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Generating realistic audio for human actions is critical for applications such as film sound effects and virtual reality games. Existing methods assume complete correspondence between video and audio during training, but in real-world settings, many sounds occur off-screen or weakly correspond to visuals, leading to uncontrolled ambient sounds or hallucinations at test time. This paper introduces AV-LDM, a novel ambient-aware audio generation model that disentangles foreground action sounds from ambient background noise in in-the-wild training videos. The approach leverages a retrieval-augmented generation framework to synthesize audio that aligns both semantically and temporally with the visual input. Trained and evaluated on Ego4D and EPIC-KITCHENS datasets, along with the newly introduced Ego4D-Sounds dataset (1.2M curated clips with action-audio correspondence), the model outperforms prior methods, enables controllable ambient sound generation, and shows promise for generalization to synthetic video game clips. This work is the first to emphasize faithful video-to-audio generation focused on observed visual content despite noisy, uncurated training data. 

Transparent conductive oxides (TCOs) are gaining increasingly high research interest for integrated photonic devices due to the strong plasma dispersion effect and process compatibility with versatile optoelectronic platforms. In this perspective article, the authors gave a brief review of research efforts both on theoretical modeling and experimental demonstration of integrated photonic devices, especially on high-efficiency electro-optic modulators through the integration with plasmonics and silicon photonics. In addition, the authors discussed the challenge and opportunity associated with TCO photonic devices and the application in photonic integrated circuits (PICs) with emphasis on high mobility materials, high-speed E-O modulators, and large-scale integration. Finally, we conclude that collaboration with existing silicon photonics foundry is a necessary route to incorporate TCOs into existing PIC ecosystems. 

In this paper, we present the design, optimization, and implementation of a sub-wavelength grating (SWG) multi-mode interference coupler (MMI) on the silicon nitride photonic integrated circuit (PIC) platform with a significantly enhanced bandwidth compared to the conventional MMI. We extend the SWG MMI theory, previously presented for the silicon-on-insulator platform, to the Si₃N₄/SiO₂platform. Our approach involves an initial parameter optimization for a non-paired design, followed by a shift to a paired design that offers a smaller footprint and a broader bandwidth. The optimized SWG MMI exhibits a 1 dB bandwidth of 300 nm for both the insertion loss and power imbalance, making it a significant addition to silicon nitride photonics. 

Abstract Silicon microring modulator plays a critical role in energy-efficient optical interconnect and optical computing owing to its ultra-compact footprint and capability for on-chip wavelength-division multiplexing. However, existing silicon microring modulators usually require more than 2 V of driving voltage (V_pp), which is limited by both material properties and device structures. Here, we present a metal-oxide-semiconductor capacitor microring modulator through heterogeneous integration between silicon photonics and titanium-doped indium oxide, which is a high-mobility transparent conductive oxide (TCO) with a strong plasma dispersion effect. The device is co-fabricated by Intel’s photonics fab and our in-house TCO patterning processes, which exhibits a high modulation efficiency of 117 pm/V and consequently can be driven by a very low V_ppof 0.8 V. At a 11 GHz modulation bandwidth where the modulator is limited by the RC bandwidth, we obtained 25 Gb/s clear eye diagrams with energy efficiency of 53 fJ/bit. 

Performing alchemical transformations, in which one molecular system is nonphysically changed to another system, is a popular approach adopted in performing free energy calculations associated with various biophysical processes, such as protein–ligand binding or the transfer of a molecule between environments. While the sampling of alchemical intermediate states in either parallel (e.g., Hamiltonian replica exchange) or serial manner (e.g., expanded ensemble) can bridge the high-probability regions in the configurational space between two end states of interest, alchemical methods can fail in scenarios where the most important slow degrees of freedom in the configurational space are, in large part, orthogonal to the alchemical variable, or if the system gets trapped in a deep basin extending in both the configurational and alchemical space. To alleviate these issues, we propose to use alchemical variables as an additional dimension in metadynamics, making it possible to both sample collective variables and to enhance sampling in free energy calculations simultaneously. In this study, we validate our implementation of “alchemical metadynamics” in PLUMED with test systems and alchemical processes with varying complexities and dimensionalities of collective variable space, including the interconversion between the torsional metastable states of a toy system and the methylation of a nucleoside both in the isolated form and in a duplex. We show that multidimensional alchemical metadynamics can address the challenges mentioned above and further accelerate sampling by introducing configurational collective variables. The method can trivially be combined with other metadynamics-based algorithms implemented in PLUMED. The necessary PLUMED code changes have already been released for general use in PLUMED 2.8. 

Abstract Silicon microring resonators (Si-MRRs) play essential roles in on-chip wavelength division multiplexing (WDM) systems due to their ultra-compact size and low energy consumption. However, the resonant wavelength of Si-MRRs is very sensitive to temperature fluctuations and fabrication process variation. Typically, each Si-MRR in the WDM system requires precise wavelength control by free carrier injection using PIN diodes or thermal heaters that consume high power. This work experimentally demonstrates gate-tuning on-chip WDM filters for the first time with large wavelength coverage for the entire channel spacing using a Si-MRR array driven by high mobility titanium-doped indium oxide (ITiO) gates. The integrated Si-MRRs achieve unprecedented wavelength tunability up to 589 pm/V, or V_πL of 0.050 V cm with a high-quality factor of 5200. The on-chip WDM filters, which consist of four cascaded ITiO-driven Si-MRRs, can be continuously tuned across the 1543–1548 nm wavelength range by gate biases with near-zero power consumption. 

We demonstrated efficient gate-tuning on-chip wavelength division multiplexing filters using a silicon microring resonator array driven by high-mobility titanium-doped indium oxide gates. It shows extensive wavelength coverage for entire channel spacing over 5 nm. 

Abstract In many applications of hierarchical models, there is often interest in evaluating the inherent heterogeneity in view of observed data. When the underlying hypothesis involves parameters resting on the boundary of their support space such as variances and mixture proportions, it is a usual practice to entertain testing procedures that rely on common heterogeneity assumptions. Such procedures, albeit omnibus for general alternatives, may entail a substantial loss of power for specific alternatives such as heterogeneity varying with covariates. We introduce a novel and flexible approach that uses covariate information to improve the power to detect heterogeneity, without imposing unnecessary restrictions. With continuous covariates, the approach does not impose a regression model relating heterogeneity parameters to covariates or rely on arbitrary discretizations. Instead, a scanning approach requiring continuous dichotomizations of the covariates is proposed. Empirical processes resulting from these dichotomizations are then used to construct the test statistics, with limiting null distributions shown to be functionals of tight random processes. We illustrate our proposals and results on a popular class of two-component mixture models, followed by simulation studies and applications to two real datasets in cancer and caries research. 

Paleostress inversion of 141 outcrop-scale faults across the eastern flank of the southern Central Range of Taiwan, where leveling and GPS data suggest a steep gradient in rock uplift rates yields two main kinematic phases of deformation. Phase 1 consists of 93 normal faults that generally dip moderately northeast, whereas phase 2 consists of 48 strike-slip faults that generally dip steeply west-northwest. Both phases record NE-trending subhorizontal extension but different orientations of principal shortening; in phase 1, the principal shortening axis is nearly vertical, whereas in phase 2, it plunges gently to moderately southeast. The northeast extension is consistent with extension directions obtained from GPS and earthquake focal mechanisms in the central part of the southern Central Range. However, these indicators of contemporary deformation also reveal more complicated states of stress along the eastern and western flanks of the range and in the deep crust southwest of the range. We interpret these more complicated stress states as reflecting the “forceful extrusion” of the southern Central Range, where the lower crust is being pinched between more rigid crustal blocks represented by the Peikang High and the Luzon Arc. In this context, the temporal progress from strike-slip to normal faulting observed in outcrops may reflect the advection of the rocks from lower to higher structural levels. The northeast extension normal faults can be interpreted as accommodating the lateral and vertical movement of the crust in the southern Central Range. Based on thermochronological data and the onset of extrusion in southwest Taiwan in the late Pleistocene, we infer that this SW extrusion process may be younger than 0.5 Ma.