Comparator Design in Sensors for Environmental Monitoring

This paper presents circuit design considerations of comparator in analog-to-digital converters (ADC) applied for a portable, low-cost and high performance nano-sensor chip which can be applied to detect the airborne magnetite pollution nano particulate matter (PM) for environmental monitoring. High-resolution ADC plays a vital important role in high perfor-mance nano-sensor, while high-resolution comparator is a key component in ADC. In this work, some important design issues related to comparators in analog-to-digital converters (ADCs) are discussed, simulation results show that the resolution of the comparator proposed can achieve 5µV , and it is appropriate for high-resolution application

Robust Dual-Modal Speech Keyword Spotting for XR Headsets

While speech interaction finds widespread utility within the Extended Reality (XR) domain, conventional vocal speech keyword spotting systems continue to grapple with formidable challenges, including suboptimal performance in noisy environments, impracticality in situations requiring silence, and susceptibility to inadvertent activations when others speak nearby. These challenges, however, can potentially be surmounted through the cost-effective fusion of voice and lip movement information. Consequently, we propose a novel vocal-echoic dual-modal keyword spotting system designed for XR headsets. We devise two different modal fusion approches and conduct experiments to test the system's performance across diverse scenarios. The results show that our dual-modal system not only consistently outperforms its single-modal counterparts, demonstrating higher precision in both typical and noisy environments, but also excels in accurately identifying silent utterances. Furthermore, we have successfully applied the system in real-time demonstrations, achieving promising results. The code is available at https://github.com/caizhuojiang/VE-KWS.Comment: Accepted to IEEE VR 202

Critical transitions on route to chaos of natural convection on a heated horizontal circular surface

The transition route and bifurcations of the buoyant flow developing on a heated circular horizontal surface are elaborated using direct numerical simulations and direct stability analysis. A series of bifurcations, as a function of Rayleigh numbers (Ra) ranging from $10^1$ to $6\times10^7$, are found on the route to the chaos of the flow at $Pr=7$. When $Ra<1.0\times10^3$, the buoyant flow above the heated horizontal surface is dominated by conduction, because of which distinct thermal boundary layer and plume are not present. At $Ra=1.1\times10^6$, a Hopf bifurcation occurs, resulting in the flow transition from a steady state to a periodic puffing state. As Ra increases further, the flow enters a periodic rotating state at $Ra=1.9\times10^6$, which is a unique state that was rarely discussed in the literature. These critical transitions, leaving from a steady state and subsequently entering a series of periodic states (puffing, rotating, flapping and doubling) and finally leading to chaos, are diagnosed using spectral analysis and two-dimensional Fourier Transform (2DFT). Moreover, direct stability analysis is conducted by introducing random numerical perturbations into the boundary condition of the surface heating. We find that when the state of a flow is in the vicinity of bifurcation points (e.g., $Ra=2.0\times10^6$), the flow is conditionally unstable to perturbations, and it can bifurcate from the rotating state to the flapping state in advance. However, for relatively stable flow states, such as at $Ra=1.5\times10^6$, the flow remains its periodic puffing state even though it is being perturbed

One-shot ultraspectral imaging with reconfigurable metasurfaces

One-shot spectral imaging that can obtain spectral information from thousands of different points in space at one time has always been difficult to achieve. Its realization makes it possible to get spatial real-time dynamic spectral information, which is extremely important for both fundamental scientific research and various practical applications. In this study, a one-shot ultraspectral imaging device fitting thousands of micro-spectrometers (6336 pixels) on a chip no larger than 0.5 cm$^2$, is proposed and demonstrated. Exotic light modulation is achieved by using a unique reconfigurable metasurface supercell with 158400 metasurface units, which enables 6336 micro-spectrometers with dynamic image-adaptive performances to simultaneously guarantee the density of spectral pixels and the quality of spectral reconstruction. Additionally, by constructing a new algorithm based on compressive sensing, the snapshot device can reconstruct ultraspectral imaging information ($\Delta\lambda$/$\lambda$~0.001) covering a broad (300-nm-wide) visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm standard deviation and spectral resolution of 0.8 nm. This scheme of reconfigurable metasurfaces makes the device can be directly extended to almost any commercial camera with different spectral bands to seamlessly switch the information between image and spectral image, and will open up a new space for the application of spectral analysis combining with image recognition and intellisense

Stimulus-responsive tumor supramolecular nanotherapeutic system based on indocyanine green

Indocyanine green (ICG), a clinical near-infrared fluorescent probe, has the potential to be used as an integrated diagnostic and therapeutic agent for tumors. In this study, ICG-COOH-TK was obtained by connecting ICG molecules through stimulus-responsive thioketone (TK) bond, which can self-assemble into nanoparticles in water. Under 808 nm near-infrared light irradiation, the molecule exhibited excellent photothermal conversion efficiency, as well as better photostability and in vivo circulation stability than free ICG. The nanoparticle can respond to reactive oxygen species (ROS) overexpression in the tumor microenvironment and release ICG upon disassembly, resulting in significantly enhanced fluorescence emission at the tumor. In vitro cell experiments demonstrated excellent biocompatibility and photothermal killing effect on cancer cells, indicating that this molecule can serve as a diagnostic and therapeutic agent for fluorescence-guided tumor photothermal therapy

BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts

Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda. However, advanced Twitter bots often attempt to mimic the characteristics of genuine users through feature manipulation and disguise themselves to fit in diverse user communities, posing challenges for existing Twitter bot detection models. To this end, we propose BotMoE, a Twitter bot detection framework that jointly utilizes multiple user information modalities (metadata, textual content, network structure) to improve the detection of deceptive bots. Furthermore, BotMoE incorporates a community-aware Mixture-of-Experts (MoE) layer to improve domain generalization and adapt to different Twitter communities. Specifically, BotMoE constructs modal-specific encoders for metadata features, textual content, and graphical structure, which jointly model Twitter users from three modal-specific perspectives. We then employ a community-aware MoE layer to automatically assign users to different communities and leverage the corresponding expert networks. Finally, user representations from metadata, text, and graph perspectives are fused with an expert fusion layer, combining all three modalities while measuring the consistency of user information. Extensive experiments demonstrate that BotMoE significantly advances the state-of-the-art on three Twitter bot detection benchmarks. Studies also confirm that BotMoE captures advanced and evasive bots, alleviates the reliance on training data, and better generalizes to new and previously unseen user communities.Comment: Accepted at SIGIR 202

Microwave electrometry with Rydberg atoms in a vapor cell using microwave amplitude modulation

We have theoretically and experimentally studied the dispersive signal of the Rydberg atomic electromagnetically induced transparency (EIT) - Autler-Townes (AT) splitting spectra obtained using amplitude modulation of the microwave (MW) field. In addition to the two zero-crossing points, the dispersion signal has two positive maxima with an interval defined as the shoulder interval of the dispersion signal $\Delta f_{\text{sho}}$. The relationship of MW field strength $E_{\text{MW}}$ and $\Delta f_{\text{sho}}$ are studied at the MW frequencies of 31.6 GHz, 22.1 GHz, and 9.2 GHz respectively. The results show that $\Delta f_{\text{sho}}$ can be used to character the much weaker $E_{\text{MW}}$ than the interval of two zero-crossing points $\Delta f_{\text{zeros}}$ and the traditional EIT-AT splitting interval $\Delta f_{\text{m}}$, the minimum $E_{\text{MW}}$ measured by $\Delta f_{\text{sho}}$ is about 30 times smaller than that by $\Delta f_{\text{m}}$. As an example, the minimum $E_{\text{MW}}$ at 9.2 GHz that can be characterized by $\Delta f_{\text{sho}}$ is 0.056 mV/cm, which is the minimum value characterized by frequency interval using vapour cell without adding any auxiliary fields. The proposed method can improve the weak limit and sensitivity of $E_{\text{MW}}$ measured by spectral frequency interval, which is important in the direct measurement of weak $E_{\text{MW}}$