Two dimensional electron gases in AlxGa1−xN/GaN based heterostructures, suitable for high electron mobility transistors, are induced by strong polarization effects. The sheet carrier concentration and the confinement of the two dimensional electron gases located close to the AlGaN/GaN interface are sensitive to a large number of different physical properties such as polarity, alloy composition, strain, thickness, and doping of the AlGaN barrier. We have investigated these physical properties for undoped and silicon doped transistor structures by a combination of high resolution x-ray diffraction, atomic force microscopy, Hall effect, and capacitance–voltage profiling measurements. The polarization induced sheet charge bound at the AlGaN/GaN interfaces was calculated from different sets of piezoelectric constants available in the literature. The sheet carrier concentration induced by polarization charges was determined self-consistently from a coupled Schrödinger and Poisson equation solver for pseudomorphically and partially relaxed barriers with different alloy compositions. By comparison of theoretical and experimental results, we demonstrate that the formation of two dimensional electron gases in undoped and doped AlGaN/GaN structures rely both on piezoelectric and spontaneous polarization induced effects. In addition, mechanisms reducing the sheet carrier concentrations like nonabrupt interfaces, dislocations, and the possible influence of surface states on the two dimensional electron gases will be discussed briefly.

Chronic inflammation generated by the tumor microenvironment is known to drive cancer initiation, proliferation, progression, metastasis, and therapeutic resistance. The tumor microenvironment promotes the secretion of diverse cytokines, in different types and stages of cancers. These cytokines may inhibit tumor development but alternatively may contribute to chronic inflammation that supports tumor growth in both autocrine and paracrine manners and have been linked to poor cancer outcomes. Such distinct sets of cytokines from the tumor microenvironment can be detected in the circulation and are thus potentially useful as biomarkers to detect cancers, predict disease outcomes and manage therapeutic choices. Indeed, analyses of circulating cytokines in combination with cancer-specific biomarkers have been proposed to simplify and improve cancer detection and prognosis, especially from minimally-invasive liquid biopsies, such as blood. Additionally, the cytokine signaling signatures of the peripheral immune cells, even from patients with localized tumors, are recently found altered in cancer, and may also prove applicable as cancer biomarkers. Here we review cytokines induced by the tumor microenvironment, their roles in various stages of cancer development, and their potential use in diagnostics and prognostics. We further discuss the established and emerging diagnostic approaches that can be used to detect cancers from liquid biopsies, and additionally the technological advancement required for their use in clinical settings.

Recent advancements and major breakthroughs in machine learning (ML) technologies in the past decade have made it possible to collect, analyze, and interpret an unprecedented amount of sensory information. A new era for “smart” sensor systems is emerging that changes the way that conventional sensor systems are used to understand the world. Smart sensor systems have taken advantage of classic and emerging ML algorithms and modern computer hardware to create sophisticated “smart” models that are tailored specifically for sensing applications and fusing diverse sensing modalities to gain a more holistic appreciation of the system being monitored. Herein, a review of the recent sensing applications, which harness ML enabled smart sensor systems, is presented. First well‐known ML algorithms implemented in smart sensor systems for practical sensing applications are discussed. Subsequent sections summarize the practical sensing applications under two major categories: physical and chemical sensing and visual imaging sensing describing how the sensor technologies are coupled with ML “smart” models and how these systems achieve practical benefits. Finally, an outlook on the current trajectory and challenges that will be faced by future smart sensing systems and the opportunities that may be unlocked is provided.

Mode and polarization-division multiplexing technologies (MDM and PDM)can offer considerable parallelism for optical multiplexing biosensors, complex optical neural networks, and high-capacity optical interconnects, while requiring only a single-wavelength laser source. Thanks to the mature fabrication processes of silicon nitride and superior material properties of lithium niobate, the silicon nitride loaded lithium niobate on insulator (LNOI) platform allows the integration of high-speed optical modulators and optical (de)multiplexing devices to achieve high-capacity and low-cost photonic integrated circuits suitable for data communication applications. In this contribution, MDM and PDM are investigated in a silicon nitride loaded LNOI (X-cut) platform. As a proof of concept, an asymmetrical directional coupler-based mode ( de)multiplexer (MMUX) and polarization splitter-rotator (PSR) are designed, fabricated, and experimentally demonstrated. The measured insertion losses are lower than 1.46 and 1.49 dB, while the inter-modal crosstalk is lower than −13.03 and −17.75 dB for the MMUX and PSR, respectively, for a wavelength range of 1525-1565 nm. A 40 Gbps data transmission experiment demonstrates the data transmission capabilities of the fabricated devices. The measured eye diagrams are clear and wide-open, and the bit error rate measurements show reasonable power penalties, indicating good device performance.

Background Supraphysiological hemodynamics are a recognized driver of platelet activation and thrombosis at high-grade stenosis and in blood contacting circulatory support devices. However, whether platelets mechano-sense hemodynamic parameters directly in free flow (in the absence of adhesion receptor engagement), the specific hemodynamic parameters at play, the precise timing of activation, and the signaling mechanism(s) involved remain poorly elucidated. Results Using a generalized Newtonian computational model in combination with microfluidic models of flow acceleration and quasi-homogenous extensional strain, we demonstrate that platelets directly mechano-sense acute changes in free-flow extensional strain independent of shear strain, platelet amplification loops, von Willebrand factor, and canonical adhesion receptor engagement. We define an extensional strain sensing “mechanosome” in platelets involving cooperative Ca2+ signaling driven by the mechanosensitive channel Piezo1 (as the primary strain sensor) and the fast ATP gated channel P2X1 (as the secondary signal amplifier). We demonstrate that type II PI3 kinase C2α activity (acting as a “clutch”) couples extensional strain to the mechanosome. Conclusions Our findings suggest that platelets are adapted to rapidly respond to supraphysiological extensional strain dynamics, rather than the peak magnitude of imposed wall shear stress. In the context of overall platelet activation and thrombosis, we posit that “extensional strain sensing” acts as a priming mechanism in response to threshold levels of extensional strain allowing platelets to form downstream adhesive interactions more rapidly under the limiting effects of supraphysiological hemodynamics.