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The convergence of hybrid broadcast and broadband delivery, companion devices, and immersive technologies enables new forms of interactive, personalized, and accessible TV services. This paper introduces the concept of Augmented Hybrid TV services and presents an exploratory user requirements and preliminary acceptance assessment for 5 representative use cases. They were selected through an exploratory stakeholder consultation and 3 co-design workshops with audiovisual professionals and participants from organizations supporting people with visual or hearing impairments. They combine conventional TV with complementary content delivered to connected devices, including AR/VR HMD. They were subsequently evaluated through a cross-sectional CAWI survey of 626 Internet and connected TV users in Spain. Each participant viewed standardized video demonstrations of 2 randomly assigned cases and assessed their perceived usefulness, anticipated benefits/limitations, and interest in them. The results show substantial interest across all five use cases, ranging from 64.7% to 76.9%. Adaptive and personalized augmented subtitles received the highest level of interest and were particularly valued for their accessibility, language-learning, and personalization benefits. Immersive services involving complementary AR content, virtual screens, 3D objects, and 360 video were also evaluated positively, although participants identified device cost, ergonomics, connectivity, usability, and synchronization as anticipated limitations. The findings provide user-centered evidence that can inform the prioritization, design, and subsequent prototype-based evaluation of standards-compliant Augmented Hybrid TV services. Because the study assessed video-based scenarios rather than functional systems, the results represent perceived usefulness and stated interest rather than observed adoption or technically validated QoE.

Quantum algorithms for machine learning, chemistry, and cryptanalysis often assume coherent access to classical data at negligible physical cost. We instead treat data loading as a hardware process and quantify the dynamic energetic cost of a quantum random access memory (QRAM) query on a superconducting processor. Using the metric-noise-resource framework, we relate query fidelity and power to gate duration, relative two-qubit drive strength, and the distribution of attenuation across a multi-stage refrigerator, while accounting for thermal photons and gate errors. We analyze the linear-depth multiplexer and the noise-resilient bucket-brigade architectures, adapting the latter to a native superconducting gate set and refining its fidelity analysis using the fully decomposed gate schedule. For a representative bucket-brigade QRAM query with a $12$-qubit address register we obtain a query fidelity of $0.969$. The query consumes $3.51\times10^{-4}\,\mathrm{J}$ of dynamic energy, corresponding to an average dynamic power of $4.38\,\mathrm{W}$ and a peak of $64.4\,\mathrm{W}$. Our optimization shows that, at fixed target fidelity, the operating point and attenuation profile can change the average power by a factor of two or more.

Diffusible signals enable communication between immune cells but can also create interference between nearby activation sites. In lymph nodes, effector T cells (Teff) concentrate around antigen-presenting cells (APCs), release interleukin-2 (IL-2) following antigen recognition, and sense IL-2 through cell-surface receptors. Experiments show high-uptake regulatory T cells (Treg) clustered around IL-2-producing cells. However, it is unclear how strongly responses at neighboring activation sites are coupled through diffusible IL-2, and how this coupling is influenced by the spatial organization of Treg acting as IL-2 sinks. We interpret two neighboring sites as a molecular communication system and study the effect of clustering using a three-dimensional IL-2 field coupled to T cell population dynamics. Across a broad parameter sweep, clustering Treg produces a larger mean reduction in neighboring-site interference than adding dispersed Treg. Compared with no Treg, clustered Treg suppress interference while largely preserving the strong local response with corresponding consequences for population expansion and survival. Information-theoretic analysis shows improved discrimination between weak and strong local sources at short separation, whereas at larger separation clustering primarily reduces the remaining estimated neighboring-source information. These findings support a spatial-filtering role for Treg clustering in maintaining locally informative immune responses.

Due to susceptibility to radiation-induced soft errors and resource constraints implementing large and complex designs on field programmable gate arrays (FPGAs) in harsh environments is challenging. Therefore, to mitigate these issues, this paper proposes an innovative approach through the introduction of a single event upset (SEU)-hardened spintronic FPGA architecture that incorporates multi-context capabilities. Leveraging the non-volatile properties of magnetic tunnel junction (MTJ), the proposed design can store two/four distinct configurations internally, eliminating the dependence on external non-volatile memory which significantly boosts the system performance. Additionally, through post-layout simulation, we demonstrate our design immunity to SEU, which enhances its reliability and operational stability in environments susceptible to radiation-induced soft errors. The efficiency of the proposed design was also evaluated using the ROSSETA benchmark, which serves as a representative model for real-world FPGA applications.

In-sensor processing (ISP) is used in various fields, including autonomous driving automotive systems, wearable healthcare devices, environmental monitoring, wireless sensor networks, smart cities, and industrial control systems. One of the main features of most of these applications is energy and hardware restriction. This restriction amplifies the importance of using high-performance and low-energy consumption computing systems and methods. This paper proposes efficient spintronic stochastic computing modules for in-sensor computing systems to address this challenge. The proposed design utilized the stochastic behavior of the magnetic tunnel junction in the subcritical switching regime to generate a probability-adjustable random stream. Probability-adjustable random stream generation is the most important step in any stochastic system because it determines the quality of the final output. The simulation results indicate that the proposed design offers almost the same peak signal-to-noise ratio and structural similarity while occupying at least 62\% lower area and consuming 60\% lower energy. These advantages made the proposed design a good choice for ISP applications with limited energy.