Anomalous Variation Research Articles

An improved typhoon monitoring model based on precipitable water vapor and pressure

The potential of monitoring the movement of typhoons using the precipitable water vapor (PWV) has been confirmed. However, monitoring the movement of typhoon is focused on PWV, making it difficult to describe the movement of a typhoon in detail minutely and resulting in insufficient accuracy. Hence, based on PWV and meteorological data, we propose an improved typhoon monitoring mode. First, the European Centre for Medium-Range Weather Forecasts Reanalysis 5-derived PWV (ERA5-PWV) and the Global Navigation Satellite System-derived PWV (GNSS-PWV) were compared with the reference radiosonde PWV (RS-PWV). Then, using the PWV and atmospheric parameters derived from ERA5, we discussed the anomalous variations of PWV, pressure (P), precipitation, and wind speed during different typhoons. Finally, we compiled a list of critical factors related to typhoon movement, PWV and P. We developed an improved multi-factor typhoon monitoring mode (IMTM) with different models (i.e., IMTM-I and IMTM-II) in different cases with a higher density of GNSS observation or only Numerical Weather Prediction (NWP) data. The IMTM was evaluated through the reference movement speeds of HATO and Mangkhut from the China Meteorological Observatory Typhoon Network (CMOTN). The results show that the root mean square (RMS) of the IMTM-I is 1.26 km/h based on ERA5-P and ERA5-PWV, and the absolute bias values are mostly within 2 km/h. Compared with the models considering the single factor ERA5-P/ERA5-PWV, the RMS of the IMTM-I is improved by 26.3% and 38.5%, respectively. The IMTM-II model manifests a residual of only 0.35 km/h. Compared with the single-factor model based on GNSS-PWV/P, the residual of the IMTM-II model is reduced by 90.8% and 84.1%, respectively. These results propose that the typhoon movement monitoring approach combining PWV and P has evident advantages over the single-factor model and is expected to supplement traditional typhoon monitoring.

Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory

ABSTRACT Urban traffic anomaly diagnosis is crucial for urban road management and smart city construction. Most existing methods perform anomaly detection from a data-driven perspective and ignore the unique spatiotemporal characteristics of traffic anomalies, resulting in reduced accuracy or incorrect extraction of anomalies. In this study, we integrate geographic methods with high-dimensional tensor theory and develop a comprehensive framework for traffic anomaly diagnosis. The framework is divided into three parts: road traffic status acquisition, traffic anomaly detection, and urban anomaly analysis. First, we perform filtering and map matching on the trajectory data to obtain the traffic states of urban roads and construct them into a tensor. For traffic anomaly detection, a novel Spatio-Temporal constrained Low-Rank Sparse Tensor (ST-LRST) method is constructed to decompose urban traffic data into normal and anomalous components. Specifically, ST-LRST introduces a truncated nuclear norm, as a tighter nonconvex alternative to the tensor low-rank function, to more accurately estimate daily traffic patterns, thus improving the extraction accuracy of the sparse anomaly tensor. The spatiotemporal features of traffic anomalies are embedded into the sparse tensor to reduce the fragmentation and error rate of urban anomaly identification. To analyze anomalies, we study the characteristics of the anomalies detected by ST-LRST, such as duration, impact scope, and impact intensity. Subsequently, combined with crowdsourced geographic information, we comprehensively analyze the anomalous spatiotemporal variations in the road network and explain the factors that induce these urban anomalies. Experiments are performed using traffic data from Xi’an, China, and the results indicate that ST-LRST achieves the most accurate and comprehensive diagnosis of urban anomalies.

Automatic Identification and Statistical Analysis of Data Steps in Electric Field Measurements from CSES-01 Satellite

The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamics of the top-side ionosphere, lithosphere–atmosphere–ionosphere coupling, and electromagnetic field emissions possibly associated with earthquake occurrence. The Extremely Low-Frequency (ELF) waveform shows anomalous step variations, and this work proposes an automatic detection algorithm to identify steps and analyze their characteristics using a convolutional neural network. The experimental results show that the developed detection method is effective, and the identification performance reaches over 90% in terms of both accuracy and area under the curve index. We also analyze the rate of the occurrence of steps in the three components of the electric field. Finally, we discuss the stability of the statistical results on steps and their relevance to the probe’s function. The research results provide a guideline for improving the quality of EFD data, and further applications in monitoring the low-Earth electromagnetic environment.

AC Conductivity and Dielectric Constant of Fast Ion-Electronic Conductor AgI-C

The conductivity, dielectric constant and crystal structure of the superionic-electronic conductor AgI-porous carbon composites have been investigated at various temperatures and carbon concentrations (ϕ ≤ 10%). At a fixed temperature, both conductivity and dielectric constant exhibit anomalous variation with ϕ showing maxima of the values. We observed significant differences in the behavior between the superionic (α) phase and insulating (β) phase. By incorporating carbon, the conductivity increases by four times in the β phase and six times in the α phase whereas the dielectric constant increases by five times and eight times respectively. Unlike in the β phase, the conductivity of the α phase exhibits two distinct maxima whereas the dielectric constant exhibits different features of the profiles in different frequency regions in the α phase. Also, the peak value of these properties exhibits power-law dependence on the frequency in both phases but with different values for the exponents.

Unusual Thermal Quenching of Photoluminescence from an Organic–Inorganic Hybrid [MnBr4]2−‐based Halide Mediated by Crystalline–Crystalline Phase Transition

AbstractThe ability to generate and manipulate photoluminescence (PL) behavior has been of primary importance for applications in information security. Excavating novel optical effects to create more possibilities for information encoding has become a continuous challenge. Herein, we present an unprecedented PL temporary quenching that highly couples with thermodynamic phase transition in a hybrid crystal (DMML)2MnBr4 (DMML=N,N‐dimethylmorpholinium). Such unusual PL behavior originates from the anomalous variation of [MnBr4]2− tetrahedrons that leads to non‐radiation recombination near the phase transition temperature of 340 K. Remarkably, the suitable detectable temperature, narrow response window, high sensitivity, and good cyclability of this PL temporary quenching will endow encryption applications with high concealment, operational flexibility, durability, and commercial popularization. Profited from these attributes, a fire‐new optical encryption model is devised to demonstrate high confidential information security. This unprecedented optical effect would provide new insights and paradigms for the development of luminescent materials to enlighten future information encryption.

Unusual Thermal Quenching of Photoluminescence from an Organic-Inorganic Hybrid [MnBr4 ]2- -based Halide Mediated by Crystalline-Crystalline Phase Transition.

The ability to generate and manipulate photoluminescence (PL) behavior has been of primary importance for applications in information security. Excavating novel optical effects to create more possibilities for information encoding has become a continuous challenge. Herein, we present an unprecedented PL temporary quenching that highly couples with thermodynamic phase transition in a hybrid crystal (DMML)2 MnBr4 (DMML=N,N-dimethylmorpholinium). Such unusual PL behavior originates from the anomalous variation of [MnBr4 ]2- tetrahedrons that leads to non-radiation recombination near the phase transition temperature of 340 K. Remarkably, the suitable detectable temperature, narrow response window, high sensitivity, and good cyclability of this PL temporary quenching will endow encryption applications with high concealment, operational flexibility, durability, and commercial popularization. Profited from these attributes, a fire-new optical encryption model is devised to demonstrate high confidential information security. This unprecedented optical effect would provide new insights and paradigms for the development of luminescent materials to enlighten future information encryption.

Anomalies of Thermal Fields Revealed by Satellite Data during Preparatio n and Occurrence of Strong Earthquakes in the Region of the Baikal Rift Zone in 2008–2022

Long-term changes in thermal fields were studied before and during strong earthquakes with magnitudes from 5.1 to 5.6 that occurred in the region of the Baikal rift zone in 2008–2022. Satellite data were used for these studies. For the analysis we used the values of land surface temperature, temperature of the near-surface layer of the atmosphere, outgoing long-wave radiation, and relative humidity recorded using the AIRS instrument mounted on the Aqua satellite. During the periods of preparation and occurrence of these seismic events, anomalous variations in the parameters of thermal fields registered with satellite were revealed. They exceeded the average long-term values: for land surface temperature and temperature of the near-surface layer of the atmosphere by 5–10%, for outgoing long-wave radiation by 11–15%, and for relative humidity by 6–10%. A strong negative correlation was found between changes in the temperature of the near-surface layer of the atmosphere and relative humidity (correlation coefficient of –0.75), as well as antiphase oscillations between the values of the outgoing long-wave radiation and relative humidity. The obtained results can be used for studies of the precursor variability of thermal fields during monitoring of seismic hazard zones.

Possible factors responsible for the withdrawal process of the South Asian high during summer-to-winter transition

This study investigates the possible factors responsible for interannual variations in the withdrawal process of the South Asian high (SAH) during its summer-to-winter transition. The SAH is more obviously intensified from July to September and lasts longer over the Tibetan Plateau in late-withdrawal years (L_SAH) than early-withdrawal years (E_SAH). The L_SAH tends to appear during the stage when an El Niño has faded away and a La Niña begins to emerge, with warm SST anomalies occurring over the northern Indian Ocean and tropical northwestern Pacific, and cold anomalies existing across the equatorial central eastern Pacific. The influences of these anomalous SST variations on the SAH's withdrawal process take place primarily through two pathways. On the one hand, warm SST anomalies over the northern Indian Ocean and tropical western Pacific can warm the local tropospheric column above via a Matsunuo-Gill response to moisture adjustment and subsequently lead to an intensified and later withdrawal of the SAH. On the other hand, accompanied by warm SST anomalies, an abnormally intensified anticyclone is observed over the northwestern Pacific that shifts southwestwards and brings abundant rainfall to the region between the Yellow River and Yangtze River in July and August via southwesterly water vapor transport. Consequently, latent heating will generate positive geopotential height anomalies on its northwest side in the upper troposphere and ultimately result in an intensified and later withdrawal of the SAH. In addition, warm surface air temperature over the Tibetan Plateau in September also plays a significant role in lengthening the maintenance of the SAH over the Tibetan Plateau. However, the E_SAH tends be weak and lasts for a shorter period over the Tibetan Plateau. The E_SAH tends to occur together with a developing El Niño event, with cold SST anomalies existing over the northern Indian Ocean and tropical northwestern Pacific. Negative SST anomalies, together with a weak and northeastward-shifting subtropical western Pacific high, result in a weak SAH and quicken its withdrawal process from the Tibetan Plateau via cooling the local tropospheric column and reducing rainfall over East Asia, respectively.

Atmospheric precursors from multiple satellites associated with the 2020 Mw 6.5 Idaho (USA) earthquake

Remote sensing has became a powerful tool for identifying lithosphere and atmosphere anomalies associated with the impending Earthquakes (EQs) in the vicinity of seismic breeding zone. In this paper, Land Surface Temperature (LST) of both the daytime and nighttime from the Moderate Resolution Imaging Spectroradiometer (MODIS) along with Air Temperature (AT), Relative Humidity (RH), Air Pressure (AP) and Outgoing Longwave Radiations (OLR) are studied for the 2020 Idaho (USA) EQ of Mw 6.5. We found the EQ induced surface and atmospheric parameters anomalies just one day prior to EQ main shock using statistical analysis. Moreover, we observed a sharp increment in LST and AT followed by the drop in both AP and RH, which are responsible for cooling the hot gases emitted from epicenter during preparation period. Also, we observed a large increase in OLR on the same day confirming these anomalous variations to be related with the main shock. Furthermore, these abrupt variations are also confirmed using neural networks (nonlinear autoregressive network with exogenous inputs (NARX), multilayer perceptron (MLP) and continuous wavelet transformation (CWT). These multi-parameter and multi-technique analyses can contribute to assist in the main shock forecasting in future with an enhanced cluster of satellite observations.

Creeping slopes in NW Himalaya and Joshimath slide: constraints from GPS measurements

Slow slope movement is very common in the Himalayan region. In most cases, the topsoil, weathered rock mass, debris of paleo-landslide or of glacial origin, etc. slowly slides until it stabilizes or fails. In some cases, even the bedrock may be involved in sliding. Here we report four such sliding slopes on which GPS were actually installed for tectonic deformation monitoring in the Himalayan region after a careful investigation but they recorded slow slope sliding. The slow sliding motion on these slopes varied from 10-15 mm/year to 5-6 m/year. The slow slides did not show any anomalous seasonal variation due to hydrological loading. Amongst the four, the Joshimath slide exhibited a large variation in sliding motion which varied from less than a mm/day to 15 mm/day during 2022-2023, causing cracks on the ground and buildings and panic amongst the residents. Even the highly non-linear motion with a sudden change in sliding motion at Joshimath appears to be of viscous creep type. The exact time of initiation of this episode of slide is not known but the available InSAR analyses imply that it is moving at least since 2018. Its motion does not seem to be affected by the February 7, 2021 floods, however, whether the anthropogenic activities around the sliding zone influenced its motion and initiation, remains to be debated.

Assessment of the global applicability of three leading indices that characterize the spectral distribution of solar irradiance impacting various photovoltaic technologies

At each instant, the actual solar irradiance has a specific spectral distribution that most generally differs substantially from the standardized reference conditions under which photovoltaic (PV) cells are rated. To help reduce the dimensionality of the calculations needed to quantify the spectral effects on PV cells, various spectral indices have been introduced in the literature to simply characterize the incident spectral distribution with a single number. In previous studies, diverging conclusions have been reached about whether or not a single number can effectively represent a specific spectral distribution. This disagreement needs to be resolved before the usage of spectral indices can be considered best practice. To that effect, this study proposes a novel modeling approach. Here, three spectral indices (Average Photon Energy, APE; Blue Fraction, BF; and Useful Fraction, UF) are critically evaluated and compared using the SMARTS radiative transfer model and a large database of atmospheric inputs that are representative of the vast diversity of possible conditions worldwide, thus avoiding the rarity and limitations of costly experimental measurements. A total of 28,260 pairs of direct normal and global horizontal spectra are obtained, from which the three indices are calculated over six different wavebands that characterize different PV technologies. The key variables that have a significant impact on the indices are found to be: air mass, aerosol optical depth, Ångström exponent, and precipitable water. Using a variety of tests to evaluate the behavior of the three indices relatively to the reference direct and global spectra, results show that UF is prone to anomalous variations under a variety of circumstances. APE and BF behave similarly and reliably, but APE is found more responsive to even small changes in atmospheric conditions, and is thus preferable. A critical finding is that none of the indices can be considered bijective because compensations between red-shifting and blue-shifting atmospheric processes often result in different spectral distributions having the same index value.

Generic and Sensitive Anomaly Detection of Network Covert Timing Channels

Network covert timing channels can be maliciously used to exfiltrate secrets, coordinate attacks and propagate malwares, posing serious threats to cybersecurity. Current covert timing channels normally conduct small-volume transmission under the covers of various disguising techniques, making them hard to detect especially when a detector has little priori knowledge of their traffic features. In this paper, we propose a generic and sensitive detection approach, which can simultaneously (i) identify various types of channels without their traffic knowledge and (ii) maintain reasonable performance on small traffic samples. The basis of our approach is the finding that the short-term timing behavior of covert and legitimate traffic is significantly different from the perspective of inter-packet delays' variation. This phenomenon can be a generic reference to detect various channels because it is resistant to major channel disguising techniques which only mimic long-term traffic features, while it is also a sensitive reference to spot small-volume covert transmission since it can capture traffic anomalies in a fine-grained manner. To obtain the inner patterns of inter-packet delays' variation, we design a context-sensitive feature-extraction technique. This technique transforms each raw inter-packet delay into a discrete counterpart based on its contextual properties, thus extracting its variation features and reducing traffic data complexity. Then we learn legitimate variation patterns using a neural network model, and identify samples showing anomalous variation as covert. The experimental results show that our approach effectively detects all currently representative channels in the absence of their knowledge, presenting once to twice higher sensitivity than the state-of-the-art solutions.

The Analysis of Lithosphere–Atmosphere–Ionosphere Coupling Associated with the 2022 Luding Ms6.8 Earthquake

Taking the Luding Ms6.8 earthquake (EQ) on 5 September 2022 as a case study, we investigated the potential seismic anomalies of the ionosphere, infrared radiation, atmospheric electrostatic field (AEF), and hot spring ions in the seismogenic region. Firstly, we analyzed the multi-parameter anomalies in the ionosphere around the epicenter and found synchronous anomalous disturbances in the ground parameters, namely the global ionospheric map (GIM), GPS, TEC, and satellite parameters, such as the He+ and O+ densities on 26 August under relatively quiet solar–geomagnetic conditions (F10.7 < 120 SFU; Kp < 3; Dst > −30 nT; |AE| < 500 nT). Next, both the anomaly analysis of the infrared radiation and AEF, and the survey results of the Luding EQ scientific expedition on the hot spring ions showed pre-seismic anomalous variations at different time periods in the seismogenic region. The characteristics of Earth’s multi-sphere coupling anomalies in temporal evolution and spatial distribution were obvious, which validated the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) mechanism. Finally, combining the analysis results and the LAIC mechanism, we suggested that the multi-sphere coupling anomalies were more likely associated with the Luding Ms6.8 EQ, and that the differential motion and the regional crustal stress accumulation between the Chuandian block and the Bayan Har block might have led to this EQ. Furthermore, remote sensing and ground-based monitoring technologies can play an important role in corroborating and compensating each other, while further study of the multi-sphere coupling mechanism will provide a clearer understanding of the seismogenic process for major EQs.

Anomalous Flux Event in the TESS Sector 43 Light Curve of the White Dwarf Photometric Standard HZ 4 was Caused by a Passing Asteroid

Frymire & Ardila reported an anomalous flux variation in the Transiting Exoplanet Survey Satellite (TESS) Sector 43 light curve of the white dwarf HZ 4. We show that this flux variation was caused by the main-belt asteroid 4382 Stravinsky traversing the nearby TESS pixels, and it is therefore not a cause for concern regarding the continued use of HZ 4 as a photometric standard star.

Characterization of the Caudal Ventral Tubercle in the Sixth Cervical Vertebra in Modern Equus ferus caballus.

This study examined the anomalous variations of the ventral process of C6 in modern E. ferus caballus. The aim was to provide an incremental grading protocol measuring the absence of the caudal ventral tubercle (CVT) in this ventral process. The findings revealed the most prevalent absent CVT (aCVT) was left unilateral (n = 35), with bilateral (n = 29) and right unilateral (n = 12). Grading was determined in equal increments of absence 1/4, 2/4, 3/4, with 4/4 representing a complete aCVT in 56/76, with a significance of p = 0.0013. This also applied to bilateral specimens. In those C6 osseous specimens displaying a 4/4 grade aCVT, 41/56 had a partial absence of the caudal aspect of the cranial ventral tubercle (CrVT). Here, grading absent CrVTs (aCrVT) followed similarly to aCVTs, though 4/4 was not observed. The significance between 4/4 grade aCVTs and the presentation of an aCrVT was left p = 0.00001 and right p = 0.00018. In bilateral specimens, C6 morphologically resembled C5, implying a homeotic transformation that limited the attachment sites for the cranial and thoracal longus colli muscle. This potentially diminishes function and caudal cervical stability. Therefore, it is recommended that further studies examine the morphological extent of this equine complex vertebral malformation (ECVM) as well as its interrelationships and genetic code/blueprint.

Characterization of the anomaly in immediate aqueous interactions of sodium borate glasses by dynamic vapour sorption with in-situ Raman

This study applied a novel technique; dynamic vapour sorption (DVS) with in-situ Raman spectroscopy, as well as complementary techniques of attenuated total reflectance-Fourier transform infrared spectroscopy and X-ray diffraction, to investigate the effect of sodium content on the immediate aqueous reactivity and reactions of a range of melt-quench-derived binary sodium borate glasses (SBGs): xNa2O-(100-x)B2O3 (x = 18, 23, 30 and 35 mol%). DVS gravimetrically measured the effect of controlled relative humidity (RH) values on SBGs, while in-situ Raman monitored their structural changes in real time. It was found that the glass boron coordination, glass transition temperature, as well as weight change and percentage of crystallinity post exposure to vapour, along with threshold % RH to initiate sorption, and threshold time to initiate crystallization under 90% RH demonstrated the anomalous variation with increasing sodium content in glasses. Relative to other formulations, 30Na2O–70B2O3 showed the lowest weight change and crystallinity after vapour desorption, and highest threshold % RH and longest threshold time. There was also a correlation between vapour- and water-induced reactions, as determined by reaction rates and structural changes. Specifically, lower glass network connectivity or non-bridging oxygen formation fostered their crystallization when exposed to either vapour or water, leading to higher weight change in aqueous environments. In sum, the results of this study validated the coupling of DVS with in-situ Raman spectroscopy in characterizing the reactivity and mechanisms of aqueous interactions of SBGs.

AC Excitation to Mitigate Drift in AlGaN/GaN HEMT-Based Sensors

AlGaN/GaN high electron mobility transistor (HEMT) based sensors hold promise as small solid-state physical and chemical sensors because they can operate without a reference electrode and can be integrated into miniaturized sensor arrays. However, over extended time periods, low frequency noise causes anomalous variations (drift) in sensor signal, especially in liquid environments. These effects occur despite electromagnetic interference mitigation. To understand the low frequency noise, 1/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> noise measurements between 0.1 and 100 kHz were undertaken, in both air and water, under constant pH and normal laboratory pressure conditions. The 1/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">γ</sup> noise for the device in water was larger in magnitude than in air, and estimates for the γ-parameter in air and water were approximately 1 and 1.5, respectively. The corner frequency was observed between 100 and 1000 Hz. Based on this analysis, AC excitation at 1 kHz was applied to the conduction channel to compare the sensor stability in de-ionized water with DC operation. In this controlled test, introduction of AC excitation resulted in a strong correlation of sensor signal with the ambient temperature variations over nearly 90 hours of testing (effectively acting as a temperature sensor with a high degree of stability) while operation in DC mode resulted in largely no correlation with temperature. This indicates that AC excitation above the corner frequency is a potentially effective method to mitigate long-term sensor instability, a critical limitation for any AlGaN/GaN transistor-based physical or chemical sensors in aqueous environments.

Absence of magnetostriction and transition from rapid positive thermal expansion to negative thermal expansion at high temperatures in Sm0.5Y0.5Fe0.58Mn0.42O3 – A synchrotron X-ray diffraction study

X-ray photoemission spectroscopic (XPS) studies and temperature dependent synchrotron X-ray diffraction (SXRD) investigation have been conducted on polycrystalline samples of Sm0.5Y0.5Fe0.58Mn0.42O3 [SYFM (58-42)]. Room temperature XPS measurements revealed the mixed valance of the Fe and Mn ions along with the traces of oxygen vacancies in the material. The room temperature synchrotron X-ray diffraction (SXRD) of specimen shows the monophasic nature of the prepared composition, without the presence of any magnetic or non-magnetic impurity phases. SXRD measurements at variable temperatures between 298 and 873 K, indicates the absence of magnetostriction in the specimen at the magnetic transition temperatures TSR1 ≈ 348 K, TSR2 ≈ 300 K and TN ≈ 361 K. At much higher temperatures above TN, an anisotropic rapid positive thermal expansion (RPTE) to negative thermal expansion (NTE) of the a lattice parameter of the unit cell is further revealed for T > 573 K. The anomalous variation of phonons, are suggested to give rise to anomalous thermal variation in a lattice parameter of the specimen.

On the magnetocaloric effect and the spin-phonon coupling in the multiferroic GdMn2O5

The spin-phonon coupling and the magnetocaloric effect (MCE) in polycrystalline GdMn2O5 are investigated by Raman spectroscopy and isothermal magnetization curves. The frequencies of 680 and 700 cm−1 modes show anomalous temperature variations suggesting a strong spin-phonon coupling below the Néel temperature TN ∼ 38 K. The frequency deviation from standard temperature dependence is quantitatively interpreted within a simplified theoretical model accounting for the modulation of the exchange interaction by phonon vibrations. A relatively large magnetic entropy change, ∆Smax = 9.8 J/(kg K), is also achieved with magnetic fields up to 70 kOe. We found that the refrigerant capacity values in GdMn2O5, at different magnetic fields, are quite similar to those of TbMn2O5 and HoMn2O5 in the polycrystalline average approximation. However, the low-cost fabrication of the polycrystalline samples of GdMn2O5 and their large electric polarisation makes this material more suitable for possible cooperative magneto-electrocaloric refrigeration.

Kalman Filter, ANN-MLP, LSTM and ACO Methods Showing Anomalous GPS-TEC Variations Concerning Turkey’s Powerful Earthquake (6 February 2023)

On 6 February 2023, at 1:17:34 UTC, a powerful Mw = 7.8 earthquake shook parts of Turkey and Syria. Investigating the behavior of different earthquake precursors around the time and location of this earthquake can facilitate the creation of an earthquake early warning system in the future. Total electron content (TEC) obtained from the measurements of GPS satellites is one of the ionospheric precursors, which in many cases has shown prominent anomalies before the occurrence of strong earthquakes. In this study, five classical and intelligent anomaly detection algorithms, including median, Kalman filter, artificial neural network (ANN)-multilayer perceptron (MLP), long short-term memory (LSTM), and ant colony optimization (ACO), have been used to detect seismo-anomalies in the time series of TEC changes in a period of about 4 months, from 1 November 2022 to 17 February 2023. All these algorithms show outstanding anomalies in the period of 10 days before the earthquake. The median method shows clear TEC anomalies in 1, 2 and, 3 days before the event. Since the behavior of the time series of a TEC parameter is complex and nonlinear, by implementing the Kalman filter method, pre-seismic anomalies were observed in 1, 2, 3, 5, and 10 days prior to the main shock. ANN as an intelligent-method-based machine learning also emphasizes the abnormal behavior of the TEC parameter in 1, 2, 3, 6, and 10 days before the earthquake. As a deep-learning-based predictor, LSTM indicates that the TEC value in the 10 days prior to the event has crossed the defined permissible limits. As an optimization algorithm, the ACO method shows behavior similar to Kalman filter and MLP algorithms by detecting anomalies 3, 7, and 10 days before the earthquake. In a previous paper, the author showed the findings of implementing a fuzzy inference system (FIS), indicating that the magnitude of the mentioned powerful earthquake could be predicted during about 9 to 1 day prior to the event. The results of this study also confirm the findings of another study. Therefore, considering that different lithosphere–atmosphere–ionosphere (LAI) precursors and different predictors show abnormal behavior in the time period before the occurrence of large earthquakes, the necessity of creating an earthquake early warning system based on intelligent monitoring of different precursors in earthquake-prone areas is emphasized.