Modal Number Research Articles

Closed-form eigensolutions and exact complex mode superposition method for non-proportionally rate-independent damped systems

PurposeThe main objectives of this paper are to develop a novel perturbation method (PM) to solve the complex-orthogonal eigenvalue problem and further propose an exact complex mode superposition method (CMSM) for the non-proportionally rate-independent damped systems.Design/methodology/approachA novel PM is developed to solve the eigenvalue problem. The PM reduced the N-order generalized complex eigenvalue problem into a set of n algebraic equations by the perturbation theory. The convergence and accuracy of the PM are demonstrated by several numerical examples. Further, an exact CMSM is presented. The influences of the imaginary part response of the modal coordinate and the off-diagonal elements of the damping matrix as well as the modal truncation on the solution by CMSM are discussed to illustrate the effectiveness of the developed CMSM.FindingsThe eigenvalues obtained by PM would converge to the exact ones with the increase of the modal numbers. For seismic response, the influence of the imaginary part solutions of the modal coordinate would increase with the increase of the coupling factor. The contribution of higher modes to acceleration response is greater than that to the displacement. The cumulative mode contribution coefficient of acceleration is developed to estimate the numbers of the complex modes for the acceleration seismic response by the CMSM.Originality/value1. An eigenvalue perturbation method for a rate-independent damped system is proposed. 2. PM is carried out by the real mode and accomplishes the reduction of the matrix. 3. CMSM is established for rate-independent damped systems. 4. CMSM considers the effect of imaginary part solutions of the modal coordinate. 5. Modal truncation index is developed to estimate the complex mode number for CMSM.

Cytogenetic and <i>ISSR</i>-Markers Polymorphism in the Population of Local Ukrainian Lebedyn Cows

Preservation of the fund of local breeds of agricultural animals, which are breeding material for the creation of new ones and the improvement of existing ones, meets the requirements of the FAO - the protection of biological diversity. The study of the genetic structure of cows of the local Lebedyn breed, which was bred in Ukraine, with the use of cytogenetic and molecular genetic methods, is aimed at establishing information about the structure of the gene pool of these animals and the uniqueness of their genotype. Cytogenetic monitoring showed that the modal number of chromosomes corresponded to the species norm and was 2n=60, no constitutional abnormalities in the form of Robertsonian translocations were detected, the average frequency of genomic disorders (aneuploidy) was 10,2±2,10%, polyploidy was not manifested. structural disorders (chromosomal breaks) accounted for 3,1±1,88% and asynchronous separation of the centromeric regions of chromosomes – 0,8±0,10%. The average share of cytogenetic parameters of cells was determined: lymphocytes with micronucleus – 3,6±0,61‰, binucleus lymphocytes – 4,3±0,97‰ and mitotic index – 3,7±1,20‰. An analysis of the genetic structure of the local, small-numbered Lebedyn cattle breed of Ukraine was carried out using 8 ISSR-systems. All 8 microsatellite primers showed high efficiency. ISSR labeling revealed 88 amplified DNA fragments, of which only 18 were polymorphic. The total share of polymorphic loci was 25,45%. 11 species-specific loci for (ACC)6G, 5 loci for (CTC)6C, 10 for (GAG)6C, 7 for (GA)6CC, 10 for (AG)8CG, 9 for (AG)8CA, 13 for (GA)9C and 14 for (AG)9C. It was established that the studied animals were characterized by karyotype stability, reduced sensitivity to mutagenic factors of various nature, absence of inbreeding depression and reproductive isolation.

Occurrence of high hyperdiploid karyotypes in childhood Acute Lymphoblastic Leukemia

Abstract Introduction/Objective High hyperdiploidy is defined as the non-random gain of chromosomes, increasing the modal chromosome number from 46 to between 51 and 65 or 67. This condition is the most common finding in childhood acute lymphoblastic leukemia, with a good outcome. It is generally characterized by the gain of chromosomes, typically X, 4, 6, 10, 14, 17, 18, and 21. The objective of this study is to determine the frequency of high hyperdiploidy in childhood ALL. Methods/Case Report Cytogenetic results of 435 patients, reported between October 2020 and September 2022 were reviewed retrospectively. All individuals were suspected for ALL between ages 1-15 years. Chromosomal analysis was performed in the Cytogenetics Lab of the Indus hospital and health network. Fluorescent in-situ hybridization (FISH) analysis were also carried out with probes for co-relating the gain of chromosomes. Results (if a Case Study enter NA) A total of 435 individuals were successfully karyotyped, 82 karyotypes showed hyperploidy without any additional abnormality, 213 patients showed hyperploidy along with additional structural aberrations, and 143 individuals showed normal karyotype. Among all the hyperploid karyotypes, chromosomes X, 4, 6, 10, 14, 17, 18, 21 were all gained in approximately 70% of the cases. Whereas, chromosome 21 was gained in 100% of all cases. FISH results also showed the gain of signals for particular probes including chromosomes 8, 9, 11, 12, 21 and 22. Conclusion In summary, this study leads to the fact that high hyperdiploidy is the most common abnormality in childhood acute lymphoblastic leukemia. It is assured that the occurrence of constituent trisomies of certain chromosomes is linked with the prognosis of the disease and also helps in determining the differences in treatment of the disease. Furthermore, correlation of karyotypes with the FISH results have also played a vital role in increasing the accuracy of results in this study.

Predicting e-commerce product prices through the integration of variational mode decomposition and deep neural networks.

Product prices frequently manifest nonlinear and nonstationary time-series attributes, indicating potential variations in their behavioral patterns over time. Conventional linear models may fall short in adequately capturing these intricate properties. In addressing this, the present study leverages the adaptive and non-recursive attributes of the Variational Mode Decomposition (VMD) methodology. It employs VMD to dissect the intricate time series into multiple Intrinsic Mode Functions (IMF). Subsequently, a method rooted in the minimum fuzzy entropy criterion is introduced for determining the optimal modal number (K) in the VMD decomposition process. This method effectively mitigates issues related to modal confusion and endpoint effects, thereby enhancing the decomposition efficacy of VMD. In the subsequent phase, deep neural networks (DNN) are harnessed to forecast the identified modes, with the cumulative modal predictions yielding the ultimate e-commerce product price prognostications. The predictive efficacy of the proposed Variational Mode Decomposition-deep neural network (VMD-DNN) decomposition model is assessed on three public datasets, wherein the mean absolute percentage error (MAPE) on the E-commerce Price Prediction Dataset and Online Retail Dataset is notably low at 0.6578 and 0.5414, respectively. This corresponds to a remarkable error reduction rate of 66.5% and 70.4%. Moreover, the VMD-DNN decomposition model excels in predicting e-commerce product prices through DNN, thereby amplifying the VMD decomposition capability by 4%. The VMD-DNN model attains superior results in terms of directional symmetry, boasting the highest Directional Symmetry (DS) score of 86.25. Notably, the forecasted trends across diverse price ranges closely mirror the actual trends.

A general method for mode decomposition on additive mixture: Generalized Variational Mode Decomposition and its sequentialization

Variational Mode Decomposition(VMD) method was proposed to separate non-stationary signal mixture by solving a optimization problem. This method is powerful and can reconstruct the signal components precisely when they are orthogonal(or quasi-orthogonal) in frequency domain. The crucial problem for VMD is that it requires the information of modal number before the decomposition. Also its applications are limited in 1D and 2D signal processing fields, of narrow scope.In this paper, by inheriting and developing the core idea of VMD, we build a general form for this method and extend it to the modal decomposition for common additive mixture, not only limited in signal processing. To overcome the obstacle of modal number, we sequentialize the generalized VMD method, such that the modes can be extracted one by one, without knowing the modal number a priori. After the generalization and sequentialization for the VMD, we apply them in different fields of additive case, such as texture segmentation, Gaussian Mixture Model(GMM), clustering, etc. From the experiments, we conclude that the generalized and sequentialized VMD methods can solve variety classical problems from the view of modal decomposition, which implies that our methods have higher generality and wider applicability. A raw Matlab code for this algorithm is shown in https://github.com/changwangke/SGVMD_additive_Clustering/blob/main/SGVMD_clustering.m.

Higher-Dimensional Communications Using Multimode Fibers and Compact Components to Enable a Dense Set of Communicating Channels

Higher-dimensional communications are of interest for multiple reasons, including increasing the classical transmission capacity and, more recently, the quantum state transfer through fibers using the many modes within the fiber. For quantum communications, this enables an increase in the number of bits per photon, increasing quantum fidelity, increasing error thresholds and enabling hyperentanglement transfer, among other possibilities. A high-dimensional quantum state transfer can be transported through multimode fiber using the many modes available. However, this transfer of information through multimode optical fiber is limited by attenuation and mode coupling among the various spatial and polarization modes. Here, we consider how this mode coupling impacts the transfer process. We consider the fiber’s modal properties, including orbital angular momentum, modal group numbers, and principal modes. We also investigate and propose input and output optical components, as well as fiber properties, which better mitigate the deleterious effects of mode coupling. We use the WKB approximation to the scaler wave equation as a guidance to quantify this coupling and then implement corrections to this approximation using exact solutions to the scaler wave equation. We consider methods to circumvent this mode coupling using optical fiber designs, holographic optical components and devices that are commercially available today. Some of these components, such as the holographic gratings and lenses, could be implemented using flat optics.

Using enhanced Variational Modal Decomposition and Dung Beetle Optimization Algorithm optimization-kernel Extreme Learning Machine model to forecast short-term wind power

With the widespread use of clean energy, the forecasting of wind power has become increasingly significant. Extracting time series from sophisticated wind power data and thus improving the prediction accuracy of wind power generation has become the key to short-term forecasting. This paper proposes a Kernel Extreme Learning Machine (KELM) prediction model based on Crested Porcupine Optimizer (CPO), Variational Modal Decomposition (VMD) with Improved Dung Beetle Optimization Algorithm (QHDBO). Firstly, by analyzing the correlation between the variables in the wind power data, the CPO algorithm is used to optimize the modal decomposition number and the penalty parameter of the VMD and extract the time-series information of the wind power series, and smooth it to obtain a number of sub-sequences with strong regularity. Then, the KELM prediction model is constructed for different subsequences, and the kernel parameters and regularization coefficients of KELM are optimized using the QHDBO algorithm. Finally, the predicted values of different subsequences are reconstructed to obtain the final prediction results. The simulation results show that the CVMD-QHDBO-KELM model can effectively improve the wind power prediction performance, and the MAPE values are all below 9 %, and most of the RE values are below 10 %.

Dynamic property evaluation of pipeline clamp based on analyzing the propagation characteristics of flexural wave in pipeline

The external clamp of hydraulic pipeline plays an important role in strengthening pipeline stiffness and improving vibration attenuation ability. In this study, wave propagation method is proposed to evaluate the translational and rotational stiffness and their loss factors of the clamp by analyzing the flexural wave propagation characteristics of pipeline. In order to validate the measured dynamic properties, experimental modal analysis was performed on the two-end elastically-supported pipeline. By modelling the pipeline with translational and rotational edge restraints, the analytical modal frequency parameters, wave numbers, and waveform coefficients were obtained. By comparing of the first-order flexural mode frequencies between experiment and analysis, the dynamic stiffness predicted by the wave propagation method was validated. The effects of the magnitude of torque, direction, clamping torque cycle, and clamp size on the complex dynamic properties of pipeline clamp were investigated. The proposed wave propagation method allows non-destructive continuous monitoring of a clamp stiffness, provides additional information about the vibration attenuation feature. It has advantages in clamp applications and is an effective methodology for measuring the dynamic properties of viscoelastic materials.

Comparative Analysis of Structural Damage Identification Methods Based on Iterative Reweighted L1/2 Regularization and Three Optimization Functions

Previous vibration-based damage detection studies mostly focus on developing a more sensitive optimization function to promote the effectiveness of damage identification. However, a few studies have conducted comparative analyses on the detection performance of different optimization functions. In the study, changes in the frequency and mode shape are applied as the inputs to different optimization functions for damage identification. Three optimization functions are established using the frequency residuals, the combinations of frequency and mode shape residuals, and the modal flexibility residuals, respectively. Considering the sparsity of damage element distribution, an iterative reweighted [Formula: see text] [Formula: see text] regularization is added as a norm penalty to the optimization function. A numerical model and an experimental example are applied to assess the performance of distinct optimization functions. The results show that the increase in modal data number cannot significantly improve the detection accuracy when the number meets the basic requirements for identifying damage. The detection error of the optimization function established by combining the frequency and mode shape residuals is 6.65% and 5.18% using the first four and fourteen-order noisy modal data, respectively. Furthermore, the optimization function constructed using the modal flexibility residuals requires more less modal data to identify damage than the other two functions.

Single channel blind source separation of rolling bearing compound faults based on self-learning sparse decomposition and feature mode decomposition

Feature mode decomposition (FMD) has advantages over the other newer time-frequency methods such as ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) in single channel blind source separation (SCBSS). However, FMD has the defect of needing to determine the precise number of fault sources manually. To solve the above defect of FMD, an adaptive method for determining the number of fault sources based on the shift invariant sparse code (SISC) is proposed. SISC was used to train a set of basis functions from the single channel signal, and the corresponding potential components were reconstructed firstly. Subsequently, the structural similarity of these potential components was used for clustering, and each of the obtained clustering signals represented one kind of fault. Then the number of clustering was determined by minimizing the structural correlation among the clustering signals. It was considered that the source separation had achieved the best effect when the structural difference among the clusters was the largest, and the number of clustering at this time was used as the optimal estimated value, which was used as the modal inputs number of FMD calculation model to realize SCBSS of rolling bearing. Simulation and experimental analysis were carried out to verify the effectiveness of the proposed method, and its superiority was also verified through comparison.

Investigation of fluid added mass matrix during hydroelastic slamming of wedges

The investigation of the fluid added mass (FAM) matrix during the water entry of an elastic structure is crucial for understanding the mechanism of hydroelastic slamming, as it characterizes the fluid–structural interaction process. In this paper, we excavate a model for directly estimating the FAM matrix during hydroelastic slamming and employ this model to study the limitations and optimized values of the relaxation factor for a partitioned coupling solver. Our simulation of hydroelastic slamming couples the Wagner theory with the modal superposition method (MSM), and the FAM matrix is computed using a monolithic coupling scheme. We conduct a series of parametric studies to analyze how the modal number, hydroelasticity, deadrise angle, and structural boundary condition influence the eigenvalues of the FAM matrix. Based on these studies, we then propose an analytical model to directly express the eigenvalues of the FAM matrix, demonstrating their linear relationship with the wetted ratio. Furthermore, we apply this analytical model to analyze the relaxation factor in the partitioned coupling scheme, theoretically explaining its strong connection to the FAM effect. The limitations and optimized values of the relaxation factor are theoretically presented, and these results are verified through our numerical tests.

Detection of Modal Numbers From Field Configurations in Rectangular Waveguides via Machine Learning Models of Noisy Datasets

Detection of Modal Numbers From Field Configurations in Rectangular Waveguides via Machine Learning Models of Noisy Datasets

Hemipenial morphology of whiptail lizards Glaucomastix abaetensis and Glaucomastix littoralis , with comments on the genus Ameivula (Teiidae: Teiinae).

Hemipenes are important structures for the systematics of Squamata, and may assist in the diagnosis of closely related taxa. Only one of the species of Glaucomastix (G. venetacauda) had its hemipenial morphology described in literature so far. Here we analyze and describe for the first time the hemipenes of seven specimens of G. abaetensis and 20 specimens of G. littoralis from the reptile collection of Museu Nacional, Universidade Federal do Rio de Janeiro. In both species the hemipenes are bilobed with a forked sulcus spermaticus in a centripetal orientation and present laminar ornamentations on the hemipenial body and paired awns on the apical region of the lobes. The two species differed from each other only in the modal number of proximal laminae. The main differences in hemipenial morphology between Glaucomastix and its sister genus Ameivula are the presence of laminae in the hemipenial body (absent in Ameivula) and the absence of digitiform papillae on the apical lobular region (present in Ameivula). We expect that our data can be used as an additional tool to diagnose species within the genus Glaucomastix/Ameivula.

Construction of a digital library of vocal music resources based on second-order data decomposition algorithm

Abstract In this paper, in order to solve the modal aliasing problem of the EMD decomposition algorithm and EEMD decomposition algorithm and optimize the vocal audio data decomposition on the basis of the adaptive VMD algorithm, the EEMD-VMD second-order data decomposition algorithm is proposed to decompose the digitized time series of vocal music resources, and to update the construction of the digital library of vocal music resources. Combined with the decomposition steps of the second-order data decomposition algorithm in the vocal resources digitized library, the overall framework of the vocal resources digitized library is designed and constructed with the main line of vocal resource types and the secondary line of content categories. Design the experimental environment, preprocess the vocal audio signal features, explore the modal number K value size of the EEMD-VMD second-order data decomposition algorithm, analyze the vocal audio denoising performance of the algorithm, and compare the correlation coefficients of the IMF components of the decomposition algorithms with the original audio signals. Explore the second-order data decomposition algorithm’s emotional classification of vocal resources and the performance of vocal signal enhancement, add noise sources, and use subjective and objective evaluation methods to assess the quality of vocal PESQ and STOI after decomposition processing. The EEMD-VMD second-order data decomposition algorithm performs the most prominently in street noise environments. The enhancement results in the case of signal-to-noise ratios of -5, -10, and -15 are 3.59, respectively, 4.36, 4.29, and the mean value of the enhancement performance reaches 4.08. The second-order data decomposition algorithm’s precise processing of vocal resources provides better quality digital resources for the construction of a digital library of vocal resources.

Treatment of posttraumatic stress disorder with prolonged exposure for primary care (PE-PC): Effectiveness and patient and therapist factors related to symptom change and retention.

Prolonged exposure (PE) is a first-line treatment for posttraumatic stress disorder (PTSD) available in specialty mental health. PE for primary care (PE-PC) is a brief version of PE adapted for primary care mental health integration, composed of four-eight, 30-min sessions. Using retrospective data of PE-PC training cases from 155 Veterans Health Administration (VHA) providers in 99 VHA clinics who participated in a 4- to 6-month PE-PC training and consultation program, we examined patients' PTSD and depression severity across sessions via mixed effects multilevel linear modeling. Additionally, hierarchical logistic regression analysis was conducted to assess predictors of treatment dropout. Among 737 veterans, medium-to-large reductions in PTSD (intent-to-treat, Cohen's d = 0.63; completers, Cohen's d = 0.79) and small-to-medium reductions in depression (intent-to-treat, Cohen's d = 0.40; completers, Cohen's d = 0.51) were observed. The modal number of PE-PC sessions was five (SD = 1.98). Providers previously trained in both PE and cognitive processing therapy (CPT) were more likely than providers who were not trained in either PE or CPT to have veterans complete PE-PC (OR = 1.54). Veterans with military sexual trauma were less likely to complete PE-PC than veterans with combat trauma (OR = 0.42). Asian American and Pacific Islander veterans were more likely than White veterans to complete treatment (OR = 2.93). Older veterans were more likely than younger veterans to complete treatment (OR = 1.11). (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Incipient speciation in allopatric Etheostoma rupestre (Percidae: Etheostomatinae) lineages, with the description of three new subspecies.

In recent years, new species descriptions for the North American darters have proliferated. Most species concepts accepted by contemporary ichthyologists require that a valid species be both monophyletic and diagnoseable, yet many lineages exhibit modal or range differences in morphological characteristics without individuals being diagnosable. Such scenarios present difficulties with regards to proper taxonomic recognition of divergent lineages and often prohibit appropriate conservation action. Following the example of recent authors, we provide meristic, geometric morphometric, and pigmentation data to support the recognition of three subspecies of Etheostoma rupestre, a species endemic to the Mobile Basin. These morphological data cohere with previous genetic work for E. rupestre. The nominate subspecies Etheostoma rupetsre rupestre (Tsais Rock Darter) is endemic to the Tombigbee River and Black Warrior River watersheds in Alabama and Mississippi and is characterized by having lower numbers of lateral blotches, lower range and mean of lateral line scales, lower modal number of scales above the lateral line, and lower degrees of nape squamation than other subspecies. Etheostoma rupestre piersoni (Shamrock Darter), ssp. nov., is endemic to the Cahaba and Alabama River Watersheds in Alabama and is characterized by intermediate counts of lateral blotches and higher scale counts and nape squamation than E. r. rupestre. Etheostoma rupestre uphapeense (Jade Darter), ssp. nov., is restricted to several small, disjunct populations in the Coosa and Tallapoosa watersheds in Alabama, Georgia, and Tennessee. Etheostoma r. uphapeense is characterized by having a higher mean number of lateral blotches than both other subspecies and higher scale counts than E. r. rupestre. While E. r. rupestre and E. r. piersoni are widespread and abundant within their respective ranges, E. r. uphapeense has a disjunct range and is often uncommon where it occurs. Etheostoma r. uphapeense should be monitored where it occurs to discern population trends.

Selective Excitation of Waveguide Modes Using a Horizontal Array of Monopoles

The spatial structure of a far-field acoustic wavefield created by a sparse horizontal array of nondirectional emitters is considered. It is shown that the array can selectively excite certain modes of the acoustic wavefield. The number of an excited mode depends on the angle with respect to the array axis. The results of numerical simulation are presented for two models of a waveguide and for an array mounted at the ocean bottom. It is shown that the efficiency of single mode excitation grows with an increase in the modal number. The angular dependence of the excited modal spectrum is studied. It is shown that this dependence consists of several branches corresponding to the most excited modes

967 Scrubbing Up: A Drain on Sustainability

Abstract Aim Surgical scrub is a vital step in infection control prior to operating. Hospitals typically opt for a traditional tap or a sensor-operated tap to control their water source. This project compared the water usage and efficiency per surgical scrub for the two different taps. Method Theatre system was reviewed to determine total number of staff members who scrubbed in for each operation, over a one-month period within one health board. Average scrubbing time and quantity of water used per scrub was calculated by observing multiple different staff members. Results During September 2022, 6076 staff members scrubbed in for theatres. The average time spent handwashing was 2 minutes and 26 seconds, however only 47 seconds worth of running water was used to wash their hands. Sites using traditional taps used approximately 18.6L of water whilst sensor-operated taps used 13.2L per surgical scrub. This equated to 110,752 litres of water used over the month solely for scrubbing up. Sensor-operated taps would run for 63 seconds when activated with the modal number of times sensors were activated 3. Therefore, traditional taps were more efficient with 32% of running water used for surgical scrub compared to 25% for sensor-operated taps. Conclusions Sensor-operated taps used less water per surgical scrub; however, the operating time of the taps reduced its efficiency. Coordinating scrubbing up and ‘sharing’ one tap or adjusting the sensor taps operating time are simple step to minimise water wastage. Furthermore, the use of ‘waterless scrub’ solution is a viable option whilst also minimising infection risk.

A hybrid model of modal decomposition and gated recurrent units for short-term load forecasting.

Electrical load forecasting is important to ensuring power systems are operated both economically and safely. However, accurately forecasting load is difficult because of variability and frequency aliasing. To eliminate frequency aliasing, some methods set parameters that depend on experiences. The present study proposes an adaptive hybrid model of modal decomposition and gated recurrent units (GRU) to reduce frequency aliasing and series randomness. This model uses average sample entropy and mutual correlation to jointly determine the modal number in the decomposition. Random adjustment parameters were introduced to the Adam algorithm to improve training speed. To assess the applicability and accuracy of the proposed hybrid model, it was compared with some state of the art forecasting methods. The results, which were validated by actual data sets from Shaanxi province, China, show that the proposed model had a higher accuracy and better reliability compared to the other forecasting methods.

Development and characterization of a spleen cell line from yellowfin seabream Acanthopagrus latus and its susceptibility to Mandarinfish ranavirus.

Yellowfin seabream (Acanthopagrus latus) is one of the most commercially important marine fish in China. In this study, a new continuous cell line, named ALS cells, was developed from the spleen tissue of A. latus. The cell line was maintained in Dulbecco's modified Eagle medium/Nutrient Mixture F-12 Ham (DMEM/F-12) supplemented with 10% fetal bovine serum (FBS) and successfully cultured up to 50 passages. The cell line was authenticated by amplifying and sequencing mitochondrial cytochrome C oxidase subunit-I (coi-I) gene. The ALS cell line had the maximum growth rate in DMEM/F-12 medium containing 20% FBS at 27°C. Chromosome number analysis showed that the ALS cells have a modal diploid chromosome number of 34. The ALS cell line was transfected with the pEGFP-N1 plasmid, and green fluorescence was observed. The ALS cell line was used for testing Mandarinfish ranavirus (MRV) susceptibility, and the cytopathic effects in the cell line were observed at 4 days post-infection (dpi). Furthermore, the susceptibility of the ALS cell line to MRV and the levels of MRV mRNA and viral loads were found to be significantly increased at 1-7 dpi. This study revealed that the ALS cell line could be useful for molecular, virological, and biotechnological studies on yellowfin seabream.