Signal Source Research Articles

Photonic Terahertz Chaos Enabling High‐Precision and Unambiguous Ranging

AbstractTerahertz (THz, 0.3–10 THz) radar systems have garnered significant attention due to their superior capabilities in high‐precision and robust sensing. However, the susceptibility to jamming, along with the sensing precision loss and ranging ambiguity induced by inflexible implementation of the conventional radar signal source, presents major challenges to the practical deployment of THz radars. Herein, a flexible photonic chaotic radar system is proposed at the THz band and investigate the ranging performance in precision and ambiguity. The photonic heterodyne detection scheme facilitates the generation of optoelectronic feedback loop‐based THz chaos at 300 GHz, achieving a seamless connection between THz domains and optical domains. The system is experimentally demonstrated its superior performance of sub‐centimeter resolution with 0.9345 cm and ranging unambiguity simultaneously. This work bridges the THz gap in the practical deployment of chaos theory and will pave the way for a new regime of THz radar empowered by chaos.

Spatial Correlations Based Fault Tolerant Source Localization Using Wireless Sensor Networks

The source localization is a process to determine the location of a signal source based on measurements from sensor nodes or receivers that are spatially distributed in the area around the source. Localizing intruders and mobile users are some of the utilizations of wireless sensor networks (WSNs) based source localization problem. However, sensor faults and channel noise are the important issues that degrade the source localization performances of the systems. In this paper, we significantly study and improve our recent results; the representative fault tolerant hitting set and feature selection approaches for localizing a source in a decentralized WSN using the faulty sensor nodes and channel noise. First, we propose a technique to place some active sensor nodes in the sleep state such that the source localization performances of the hitting set and feature selection approaches do not significantly degrade. The proposed technique takes advantage of spatial correlations among sensor nodes, where nearby sensor nodes provide same decisions to the fusion center with a high probability. We observe that the performance gap for the results with and without sleeping sensor nodes decreases by increasing total sensor nodes. In addition, we improve our recent results by proposing a technique based on spatial correlations among sensor nodes to minimize the impact of channels’ noises, especially for a higher fault probability of sensor nodes. Finally, extensive simulations on synthetic and real-world data sets validate our theoretical results.

KRASG12D drives immunosuppression in lung adenocarcinoma through paracrine signaling.

Lung cancer is the leading cause of cancer deaths in the United States. New targeted therapies against the once-deemed undruggable oncogenic KRAS are changing current therapeutic paradigms. However, resistance to targeted KRAS inhibitors almost inevitably occurs; resistance can be driven by tumor cell-intrinsic changes or by changes in the microenvironment. Here, we utilized a genetically engineered mouse model of KRASG12D-driven lung cancer that allows for inducible and reversible expression of the oncogene: activation of oncogenic KRASG12D induces tumor growth; conversely, inactivation of KRASG12D causes tumor regression. We showed that in addition to regulating cancer cell growth and survival, oncogenic KRAS regulated the transcriptional status of cancer-associated fibroblasts and macrophages in this model. Utilizing ex vivo approaches, we showed that secreted factors from cancer cells induced the expression of multiple cytokines in lung fibroblasts, and in turn drove expression of immunosuppressive factors, such as arginase 1, in macrophages. In summary, fibroblasts emerged as a key source of immune regulatory signals, and a potential therapeutic target for improving the efficacy of KRAS inhibitors in lung cancer.

Noninvasive intracranial source signal localization and decoding with high spatiotemporal resolution

Noninvasive intracranial source signal localization and decoding with high spatiotemporal resolution

How are brands associated by users in short videos-A study on the mechanism of user associations with brand placements in short videos based on signal theory.

The emergence of short video platforms has opened new avenues and opportunities for brand marketing. This paper investigates the mechanisms of brand dissemination in short videos, examining strategies for fostering brand associations to fulfill communication objectives. Drawing on signal theory, the study identifies the perceived value of short videos as the source of signals, with brand value and transparency serving as mediating factors, and brand association as the outcome. The research employs hypothesis testing and model building, supplemented by analysis of 560 valid questionnaires from research platforms, to scrutinize these mechanisms. Findings suggest that brand transparency and value effectively mediate the relationship between the perceived value and brand association, with brand transparency also mediating between perceived personality, utility, and brand association. Finally, this paper outlines management implications and acknowledges limitations based on the results.

Online Continuous Monitoring of Time Domain Parameters of Heart Rate Variability Using MATLAB and Its Implementation on Human and Rat Electrocardiogram Data

The project calculates the heart rate variability using the variation in the consecutive R peaks in the electrocardiogram signals. The code can calculate various dependent factors based on the calculated R peak orientation. Meanrespiratory rate (RR), SD of NN (normal-to-normal)intervals (SDNN), mean heart rate, SD of heart rate, root mean square of successive differences between adjacent RR intervals (RMSSD), number of pairs of successive NN intervals that differ by more than 50 milliseconds (NN50), percentage of NN50 (pNN50), RR triangular index, and triangular interpolation of NN interval histogram (TINN) are the respective outputs of the project. Apart from the calculated parameters (mentioned above), several graphs are plotted at continuous time intervals. These graphs include the continuous plotting of the electrocardiogram signal with detected R peaks over time. Second, a tachogram of the time difference between consecutive R peaks and time is calculated. A separate graph for magnitude and frequency is also plotted. These data are used to govern fundamental as well as complex analogies about the signal source. The tachogram is fundamentally used to observe the behavioral change in the source. Observing the tachogram in the time domain can also help study intense emotions and calmness.

Detection properties of indium-111 and IRDye800CW for intraoperative molecular imaging use across tissue phantom models.

Intraoperative molecular imaging (IMI) enables the detection and visualization of cancer tissue using targeted radioactive or fluorescent tracers. While IMI research has rapidly expanded, including the recent Food and Drug Administration approval of a targeted fluorophore, the limits of detection have not been well-defined. The ability of widely available handheld intraoperative tools (Neoprobe and SPY-PHI) to measure gamma decay and fluorescence intensity from IMI tracers was assessed while varying characteristics of both the signal source and the intervening tissue or gelatin phantoms. Gamma decay signal and fluorescence from tracer-bearing tumors (TBTs) and modifiable tumor-like inclusions (TLIs) were measured through increasing thicknesses of porcine tissue and gelatin in custom 3D-printed molds. TBTs buried beneath porcine tissue were used to simulate IMI-guided tumor resection. Gamma decay from TBTs and TLIs was detected through significantly thicker tissue and gelatin than fluorescence, with at least 5% of the maximum signal observed through up to 5 and 0.5cm, respectively, depending on the overlying tissue type or gelatin. We developed novel systems that can be fine-tuned to simulate variable tumor characteristics and tissue environments. These were used to evaluate the detection of fluorescent and gamma signals from IMI tracers and simulate IMI surgery.

Combined 7Li NMR, density functional theory and operando synchrotron X-ray powder diffraction to investigate a structural evolution of cathode material LiFeV2O7.

In our recent study, we demonstrated using 7Li solid-state Nuclear Magnetic Resonance (ssNMR) and single-crystal X-ray diffraction that the cathode LiFeV2O7 possesses a defect associated with the positioning of vanadium atoms. We proposed that this defect could be the source of extra signals detected in the 7Li spectra. In this context, we now apply density functional theory (DFT) calculations to assign the experimental signals observed in 7Li NMR spectra of the pristine sample. The calculation results are in strong agreement with the experimental observations. DFT calculations are a useful tool to interpret the observed paramagnetic shifts and understand how the presence of disorder affects the spectra behavior through the spin-density transfer processes. Furthermore, we conducted a detailed study of the lithiated phase combining operando synchrotron powder X-ray diffraction (SPXRD) and DFT calculations. A noticeable volume expansion is observed through the first discharge cycle which likely contributes to the enhanced lithium dynamics in the bulk material, as supported by previously published ssNMR data. DFT calculations are used to model the lithiated phase and demonstrate that both iron and vanadium participate in the redox process. The unusual electronic structure of the V4+ exhibits a single electron on the 3dxy orbital perpendicular to the V-O-Li bond being a source of a negative Fermi contact shift observed in the 7Li NMR of the lithiated phase.

Working memory needs pointers.

Cognitive neuroscience has converged on a definition of working memory (WM) as a capacity-limited system that maintains highly accessible representations via stimulus-specific neural patterns. We argue that this standard definition may be incomplete. We highlight the fundamental need to recognize specific instances or tokens and to bind those tokens to the surrounding context. We propose that contextual binding is supported by spatiotemporal 'pointers' and that pointers are the source of neural signals that track the number of stored items, independent of their content. These content-independent pointers may provide a productive perspective for understanding item-based capacity limits in WM and the role of WM as a gateway for long-term storage.

Obstacle-enhanced spontaneous oscillation of confined active granules.

Spontaneous oscillation in particle numbers has been reported recently, in which two chambers connected by a narrow channel are alternately filled and emptied by self-propelled particles. The challenge in realizing the application of this oscillation lies in promotion of the oscillatory periodicity. By placing an asymmetric obstacle at an appropriate position near a channel opening, we can significantly improve the oscillation quality, which approaches the quality of an ideal oscillation. Additionally, we experimentally explore the relationship between the oscillation quality and various system parameters such as the obstacle position. Based on experimental observations, we incorporate a random noise into our previous model and properly reproduce the experimental results. The agreement between theory and experiment uncovers the mechanism of delicate competition between noise and unidirectional particle flow in influencing the oscillation quality. Our findings provide new insights for the optimization of the oscillation quality, expand the conventional rectification capability of the ratchet effect due to the obstacle, and make it possible for spontaneous oscillation to serve as a reliable source for rhythmic signals.

Fatty acid carbon isotopes as tracers of trophic structure and contaminant biomagnification in Arctic marine food webs.

Mercury (Hg) and persistent organic pollutant (POP) accumulation among species and biomagnification through food webs is typically assessed using stable isotopes of nitrogen (δ15N) and carbon (δ13C) in bulk (whole) tissues. Yet, bulk isotopic approaches have limitations, notably from the potential overlap of isotope values from different dietary sources and from spatial variation in source (baseline) signals. Here, we explore the potential of fatty acid carbon isotopes (FA δ13C) to (1) evaluate the trophic structure of a marine food web, (2) distinguish feeding patterns among four marine mammal consumers, (3) trace contaminant biomagnification through a food web, and (4) explain interspecific variation in contaminants among high-trophic position predators. In the Cumberland Sound (CS) food web of Nunavut, Canada, ranging from zooplankton to Greenland shark (Somniosus microcephalus), FA δ13C values for the monounsaturated FAs, 20:1 and 22:1 isomers, did not vary across the food web, while the long-chain polyunsaturated FA, 22:6n3 showed δ13C values that were enriched by ~1.5‰ with each trophic position. Values of δ13C for shorter-chain and saturated FAs varied widely across this food web. In East Greenland (EG) marine mammals, FA δ13C values were significantly higher in migratory sub-Arctic species relative to Arctic residents. Linear models using FA δ13C as explanatory variables for contaminant concentrations demonstrated that baseline-corrected δ13C values of certain dietary FAs explained more variation in POP concentrations than did bulk stable isotopes in EG marine mammals. However, bulk δ15N better explained Hg variation in the CS food web. This study details the FA δ13C instrumental methods, such that other researchers can test this novel approach on other species, locations, and food webs to further evaluate whether the δ13C values of certain diet-derived FAs consistently show limited or predictable trophic fractionation and may therefore be useful for assessing the accumulation and biomagnification of lipophilic contaminants.

A DAQ system with low-dead-time, high-precision TDC for APD detection efficiency calibration

Correlated photon calibration based on spontaneous parametric down-conversion (SPDC) provides a highly precise means to calibrate the detection efficiency of avalanche photodiode (APD). During the calibration process of detection efficiency via SPDC, precise measurement of the arrival time of correlated photons and accurate photon counting are essential. To achieve this goal, a data acquisition (DAQ) system with low-dead-time, high-resolution Time-to-Digital Converter (TDC) was designed in this paper. This TDC is designed based on tapped delay line (TDL), which is implemented on Xilinx Kintex-7 series field programmable gate array (FPGA). This TDC can accurately measure the time of arrival of input signals. Upon arrival of a photon signal, the TDC rapidly generates a timestamp to record the arrival time of the photon signal. Utilizing these timestamps, time delay and accurate measurements of time intervals can be achieved. The specially designed TDC input stage structure and encoding algorithm enable the alternating propagation and sampling of `01' and `10' transitions on TDL. Coupled with a pipelined architecture, the TDC's dead time is close to one clock cycle, which is 2.33 ns in the current implementation version. The structure of mode recognition and triggering ensures that the TDC can correctly calibrate time measurements and count photon counts. Experimental results show that the TDC achieves an RMS precision of better than 11.08 ps, and this measurement precision is maintained over long time intervals (0–10 us). The reliability of this DAQ for photon counting has been verified through standard signal sources.

Measurement system construction of transient waveform signal source

Measurement system construction of transient waveform signal source

Optimizing the identification of long-interval intracortical inhibition from the dorsolateral prefrontal cortex.

This study aimed to optimally evaluate the effect of the long-interval intracortical inhibition (LICI) in the dorsolateral prefrontal cortex (DLPFC) through transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) by eliminating the volume conductance with signal source estimation and using a realistic sham coil as a control. We compared the LICI effects from the DLPFC between the active and sham stimulation conditions in 27 healthy participants. Evoked responses between the two conditions were evaluated at the sensor and source levels. At the sensor level, a significant LICI effect was confirmed in the active condition in the global mean field power analysis; however, in the local mean field power analysis focused on the DLPFC, no LICI effect was observed in the active condition. However, in the signal source estimation analysis for the DLPFC, we could reconfirm a significant LICI effect (p=0.023) in the interval 30-250ms post-stimulus, compared to the sham condition. Our results demonstrate that application of realistic sham stimulation condition and source estimation method allows for a robust and optimal identification of the LICI effect in the DLPFC. The optimal DLPFC-LICI effect was identified by the use of the sophisticated sham coil.

Research and Design of Sine Wave and Square Wave Signal Generator

In modern electronic systems, signal generators are widely used in fields such as communication, signal processing, and automatic control systems. High-quality signal sources are key to ensuring system stability and reliability, especially in testing and measurement processes. Traditional signal generators often use complex hardware designs and costly dedicated chips, making it difficult to meet the cost and size requirements for mid- to low-frequency applications. Therefore, it is important to design a simple, cost-effective, and high-performance signal generator based on general-purpose operational amplifiers. In response to this need, this paper designs and implements a sine wave and square wave signal generator based on the UA741 operational amplifier, with a focus on adjustable control of signal frequency and duty cycle. By optimizing the design of the RC oscillation circuit and feedback network, the sine wave generator can output high-quality signals with low distortion, while the square wave generator achieves flexible duty cycle adjustment via adjustable resistors. Simulation results show that these circuits exhibit good stability and flexibility, making them suitable for communication, signal processing, and automatic control systems. Despite achieving the desired results, further research is needed in component selection and circuit optimization to improve precision and adaptability. Future work will focus on the automation of circuit adjustment mechanisms and performance validation under extreme conditions to meet more demanding application needs.

Construction of colorimetric-fluorescent dual-signal aptamer-based assay using COF-Au nanozyme and magnetic nanoparticle-based CdTe quantum dots for sensitive zearalenone determination.

Adual-signal aptamer-based assay utilizing colorimetric and fluorescence techniques was developed for the determination of zearalenone (ZEN). The CdTe quantum dots, serving as the fluorescent signal source, were surface-modified onto Fe3O4@SiO2 and subsequently functionalized with the aptamer. The COF-Au was modified with complementary chain, which possessed peroxide (POD)-like enzyme properties, and could catalyze the peroxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to ox TMB, resulting in the generation of colorimetric signals. The two parts were merged based on the principle of base complementary pairing, resulting in an assembled structure exhibiting a diminished fluorescence signal due to the Förster resonance energy transfer (FRET) effect. Due to the higher affinity of the aptamer towards the target, the presence of ZEN resulted in the detachment of COF-Au, leading to an increase in supernatant concentration of COF-Au proportional to ZEN concentration. Consequently, this enhanced thecatalytic ability and amplified thecolorimetric signal. The fluorescence of precipitation increased simultaneously with the reduction of FRET, enabling linear detection of colorimetry in the range 0.5 ~ 10,000μg·kg-1 and fluorescence in the range 0.1 ~ 10,000μg·kg-1, with respective detection limits of 0.36μg·kg-1 and 0.09μg·kg-1. The spike recovery in wheat flour and corn ranged from 93.4 to122.0%. This technology was simple to operate and had low cost and good application prospects.

Effectiveness and Characteristics of Virtual Antennas in the Multiple Signal Classification Algorithm

This paper proposes a novel direction of arrival (DoA) estimation method based on the Multiple Signal Classification (MUSIC) algorithm using virtual antennas. The MUSIC method is a widely used DoA estimation technique known for its high accuracy and high resolution. However, it has a fundamental limitation: when the necessary condition of having more antenna elements at the base station than users is not met, DoA estimation becomes infeasible. To address this limitation, we introduce the concept of virtual antennas, allowing DoA estimation, even under restricted conditions. Virtual antennas are not physically present but can be virtually arranged, enabling the generation of virtual-received signals similar to those of real array antennas. Through simulation experiments, we demonstrate that our approach enables DoA estimation with the MUSIC algorithm even when its necessary conditions are not satisfied. Additionally, this paper explores the characteristics of virtual antennas in detail. We conduct simulation experiments to examine the differences in estimation accuracy between real and virtual antennas, as well as the impact of virtual antenna arrangement and count on estimation accuracy. The results show that, although virtual antennas provide lower estimation accuracy compared to real antennas, their flexible arrangement allows for improved resolution when signal sources are closely spaced by increasing the spacing between virtual antennas. Furthermore, under Additive White Gaussian Noise (AWGN) conditions, increasing the number of virtual antennas enhances estimation accuracy.

Study of autotransformer bridges for measurements of the impedance parameters

The analysis of the existing impedance measurement methods showed that for the establishment of precision comparators that operate in a wide range of values in the audio frequency range, it is best to use transformer and autotransformer bridges. Autotransformer bridges are used for measurements in a wide range of the impedance values. The use of autotransformer bridges allows reducing the measurement error to 10–7–10–9. High metrological characteristics of transformer bridge circuits make it possible to use them in commercial devices and precision measuring equipment. Simple autotransformer bridges do not provide the opportunity to measure the impedance parameters in a wide range of values of the tangent of the loss angle (phase shift). For the synthesis of measuring circuits of bridges and their balancing, it is necessary to have a precision quadrature channel that will ensure high accuracy of the transmission coefficient both by phase and by module. The structures of universal autotransformer comparators and their properties are determined by two main factors: by the method of forming the source of the complex balancing signal and by the types of schemes for replacing the impedances of the compared objects. To determine ways to improve universal precision impedance comparators based on autotransformer bridges, it is necessary to develop and analyze mathematical models of universal comparators. The conducted theoretical analysis showed that in the process of comparison, it is possible to compare impedances with different substitution schemes with a direct reading of reactive and active parameters. By choosing the appropriate transmission direction, with a simple reconstruction of the measuring circuit, it is possible to compare two impedances with a parallel substitution scheme, two impedances with a series substitution scheme, or two impedances with a different substitution scheme. The obtained results made it possible to implement them in a universal autotransformer-comparator bridge.

Rapid and Visual Detection of Urinary Pathogens by Employing Bifunctional Deoxyribonucleic Acid Sensors and Aggregation of Gold Nanoparticles.

A simple, rapid, and visual approach is developed to perform diagnosis of urinary tract infection (UTI) and antimicrobial susceptibility testing (AST) by employing smart bifunctional DNA (bfDNA) sensors, exonuclease III, concatermers of CuO nanoparticles (CuONPs), and gold NPs (AuNPs) aggregation [AuNPs agglutination (AA)], namely, the bfDEC-AA method. The bfDNA sensors serve as probes for identifying 16S rRNA genes of bacterium or 18S rRNA of fungus and as mediators connecting the concatermers of CuONPs. The AA as a signal source is triggered by Cu(I)-catalyzed azide-alkyne cycloaddition click chemistry. In this study, the urine samples are analyzed directly, eliminating the need for overnight incubation or bacterial isolation. A crucial color change from red to purple occurs at the UTI diagnostic threshold of 104 CFU mL-1; thus the results of UTI diagnosis can be qualitatively interpreted by the unaided eyes. Similarly, AST was performed visually under our optimal conditions. The color shift can also be quantified using a point-of-care (POC) device. UTI identification, bacteria strain identification, and AST were achieved within 55, 55, and 145 min for 96 samples, respectively. Here, 128 urine samples from suspected UTI patients were tested. Notably, the sensitivity and specificity of our method were 99% and 100% for Gram-negative bacteria (G-) infection, 100% and 100% for Gram-positive bacteria (G+) infection, and 98% and 100% for AST, respectively. Furthermore, the low cost of our POC device (US$156) is friendly to underdeveloped regions.

Space-Frequency Processing Methods for Satellite Navigation Signals

Relevance. Quite low power of the global satellite navigation systems’ useful informational signals near the Earth surface along with an ongoing noticeable increase of the number of easily available and efficient portable means of blocking wideband energetic interference radiation make the problem of radionavigational satellite devices antijamming capabilities improvement especially relevant both from practical and scientific points of view. Therefore, the goal of this research was to increase the antijamming capabilities of the global satellite navigation systems via processing of the corresponding receiving apparatus’ input signals by special spatial filters. To achieve the work goal the scientific task of researching on the antijamming capability improvement in radionavigational devices by means of space-frequency signal processing was solved. The methods used. During the research, different spatial signal processing algorithms were considered, among them both the ones functioning without any information about interference situation, external with respect to the receiving radionavigational system, and the ones using the knowledge about the number and relative disposition of the jamming sources. Additionally different methods of interference sources number and angular directions finding were studied, as well as modern cost function optimization algorithms which are used for signal sources’ location determination. Scientific novelty of this work consists of usage of new algorithms that implement separate signal processing stages and that provide necessary information to the filtering algorithms during the problem solution, as well as of combining known methods with new approaches to their design. The results. During the scientific task solution, the performance quality metrics comparison was carried out for all the considered algorithms via the computer modeling method that employed recordings of real satellite navigational signals with addition of varying number of uncorrelated energetic interferences sources. As a result of modeling, the performance quality measure values were obtained for all the investigated algorithms and the comparative analysis thereof was conducted, at the end whereof the methods with the best characteristics were picked out. The significance of the work results consists of possibility of using the considered algorithms in real antijamming satellite navigation devices design.