features on animal movement have seen relatively little research in avian systems, despite ample evidence of their effects in mammalian systems and that some types of linear features, including both roads and transmission lines, are substantial sources of mortality. Here, we used satellite telemetry combined with step selection functions designed to explicitly incorporate the energy landscape (el-SSFs) to investigate the effects of linear features and habitat on movements and space use of a large soaring bird, the golden eagle Aquila chrysaetos, during migration. Our sample consisted of 32 adult eagles tracked for 45 spring and 39 fall migrations from 2014 to 2017. Fitted el-SSFs indicated eagles had a strong general preference for south-facing slopes, where thermal uplift develops predictably, and that these areas are likely important aspects of migratory pathways. el-SSFs also provided evidence that roads and railroads affected movement during both spring and fall migrations, but eagles selected areas near roads to a greater degree in spring compared to fall and at higher latitudes compared to lower latitudes. During spring, time spent near linear features often occurred during slower-paced or stopover movements, perhaps in part to access carrion produced by vehicle collisions. Regardless of the behavioural mechanism of selection, use of these features could expose eagles and other soaring species to elevated risk via collision with vehicles and/or transmission lines. Linear features have previously been documented to affect the ecology of terrestrial species (e.g. large mammals) by modifying individuals' movement patterns; our work shows that these effects on movement extend to avian taxa.

Acute intraparenchymal cerebral haemorrhage in an Iberian golden eagle - a case report.

BACKGROUND: In birds there are reports of intracranial lesions but not of the clinical, computed tomographic and histopathologic features of acute intraparenchymal cerebral haemorrhage in Iberian golden eagle. CASE PRESENTATION: The following report describes a case of a 30-year-old Iberian golden eagle (Aquila chrysaetos homeyeri) with no history of trauma, presented with acute opisthotonus, left head tilt and circling, anisocoria, positional nystagmus, and ataxia. The main differential diagnosis were hypovitaminosis B or E and intracranial disease due to trauma, infection, toxins or masses. A computed tomography (CT) of the head was performed with an 8-slices scanner and evidenced a hyperdense (63-65 HU) non-enhancing homogeneous well delineated round area in the midbrain, with 6 mm in its highest diameter. The attenuation values and the non-enhancing nature of the lesion strongly suggested the diagnosis of acute intraparenchymal haemorrhage, which was histologically confirmed after necropsy. CONCLUSIONS: In birds with a central neurological dysfunction, the diagnosis of acute brain haemorrhage should be considered when the CT evidences a non-enhancing, homogeneous, well circumscribed hyperattenuated round area.

SPATIAL DEMOGRAPHIC MODELS TO INFORM CONSERVATION PLANNING OF GOLDEN EAGLES IN RENEWABLE ENERGY LANDSCAPES.

Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land-use and other anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (Aquila chrysaetos). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, USA. We developed a spatially-explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind-turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative impacts. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative risks of proposed management options to Golden Eagles and their habitats.

Electrocution of Raptors on Power Lines: A Review of Necropsy Methods and Findings.

Decades after the problem was first identified, power line electrocution continues to be a cause of avian mortality. Currently, several federal laws protect eagles and other migratory birds, meaning that utility companies may be liable for electrocution-related deaths. Veterinarians and veterinary pathologists called upon to diagnose and treat electrocuted birds should keep this in mind when conducting clinical and postmortem examinations. This review details necropsy findings and methods used to diagnose electrocution. A combination of gross, subgross, and radiographic examinations can aid in identification of subtle injury. Diagnosis is made based on the presence of skin and/or feather burns. Other necropsy findings may include skin lacerations, subcutaneous burns, bruising, limb avulsion, hemopericardium, and vascular rupture. At the US Fish and Wildlife Service's National Forensics Laboratory, from 2000 to 2015, 417 raptor deaths were determined to have been caused by electrocution. Bald eagles and golden eagles were the most commonly submitted species. In a retrospective review of 377 cases, for which whole bodies were submitted, 18% of the electrocuted birds had only a single, small (less than 3 cm in diameter) external burn. Small, isolated burns tended to occur on the undersides of the wings at and distal to the elbow and on the lower legs and feet. These areas should be most carefully examined in cases where electrocution injury is not immediately apparent.

Heterotopic Ossification Secondary to Gunshot and Fragment Wounds in a Golden Eagle ( Aquila chrysaetos ).

Heterotopic ossification is the process of pathologic bone formation in soft tissue structures that usually do not form bone. An immature golden eagle ( Aquila chrysaetos ) was examined 2 months after a gunshot wound in the right wing. A solid oval mass with a gun pellet at its core was found attached to the ulna by a bony pedicle and was surgically excised. Heterotopic ossification secondary to gunshot and fragment wounds in the right ulna was diagnosed based on clinical, radiographic, and histopathologic findings. This report is the first to describe heterotopic ossification occurring around a gun pellet in a bird.

CHARACTERIZATION OF NATURAL EJACULATES AND SPERM CRYOPRESERVATION IN A GOLDEN EAGLE (AQUILA CHRYSAETUS).

This paper describes the sperm characteristics and response to cooling and freezing of naturally ejaculated semen from a captive, adult golden eagle (Aquila chrysaetus) trained to allow sperm recovery via cooperative copulation. A basic spermiogram was prepared, and sperm motility and morphometric variables recorded using a computer-aided system. For sperm storage, the effects of a polyvinylpyrrolidone-based extender were evaluated at 5°C. The same extender was also used in freezing procedures in which glycerol (11%) and dimethylacetamide (6%) were compared as cryoprotectants. The extender preserved sperm viability over storage periods of up to 6 days. Although sperm motility and percentage live sperm values were poorer for frozen-thawed (5.8-14.6% and 44-42%, respectively) than for fresh samples (46.7 and 74.6%, respectively), no differences were seen between the effects of the two cryoprotectants. These results could be of use when attempting to store the sperm of golden eagles and other raptors.

Mange Caused by a Novel Micnemidocoptes Mite in a Golden Eagle ( Aquila chrysaetos ).

A second-year, female golden eagle ( Aquila chrysaetos ) was live trapped in northern California because of severe feather loss and crusting of the skin on the head and legs. On physical examination, the bird was lethargic, dehydrated, and thin, with severe feather loss and diffuse hyperemia and crusting on the head, ventral wings, ventrum, dorsum, and pelvic limbs. Mites morphologically similar to Micnemidocoptes derooi were identified with scanning electron microscopy. The eagle was treated with ivermectin (0.4 mg/kg) once weekly for 7 weeks, as well as pyrethrin, meloxicam, ceftiofur crystalline free acid, and voriconazole. Although the eagle's condition improved, and live mites or eggs were not evident on skin scrapings at the time of completion of ivermectin treatment, evidence of dead mites and mite feces were present after the last dose of ivermectin. Two additional doses of ivermectin and 2 doses of topical selamectin (23 mg/kg) were administered 2 and 4 weeks apart, respectively. No mite eggs, feces, or adults were evident after treatment was completed. A second golden eagle found in the same region was also affected with this mite but died soon after presentation. This is the first report, to our knowledge, of successful treatment, as well as treatment with selamectin, of mites consistent with Micnemidocoptes species in any raptorial species.

Assessing risk to birds from industrial wind energy development via paired resource selection models.

When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework can be applied across multiple spatial scales to understand and mitigate impacts of industry on wildlife. We estimated risk to Golden Eagles (Aquila chrysaetos) from wind energy development in 3 topographically distinct regions of the central Appalachian Mountains of Pennsylvania (United States) based on models of resource selection of wind facilities (n = 43) and of northbound migrating eagles (n = 30). Risk to eagles from wind energy was greatest in the Ridge and Valley region; all 24 eagles that passed through that region used the highest risk landscapes at least once during low altitude flight. In contrast, only half of the birds that entered the Allegheny Plateau region used highest risk landscapes and none did in the Allegheny Mountains. Likewise, in the Allegheny Mountains, the majority of wind turbines (56%) were situated in poor eagle habitat; thus, risk to eagles is lower there than in the Ridge and Valley, where only 1% of turbines are in poor eagle habitat. Risk within individual facilities was extremely variable; on average, facilities had 11% (SD 23; range = 0-100%) of turbines in highest risk landscapes and 26% (SD 30; range = 0-85%) of turbines in the lowest risk landscapes. Our results provide a mechanism for relocating high-risk turbines, and they show the feasibility of this novel and highly adaptable framework for managing risk of harm to wildlife from industrial development.

Conservative treatment of a synovial cyst in a golden eagle (Aquila chrysaetos) with triamcinolone acetonide.

In human and veterinary medicine, the treatment of synovial cysts involves medical or surgical approach. When medical treatment is chosen, triamcinolone acetonide is one of the most used drugs. In this case, intracystic triamcinolone was administered for the treatment of a non-infectious elbow synovial cyst in a subadult female Golden eagle (Aquila chrysaetos), unable to fly. The bird was brought to a wildlife rescue center after an aerial fight with a conspecific. After the treatment, no clinically detectable adverse effects were noted and there was no recurrence within two weeks. Given the improvement of the clinical conditions and the recovery of flight ability, the animal was released back into the wild 17 days after administration of the drug.

IoT-based COVID-19 detection using recalling-enhanced recurrent neural network optimized with golden eagle optimization algorithm.

New potential for healthcare has been made possible by the development of the Internet of Medical Things (IoMT) with deep learning. This is applied for a broad range of applications. Normal medical devices together with sensors can gather important data when connected to the Internet, and deep learning uses this data to reveal symptoms and patterns and activate remote care. In recent years, the COVID-19 pandemic caused more mortality. Millions of people have been affected by this virus, and the number of infections is continually rising daily. To detect COVID-19, researchers attempt to utilize medical imaging and deep learning-based methods. Several methodologies were suggested utilizing chest X-ray (CXR) images for COVID-19 diagnosis. But these methodologies do not provide satisfactory accuracy. To overcome these drawbacks, a recalling-enhanced recurrent neural network optimized with golden eagle optimization algorithm (RERNN-GEO) is proposed in this paper. The intention of this work is to provide IoT-based deep learning method for the premature identification of COVID-19. This paradigm can be able to ease the workload of radiologists and medical specialists and also help with pandemic control. RERNN-GEO is a deep learning-based method; this is utilized in chest X-ray (CXR) images for COVID-19 diagnosis. Here, the Gray-Level Co-Occurrence Matrix (GLCM) window adaptive algorithm is used for extracting features to enable accurate diagnosis. By utilizing this algorithm, the proposed method attains better accuracy (33.84%, 28.93%, and 33.03%) and lower execution time (11.06%, 33.26%, and 23.33%) compared with the existing methods. This method can be capable of helping the clinician/radiologist to validate the initial assessment related to COVID-19.

Fault causes and its detection in standalone PV system using ANN and GEO technique.

Power generation systems using photovoltaic (PV) technology have become increasingly popular due to their high production efficiency. A partial shading defect is the most common defect in this system under the process of production, diminishing both the amount and quality of energy produced. This paper proposes an Artificial Neural Network and Golden Eagle Optimization based prediction of the fault and its detection in a standalone PV system to recover the optimum performance and diagnosis of the PV system. The proposed technique combines the Artificial Neural Network (ANN) and Golden Eagle Optimization (GEO) algorithm. The major contribution of this work is to raise PV systems' performance. The result is a defect in the classification and identification of an ANN is used. The use of GEO provides an efficient optimization technique for ANN training, which reduces the training time and improves the accuracy of the model. The proposed technique is executed on the MATLAB site and contrasted with different present techniques, like genetic algorithm (GA),Elephant Herding Optimization (EHO) and Particle Swarm Optimization (PSO). The findings displays that the proposed technique is more accurate and effective than the existing methodologies for detecting and diagnosing defects in PV systems.

Developmental stage shapes the realized energy landscape for a flight specialist.

The heterogeneity of the physical environment determines the cost of transport for animals, shaping their energy landscape. Animals respond to this energy landscape by adjusting their distribution and movement to maximize gains and reduce costs. Much of our knowledge about energy landscape dynamics focuses on factors external to the animal, particularly the spatio-temporal variations of the environment. However, an animal's internal state can significantly impact its ability to perceive and utilize available energy, creating a distinction between the 'fundamental' and the 'realized' energy landscapes. Here, we show that the realized energy landscape varies along the ontogenetic axis. Locomotor and cognitive capabilities of individuals change over time, especially during the early life stages. We investigate the development of the realized energy landscape in the Central European Alpine population of the golden eagle Aquila chrysaetos, a large predator that requires negotiating the atmospheric environment to achieve energy-efficient soaring flight. We quantified weekly energy landscapes using environmental features for 55 juvenile golden eagles, demonstrating that energetic costs of traversing the landscape decreased with age. Consequently, the potentially flyable area within the Alpine region increased 2170-fold during their first three years of independence. Our work contributes to a predictive understanding of animal movement by presenting ontogeny as a mechanism shaping the realized energy landscape.

Estimating Raptor Nesting Success: Old and New Approaches.

Studies of nesting success can be valuable in assessing the status of raptor populations, but differing monitoring protocols can present unique challenges when comparing populations of different species across time or geographic areas. We used large datasets from long-term studies of 3 raptor species to compare estimates of apparent nest success (ANS, the ratio of successful to total number of nesting attempts), Mayfield nesting success, and the logistic-exposure model of nest survival. Golden eagles (Aquila chrysaetos), prairie falcons (Falco mexicanus), and American kestrels (F. sparverius) differ in their breeding biology and the methods often used to monitor their reproduction. Mayfield and logistic-exposure models generated similar estimates of nesting success with similar levels of precision. Apparent nest success overestimated nesting success and was particularly sensitive to inclusion of nesting attempts discovered late in the nesting season. Thus, the ANS estimator is inappropriate when exact point estimates are required, especially when most raptor pairs cannot be located before or soon after laying eggs. However, ANS may be sufficient to assess long-term trends of species in which nesting attempts are highly detectable.

Study on optimization of multi-UAV nucleic acid sample delivery paths in large cities under the influence of epidemic environment.

In the context of global novel coronavirus infection, we studied the distribution problem of nucleic acid samples, which are medical supplies with high urgency. A multi-UAV delivery model of nucleic acid samples with time windows and a UAV (Unmanned Aerial Vehicle) dynamics model for multiple distribution centers is established by considering UAVs' impact cost and trajectory cost. The Golden Eagle optimization algorithm (SGDCV-GEO) based on gradient optimization and Corsi variation is proposed to solve the model by introducing gradient optimization and Corsi variation strategy in the Golden Eagle optimization algorithm. Performance evaluation by optimizing test functions, Friedman and Nemenyi test compared with Golden Jackal Optimization (GJO), Hunter-Prey Optimization (HPO), Pelican Optimization Algorithm (POA), Reptile Search Algorithm (RSA) and Golden Eagle Optimization (GEO), the convergence performance of SGDCV-GEO algorithm was demonstrated. Further, the improved RRT (Rapidly-exploring Random Trees) algorithm is used in the UAV path planning, and the pruning process and logistic chaotic mapping strategy are introduced in the path generation method. Finally, simulation experiments are conducted based on 8 hospitals and 50 randomly selected communities in the Pudong district of Shanghai, southern China. The experimental results show that the developed algorithm can effectively reduce the delivery cost and total delivery time compared with simulated annealing algorithm (SA), crow search algorithm (CSA), particle swarm algorithm (PSO), and taboo search algorithm (TS), and the developed algorithm has good uniformity, robustness, and high convergence accuracy, which can be effectively applied to the multi-UAV nucleic acid sample delivery path optimization in large cities under the influence of an epidemic environment.