A direct laser-synthesized magnetic metamaterial for low-frequency wideband passive microwave absorption

Microwave absorption in radar stealth technology is faced with challenges in terms of its effectiveness in low-frequency regions.Herein,we report a new laser-based method for producing an ultrawideband metamaterial-based microwave absorber with a highly uniform sheet resistance and negative magnetic permeability at resonant frequencies,which results in a wide bandwidth in the L-to S-band.Control of the electrical sheet resistance uniformity has been achieved with less than 5%deviation at 400Ωsq^(-1)and 6%deviation at 120Ωsq^(-1),resulting in a microwave absorption coefficient between 97.2%and 97.7%within a1.56–18.3 GHz bandwidth for incident angles of 0°–40°,and there is no need for providing energy or an electrical power source during the operation.Porous N-and S-doped turbostratic graphene 2D patterns with embedded magnetic nanoparticles were produced simultaneously on a polyethylene terephthalate substrate via laser direct writing.The proposed low-frequency,wideband,wide-incident-angle,and high-electromagnetic-absorption microwave absorber can potentially be used in aviation,electromagnetic interference(EMI)suppression,and 5G applications.

New era:prospects for managing cancer of unknown primary

Cancer of unknown primary(CUP)is a highly heterogeneous tumor type that is confirmed to be metastatic through pathological examination;however,its primary lesion cannot be determined on the basis of detailed clinical information and diagnostic methods.The current guidelines have not changed the basic definition of CUP.Some studies have reported a decline in the incidence of CUP,to approximately 2%1,with the development of diagnostic techniques such as radiology,histopathology,and genetic testing.

Cationized Melamine-formaldehyde Resin for Improving the Wet Strength of Paper

In this work, melamine-formaldehyde resin was cationized by adding modifiers so that the fibers closely bonded to improve their usability and the wet strength of paper was greatly improved. Triethanolamine and dimethylamine were added to modify the melamine-formaldehyde resin,respectively.The mechanism of the cationized resin was explored and the possible chemical reactions were deduced. It was concluded that,with the use of triethanolamine,the most optimum product was obtained by hydroxymethylation for 30 min with a temperature of 85℃ and p H of 9. 0 where n( melamine) ∶ n( formaldehyde) ∶ n( methanol) ∶ n( triethanolamine) was 100 ∶ 330 ∶ 450 ∶ 15. With the combined use of dimethylamine and methanol,the optimal product was acquired by condensation for 30 min at a temperature of 50℃ and p H of 2. 0 at melamine, formaldehyde, methanol, and dimethylamine molar ratio of100∶ 330∶ 350∶ 20. With the only use of dimethylamine,the optimal product was obtained by condensation at melamine,formaldehyde,dimethylamine molar ratio of 100∶ 330∶ 10. The wet tensile strength of fruit-bagging paper was improved by adding cationized melamine-formaldehyde resin. The zeta potential,charge density,and conductivity of the melamine-formaldehyde resin were also studied.

VisCI:A visualization framework for anomaly detection and interactive optimization of composite index

Composite index is always derived with the weighted aggregation of hierarchical components,which is widely utilized to distill intricate and multidimensional matters in economic and business statistics.However,the composite indices always present inevitable anomalies at different levels oriented from the calculation and expression processes of hierarchical components,thereby impairing the precise depiction of specific economic issues.In this paper,we propose VisCI,a visualization framework for anomaly detection and interactive optimization of composite index.First,LSTM-AE model is performed to detect anomalies from the lower level to the higher level of the composite index.Then,a comprehensive array of visual cues is designed to visualize anomalies,such as hierarchy and anomaly visualization.In addition,an interactive operation is provided to ensure accurate and efficient index optimization,mitigating the adverse impact of anomalies on index calculation and representation.Finally,we implement a visualization framework with interactive interfaces,facilitating both anomaly detection and intuitive composite index optimization.Case studies based on real-world datasets and expert interviews are conducted to demonstrate the effectiveness of our VisCI in commodity index anomaly exploration and anomaly optimization.

Visual evaluation of graph representation learning based on the presentation of community structures

Various graph representation learning models convert graph nodes into vectors using techniques like matrix factorization,random walk,and deep learning.However,choosing the right method for different tasks can be challenging.Communities within networks help reveal underlying structures and correlations.Investigating how different models preserve community properties is crucial for identifying the best graph representation for data analysis.This paper defines indicators to explore the perceptual quality of community properties in representation learning spaces,including the consistency of community structure,node distribution within and between communities,and central node distribution.A visualization system presents these indicators,allowing users to evaluate models based on community structures.Case studies demonstrate the effectiveness of the indicators for the visual evaluation of graph representation learning models.

A Role for Transmembrane Protein 16C/Slack Impairment in Excitatory Nociceptive Synaptic Plasticity in the Pathogenesis of Remifentanil-induced Hyperalgesia in Rats

Remifentanil is widely used to control intraoperative pain. However, its analgesic effect is limited by the generation of postoperative hyperalgesia. In this study, we investigated whether the impairment of transmembrane protein 16C(TMEM16C)/Slack is required for a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic receptor(AMPAR) activation in remifentanil-induced postoperative hyperalgesia. Remifentanil anesthesia reduced the paw withdrawal threshold from 2 h to 48 h postoperatively,with a decrease in the expression of TMEM16C and Slack in the dorsal root ganglia(DRG) and spinal cord.Knockdown of TMEM16C in the DRG reduced the expression of Slack and elevated the basal peripheral sensitivity and AMPAR expression and function. Overexpression of TMEM16C in the DRG impaired remifentanilinduced ERK1/2 phosphorylation and behavioral hyperalgesia. AMPAR-mediated current and neuronal excitability were downregulated by TMEM16C overexpression in the spinal cord. Taken together, these findings suggest that TMEM16C/Slack regulation of excitatory synaptic plasticity via GluA1-containing AMPARs is critical in the pathogenesis of remifentanil-induced postoperative hyperalgesia in rats.