Frame Length Research Articles

Characterization and regulatory analysis of betaine homocysteine S-methyltransferase gene 1 (BHMT1) in mud crab: A gene responsive to salinity and feeding behavior

Betaine homocysteine S-methyltransferase gene 1 (BHMT1) encoded betaine homocysteine S-methyltransferase (BHMT) catalyzes the homocysteine-to-methionine reaction using betaine as a methyl donor. Previously, we found that BHMT was lost in the genome of the insect clade of arthropods, but was highly expressed in the mandibular organ (MO) of the mud crab Scylla paramamosain (Sp). To further explore its significance, we performed a primary regulatory analysis of BHMT in mud crabs. The open reading frame (ORF) length of Sp-BHMT1 was 1203 bp, encoding 400 amino acids. Sequence alignment revealed that BHMT1 was highly conserved in different animals, and its identity was higher in more closely related species. Sp-BHMT1 had the highest expression in the MO of both sexes, while its expression in the MO was 1.6-fold higher in males than in females; similar results were also found in the cerebral ganglion, hepatopancreas, and thoracic ganglia tissues. During larval development, Sp-BHMT1 was weakly expressed on most days but was significantly elevated on the first day of the Zoea 2nd (Z2) and Z3 stages. Sp-BHMT1 exhibited the highest expression at a salinity of 10 ‰ and the lowest at a salinity of 30 ‰. With decreasing salinity, the expression of Sp-BHMT1 increased significantly at 6 h and then returned to baseline at 8 h. After starvation treatment, the expression of Sp-BHMT1 was significantly upregulated compared to that in the feed group at all examined time points, with a peak expression at 18:00 on the third day in the starvation group. Krüppel homolog 1 (Kr-h1), a methyl farnesoate (MF) signal gene, could increase Sp-BHMT1 expression under low salinity and starvation, suggesting that a “salinity/starvation→BHMT1 → MF biosynthesis” regulatory axis might exist in crabs. This study provides valuable insights into the functional study of Sp-BHMT1 and MF biosynthetic regulation.

Blind Recognition of Frame Synchronization Based on Deep Learning.

In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques. By incorporating a scaling factor, we generate RGB images. Based on the matching radius, frame length, and frame synchronization code, RGB images with distinct stripe features are classified as positive samples for each category, while the remaining images are classified as negative samples. Finally, the neural network is trained on these sets to classify test data effectively. Simulation results demonstrate that the proposed algorithm achieves a 100% probability in frame recognition when BER is below 0.2. Even with a BER of 0.25, the recognition probability remains above 90%, which exhibits a performance improvement of over 60% compared with traditional algorithms. This work addresses the shortcomings of existing methods under high error conditions, and the idea of converting sequences into RGB images also provides a reliable solution for frame synchronization in challenging communication environments.

Parallel Implementation of the CCSDS Turbo Decoder on GPU

This paper presents a software turbo decoder on graphics processing units (GPU). Unlike previous works, the proposed decoding architecture for turbo codes mainly focuses on the Consultative Committee for Space Data Systems (CCSDS) standard. However, the information frame lengths of the CCSDS turbo codes are not suitable for flexible sub-frame parallelism design. To mitigate this issue, we propose a padding method that inserts several bits before the information frame header. To obtain low-latency performance and high resource utilization, two-level intra-frame parallelisms and an efficient data structure are considered. The presented Max-Log-Map decoder can be adopted to decode the Long Term Evolution (LTE) turbo codes with only small modifications. The proposed CCSDS turbo decoder at 10 iterations on NVIDIA RTX3070 achieves about 150 Mbps and 50 Mbps throughputs for the code rates 1/6 and 1/2, respectively.

The potential role of galectin-4 in protecting the intestinal barrier in the lined seahorse Hippocampus erectus

Galectin-4 is a prominent antimicrobial peptide primarily expressed in the gastrointestinal tract of animals. It plays crucial roles in antimicrobial defense and in regulating the repair of intestinal epithelial cells. Given the unique immune system in seahorses, which are known for male pregnancy, the function of galectin-4 in their intestinal tract, which lack gut-associated lymphoid tissues, remains unknown. In this study, we identified a galectin-4 gene (HeGal-4) in the lined seahorse (Hippocampus erectus). The sequence length of the open reading frame (ORF) was 1041 bp, encoding 346 amino acids. The mRNA expression of HeGal-4 in the intestine was significantly higher than that in other internal organs. However, the synthesized peptide fragment (HeGal-4(302–315)) from the functional domain of HeGal-4 only showed moderate inhibitory effects against Escherichia coli, Klebsiella pneumoniae, and Micrococcus luteus. Interestingly, in situ hybridization showed that HeGal-4 was predominantly expressed in seahorse intestinal epithelial cells, while genes associated with galectin-4 in the repair of intestinal epithelium, such as β-catenins, were highly expressed in their intestines. Therefore, our results suggest that HeGal-4 may be crucial for regulating the repair of intestinal epithelial cells in seahorse intestinal epithelial cells, and that it possesses significant potential for the prevention and control of intestinal diseases in seahorse aquaculture.

Accelerable adaptive cepstrum and L2-Dual Net for acoustic emission-based quality monitoring in laser shock peening

Acoustic emission monitoring in laser shock peening facilitates real-time detection of potential quality issues arising from variations in industrial parameters, enabling iterative optimization of the manufacturing process through material behavior analysis. However, existing research still lacks a comprehensive understanding of the time-varying time-frequency characteristics in dynamic acoustic emission and efficient corresponding models. Therefore, this study proposes an innovative monitoring approach that integrates accelerable adaptive cepstrum (AAC) and L2-Dual Net. Specifically, AAC first employs variable frames and filters to map time-varying features in the signal, and then obtains representative frame length distributions and filter weights for different operating conditions based on statistical information. AAC not only unveils time-varying features in signals but also boasts an efficient computational process. L2-Dual Net is a novel quality assessment model with robust feature extraction and local spatial feature interactions. The incorporation of L2 norm equips the model with robust interference immunity, while the dual spatial attention mechanism helps the model to interact with spatial features exhibiting different time-frequencies. Variable process parameter experiments for aluminum alloy 7075 and titanium alloy TC4 were conducted to validate the reliability of the proposed method. Results demonstrate that AAC showcases optimal computational efficiency and higher feature resolution. When compared with state-of-the-art network architectures, L2-Dual Net exhibits superior information flow, along with higher recognition accuracy and robustness. Moreover, various variants of L2-Dual Net are explored and the code is accessible at https://github.com/Qinr1026/L2-Dual-Net. The proposed method holds promising potential for application in other areas of acoustic emission monitoring.

Optimizing MFCC parameters for the automatic detection of respiratory diseases

Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) are widely used for automatic analysis, with MFCC extraction commonly relying on default parameters. However, no comprehensive study has systematically investigated the impact of MFCC extraction parameters on respiratory disease diagnosis. In this study, we address this gap by examining the effects of key parameters, namely the number of coefficients, frame length, and hop length between frames, on respiratory condition examination. Our investigation uses four datasets: the Cambridge COVID-19 Sound database, the Coswara dataset, the Saarbrücken Voice Disorders (SVD) database, and a TACTICAS dataset. The Support Vector Machine (SVM) is employed as the classifier, given its widespread adoption and efficacy. Our findings indicate that the accuracy of MFCC decreases as hop length increases, and the optimal number of coefficients is observed to be approximately 30. The performance of MFCC varies with frame length across the datasets: for the COVID-19 datasets (Cambridge COVID-19 Sound database and Coswara dataset), performance declines with longer frame lengths, while for the SVD dataset, performance improves with increasing frame length (from 50 ms to 500 ms). Furthermore, we investigate the optimized combination of these parameters and observe substantial enhancements in accuracy. Compared to the worst combination, the SVM model achieves an accuracy of 81.1%, 80.6%, and 71.7%, with improvements of 19.6%, 16.10%, and 14.90% for the Cambridge COVID-19 Sound database, the Coswara dataset, and the SVD dataset respectively. To validate the generalization of these findings, we employ the Long Short-Term Memory (LSTM) model as a validation model. Remarkably, the LSTM model also demonstrates improved accuracy of 14.12%, 10.10%, and 6.68% across the datasets when utilizing the optimal combination of parameters. The optimal parameters are validated using an external voice pathology dataset (TACTICAS dataset). The results demonstrate the generalization capabilities of the optimized parameters across various pathologies, machine-learning models, and languages.

An Adaptive 3D Neighbor Discovery and Tracking Algorithm in Battlefield Flying Ad Hoc Networks with Directional Antennas.

Neighbor discovery and tracking with directional antennas in flying ad hoc networks (FANETs) is a challenging issue because of dispersed node distribution and irregular maneuvers in three-dimensional (3D) space. In this paper, we propose an adaptive 3D neighbor discovery and tracking algorithm in battlefield FANETs with directional antennas. With time synchronization, a flying node transmits/receives the neighbor discovery packets sequentially in each beam around it to execute a two-way handshake for neighbor discovery. The transmitting or receiving status of each discovery slot depends on the binary code corresponding to the identification of the node. Discovered neighbor nodes exchange their 3D positions in tracking slots periodically for node tracking, and the maximum tracking period is determined by node velocity, beamwidth, and the minimum distance between nodes. By configuring the relevant parameters, the proposed algorithm can also apply to two-dimensional planar ad hoc networks. The simulation results suggest that the proposed algorithm can achieve shorter neighbor discovery time and longer link survival time in comparison with the random scanning algorithm in scenarios with narrow beamwidth and wide moving area. When the frame length increases, the protocol overhead decreases but the average neighbor discovery time increases. The suitable frame length should be determined based on the network range, node count, beamwidth, and node mobility characteristics.

Design and Implementation of TDMA Scheduling Based on BRKGA

Abstract Messages in wireless Ad hoc networks may require intermediate multi-hop forwarding from the source to the target node. To find an optimum contend-free time slots scheduling solution in Ad hoc, a TDMA (Time Division Multiple Access) scheduling scheme based on BRKGA (Biased Random-key GA) is proposed. The algorithm divides the population of generation k into elite group and rest group. The elite solutions are copied directly to the next generation. One parent from the elite group and another parent from the rest population are randomly selected to crossover a new solution. The worst Pm solutions of the population of generation k are replaced by the mutants. The simulation results demonstrate that the TDMA based on BRKGA exhibits better performance in terms of lower frame length and higher channel utilization.

Optical performance of a solar dish concentrator formed by the same size mirror located on parabolic frame

Solar dish concentrator with low cost and meeting the flux distribution is always pursued for the efficient utilization of concentrated solar energy. This paper investigates the optical performance of a solar dish concentrator formed by using a number of identical square mirror units arranged on a parabolic surface frame. The manufacturing of the mirror surface of this concentrator requires only one kind of mold, which has the significant advantage of low-cost manufacturing. Three common types of mirror units including the parabolic mirror (focal length fm), spherical mirror (radius Rm) and plane mirror are considered. The influence of key geometric parameters including the mirror width d (250–750 mm) and dimensionless parameters such as f1/D, fm/f1 and Rm/f1 (f1 is the focal length of parabolic frame) on its optical performance indexes such as the focused spot size (i.e., intercept width w), average local concentrator ratio (LCR), peak LCR and flux uniformity is analyzed using ray-tracing method, and the correctness of optical model and concentrator optical function is verified by outdoor concentrating experiments. The results show that the concentrator composed of parabolic or spherical mirrors can easily obtain a small circular focusing spot with high LCR and the intercept width can be easily controlled within 200 mm, the peak LCR can reach 34457 (average LCR is 12898), and average LCR reaches 14794 (peak LCR is 29497) at the smallest spot with w = 38.4 mm, which can be a low-cost alternative to parabolic dish concentrator. The concentrator with plane mirrors are easier to obtain square focusing spots with excellent flux uniformity, w can be controlled from 180 to 380 mm and uniform LCR is between 100 and 1400, which is very suitable for concentrating photovoltaic field.

Molecular cloning and functional study of a Rel homologous gene in sea urchin Strongylocentrotus intermedius

NF-κB (Nuclear factor-kappa B) family proteins are versatile transcription factors that play crucial regulatory roles in cell development, growth, apoptosis, inflammation, and immune response. However, there is limited research on the function of these key genes in echinoderms. In this study, an NF-κB family gene (SiRel) was identified in sea urchin Strongylocentrotus intermedius. The gene has an open reading frame length of 1809 bp and encodes for 602 amino acids. Domain prediction results revealed that the N-terminal of SiRel protein encodes a conserved Rel homology domain (RHD), including the RHD-DNA binding domain and the RHD-dimerization domain. Multiple sequence comparison results showed that the protein sequences of these two domains were conserved. Phylogenetic analysis indicated that SiRel clustered with Strongylocentrotus purpuratus p65 protein and Rel protein of other echinoderms. Results from quantitative real-time PCR demonstrated detectable SiRel mRNA expression in all tested sea urchin tissues, with the highest expression level found in the gills. And SiRel mRNA expression levels were significantly induced after LPS (Lipopolysaccharide) and poly(I:C) (Polyinosinic:polycytidylic acid) stimulation. In addition, SiRel protein expression can be found in cytoplasm and nucleus of HEK293T cells. Co-immunoprecipitation results showed that SiRel could interact with sea urchin IκB (Inhibitor of NF-κB) protein. Western blotting and dual-luciferase reporter gene assay results indicated that overexpression of SiRel in HEK293T cells could impact the phosphorylation levels of JNK (c-Jun N-terminal kinase) and Erk1/2 (Extracellular signal-regulated kinases1/2) and activate interleukin-6 (IL-6), activating protein 1 (AP-1), interferon (IFN)α/β/γ, and signal transducer and activator of transcription 3 (STAT3) reporter genes in HEK293T cells. In conclusion, this study reveals that SiRel plays an important role in the innate immune response of sea urchins and enriches our understanding of comparative immunology theory.

Optimal interference mitigation with deep learningbased channel access in wireless body area networks

SummaryWireless body area networks (WBANs) are essential for medical applications, especially in remote health monitoring, as they transmit crucial and time‐sensitive data collected by nodes positioned around or within the body. However, the coexistence of WBANs with wireless channels can degrade performance due to interference. This study introduces OIM‐DLCAM, an optimal interference mitigation scheme for WBANs, which utilizes a deep learning‐based channel access method. OIM‐DLCAM addresses interference through the multiobjective Hungarian optimization (MOHO) algorithm, considering design constraints such as node transmission power, packet delivery ratio, and interference range. Additionally, it employs a deep probabilistic neural network‐based channel access method (DPNN‐CAM) to effectively mitigate interference by making decisions regarding contention window size, frame length, and buffer size. The proposed OIM‐DLCAM scheme ensures fairness between users while enhancing system performance. Simulation results from both static and dynamic sensor node scenarios demonstrate its effectiveness under various conditions, showcasing its potential to improve WBAN performance in medical applications. The simulations reveal that OIM‐DLCAM outperforms existing state‐of‐the‐art schemes across various scenarios, with efficiency gains of up to 86.187%, 72.452%, and 47.954% for WBAN node density, mobility, and packet arrival rate, respectively. Moreover, it significantly reduces the average end‐to‐end delay and packet drop rate while improving throughput and packet delivery ratio compared with existing schemes. Additionally, comparisons with industry standards, such as the IEEE 802.15.4e norm, validate the suitability of OIM‐DLCAM for cofounded WBANs.

Functional Study of the Role of the Methyl Farnesoate Epoxidase Gene in the Ovarian Development of Macrobrachium nipponense.

Methyl farnesoate epoxidase (MFE) is a gene encoding an enzyme related to the last step of juvenile hormone biosynthesis. Mn-MFE cDNA has a total length of 1695 bp and an open reading frame (ORF) length of 1482 bp, encoding 493 amino acids. Sequence analysis showed that its amino acid sequence has a PPGP hinge, an FGCG structural domain, and other structural domains specific to the P450 family of enzymes. Mn-MFE was most highly expressed in the hepatopancreas, followed by the ovary and gill, weakly expressed in heart and muscle tissue, and barely expressed in the eyestalk and cranial ganglion. Mn-MFE expression remained stable during the larval period, during which it mainly played a critical role in gonadal differentiation. Expression in the ovary was positively correlated and expression in the hepatopancreas was negatively correlated with ovarian development. In situ hybridization (ISH) showed that the signal was expressed in the oocyte, nucleus, cell membrane and follicular cells, and the intensity of expression was strongest at stage O-IV. The knockdown of Mn-MFE resulted in a significantly lower gonadosomatic index and percentage of ovaries past stage O-III compared to the control group. However, no differences were found in the cumulative frequency of molting between the experimental and control groups. Moreover, the analysis of ovarian tissue sections at the end of the experiment showed differences between groups in development speed but not in subcellular structure. These results demonstrate that Mn-MFE promotes the ovarian development of Macrobrachium nipponense adults but has no effect on molting.

Parametric Modelling of the Crystalline Microstructure of the MCM41-Type Mesoporous Silica Modified with Derivatives of Alkyls.

A siliceous material in which a framework order was established with a surfactant with sixteen carbon atoms in alkyl chains, MCM-41-C16, was synthesised, surface-modified, and tested regarding the selected physical properties. The pristine material was extracted in an acidic aqueous alcohol and then lined with different surface groups. The properties of four adsorbents were investigated using XRD, X-ray photoelectron spectroscopy, and N2 physisorption techniques. The unit-cell constant was determined from X-ray diffractograms, being in fixed relation to the edge length of the hexagonal frame. The specific surface areas of mesopores and whole crystallites were determined from low-temperature N2-physisorption isotherms. The novelty of this work is a mathematical model of a crystalline microstructure explaining the sizes and shapes of crystalline grains in relation to adsorption features, proposed and successfully tested with the aforementioned experimental data. The roughness of the surface is different from one that is necessary to explain the experimental characteristics quantitatively.

Deep Learning for Asynchronous Massive Access With Data Frame Length Diversity

Deep Learning for Asynchronous Massive Access With Data Frame Length Diversity

RANCANG BANGUN MESIN PENGUPAS BAWANG

The making of this shallot peeling machine is intended for farmers and catering entrepreneurs to facilitate the process of peeling shallots. The research and design of this machine were conducted at the Poluteknik campus and Sirarata workshop, Sibowi Village, Tanambulava District. Sigi Regency, Central Sulawesi Province. This shallot peeling machine is very simple, using an electric motor with a speed of 1400 rpm as a driving force. This peeler rubber serves to peel the shallot skin. The result of this research is the creation of an shallot peeling machine with a frame length of 75 cm, a width of 40 cm, and a height of 88 cm so that the peeling results can help shallot farmers.

Regulatory roles of long non-coding RNAs in short-term heat stress in adult worker bees

Long non-coding RNAs (lncRNAs) are crucial modulators of post-transcriptional gene expression regulation, cell fate determination, and disease development. However, lncRNA functions during short-term heat stress in adult worker bees are poorly understood. Here, we performed deep sequencing and bioinformatic analyses of honeybee lncRNAs. RNA interference was performed by using siRNA targeting the most highly expressed lncRNA. The silencing effect on lncRNA and the relative expression levels of seven heat shock protein (HSP) genes, were subsequently examined. Overall, 7,842 lncRNAs and 115 differentially expressed lncRNAs (DELs) were identified in adult worker bees following heat stress exposure. Structural analysis revealed that the overall expression abundance, length of transcripts, exon number, and open reading frames of lncRNAs were lower than those of mRNAs. GO analysis revealed that the target genes were mainly involved in “metabolism,” “protein folding,” “response to stress,” and “signal transduction” pathways. KEGG analysis indicated that the “protein processing in endoplasmic reticulum” and “longevity regulating pathway-multiple species” pathways were most enriched. Quantitative real-time polymerase chain reaction (qRT-PCR) detection of the selected DELs confirmed the reliability of the sequencing data. Moreover, the siRNA experiment indicated that feeding siRNA yielded a silencing efficiency of 77.51% for lncRNA MSTRG.9645.5. Upon silencing this lncRNA, the expression levels of three HSP genes were significantly downregulated (p < 0.05), whereas those of three other HSP genes were significantly upregulated (p < 0.05). Our results provide a new perspective for understanding the regulatory mechanisms of lncRNAs in adult worker bees under short-term heat stress.

Biomechanical Analyses of Scoop in Field Hockey

Field hockey is an Olympic sport played all over the world. Hockey is played with a stick where one requires endurance, agility, balance coordination, and high skill to convert the shot. There are various kinds of skills i.e. hitting, dribbling, scooping, tackling etc. Only scoop was selected for the study in different phases (stance phase, execution phase, follow through phase). Field hockey scoop is the aerial passing by lifting the ball from the ground inserting head of hockey stick under the ball. Scoop plays vital role in competitive field hockey games. The aim of the study was to find out the kinematic difference in the elbow joint, knee joint, and ankle joint. The objective of the study was to find out the angular differences of elbow joint, knee joint, and ankle joint in different phases of delivery of field hockey scoop shot. Researchers hypothesised that there are significance differences in elbow joint angle, knee joint angle, and ankle joint angle during delivering of field hockey scoop shot. Six males inter university players aged from 20-24 years were selected for the study and at least they represented at inter university games /national level. Set of the camera is at 1.10 m in height and 3.70 meters. The focal length is 5.6, the resolution is 1080, and the frame rate is 100 per sec. A Sony FRD-AX700 camera was placed 3.7 meters apart on the right side of the hockey player. Angle of elbow joint, angle of knee joint, angle ankle joint, cadence, stride length, and numbers of frames were analysed using Kinovea 0.9.5 software. This research will help the players to execute scoop after knowing elbow joint angle, knee joint angle, and ankle joint angle. Key Words: Field Hockey, Scoop, Elbow, Ankle, Knee.

Cepstral coefficients effectiveness for gunshot classifying

This paper analyses the efficiency of various frequency cepstral coefficients (FCC) in a non-speech application, specifically in classifying acoustic impulse events-gunshots. There are various methods for such event identification available. The majority of these methods are based on time or frequency domain algorithms. However, both of these domains have their limitations and disadvantages. In this article, an FCC, combining the advantages of both frequency and time domains, is presented and analyzed. These originally speech features showed potential not only in speech-related applications but also in other acoustic applications. The comparison of the classification efficiency based on features obtained using four different FCC, namely mel-FCC (MFCC), inverse mel-frequency cepstral coefficients (IMFCC), linear-frequency cepstral coefficients (LFCC), and gammatone-frequency cepstral coefficients (GTCC) is presented. An optimal frame length for an FCC calculation is also explored. Various gunshots from short guns and rifle guns of different calibers and multiple acoustic impulse events, similar to the gunshots, to represent false alarms are used. More than 600 acoustic events records have been acquired and used for training and validation of two designed classifiers, support vector machine, and neural network. Accuracy, recall and Matthew’s correlation coefficient measure the classification success rate. The results reveal the superiority of GFCC to other analyzed methods.

Performance evaluation of lung sounds classification using deep learning under variable parameters

It is desired to apply deep learning models (DLMs) to assist physicians in distinguishing abnormal/normal lung sounds as quickly as possible. The performance of DLMs depends on feature-related and model-related parameters heavily. In this paper, the relationship between performance and feature-related parameters of a DLM, i.e., convolutional neural network (CNN) is analyzed through experiments. ICBHI 2017 is selected as the lung sounds dataset. The sensitivity analysis of classification performance of the DLM on three parameters, i.e., the length of lung sounds frame, overlap percentage (OP) of successive frames and feature type, is performed. An augmented and balanced dataset is acquired by the way of white noise addition, time stretching and pitch shifting. The spectrogram and mel frequency cepstrum coefficients of lung sounds are used as features to the CNN, respectively. The results of training and test show that there exists significant difference on performance among various parameter combinations. The parameter OP is performance sensitive. The higher OP, the better performance. It is concluded that for fixed sampling frequency 8 kHz, frame size 128, OP 75% and spectrogram feature is optimum under which the performance is relatively better and no extra computation or storage resources are required.

Hierarchical Cross Traffic Scheduling Based on Time-Aware Shapers for Mobile Time-Sensitive Fronthaul Network

To solve the problem of jitter and low network throughput caused by the impact of background flows on IQ traffic in mobile fronthaul network, this paper proposed a new scheduling model for background flows, named hierarchical crossover traffic scheduling mechanism based on time-aware shaper (HC-TAS) by improving the traditional counterpart. Then, in this new model, we designed an inbound scheduling algorithm based on frame length matching and an outbound scheduling algorithm based on queue status, making sure that smaller data frames will not be blocked by large data frames. This greatly improves the utilization of timeslots in the scheduling process and reduces the jitter impact of background flows. To verify its performance, we conducted experiments in a simulated fronthaul network conforming to IEEE 802.1CM. The experimental results show that, under the condition that the jitter is guaranteed to be zero, compared with two mainstream scheduling schemes, Comb-FITting and TAS + Preemption, our proposed scheme can achieve lower maximum end-to-end delay and higher link utilization. The proposed HC-TAS meets the requirements of low jitter and high bandwidth utilization in 5G fronthaul network, and the research results provide a technical basis for the application and development of general time-sensitive networks as well.