A Room-Temperature Ferroelectric Resonant Tunneling Diode

Resonant tunneling is a quantum-mechanical effect in which electron transport is controlled by the discrete energy levels within a quantum-well (QW) structure. A ferroelectric resonant tunneling diode (RTD) exploits the switchable electric polarization state of the QW barrier to tune the device resistance. Here, the discovery of robust room-temperature ferroelectric-modulated resonant tunneling and negative differential resistance (NDR) behaviors in all-perovskite-oxide BaTiO3/SrRuO3/BaTiO3 QW structures is reported. The resonant current amplitude and voltage are tunable by the switchable polarization of the BaTiO3 ferroelectric with the NDR ratio modulated by ≈3 orders of magnitude and an OFF/ON resistance ratio exceeding a factor of 2 × 104. The observed NDR effect is explained an energy bandgap between Ru-t2g and Ru-eg orbitals driven by electron–electron correlations, as follows from density functional theory calculations. This study paves the way for ferroelectric-based quantum-tunneling devices in future oxide electronics

Mapping white matter structural and network alterations in betel quid-dependent chewers using high angular resolution diffusion imaging

BackgroundTo evaluate brain white matter diffusion characteristics and anatomical network alterations in betel quid dependence (BQD) chewers using high angular resolution diffusion imaging (HARDI).MethodsThe current study recruited 53 BQD chewers and 37 healthy controls (HC) in two groups. We explored regional diffusion metrics alternations in the BQD group compared with the HC group using automated fiber quantification (AFQ). We further employed the white matter (WM) anatomical network of HARDI to explore connectivity alterations in BQD chewers using graph theory.ResultsBQD chewers presented significantly lower FA values in the left and right cingulum cingulate, the left and right thalamic radiation, and the right uncinate. The BQD has a significantly higher RD value in the right uncinate fasciculus than the HC group. At the global WM anatomical network level, global network efficiency (p = 0.008) was poorer and Lp (p = 0.016) was greater in the BQD group. At the nodal WM anatomical network level, nodal efficiency (p < 0.05) was lower in the BQD group.ConclusionOur findings provide novel morphometric evidence that brain structural changes in BQD are characterized by white matter diffusivity and anatomical network connectivity among regions of the brain, potentially leading to the enhanced reward system and impaired inhibitory control

Flexible and wearable acoustic wave technologies

Flexible and wearable acoustic wave technology has recently attracted tremendous attention due to their wide-range applications in wearable electronics, sensing, acoustofluidics, and lab-on-a-chip, attributed to its advantages such as low power consumption, small size, easy fabrication, and passive/wireless capabilities. Great effort has recently been made in technology development, fabrication, and characterization of rationally designed structures for next-generation acoustic wave based flexible electronics. Herein, advances in fundamental principles, design, fabrication, and applications of flexible and wearable acoustic wave devices are reviewed. Challenges in material selections (including both flexible substrate and piezoelectric film) and structural designs for high-performance flexible and wearable acoustic wave devices are discussed. Recent advances in fabrication strategies, wave mode theory, working mechanisms, bending behavior, and performance/evaluation are reviewed. Key applications in wearable and flexible sensors and acoustofluidics, as well as lab-on-a-chip systems, are discussed. Finally, major challenges and future perspectives in this field are highlighted

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Comparing Asset Pricing Factor Models under Multivariate t-Distribution: Evidence from China

Factor models provide a cornerstone for understanding financial asset pricing; however, research on China’s stock market risk premia is still limited. Motivated by this, this paper proposes a four-factor model for China’s stock market that includes a market factor, a size factor, a value factor, and a liquidity factor. We compare our four-factor model with a set of prominent factor models based on newly developed likelihood-ratio tests and Bayesian methods. Along with the comparison, we also find supporting evidence for the alternative t-distribution assumption for empirical asset pricing studies. Our results show the following: (1) distributional tests suggest that the returns of factors and stock return anomalies are fat-tailed and therefore are better captured by t-distributions than by normality; (2) under t-distribution assumptions, our four-factor model outperforms a set of prominent factor models in terms of explaining the factors in each other, pricing a comprehensive list of stock return anomalies, and Bayesian marginal likelihoods; (3) model comparison results vary across normality and t-distribution assumptions, which suggests that distributional assumptions matter for asset pricing studies. This paper contributes to the literature by proposing an effective asset pricing factor model and providing factor model comparison tests under non-normal distributional assumptions in the context of China

Gain-Loss Evaluation-Based Generic Selection for Steganalysis Feature

Fewer contribution feature components in the image high-dimensional steganalysis feature are able to increase the spatio-temporal complexity of detecting the stego images, and even reduce the detection accuracy. In order to maintain or even improve the detection accuracy while effectively reducing the dimension of the DCTR steganalysis feature, this paper proposes a new selection approach for DCTR feature. First, the asymmetric distortion factor and information gain ratio of each feature component are improved to measure the difference between the symmetric cover and stego features, which provides the theoretical basis for selecting the feature components that contribute to a great degree to detecting the stego images. Additionally, the feature components are arranged in descending order rely on the two measurement criteria, which provides the basis for deleting the components. Based on the above, removing feature components that are ranked larger differently according to two criteria. Ultimately, the preserved feature components are used as the final selected feature for training and detection. Comparison experiments with existing classical approaches indicate that this approach can effectively reduce the feature dimension while maintaining or even improving the detection accuracy. At the same time, it can reduce the detection spatio-temporal complexity of the stego images

SR-TTS: a rhyme-based end-to-end speech synthesis system

Deep learning has significantly advanced text-to-speech (TTS) systems. These neural network-based systems have enhanced speech synthesis quality and are increasingly vital in applications like human-computer interaction. However, conventional TTS models still face challenges, as the synthesized speeches often lack naturalness and expressiveness. Additionally, the slow inference speed, reflecting low efficiency, contributes to the reduced voice quality. This paper introduces SynthRhythm-TTS (SR-TTS), an optimized Transformer-based structure designed to enhance synthesized speech. SR-TTS not only improves phonological quality and naturalness but also accelerates the speech generation process, thereby increasing inference efficiency. SR-TTS contains an encoder, a rhythm coordinator, and a decoder. In particular, a pre-duration predictor within the cadence coordinator and a self-attention-based feature predictor work together to enhance the naturalness and articulatory accuracy of speech. In addition, the introduction of causal convolution enhances the consistency of the time series. The cross-linguistic capability of SR-TTS is validated by training it on both English and Chinese corpora. Human evaluation shows that SR-TTS outperforms existing techniques in terms of speech quality and naturalness of expression. This technology is particularly suitable for applications that require high-quality natural speech, such as intelligent assistants, speech synthesized podcasts, and human-computer interaction

Effect of heat input on the microstructure and mechanical properties of Ti–6Al–4V alloy repaired by wire-feed electron beam additive manufacturing

Wire-feed electron beam additive manufacturing (WFEBAM) was utilized to repair the damaged Ti6Al4V (abbreviated as Ti64) alloy with B and Y modified Ti64 wire, and the effect of heat input on the repaired microstructure and properties of Ti64 alloy was investigated. The results indicated that the sizes of prior columnar β grains and α laths increased gradually with increased heat input. Besides the fine acicular α laths, continuous αGB, and retained β phase, bits of needle-like TiB and Y2O3 nanoparticles were formed in the deposited zone (DZ) due to the addition of B and Y elements in Ti64 wire. In addition, the increased heat input reduced the microhardness and wear resistance of the DZ, while still being superior to the mechanical properties of Ti64 substrate. It is attributed to the refinement of α laths and precipitates. Compared with Ti64 substrate, the DZ in as-repaired sample 1# with the lowest heat input (288 J/mm) showed the maximum microhardness (386HV), 18% higher than that of Ti64 substrate. While the DZ 1# also obtained the lowest friction coefficient (0.49), about 80.3% of Ti64 substrate. The tensile strength and elongation of the DZ 1# were 840.6 MPa and 14%, respectively, both of which remained above 88% of Ti64 substrate. Therefore, the as-repaired sample 1# with the lowest heat input could meet the repair requirements

Alternating Positive and Negative Feedback Control Model Based on Catastrophe Theories

In automatic control systems, negative feedback control has the advantage of maintaining a steady state, while positive feedback control can enhance some activities of the control system. How to design a controller with both control modes is an interesting and challenging problem. Motivated by it, on the basis idea of catastrophe theories, taking positive feedback and negative feedback as two different states of the system, an adaptive alternating positive and negative feedback (APNF) control model with the advantages of two states is proposed. By adaptively adjusting the relevant parameters of the constructed symmetric catastrophe function and the learning rule based on error and forward weight, the two states can be switched in the form of catastrophe. Through the Lyapunov stability theory, the convergence of the proposed adaptive APNF control model is proven, which indicates that system convergence can be guaranteed by selecting appropriate parameters. Moreover, we present theoretical proof that the negative feedback system with negative parameters can be equivalent to the positive feedback system with positive parameters. Finally, the results of the simulation example show that APNF control has satisfactory performance in response speed and overshoot