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Advanced detection is an important subject in roadway excavation in coal mining. The mostly used methods include the seismic, electric, and electromagnetic (EM) evaluations, which are independently treated. Due to the existence of the electrokinetic effect in the underground rocks, the seismic and EM waves can be coupled, resulting in the well-known seismoelectric conversion, which would be useful for advance detection of anomalous body. In this study, we investigate the seismoelectric signals generated during the coal-mining process. We use the COMSOL software to establish the computational model and solve the frequency-domain response of the seismoelectric waves excited by a point force source. The time-domain waveforms of seismoelectric waves are obtained by the fast Fourier transformation. We simulate the seismoelectric waves in the models containing collapsed column and intrusive body. The results show that the seismic waves can generate interfacial seismoelectric waves at the boundaries of the collapsed column. The seismoelectric waves contain the information of collapsed column, including its width and conductivity as well as its distance from the heading face. The simulations of the intrusive body model show that the seismic waves can excite seismoelectric waves at the interface of the intrusive body. The numerical results suggest a potential of the seismoelectric waves in advance detection in coal mining.

This article studies distributed state estimation for a dynamic system based on measurements collected by every node in a sensor network. Depending on the communications among nodes, information spreads across the network node by node through iterations. Then, nodes work collaboratively to estimate the system state timely. Most of the existing networked filters aim to make all nodes reach consensus at the centralized estimation with sufficient communications. To accommodate limited communication resources in practice, this article proposes to optimize the entire network's estimation accuracy given in a fixed number of communications. This is done by optimizing the sequence of node activations for selective communication. We propose two selective activation schemes: link activation (LA) and star activation (SA). In each iteration, they activate a single link and a single star (i.e., a node with all its neighbors), respectively. We develop two iterative distributed filters (DFs): 1) LA based (LA-DF); and 2) SA based (SA-DF). LA-DF and SA-DF possess many important properties. For example, they are unbiased, convergent, stable, and credible. Finally, we analyze the performance of our filters and provide simulation results compared with existing filters to verify the superiority of the proposed filters.

This paper focuses on fixed-interval smoothing for stochastic hybrid systems. When the truth-mode mismatch is encountered, existing smoothing methods based on fixed structure of model-set have significant performance degradation and are inapplicable. We develop a fixed-interval smoothing method based on forward- and backward-filtering in the Variable Structure Multiple Model (VSMM) framework in this paper. We propose to use the Simplified Equivalent model Interacting Multiple Model (SEIMM) in the forward and the backward filters to handle the difficulty of different mode-sets used in both filters, and design a re-filtering procedure in the model-switching stage to enhance the estimation performance. To improve the computational efficiency, we make the basic model-set adaptive by the Likely-Model Set (LMS) algorithm. It turns out that the smoothing performance is further improved by the LMS due to less competition among models. Simulation results are provided to demonstrate the better performance and the computational efficiency of our proposed smoothing algorithms.

In this work, pyrrole-2-carboxamides were designed with a structure-guided strategy based on the crystal structure of MmpL3 and a pharmacophore model. The structure–activity relationship studies revealed that attaching phenyl and pyridyl groups with electron-withdrawing substituents to the pyrrole ring and attaching bulky substituents to the carboxamide greatly improved anti-TB activity. Most compounds showed potent anti-TB activity (MIC < 0.016 μg/mL) and low cytotoxicity (IC50> 64 μg/mL). Compound 32displayed excellent activity against drug-resistant tuberculosis, good microsomal stability, almost no inhibition of the hERG K+channel, and good in vivoefficacy. Furthermore, the target of the pyrrole-2-carboxamides was identified by measuring their potency against M. smegmatisexpressing wild-type and mutated variants of the mmpL3gene from M. tuberculosis(mmpL3tb) and determining their effect on mycolic acid biosynthesis using a [14C] acetate metabolic labeling assay. The present study provides new MmpL3 inhibitors that are promising anti-TB agents.

It is reported that earthquakes are accompanied by electromagnetic (EM) anomalies. These anomalies are thought to be caused by earthquakes but their generation mechanism is still unclear. The piezoelectric effect has been proposed as a possible mechanism, particularly in quartz‐rich rocks. However, the EM responses to earthquakes due to such an effect have not been well understood. In this article, we study the EM signals generated by an earthquake source due to the piezoelectric effect. We develop a semi‐analytical method to simulate the EM responses to earthquake sources in a 3‐D layered model and conduct numerical simulations to investigate the characteristics of the EM fields. The results show that the piezoelectric effect in quartz‐rich rocks could be the responsible mechanism for the EM signals recorded during the earthquake. Two kinds of EM signals can be generated by the earthquake, namely, the early EM wave arriving before the seismic waves and the coseismic EM field accompanying the seismic waves. For an Mw6.1 earthquake, the coseismic electric field is ∼0.1 μV/m and the magnetic field can only reach ∼10−5nT. We also study the sensitivity of the coseismic EM fields to the rock conductivity. The results indicate that the coseismic EM fields are mainly affected by the conductivity of the shallow layer where the receiver is located, and if the top layer is thin, they are also affected by the conductivity of the deeper layer due to the contribution of the evanescent EM wave created at the interface. When a quartz‐rich rock is under stress, the positive and negative charge centers of quartz crystals are shifted, resulting in a polarization, which manifests macroscopically as the EM radiation. Such a phenomenon is known as the piezoelectric effect. It is a plausible mechanism for the generation of the earthquake‐associated electromagnetic (EM) anomaly. In this paper, we propose a simple method to simulate the EM disturbances generated by an earthquake source arising from the piezoelectric effect. We also conduct numerical simulations to study the properties of the EM fields. The results show that earthquakes can produce two kinds of EM signals. One signal propagates with the speed of the EM wave in the rocks and it arrives earlier than the seismic waves. The other is the coseismic EM field that appears simultaneously with the seismic waves. Such a coseismic signal is restricted to inside of the area disturbed by the seismic wave. Based on the sensitivity analysis, we find that the coseismic EM signal is sensitive not only to the conductivity of shallow rocks, but also to that of the deep rocks. The results also indicate that the electric signals produced by the piezoelectric effect during an earthquake are observable. A method is presented to simulate the seismo‐electromagnetic fields due to the piezoelectric effect in quartz‐rich strataAn earthquake source can generate an early electromagnetic (EM) wave and coseismic EM fields due to the piezoelectric effectNumerical results show that the piezoelectric effect is an effective mechanism to produce observable electric signals A method is presented to simulate the seismo‐electromagnetic fields due to the piezoelectric effect in quartz‐rich strata An earthquake source can generate an early electromagnetic (EM) wave and coseismic EM fields due to the piezoelectric effect Numerical results show that the piezoelectric effect is an effective mechanism to produce observable electric signals

BCR-ABL kinase inhibition is an effective strategy for the treatment of chronic myeloid leukemia (CML). Herein, we report compound 3a-P1, bearing a difluoro-indene scaffold, as a novel potent pan-inhibitor against BCR-ABL mutants, including the most refractory T315I mutant. As the privileged (S)-isomer compared to its (R)-isomer 3a-P2, 3a-P1exhibited potent antiproliferative activities against K562 and Ku812 CML cells and BCR-ABL and BCR-ABLT315IBaF3 cells, with IC50values of 0.4, 0.1, 2.1, and 4.7 nM, respectively. 3a-P1displayed a good safety profile in a battery of assays, including single-dose toxicity, hERG K+, and genotoxicity. It also showed favorable mice pharmacokinetic properties with a good oral bioavailability (32%), a reasonable half-life (4.61 h), and a high exposure (1386 h·ng/mL). Importantly, 3a-P1demonstrated a higher potency than ponatinib in a mice xenograft model of BaF3 harboring BCR-ABLT315I. Overall, the results indicate that 3a-P1is a promising drug candidate for the treatment of CML to overcome the imatinib-resistant T315I BCR-ABL mutation.

Herein, we report our work exploring the essential requirements for fluorophore selection during the development of various fluorescence applications. We assembled a library of chromone-derived fluorophores with diverse structure–fluorescence properties, which allowed us to choose the fluorophore pairs with similar structures but differing fluorescence properties and compared the performance of the selected fluorophore pairs in three types of commonly used fluorescence applications. We found that the selection standard of a suitable fluorophore is variable depending on the application. (1) In fluorescence imaging, fluorophores with strong and constant fluorescence under various conditions, such as a large pH range, are preferred. Notably, (2) in the detection of bioactive species, fluorophores with relatively lower fluorescence quantum yield favor the detection sensitivity. Furthermore, (3) in enzymatic assays employing fluorescence, the key parameter is the binding affinity between the fluorophore and the enzyme.

Quasi‐static electromagnetic (EM) approximation was frequently used in numerical modeling of the seismoelectric wavefields, but the computational error it brings is unclear. In this study, we investigate the error caused by the quasi‐static EM approximation based on a horizontally layered model. With such an approximation we obtain a simplified set of Pride's equations and present an analytically based algorithm to solve the seismoelectric responses to an explosive source. First, we solve the seismic wavefields by ignoring the influence of the converted EM fields on the propagation of the seismic waves. Second, we simplify Maxwell equations to a Poisson equation of the electric potential, from which the EM signals are solved. The solved EM signals are compared with the solutions solved from the full Pride's equations to investigate the error caused by the quasi‐static EM approximation. The result shows that the quasi‐static EM approximation causes the loss of the electric field accompanying the Swaves and yields errors in modeling the coseismic magnetic fields accompanying the Swaves. The errors tend to become smaller when increasing the frequency and decreasing the salinity, implying that the quasi‐static EM approximation seems to be more suitable for simulating the coseismic EM signals under high‐frequency and low‐salinity conditions. The quasi‐static EM approximation also affects the simulation of the interfacial EM waves. Only under the condition that the wavelength of the EM wave is much larger than the source‐receiver distance, the quasi‐static method is valid in simulating the EM wave. An algorithm with quasi‐static EM approximation is presented to solve the seismoelectric wavefields in a horizontally layered mediaSeismoelectric wavefields solved with and without introducing quasi‐static EM approximation are compared to analyze the errorsErrors caused by quasi‐static EM approximation increase with the decrease of the frequency and the increase of the pore fluid salinity

We numerically compute seismoelectric wavefields generated at a fluid/porous medium interface by an explosive source in the fluid. Our numerical experiments show that electromagnetic (EM) signals accompanying the P, S, and interface waves can be observed at receivers located in the fluid regions near the interface. Such accompanying EM signals are produced by the inhomogeneous EM waves that are generated by the seismic waves at the interface and their amplitudes decrease with the distance from interface. Under the excitation of an explosive source whose strength is within the capability of industry air guns, electric and magnetic fields that accompany the Scholte wave are on the order of 1 μV/m and 0.01 nT, respectively. This means that the EM signals arising from the electrokinetic effect at an ocean bottom are detectable and suggest that it is possible to measure the EM signals during marine seismic explorations to study the properties of the seafloor material. EM signals that accompany the P, S, and interface waves are also observed in the porous medium region near the interface. Component analysis shows that they contain contributions from multiple modes of waves, among which the slow compressional wave contributes significantly to the vertical electric field, leading to a much stronger vertical electric field than the horizontal electric field during the passage of a seismic wave along the interface. Seismoelectric wavefields generated by an explosive source in the fluid at a fluid/porous medium interface are solvedEM signals accompanying seismic waves are observed in the fluid, and porous medium near the interface and their components are analyzedNumerical results show that the EM signals generated by seismic waves at an ocean bottom due to the electrokinetic effect are detectable

Studied in this article are the properties of the electromagnetic (EM) fields generated by an earthquake due to the motional induction effect, which arises from the motion of the conducting crust across the Earth's magnetic field. By solving the governing equations that couple the elastodynamic equations with Maxwell equations, we derive the seismoelectromagnetic wavefields excited by a single‐point force and a double‐couple source in a full space. Two types of EM disturbances can be generated, i.e., the coseismic EM field accompanying the seismic wave and the independently propagating EM wave which arrives much earlier than the seismic wave. Simulation of an Mw6.1 earthquake shows that at a receiving location where the seismic acceleration is on the order of 0.1 m/s2, the coseismic electric and magnetic fields are on the orders of 1 μV/m and 0.1 nT, respectively, agreeing with the EM data observed in 2008 Mw6.1 Qingchuan earthquake, China, and indicating that the motional induction effect is effective enough to generate observable EM signal. We also simulated the EM signals observed by Haines et al. ([Haines, S. S., 2007]) which were called the Lorentz fields and cannot be explained by the electrokinetic effect. The result shows that the EM wave generated by a horizontal force can explain the data well, suggesting that the motional induction effect is responsible for the Lorentz fields. The motional induction effect is compared with the electrokinetic effect, showing the overall conclusion that the former dominates the mechanoelectric conversion under low‐frequency and high‐conductivity conditions while the latter dominates under high‐frequency and low‐conductivity conditions. EM wavefields arising from to the motional induction effect are simulatedThe motional induction effect is effective to generate observable EM signalsThe motional induction effect is compared with the electrokinetic effect

The magma plumbing in the lower crust beneath the Coso volcanic field (CVF) remains controversial, largely because of the absence of high‐resolution lower crustal velocity models. For the first time, we develop a high‐resolution crustal P‐wave velocity model for the Coso‐Ridgecrest region by jointly inverting 137,992 first P and 8,636 PmP travel‐time data using an eikonal equation‐based seismic reflection tomography method. More than half of the PmP travel times are picked from earthquakes after the 2019 Mw7.1 Ridgecrest earthquake. Such abundant PmP travel times significantly improve the resolution of the lower crust. Our final velocity model reveals a prominent low‐velocity body sitting right beneath the CVF at 5–20 km depths, which we interpret as a rhyolite magma reservoir that supplies heat flux to the hot springs and also feeds the volcanic activities at Coso. We find that the upper‐middle crustal low‐velocity body dips southwards into the lower crust, extending to regions beneath the Indian Wells Valley and the Garlock Fault at depth greater than 20 km. We ascribe the lower crustal low‐velocity body (more than 4% Vp reduction) to a basaltic magma reservoir that connects the melts in the uppermost mantle with the eruptible rhyolitic reservoir at shallower depths. The basaltic magma reservoir constitutes an important part of a continuous N‐S elongated crustal magma plumbing system beneath the CVF, formed as a combined result of local extension, faulting, and stress distribution. The deep origin of the Coso volcanic field (CVF) in the lower crust is not fully understood. To well constrain the deep origin of magmas, we use a newly developed seismic reflection tomography method to image the entire crustal P‐wave velocity structure beneath the CVF by incorporating the direct P and the Moho reflected waves. Tomographic results reveal a significant low‐velocity anomaly right beneath the CVF in the upper‐middle crust, which dips southwards into the lower crust and extends to the Indian Wells Valley and the Garlock Fault. The low‐velocity anomaly in the upper‐middle crust is interpreted as a rhyolite magma reservoir (contains mostly crystallized silicic magma) directly supplying hot springs at or near the surface, whereas the low‐velocity anomaly in the lower crust is interpreted as a basaltic magma reservoir (contains fewer silica contents) that constitutes a continuous magma plumbing system mobilizing melts from the upper mantle along N‐S direction into the more eruptible shallower Coso reservoir. We obtain a new Vp model of the whole crust beneath the Coso volcanic field by inverting the first and Moho reflected P‐wave arrivalsOur model shows a pervasive low‐velocity anomaly in the upper‐middle crust, which dips southwards beneath the Coso volcanic fieldLower crust low Vp may represent a basaltic magma reservoir that ascends northwards and differentiates into a shallower rhyolite reservoir We obtain a new Vp model of the whole crust beneath the Coso volcanic field by inverting the first and Moho reflected P‐wave arrivals Our model shows a pervasive low‐velocity anomaly in the upper‐middle crust, which dips southwards beneath the Coso volcanic field Lower crust low Vp may represent a basaltic magma reservoir that ascends northwards and differentiates into a shallower rhyolite reservoir

Movement of the conductive subsurface medium in the Earth's magnetic field can generate electromagnetic (EM) disturbances. This phenomenon is referred to as the motional induction (MI) effect and, though previously proposed as a possible mechanism for the generation of earthquake‐associated EM signals, has not yet been well understood. In this study, we present a semianalytical method to derive the EM response to an earthquake due to the MI effect in a 3D horizontally layered model. We solve the coupled elastodynamic and Maxwell's equations in the frequency–wavenumber domain through the global matrix method and then compute the seismic and EM responses in the time domain. We first verify the proposed method by comparing results to the analytical solution in a full‐space model and then conduct numerical simulations to investigate the properties of the EM fields and their sensitivities to the rock conductivity. Finally, we use the proposed method to model coseismic EM data observed during the 2008 Mw6.1 Qingchuan earthquake. The results show that the simulated coseismic electric fields can fit the observed electric signals well in both arrival time and amplitude, suggesting that the MI effect is a possible mechanism for the generation of the observed electric signals. The simulated magnetic fields are 1 order of magnitude weaker in amplitude than the observed magnetic data, implying that the observed magnetic fields are mainly generated by other mechanisms. Much observational evidence shows that anomalous electromagnetic (EM) signals are detected during earthquakes. These EM signals have attracted a lot of attention because they might be useful for earthquake early warning and disaster mitigation. But we lack sufficient understanding. Although the motional induction (MI) effect has been proposed, the precise mechanism by which earthquake (rupture) energy transforms to EM energy is unclear. MI effect results from motion of the conductive subsurface medium in the ambient geomagnetic field due to the Faraday's law. In this study, we present a method to simulate the EM fields generated by the earthquake due to MI effect. Our results show that earthquakes can produce two kinds of EM signals. One arrives before the seismic waves (called early EM signals) and the other arrives simultaneously with seismic waves (called coseismic EM signals). We also use our method to simulate the EM data recorded during a real earthquake (which happened in 2008 in Sichuan, China). The synthetic coseismic electric fields can explain the observed data well, indicating that MI effect is an effective mechanism to produce the earthquake‐associated EM signals. We present a method to simulate electromagnetic field generated by an earthquake due to motional induction effect in 3D‐layered mediaNumerical simulations are conducted to investigate the character of the electromagnetic fields and their sensitivity to rock conductivityThe method is applied to the 2008 Qingchuan Mw6.1 earthquake; synthetic electric signals can explain observed electric signals We present a method to simulate electromagnetic field generated by an earthquake due to motional induction effect in 3D‐layered media Numerical simulations are conducted to investigate the character of the electromagnetic fields and their sensitivity to rock conductivity The method is applied to the 2008 Qingchuan Mw6.1 earthquake; synthetic electric signals can explain observed electric signals

Geomagnetic pulsations with an enhanced amplitude of 0.1–1 nT in a frequency band of 0.1–0.2 Hz were observed by three three‐component magnetometers. The geomagnetic pulsations exhibit slight time difference that is unusually observed within a limited area of ∼5 × 5 km2at the northern end of Taiwan. The time difference suggests the geomagnetic pulsations are not dominated by global effects but local ones. We compare the seismic signals recorded by the cosited broadband seismometers for investigating potential mechanisms of these geomagnetic pulsations. Results from analysis of both seismic and geomagnetic data exhibit consistent source azimuths from the Pacific Ocean to the northeast of the observation sites with a wave propagation speed of ∼2.9 km/s estimated based on P‐SV‐type microseisms. Polarization and particle motion analyses demonstrate that the geomagnetic pulsations move with an elliptical rotation form, showing a close association with the P‐SV‐type microseisms. The 90° phase difference between the horizontal and vertical components of the geomagnetic signals suggests that the time‐lagged geomagnetic pulsations are possibly caused by the motional induction effect after the arrivals of P‐SV‐type microseisms. Time‐lagged magnetic pulsations ranged at 0.1–0.2 Hz are observed in a limited areaElliptical particle motion suggests dominant P‐SV‐type microseismsTime‐lagged magnetic pulsations can be generated by the motional induction effect Time‐lagged magnetic pulsations ranged at 0.1–0.2 Hz are observed in a limited area Elliptical particle motion suggests dominant P‐SV‐type microseisms Time‐lagged magnetic pulsations can be generated by the motional induction effect