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The addition of methylammonium chloride (MACl) significantly improves the performance and stability of perovskite fabricated by two-step processes. However, its role in crystallization dynamics has not been thoroughly studied. In this work, a comparison study is carried out using different additions of MACl to investigate the impact of the perovskite crystallization dynamics. In situ grazing incidence wide-angle X-ray scattering (GIWAXS) observations during the annealing process of perovskite revealed that the amount of MACl significantly influences the crystallinity and orientation of the perovskite. Increasing the MACl addition enhances the crystallinity of the perovskite in the wet film's intermediate phase and strengthens the out-of-plane orientation of the FAPbI3 perovskite α-phase (001) planes during annealing. Moreover, it was found that both excessive and insufficient amounts of MACl introduce defects into the perovskite, which are detrimental to device performance. In contrast, an optimal ratio of MACl-9 mg leads to the formation of uniform and large-grained FAPbI3 perovskite films, with the longest carrier lifetimes (163.7 ns) compared to MACl-5 mg (68.4 ns) and MACl- 13 mg (120.1 ns). As a result, the fabricated MACl-9 mg-based solar cell achieved the highest efficiency (22.63%), which is higher than those of MACl-5 mg (21.47%) and MACl-13 mg (20.07%). [ABSTRACT FROM AUTHOR]

The treadmill exercise test (TET) serves as a non-invasive method for the diagnosis of coronary artery disease (CAD). Despite its widespread use, TET reports are susceptible to external influences, heightening the risk of misdiagnosis and underdiagnosis. In this paper, we propose a novel automatic CAD diagnosis approach. The proposed approach introduces a customized preprocessing method to obtain clear electrocardiograms (ECGs) from individual TET reports. Additionally, it presents TETDiaNet, a novel neural network designed to explore the temporal relationships within TET ECGs. Central to TETDiaNet is the TETDia block, which mimics clinicians' diagnostic processes to extract essential diagnostic information. This block encompasses an intra-state contextual learning module and an inter-state contextual learning module, modeling the temporal relationships within a single state and between states, respectively. These two modules help the TETDia block to capture effective diagnosis information by exploring the temporal relationships within TET ECGs. Furthermore, we establish a new TET dataset named TET4CAD for CAD diagnosis. It contains simplified TET reports for 192 CAD patients and 224 non-CAD patients, and each patient undergoes coronary angiography for labeling. Experimental results on TET4CAD underscore the superior performance of the proposed approach, highlighting the discriminative value of the temporal relationships within TET ECGs for CAD diagnosis. [ABSTRACT FROM AUTHOR]

An intelligent, vision-guided welding robot is highly desired in machinery manufacturing, the ship industry, and vehicle engineering. The performance of the system greatly depends on the effective identification of weld seam features and the three-dimensional (3D) reconstruction of the weld seam position in a complex industrial environment. In this paper, a 3D visual sensing system with a structured laser projector and CCD camera is developed to obtain the geometry information of fillet weld seams in robot welding. By accounting for the inclination characteristics of the laser stripe in fillet welding, a Gaussian-weighted PCA-based laser center line extraction method is proposed. Smoother laser centerlines can be obtained at large, inclined angles. Furthermore, an improved chord-to-point distance accumulation (CPDA) method with polygon approximation is proposed to identify the feature corner location in center line images. The proposed method is validated numerically with simulated piece-wise linear laser stripes and experimentally with automated robot welding. By comparing this method with the grayscale gravity method, Hessian-matrix-based method, and conventional CPDA method, the proposed improved CPDA method with PCA center extraction is shown to have high accuracy and robustness in noisy welding environments. The proposed method meets the need for vision-aided automated welding robots by achieving greater than 95% accuracy in corner feature point identification in fillet welding. [ABSTRACT FROM AUTHOR]

The arc sound signal is one of the most important aspects of information related to pattern identification regarding the penetration state of ship robotic GMAW; however, arc sound is inevitably affected by noise interference during the signal acquisition process. In this paper, an improved wavelet threshold denoising method is proposed to eliminate interference and purify the arc sound signal. The non-stationary random distribution characteristics of GMAW noise interference are also estimated by using the high-frequency detail coefficients in different domains after wavelet transformation, and a mode of measuring scale that is logarithmically negatively correlated with the wavelet decomposition scale is created to update the threshold. The gradient convergent threshold function is established using the natural logarithmic function structure and concave–convex gradient to enable the nonlinear adjustment of the asymptotic rate. Further, some property theorems related to the optimized threshold function are proposed and theoretically proven, and the effectiveness and adaptability of the improved method are verified via the denoising simulation of speech synthesis signals. The four traditional denoising methods and our improved version are applied in the pretreatment of the GMAW arc sound signal, respectively. Statistical analysis and short-time Fourier transform are used to extract eight-dimensional time and frequency domain feature parameters from the denoised signals with randomly time-varying characteristics, and the extracted joint feature parameters are used to establish a nonlinear mapping model of penetration state identification for ship robotic GMAW using the pattern classifiers of RBFNN, PNN and PSO-SVM. The simulation results yielded by visual penetration classification and the multi-dimensional evaluation index of the confusion matrix indicate that the improved denoising method proposed in this paper achieves a higher accuracy in the extraction of penetration state features and greater precision in the identification of pattern classification. [ABSTRACT FROM AUTHOR]

Metal halide perovskite materials have demonstrated significant potential in various optoelectronic applications, such as photovoltaics, light emitting diodes, photodetectors, and lasers. However, the stability issues of perovskite materials continue to impede their widespread use. Many studies have attempted to understand the complex degradation mechanism and dynamics of these materials. Among them, in situ and/or operando approaches have provided remarkable insights into the degradation process by enabling precise control of degradation parameters and real-time monitoring. In this review, we focus on these studies utilizing in situ and operando approaches and demonstrate how these techniques have contributed to reveal degradation details, including structural, compositional, morphological, and other changes. We explore why these two approaches are necessary in the study of perovskite degradation and how they can be achieved by upgrading the corresponding ex situ techniques. With recent stability improvements of halide perovskite using various methods (compositional engineering, surface engineering, and structural engineering), the degradation of halide perovskite materials is greatly retarded. However, these improvements may turn into new challenges during the investigation into the retarded degradation process. Therefore, we also highlight the importance of enhancing the sensitivity and probing range of current in situ and operando approaches to address this issue. Finally, we identify the challenges and future directions of in situ and operando approaches in the stability research of halide perovskites. We believe that the advancement of in situ and operando techniques will be crucial in supporting the journey toward enhanced perovskite stability. [ABSTRACT FROM AUTHOR]

Part cleaning is very important for the assembly of precision machinery. After cleaning, the parts are randomly distributed in the collection area, which makes it difficult for a robot to collect them. Common robots can only collect parts located in relatively fixed positions, and it is difficult to adapt these robots to collect at randomly distributed positions. Therefore, a rapid part classification method based on a non-pooling YOLOv5 network for the recognition of randomly distributed multiple types of parts is proposed in this paper; this method classifies parts from their two-dimensional images obtained using industrial cameras. We compared the traditional and non-pooling YOLOv5 networks under different activation functions. Experimental results showed that the non-pooling YOLOv5 network improved part recognition precision by 8% and part recall rate by 3% within 100 epochs of training, which helped improve the part classification efficiency. The experiment showed that the non-pooling YOLOv5 network exhibited improved classification of industrial parts compared to the traditional YOLOv5 network. [ABSTRACT FROM AUTHOR]

In vitro expansion-mediated replicative senescence has severely limited the clinical applications of mesenchymal stem cells (MSCs). Accumulating studies manifested that nicotinamide adenine dinucleotide (NAD+) depletion is closely related to stem cell senescence and mitochondrial metabolism disorder. Promoting NAD+ level is considered as an effective way to delay aging. Previously, we have confirmed that nicotinamide mononucleotide (NMN), a precursor of NAD+, can alleviate NAD+ deficiency-induced MSC senescence. However, whether NMN can attenuate MSC senescence and its underlying mechanisms are still incompletely clear. The present study herein showed that late passage (LP) MSCs displayed lower NAD+ content, reduced Sirt3 expression and mitochondrial dysfunction. NMN supplementation leads to significant increase in intracellular NAD+ level, NAD+/ NADH ratio, Sirt3 expression, as well as ameliorated mitochondrial function and rescued senescent MSCs. Additionally, Sirt3 over-expression relieved mitochondrial dysfunction, and retrieved senescence-associated phenotypic features in LP MSCs. Conversely, inhibition of Sirt3 activity via a selective Sirt3 inhibitor 3-TYP in early passage (EP) MSCs resulted in aggravated cellular senescence and abnormal mitochondrial function. Furthermore, NMN administration also improves 3-TYP-induced disordered mitochondrial function and cellular senescence in EP MSCs. Collectively, NMN replenishment alleviates mitochondrial dysfunction and rescues MSC senescence through mediating NAD+/Sirt3 pathway, possibly providing a novel mechanism for MSC senescence and a promising strategy for anti-aging pharmaceuticals. [ABSTRACT FROM AUTHOR]

Quantitative probability has been computed for the tsunami hazard posed by earthquakes from the Manila Trench, which has been regarded as a huge threat in the South China Sea. This study provides a spatial distribution of the tsunami hazard covering the affected area with a spatial resolution of 0.1° for disaster prevention of islands and continental coasts. The quantitative probability of the tsunami hazard is computed by an efficient model, which can realize a large amount of potential tsunami scenarios analysis in order to consider the randomness and uncertainty in earthquake magnitude, source location and focal depth. In the model, for each potential tsunami scenario, the occurrence probability of the corresponding earthquake and the intensity of tsunami waves at each target location are computed. The occurrence probability of each scenario is estimated based on the historical earthquake records. Then, the subsequent tsunami caused by each scenario is computed using a new, efficient approach, instead of direct simulation using an ocean dynamics model. A total of 1,380,000 scenarios are computed in order to obtain a stable statistical result. Based on the results, the spatial distribution of the tsunami hazard is discussed and high-hazard regions along the coast have been identified. [ABSTRACT FROM AUTHOR]

The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and statistical test method are defined. The simulation verifies the effectiveness and superiority of the method compared with traditional methods. An empirical analysis uses the carbon price data of the European Union carbon market and seven pilot carbon markets in China. The results show many abrupt transitions in the carbon price series of the two markets, whose occurrence period is closely related to major events. [ABSTRACT FROM AUTHOR]

X-ray diffraction can non-destructively reveal microstructure information, including stress distribution on thermal coatings of aeroengine blades. In order to accurately pinpoint the detection position and precisely set the measurement geometry, a 3D camera is adopted to obtain the point cloud data on the blade surface and perform on-site modeling. Due to hardware limitations, the resolution of raw point clouds is insufficient. The point cloud needs to be upsampled. However, the current upsampling algorithm is greatly affected by noise and it is easy to generate too many outliers, which affects the quality of the generated point cloud. In this paper, a generative adversarial point cloud upsampling model is designed, which achieves better noise immunity by introducing dense graph convolution blocks in the discriminator. Additionally, filters are used to further process the noisy data before using the deep learning model. An evaluation of the network and a demonstration of the experiment show the effectivity of the new algorithm. [ABSTRACT FROM AUTHOR]

Discrete time crystals (DTC) have been demonstrated experimentally in several different quantum systems in the past few years. Spin couplings and cavity losses have been shown to play crucial roles for realizing DTC order in open many-body systems out of equilibrium. Recently, it has been proposed that eternal and transient DTC can be present with an open Floquet setup in the thermodynamic limit and in the deep quantum regime with few qubits, respectively. In this work, we consider the effects of spin damping and spin dephasing on the DTC order in spin-optomechanical and open cavity systems in which the spins can be all-to-all coupled. In the thermodynamic limit, it is shown that the existence of dephasing can destroy the coherence of the system and finally lead the system to its trivial steady state. Without dephasing, eternal DTC is displayed in the weak damping regime, which may be destroyed by increasing the all-to-all spin coupling or the spin damping. By contrast, the all-to-all coupling is constructive to the DTC in the moderate damping regime. We also focus on a model which can be experimentally realized by a suspended hexagonal boron nitride (hBN) membrane with a few spin color centers under microwave drive and Floquet magnetic field. Signatures of transient DTC behavior are demonstrated in both weak and moderate dissipation regimes without spin dephasing. Relevant experimental parameters are also discussed for realizing transient DTC order in such an hBN optomechanical system. [ABSTRACT FROM AUTHOR]

In this article, CsPbI2Br perovskite thin films were spin-coated on FTO, on which CuPc was deposited by thermal evaporation. The electronic structure at the CsPbI2Br/CuPc interface was examined during the CuPc deposition by in situ X-ray photoelectron spectroscopy (XPS) and ultraviolet photoelectron spectroscopy (UPS) measurements. No downward band bending was resolved at the CsPbI2Br side, whereas there is ~0.23 eV upward band bending as well as a dipole of ~0.08 eV identified at the molecular side. Although the hole injection barrier as indicated by the energy gap from CsPbI2Br valance band maximum (VBM) to CuPc highest occupied molecular orbital (HOMO) was estimated to be ~0.26 eV, favoring hole extraction from CsPbI2Br to CuPc, the electron blocking barrier of ~0.04 eV as indicated by the offset between CsPbI2Br conduction band minimum (CBM) and CuPc lowest unoccupied molecular orbital (LUMO) is too small to efficiently block electron transfer. Therefore, the present experimental study implies that CuPc may not be a promising hole transport material for high-performance solar cells using CsPbI2Br as active layer. [ABSTRACT FROM AUTHOR]

Blending perovskite with different cations has been successful in improving performance of perovskite solar cells, but the complex pathway of perovskite crystal formation remains a mystery, hindering its further development. In this paper, the detailed crystallization process of formamidinium lead iodide (FAPbI3) perovskite films doped by methylammonium lead bromide (MAPbBr3) additive was investigated by in situ grazing incident wide-angle X-ray scattering measurements during both spin coating and annealing. During spin-coating, it was found that the FAPbI3 perovskite precursor easily formed a mixture of black perovskite phase (α phase) and non-perovskite yellow phase (δ phase) after the addition of MAPbBr3, whereas only δ phase formed without MAPbBr3. The δ phase gradually converted to α phase during annealing and there was only α phase left in both films with and without MAPbBr3. However, the doped films presented high film quality without PbI2 residue in contrast to the undoped films. These findings imply that the MAPbBr3 additive can effectively suppress the formation of the unfavorable δ phase and trigger the formation of the optically active α phase even during spin-coating, which enhances the film quality possibly by removing the energy barriers from δ phase to α phase at room temperature. Finally, PSCs based on MAPbBr3-doped FAPbI3 were fabricated with a champion efficiency as high as 19.4% from 14.2% for the PSCs based on undoped FAPbI3. [ABSTRACT FROM AUTHOR]

In the present work, the localized features of adiabatic shear bands (ASBs) of our recently designed damage tolerance α+β dual-phase Ti alloy are investigated by the integration of electron backscattering diffraction and experimental and theoretical Schmid factor analysis. At the strain rate of 1.8 × 104 s−1 induced by a split Hopkinson pressure bar, the shear stress reaches a maximum of 1951 MPa with the shear strain of 1.27. It is found that the α+β dual-phase colony structures mediate the extensive plastic deformations along α/β phase boundaries, contributing to the formations of ASBs, microvoids, and cracks, and resulting in stable and unstable softening behaviors. Moreover, the dynamic recrystallization yields the dispersion of a great amount of fine α grains along the shearing paths and in the ASBs, promoting the softening and shear localization. On the contrary, low-angle grain boundaries present good resistance to the formation of cracks and the thermal softening, while the non-basal slipping dramatically contributes to the strain hardening, supporting the promising approaches to fabricate the advanced damage tolerance dual-phase Ti alloy. [ABSTRACT FROM AUTHOR]