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Abstract A low‐complexity anti‐multipath interference spread spectrum communication system is proposed to address shortcomings in traditional anti‐multipath technology, such as complex structures and high resource consumption. The system utilizes a fast Fourier transform to capture pseudo‐noise code signals and simultaneously detect multipath signals. Moreover, the signal‐to‐noise ratio (SNR) of each path signal is calculated, and the multipath signal is synthesized through the designed optimal SNR synthesis method to improve the SNR of the demodulated signal to reduce the bit error rate. MATLAB is used to perform functional simulations of the system to verify its feasibility. The simulation results show that the system can successfully detect and synthesize multipath signals and achieve lower communication error rates than traditional code division multiple access (CDMA) systems.

The histone lysine methyltransferase SET (Suppressor of variegation, Enhancer of Zeste, Trithorax) and MYND (Myeloid-Nervy-DEAF1) domain-containing protein (SMYD2) plays a role in the tumorigenesis of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, the prognostic significance of SMYD2 in CESC and the link between SMYD2 and tumor-infiltrating immune cells are unknown. The prognostic value of SMYD2 in CESC was obtained from The Cancer Genome Atlas (TCGA). SMYD2 mRNA and protein were both highly expressed in CESC compared with normal tissues. The high expression of SMYD2 was associated with advanced tumor status and poor prognosis in CESC patients. SMYD2 was an independent prognostic factor for overall survival. In vitro experiments with knockdown of SMYD2 suppressed CESC cell migration and invasion. The online tumor immune estimation resource (TIMER) and Kaplan-Meier analysis results revealed that the infiltration of CD4+ T and CD8+ T cells was related to poor prognosis. In TIMER-based multivariate Cox regression analysis, CD8+ T cells and SMYD2 were demonstrated as independent prognostic factors of CESC. In conclusion, our data suggest that high SMYD2 expression is a predictor of poor prognosis in CESC patients; SMYD2 could serve as a prognostic biomarker and molecular therapeutic target for CESC.

In recent years, the low Earth orbit microsatellite network technology has experienced rapid development due to its advantages of low latency, low cost, and short development cycles. However, building an efficient and reliable satellite network routing system faces many challenges due to the characteristics of satellite networks, such as fast‐changing topology, large variations in link latency, higher probabilities of node and link failures, and limited resources. Routing algorithms have a significant impact on intersatellite communication and have become a research hotspot. The current mainstream algorithms focus on reducing information propagation delays between satellites to enable faster transmission. However, many satellite networks, such as meteorological observation satellite networks, are not sensitive to propagation delays but emphasize reducing hardware costs, especially for the receiving and transmitting signal systems of satellites. This means minimizing the single‐step signal transmission distance of satellites. This article proposes a routing algorithm based on time slot planning and the shortest path step length. Experimental simulation results demonstrate that this algorithm significantly reduces the step length of signal transmission and lowers hardware costs. [ABSTRACT FROM AUTHOR]

College student education and management can be enhanced through a data‐driven approach involving student surveys, academic records, and text analysis to understand student interests and concerns. Effective categorization of relevant topics enables universities to provide tailored support and educational content, thus improving the quality of education and fostering student success and well‐being by adapting to evolving student needs and aspirations. The primary contribution of this work is demonstrating the effectiveness of semisupervised learning methods in educational content classification, providing a robust solution for enhancing college student education and management with limited labeled data. The objective of this study was to evaluate the feasibility of using semisupervised learning methods in educational content classification using the Yahoo Answers dataset. For the Yahoo_500 dataset, the supervised neural network achieved a best evaluation accuracy of 0.6565, an average precision of 0.6539, an average recall of 0.6565, and an average F1 score of 0.6547. In contrast, semisupervised approaches, Dash, FixMatch, and FreeMatch, consistently demonstrated superior performance. Among the evaluated semisupervised architectures, FreeMatch achieved the highest best evaluation accuracy (0.6759), average precision (0.6739), average recall (0.6759), and average F1 score (0.6744). The Yahoo_2000 dataset, which benefited from an increased labeled data pool, exhibited a similar trend with semisupervised approaches consistently surpassing the supervised approach. FreeMatch maintained its top performing position in several categories, including computers and Internet, consumer electronics, and business and finance, with impressive F1 score of ≥0.753. Overall, the semisupervised approaches prove highly effective in improving model performance, highlighting its practical advantages. These results underscore the robustness of semisupervised approaches and their capability to improve classification performance even with limited labeled data. Employing semisupervised learning on the Yahoo Answers dataset and additional data sources for college student management and education can be a powerful tool for gaining insights into students' interests and concerns. [ABSTRACT FROM AUTHOR]

In warehouses with vast quantities of heavy goods, heavy-duty forklift Automated Guided Vehicles (AGVs) play a key role in facilitating efficient warehouse automation. Due to their large load capacity and high inertia, heavy-duty forklift AGVs struggle to automatically navigate optimized routes. Additionally, rapid acceleration and deceleration can pose safety hazards. This paper proposes a velocity-adaptive model predictive control (MPC)-based path tracking method for heavy-duty forklift AGVs. The movement of heavy-duty forklift-type AGVs is categorized into straight-line and curve-turning motions, corresponding to the straight and curved sections of the reference path, respectively. These sections are segmented based on their curvature. The best driving speeds for straight and curved sections were 1.5 m/s and 0.3 m/s, respectively, while the optimal acceleration rates were 0.2 m/s2 for acceleration and −0.2 m/s2 for deceleration in straight paths and 0.3 m/s2 for acceleration with −0.15 m/s2 for deceleration in curves. Moreover, preferred sampling times, prediction domain, and control domain were determined through simulations at various speeds. Four path tracking methods, including pure tracking, Linear Quadratic Regulator (LQR), MPC, and the velocity-adaptive MPC, were simulated and evaluated under straight-line, turning, and complex double lane change conditions. Field experiments conducted in a warehouse environment demonstrated the effectiveness of the proposed path tracking method. Findings have implications for advancing path tracking control in narrow aisles. [ABSTRACT FROM AUTHOR]

BACKGROUND: Accurate detection of weeds and estimation of their coverage is crucial for implementing precision herbicide applications. Deep learning (DL) techniques are typically used for weed detection and coverage estimation by analyzing information at the pixel or individual plant level, which requires a substantial amount of annotated data for training. This study aims to evaluate the effectiveness of using image‐classification neural networks (NNs) for detecting and estimating weed coverage in bermudagrass turf. RESULTS: Weed‐detection NNs, including DenseNet, GoogLeNet and ResNet, exhibited high overall accuracy and F1 scores (≥0.971) throughout the k‐fold cross‐validation. DenseNet outperformed GoogLeNet and ResNet with the highest overall accuracy and F1 scores (0.977). Among the evaluated NNs, DenseNet showed the highest overall accuracy and F1 scores (0.996) in the validation and testing data sets for estimating weed coverage. The inference speed of ResNet was similar to that of GoogLeNet but noticeably faster than DenseNet. ResNet was the most efficient and accurate deep convolution neural network for weed detection and coverage estimation. CONCLUSION: These results demonstrated that the developed NNs could effectively detect weeds and estimate their coverage in bermudagrass turf, allowing calculation of the herbicide requirements for variable‐rate herbicide applications. The proposed method can be employed in a machine vision‐based autonomous site‐specific spraying system of smart sprayers. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Three-dimensional profilometry tends to be less effective at measuring discontinuous surfaces. To overcome this problem, an optimized profilometry based on fringe projection is proposed in this paper. Due to the limitation of the shooting angle, there are projection blind spots on the surface of discontinuous objects. Since the noises and unwrapping errors are always localized at the projection blind spots, an algorithm is designed to determine the blind spots automatically with the light intensity difference information. Besides, in order to improve the measurement accuracy, a processing scheme is introduced to deal with the local height distortion introduced by the dual-frequency grating profilometry. Lots of measurement tests on various surfaces are carried out to assess the optimized profilometry, and experimental results indicate that the modified profilometry system works more robust with high reliability and accuracy in measuring different kinds of surfaces, especially discontinuous ones.

Wastewater treatment using microbial fuel cells (MFCs) is a potentially useful technology due to its low cost, environmental friendliness, and low sludge production. In this study, a single-chambered air cathode MFC (SCMFC) was developed and investigated regarding its performance and microbial community evolution following nitrate exposure. During long-term operation, diverse denitrifiers accumulated on the electrodes to form a denitrifying MFC (DNMFC) with stable activity for nitrate reduction. The DNMFC presented considerably higher electroactivity, stability, and denitrification rates than the SCMFC. Though energy recovery decreased in the DNMFC by partial organics utilized for heterotrophic denitrification, the electron transfer efficiency increased. Geobacter as the absolutely dominant genus in the SCMFC anode was eliminated and replaced by Azonexus and Pseudomonas in the DNMFC. Furthermore, the biomass of Pseudomonas (151.0 ng/μL) in the DNMFC cathode was five-fold higher than that in the SCMFC, although the bacterial community compositions were quite similar. The DNMFC with highly abundant Pseudomonas exhibited much better performance in terms of electrochemical activity and nitrate removal. The evolution process of functional bacteria from the SCMFC to the DNMFC comprehensively reveals the significant role of denitrifying electroactive bacteria in a bioelectrochemical system for nitrogen-containing wastewater treatment. [ABSTRACT FROM AUTHOR]

Hepatitis B virus (HBV) has been classified into ten genotypes (A-J). Genotype B (HBV/B) is divided into nine subgenotypes (B1-B9), each with specific geographical predominance. Some reference sequence of HBV/B subgenotypes are currently in use, but these sequences have defects, being insufficient to represent the reference of individual subgenotype. The aim of this study was to establish a more representative reference of HBV/B subgenotypes in different regions. Full genomic sequences of HBV/B were obtained from GenBank and compartmentalized into genomic subtypes. The homology between our established HBV/B subgenotype references was evaluated at the nucleotide level. We established reference strains for B1-Japan, B2-China, B3-Indonesia, B4-Vietnam, B6-North America, B7-Indonesia and B9-Southeast Asia. Fractional significant mutation sites of the strains that were established were observed in the BCP/Pre-C regions. We calculated the genetic divergence time from the most recent common ancestor of HBV/B pedigree. The reference sequences established in the study provide reference standards for studies on molecular characterization, virology and pathogenesis of HBV/B.