FM Components Research Articles

A local modulation signal bispectrum for multiple amplitude and frequency modulation demodulation in gearbox fault diagnosis

This paper proposes a novel multiple amplitude modulation and frequency modulation (AM–FM) demodulation method based on local modulation signal bispectrum (LMSB), which can demodulate the fault features of different components from the gearbox signal with multi-mesh frequency bands and multi-modulation components. Firstly, the collected measurement signal is decomposed into a series of sub-band signals, and the generated sub-band signals are demodulated by modulation signal bispectrum (MSB), which realizes the simultaneous demodulation of multi-mesh frequency bands and multi-modulation components. Subsequently, each sub-band signal resulting from MSB demodulation is synchronously averaged to generate the LMSB, which removes random noise and interference frequencies from the sub-band signals. Finally, the periodic modulation intensity (PMI) is utilized to evaluate the ability of the LMSB to demodulate multi-component signals with AM–FM components. The effectiveness of LMSB in processing multi-component signals with AM–FM components is demonstrated by numerical simulation signals and experimental analysis. Analysis results demonstrate the superiority of LMSB in multiple AM–FM demodulation compared with MSB, envelope analysis (EA) and Teager energy operator (TEO). This research provides a novel perspective for gearbox fault detection.

Improved vibration AM-FM sideband phenomenon models of planetary gear set with distributed faults and fault-induced speed fluctuation

Vibration modulation features are the important indicators for the planetary gear set fault diagnosis. However, the modulation sidebands caused by the distributed faults of planetary gear set are complicated, especially the FM components related to fault-induced periodic speed fluctuation, which have not been clearly revealed. In this paper, the transfer path function, gear meshing force and measuring-direction projection function with FM components are combined to develop a series of phenomenon models when considering the distributed gear fault-induced speed fluctuation, which can theoretically deduce the vibration modulation sidebands. Field test of the wind turbine planetary gearbox and the fault simulation of experiment platform verify the high consistency of the vibration AM-FM sidebands obtained from the phenomenon models and the practical planetary gear sets. The proposed models contribute a clear explanation for the generation mechanism of vibration AM-FM sidebands even the sidebands with small amplitudes caused by the distributed faults of sun and planet gear, and provide the important and effective frequency features to confirm the condition of planetary gear set.

A Data-Driven Self-Supervised LSTM-DeepFM Model for Industrial Soft Sensor

Soft sensor, as an important paradigm for industrial intelligence, is widely used in industrial production to achieve efficient monitoring and prediction of production status including product quality. Data-driven soft sensor methods have attracted attention, which still have challenges because of complex industrial data with diverse characteristics, nonlinear relationships, and massive unlabeled samples. In this article, a data-driven self-supervised long short-term memory–deep factorization machine (LSTM-DeepFM) model is proposed for industrial soft sensor, in which a framework mainly including pretraining and finetuning stages is proposed to explore diverse industrial data characteristics. In the pretraining stage, an LSTM-autoencoder is first unsupervised pretrained. Then, based on two self-supervised mask strategies, LSTM-deep can explore the interdependencies between features as well as the dynamic fluctuation in time series. In the finetuning stage, relying on pretrained representation, the temporal, high-dimensional, and low-dimensional features can be extracted from the LSTM, deep, and FM components, respectively. Finally, experiments on the real-world mining dataset demonstrate that the proposed method achieves state of the art comparing with stacked autoencoder-based models, variational autoencoder-based models, semisupervised parallel DeepFM, etc.

Structural and magnetic properties of FeRh films grown on MgO(0 0 1), MgO(0 1 1) and MgO(1 1 1) substrates

FeRh thin films are grown on MgO(0 0 1), MgO(0 1 1) and MgO(1 1 1) single-crystal substrates at 600 °C by dc magnetron sputtering and post-annealed at the same temperature for 1 h. Effect of substrate orientation on structural and magnetic properties of FeRh films is studied using X-ray diffraction (Cu-Kα and synchrotron radiation), temperature, and field dependent magnetization measurements. FeRh(0 0 1), (1 1 2), (0 1 1) orientated films with CsCl ordering are obtained on MgO(0 0 1), MgO(0 1 1) and MgO(1 1 1) substrates, respectively. Epitaxial quality of FeRh(0 0 1) is relatively better than FeRh(1 1 2) and FeRh(0 1 1) films. The FeRh(0 1 1) film grows on two orientation relationships: Nishiyama-Wassermann (NW) and Kurdjumov-Sachs (KS). Temperature-dependent out-plane XRD measurements indicate an increase in c-parameter ∼0.56% to 0.62% across the AF-FM phase transition. The c/a ratio indicate that FeRh(0 0 1) film has in-plane compressive strain, while FeRh(1 1 2) and FeRh(0 1 1) films have tensile strain. The c/a ratio and temperature-dependent magnetization measurements (M–T) indicate that AF-FM phase transition can be tuned by appx. 52 K (388 K to 440 K) by variation of lattice strain at FeRh/MgO interface. Thermal hysteresis of appx. 12.8 K, 17 K and 22.9 K is observed for FeRh(0 0 1), FeRh(1 1 2) and FeRh(0 1 1) thin films. Larger thermal hysteresis is expected due to relatively poor epitaxial quality of the FeRh(1 1 2) and FeRh(0 1 1) films as compared to FeRh(0 0 1) film. The larger remnant FM component is observed in nominal AF state (room temperature) in all the samples, and is expected due to combined effect of composition inhomogeneity, substrate-induced strain and defects.

Magnetic carbon nanoparticles derived from candle soot for SALDI MS analyses of drugs and heavy metals in latent fingermarks

For decades, the analysis of fingerprints (FP) has been used as the primary biometric mean of human identification. In parallel, the chemical analysis of latent fingermark (LFM) with particular reference to “touch chemistry”, offersadditional intelligence to forensic examination; as such,continuous improvements in the versatility and sensitivity of detection of the molecular make up of FM is of obvious importance. In this light, we propose a facile approach to synthesize magnetic carbon nanoparticles (MCNPs) from candle soot for extraction and detection of endogenous and exogenous FM components. Initially, endogenous components of FM including fatty acids (FAs), squalene andtriacylgycerols(TAGs), were successfully extracted and detected using the developed MCNPs and surface assisted laser desorption/ionization-mass spectrometry (SALDI-MS). Furthermore, the MCNPs enabled the detection of exogenous substances including antihistamine,β-blocker, antibiotic drugs and lead in contaminated FMs, whilst providing characteristic and unique fragmentation patterns for each drugs in the FM. The influence of environmental factors such as temperature on the stability of the exogenous substances in FM was investigated by exposing the contaminated FM to different temperatures over 24 h, the findings revealed thedrugs' instability at high temperatures and undergo different degrees of degradationwhereas lead was more resilient to thermal stress. The detection oftriprolidine, metoprolol and sulfamethoxazolefrom pharmaceutical tablets in FM was successfully achieved by gently touching the tablet powder. Thelimit of detection (LOD) values of the drugs in the tablet forms were 50, 200 and 750 ng mL−1for triprolidine, metoprolol and sulfamethoxazole, respectively and their recovery rates were91.17% fortriprolidine, 94.67% formetoprolol and 120.86% for sulfamethoxazole. Finally, to create a genuine casework scenario, contaminated FM was deposited on glass and metal surfaces then subjected to extraction usingMCNPs and magnet without compromising the FM impression. Substrate control experiments revealed that the glass surface exhibiting some background signal, however, they did not interfere with the analysis and satisfactory extraction efficiency of endogenous and exogenous components of the FM on both surfaces was obtained using the MCNPs. Overall, this study proves the capability of MCNPs as new SALDI-MS substrate for both extraction and detection of FM components gathering more information pertaining to the donor’s lifestyle.

Holo-Hilbert spectral-based noise removal method for EEG high-frequency bands

Simultaneous EEG-fMRI is a growing and promising field, as it has great potential to further our understanding of the spatiotemporal dynamics of brain function in health and disease. In particular, there is much interest in understanding the fMRI correlates of brain activity in the gamma band (> 30 Hz), as these frequencies are thought to be associated with cognitive processes involving perception, attention, and memory, as well as with disorders such as schizophrenia and autism. However, progress in this area has been limited due to issues such as MR-induced artifacts in EEG recordings, which seem to be more problematic for gamma frequencies. This paper presents a noise removal method for the gamma band of EEG that is based on the Holo-Hilbert spectral analysis (HHSA), but with a new implementation strategy. HHSA uses a nested empirical mode decomposition (EMD) to identify amplitude and frequency modulations (AM and FM, respectively) by averaging over frequencies with high and significant powers. Our method examines gamma band by applying two layers of EMD to the FM and AM components, removing components with very low power based on the power-instantaneous frequency spectrum, and subsequently reconstructs the denoised gamma-band signal from the remaining components. Simulations demonstrate that our proposed method efficiently reduces artifacts while preserving the original gamma signal which is especially critical for simultaneous EEG/fMRI studies.

Effect of fish meal substitution with fermented soy pulp on growth performance, digestive enzyme, amino acid profile, and immune-related gene expression of African catfish (Clarias gariepinus)

Fermented soy pulp (FSP) is currently capturing attention worldwide because of the high price of fish meal and its inconsistent supply in recent years. FSP replaces fish meal as a source of protein and energy towards improved fish health and growth. The protein replacement was employed in this study to assess the growth and health status, digestive enzyme, amino acid profile, and immune-related gene expression of African catfish, Clarias gariepinus. The duration of the feeding experiment was 70 days. Five isonitrogenous. (32% crude protein) diets were prepared with FSP replacing D1 (0% FSP), D2 (25% FSP), D3 (50% FSP), D4 (75% FSP) and D5 (100% FSP) to FM component of the diets. D1 diet with 0% FSP was considered as a control. The fermentation process of FSP was carried out for three weeks. This resulted in the experimental diets having significantly different (p < 0.05) growth parameters. The D3 diet showed the highest weight gain and SGR with a mean and standard deviation of 1552.41 ± 81.67% and 1.73 ± 0.03%, respectively. D3 diet had better relative protein digestibility (RPD) value of 92.33 ± 2.19 compared with fish fed with the control diet. Amylase and lipase activities were found to be significantly higher in the D3 diet. The muscle amino acid profiles (arginine, isoleucine, histidine, and leucine) and gene expression (TGF-β1, lyzg, NF-kβ, and hsp90a) were significantly highest (p < 0.05) in the D3 diet. Fresh insights have been demonstrated by the findings of the study into the production of FSP as a replacement product. These insights would efficiently enhance the generation of aquafeed, which are low in cost and healthy towards the production of African catfish and other freshwater species. In conclusion, a new theory on using FSP as a plant-based replacement material and a protein replacement for fish growth and health status booster may be achieved at 50% of FSP inclusion.

Origin of ferroelectricity in multiferroic ErFeO3

ErFeO3 is a centrosymmetric Pnma/Pbnm structure with no ferroelectricity. However, most surprisingly, it shows ferroelectricity and antiferromagnetism at room temperature. Here, the Fe3+-O-Fe3+ bond angles are 143.50 and 159.280 which is deviated from 1800. This Fe3+-O-Fe3+ super-exchange interaction contributes to an AFM ordering with a weak FM component. An antisymmetric DM exchange interaction (Di. Si x Sj) is attributed to the weak FM component between adjacent spins and introduced spin-orbit interaction. As a result an electric polarization P ~ eij x (Si x Sj) is produced due to local crystal anisotropy. To acquire a conception involving the contribution of grain and grain boundary of ErFeO3, we have analyzed complex impedance and modulus spectra and fitted with the equivalent circuit diagram. The imaginary part of electric modulus is fitted by KWW function and the stretched exponent is found to be 0.3<β< 0.48. The conduction mechanism of ErFeO3 is followed CBH model.

Effects of Transmission Ratio on the Nonlinear Vibration Characteristics of a Gear-Driven High-Speed Centrifugal Pump

The gear transmission system is widely used in high-speed centrifugal pump to improve the operating speed and hydraulic performances of the whole pump. Vibration characteristics and the stability of these high-speed rotor systems with gear transmission have great impacts on the stability of the whole fluid transmission system of the plant. Based on the lumped-mass method and the principle of displacement equilibrium of the rotor system, a coupled lateral-torsional dynamic model describing the gear-rotor-seal-bearing (GRSB) system of high-speed centrifugal pumps which has considered the nonlinear factors within the gear pair, nonlinear forces of bearings, and those of the seals is proposed. Then, the stability and nonlinear vibration responses of a model GRSB system under different gear transmission ratios (i) have been studied. The following conclusions are drawn from the results: (1) The components with frequencies like fp, f g , fm, and 2fm have great impacts on the vibration responses of the gear pair, especially the fm component; moreover, the amplitude of fm first increases and then decreases with the ratio increase and reaches the maximum value under the ratio of 3. (2) A jump motion state will occur when the ratio i is 1.25 and the stability of the system is obviously worse than the bifurcation state. Quite different from those under the other states, under this jump motion state, the 0.2 f g component and 0.5fp component will appear in the vibration responses of both gears and become the most contributed two factors to the responses of the driven gear. (3) In the design process, the transmission ratio of a high-speed centrifugal pump with a simplified GRSB system should be specially designed to avoid the jump-point state and the maximum-amplitude-of-fm state to ensure the stability of the system as well as reduce the mechanical impacts and noises.

Vibration signal fusion using improved empirical wavelet transform and variance contribution rate for weak fault detection of hydraulic pumps

This paper presents a novel vibration signal fusion algorithm using improved empirical wavelet transform and variance contribution rate to fuse three-channel vibration signals for weak fault detection of hydraulic pumps. Firstly, empirical wavelet transform (EWT) is utilized to decompose the three-channel signals into several AM–FM components. Then in accordance with the statistical characteristics of these component data, variance contribution rate is defined to measure the weight of component data points. A series of fusion coefficients are computed and assigned to every component point. Finally, these component points are fused into one single signal and Hilbert transform is conducted to demodulate the fault characteristic frequency for weak fault detection. Moreover, to address the issue of improper EWT spectrum segmentation, we introduce Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to improve EWT in the full space and the frequencies corresponding to outlier points are taken as the boundaries of spectrum segmentation. Therefore, the number of boundaries is more reasonable and the AM–FM components are more consistent with inherent components existing in the vibration signals of pumps. Results of simulation and experiment analysis demonstrate the good performance of the exhibited fusion algorithm in weak fault detection of hydraulic pumps.

Combination of Amplitude and Frequency Modulation Features for Presentation Attack Detection

In this paper, we propose the combination of Amplitude Modulation and Frequency Modulation (AM-FM) features for replay Spoof Speech Detection (SSD) task. The AM components are known to be affected by noise (in this case, due to replay mechanism). In particular, we exploit this damage in AM component to corresponding Instantaneous Frequency (IF) for SSD task. Thus, the novelty of proposed Amplitude Weighted Frequency Cepstral Coefficients (AWFCC) feature set lies in using frequency components along with squared weighted amplitude components that are degraded due to replay noise. The AWFCC feature set contains the information of both AM and FM components together and hence, gave discriminatory information in the spectral characteristics. The experiments were performed on publicly available ASVspoof 2017 challenge version 1.0 and 2.0 databases using AWFCC feature set. We have compared results of proposed feature set with the other state-of-the-art feature set, such as Constant Q Cepstral Coefficients (CQCC), Linear Frequency Cepstral Coefficients (LFCC), Mel Frequency Cepstral Coefficients (MFCC) and using a simple Gaussian Mixture Model (GMM) classifier. The individual performance of AWFCC feature set obtained lower % EER than the other feature sets on both version 1.0 and 2.0 databases. Furthermore, we used score-level fusion in order to obtain the possible complementary information of two feature sets to reduce the % EER further. To that effect, the score-level fusion of CQCC and AWFCC feature sets gave 5.75 % and 10.42 % EER on development and evaluation sets, respectively, of ASVspoof 2017 version 2.0 database. Moreover, for evaluation dataset, we have also studied the performance of proposed feature set on different Replay Configurations (RC), namely, acoustic environments, playback, and recording devices. For all the levels of threat conditions (i.e., low, medium, and high) to the ASV system, the proposed feature set performed better compared to the existing state-of-the-art feature sets.

Rockfall monitoring based on multichannel synthetic aperture radar

Rockfall influences the safety of infrastructure and transportation lines normal operation, application of SAR technology to monitor the rockfall could predict rockfall disaster. One of the most important factors in rockfall target detection is the signal-to-clutter-plus noise ratio (SCNR) after clutter suppression, which should be maximized before rockfall target detection. Through analyzing remainder rockfall target characteristic after clutter suppression, the method of removing quadratic FM component introduced by platform velocity and along track velocity of rockfall target is proposed. After removing quadratic FM component by Dechirp technology, remainder rockfall target is focused in Doppler region image and the SCNR of remainder rockfall target is maximized. So, it has a preferable result in rockfall target detection. To resolve the contradiction between calculated amount and the accuracy of along track velocity, this paper adopts the technology of gradual approach. The effectiveness of the presented method is demonstrated by both theoretic analysis and simulated data.

Behaviorally relevant frequency selectivity in single- and double-on neurons in the inferior colliculus of the Pratt's roundleaf bat, Hipposideros pratti.

Frequency analysis is a fundamental function of the auditory system, and it is essential to study the auditory response properties using behavior-related sounds. Our previous study has shown that the inferior collicular (IC) neurons of CF-FM (constant frequency-frequency modulation) bats could be classified into single-on (SO) and double-on (DO) neurons under CF-FM stimulation. Here, we employed Pratt's roundleaf bats, Hipposideros pratti, to investigate the frequency selectivity of SO and DO neurons in response to CF and behavior-related CF-FM sounds using in vivo extracellular recordings. The results demonstrated that the bandwidths (BWs) of iso-frequency tuning curves had no significant differences between the SO and the DO neurons when stimulated by CF sounds. However, the SO neurons had significant narrower BWs than DO neurons when stimulated with CF-FM sounds. In vivo intracellular recordings showed that both SO and DO neurons had significantly shorter post-spike hyperpolarization latency and excitatory duration in response to CF-FM in comparison to CF stimuli, suggesting that the FM component had an inhibitory effect on the responses to the CF component. These results suggested that SO neurons had higher frequency selectivity than DO neurons under behavior-related CF-FM stimulation, making them suitable for detecting frequency changes during echolocation.

The Instantaneous Spectrum: A General Framework for Time-Frequency Analysis

This paper is a contribution to the old problem of representing a signal in the coordinates of time and frequency. We review the fundamental Hilbert transform relationship in systems analysis and argue that the dual relationship assumed in signal analysis, i.e. spectral single-sidedness is not necessarily justifiable. Therefore, we abandon the analytic signal and utilize a carefully parameterized signal model composed of a superposition of complex, AM–FM components that enables rigorous definition of instantaneous amplitude and instantaneous frequency. We then propose the instantaneous spectrum (IS) and prove that it exactly localizes signal components in an instantaneous bandwidth sense. The relation of the IS to traditional time-frequency distributions is discussed and comparative examples are provided. It is shown that under certain conditions the IS specializes to the Fourier spectrum and properties of the IS, similar to standard Fourier transform properties, are given.

High temperature magnetic studies on Bi1-xCaxFe1−yTiyO3-δ nanoparticles: Observation of Hopkinson-like effect above TN

The magnetic properties of Bi1-xCaxFe1-yTiyO3-δ (BCFO: y = 0 and BCFTO: x = y) nanoparticles are studied across a wide range of temperatures (20 K to 960 K) for different Ca (and Ti) concentrations [x (= y) = 0, 0.025, 0.05, and 0.1]. X-ray diffraction and electron microscopy revealed the gradual emergence of the orthorhombic phase (Pnma) with an increase in the Ca2+ content in BCFO, contrary to the retention of parent rhombohedral symmetry (R3c) in Ca2+-Ti4+ co-doped BCFTO. XPS indicates the presence of 3+ valence states for Bi and Fe and under-coordinated defect peaks in O 1s spectra. The ordering of oxygen vacancies in BCFO affects the FeO6 octahedral alignment, resulting in a systematic shift of Fe-O Raman modes. Oxygen vacancies formed due to Ca2+ doping in BCFO and the non-magnetic Ti4+ ion at the Fe3+ site in BCFTO disrupt the spin-cycloid propagation in BiFeO3, largely influencing the magnetic properties. These substitutional changes, in addition to the large surface area, are the sources of net magnetization in these systems. Magnetic hysteresis and field dependent zero field cooled-field cooled curves indicate the combined presence of anti-ferromagnetic and ferromagnetic components in BCFO and BCFTO nanoparticles. High temperature magnetic studies present a clear bifurcation of magnetic Néel transition centered at ∼600 K associated with the structural variation in BCFO. A strong anomaly observed at 860 ± 40 K in all the samples suggests a Hopkinson-like effect arising due to sudden loss of anisotropy by the FM component.

Electron mass enhancement and magnetic phase separation near the Mott transition in double-layer ruthenates

We present a detailed investigation of the specific heat of Ca3(Ru1-xMx)2O7 (M = Ti, Fe, Mn) single crystals. Depending on the dopant and doping level, three distinct regions are present: a quasitwo-dimensional metallic state with antiferromagnetic (AFM) order formed by ferromagnetic bilayers (AFM-b), a Mott insulating state with G-type AFM order (G-AFM), and a localized state with a mixed AFM-b and G-AFM phase. Our specific heat data provide deep insights into the Mott transitions induced by Ti and Mn doping. We observed not only an anomalous large mass enhancement, but also an additional term in the specific heat, i.e., C ∝ T2, in the localized region. The C ∝ T2 term is most likely due to long-wavelength excitations with both FM and AFM components. A decrease in the Debye temperature is observed in the G-type AFM region, indicating lattice softening associated with the Mott transition.

Detection of the Glottal Closure Instants Using Empirical Mode Decomposition

This work explores the effectiveness of the Intrinsic Mode Functions (IMFs) of the speech signal, in estimating its Glottal Closure Instants (GCIs). The IMFs of the speech signal, which are its AM–FM or oscillatory components, are obtained from two similar nonlinear and non-stationary signal analysis techniques—Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), and Modified Empirical Mode Decomposition (MEMD). Both these techniques are advanced variants of the original technique—Empirical Mode Decomposition (EMD). MEMD is much faster than ICEEMDAN, whereas the latter curtails mode-mixing (a drawback of EMD) more effectively. It is observed that the partial summation of a certain subset of the IMFs results in a signal whose minima are aligned with the GCIs. Based on this observation, two different methods are devised for estimating the GCIs from the IMFs of ICEEMDAN and MEMD. The two methods are captioned ICEEMDAN-based GCIs Estimation (IGE) and MEMD-based GCIs Estimation (MGE). The results reveal that IGE and MGE provide consistent and reliable estimates of the GCIs, compared to the state-of-the-art methods, across different scenarios—clean, noisy, and telephone channel conditions.

An optimum allocation sampling based feature extraction scheme for distinguishing seizure and seizure-free EEG signals.

Epileptic seizure is the common neurological disorder, which is generally identified by electroencephalogram (EEG) signals. In this paper, a new feature extraction methodology based on optimum allocation sampling (OAS) and Teager energy operator (TEO) is proposed for detection of seizure EEG signals. The OAS scheme selects the finite length homogeneous sequence from non-homogeneous recorded EEG signal. The trend of selected sequence by OAS is still non-linear, which is analyzed by non-linear operator TEO. The TEO convert non-linear but homogenous EEG sequence into amplitude-frequency modulated (AM-FM) components. The statistical measures of AM-FM components used as input features to least squares support vector machine classifier for classification of seizure and seizure-free EEG signals. The proposed methodology is evaluated on a benchmark epileptic seizure EEG database. The experimental results demonstrate that the proposed scheme has capability to effectively distinguish seizure and seizure-free EEG signals.

In-plane magnetic anisotropy in strontium iridate Sr2IrO4

Magnetic anisotropy in strontium iridate ($\mathrm{S}{\mathrm{r}}_{2}\mathrm{Ir}{\mathrm{O}}_{4}$) is found to be large because of the strong spin-orbit interactions. In our work, we studied the in-plane magnetic anisotropy of $\mathrm{S}{\mathrm{r}}_{2}\mathrm{Ir}{\mathrm{O}}_{4}$ and traced the anisotropic exchange interactions between the isospins in the crystal. The magnetic-field--dependent torque \ensuremath{\tau}($H$) showed a prominent transition from the canted antiferromagnetic state to the weak ferromagnetic (WFM) state. A comprehensive analysis was conducted to examine the isotropic and anisotropic regimes and probe the easy magnetization axis along the $ab$ plane. The angle-dependent torque \ensuremath{\tau}(\ensuremath{\theta}) revealed a deviation from the sinusoidal behavior, and small differences in hysteresis were observed around 0\ifmmode^\circ\else\textdegree\fi{} and 90\ifmmode^\circ\else\textdegree\fi{} in the low-magnetic-field regime. This indicates that the orientation of the easy axis of the FM component is along the $b$ axis, where the antiferromagnetic to WFM spin-flop transition occurs. We compared the coefficients of the magnetic susceptibility tensors and captured the anisotropy of the material. The in-plane \ensuremath{\tau}(\ensuremath{\theta}) revealed a tendency toward isotropic behavior for fields with values above the field value of the WFM transition.

Differences in velocity-information processing between two areas in the auditory cortex of mustached bats

The bio-sonar pulse of the mustached bat, Pteronotus parnellii parnellii, consists of four harmonics of constant frequency (CF1-4) and frequency-modulated (FM1-4) components. The CF and FM components carry velocity and distance information, respectively. In the auditory cortex of mustached bats, the CC (“C” stands for constant frequency) and DIF (dorsal intrafossa) areas consist of CF/CF neurons tuned to a combination of pulse CF1 and echo CFn (n = 2 or 3). They show facilitative responses to pulse-echo stimuli with specific frequency differences, corresponding to Doppler shifts. Their facilitative responses are sharply tuned to a specific relative target velocity (best velocity). Compared with CC neurons, DIF neurons are tuned to higher velocities and to larger CF1 amplitudes, and adapt faster to repetitive pulse-echo stimuli. The great majority of CC neurons are suited for the processing of velocity information during cruising and target-directed flight, whereas the majority of DIF neurons are suited for the processing of velocity information when the bat is emitting loud pulses at low repetition rates during cruising flight. CC and DIF neurons are broadly tuned to 0–2-ms echo delays and not suited for ranging.