Myanmar is located within an important geographic corridor of prehistoric demographic and technological exchange, yet relatively few archaeological sites have been securely dated. Here, the authors present a new radiocarbon chronology for Halin, a UNESCO-listed complex in the north-central Sagaing Division of Myanmar, which contributes to the generation of nuanced regional chronologies and to improving the temporal resolution of Southeast Asia more generally. Discussion of 94 radiocarbon determinates, together with site stratigraphy and pottery traditions, provides a chronological sequence from the early third millennium BC to the early second millennium AD. Corroboration of the beginning of this sequence would place Halin as the oldest currently dated Neolithic site in Mainland Southeast Asia and would provide support for the two-layer model of Neolithic migration.

Continuous risky decisions refer to decisions that involve trade-offs among options with persistent risks. People can use the probability of occurrence per unit time (e.g., ‘the probability of occurrence is 1% per month’) or the average time of risk occurrence (e.g., ‘the average occurrence time is 100 months’) to represent continuous risky options. In this study, we examined the effect of the presentation format (i.e., the probability of occurrence per unit time vs. the average time of risk occurrence) on continuous risky decisions in the gain domain and further explored the underlying mechanism. In Study 1 (N = 122), we demonstrated the effect of presentation format on continuous risky decisions and the moderating effect of the magnitude of probabilities. Specifically, when the probabilities were relatively low, compared with the probability of occurrence per unit time, using the average time of risk occurrence to present the continuous risky options led to more risk-averse decisions. However, when the probabilities were relatively high, compared with the probability of occurrence per unit time, the presentation format of the average time occurrence led to more risk-seeking decisions. In Study 2 (N = 136), we found that the moderating effect of the option probabilities on continuous risky decisions was mediated by the subjective attribute-wise difference judgment. In Study 3 (N = 221), we replicated the effect of presentation format on continuous risky decisions in more natural scenarios. The study offered a deep understanding of the mechanism of continuous risky decision-making, and the results were conducive to further developing theories in relevant fields.

Model order reduction (MOR) can provide low-dimensional numerical models for fast simulation. Unlike intrusive methods, nonintrusive methods are attractive because they can be applied even without access to full order models (FOMs). Since nonintrusive MOR methods strongly rely on snapshots of the FOMs, constructing good snapshot sets becomes crucial. In this work, we propose a novel active-learning-based approach for use in conjunction with nonintrusive MOR methods. It is based on two crucial novelties. First, our approach uses joint space sampling to prepare a data pool of the training data. The training data are selected from the data pool using a greedy strategy supported by an error estimator based on Gaussian process regression. Second, we introduce a case-independent validation strategy based on probably approximately correct learning. While the methods proposed here can be applied to different MOR methods, we test them here with artificial neural networks and operator inference.

Excitation–emission-spectral unmixing-based fluorescence resonance energy transfer (ExEm-spFRET) microscopy exhibits excellent robustness in living cells. We here develop an automatic ExEm-spFRET microscope with 3.04 s of time resolution for a quantitative FRET imaging. The user-friendly interface software has been designed to operate in two modes: administrator and user. Automatic background recognition, subtraction, and cell segmentation were integrated into the software, which enables FRET calibration or measurement in a one-click operation manner. In administrator mode, both correction factors and spectral fingerprints are only calibrated periodically for a stable system. In user mode, quantitative ExEm-spFRET imaging is directly implemented for FRET samples. We implemented quantitative ExEm-spFRET imaging for living cells expressing different tandem constructs (C80Y, C40Y, C10Y, and C4Y, respectively) and obtained consistent results for at least 3 months, demonstrating the stability of our microscope. Next, we investigated Bcl-xL-Bad interaction by using ExEm-spFRET imaging and FRET two-hybrid assay and found that the Bcl-xL-Bad complexes exist mainly in Bad-Bcl-xL trimers in healthy cells and Bad-Bcl-xL2 trimers in apoptotic cells. We also performed time-lapse FRET imaging on our system for living cells expressing Yellow Cameleon 3.6 (YC3.6) to monitor ionomycin-induced rapid extracellular Ca2+ influx with a time interval of 5 s for total 250 s.

Accurate predetermination of the quantum yield ratio (QA/QD) and the extinction coefficient ratio (KA/KD) between acceptor and donor is a prerequisite for quantitative fluorescence resonance energy transfer (FRET) imaging. We here propose a method to measure KA/KD and QA/QD by measuring the excitation–emission spectra (ExEm-spectra) of one dish of cells expressing m (≥3) kinds of FRET constructs. The ExEm-spectra images are unmixed to obtain the weight maps of donor (WD), acceptor (WA), and acceptor sensitization (WS). For each cell, the frequency distribution plots of the WS/WD and WS/WA images are fitted by using a single-Gaussian function to obtain the peak values of WS/WD (SD) and WS/WA (SA). The statistical frequency-SD/SA plots from all cells are fitted by using a multi-Gaussian function to obtain the peak values of both SD and SA, and then the ranges of WS/WD (RSD) and WS/WA (RSA) for each FRET construct are predetermined. Based on the predetermined RSD and RSA values of FRET constructs, our method is capable of automatically classifying cells expressing different FRET constructs. Finally, the WS/WD–WA/WD plot from different kinds of cells is linearly fitted to obtain KA/KD and QA/QD values.

Model order reduction (MOR) methods enable the generation of real-time-capable digital twins, with the potential to unlock various novel value streams in industry. While traditional projection-based methods are robust and accurate for linear problems, incorporating machine learning to deal with nonlinearity becomes a new choice for reducing complex problems. These kinds of methods are independent to the numerical solver for the full order model and keep the nonintrusiveness of the whole workflow. Such methods usually consist of two steps. The first step is the dimension reduction by a projection-based method, and the second is the model reconstruction by a neural network (NN). In this work, we apply some modifications for both steps respectively and investigate how they are impacted by testing with three different simulation models. In all cases Proper orthogonal decomposition is used for dimension reduction. For this step, the effects of generating the snapshot database with constant input parameters is compared with time-dependent input parameters. For the model reconstruction step, three types of NN architectures are compared: multilayer perceptron (MLP), explicit Euler NN (EENN), and Runge–Kutta NN (RKNN). The MLPs learn the system state directly, whereas EENNs and RKNNs learn the derivative of system state and predict the new state as a numerical integrator. In the tests, RKNNs show their advantage as the network architecture informed by higher-order numerical strategy.

The dynamical stability of the cable-driven lower-limb rehabilitation training robot (CLLRTR) is a crucial question. Based on the established dynamics model of CLLRTR, the solution to the wrench closure of the under-constrained system is presented. Secondly, the stability index of CLLRTR is proposed by the Krasovski method. Finally, in order to analyze the stability distribution of CLLRTR in the workspace, the stability evaluation index in the workspace is calculated using the eigenvalue decomposition method. The stability distribution laws of CLLRTR are further verified by the experimental study. The results provide references for studying trajectory planning and anti-pendulum control of CLLRTR.

Ambient temperature α-to-β phase transition and nanocrystallization in the aged Ti–25Nb–3Mo–3Zr–2Sn titanium alloy was achieved by surface mechanical attrition treatment (SMAT). The phase transition occurs at α/β interfaces and extends to α phase interiors with increasing strain. It is irreversible and diffusion controlled. The stress-induced increase of Gibbs energy and enrichment of Nb may cause a high order of lattice instability of the α phase adjacent to the α/β interfaces and compel the α phase to β phase. The presence of fine α needles in the aged alloy and the phase transition from α to β with increasing strain are viewed to play a crucial role in the subsequent nanostructuring.

The influence of casting temperatures on microstructures and mechanical properties of rapidly solidified Cu50Zr45.5Ti2.5Y2 alloy was investigated. With increasing casting temperatures, the amount of the crystalline phase decreases. At a high casting temperature, i.e., 1723 K, glass-forming ability (GFA) of the present alloy is enhanced. The results imply that adjusting the casting temperature could be used for designing the microstructures of bulk metallic glass matrix composite. Nanoindentation tests indicated that CuZr phases are slightly softer and can accommodate more plastic deformation than the amorphous matrix. Compression tests confirmed that this kind of second phase (CuZr) precipitated under lower casting temperatures helps to initiate multiple shear bands, resulting in a great improvement in mechanical properties of the samples. Our work indicates that casting temperatures have a great influence on GFA, microstructures, and mechanical properties of the rapidly solidified alloy, therefore controlling the casting temperature is crucial to the production of BMGs.