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The emergence and transmission of the colistin-resistance gene mcr and extended-spectrum β-lactamase (ESBL) encoding genes pose a significant threat to global public health. In recent years, it has been reported that mcr-1 and ESBL genes can coexist in single bacteria strain. The objective of this study was to characterize a multidrug-resistant (MDR) avian pathogenic Escherichia coli (APEC) isolate carrying mcr and ESBL encoding genes in China. A total of 200 APEC isolates were collected for antimicrobial susceptibility testing by Kirby–Bauer (K–B) disk method. The MDR strain EC012 were then further analyzed for minimum inhibitory concentrations, antimicrobials resistance genes (ARGs) detection, conjugation, and whole-genome sequencing (WGS). Among all APEC isolates determined by K–B disk method, strain EC012 was resistant to almost all the antimicrobials, including polymyxin B, cefotaxime, and ceftazidime. Moreover, EC012 harbored ARGs mcr-1, blaTEM-176, and blaCTX-M-14. WGS analysis revealed that EC012 belonged to epidemic APEC serotype O1:H16 and multilocus sequence type ST295. EC012 consisted of one chromosome and six plasmids, encoding a broad ARGs. The blaCTX-M-14, mcr-1 or blaTEM-176 genes were located on conjugative plasmids pEC012-1 or pEC012-5, respectively. These plasmids were successfully transferred to transconjugants and resulted in the resistance to polymyxin B, cefotaxime, and ceftazidime. This study indicated that APEC was a potential reservoir of colistin-resistance gene mcr-1 and ESBL encoding genes, and highlighted the necessity for enhanced monitoring of ARGs dissemination among bacteria from different origins. [ABSTRACT FROM AUTHOR]

The microstructure and mechanical properties of FeCr 2 VW x (x = 0, 0.1, 0.3, 0.5) medium-entropy alloys (MEAs) manufactured using arc melting under an argon atmosphere were investigated. The investigated FeCr 2 VW x (x = 0, 0.1, 0.3) MEAs exhibited a dual-phase microstructure consisting of body-centred-cubic (BCC) phases. With the further addition of W, additional W-rich phase formed in the microstructure of the FeCr 2 VW 0.5 sample. Compression tests at the ambient and elevated temperatures revealed that the compressive performance of the MEAs improved with the introduction of W. Among them, FeCr 2 VW 0.3 demonstrated an exceptional combination of enhanced strength and ductility, showing the yield strength of 1452 MPa at ambient temperature and 627 MPa at 1223 K as well as compression reduction over 30% at both temperatures. These compressive properties are comparable to those of existing low activation refractory high-entropy alloys. The excellent high-temperature performance was attributed to the enhanced strengthening effects of precipitation and solid-solution resulting from W addition. Moreover, it was found that during the hot deformation process FeCr 2 VW x MEAs with higher W contents (above 0.3) resulted in more work hardening than that of the lower W contents, and required more dynamic recrystallization to achieve the dynamic equilibrium. These results provide valuable insights for the future development and microstructural engineering of new MEAs. • Microstructure and mechanical properties at room and high temperatures of novel low-activation high-entropy alloys, FeCr 2 VWx (x = 0, 0.1, 0.3, 0.5), were studied. • The effect of W alloying on the microstructure and hot compression properties of the prepared alloys were revealed. • FeCr 2 VW 0.3 showed superior strength at both ambient and elevated temperatures, attributed to the combined effects of precipitation and solid solution strengthening. [ABSTRACT FROM AUTHOR]

Two-dimensional photonic crystals (2D PhCs) select photons by cavity resonance, and can be used to design selective filters for thermophotovoltaic (TPV) applications. Due to the broad pass band and high out-band reflectance of the 2D PhC structure, the TPV system can achieve both high power density and high efficiency. However, the absorption during cavity resonance restrains the further improvement of performance. In this article, a 2D metallic PhC layer was added on top of a one-dimensional photonic crystal filter, and the best geometric parameters were obtained. The simulation indicated that the parasitic absorption of the optimized tandem photonic crystal filter can be reduced to half of the traditional metallic 2D PhC filters. The new filter also shows a sharper cut-off edge and better in-band transmittance. Moreover, an ideal thermodynamic model was applied to estimate the performance of TPV systems with a filter. Using a 1200 ∘C blackbody emitter, the spectral efficiency of the tandem photonic crystal filter can reach 73%, and the in-band transmittance is over 80%. When optimizing the filter based on existing GaSb cells, the system power conversion efficiency can reach 28%. • The filter achieves excellent out-band reflectance and high in-band transmittance. • The tandem PhC structure significantly reduces the parasitic absorption of filters. • A simplified scheme for calculating effective radiant heat transfer in TPV systems. • The efficiency of TPV system with GaSb cell can be expected to be 28% at 1473 K. [ABSTRACT FROM AUTHOR]

In this paper, we propose and numerically characterize the optical characteristics of a dual eccentric-core D-shaped photonic crystal fiber (PCF) surface plasmon resonance (SPR) refractive index (RI) sensor. The dual eccentric-core structure can leak more power to plasma film to excite SPR phenomenon than conventional structures. We investigate the influences induce by diameter of air holes, distance between air holes and thickness of gold film. The results show that our sensor has the wavelength sensitivities (WS) of 44,000 nm/RIU for odd mode and 39,000 nm/RIU for even mode. Moreover, the sensor has the detection range of RI from 1.00 to 1.37, the maximum figure-of-merit (FOM) of 325/RIU, maximum resolution of 2.27 × 10−6 RIU for analyte RI change of 0.1 nm, and the minimum full-width at half-maximum (FWHM) of 56 nm. The sensor has wide application prospects in methane, blood plasma, and methanol detecting. [ABSTRACT FROM AUTHOR]

The equivalence of absorption rates and extents between generic drugs and their reference formulations is crucial for ensuring therapeutic comparability. Bioequivalence (BE) studies are widely utilized and play a pivotal role in substantiating the approval and promotional efforts for generic drugs. Virtual BE simulation is a valuable tool for mitigating risks and guiding clinical BE studies, thereby minimizing redundant in vivo BE assessments. Herein, we successfully developed a physiologically based absorption model for virtual BE simulations, which precisely predicts the BE of the apixaban test and reference formulations. The modeling results confirm that the test and reference formulations were bioequivalent under both fasted and fed conditions, consistent with clinical studies. This highlights the efficacy of physiologically based absorption modeling as a powerful tool for formulation screening and can be adopted as a methodological and risk assessment strategy to detect potential clinical BE risks. [ABSTRACT FROM AUTHOR]

In the development of atomic physics, laser sources with Frequencies corresponding to atomic transition and high stability are essential. The Faraday laser is a special diode laser using the Faraday anomalous dispersion optical filter (FADOF) to realize frequency selection, so the output laser frequency is automatically limited to the atomic Doppler broadening. However, the frequency of a Faraday laser corresponds to the range around only one atomic hyperfine transition. Here, we realize a switchable Faraday laser with two isotopes laser frequencies corresponding to 85Rb 5 2 S 1 / 2 (F = 3) → 5 2 P 3 / 2 and 87Rb 5 2 S 1 / 2 (F = 2) → 5 2 P 3 / 2 transitions based on a single isotope 87Rb-FADOF. The laser has good robustness against the fluctuation of diode current and temperature, with wavelength fluctuating within 0.8 pm from 16 to 30 °C of diode temperature, and has a free-running linewidth of 18 kHz. We also lock the laser frequency to the two cycling transitions of 85Rb 5 2 S 1 / 2 (F = 3) → 5 2 P 3 / 2 (F ′ = 4) and 87Rb 5 2 S 1 / 2 (F = 2) → 5 2 P 3 / 2 (F ′ = 3) by the modulation transfer spectroscopy technique. The Allan deviation of the residual error signal is 3 × 10 − 14 / τ , and the frequency stability of the beat detection reaches 2.8 × 10 − 12 at 1 s integration time. This 780 nm switchable Faraday laser expands the application scenarios of Faraday lasers, which can be used in laser cooling atoms, optical frequency standards, and other quantum precision measurement fields. [ABSTRACT FROM AUTHOR]

• DHM-FDEM for reproducing rock meso-macro mechanical behavior with acceptable computational costs is proposed. • Upscale elements assembly to establish connections between rock meso- and macro- mechanical properties is constructed. • A data-driven method to predict rock inherent heterogeneity and irreversible damage is established. This study presents a data-driven based hierarchical multiscale combined finite-discrete element method (DHM-FDEM) for accurately reproducing rock macro-scale mechanical behavior while ensuring acceptable computational costs. To construct the DHM-FDEM scheme, firstly, upscale finite elements assembly (UFEA) and upscale crack elements assembly (UCEA) are constructed, incorporating meso-scale finite elements and crack elements with mechanical parameters directly derived from meso mechanics test results. Then, a conversion method is proposed to transform the mechanical response of UFEA and UCEA into a strain-stress pair of the macro-scale element, avoiding directly solving the mechanical state of macro-scale elements with mismatched mechanical parameters, thus ensuring the accurate reproduction of rock mechanical properties. Furthermore, UFEA and UCEA subjected to various loading paths are conducted by meso-scale FDEM to generate data sets comprising sequential strain-stress pairs with history dependence and one-to-many mapping relationships. The generated data sets are then applied to train a data-driven method, long short-term memory with mixture density network (LSTM-MDN), which directly maps strain input to stress output, thus replacing tedious and repetitive meso-scale FDEM computation on UFEA and UCEA to significantly save computational costs. Subsequently, UFEA and UCEA driven by LSTM-MDN are equivalent to macro-scale FDEM elements, replacing their phenomenological constitutive relationships and thereby achieving the multiscale numerical computation scheme. After that, the uniaxial compression test and Brazilian disk test are conducted to validate the computational accuracy and efficiency of DHM-FDEM. Finally, the capability of DHM-FDEM to accurately reproduce rock accumulated damage from loading-unloading cycles is verified through uniaxial and biaxial cyclic loading-unloading tests. [ABSTRACT FROM AUTHOR]

The asymmetric wave equation encompasses the influence of the actual fine structure inside the medium on the wave field, which can better represent the complex seismic wavefield excited by the complex source and reflect the scale effects of the seismic wave response under equal computational power. However, when the finite-difference (FD) operator is applied to implement the numerical modelling using the asymmetric wave equation, numerical dispersion appears due to the use of difference operator to approximate the differential operator, which negatively affects the analysis of the seismic wavefield. To suppress the numerical dispersion, this paper proposes an improved Dung Beetle optimization (IDBO) algorithm to obtain the optimized FD operators. The IDBO algorithm adopts an improved Tent map and the opposition-based learning strategy to initialize the population, which improves the diversity of the population. The nonlinear function adaptive control strategy is introduced to adjust the population allocation ratio and boundary selection parameter R to achieve an adequate balance between global exploration and local exploitation. In addition, adaptive weights and the Levy flight mechanism are combined to improve the ball-rolling dung beetle position updating strategy to avoid falling into local extremes. Numerical dispersion analysis and numerical modelling results demonstrate that the optimization of FD operators based on the IDBO algorithm can effectively suppress numerical dispersion. It is of great significance to extract the wave field perturbation caused by heterogeneity due to the complex microstructure in the medium and analyse the influence of the microstructural properties in the medium on seismic wave propagation. [ABSTRACT FROM AUTHOR]

In this study, an enhanced numerical manifold method (NMM) simulator is developed to determine the combined impacts of reinforcement range and grouting timing on the effectiveness of grouting reinforcement for preventing the large deformation geo-hazard during the tunnel excavation through a fault rupture zone. To accomplish this objective, the limitations of the current two-dimensional simulation method, which lacks connection to the actual tunnel excavation process, are overcome by proposing a novel softening path function. Using this novel softening path function, each simulation step is given a specific physical meaning, establishing a connection to the actual tunnel excavation process. This improvement enables more accurate and analyzable simulation outcomes. To verify the accuracy of the proposed softening path function, a series of simulations of tunnel excavation are conducted using this softening path function. These results align closely with the results obtained by other reliable numerical methods and previous studies. After validation, several sets of numerical cases are conducted, considering 6 different geo-stress conditions, 10 different grouting reinforcement ranges, and 7 different grouting timings. Based on these simulation results, a critical value for reinforcement range, which equals to the diameter of tunnel face, is identified, and it is founded that delaying the grouting timing can increase the slurry migration range up to 94.6%. Furthermore, delaying the grouting timing can also reduce the convergence displacement of reinforced surrounding rocks after excavation up to 18.2% within a geo-stress range of 10 to 20 MPa. • A novel softening path function with clear physical meanings for tunnel excavation simulations is proposed. • A critical value of the grouting reinforcement range is identified. • Influences of grouting timing on the slurry migration range are revealed. • Influences of grouting timing on the convergence displacement of tunnels are revealed. [ABSTRACT FROM AUTHOR]

The determination of fundamental rock mechanical properties, uniaxial compression strength (UCS) and elastic modulus (E), constitutes a pivotal facet of rock engineering design. However, deriving these properties directly from standard laboratory tests on rock core samples can be challenging, especially when dealing with deep high-stress rock formations and weak fractured strata. Thus, it is crucial to establish a cost-effective and practical approach for predicting the macro-mechanical properties of rocks in situ. In this study, a machine learning approach was proposed to predict UCS and E by upscaling meso -mechanical parameters at particle scale in low-porosity crystalline rocks. To expand the correlation database of rock meso -macro mechanical properties, the meso -mechanical parameters, including the fracture toughness, tensile strength of the rock crystal interface, and the elastic modulus of rock crystal, were accurately measured, using a newly designed mechanical apparatus and a nanoindentation device. The grain-based models implemented in the combined finite discrete element method (FDEM-GBM) were developed based on these experimental results, and their reliability was validated though standard tests. Subsequently, a database, including 225 groups of data, was established using the numerical method. Five machine learning algorithms were applied to develop prediction models for UCS and E through data training in the database. Excellent performance improvement was achieved through the application of the grid-search method. The results indicate the optimized kernel ridge regression (KRR) and gaussian process regression (GPR) models demonstrated excellent performance with relative average errors of 4.9% and 1.1% in predicting UCS and E , respectively. Finally, the predicted values of UCS and E were compared with the experimental results, validating the feasibility of the optimized KRR and GPR models. [ABSTRACT FROM AUTHOR]

In this paper, we present a tetragonal cluster-based photonic crystal fiber (PCF) surface plasmon resonance (SPR) sensor with high wavelength sensitivity (WS). Indium tin oxide (ITO), as a dielectric material with adjustable photoelectric properties and low loss in the infrared range, is used in this sensor. The central rectangular air hole is used to construct an asymmetric structure which enables the sensor work in y and x polarization. We optimized the structural parameters of the sensor and the result shows that the sensor has high WS of 31,500 nm/RIU and 31,000 nm/RIU, wavelength resolution of 3.17 × 10−6 RIU and 3.23 × 10−6 RIU, maximum AS of 141.0 RIU−1 and 148 RIU−1, the refractive index (RI) detection range of 1.32–1.42 for y and x polarization, respectively. The sensor shows great potential in the detection of plasma, ethanol, and silicone oil. [ABSTRACT FROM AUTHOR]