High-performance Signal Research Articles

Patterned Gold Nanoparticle Superlattice Film for Wearable Sweat Sensors.

Nanoparticle superlattices are beneficial in terms of providing strong and uniform signals in analysis owing to their closely packed uniform structures. However, nanoparticle superlattices are prone to cracking during physical activities because of stress concentrations, which hinders their detection performance and limits their analytical applications. In this work, template printing methods were used in this study to prepare a patterned gold nanoparticle (AuNP) superlattice film. By adjustment of the size of the AuNP superlattice domain below the critical size of fracture, the mechanical stability of the AuNP superlattice domain is improved. Thus, long-term sustainable high-performance signal output is achieved. The patterned AuNP superlattice film was used to construct a wearable sweat sensor based on surface-enhanced Raman scattering (SERS). The designed sensor showed promise for long-term reliable use in actual scenarios in terms of recommending water replenishment, monitoring hydration states, and tracking the intensity of activity.

Neuron-astrocyte interaction-inspired percolative networks with metal microdendrites and nanostars for ultrasensitive and transparent electronic skins

Biological systems provide innovative designs for electronic devices, optimizing network configurations for high-performance signal transmission with minimal energy consumption. The brain, as one of the most complex biological structures, demonstrates efficient network design through the multiscale radial networks of neurons and astrocytes. Emulating these brain networks offers a blueprint for the development of ultrasensitive pressure sensors for electronic skin, aiming to provide a more intuitive and sensitive mode of interaction between humans and machines. Herein, we propose a neuromorphic percolative network inspired by neuron-astrocyte interactions for ultrasensitive pressure sensors employing metal microdendrites and nanostars. Electromechanical investigation through representative volume elements simulation reveals that the optimized arrangement of microdendrites and nanostars in the neuromorphic percolative system enhances the percolation threshold and probability. Following these simulation results, we developed a neuromorphic percolative polyurethane (NP-PU) matrix utilizing the metal microdendrite-nanostar networks. The augmented quantum tunneling effect in the NP-PU matrix was investigated through electrochemical impedance spectroscopy and capacitance analysis. The fabricated piezoresistive pressure sensor with the NP-PU matrix shows ultrahigh sensitivity (160.3 kPa−1) at a low pressure range and a low limit of detection resolution (4 Pa), enabled by multi-channel quantum tunneling in the metal particle networks. Furthermore, the sensor maintains excellent mechanical flexibility and high optical transparency (75.4 %), improving its efficacy in applications like electronic skin and force touch panel. Our study highlights the potential of leveraging biological system-inspired network designs for crafting advanced electronic devices.

Corporate Environmental, Social, and Governance (ESG) Performance and the Internal Control Environment

SYNOPSIS We consider how corporate environmental, social, and governance (ESG) performance relates to the strength of the internal control environment. The transparent reporting hypothesis predicts that high ESG performance signals ethical decision making and/or strong financial performance, both of which manifest in a stronger internal control environment and, therefore, fewer material weaknesses in internal controls. We find that ESG performance is negatively related to the likelihood of general internal control weaknesses, consistent with transparent reporting. We also find that ESG performance is negatively related to company-level internal control weaknesses, which are considered relatively severe. Further, we find that ESG performance is negatively associated with specific internal control weaknesses that indicate a lack of ethical tone at the top. We find support for both ethical and performance explanations behind the transparent reporting hypothesis. Overall, our results suggest that ESG performance is positively associated with the strength of the internal control environment. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: M14; M40; M42.

Human-robot collaborative disassembly enabled by brainwaves and improved generative adversarial network

Human-robot collaboration (HRC) can greatly facilitate the disassembling processes of end-of-life (EoL) products. For the robot in HRC, an intuitive control function enabled by a brain-machine interface (BMI) and human brainwaves will be useful to support dynamic decision-making under various disassembly conditions. However, a major challenge in developing a BMI-enabled HRC disassembly system is that there are usually a limited number of brainwave signals available for system training. To address the challenge, a novel model, namely TCN-D2GAN, was designed in this study. The model was used to augment acquired brainwave signals and support the establishment of the BMI-enabled HRC disassembly system. The innovations of the TCN-D2GAN model come from the following aspects: (i) the strengths of a temporal convolutional network (TCN) and a dual discrimination generative adversarial network (D2GAN) were combined to accomplish high-performance signal augmentation, and (ii) new loss functions were defined in the model to avoid the use of hyperparameters, so the training effect of the model can be optimised. Based on two public electroencephalography (EEG) datasets, experiments for signal augmentation and system training were carried out. The TCN-D2GAN model was compared with several mainstream generative adversarial network (GAN) models. Results indicated that the TCN-D2GAN model exhibited better performance in terms of signal classification accuracy and training efficiency. Finally, disassembly experiments were presented to validate the applicability of the system.

A Controlled Release Aptasensor Utilizing AIE-Active MOFs as High-Efficiency ECL Nanoprobe for the Sensitive Detection of Adenosine Triphosphate.

Improving the sensitivity in electrochemiluminescence (ECL) detection systems necessitates the integration of robust ECL luminophores and efficient signal transduction. In this study, we report a novel ECL nanoprobe (Zr-MOF) that exhibits strong and stable emission by incorporating aggregation-induced emission ligands into Zr-based metal-organic frameworks (MOFs). Meanwhile, we designed a high-performance signal modulator through the implementation of a well-designed controlled release system with a self-on/off function. ZnS quantum dots (QDs) encapsulated within the cavities of aminated mesoporous silica nanoparticles (NH2-SiO2) serve as the ECL quenchers, while adenosine triphosphate (ATP) aptamers adsorbed on the surface of NH2-SiO2 through electrostatic interaction act as "gatekeepers." Based on the target-triggered ECL resonance energy transfer between Zr-MOF and ZnS QDs, we establish a coreactant-free ECL aptasensor for the sensitive detection of ATP, achieving an impressive low detection limit of 0.033 nM. This study not only demonstrates the successful combination of ECL with controlled release strategies but also opens new avenues for developing highly efficient MOFs-based ECL systems.

Coherent arrangement of perylene diimide derivative via adhesion-controlled transfer for noise-suppressed light signal detection

The coherent arrangement of NPDI is successfully processed using molecule interaction to produce a uniform surface. This process leads to effective trap density suppression resulting in high performance and clean signals from optoelectronics.

An advanced ratiometric molecularly imprinted sensor based on metal ion reoxidation for indirect and ultrasensitive glyphosate detection in fruit.

An indirect and ultrasensitive ratiometric molecularly imprinted (MIP) sensor, based on metal ion reoxidation, is introduced for glyphosate (GLY) determination in fruit. As high-performance signal amplification substrates, carbon nanotubes (MWCNTs) and gold nanoparticles (AuNPs) are conveniently modified on GCE. The artificial antibody-MIP membrane, presents typical three-dimensional structure to GLY template. Built-in reference methylene blue (MB) is directly electropolymerized on MWCNTs-Au/GCE. Particularly, Cu2+ and GLY interestingly form chelate complex, and the Cu2+ (ICu) in Cu(Ⅱ)-GLY-complex can be reoxidized, and indirectly quantizes GLY. The reference signal (IMB) presents noteworthy stability with different GLY levels, and the ratiometric readout (ICu/IMB) is recognized as a more trustworthy indicator to quantize GLY. Proposed sensor presents broad range as 1.73∼400ng/mL, and limit of detection is well found as 0.24ng/mL (S/N=3). Finally, as-fabricated method is verified with standard HPLC in real-fruit-sample, and the errors and recovery rates are calculated as 3.4%∼6.7% and 94.4%∼104.6%, respectively.

Halloysite nanotubes-loaded conductive polymer as substrate and label material for sensitive detection of amyloid-β protein by electrochemical immunosensor

Amyloid-beta protein (Aβ) is a unique biomarker for Alzheimer's disease (AD). The sandwich-type electrochemical immunosensor, one of the key tools for detecting biomarkers, relies on a high-performance signal amplification approach to enhance its sensitivity. Ni/PdH nanodendrites (Ni/PdH NDs) have increased catalytic activity due to their unique interaction with palladium hydride and their nickel-rich surface, tunable shape and high specific surface area. Modified halloysite nanotubes (mHNT)-loaded with polypyrrole (PPy@mHNT) possess excellent dispersion and a large surface area. This enables the formation of a conductive network to prevent the accumulation of Ni/PdH NDs. Additionally, it exposes more electrocatalytic active centers, effectively amplifying electrical signals. By utilizing Ni/PdH@PPy@mHNT as the labeling material, it shows a consistent and remarkable electrocatalytic activity in H2O2 reduction, leading to signal amplification. The acid-etched HNT coated with polyaniline (PANI@eHNT) exhibits an exceptionally low background signal and outstanding conductivity. This not only accelerates electron transfer on the electrode surface, but also ensures the stable incubation of biomolecules post-amino grafting. Utilizing NH2-PANI@eHNT as a substrate material can guarantee stable biomolecule incubation, offer a stable sensing platform and enhance immunosensor performance. The signal can be amplified and the immunosensor's sensitivity can be raised through the efficient cooperation of the aforementioned nanomaterials. Under optimum circumstances, the electrochemical immunosensor had the lowest detection limit of 5.53 fg mL−1 and a linear range of 50 fg mL−1 to 100 ng mL−1. Based on the outstanding performance previously mentioned, this immunosensor is anticipated to aid in the early detection of AD.

Empowering 5G and Beyond: Advanced Multiband Signal Generation and High-Performance Signal Synthesis Techniques for Communications and Sensing Systems [From the Guest Editor’s Desk

Empowering 5G and Beyond: Advanced Multiband Signal Generation and High-Performance Signal Synthesis Techniques for Communications and Sensing Systems [From the Guest Editor’s Desk

Creating Stretchable Electronics from Dual Layer Flex-PCB for Soft Robotic Cardiac Mapping Catheters

The authors present in this study the development of a novel method for creating stretchable electronics from dual-layer flex printed circuit boards (flex-PCBs) as a platform for soft robotic sensor arrays (SRSAs) for cardiac voltage mapping applications. There is a crucial need for devices that utilize multiple sensors and provide high performance signal acquisition for cardiac mapping. Previously, our group demonstrated how single-layer flex-PCB can be postprocessed to create a stretchable electronic sensing array. In this work, a detailed fabrication process for creating a dual-layer multielectrode flex-PCB SRSA is presented, along with relevant parameters to achieve optimal postprocessing with a laser cutter. The dual-layer flex-PCB SRSA’s ability to acquire electrical signals is demonstrated both in vitro as well as in vivo on a Leporine cardiac surface. These SRSAs could be extended into full-chamber cardiac mapping catheter applications. Our results show a significant contribution towards the scalable use of dual-layer flex-PCB for stretchable electronics.

Influence of Signalling Systems on the Capacity of Railways by Lines and Nodes Assessment Methods

In the complex railway networks characterized by mixed traffic, a key focus is the increase of railway capacity by high-performance signaling systems, including ETCS/ERTMS and beyond. Nevertheless, the estimation of effects on the headway of the introduction of innovations in signaling systems is not consolidate for complex networks.This study highlights several challenges in the line-node capacity calculation of congested networks considering a combined effect of routes conflicts in the station on lines and propagation in stations of delays suffered along the lines. The paper describes some results of the ongoing research based on the integrated use of analytical methods and simulation to networks controlled by different standard signaling systems and able to increase the capacity under specific operational conditions.The paper introduces the application of the methods to the complex mixed-traffic network nearby the Trieste railway node, situated in Northeastern Italy, including the main passengers and freight terminals and the lines operated for both services. The objective is to identify the most appropriate technological solutions and methodological approaches for the optimization of the network capacity and the minimization of delays.

Detection of Uniform Gearbox Wear in Induction Motors Based on the Analysis of Stray Flux Signals Through Statistical Time-Domain Features and Dimensionality Reduction Techniques

Gearboxes are core elements in power transmission systems. Although gearboxes are reliable and high-efficiency components, the occurrence of different faults is frequent since they are often subjected to adverse operating conditions. Classical gearbox condition monitoring approaches are based on the analysis of vibration and current motor signals and rely on the identification of specific fault-related frequency patterns. In this regard, this article proposes a novel diagnosis methodology based on the analysis of stray flux signals for detecting uniform wear in the gear teeth. The proposed methodology is based on the processing of the stray flux signals through feature calculation and extraction stages that lead to a high-performance signal characterization by estimating a set of statistical time domain-based features and then reducing the dimensionally by means of the principal component analysis and linear discriminant analysis techniques. Additionally, an automatic fault diagnosis is achieved through a neural network-based classifier for the detection and identification of uniform wear in a gearbox. The obtained results prove the potential of the proposal for its incorporation in condition maintenance programs in the industry, becoming an excellent alternative to classical approaches.

A survey of 3D printing technology applied to paper microfluidics.

Paper microfluidics is a rapidly growing subfield of microfluidics in which paper-like porous materials are used to create analytical devices that are well-suited for use in field applications. 3D printing technology has the potential to positively affect paper microfluidic device development by enabling tools and methods for the creation of devices with well-defined and tunable fluidic networks of porous matrices for high performance signal generation. This critical review focuses on the progress that has been made in using 3D printing technologies to advance the development of paper microfluidic devices. We describe printing work in three general categories: (i) solid support structures for paper microfluidic device components; (ii) channel barrier definition in existing porous materials; and (iii) porous channels for capillary flow, and discuss their value in advancing paper microfluidic device development. Finally, we discuss major areas of focus for highest impact on the next generation of paper microfluidics devices.

VR-PRUNE: Decidable Variable-Rate Dataflow for Signal Processing Systems

The dataflow concept has been successfully used for modeling and synthesizing signal processing applications since decades, and recently, dataflow has also been discovered to match the computation model of machine learning applications, leading to extremely successful dataflow based application design frameworks. One of the most attractive features of dataflow, especially for signal processing, is related to its formal nature: when properly defined, a dataflow-based application model can be analytically verified for correctness at the stage of application design. This paper proposes VR-PRUNE, a novel dataflow model of computation that is aimed for design of high-performance signal processing software, together with runtime support that allows efficient application deployment to heterogeneous GPU-equipped platforms. Compared to prior work, VR-PRUNE features variable token rate processing, which enables designing adaptive signal processing applications, and implementing solutions that, e.g., allow trading-off between power consumption and filtering bandwidth at runtime. The paper presents the formal concepts of VR-PRUNE, as well as four application examples from domains related to signal processing, accompanied with quantitative results, which show that using VR-PRUNE enables, for example, application power-performance scaling, and on the other hand describing adaptive application behavior with 59% fewer dataflow graph components compared to previous work.

Method for Analyzing Bit Error Rates (BERs) of Nonlinear Circuits and Systems for High-Performance Signaling

Bit error rate (BER) is an important figure of merit to evaluate the performance of a communication system. Analyzing the BER of a linear-time-invariant system has been extensively studied. However, analyzing the BER of nonlinear circuits and systems is challenging because it cannot rely on linear time invariant (LTI) principles, while an exhaustive nonlinear simulation is computationally prohibitive. To find BER, an exhaustive approach requires nonlinear simulations of $2^m$ bit patterns for a channel of m-bit memory, where m can be larger than 100 in today's high-speed and high-performance design. In this work, we develop a fast and accurate method to analyze the BER of large-scale nonlinear circuits. Only O(k) nonlinear simulations are required, with k much less than 2^m and independent of $2^m$ . While performing O(k) nonlinear simulations only, we find a method to determine the probability density function of the nonlinear responses, from which accurate BER results can be obtained. An error assessment method is also developed to evaluate the true error of the nonlinear signaling analysis without the need for knowing the entire nonlinear responses of the channel. Simulations of large-scale real-world nonlinear circuits have demonstrated the accuracy, efficiency, and capacity of the proposed method. A BER as low as $10^{-56}$ is accurately predicted.

DNAzyme based dual signal amplification strategy for ultrasensitive myocardial ischemia related MiRNA detection

Abnormal expression of microRNAs (miRNAs) is closely associated with a diverse of important biological processes, such as metastasis, myocardial ischemia and progression. Development of a facile and enzyme-free method for sensitive miRNA detection remains a huge challenge. Herein, we proposed a cross-catalytic circuit for trace miRNA detection by facilely integrating hairpin catalytic reaction (HCR) and DNAzyme biocatalyst through an ingenious feedback loop. The DNAzyme functional part was originally grafted in the designed hairpin structure probes, which would be released from hairpin structure probe and induce subsequent signal amplification after the recognition of target miRNA and the formation of double-strand DNA products. Through the dual signal amplification, the method exhibited a favorable detection sensitivity with a low of detection of 56 fM. These two indispensable catalytic reactions play vital roles in executing high-performance signal amplification, as demonstrated experimentally and theoretically.

Au\u2013Ag assembled on silica nanoprobes for visual semiquantitative detection of prostate-specific antigen

BackgroundBlood prostate-specific antigen (PSA) levels are widely used as diagnostic biomarkers for prostate cancer. Lateral-flow immunoassay (LFIA)-based PSA detection can overcome the limitations associated with other methods. LFIAbased PSA detection in clinical samples enables prognosis and early diagnosis owing to the use of high-performance signal reporters.ResultsHere, a semiquantitative LFIA platform for PSA detection in blood was developed using Au–Ag nanoparticles (NPs) assembled on silica NPs (SiO2@Au–Ag NPs) that served as signal reporters. Synthesized SiO2@Au–Ag NPs exhibited a high absorbance at a wide wavelength range (400–800 nm), with a high scattering on nitrocellulose membrane test strips. In LFIA, the color intensity of the test line on the test strip differed depending on the PSA concentration (0.30–10.00 ng/mL), and bands for the test line on the test strip could be used as a standard. When clinical samples were assessed using this LFIA, a visual test line with particular color intensity observed on the test strip enabled the early diagnosis and prognosis of patients with prostate cancer based on PSA detection. In addition, the relative standard deviation of reproducibility was 1.41%, indicating high reproducibility, and the signal reporter showed good stability for 10 days.ConclusionThese characteristics of the signal reporter demonstrated the reliability of the LFIA platform for PSA detection, suggesting potential applications in clinical sample analysis.

Compact polarimetric heterodyning DBR fiber laser sensor with high temperature resistance.

We report on a short-cavity polarization beat-frequency distributed Bragg reflector (DBR) fiber laser that can operate in an unprecedentedly wide range of temperatures from -200∘ C to 500°C. The beat-frequency signal inherited by the intrinsic fiber birefringence enables implementation of the laser as an eligible temperature or hydrostatic pressure sensor. Furthermore, type-IIa Bragg reflectors allow the annealing of high temperature on the laser cavity to suppress the phase noise of the lasing signal effectively. This research will guide future attempts to achieve high-precision sensing and high-performance signal generation using polarized beat-frequency DBR fiber lasers in harsh environments.

A Signal Engine for a Live Coding Language Ecosystem

This paper reports on early advances in the design of a browser-based ecosystem for creating new live coding languages, optimal for audio synthesis, machine learning, and machine listening. We present the rationale and challenges when applying the Web Audio API to the design of a high-performance signal synthesis engine, using an AudioWorklet-based solution and refactoring our digital signal processing library Maximilian.js. Furthermore, we contribute with the latest advances in Sema, a new user-friendly playground that integrates the signal engine to empower the live coding community to design their own idiosyncratic languages and interfaces. The evaluation shows that the system runs with high reliability and efficiency and low latency.

A Low-Power On-Chip ECG Monitoring System Based on MWCNT/PDMS Dry Electrodes

Wearable technologies have established novel strategies for continuous electrocardiogram (ECG) monitoring, exploiting recent developments in sensors and integrated circuit technology. Advances in dry electrodes fabrication improved the growth of wearable devices. Herein, we present an on-chip integrated ECG signal acquisition system along with dry electrodes for wearable and long-term monitoring. Custom electrodes are fabricated using multi-walled carbon nanotube (MWCNT) and Polydimethylsiloxane (PDMS) composite on a flexible substrate. A $1.5~\mu \text{W}$ fully-differential operational transconductance amplifier (OTA) with a capacitive-resistive feedback network is designed in 130 nm CMOS process achieving a mid-band gain of 43.09 dB and an input-referred noise of $2.81~\mu \text{V}_{\textit {rms}}$ in the range from 0.175 Hz to 1.636 kHz. Reconfigurability of the lower cut-off frequency is achieved by controlling the bias voltage of the triple-well nMOS transistors acting as the feedback pseudoresistor. Electrodes with different surface area and MWCNT concentrations were investigated in a real-time ECG measurement scenario. The recorded signals achieve a high signal-to-noise ratio which spans from 35.7 dB to 38.6 dB with the increasing MWCNT concentration. Experimental results demonstrate that the proposed system allows for high performance and low-power ECG signal recording for the long-term and wearable applications.