Strong Interference Research Articles

Phase Synchronization and Magnitude Control With Interference Between Transmitters in Wireless Power Transfer

With coupling between transmitter (TX) coils, the weakly-activated TX experiences interference current from adjacent strong TX. The strong interference has prohibited the magnitude and phase control. We reveal two operating modes (called negative and positive) that simultaneously achieve magnitude and phase control of TX coil currents. The negative mode is for TX which is a victim of strong interference current originating from adjacent TX. This mode is chosen when the target level of TX coil current is lower than the interference level. At such mode, its inverter voltage should be significantly delayed with respect to adjacent TX to maintain phase synchronization and interference regulation. On the other hand, the positive mode is chosen when the target level of TX coil current is higher than interference current. Hence, the proposed controller first chooses one of the two modes depending on the target magnitude of TX coil currents. The phase of two TX coil currents are synchronized and their magnitude ratio is regulated to coupling ratio even with strong interference level. No additional power components or RF communication is required. High cross coupling between TXs is tolerable, increasing the flexibility in coil geometry.

High-resolution frequency-difference beamforming for a short linear array.

Conventional beamforming (CBF) is a commonly employed approach for detecting and estimating the direction-of-arrival (DOA) of acoustic signals in underwater environments. However, CBF becomes ambiguous due to spatial aliasing when the received signal's half wavelength is smaller than the array spacing. Frequency-difference beamforming (FDB) allows for processing data in the lower frequency Δf without encountering spatial aliasing by utilizing the product of array data at frequency f with its complex conjugate at frequency f+Δf. However, lower frequency results in a wider mainlobe, which can lead to poorer DOA performance for short arrays. In this paper, a fourth-order cumulants FDB method and a conjugate augmented FDB method are proposed to extend an M-element uniform linear array to 2M-1 and 4M-3 elements. The proposed methods generate narrower beams and lower sidelobe levels than the original FDB for short arrays with large spacing. And by setting the signal subspace dimension reasonably, the proposed methods can improve the weak target detection ability under strong interference compared with FDB. Last, we verify the excellent performance of the proposed methods through simulations and experimental data.

Interference Analysis for UAV Radar Networks With Guard Zones Based on Stochastic Geometry

Due to the increasing number of aerial radars and joint communication/sensing technologies, interference from uncoordinated radars will limit the target detection and ranging performance in the future. In this paper, we investigate the interference behavior in an aerial radar network for sensing ground targets. We consider that the radars mounted on unmanned aerial vehicles (UAVs) that fly at a certain altitude are randomly distributed according to a two-dimensional homogeneous Poisson point process (HPPP), and that the propagation is modeled using a probabilistic line-of-sight (LoS) channel model. For such a sensing network, we derive the distribution of the radar interference using a stochastic geometry based analysis. In particular, when Swerling I model is considered for radar cross-section area (RCS) for the target, we derive the Laplace transform of the radar interference. To avoid a strong interference between neighboring radars, a guard zone is introduced within which the UAV radar transmission around the permitted active radar is inhibited. As the radar performance metric, we derive the successful ranging probability (SRP) of a given radar by exploiting the Laplace transform of radar interference. Using the analytic SRP, we show that we can optimize the radar network parameters such as the radius of the guard zone and the density of the active radars. In addition, we also discuss how the analytic SRP gives an insight into the spectrum utilization strategy for the UAV radar networks with the guard zones.

Price limit hits in the Chinese fund market: Determinants and post-hit performance

This article examines the predictors of price limit hits and post-hit market behaviors in the Chinese fund market. We show that macroeconomic news, past market returns, lagged limit hit dummies, and lagged price deviations have significant predictive powers for limit hits. We find that there is asymmetry between upper and lower limits, and between positive news and negative news. Furthermore, our tests of post-hit market dynamics provide evidence of volatility spillover after news upper-limit hits and no-news lower-limit hits. We find delayed price discovery except for no-news lower-limit hits, and a strong short-lived trading interference effect for news lower-limit hits. The price deviation is larger after news lower-limit hits but smaller after news upper-limit hits.

Eating an elephant, one bite at a time: Predator interactions at carrion bonanzas

Resource specific competition between predators has typically been studied from their interactions at meso-herbivore carcasses, because such carcasses are abundant. Mega-carcasses like those of elephants are rare but unparalleled in the extent of carrion biomass they offer and the long durations they can persist. These rare resource bonanzas can thus provide unique opportunities to understand sympatric species interactions within likely relaxed competitive scenarios. Using remote cameras that were operational 24-h a day, we monitored two elephant carcasses in Tsavo, Kenya, from when they were discovered until they were completely consumed or became inaccessible. While we found high temporal overlaps in activity patterns between all predators, the terrestrial predator guild (lion/leopard/spotted hyena) was not observed to feed simultaneously, suggesting strong interference competition. Based on photo-analysis and video-evidence of exclusion from a carcass, interference competition within the terrestrial predator guild favored lions over hyenas, and hyenas over leopards. The carcass at the terrestrial-aquatic interface showed more simultaneous feeding bouts between predators (crocodile/spotted hyena), indicating either facilitation and/or higher coexistence between predators that typically occupy different niches. We also observed a hippopotamus scavenging from an elephant carcass, thereby documenting a rare instance of a megaherbivore feeding on a megaherbivore. Our results highlight the importance of monitoring such carcasses through remote cameras, which can significantly add to our existing understanding of food webs and carrion ecology.

Porphyrin-based hydrogen-bonded organic framework for visible light driven photocatalytic removal of U(VI) from real low-level radioactive wastewater

The reduction of soluble U(VI) to insoluble U(IV) precipitates by visible light is an environmentally friendly and highly effective strategy to remove uranium from uranium-containing radioactive wastewater. Herein, a porous hydrogen-bonded organic framework (HOF) of UPC-H4a was self-assembled by intermolecular hydrogen bonds of 5,10,15,20-tetra(4-(2,4-diaminotriazine)phenyl) porphyrin to remove U(VI) from aqueous solution. UPC-H4a has high crystallinity with permanent porosity, excellent photocatalytic property, good chemical stability, and strong photocatalytic reducibility. The experiments showed that UPC-H4a removed 98.18% of U(VI) after illumination for 120 min, with high selectivity, strong ion interference resistance, and good reusability. A real low-level radioactive wastewater was employed to estimate the potential of UPC-H4a for practical application and its removal rate can reach 66.14% in the presence of redox competing metal ions, exhibiting great potential for practical application. The DFT calculations and EPR spectra revealed that a more negative electrostatic potential of DAT-porphyrin and the formed intermolecular hydrogen bonds in UPC-H4a can facilitate the participation of photogenerated electrons in the O2/∙O2– reaction, and the radical of ∙O2– was proved to be the critical participant in U(VI) photoreduction. The discovery of UPC-H4a in this work will help to develop more potential applications of HOFs as photocatalysts in radioactive wastewater treatment.

Spatial Distribution and Migration Characteristic of Forchlorfenuron in Oriental Melon Fruit by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Forchlorfenuron is a widely used plant growth regulator to support the pollination and fruit set of oriental melons. It is critical to investigate the spatial distribution and migration characteristics of forchlorfenuron among fruit tissues to understand its metabolism and toxic effects on plants. However, the application of imaging mass spectrometry in pesticides remains challenging due to the usually extremely low residual concentration and the strong interference from plant tissues. In this study, a matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) method was developed for the first time to obtain the dynamic images of forchlorfenuron in oriental melon. A quantitative assessment has also been performed for MALDI-MSI to characterize the time-dependent permeation and degradation sites of forchlorfenuron in oriental melon. The majority of forchlorfenuron was detected in the exocarp and mesocarp regions of oriental melon and decreased within two days after application. The degradation rate obtained by MALDI-MSI in this study was comparable to that obtained by HPLC-MS/MS, indicating that the methodology and quantification approach based on the MALDI-MSI was reliable and practicable for pesticide degradation study. These results provide an important scientific basis for the assessment of the potential risks and effects of forchlorfenuron on oriental melons.

A Modified Model-Free Adaptive Control Method for Large-Scale Morphing Unmanned Vehicles

This paper investigates the attitude control problem for large-scale morphing unmanned vehicles. Considering the rapid time-varying and strong aerodynamic interference caused by large-scale morphing, a modified model-free control method utilizing only the system input and output is proposed. Firstly, a two-loop equivalent data model for the morphing unmanned vehicle is developed, which can better reflect the practical dynamics of morphing unmanned vehicles compared to the traditional compact form dynamic linearization data model. Based on the proposed data model, a modified model-free adaptive control (MMFAC) scheme is proposed, consisting of an external-loop and an inner-loop controller, so as to generate the required combined control torques. Additionally, in light of the aerodynamic uncertainties of the large-scale morphing unmanned vehicle, a rudder deflection actuator control scheme is designed by employing the model-free adaptive control approach. Finally, the boundedness of the closed-loop system and the convergence of tracking errors are guaranteed, based on the stability analysis. Additionally, numerical examples are presented to demonstrate the effectiveness and robustness of the proposed control scheme in the case of the effect of large-scale morphing.

Detection of gaseous halocarbon refrigerants and extinguishing agent based on photoacoustic spectroscopy

A photoacoustic (PA) gaseous halocarbon refrigerants and extinguishing agent detector based on a mid-infrared broadband source was developed. H1301 (extinguishing agent), R134a and R410A (refrigerants) were the target gases. A mid-infrared thermal radiation source radiated along the longitudinal direction of the cylindrical PA cell and was reflected by a gold-plated mirror to excite PA signals. The concentrations of CO2 and H2O were measured to reduce their interference. The PA signals of H1301, R134a, R410A, CO2 and H2O were excited by using a thermal radiation source with five different optical filters, respectively. The fundamental-frequency intensity modulation (1f-IM) technique was used to measure the generated PA signals. The detection limits (1σ) of H1301, R134a and R410A were 49 ppb, 80 ppb and 211 ppb with an average time of 100 s, respectively. According to the absorption spectrum of the three target gases, there are strong cross interference around the wavelength of 8.5 µm. By using the proposed calculation method to obtain the concentrations of the target gases, the high cross interference among these gases is reduced to less than 2 %.

A novel turn-on fluorescent probe for detection of pH in extremely acidic environment and its application

A water-soluble turn-on fluorescent probe PNAP for pH has been designed and synthesized. PNAP was consist of pyrene as fluorophore and morpholine as receptor. Owing to the photoinduced electron transfer (PET) effect, the fluorescence of PNAP was quenched, while PNAP exhibited a remarkable “turn-on” fluorescence with the increase of acidity. Notably for its pKa of 2.15, PNAP was one of the pH fluorescent probes used in extremely acidic environments. Furthermore, PNAP also displayed good repeatability, strong anti-ion interference ability, high sensitivity and selectivity toward pH. In addition, PNAP has been successfully applied to the test strips and monitor the pH of environment water samples and realistic samples, showing its good promising prospect.

Fault Diagnosis of Train Wheelset Bearing Roadside Acoustics Considering Sparse Operation with GA-RBF

Trackside acoustic signals are useful for non-contact measurements as well as early warnings in the diagnosis of train wheelset bearing faults. However, there are two important problems when using roadside acoustic signals to diagnose wheel-to-wheel bearing faults; one is the presence of strong interference from strong noise and high harmonics in the signal, and the other is the low efficiency of bearing fault identification caused by it. Therefore, from the viewpoint of solving the two problems, a sparse operation method is proposed for denoising and detuning the modulation of the roadside acoustic signal, and a machine learning classifier with a Genetic Algorithm (GA)-optimized Radial Basis Neural Network (RBFNN) is proposed to improve the rate at which the features of roadside acoustic signal faults are recognized. Firstly, the background noise is filtered out from the Doppler-corrected acoustic signal using the Sparse Representation method, and the inverse wavelet transform is reconstructed into a noiseless signal. Secondly, the interference high-harmonic signal in the signal is filtered out using the Resonant Sparse Signal Decomposition (RSSD) method. Then, the GA is selected to optimize the parameters of the RBF neural network and build a fault diagnosis model. Finally, the extracted acoustic signal feature set is trained on the network model, and the trained model is used for testing. In summary, the sparse operation on the roadside acoustic signal processing and the GA-RBFNN diagnosis model were verified as being very effective in the diagnosis of roadside acoustic train wheel pair faults through the simulation experiment.

Towards precise complex AM-FM signals decomposition under strong noise conditions: A novel two-level chirp mode decomposition approach

Many signals in the real world contain noise, which interferes with the analysis of signals. Under harsh environments, the signal will be seriously disturbed by strong noise and overwhelm its changing features. Decomposing the signal with strong noise can effectively reveal the actual change law of original signal. However, the current methods cannot effectively process complex amplitude modulation-frequency modulation (AM-FM) signals with strong noise, and suffer from serious mode aliasing problems. In order to effectively decompose complex AM-FM signals with strong noise, a novel two-level chirp mode decomposition (TCMD) approach is proposed in this paper. TCMD can effectively solve the mode aliasing problem caused by strong noise interference and accurately decompose each sub-signal from original signal with strong noise. TCMD mainly includes two core parts: instantaneous frequency (IF) extraction and signal decomposition. Firstly, we establish a new IF extraction model for strong noise signals called improved parameterized time–frequency transform (IPTFT), which overcomes the shortcomings of current PTFT that cannot effectively handle multi-component signals. IPTFT can effectively filter out the interference of strong noise and accurately extract the initial IFs of multi-component signal. Then, we propose a novel adaptive iterative envelope filter tracking (AIETF) for signal decomposition that adopts the adaptive decomposition idea. AIETF can effectively decompose complex multi-component signals with strong noise, accurately estimate the IFs and reconstruct sub-signals. Decomposition experiments of both simulated and experimental signals with strong noise were carried out to verify proposed TCMD. The results show that TCMD can effectively decompose strong noisy AM-FM signals with close IFs, fast-changing IFs and crossing IFs. Meanwhile, TCMD can also effectively decompose the vibration signals with strong noise of wind turbine gearboxes, aero-engine gearboxes, and faulty bearings under non-stationary conditions to obtain high-quality TFR. Furthermore, TCMD achieves better decomposition effect for strong noise signals than the existing decomposition and TFT methods.

Multi-frequency polarization and electro-optical modulator based on triple plasmon- induced transparency in monolayer graphene metamaterials

In this paper, a dynamically tunable triple plasmon-induced transparency (PIT) is numerically investigated in a simple monolayer graphene- patterned structure. The structure is composed of five graphene strips and a silicon substrate. Electric field distributions show that the triple PIT effect is originated from the strong destructive interference between three bright modes and one dark mode, coupled mode theory (CMT) is utilized to confirm the finite-difference-time-domain (FDTD) simulation. Results show the maximum figure of merit (FOM) and sensitivity can reach 15.88 and 0.91 THz/RIU. A on-to-off electro-optical modulator is realized by tuning the Fermi levels of the graphene, the modulation degrees of amplitude are 79.3 %, 87.1 %, 70.5 %, 79.2 %, and 84.3 %, corresponding to 2.35 terahertz (THz), 3.12THz, 3.58 THz, 3.91THz, and 4.31 THz, respectively. In addition, the effect of polarized angle on the transmission spectra was studied in detail. A multi-frequency polarization modulator can also be realized with modulation degrees of amplitude (MDA) of 77.6 %, 85.9 %, and 93.7 % at 2.09 THz, 2.82 THz, and 3.59 THz, respectively, and the corresponding polarization extinction ratio (PER) are 6.5 dB, 8.5 dB, and 12.1 dB, respectively. Therefore, the results of the paper are significant to the design of multi-frequency, terahertz sensors, slow light, and modulators.

Numerical study into the impact of fixed upstream cylinder diameter ratios on vibration of leeward tandem cylinders

Multiple-cylinder fluid flows present challenges due to the strong interference between wakes, shear layers, and Kármán vortex streets, resulting in high-amplitude vibration responses. Despite these challenges, recent research has explored the potential for extracting hydrokinetic energy from such phenomena. In the present study, high-fidelity simulations are performed for flow-induced vibrations (FIV) of large spacing tandem cylinders, located leeward of a fixed cylinder with a small spacing ratio. The objective is to investigate the effect of diameter ratios of the upstream fixed cylinder on the energy conversion of its leeward tandem cylinders. Vibration responses of the midstream and downstream cylinders are identified by analyzing their amplitudes, frequencies and force coefficients, as well as vorticity contours. Results show that the presence of a large fixed upstream cylinder generates large vortices capable of synchronizing the vibrations of leeward cylinders, resulting in regular, larger amplitudes, and higher power harnessing efficiency compared to a fixed upstream cylinder with smaller diameters. Overall, this study contributes to a better understanding of fluid–structure interactions and their potential for energy conversion in multiple-cylinder systems.

Infrared small target detection using reinforced MSER-induced saliency measure

This paper presents a robust scheme to extract weak small target under intricate backgrounds. Firstly, the maximally stable extremal regions (MSER) algorithm is employed to seek extremal regions whose size and shape are consistent with the definition of small target and whose gray level is relatively stable. Then, in view of the fact that small targets are relatively sparse defect areas in the whole image, the MSER-induced global saliency measure (MGSM) is developed to reduce regular backgrounds and enhance target signal. Meanwhile, based on the characteristics of small targets with compact gray levels and a certain contrast with its surrounding background, the MSER-induced local saliency measure (MLSM) is designed to reliably enlarge the target signal and remove strong clutter interferences. Finally, the reinforced MSER-induced saliency measure (RMSM) defined by fusing MGSM and MLSM can successfully eliminate complex backgrounds and highlight real targets. Results demonstrate that this method has superiority in enhancing dim target against various backgrounds and has strong robustness to different target shapes and sizes.

Weak Fault Feature Extraction Method of Rolling Bearings Based on MVO-MOMEDA Under Strong Noise Interference

Weak Fault Feature Extraction Method of Rolling Bearings Based on MVO-MOMEDA Under Strong Noise Interference

Graphene/Polyaniline Film Optical Fiber Ammonia Gas Sensor With Excellent Sensing Performance

The possibility to improve the detection index of the optical ammonia gas sensors on the basis of the graphene/polyaniline (graphene/PANI) coated Mach–Zehnder interferometric optical fiber structure with etched thinned core fiber(e-TCF) is investigated. Based on the analysis of the output wavelength, a significant increase in sensitivity and stability of the ammonia sensors is achieved by using TCF. Experimental results show that its sensitivity is -27.8 pm/ppm, the response time is 32 s, dip wavelength error is lower than ±0.02 nm, and the dip intensity error is lower than ±0.002 dB in the stability test. This research illustrates that the proposed sensor has numerous advantages, including small size, strong anti-electromagnetic interference, and excellent repeatability characteristics. Furthermore, it can be applied in biomedical detection applications as it can improve the detection resolution of ammonia concentration at room temperature.

Dynamic imaging of interfacial electrochemistry on single Ag nanowires by azimuth-modulated plasmonic scattering interferometry

Direct visualization of surface chemical dynamics in solution is essential for understanding the mechanisms involved in nanocatalysis and electrochemistry; however, it is challenging to achieve high spatial and temporal resolution. Here, we present an azimuth-modulated plasmonic imaging technique capable of imaging dynamic interfacial changes. The method avoids strong interference from reflected light and consequently eliminates the parabolic-like interferometric patterns in the images, allowing for a 67-fold increase in the spatial resolution of plasmonic imaging. We demonstrate that this optical imaging approach enables comprehensive analyses of surface chemical dynamics and identification of previously unknown surface reaction heterogeneity by investigating electrochemical redox reactions over single silver nanowires as an example. This work provides a general strategy for high-resolution plasmonic imaging of surface electrochemical dynamics and other interfacial chemical reactions, complementing existing surface characterization methods.

Electromagnetically Induced Transparency Analog of Asymmetric Perovskite Metamaterial in the THz Spectral Region

The analogy of electromagnetically induced transparency (EIT) in perovskite metamaterials is characterized by the numerical simulations in finite-difference time-domain (FDTD). The perovskite metamaterials consist of two cut wire resonators (CWRs) and a disk resonator (DR) on a polyimide substrate. The analysis revealed the characteristic dynamics of the electromagnetic field, the near-field couplings of CWRs and DR, and the EIT-like spectral features of perovskite metamaterials as functions of the asymmetry parameter and polarization direction. The strong coupling and destructive interference of bright and bright–dark transitions in perovskite metamaterials displayed EIT-like transparency at 653.5 GHz with a high Q-factor of approximately 1470, a sensitivity of 531 GHz/RIU and a figure of merit of around 780. In addition, perovskite metamaterials exhibited slow light with a group delay of about 106 ps and a group index of approximately 3100. These results may provide an important perspective for understanding the coupling mechanism and applications of perovskite materials in slow-light devices, THz sensors, and tunable switching in THz spectral region.

Diagnostic criteria to differentiate pathological procrastinators from common delayers: a re-analysis.

Detection and treatment of clinically relevant forms of procrastination would be greatly facilitated by diagnostic criteria as formulated for psychological disorders in the Diagnostic and Statistical Manual (DSM-5). In the present article, the steps for deriving and validating diagnostic criteria for pathological procrastination are described. In an online survey of a random sample of N = 10,000 German university students, 990 answered 13 items derived from the attempts in the literature to define procrastination, the Aitken Procrastination Inventory (API) and the Patient Health Questionnaire (PHQ-9). A subset of six items related to the first factor onset delay of the API was selected by Best Subset Multiple Regression (BSMR). A latent class analysis (LCA) of these six items sorted the students into six clusters. A cluster of pathological procrastinators (10%) was separated from the clusters of less impaired habitual, average, and occasional delayers. In addition, a cluster of unconcerned delayers (10%), with strong procrastination tendencies but little personal disadvantages, and a small cluster of fast performers (2%) emerged. The pathological procrastinators differed from all other clusters significantly on nine of the 13 items. They were older, had studied longer but had fulfilled less of their study obligations and were more depressed. The answer options of the six questions were collapsed into two categories (procrastination feature present for at least half a year or absent). These criteria were used for the clinical diagnosis of pathological procrastination. For a diagnosis, two fixed criteria (delaying important tasks needlessly and strong interference with personal goals) plus at least two of four additional criteria (time spent procrastinating, time pressure, physical and psychological complaints, below performance potential) must be met. This diagnostic rule captured 92% from the cluster of pathological procrastinators and 10% of the habitual delayers, but no one from the remaining clusters. Using these diagnostic criteria for clinical diagnosis and intervention decisions will facilitate the comparison and integration of the results from future studies of procrastination.