Two-way Signaling Research Articles

Second contribution to the knowledge of drumming signals of stoneflies from Corsica (Plecoptera: Nemouridae, Leuctridae and Perlodidae)

In this second article on drumming signals of Corsican stoneflies, the complete vibrational duets of three species are described. Protonemura corsicana (Morton, 1930) shows the typical signal pattern of other studied Protonemura species, a two-way exchange with monophasic grouped call and monophasic answer. In absence of direct female answer, when the male had participated in a previous duet, the male can make a second signal just after it call similar to the female answer (probably mimicking it). That could act as a stimulation for the female because, sometimes, the female answers after it. Leuctra fraterna Morton, 1930 males and females communicate with three-way or two-way signal exchanges. Call, answer, and reply are remarkably similar in structure, a signal composed by usually three parts with different rhythm (varied beat-interval signal type). The complete Isoperla insularis (Morton, 1930) duet is described. The male call is a repeated monophasic signal (call train), and the female answer is a one beat signal. A particular interaction between I. insularis males, producing an inter-male rejection signal, is also described.

Unmanned Airborne Bistatic Interferometric Synthetic Aperture Radar Data Processing Method Using Bi-Directional Synchronization Chain Signals

The bistatic Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of monostatic dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration. Unmanned aerial vehicles (UAVs) equipped with bistatic InSAR, having relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne bistatic InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne bistatic InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision bistatic InSAR imaging, and interferometric processing. Height inversion results based on the proposed method are also provided, which demonstrate the effectiveness of the proposed method in improving the accuracy of interferometric measurement at calibration points from 0.66 m to 0.42 m.

Loss of Neogenin alters branchial arch development and leads to craniofacial skeletal defects.

The formation of complex structures, such as the craniofacial skeleton, requires precise and intricate two-way signalling between populations of cells of different embryonic origins. For example, the lower jaw, or mandible, arises from cranial neural crest cells (CNCCs) in the mandibular portion of the first branchial arch (mdBA1) of the embryo, and its development is regulated by signals from the ectoderm and cranial mesoderm (CM) within this structure. The molecular mechanisms underlying CM cell influence on CNCC development in the mdBA1 remain poorly defined. Herein we identified the receptor Neogenin as a key regulator of craniofacial development. We found that ablation of Neogenin expression via gene-targeting resulted in several craniofacial skeletal defects, including reduced size of the CNCC-derived mandible. Loss of Neogenin did not affect the formation of the mdBA1 CM core but resulted in altered Bmp4 and Fgf8 expression, increased apoptosis, and reduced osteoblast differentiation in the mdBA1 mesenchyme. Reduced BMP signalling in the mdBA1 of Neogenin mutant embryos was associated with alterations in the gene regulatory network, including decreased expression of transcription factors of the Hand, Msx, and Alx families, which play key roles in the patterning and outgrowth of the mdBA1. Tissue-specific Neogenin loss-of-function studies revealed that Neogenin expression in mesodermal cells contributes to mandible formation. Thus, our results identify Neogenin as a novel regulator of craniofacial skeletal formation and demonstrates it impinges on CNCC development via a non-cell autonomous mechanism.

Sleep and longevity tied to glia.

Glia mediate two-way signaling between the brain and gut that supports sleep and healthy aging.

Neuropathic pain; what we know and what we should do about it.

Neuropathic pain can result from injury to, or disease of the nervous system. It is notoriously difficult to treat. Peripheral nerve injury promotes Schwann cell activation and invasion of immunocompetent cells into the site of injury, spinal cord and higher sensory structures such as thalamus and cingulate and sensory cortices. Various cytokines, chemokines, growth factors, monoamines and neuropeptides effect two-way signalling between neurons, glia and immune cells. This promotes sustained hyperexcitability and spontaneous activity in primary afferents that is crucial for onset and persistence of pain as well as misprocessing of sensory information in the spinal cord and supraspinal structures. Much of the current understanding of pain aetiology and identification of drug targets derives from studies of the consequences of peripheral nerve injury in rodent models. Although a vast amount of information has been forthcoming, the translation of this information into the clinical arena has been minimal. Few, if any, major therapeutic approaches have appeared since the mid 1990's. This may reflect failure to recognise differences in pain processing in males vs. females, differences in cellular responses to different types of injury and differences in pain processing in humans vs. animals. Basic science and clinical approaches which seek to bridge this knowledge gap include better assessment of pain in animal models, use of pain models which better emulate human disease, and stratification of human pain phenotypes according to quantitative assessment of signs and symptoms of disease. This can lead to more personalized and effective treatments for individual patients. Significance statement: There is an urgent need to find new treatments for neuropathic pain. Although classical animal models have revealed essential features of pain aetiology such as peripheral and central sensitization and some of the molecular and cellular mechanisms involved, they do not adequately model the multiplicity of disease states or injuries that may bring forth neuropathic pain in the clinic. This review seeks to integrate information from the multiplicity of disciplines that seek to understand neuropathic pain; including immunology, cell biology, electrophysiology and biophysics, anatomy, cell biology, neurology, molecular biology, pharmacology and behavioral science. Beyond this, it underlines ongoing refinements in basic science and clinical practice that will engender improved approaches to pain management.

Deep Reinforcement Learning Two-Way Transit Signal Priority Algorithm for Optimizing Headway Adherence and Speed

Transit Signal Priority (TSP) is a broadly used traffic signal control strategy designed for reducing transit delays at signalized intersections. Although recent TSP systems began to consider more objectives, TSPs that addressed transit reliability issues commonly focused on improving schedule adherence and were only able to reduce schedule delays by expediting buses. Buses running ahead of the schedule were not considered. This paper proposed a dual-objective two-way TSP algorithm (D2 TSP) using Deep Reinforcement Learning (DRL). D2 TSP concurrently optimizes transit delays and reliability (i.e., headway adherence) by expediting late buses or delaying early buses. Further, the DRL agents were enhanced with a coordination algorithm for an optimized solution balancing opposite directions. This D2 TSP reacts adaptively and efficiently to real-time bus performance using data provided by readily available technology (loop detector) at low communication frequencies. We trained and tested this algorithm in a stochastic microsimulation environment in Aimsun Next that modelled a transit route segment with reliability issues in the City of Toronto. The performance of D2 TSP was compared with four baseline scenarios, one without TSP, one with the current TSP algorithm used in the field in the City of Toronto, one conditional TSP with an arrival prediction model, and one using DRL agents with a First-Come-First-Served logic. D2 TSP demonstrated its advantages in providing an efficient and balanced solution in reducing headway variability and travel time for both directions.

High-Performance Acoustic Wave Sensor Based on PVDF-TrFE Membrane Combing the Piezoelectric and Fabry–Pérot Effects

We present a dual-channel resonance acoustic sensor based on a poly (vinylidene fluoride-co-trifluoroethylene) piezo-electric membrane which combines the Fabry-Pérot interference and piezoelectric effects. The deformation of circular thin films is indicated by interference and piezoelectric effects at the same time, and the noise level was decreased by real-time convolution of the two-way parallel signal. Studies reveal that at the film’s resonance frequency, the minimum detection limits for Fabry-Pérot interference and the piezoelectric impact on acoustic waves are 2.61 μPa/Hz <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/2</sup> and 15.64 μPa/Hz <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1/2</sup> , respectively. The result of the convolution shows that the background noise has been reduced by 98.81% in relation to the piezoelectric signal and by 96.73% in relation to the Fabry-Pérot interference signal, respectively. The signal-to-noise ratio of the convolution is several times greater than the other two signals at 2 mPa.

Self-Regulated and Bidirectional Communication in Synthetic Cell Communities.

Cell-to-cell communication is not limited to a sender releasing a signaling molecule and a receiver perceiving it but is often self-regulated and bidirectional. Yet, in communities of synthetic cells, such features that render communication efficient and adaptive are missing. Here, we report the design and implementation of adaptive two-way signaling with lipid-vesicle-based synthetic cells. The first layer of self-regulation derives from coupling the temporal dynamics of the signal, H2O2, production in the sender to adhesions between sender and receiver cells. This way the receiver stays within the signaling range for the duration sender produces the signal and detaches once the signal fades. Specifically, H2O2 acts as both a forward signal and a regulator of the adhesions by activating photoswitchable proteins at the surface for the duration of the chemiluminescence. The second layer of self-regulation arises when the adhesions render the receiver permeable and trigger the release of a backward signal, resulting in bidirectional exchange. These design rules provide a concept for engineering multicellular systems with adaptive communication.

PVDF Membrane-Based Dual-Channel Acoustic Sensor Integrating the Fabry–Pérot and Piezoelectric Effects

A resonant acoustic wave detector combined with Fabry-Pérot interference (FPI) and piezoelectric (PE) effects based on a polyvinylidene fluoride (PVDF) piezoelectric film was proposed to enhance the ability of the sensor to detect acoustic signals in a specific frequency band. The deformation of circular thin films was indicated by the interference and piezoelectric effects simultaneously, and the noise level was decreased by the real-time convolution of the two-way parallel signal. This study reveals that, at the film's resonance frequency, the minimum detection limits for the FPI and piezoelectric impacts on acoustic waves are 3.39 μPa/Hz1/2 and 20.8 μPa/Hz1/2, respectively. The convolution result shows that the background noise was reduced by 98.81% concerning the piezoelectric signal, and by 85.21% concerning the FPI signal. The convolution's signal-to-noise ratio (SNR) was several times greater than the other two signals at 10 mPa. Therefore, this resonance sensor, which the FPI and the piezoelectric effect synergistically enhance, can be applied to scenarios of acoustic wave detection in a specific frequency band and with ultrahigh sensitivity requirements.

CD206+ tendon resident macrophages and their potential crosstalk with fibroblasts and the ECM during tendon growth and maturation.

Resident macrophages exist in a variety of tissues, including tendon, and play context-specific roles in their tissue of residence. In this study, we define the spatiotemporal distribution and phenotypic profile of tendon resident macrophages and their crosstalk with neighboring tendon fibroblasts and the extracellular matrix (ECM) during murine tendon development, growth, and homeostasis. Fluorescent imaging of cryosections revealed that F4/80+ tendon resident macrophages reside adjacent to Col1a1-CFP+ Scx-GFP+ fibroblasts within the tendon fascicle from embryonic development (E15.5) into adulthood (P56). Through flow cytometry and qPCR, we found that these tendon resident macrophages express several well-known macrophage markers, including Adgre1 (F4/80), Mrc1 (CD206), Lyve1, and Folr2, but not Ly-6C, and express the Csf1r-EGFP ("MacGreen") reporter. The proportion of Csf1r-EGFP+ resident macrophages in relation to the total cell number increases markedly during early postnatal growth, while the density of macrophages per mm2 remains constant during this same time frame. Interestingly, proliferation of resident macrophages is higher than adjacent fibroblasts, which likely contributes to this increase in macrophage proportion. The expression profile of tendon resident macrophages also changes with age, with increased pro-inflammatory and anti-inflammatory cytokine expression in P56 compared to P14 macrophages. In addition, the expression profile of limb tendon resident macrophages diverges from that of tail tendon resident macrophages, suggesting differential phenotypes across anatomically and functionally different tendons. As macrophages are known to communicate with adjacent fibroblasts in other tissues, we conducted ligand-receptor analysis and found potential two-way signaling between tendon fibroblasts and resident macrophages. Tendon fibroblasts express high levels of Csf1, which encodes macrophage colony stimulating factor (M-CSF) that acts on the CSF1 receptor (CSF1R) on macrophages. Importantly, Csf1r-expressing resident macrophages preferentially localize to Csf1-expressing fibroblasts, supporting the "nurturing scaffold" model for tendon macrophage patterning. Lastly, we found that tendon resident macrophages express high levels of ECM-related genes, including Mrc1 (mannose receptor), Lyve1 (hyaluronan receptor), Lair1 (type I collagen receptor), Ctss (elastase), and Mmp13 (collagenase), and internalize DQ Collagen in explant cultures. Overall, our study provides insights into the potential roles of tendon resident macrophages in regulating fibroblast phenotype and the ECM during tendon growth.

A speech separation algorithm based on the comb-filter effect

In the field of speech separation, the traditional single-channel and multi-channel speech separation methods have made great progress. However, the accuracy of separation and automatic speech recognition(ASR) rate are not yet satisfactory. With the development of neural networks, some scholars began to use deep learning to achieve speech separation. Although this kind of method improves the accuracy of speech separation, it also leads to the need for pre-training the model, higher computational complexity and reduced separation performance when the model does not match the mixed signal. This paper has conducted an in-depth study on the scene of multi-speaker separation, and proposed a new dual-channel speech separation algorithm based on the Comb-Filter Effect (CFE). The CFE is an effect that occurs when a signal passes through a first-order differential microphone(FDM) array. And this effect is discovered and exploited for the first time. By using this effect, this paper designed a new signal spectrum estimation method that can realize accurate estimation of speech signal, and combined this method with traditional spectral subtraction to achieve the purpose of speech separation. Finally, this paper compared the proposed algorithm with the traditional FastICA-based algorithm and the fully-convolutional time-domain audio separation network(Conv-TasNet)-based algorithm. The results of simulation and comparison experiments show that the algorithm can effectively separate two-way speech signals while greatly reducing the computational complexity and has excellent robustness. In various situations, the proposed algorithm can obtain the Scale-Invariant Source-to-Noise Ratio improvement (SI-SNRi) of 9.19 dB on average. In addition, the Short-Time Objective Intelligibility (STOI) and Perceptual Evaluation of Speech Quality (PESQ) of the speech signal can be improved by an average of 33% and 70% or more respectively.

Skeletal muscle integrin expression in non-obese men with varying degrees of insulin sensitivity.

The remodeling of skeletal muscle extracellular matrix (ECM) components is related to the degree of insulin resistance (IR). Membrane receptors such as integrins provide two-way signaling ("inside-out" and "outside-in" signaling) between ECM components of skeletal muscle (e.g., collagen, laminin, fibronectin) and intracellular signaling pathways. The aim of the study was to analyze the relationship between the expression of integrins in skeletal muscle and insulin sensitivity (IS) in young, healthy, non-obese volunteers. We studied 36 healthy non-obese male participants. Subjects were divided into three subgroups on the basis of the hyperinsulinemic-euglycemic clamp: upper IS tertile, medium IS tertile, and lower IS tertile. Vastus lateralis muscle biopsies were performed before each clamp. Next, analysis of integrin mRNA expression was performed. Waist circumference, percent body fat, fasting serum insulin, total cholesterol, triglycerides and LDL-cholesterol were higher in the lower IS tertile subgroup compared to the other two subgroups (p < 0.05). The lower IS tertile showed increased expression of ITGA5, ITGA6, ITGA7, SPARC (p < 0.05) in comparison with the upper IS tertile and ITGA6 (p < 0.05) compared to the medium IS tertile. ITGA2, ITGA3, ITGA5, ITGA6, ITGA7, SPARC correlated inversely with IS (p < 0.05). Skeletal muscle integrin are associated with low IS in healthy nonobese men. Our data suggest that factors associated with ECM in muscle may be involved in modulation of insulin action even at the early stages of the development of IR.

High-precision comparison of time scales over fiber optic lines using satellite modems with additional tone modulation

The use of a new type of modems with pseudonoise coding and additional tone modulation designed to compare reference time scales over telecommunication geostationary satellites is considered. Experimental studies were carried out on the possibility of comparing time scales of hydrogen keepers from the State primary standard of unit of time, frequency and national time scale using these modems via an optical link. A fiber-optical lines of various lengths were used for a two-way signal transmission. The output radio-frequency signals of the modems connected to the optical transmitters at the ends of the fiber-optical lines were transmitted towards each other on an optical carrier with a wavelength of 1.55 μm. Demodulation of optical signals into the radio frequency range was carried out using optical receivers at the ends of fiber lines. The results of experimental evaluation of type A uncertainty by comparing time scales using fiber-optical lines with 50, 100, and 200 km of length are presented. For the 200 km line, the type A measurement uncertainty does not exceed 3 ps for one day of averaging interval. For the first time, it has been experimentally shown that the implementation of the method of time scales comparison using modems with pseudo-noise coding and additional tone modulation over 200 km of fiber line is possible without the intermediate optical amplifiers. The result opens up the prospect of creating cascaded systems for comparing time scales of remote standards via fiber-optic communication lines with a smaller number of intermediate optical amplifiers.

Coordinated Control Model for Oversaturated Arterial Intersections

In order to improve the traffic efficiency of oversaturated arterial traffic, a two-way signal coordinated control method is proposed. Taking traffic speeds, turning flow proportions and the number of lanes into consideration, a traffic flow model for oversaturated arterial is established on the basis of LWR theory, and vehicle trajectory data of arterials is used to verify this model. Then a coordinated control model for two-way oversaturated arterials is introduced, which is composed of a throughput maximization model and a delay minimization model. For the former one, the cycle length and green time at the arterial intersections are optimized to improve the arterial capacity, while the latter is built to realize the signal coordination of the consecutive intersections by optimizing offsets. A multi-objective algorithm is proposed to solve the coordinated control model. First, the throughput maximization model is solved by the standard algorithm of mixed-integer linear programming. Second, the feasible solutions of the signal orders are obtained by a phase pattern searching algorithm. Third, the delay minimization model is solved by a standard algorithm of quadratic programming model. Finally, the proposed model is used to coordinate and optimize the traffic signals on East Zhongshan Road containing 10 intersections in Nanjing, China. A trajectory-based simulation model is put forward to simulate the arterial traffic, demonstrating that the proposed coordinated control model can avoid the spillover and queue retention. After optimization, the capacity increases by 12.6% while the average vehicle delay for through vehicles drops by 23.6% compared to Synchro’s coordinated control.

How scientists interpret and address funding criteria: value creation and undesirable side effects

Scientists and funding bodies are interdependent actors involved in an ongoing two-way signalling interaction; however, we lack insight on the social mechanisms underpinning this interaction. To address this issue, we examine how successfully funded scientists interpret and address criteria set by the funding body to maximise their chances of funding success. We also consider the possible adverse side effects that can arise from scientists’ competitive efforts to address these criteria. Our findings identify a portfolio of funding criteria—research feasibility, research alignment and team credentials—that scientists address when preparing grant applications. Effectively addressing these criteria enhances the prospects of funding success and value creation. However, we also find that scientists can over-address funding criteria, which is counterproductive and yields undesirable side effects. Our research therefore makes an important distinction between the possibilities for value creation and the value creation frictions that can unintentionally arise based on how grant-submitting scientists interpret and address the criteria signalled by the funding body. Our research has implications for policymakers, funding bodies and scientists which we also discuss.

An open microfluidic coculture model of fibroblasts and eosinophils to investigate mechanisms of airway inflammation.

Interactions between fibroblasts and immune cells play an important role in tissue inflammation. Previous studies have found that eosinophils activated with interleukin-3 (IL-3) degranulate on aggregated immunoglobulin G (IgG) and release mediators that activate fibroblasts in the lung. However, these studies were done with eosinophil-conditioned media that have the capacity to investigate only one-way signaling from eosinophils to fibroblasts. Here, we demonstrate a coculture model of primary normal human lung fibroblasts (HLFs) and human blood eosinophils from patients with allergy and asthma using an open microfluidic coculture device. In our device, the two types of cells can communicate via two-way soluble factor signaling in the shared media while being physically separated by a half wall. Initially, we assessed the level of eosinophil degranulation by their release of eosinophil-derived neurotoxin (EDN). Next, we analyzed the inflammation-associated genes and soluble factors using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and multiplex immunoassays, respectively. Our results suggest an induction of a proinflammatory fibroblast phenotype of HLFs following the coculture with degranulating eosinophils, validating our previous findings. Additionally, we present a new result that indicate potential impacts of activated HLFs back on eosinophils. This open microfluidic coculture platform provides unique opportunities to investigate the intercellular signaling between the two cell types and their roles in airway inflammation and remodeling.

Bidirectional Siamese correlation analysis method for enhancing the detection of SSVEPs

Objective. Steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) have attracted increasing attention due to their high information transfer rate. To improve the performance of SSVEP detection, we propose a bidirectional Siamese correlation analysis (bi-SiamCA) model. Approach. In this model, an long short-term memory-based Siamese architecture is designed to measure the similarity between the SSVEP signal and the template in each frequency and obtain the probability that the SSVEP signal belongs to each frequency. Additionally, a maximize agreement module with a designed contrastive loss is adopted in the Siamese architecture to increase the similarity between the SSVEP signal and the reference signal in the same frequency. Moreover, a two-way signal processing mechanism is built to effectively integrate complementary information from two temporal directions of the input signals. Our model uses raw SSVEPs as inputs and can be trained end-to-end. Main results. Experimental results on a 40-class dataset and a 12-class dataset indicate that bi-SiamCA can significantly improve the classification accuracy compared with the prominent traditional and deep learning methods, especially under short data lengths. Feature visualizations show that the similarity between the SSVEP signal and the reference signal in the same frequency gradually improved in our model. Conclusion. The proposed bi-SiamCA model enhances the performance of SSVEP detection and outperforms the compared methods. Significance. Due to its high decoding accuracy under short signals, our approach has great potential to implement a high-speed SSVEP-based BCI.

Remote Run-Time Failure Detection and Recovery Control For Quadcopters

We propose an adaptive run-time failure recovery control system for quadcopter drones, based on remote real-time processing of measurement data streams. Particularly, the measured RPM values of the quadcopter motors are transmitted to a remote machine which hosts failure detection algorithms and performs recovery procedure. The proposed control system consists of three distinct parts: (1) A set of computationally simple PID controllers locally onboard the drone, (2) a set of computationally more demanding remotely hosted algorithms for real-time drone state detection, and (3) a digital twin co-execution software platform — the ModelConductor-eXtended — for two-way signal data exchange between the former two. The local on-board control system is responsible for maneuvering the drone in all conditions: path tracking under normal operation and safe landing in a failure state. The remote control system, on the other hand, is responsible for detecting the state of the drone and communicating the corresponding control commands and controller parameters to the drone in real time. The proposed control system concept is demonstrated via simulations in which a drone is represented by the widely studied Quad-Sim six degrees-of-freedom Simulink model. Results show that the trained failure detection binary classifier achieves a high level of performance with F1-score of 96.03%. Additionally, time analysis shows that the proposed remote control system, with average execution time of 0.49 milliseconds and total latency of 6.92 milliseconds in two-way data communication link, meets the real-time constraints of the problem. The potential practical applications for the presented approach are in drone operation in complex environments such as factories (indoor) or forests (outdoor).

Analysis of Angles-Only Hybrid Space-Based/Ground-Based Approach for Geosynchronous Orbit Catalog Maintenance

Geosynchronous Equatorial Orbit (GEO) is critical to Earth communications, weather monitoring, and national defense. Orbit estimation of GEO objects is difficult due to physical constraints placed on ground-based tracking devices such as weather, object range, lighting conditions and tracking frequency restrictions. These constraints are commonly mitigated through the use of two-way signaling devices for cooperative GEO satellites. However, determining the position and velocity of uncooperative GEO satellites and/or objects is more challenging. The objective of this paper is to develop an efficient tool to quantify the increased orbit determination accuracy of objects in the GEO catalog when the Air Force Space Command Space Surveillance Network (AFSPC SSN) is augmented with space-based angles-only measurements from a sensor in a unique near-GEO orbit. To accomplish this, a linear covariance tool is developed and validated by Monte Carlo analysis over a range of problem parameters. It is shown that linear covariance analysis is an efficient approach in determining the covariance of the position and velocity estimation errors of an uncooperative GEO object. Additionally, the linear covariance tool is used to perform error budget analysis.

Physical-Layer Secret Key Generation in Power Line Communication Networks

Due to the inherent broadcast nature, power line communication (PLC) is vulnerable to eavesdropping. Traditionally, the secret keys are generated/distributed by pre-shared keys, adaptive tone mapping, or asymmetric encryption algorithm. All of these methods face problems such as high computational complexity, high cost, or less security. To solve the problem, a physical layer security (PLS)-based secret key generation (SKG) scheme aiming at the typical in-home broadband PLC network is proposed in this paper. However, the slowly time-varying characteristic and the serious noise interference in PLC channels will degrade the performance of the PLS-based SKG scheme. To break through the limitation of the randomness of PLC channels, two-way random signals are introduced. To make the SKG system more resistant to noise, the channel frequency response-based adaptive quantization (CFR-AQ) algorithm is designed, in which the amplitude threshold and the quantization level are adaptive to the noise power and the target key disagreement rate (KDR) to maximize the key generation rate (KGR). The performance is analyzed in two scenarios: single eavesdropper and multiple eavesdroppers. The simulation results demonstrate that the proposed scheme has a good overall performance in terms of KDR, KGR, and security with a lower complexity in the presence of single or multiple non-collusive eavesdroppers, and it can be regarded as an alternative solution to generate secret keys in PLC networks.