Development of a recombinase-aided amplification combined with a lateral flow dipstick assay for rapid detection of H7 subtype avian influenza virus

Avian influenza viruses (AIV) pose a significant persistent threat to the public health and safety. It is estimated that there have been over 100 outbreaks caused by various H7 subtypes of avian influenza viruses (AIV-H7) worldwide, resulting in over 33 million deaths of poultry. In this study, we developed a recombinase-aided amplification combined with a lateral flow dipstick assay for the detection of hemagglutinin (HA) genes to provide technical support for rapid clinical detection of AIV-H7. The results showed that the assay can complete the reaction within 30 min at a temperature of 39°C. Specificity tests demonstrated that there was no cross-reactivity with other common poultry pathogens, including Newcastle disease virus (NDV) and infections bronchitis virus (IBV). The detection limit of this assay was 1 × 101 copies/μL, while RT-qPCR method was 1 × 101 copies/μL, and RT-PCR was 1 × 102 copies/μL. The κ value of the RT-RAA-LFD and RT-PCR assay in 132 avian clinical samples was 0.9169 (p < 0.001). These results indicated that the developed RT-RAA-LFD assay had good specificity, sensitivity, stability and repeatability and may be used for rapid detection of AIV-H7 in clinical diagnosis

Tm,Ho:Ca(Gd,Lu)AlO4 crystals: Crystal growth, structure refinement and Judd-Ofelt analysis

“Mixed” calcium rare-earth aluminate laser host crystals Ca(Gd,Lu)AlO4 (CALGLO) with up to 10.8 at.% Lu codoped with Tm3 + and Ho3 + ions are grown by the Czochralski method along the [001] direction. The segregation of rare-earth ions is studied. The crystal structure is refined by the Rietveld method. Tm,Ho:Ca(Gd, Lu)AlO4 crystallizes in the tetragonal system (sp. gr. I4/mmm) exhibiting a K2NiF4 type structure. The lattice constants are a = 3.6585(6) Å and c = 11.9660(9) Å for a crystal with a composition of CaG-d0.8947Lu0.0551Tm0.0448Ho0.0054AlO4. The stability of Ca(Gd,Lu)AlO4 solid-solutions is discussed. The polarized Raman spectra are measured, revealing a most intense mode at 311 cm 1 and a maximum phonon frequency of ~650 cm 1. The polarized absorption spectra are measured. The transition intensities for the Ho3 + ion are analyzed using the modified Judd-Ofelt theory accounting for configuration interaction

Prediction Model of Car Ownership Based on Back Propagation Neural Network Optimized by Particle Swarm Optimization

Aiming to address the problems of traditional BP neural networks, which include their slow convergence speed and low accuracy, a vehicle ownership prediction model based on a BP neural network with particle swarm optimization is proposed. The weights and thresholds of the BP neural network are optimized by PSO to make the prediction results more accurate. Based on the current literature regarding BP neural networks’ ability to predict car ownership, a 9-10-1 BP neural network structure model is established. A traditional BP neural network and a PSO-optimized BP neural network are used to predict car ownership at the same time. In order to compare their prediction accuracy, a genetic algorithm (GA) and whale optimization algorithm (WOA) are additionally selected to optimize the BP neural network as a control group to predict car ownership. The data on China’s car ownership from 2005 to 2021 were collected as experimental data. The data from 2005 to 2016 were used as training data, and the remaining data were used as validation data for model prediction. The results show that the PSO-optimized neural network only undergoes three iterations of training, and the convergence accuracy reaches 1.41 × 10−8. The relative error between the predicted value of car ownership and the corresponding real value is between 0.023 and 0.083, and the decisive coefficient R2 is 0.96002, indicating that the neural network has better prediction ability and higher prediction accuracy for car ownership. The particle swarm optimization algorithm is used to optimize the weights and thresholds of the BP neural network, which solves the problems of the traditional BP neural network, including the ease with which it falls into the local minimum value and its slow convergence speed, and improves its prediction accuracy of car ownership. Compared with the results optimized by the genetic algorithm and whale optimization algorithm, the error of the BP neural network optimized by PSO is the smallest, and the prediction accuracy is the highest. Through the comparative analysis of training results, it can be seen that the PSO-BP prediction model has the best stability and accuracy

Ternary Ag2Se1- xTex: A Near-Room-Temperature Thermoelectric Material with a Potentially High Figure of Merit

Discovering high-performance near-room-temperature thermoelectric materials is extremely imperative to widen the practical application in thermoelectric power generation and refrigeration. Here, ternary Ag2Se1–xTex (x = 0.1, 0.2, 0.3, 0.4, and 0.5) materials are prepared via the wet-mechanical alloying and spark plasma sintering process to investigate their near-room-temperature thermoelectric properties. From density functional theory calculation and single-parabolic-band modeling study, we found that the reduced contribution of Se 4p orbitals to the total density of states decreases the carrier effective mass with increasing Te content, which should enhance the theoretically maximum zT. These calculation results are also verified by the experimental results. Meanwhile, complex microstructures including dislocations, nanograins, high-density boundaries, TeSe substitution, lattice distortions, and localized strain have been observed in ternary Ag2Se1–xTex. These complex microstructures strengthen phonon scattering and in turn lead to ultralow lattice thermal conductivity in the range of 0.21–0.31 W m–1 K–1 in ternary Ag2Se1–xTex at 300 K. Although the increased deformation potential suppresses the carrier mobility, benefiting from the engineered band structures and ultralow lattice thermal conductivity, a high zT of >1 can be potentially obtained in the ternary Ag2Se1–xTex with appropriate carrier concentration. This study indicates that ternary Ag2Se1–xTex is a promising candidate for near-room-temperature thermoelectric applications.</p

A synergy of strain loading and laser radiation in determining the high-performing electrical transports in the single Cu-doped SnSe microbelt

Semiconducting microbelts are key components of the thermoelectric micro-devices, and their electrical transport properties play significant roles in determining the thermoelectric performance. Here, we report heavily Cu-doped single-crystal SnSe microbelts as potential candidates employed in thermoelectric micro-devices, fabricated by a facile solvothermal route. The considerable Cu-doping concentration of ∼11.8 % up to the solubility contributes to a high electrical conductivity of ∼416.6 S m-1 at room temperature, improved by one order of magnitude compared with pure SnSe (38.0 S m-1). Meanwhile, after loading ∼1 % compressive strain and laser radiation, the electrical conductivity can be further improved to ∼601.9 S m-1 and ∼589.2 S m-1, respectively, indicating great potentials for applying to thermoelectric micro-devices. Comprehensive structural and compositional characterizations indicate that the Cu+ doping state provides more hole carriers into the system, contributing to the outstanding electrical conductivity. Calculations based on first-principle density functional theory reveal that the heavily doped Cu lowers the Fermi level down into the valence bands, generating holes, and the 1 % strain can further reduce the bandgap, strengthening the ability to release holes, and, in turn, leading to such an excellent electrical transport performance. This study fills the gaps of finding novel materials as potential candidates employed in the thermoelectric micro-devices and provides new ideas for micro/nanoscale thermoelectric material design

Tm,Ho:Ca(Gd,Lu)AlO4 crystals: Polarized spectroscopy and laser operation

Tm3+,Ho3+-codoped and compositionally “mixed” disordered Ca(Ga,Lu)AlO4 aluminate crystals are promising materials for ultrashort pulse generation above 2 μm. Their polarized spectroscopic properties are studied and the effect of Lu3+ codoping on the inhomogeneous spectral broadening is verified. The peak stimulated-emission cross-section for the 5I7 → 5I8 Ho3+ transition is 1.05 × 10−20 cm2 at 2000 nm for π-polarization. The Tm3+ ↔ Ho3+ energy-transfer parameters are P28 = 1.42 and P71 = 0.090 [10−22 cm3μs−1] indicating a direct transfer with a thermal equilibrium time of 4.35 ms. The effective gain spectra for the codoped crystal are derived. For σ-polarization, the gain bandwidth at ∼2.04 μm is about 100 nm; particularly for this light polarization, Lu3+ codoping induces a noticeable red-shift of the emission spectra further beyond 2 μm. Using absorption studies at 12 K, the Stark splitting of the Tm3+ and Ho3+ multiplets is resolved. A laser-pumped Tm,Ho:Ca(Ga,Lu)AlO4 laser generated a maximum output power of 763 mW at 2078.6 nm with a slope efficiency of 26.4% and π-polarized emission. A continuous wavelength tuning between 1887.7 and 2127 nm (tuning range: 239.3 nm) was achieved for σ-polarization. Diode-pumped operation of a-cut and c-cut crystals was also studied