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The design level of channel physical characteristics has a crucial influence on the transmission quality of high-speed serial links. However, channel design requires a complex simulation and verification process. In this paper, a cascade neural network model constructed of a Deep Neural Network (DNN) and a Transformer is proposed. This model takes physical features as inputs and imports a Single-Bit Response (SBR) as a connection, which is enhanced through predicting frequency characteristics and equalizer parameters. At the same time, signal integrity (SI) analysis and link optimization are achieved by predicting eye diagrams and channel operating margins (COMs). Additionally, Bayesian optimization based on the Gaussian process (GP) is employed for hyperparameter optimization (HPO). The results show that the DNN–Transformer cascaded model achieves high-precision predictions of multiple metrics in performance prediction and optimization, and the maximum relative error of the test-set results is less than 2% under the equalizer architecture of a 3-taps TX FFE, an RX CTLE with dual DC gain, and a 12-taps RX DFE, which is more powerful than other deep learning models in terms of prediction ability. [ABSTRACT FROM AUTHOR]

Prestressing basalt‐fiber‐reinforced polymer (BFRP) bars and three types of fibers were used to enhance precast slabs during construction. Experimental investigation was conducted on one control slab and three reinforced slabs, while equations for the flexural behavior of slabs and optimization were performed. The results demonstrated that the addition of fibers had minimal impact on the compressive strength of concrete, but significantly improved its flexural strengths by up to 36%. Fibers and BFRP bars with a prestress level of 40% enhanced the cracking load by a range of 506% to 584%, and the ultimate load by a range of 28% to 48%, while exerting minimal influence on the yield load. Reinforced slabs exhibited a reduction in yield deflection ranging from 57% to 67%, along with a decrease in ultimate deflection ranging from 33% to 42%. Prestress played a crucial role in controlling slab cracks, whereas fiber type had only minor effects. The equation derived for predicting experimental results regarding normal section cracking moment showed a maximum deviation not exceeding 5%. Material utilization can be improved by reducing slab thickness or the number of prestressing bars, followed by lowering prestress levels and truss numbers. Prioritizing reduction in slab thickness is recommended from a construction perspective. [ABSTRACT FROM AUTHOR]

The study proposed using twisted rope made of flexible fiber‐reinforced polymers (FRPs) instead of wire and synthetic ropes in high load‐bearing and corrosive environments. Finite element model verification and parameter analysis were conducted for the rope, along with deriving theoretical equations for its tensile properties. Increasing the lay length improved model accuracy, with a maximum bearing capacity within a 10% margin of error compared to experimental results. The model length had minimal impact on calculation results, while changes in radial mesh size (0.13 and 0.2 mm) and friction coefficient (0–0.2) greatly affected maximum contact stress. The tensile strength and elastic modulus of the strand remained almost constant (approximately 1142 MPa and 44 GPa) when the friction coefficient was altered. Increasing lay length (6D–20D) enhanced the tensile properties of the strand, whereas tendon diameter (1–3 mm) had negligible impact. Arranging inner and outer strands with the same lay length was better for circular ropes than those with the same lay angle. Inverse lay direction reduced rope torque and increased strand contact stress. Rectangular ropes had higher strength and modulus conversion efficiency, with lower contact stress compared to circular ones. The accuracy of rope equations improved with longer lay lengths, and adding a correction factor for lay length can modify the equation. Highlights: A flexible FRP rope with high strength and twisted form was proposed.The effect of construction factors on the tensile behaviors of ropes was clarified.Equations for calculating the tensile properties of ropes were derived. [ABSTRACT FROM AUTHOR]

To reveal the durability of fiber‐reinforced polymer (FRP) profiles, which differ from FRP bars due to the clear variations in the internal structure of the fibers. This study experimentally investigated the tensile properties of FRP profiles in the seawater sea sand concrete (SSC) environment at 25, 45, and 60°C. Unidirectional basalt FRP profiles, multidirectional basalt FRP profiles, and basalt and carbon hybrid FRP profiles were considered. SEM analysis was performed to evaluate the corrosion mechanism. Results show that the strength degradation of FRP profiles accelerated with rising ambient temperature due to resin corrosion in hyperthermia. After 63 days of immersion in the SSC environment solution, multidirectional basalt FRP (BFRP) profiles exhibited more severe corrosion than unidirectional BFRP profiles (82.5% and 88.2%, respectively). The hybrid FRP profiles exhibited a strength retention of 86.4%, which was higher than that of multidirectional BFRP profiles due to the superior alkali resistance of carbon fibers compared to basalt fibers. In addition, prediction models of FRP profiles based on the Arrhenius relation were proposed with a high correlation coefficient of R2. Highlights: Durability of FRP profiles in SSC environment was studied.Basalt and carbon fibers hybrid reinforced multidirectional polymer profiles.Corrosion mechanism of FRP profiles was revealed.Tensile property prediction model of FRPs in SSC environment was proposed. [ABSTRACT FROM AUTHOR]

The cognitive radar framework presents a closed-loop adaptive processing paradigm that ensures the efficient acquisition of target information while exploring the environment and enhancing overall sensing performance. In this study, instead of mutual information, we employed the squared Pearson correlation coefficient (SPCC) to measure the target information in observations specifically considering only linear dependency. A waveform design method is proposed that simultaneously maximizes target information and minimizes the integrated sidelobe level (ISL) under the constant modulus constraint (CMC). To enhance computational efficiency, we reformulated the constrained problem as an unconstrained optimization problem by leveraging the inherent geometric property of CMC. Additionally, we present two conditional equivalences associated with waveform design in relation to target information. The simulation results validate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

To realize the low-carbon, environmentally protection and efficient resource utilization of metallurgical dust containing zinc in iron and steel enterprises, the reduction roasting-magnetic separation of metallurgical dust containing zinc with iron content of 30. 38% and zinc content of 4. 79% was studied. The experimental results show that the direct magnetic separation of metallurgical dust containing zinc is difficult to achieve effective separation of zinc and iron. Under the conditions of roasting temperature of 950 °C, roasting time of 20 min and magnetic separation intensity of 100 mT. The iron recovery rate of magnetic separation concentrate is 79.50%, the iron content is 57. 00%,and the zinc content is 2. 45%. The zinc recovery rate of magnetic separation taillings is 71. 06%, the zinc content is 9. 92%, and the iron content is 16. 81% . The separation rates of zinc and iron is better. The concentrate in the magnetic separation product is mainly composed of elemental Fe, and the tailings are mainly composed of SiO2 and ZnO. [ABSTRACT FROM AUTHOR]

Ankylosing spondylitis (AS) is a chronic, progressive inflammatory rheumatic disease affecting the spine, axial skeleton, and sacroiliac joints. Pathogenesis of AS encompasses enthesitis, synovitis, and osteoproliferation, leading to the formation of syndesmophytes, ankylosis, and spinal rigidity. Bioinformatics, an interdisciplinary field combining computer science, mathematics, and biology, enables the analysis of complex biological data for investigating AS pathogenesis. This review summarizes differentially expressed protein‐coding genes in peripheral blood or local tissues of AS patients compared with healthy controls and comprehensively reviews currently available therapeutic agents. The objective is to enhance the understanding of AS pathogenesis, inform diagnosis, identify novel therapeutic targets, and facilitate personalized medicine. This review contributes to a deeper understanding of AS pathogenesis and provides a foundation for developing innovative therapeutic approaches. [ABSTRACT FROM AUTHOR]

The bond properties between polymer impregnated basalt textile and fine‐grained concrete were studied by pull‐out test considering the effects of bond length, impregnation polymer type, surface condition, and transverse yarn. The experimental results showed the pull‐out load increased with the bond length increasing, and the slight decrease in bond strength was attributed to the nonlinear distribution of bond stress. Owing to the high viscosity and good permeability of epoxy resin, the bond strength of epoxy resin‐impregnated textile was 238% and 592% higher than that of textile impregnated with acrylic emulsion and polyvinyl chloride, respectively. Moreover, the bond properties were improved significantly for impregnated textile with sticking sand or fiber by increasing the interfacial friction between textile and concrete, and the highest bond strength was obtained for yarn sticking sand with particle sizes of 0.09 ~ 0.18 mm. The transverse yarn of epoxy resin‐impregnated textile can generate an interlocking effect to concrete due to the semi‐rigid node, which increased the bond strength by 48.6%, whereas this did not happen for textile impregnated with flexible material. Furthermore, the anchorage lengths of textile were calculated, and the proposed simple bond slip model can be used to describe the pull‐out response of polymer impregnated basalt textile embedded in concrete. [ABSTRACT FROM AUTHOR]

In a general wireless sensor network, a sink node collects data from each node successively and then post-processes the data to obtain useful information. However, conventional methods have a scalability problem: the data collection/processing time increases with the number of nodes, and frequent transmission collisions degrade spectrum efficiency. If only statistical values of the data are needed, using over-the-air computation (AirComp) can efficiently perform data collection and computation. However, AirComp also has its problems: when the channel gain of a node is too low, (i) the transmission power of that node will be high, decreasing the lifetime of that node and the entire network, and (ii) sometimes, the computation error still occurs even though the maximal transmission power is used. To jointly solve these two problems, in this paper we investigate the relay communication for AirComp and study a relay selection protocol. The basic method selects an ordinary node with a good channel condition as a relay node, considering both computation error and power consumption. This method is further enhanced to explicitly consider network lifetime in relay selection. Extensive simulation evaluations confirm that the proposed method helps to prolong the lifetime of the entire network and reduce computation errors as well. [ABSTRACT FROM AUTHOR]