Panthera Tigris Altaica Research Articles

A Multi-Strategy Siberian Tiger Optimization Algorithm for Task Scheduling in Remote Sensing Data Batch Processing

With advancements in integrated space–air–ground global observation capabilities, the volume of remote sensing data is experiencing exponential growth. Traditional computing models can no longer meet the task processing demands brought about by the vast amounts of remote sensing data. As an important means of processing remote sensing data, distributed cluster computing’s task scheduling directly impacts the completion time and the efficiency of computing resource utilization. To enhance task processing efficiency and optimize the allocation of computing resources, this study proposes a Multi-Strategy Improved Siberian Tiger Optimization (MSSTO) algorithm based on the original Siberian Tiger Optimization (STO) algorithm. The MSSTO algorithm integrates the Tent chaotic map, the Lévy flight strategy, Cauchy mutation, and a learning strategy, showing significant advantages in convergence speed and global optimal solution search compared to the STO algorithm. By combining stochastic key encoding schemes and uniform allocation encoding schemes, taking the task scheduling of aerosol optical depth retrieval as a case study, the research results show that the MSSTO algorithm significantly shortens the completion time (21% shorter compared to the original STO algorithm and an average of 15% shorter compared to nine advanced algorithms, such as a particle swarm algorithm and a gray wolf algorithm). It demonstrates superior solution accuracy and convergence speed over various competing algorithms, achieving the optimal execution sequence and machine allocation scheme for task scheduling.

Amyloid-Beta, Tau, and Microglial Activation in Aged Felid Brains.

Alzheimer's disease (AD) and its associated pathology have been primarily identified in humans, who have relatively large brains and long lifespans. To expand what is known about aging and neurodegeneration across mammalian species, we characterized amyloid-beta (Aβ) and tau lesions in five species of aged felids (n = 9; cheetah, clouded leopard, African lion, serval, Siberian tiger). We performed immunohistochemistry to detect Aβ40 and Aβ42 in plaques and vessels and hyperphosphorylated tau in the temporal lobe gyrus sylvius and in the CA1 and CA3 subfields of the hippocampus. We also quantified the densities and morphological types of microglia expressing IBA1. We found that diffuse Aβ42 plaques, but not dense-core plaques, were present more frequentlyin the temporal cortex and tended to be more common thanAβ40 plaques across species. Conversely, vascular Aβ was labeled more consistently with Aβ40 for each species on average. Although all individuals showed some degree of Aβ40 and/or Aβ42 immunoreactivity, only the cheetahs and clouded leopards exhibited intraneuronal hyperphosphorylated tau (i.e., pretangles), which was more common in the hippocampus. Reactive, intermediate microglia were significantly associated with total Aβ40 vessel area and pretangle load in the hippocampus. This study demonstrates the co-occurrence of Aβ and tau pathology in two felid species, cheetahs and clouded leopards. Overall, these results provide an initial view of the manifestation of Aβ and tau pathology in aged, large-brained felids, which can be compared with markers of neurodegeneration across different taxa, including domestic cats, nonhuman primates, and humans.

Gut Microbiome Diversity and Composition in Captive Siberian Tigers (Panthera tigris altaica): The Influence of Diet, Health Status, and Captivity on Microbial Communities

The gut microbiome is essential for the health of carnivorous mammals, including the endangered Siberian tiger (Panthera tigris altaica). However, limited research exists on the gut microbiome of captive Siberian tigers, especially regarding how diet and health status influence microbial diversity. This study addresses this gap by investigating the gut microbiome diversity and composition of six captive-born Siberian tigers housed at the Baekdudaegan National Arboretum in South Korea, using 16S rRNA gene sequencing. The study aimed to examine how diet and health status influence microbial communities, providing baseline data for managing captive tigers. Alpha diversity analysis revealed significant variation in microbial richness and evenness, with Tigers 2 and 6 exhibiting the highest microbial diversity and Tiger 3 the lowest, likely due to its surgical history and limited diet. Beta diversity analysis showed distinct microbial community structures influenced by diet and health. Taxonomic profiling identified Firmicutes and Bacteroidota as the dominant phyla, with Clostridium sensu stricto more prevalent in healthier tigers, while Escherichia-Shigella and Proteobacteria were abundant in tigers with lower diversity, suggesting dysbiosis. Comparisons with other tiger species confirm that diet, health, and captivity significantly shape the gut microbiome. These findings highlight the need for personalized health management in captive environments.

Unveiling the Secrets: How Landscape Patterns Shape Habitat Quality in Northeast China Tiger and Leopard National Park

The Northeast China Tiger and Leopard National Park (NCTLNP) is a critical habitat for the endangered Amur tiger and Amur leopard, making it a global biodiversity hotspot. This study explores how changes in landscape patterns have influenced habitat quality in the park, aiming to develop strategies for enhancing biodiversity conservation and ensuring the park’s long-term sustainability. From 2012 to 2017, habitat quality in the NCTLNP experienced a significant decline; however, the launch of the national park pilot program in 2017 resulted in improvements, particularly in core protected areas, where habitat quality increased and landscape fragmentation decreased. These findings indicate that the national park initiative reduced the degradation of habitat quality. Key landscape metrics, especially the Shannon Diversity Index (SHDI), were found to significantly affect habitat quality. Additionally, the interaction between SHDI and landscape contagion (CONTAG) played a pivotal role in shaping habitat quality over time. Areas with high SHDI and low CONTAG showed declines in habitat quality, pointing to the need for focused conservation efforts. This study offers valuable insights for policymakers seeking to improve habitat quality through targeted landscape management practices.

External and internal driving forces of community and functional group stability in the forest mammal community

Conserving mammal community stability in forest ecosystems is an urgent challenge in the face of global biodiversity threats and complex trophic interaction. However, understanding of the stability of mammal communities and targeted functional groups is still limited, hindering adaptive strategy development. We collected 210 120 camera trap photos across 5897 km 2 within the Amur tiger ( Panthera tigris altaica ) range in China’s natural forests. We decomposed stability into compensatory effects, statistical-averaging effects and population stability. Using structural equation modelling, we explored the impact of external factors, species diversity and vertical effects on the stability of the community and of four functional groups. As external factors, primary productivity increased the stability of top predators, while precipitation had inconsistent effects. Horizontal diversity (richness and evenness) positively impacted community stability. However, the vertical structure of the community, including trophic-level richness and functional groups’ compensatory dynamics, were the largest drivers for maintaining community stability. Horizontal diversity within functional groups and the diversity or biomass of their food resources/consumers both influenced the stability of functional groups. Our results recognize the importance of conserving and even re-establishing vertical trophic structures in forest communities. Acknowledging multiple levels of stability, from functional groups to communities, is an indispensable step for effective conservation strategies.

Графовые алгоритмы для расчёта распределения следов амурского тигра на территории Приморского края

The paper analyzes the distribution of the Amur tiger (Panthera tigris altaica) tracks in the Primorsky Krai municipalities according to observations obtained during the one-time winter count organized by the Pacific Institute of Geography of the Far Eastern Branch of the Russian Academy of Sciences in 2005. This task is related to the need to calculate the number of animals based on the tracks of their vital activity. Based on the initial data we form a sample to analyze a set of tracks to identify intersection areas of various tiger habitats in Primorsky Krai. The map of Primorsky Krai municipalities was presented in the form of a planar graph to identify their intersections. A recurrent algorithm for identifying tiger clusters was developed using graph theory methods. According to them, the territory of Primorsky Krai is divided into northern, central, southern and southwestern zones with intersections. The districts of Primorsky Krai included in the designated zones are listed. The total number of tracks in intersecting adjacent zones was counted to identify possible tiger migrations in Primorsky Krai. A quantitative assessment of the degree of intersection of the selected zones by the number of tiger tracks is given. The proposed calculation scheme can be used to clarify and verify the results of modeling the spatial distribution and total population size of the Amur tiger.

Gut microbiota dynamics of adult and sub‐adult sika deer during reintroduction

AbstractPrey populations significantly influence the distribution of top predators. The sika deer (Cervus nippon), a key prey species for the Amur tiger in Northeast China, plays a critical role in the recovery and dispersal of Amur tiger populations. Reintroduction is a pivotal strategy for restoring prey populations, but it presents challenges, especially in terms of adaptation to the natural environment during the natural training process before animals are released. In this study, we sampled six adult and six sub‐adult sika deer and employed high‐throughput sequencing of the 16S ribosomal RNA gene to investigate changes in gut microbial diversity, composition, and function during natural training. The results showed that adult sika deer had higher gut microbiota diversity compared to sub‐adults. However, as natural training progressed, the gut microbial diversity in sub‐adults approached that of adults. Additionally, beneficial, fiber‐digesting bacteria associated with adaptation to the natural environment tended to increase during nature training in both adult and sub‐adult sika deer, while pathogenic bacteria tended to decrease. We also compared the metabolic function of the gut microbiota in adult and sub‐adult sika deer, which showed that the carbohydrate metabolic function of both adults and sub‐adults decreased significantly with natural training, declining more rapidly in sub‐adults. Conversely, the lipid metabolic function in sub‐adults increased significantly with natural training. Overall, a period of nature training is necessary before reintroducing animals to their natural habitats, and sub‐adult sika deer, in particular, exhibit greater adaptability to environmental changes as reflected by their gut microbiota dynamics. These findings offer valuable insights for the reintroduction of sika deer and other ungulates. We recommend incorporating natural training in reintroduction programs and prioritizing sub‐adult animals for reintroduction.

BILIARY DUCTAL PLATE MALFORMATION WITH SECONDARY PORTAL HYPERTENSION AND MULTIPLE ACQUIRED SHUNTS IN A LITTER OF AMUR TIGERS (PANTHERA TIGRIS ALTAICA).

Congenital abnormalities in tigers (Panthera tigris) are infrequently reported but have included ectrodactyly, cataracts, and vestibular disease. Primary hepatic disease has been documented in multiple nondomestic felid species but is considered uncommon in tigers. To the authors' knowledge, there are no previous reports of congenital abnormalities of the liver in tigers. In May 2022, two male Amur tiger cubs (Panthera tigris altaica) were born at a zoological institution via cesarean section to address dystocia, following the natural birth of a female cub. Between two and six months of age, all three cubs developed progressive lethargy, inappetence, and neurological signs consistent with hepatic encephalopathy, including obtundation and ataxia. In all three cases, serum biochemical values revealed progressive, marked elevations in hepatic enzyme levels with reduction in hepatic synthetic products (albumin, urea, cholesterol). Computed tomographic imaging showed a large cluster of aberrant tortuous vessels craniomedial to the left kidney in all three tigers, consistent with acquired extrahepatic portosystemic shunts. Histologic examination of the livers identified biliary ductal plate malformations. This report details the presentation, clinical findings, diagnoses, and therapeutic interventions attempted in three Amur tiger cubs with biliary ductal plate malformation and subsequent portal hypertension with multiple acquired portosystemic shunts, an unusual abnormality not previously reported in non-domestic felids.

Does presence of top predator improve forest birds' survival and diversity? An ecological case study assessing umbrella conservational impact of tiger using carrion

After hunting, predators tend to leave a large amount of carrion behind. It is widely reported that this resource is commonly used by various species in the ecosystem and is essential for the survival of scavengers, particularly in winter. Although recent studies are focused on mammals, little is known about how this works with facultative scavenger birds, which may lead to a serious underestimation of the key role that top predators such as the Amur tiger (Panthera tigris altaica) play in ecosystems. Here, we conducted a field feeding experiment to quantitatively evaluate the effects of Amur tiger on avian scavengers by simulating their predation residue. The results show that the Corvidae is the main bird species that consumes carrion, while woodpeckers and some insectivorous songbirds also benefit from the remains that Amur tiger leaves behind. We assumed that in winter, if the daily energy demand for the six main scavenger birds completely relied on the predation residues of Amur tiger separately, the prey remains of one Amur tiger could feed about 28 crows, 49 Azure-winged magpies, 61 Eurasian jays, 235 Eurasian nuthatches, 96 Great spotted woodpeckers, or 385 Willow tits. It means that the prey remains of top predators like Amur tiger may be an extremely important resource to avian scavengers and carrion could be a potential ecological indicator of Amur tiger keystone effect. This study provides experimental evidence from the field for the first time, and reveals the ecological mechanism of the role of keystone species of the Amur tiger, i.e., how to indirectly protect other animal groups in the forest ecosystem that have important ecological value for the biodiversity and the health of local forest vegetation through the protection of the Amur tiger.

Amur Tiger Individual Identification Based on the Improved InceptionResNetV2.

Accurate and intelligent identification of rare and endangered individuals of flagship wildlife species, such as Amur tiger (Panthera tigris altaica), is crucial for understanding population structure and distribution, thereby facilitating targeted conservation measures. However, many mathematical modeling methods, including deep learning models, often yield unsatisfactory results. This paper proposes an individual recognition method for Amur tigers based on an improved InceptionResNetV2 model. Initially, the YOLOv5 model is employed to automatically detect and segment facial, left stripe, and right stripe areas from images of 107 individual Amur tigers, achieving a high average classification accuracy of 97.3%. By introducing a dropout layer and a dual-attention mechanism, we enhance the InceptionResNetV2 model to better capture the stripe features of individual tigers at various granularities and reduce overfitting during training. Experimental results demonstrate that our model outperforms other classic models, offering optimal recognition accuracy and ideal loss changes. The average recognition accuracy for different body part features is 95.36%, with left stripes achieving a peak accuracy of 99.37%. These results highlight the model's excellent recognition capabilities. Our research provides a valuable and practical approach to the individual identification of rare and endangered animals, offering significant potential for improving conservation efforts.

The gut microbial differences between pre-released and wild red deer: Firmicutes abundance may affect wild adaptation after release.

Insufficient density of red deer has affected the stability of forest ecosystems and the recovery of large carnivores (represented by Amur tiger). Conservation translocations from captivity to the wild has become an important way to restore the red deer populations. However, the difference in gut microbes between pre-release and wild red deer may affect the feeding adaptability of red deer after release. In this study, we clarified the differences in gut microbes between pre-released and wild red deer and screened the key gut microbes of the red deer involved in feeding by using metagenomic sequencing and feeding analysis. The results showed that the microbial difference between pre-released and wild red deer was mainly related to Firmicutes represented by Eubacteriales and Clostridia, and Firmicutes abundance in pre-released red deer (68.23%) was significantly lower than that of wild red deer (74.91%, p < 0.05). The expression of microbial metabolic pathways in pre-released red deer were significantly lower than those in wild red deer (p < 0.05), including carbohydrate metabolism, amino acid metabolism, glycan biosynthesis and metabolism, etc. The combinations of Firmicutes were significantly positively correlated with the intake of plant fiber and carbohydrate (p < 0.05), and were key microbes to help red deer deal with wild plant resources. Additionally, the combinations of Firmicutes represented by Eubacteriales and Clostridia lacking in pre-released red deer contributed the most to expression of microbial metabolic pathways (importance > 1), showing a significant positive correlation (p < 0.05). This study indicates that high abundance of Firmicutes is an important guarantee for red deer to adapt to the wild feeding environment, which provides critical implications for the recovery of red deer populations and the protection of endangered ungulates.

Drivers of human–tiger conflict risk and potential mitigation approaches

AbstractHuman–wildlife conflict has become a significant challenge for conservationists, particularly in areas where endangered species, such as large carnivores, are recovering. If we fail to keep a balance between the interests of humans and wildlife, the human–wildlife conflict can have adverse outcomes. However, the drivers of human–wildlife conflict, and how to mitigate conflict, are often poorly understood. In this study, we aimed to explore the possible causes for and potential mitigating approaches to human–tiger conflict risks through spatiotemporal niche partitioning. Based on data from the reports of Amur tiger (Panthera tigris altaica) preying on cattle and camera trap detection data from 2014 to 2019 in Hunchun, Northeast China, we predicted Amur tiger occurrence and created risk maps of human–tiger potential encounters. We found that Amur tiger occurrence was positively driven by prey distribution and negatively by the distribution of pastures used for domestic cattle grazing. Livestock was increasingly predated in areas with limited preferred prey, that is, wild pig (Sus scrofa) and sika (Cervus nippon), and in closer proximity to cattle‐grazing land. On the basis of our models, we divided areas utilized by human and Amur tigers into low‐, medium‐, and high‐risk areas across multiple spatiotemporal scales. We suppose that multiple spatiotemporal scale niche partitioning management might effectively reduce the risk of human–tiger encounters, prompt harmonized coexistence between humans and tigers, and provide new solutions to other areas experiencing human–wildlife conflicts.

SARS-CoV-2 morbidity, treatment interventions, and vaccination practices in tigers (Panthera tigris ssp) in North American zoos.

Evaluate SARS-CoV-2 morbidity, mortality, clinical signs, treatment interventions, and vaccination practices in tigers under professional care. Amur (Panthera tigris altaica), Sumatran (Panthera tigris sumatrae), and Malayan (Panthera tigris jacksoni) tigers managed under the Tiger Species Survival Plan (SSP). A retrospective, voluntary online survey was sent to all North American zoos holding SSP tigers between January 2020 and June 2023. Responses were received from 55 of 108 institutions (51%) housing 162 tigers in total, and SARS-CoV-2 infection was diagnosed in 39 tigers from 15 institutions (20 Amur, 8 Sumatran, and 11 Malayan [1 to 18 years old; 17 males and 22 females]). This corresponds to a minimum study group infection incidence of 24% over 42 months. Clinical signs included dry cough (82%), inappetence (64%), lethargy (62%), nasal discharge (46%), wheezing (31%), wet cough (18%), and ocular discharge (15%). Most cases were characterized as mild (n = 22) or moderate (14). A single case was characterized as severe. Two cases were asymptomatic. Seventeen positive tigers had been vaccinated once (n = 8) or twice (9) for SARS-CoV-2 prior to infection. No deaths due to SARS-CoV-2 were reported in the study group. Treatment interventions included antibiotics (49%), NSAIDs (18%), antiemetics (15%), and fluids (13%). No treatments were administered in 19 of 39 cases (49%). Amongst participating institutions, 69% reported fully vaccinating tigers for SARS-CoV-2 (≥ 2 doses). Most SARS-CoV-2-infected tigers presented with mild to moderate clinical signs and recovered with limited to no treatment interventions. Asymptomatic SARS-CoV-2 infections can occur in tigers and may be underreported. Tigers vaccinated for SARS-CoV-2 remain susceptible to infection.

Design and Performance Evaluation of Network Intrusion Detection System Based on Deep Learning

Today’s internets are made up of nearly half million various networks. In any network connection, detecting attacks by their kinds is challenging task as various attacks may have several connections, their number vary from few to hundreds of network connections. In this paper, Design and Performance Evaluation of Network Intrusion Detection System Based on Deep Learning (NID-SPGAN-STO) is proposed. Initially, input data are collected by NSL-KDD dataset. Afterward, data are fed to preprocessing. In preprocessing, Distributed Set-Membership Fusion Filtering is used to remove redundant and biased records from input data. The pre-processed output is given to feature selection for selecting optimal features utilizing Piranha foraging Optimization Algorithm. Finally the selected features are transferred into the Semantic-Preserved Generative Adversarial Network (SPGAN) for detecting Network Intrusion, like DoS, Probe, R2L, U2R and Normal. Generally SPGAN doesn’t reveal some adoption of optimization techniques for computing optimal parameters for promising precise network intrusion detection. Hence Siberian Tiger Optimisation (STO) is used to enhance weight parameters of SPGAN. The proposed NID-SPGAN-STO method is implemented using Python. To detect network intrusion detection, performance metrics likes precision, sensitivity, FI-score, specificity, accuracy, RoC, computational time are considered. The NID-SPGAN-STO method attains 30.58%, 28.73% and 25.62%, higher precision, 20.48%, 24.73%, 29.32% higher specificity and 30.98%, 26.66% and 21.32% higher F-score, 26.78%, 34.47%, and 22.86% higher recall analysed, with existing techniques likes improved binary gray wolf optimizer with SVM for intrusion detection system in WSNs (NID-SVM-IDS), network intrusion detection system utilizing deep learning (NID-DNN), design with improvement of efficient network intrusion detection system utilizing ML methods (NID-IDS-ANN) respectively.

Efficient malicious node detection by multi-objective energy trust aware hybrid optimization based maximizing lifetime of wireless sensor networks

Wireless sensor network (WSN) collect and detect data in real time, but their battery life limits their lifetime. The CH selection process increases network overhead and reduces lifetime, but it considers node processing and energy limitations. To solve that problem this research methodology proposed Multi Objective Energy trust - Aware Optimal Clustering and Secure Routing (MOETAOCSR) protocol. At first, the trust factors such as direct and indirect factors are calculated. Thus, the calculated values are given as input to the SDLSTM to detect the malicious node and normal node. Here, the network deployment process is initially carried out and then the cluster is formed by HWF-FCM. From the clustered sensor nodes, the cluster head is selected using Golden Jackal Siberian Tiger Optimization (GJSTO) approach. Then, the selection of CH the paths are learned by using the Beta Distribution and Scaled Activation Function based Deep Elman Neural Network (BDSAF-DENN) and from the detected paths the optimal paths are selected using the White Shark Optimization (WSO). From the derived path sensed data securely transferred to the BS for further monitoring process using FPCCRSA. The proposed technique is implemented in a MATLAB platform, where its efficiency is assessed using key performance metrics including network lifetime, packet delivery ratio, and delay. Compared to existing models such as EAOCSR, RSA, and Homographic methods, the proposed technique achieves superior results. Specifically, it demonstrates a 0.95 improvement in throughput, 0.8 enhancement in encryption time, and a network lifetime of 7.4.

Detection of SARS-CoV-2 Delta Variant (B.1.617.2) in Domestic Dogs and Zoo Tigers in England and Jersey during 2021.

Reverse zoonotic transmission events of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been described since the start of the pandemic, and the World Organisation for Animal Health (WOAH) designated the detection of SARS-CoV-2 in animals a reportable disease. Eighteen domestic and zoo animals in Great Britain and Jersey were tested by APHA for SARS-CoV-2 during 2020-2023. One domestic cat (Felis catus), three domestic dogs (Canis lupus familiaris), and three Amur tigers (Panthera tigris altaica) from a zoo were confirmed positive during 2020-2021 and reported to the WOAH. All seven positive animals were linked with known SARS-CoV-2 positive human contacts. Characterisation of the SARS-CoV-2 variants by genome sequencing indicated that the cat was infected with an early SARS-CoV-2 lineage. The three dogs and three tigers were infected with the SARS-CoV-2 Delta variant of concern (B.1.617.2). The role of non-human species in the onward transmission and emergence of new variants of SARS-CoV-2 remain poorly defined. Continued surveillance of SARS-CoV-2 in relevant domestic and captive animal species with high levels of human contact is important to monitor transmission at the human-animal interface and to assess their role as potential animal reservoirs.

The genetic status and rescue measure for a geographically isolated population of Amur tigers

The Amur tiger is currently confronted with challenges of anthropogenic development, leading to its population becoming fragmented into two geographically isolated groups: smaller and larger ones. Small and isolated populations frequently face a greater extinction risk, yet the small tiger population’s genetic status and survival potential have not been assessed. Here, a total of 210 samples of suspected Amur tiger feces were collected from this small population, and the genetic background and population survival potentials were assessed by using 14 microsatellite loci. Our results demonstrated that the mean number of alleles in all loci was 3.7 and expected heterozygosity was 0.6, indicating a comparatively lower level of population genetic diversity compared to previously reported studies on other subspecies. The genetic estimates of effective population size (Ne) and the Ne/N ratio were merely 7.6 and 0.152, respectively, representing lower values in comparison to the Amur tiger population in Sikhote-Alin (the larger group). However, multiple methods have indicated the possibility of genetic divergence within our isolated population under study. Meanwhile, the maximum kinship recorded was 0.441, and the mean inbreeding coefficient stood at 0.0868, both of which are higher than those observed in other endangered species, such as the African lion and the grey wolf. Additionally, we have identified a significant risk of future extinction if the lethal equivalents were to reach 6.26, which is higher than that of other large carnivores. Further, our simulation results indicated that an increase in the number of breeding females would enhance the prospects of this population. In summary, our findings provide a critical theoretical basis for further bailout strategies concerning Amur tigers.

Isolation, genome analysis and comparison of a novel parainfluenza virus 5 from a Siberian tiger (Panthera tigris).

Paramyxoviruses are important pathogens affecting various animals, including mammals and humans. Parainfluenza virus 5 (PIV5)-a member of the family Paramyxoviridae-is a major threat to the health of mammals and humans. However, studies on terrestrial wild animals infected with PIV5 are scanty. In this study, we utilized reverse transcription PCR to detect PIV5 infection in the visceral organ tissues of a Siberian tiger (Panthera tigris ssp. altaica) with vomiting, diarrhea, and dyspnea before its death. A novel PIV5 (named SR strain) with a slowly progressive cytopathic effect was isolated in Vero cells and validated using a transmission electron microscope. Full-length sequencing and analysis revealed that the whole genome of the PIV5 SR strain contained 15,246 nucleotides (nt) and seven non-overlapping genes (3'-N-V/P-M-F-SH-HN-L-5') encoding eight proteins. Phylogenetic analysis of three PIV5 strains identified in the same zoo confirmed that PIV5 strains SR and ZJQ-221 shared the closest genetic relationship as they were clustered in the same branch, while the recently found Siberian tiger strain SZ2 kept a certain distance and formed a relatively unique branch. Furthermore, mutations of nt and amino acids (aa) between strains ZJQ-221, SR, and SZ2 were identified. In summary, we report the identification and genomic characterization of a novel PIV5 strain SR isolated in a Siberian tiger, which may help future research on interspecific transmission mechanisms.

A Serial Multi-Scale Feature Fusion and Enhancement Network for Amur Tiger Re-Identification.

The Amur tiger is an important endangered species in the world, and its re-identification (re-ID) plays an important role in regional biodiversity assessment and wildlife resource statistics. This paper focuses on the task of Amur tiger re-ID based on visible light images from screenshots of surveillance videos or camera traps, aiming to solve the problem of low accuracy caused by camera perspective, noisy background noise, changes in motion posture, and deformation of Amur tiger body patterns during the re-ID process. To overcome this challenge, we propose a serial multi-scale feature fusion and enhancement re-ID network of Amur tiger for this task, in which global and local branches are constructed. Specifically, we design a global inverted pyramid multi-scale feature fusion method in the global branch to effectively fuse multi-scale global features and achieve high-level, fine-grained, and deep semantic feature preservation. We also design a local dual-domain attention feature enhancement method in the local branch, further enhancing local feature extraction and fusion by dividing local feature blocks. Based on the above model structure, we evaluated the effectiveness and feasibility of the model on the public dataset of the Amur Tiger Re-identification in the Wild (ATRW), and achieved good results on mAP, Rank-1, and Rank-5, demonstrating a certain competitiveness. In addition, since our proposed model does not require the introduction of additional expensive annotation information and does not incorporate other pre-training modules, it has important advantages such as strong transferability and simple training.

Game Analysis of Financial Regulation in International Financial Crisis using Multi-view Graph Convolutional Network

The concept of "game analysis" generally refers to the study and assessment of video games, frequently from the viewpoints of player experience, story, mechanics, design, and other relevant variables. It can be used for a variety of games, such as sports, board, card, and video games. A sudden drop in the value of assets or financial institutions is referred to as a financial crisis. It frequently causes the regular operation of financial markets to be interrupted and may have negative impacts on the economy as a whole. In this manuscript, Game Analysis of Financial Regulation in International Financial Crisis using Multi-view Graph Convolutional Network (GA-FR-IFC-MGCN). The proposed method comprises of four phases: dataset, pre-processing, feature selection, classification. Initially, the data is taken from Analcat dataset. Then, Federated Neural Collaborative Filtering (FNCF) method is used to enhancing the networks data. For feature selection phase, the ideal features are chosen by Siberian Tiger Optimization (STO). After, the Multi-view graph convolutional network (MGCN) method is used to classifying international financial crisis as bankruptcy and Non-bankruptcy. In general, MGCN does not express some adaption of optimization strategies for determining optimal parameters to promise exact classification of International Financial Crisis. Therefore, Harbor Seal Whiskers Optimization Algorithm is proposed to enhance weight parameter of MGCN classifier, which precisely predicts the International Financial Crisis. The proposed technique is executed and efficiency of GA-FR-IFC-MGCN depend classification framework is assessed by support of numerous performances evaluating metrics likes accuracy, recall, precision, FI-score, specificity. Finally the performance of proposed GA-FR-IFC-MGCN methods provides 25.32%, 29.30% and 27.32% higher accuracy, 22.41%, 29.30% and 24.31% higher specificity and 25.71%, 27.12% and 25.31% higher precision though analyzed with existing method likes game analysis of financial supervision in international financial crisis(GA-FS-IFC), performance evaluation of clustering techniques for financial crisis prediction(PE-CT-FC) and modified grey wolf optimizer with sparse auto-encoder for financial crisis prediction in small marginal firms (MGWO-SA-FCP) respectively.