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In the era of 5G and beyond, dynamic Time Division Duplex (TDD) has become essential for supporting applications that demand high bandwidth and low latency. Emerging uplink-intensive use cases such as real-time video analytics, autonomous vehicles and augmented reality further complicate the balance between uplink and downlink resources. Despite their potential, TDD policies employed by current 5G networks remain underexplored. Our investigation reveals that existing TDD policies are static and predominantly downlink-focused, failing to adapt to fluctuating network demands. We introduce Wixor, a robust dynamic TDD policy adaptation system tailored for 5G and next-generation (xG) networks. It proactively adjusts the allocation of TDD resources between uplink and downlink, addressing various practical challenges. Prototyped on a programmable testbed, Wixor demonstrates substantial performance improvements across diverse applications, achieving up to 96.5% enhancement in Quality of Experience (QoE) compared to existing baselines. 

Abstract Nanostructured titania, TiO₂, holds significant importance in various scientific fields and technologies for their distinctive properties and multipurpose characteristics. In this article, the facile, economical, and scalable synthesis of 1D lepidocrocite, 1DL, titania nanostructures derived from a water‐soluble Ti precursor, titanium oxysulfate (with oxidation of Ti⁺⁴) at temperature <100 °C under atmospheric pressure is discussed. Titanium oxysulfate with tetramethyl ammonium hydroxide, TMAH, is simply reacted to yield individual lepidocrocite titania‐based chain‐forming nanofilaments, NFs, 6 × 6 Ųin minimal cross‐section and aspect ratios of ≈20 1DLs. If only ethanol is used for washing, the 1DL self‐assemble into ≈10 µm, porous mesostructured particles, PMPs. If water is used, quasi‐2D sheets form instead. Characterization of the resulting powders showed them to be quite similar to those derived from TiB₂, and other water‐insoluble Ti precursors. The 1DL bandgap energies are ≈4 eV, due to quantum confinement. They adsorbed rhodamine 6G. The latter also sensitized the 1DLs and allowed for dye degradation using only visible light. Used as electrodes in supercapacitors, the 1DLs can be cycled over 1.6 V and result in high power densities (300 W kg⁻¹). Stronger birefringence started to appear in samples with concentrations >15 gL⁻¹indicating the formation of a liquid crystal phase. This new synthesis protocol enables the cheaper scalable production of 1DLs with significant implications across various fields. 

Early detection of dental disease is crucial to prevent adverse outcomes. Today, dental X-rays are currently the most accurate gold standard for dental disease detection. Unfortunately, regular X-ray exam is still a privilege for billions of people around the world. In this paper, we ask: Can we develop a low-cost sensing system that enables dental self-examination in the comfort of one's home? This paper presents ToMoBrush, a dental health sensing system that explores using off-the-shelf sonic toothbrushes for dental condition detection. Our solution leverages the fact that a sonic toothbrush produces rich acoustic signals when in contact with teeth, which contain important information about each tooth's status. ToMoBrush extracts tooth resonance signatures from the acoustic signals to characterize the dental condition of each tooth. We further develop a data-driven signal processing pipeline to detect and discriminate different dental conditions. We evaluate ToMoBrush on 19 participants and dental-standard models for detecting common dental problems including caries, calculus, and food impaction, achieving a detection ROC-AUC of 0.90, 0.83, and 0.88 respectively. Interviews with dental experts further validate ToMoBrush's potential in enhancing at-home dental healthcare. 

Recent work has shown that repetition coding followed by interleaving induces signal structure that can be exploited to separate multiple co-channel user transmissions, without need for pilots or coordination/synchronization between the users. This is accomplished via a statistical learning technique known as canonical correlation analysis (CCA), which works even when the channels are time-varying. Previous analysis has established that it is possible to identify the user signals up to complex scaling in the noiseless case. This letter goes one important step further to show that CCA in fact yields the linear MMSE estimate of the user signals up to complex scaling, without using any explicit training. Instead, CCA relies only on the repetition and interleaving structure. This is particularly appealing in asynchronous ad-hoc and unlicensed setups, where tight user coordination is not practical. 

Channel estimation in rapidly time-varying or short and bursty communication scenarios is costly in terms of both pilot overhead and co-channel interference. In recent work, it was shown that multipath delay-diversity can be exploited to detect multiple co-channel user signals, provided that the relative multipath delays for the different users are distinct, and the two multipath ‘taps’ of each user have roughly commensurate power. These requirements may not hold naturally, however, especially for relatively narrowband or short-range transmissions with small delay spread. As an alternative, this paper advocates using dual antenna transmission in a manner that introduces artificial multipath and tight control of the power of the two channel taps, via baseband processing at the transmitter. The approach enjoys theoretical guarantees and affords simple decoding and accurate synchronization as a side bonus. Similar claims have been previously laid using packet repetition via a single transmit-antenna, but the dual-antenna artificial multipath scheme proposed herein doubles the transmission rate relative to packet repetition. Laboratory experiments using programmable radios are used to demonstrate successful operation of the proposed transmission scheme in practice.