Search Results (583)

A central challenge in reconfigurable photonics based on quasi bound states in the continuum (quasi-BICs) is to move beyond binary switching toward multistate and polarization-aware programmability. Here we propose a dual-phase-change material (PCM) metasurface that enables four-state nonvolatile switching and polarization-divergent dispersion rewriting within a single unit cell. Two independently switchable PCM layers provide four addressable configurations (0-0, 0-1, 1-0, 1-1) at a fixed geometry, allowing the resonance landscape to be reprogrammed through complex-index rewriting without structural modification. Angle-resolved transmission maps reveal fundamentally different evolution pathways for orthogonal polarizations. For p polarization, the quasi-BIC exhibits strong state sensitivity with dispersion reshaping and multi-branch features near normal incidence; the resonance red-shifts from ~1331 nm to ~1355 nm while the quality factor decreases from ~6.7 × 10⁴ to ~4.0 × 10⁴. In contrast, for s polarization, a single weakly dispersive branch translates coherently across states, producing a much larger shift from ~1635 nm to ~1790 nm while the quality factor increases from ~9.0 × 10³ to ~1.8 × 10⁴. The opposite quality-factor trajectories, together with the polarization-contrasting tuning ranges, demonstrate that dual-PCM programming reconfigures polarization-selective radiative coupling rather than imposing a uniform resonance shift. This compact two-bit metasurface platform provides multistate, high-Q control with active dispersion engineering, enabling polarization-multiplexed reconfigurable filters, state-addressable sensors, and other programmable photonic devices. Full article

This paper presents a compact four-beam dual-polarized phased array with the high performance front-end module based on system-in-package (SiP) technology. By employing high-temperature co-fired ceramic (HTCC) substrates, the proposed design achieves efficient thermal management and high level of integration within a tile-type architecture. The front-end module based on SiP can simultaneously generate four independent beams with switchable left- and right-hand circular polarizations, providing flexible beam control. To verify the proposed method, a Ku-band 256-element phased array receiver with four beams has been designed and experimentally verified using HTCC and SiP process. Operating in 14–14.5 GHz, the proposed low-profile array demonstrates stable radiation characteristics, beam pointing accuracy and excellent beam consistency across the entire frequency range. The measurement results confirm that the SiP-based phased array maintains efficient thermal management, high polarization purity and robust beam-scanning capability, validating its suitability for mobile satellite communication. Full article

A mechanically reconfigurable phased array antenna (MRPA) with switchable radiation and scattering characteristics is presented. By adjusting the height of each array element, a continuous aperture phase response is achieved, enabling mechanical beam steering without electronic phase shifters. In the radiation mode, a height-induced phase gradient is used to steer the beam, while in the scattering mode, the same height–phase mapping mechanism produces multi-element phase cancellation for radar cross-section (RCS) reduction. An 8 × 8 prototype operating at 7.9 GHz is designed and validated. The array achieves beam steering up to ±45° with a peak realized gain of 21.5 dBi and an aperture efficiency of 87.6%. Moreover, more than 10 dB monostatic RCS reduction is obtained over a wide frequency range from 3 to 38 GHz. The proposed design provides a unified mechanical approach for radiation enhancement and scattering suppression in multifunctional phased arrays. Full article

Early diagnosis of breast and skin cancers significantly reduces mortality rates, yet manual segmentation remains challenging due to subjective interpretation, radiologist fatigue, and irregular lesion boundaries. This study presents BAS-SegNet, a novel boundary-aware segmentation framework that addresses these limitations through an enhanced deep learning architecture. The proposed method integrates three key innovations: (1) an enhanced CNN-based architecture with a switchable feature pyramid interface, a tunable ASPP module, and consistent dropout regularization; (2) an edge-aware preprocessing pipeline using Sobel-based edge magnitude maps stacked as additional channels with geometric augmentations; (3) a boundary-aware hybrid loss combining Binary Cross-Entropy, Dice, and Focal losses with auxiliary edge supervision from morphological gradients. Experimental validation on the BUSI breast ultrasound and ISIC skin lesion datasets demonstrates superior performance, achieving Dice scores of 0.814 and 0.935, respectively, with IoU improvements of 16.3–22.4% for breast cancer and 8.8–11.5% for skin cancer compared with existing methods. The framework shows particular effectiveness under challenging ultrasound conditions where lesion boundaries are ambiguous, offering significant potential for automated clinical diagnosis support. Full article

Prostate-specific antigen (PSA) is a key biomarker for the early detection of prostate cancer recurrence following surgical treatment. In this study, we present a PSA-responsive, aptamer-based switchable aggregate system, named AS2-US-AuNP-Aggregate, composed of ultrasmall gold nanoparticles (US-AuNPs) linked by (partially) pairing oligomers that selectively disassemble in the presence of PSA. The system was optimised also using a previously developed in silico routine and is designed for enhanced detection capabilities and for supporting in vivo applicability. We measured the sizes of the nanosystems by dynamic light scattering (DLS) and their extinction spectra, also in the presence of PSA in simple buffers, in the presence of DNaseI, and under blood-mimicking conditions (filtered plasma), obtaining a response down to 10 fM PSA in buffers and to 1 pM in filtered plasma. Our findings highlight the potential of aptamer-based nanoparticle aggregates as a basis for user-friendly diagnostic tools. Additionally, we discuss key optimisation strategies to further advance their development for in vivo diagnostic applications. Full article

In the present study, molecular dynamics simulations with three interatomic potentials (Polymer Consistent Force Field, Adaptive Intermolecular Reactive Empirical Bond Order, and Tersoff) are employed to investigate strain-dependent interfacial thermal resistance across one-dimensional to two-dimensional junctions. Carbon nanotube–graphene junctions exhibit exceptionally low interfacial resistances (1.69–2.37 × 10⁻¹⁰ K·m²/W at 300 K)—two to three orders of magnitude lower than conventional metal–dielectric interfaces. Strain-dependent behavior is highly potential-dependent, with different potentials showing inverse, positive, or minimal strain sensitivity. Local phonon density of states analysis with Tersoff reveals that strain-induced spectral redistribution in graphene toward lower frequencies enhances phonon coupling with carbon nanotube modes. Temperature significantly affects resistance, with 37–59% increases at 10 K compared to 300 K due to long-wavelength phonon scattering. Boron nitride nanotube–hexagonal boron nitride nanosheet junctions exhibit 60% higher resistance (3.2 × 10⁻¹⁰ K·m²/W) with temperature-dependent strain behavior and spacing-insensitive performance. Interfacial resistance is independent of pillar height, confirming junction-dominated transport. The discovery of exceptionally low interfacial resistances and material-specific strain responses enables the engineering of thermally switchable devices and mechanically robust thermal pathways. These findings directly address critical challenges in next-generation flexible electronics where devices must simultaneously manage high heat fluxes while maintaining thermal performance under repeated mechanical deformation. Full article

Photo-induced bond linkage isomerization (BLI) in metal–nitrosyl compounds provides a molecular mechanism for controlling light-induced changes in refractive index and phase modulation. In this study, the ground and metastable states of a series of Ru–NO complexes and their Au₂₀, Ag₂₀, and mixed Au₁₀Ag₁₀ nanocluster hybrids were investigated by DFT and TDDFT calculations. The photochemical rearrangement between the linear, side-on, and O-bound forms of Ru–NO was examined together with their electronic transitions, oscillator strengths, and characteristic vibrational shifts. From these data, parameters describing radiative efficiency, non-radiative coupling, and metastable-state stability were derived to identify compounds with favorable properties for holography and photonic applications. Particular attention was given to the [(Salen)Ru(NO)(HS)@Au₂₀] complex, which shows a strong red-to-NIR response and balanced stability among its linkage isomers. Frequency-dependent polarizabilities α(ω) were calculated for its ground and metastable states and compared with those of the classical holographic material [Fe(CN)₅NO]²⁻ (nitroprusside). The refractive-index changes derived from α(ω) reveal that the Au₂₀–salen hybrid produces a much larger and more strongly wavelength-dependent Δn(λ) than nitroprusside. At 635 nm, the modulation reaches approximately 0.06 for the hybrid, compared with 0.02 for nitroprusside. This enhancement reflects the cooperative effect of the Ru–NO chromophore and the Au₂₀ nanocluster, which amplifies both polarizability and optical dispersion. The results demonstrate that coupling molecular photo-linkage isomerism with nanoplasmonic environments can significantly improve the performance of molecular systems for holography and optical-phase applications. Full article

Two types of devices capable of switchable infrared spectral control are demonstrated by utilizing the phase-change characteristics of In₃SbTe₂ (Indium–Antimony–Tellurium, IST), which transitions from a low-loss dielectric amorphous phase to a high-loss metallic crystalline state. Through comprehensive structural design, theoretical calculation, simulation analysis, experimental measurement, and application demonstration, we realize distinct switching effects and functions of these two devices. In the first design, IST mono-layer thin films integrated with infrared-transparent substrates (KBr and ZnSe) enable switching between amorphous high transmittance and crystalline high reflectance states over the 2.5–15 μm range, suitable for infrared optical switches and stealth applications. In the second design, introducing a Si metasurface disk array atop the IST mono-layer thin film enables switching between broadband infrared transparency and narrowband high emissivity. This configuration allows independent spectral control of the infrared spectra within the non-atmospheric (5–8 μm) and atmospheric (8–14 μm) windows, providing a versatile platform for tunable thermal radiation management and adaptive infrared camouflage. Full article

Despite the groundbreaking impact of currently approved CAR T-cell therapies, substantial unmet clinical needs remain. This highlights the need for CAR T treatments that are easier to tune, combine, and program with logic rules, in oncology and autoimmunity. Modular CAR T cells use a two-part system: the CAR on the T cell binds an adaptor molecule (AM), and that adaptor binds the tumour-associated antigen (TAA). This design separates recognition of the target antigen and activation of the T cells, resulting in a cellular therapy concept with better control, flexibility, and safety compared to established direct-targeting CAR T-cell systems. The key advantage of the system is the adaptor molecule, often an antibody-based reagent, that targets the TAA. Adaptors can be swapped or combined without re-engineering the T cells, enabling straightforward multiplexing and logic-gated control. The CAR itself is designed to recognise the AM via a unique tag on the adaptor. Only when the CAR, AM, and antigen-positive target cell assemble correctly is T-cell effector function activated, leading to cancer cell lysis. This two-component system has several features that need to be considered when designing a modular CAR: First, the architecture of the CAR, i.e., how the binding domain and the backbone are designed, can influence tonic signalling and activation/exhaustion parameters. Second, the affinity of CAR–AM and AM–TAA will mostly define the engagement kinetics of the system. Third, the valency of the AM has an impact on exhaustion and non-specific activation of CAR T cells. And lastly, the architecture of the AM, especially the size, defines the pharmacokinetics and, consequently, the dosing scheme of the AM. The research conducted on direct-targeting CAR T cells have generated in-depth knowledge of the advantages and disadvantages of the technology in its current form, with remarkable clinical success in relapsed/refractory disease and long-term survival in otherwise difficult-to-treat patient populations. On the other hand, CAR T-cell therapy poses the risk of severe adverse events and antigen loss coupled with antigen-negative relapse which remains the main reason for failed therapies. Addressing these issues in the traditional setting of one CAR targeting one antigen will always be difficult due to the heterogeneous nature of most oncologic diseases, but the flexibility to change target antigens and the modulation of CAR T response by dosing the AM in a modular CAR system might be pivotal to mitigate these hurdles of direct CAR T cells. Since the first conception of modular CARs in 2012, there have been more than 30 constructs published, and some of those have been translated into phase I/II clinical trials with early signs of success, but whether these will progress into a late-stage clinical trial and gain regulatory approval remains to be seen. Full article

A special class of complex adaptive systems—biological and social—thrive not by passively accumulating patterns, but by engineering coherence, i.e., the deliberate alignment of prior knowledge, real-time updates, and teleonomic purposes. By contrast, today’s AI stacks—Large Language Models (LLMs) wrapped in agentic toolchains—remain rooted in a Turing-paradigm architecture: statistical world models (opaque weights) bolted onto brittle, imperative workflows. They excel at pattern completion, but they externalize governance, memory, and purpose, thereby accumulating coherence debt—a structural fragility manifested as hallucinations, shallow and siloed memory, ad hoc guardrails, and costly human oversight. The shortcoming of current AI relative to human-like intelligence is therefore less about raw performance or scaling, and more about an architectural limitation: knowledge is treated as an after-the-fact annotation on computation, rather than as an organizing substrate that shapes computation. This paper introduces Mindful Machines, a computational paradigm that operationalizes coherence as an architectural property rather than an emergent afterthought. A Mindful Machine is specified by a Digital Genome (encoding purposes, constraints, and knowledge structures) and orchestrated by an Autopoietic and Meta-Cognitive Operating System (AMOS) that runs a continuous Discover–Reflect–Apply–Share (D-R-A-S) loop. Instead of a static model embedded in a one-shot ML pipeline or deep learning neural network, the architecture separates (1) a structural knowledge layer (Digital Genome and knowledge graphs), (2) an autopoietic control plane (health checks, rollback, and self-repair), and (3) meta-cognitive governance (critique-then-commit gates, audit trails, and policy enforcement). We validate this approach on the classic Credit Default Prediction problem by comparing a traditional, static Logistic Regression pipeline (monolithic training, fixed features, external scripting for deployment) with a distributed Mindful Machine implementation whose components can reconfigure logic, update rules, and migrate workloads at runtime. The Mindful Machine not only matches the predictive task, but also achieves autopoiesis (self-healing services and live schema evolution), explainability (causal, event-driven audit trails), and dynamic adaptation (real-time logic and threshold switching driven by knowledge constraints), thereby reducing the coherence debt that characterizes contemporary ML- and LLM-centric AI architectures. The case study demonstrates “a hybrid, runtime-switchable combination of machine learning and rule-based simulation, orchestrated by AMOS under knowledge and policy constraints”. Full article

In this study, the operation features of a transformerless voltage divider, with transistor–diode commutation of switchable capacitors, designed to operate as a part of low-power autonomous electronic systems with reduced output voltage are studied both theoretically and experimentally. The analysis is carried out for a divider operation with a constantly or periodically connected voltage source V₀ with unlimited power. It is found that the divider’s efficiency during operation with a constantly connected primary voltage source V₀ with unlimited power is very low. However, the efficiency can reach 60% during the divider’s operation using a periodically connected voltage source V₀ with unlimited power. It has been shown that the efficiency can only reach 40% in the case of using a voltage source with limited power connected to the divider periodically. It has been established that for circuits with transistor–diode commutation of the capacitors, the stabilization effect is much stronger than for circuits with diode commutation of the capacitors. Therefore, an excess of the maximum load voltage relative to the expected value V₀/N is significantly lower for transistor–diode commutation in comparison with diode commutation (N is the number of divider stages). Based on the ideas developed regarding the divider operation, analytical expressions are obtained, enabling us to calculate the parameters of the studied divider circuits in a wide range. The good agreement between the analytical estimations and experimental data suggests that these calculations adequately describe the operation of the dividers, and that the derived analytical expressions can be successfully used during the preliminary design stage. In general, the analysis carried out herein and the developed approach make it possible to significantly narrow the range of search for the necessary system parameters when designing voltage dividers. Full article

Selective gene delivery to defined cell populations remains one of the key challenges in lentiviral vector-based gene therapy. The vesicular stomatitis virus glycoprotein (VSV-G) confers high infectivity but lacks cell-type specificity because of the ubiquitous expression of its receptor, LDLR. To enable modular, receptor-specific targeting while retaining the production efficiency of VSV-G-pseudotyped vectors, we designed a bispecific adapter, 929-B6, comprising a VSV-G-binding nanobody and an ERBB2-binding DARPin 9.29. Anti-VSV-G nanobodies were isolated from an alpaca immune library and screened in cell-based pseudoreceptor assays to identify the optimal binder (VSVG-B6). The resulting adapter was evaluated with receptor-ablated (VSV-G_mut) and wild-type VSV-G-pseudotyped LVs across ERBB2-positive and -negative cell lines and in a mouse xenograft model. 929-B6 enabled efficient, receptor-specific transduction of ERBB2-expressing cells without increasing infection of ERBB2-negative controls. Pre-incubation of VSV-G_mut-pseudotyped LVs with 1–2 µg/mL 929-B6 increased transduction up to eight-fold in ERBB2⁺ cells, with similar but smaller effects for VSV-G and VSV-G_mut + 929R pseudotypes. Across breast cancer lines, transduction enhancement correlated with ERBB2 surface density, and co-culture experiments confirmed selective entry into ERBB2⁺ populations. In vivo imaging of ERBB2⁺ tumors revealed a visible tumor-localized luminescent signal following administration of 929-B6-treated vectors. The 929-B6 adapter provides a rapid, scalable means to retarget standard LV stocks toward chosen receptors without re-engineering the envelope or co-packaging pseudoreceptor plasmids. Its modularity suggests a generalizable platform for both gene therapy and oncolytic applications requiring flexible, receptor-defined tropism. Full article

With the widespread application of fiber laser technology in industries, communications, medical fields, and beyond, the demand for controlling the spatial modes of their output beams has been increasingly growing. Traditional mode control methods are constrained by factors such as device power thresholds, system complexity, and cost, making it difficult to meet the requirements for high-power, high-purity, and rapidly switchable multimode regulation. This paper reviews adaptive mode control technology based on photonic lanterns (PLs). By integrating ideas from adaptive optics and photonics, this technology utilizes photonic lanterns to achieve efficient mode evolution from single-mode to multimode fibers. Combined with optimization algorithms, it enables real-time regulation of input phases, thereby producing stable, high-purity target modes or mode superposition fields at the multimode output end. The paper systematically introduces the structural classifications, propagation characteristics, and fabrication processes of photonic lanterns, as well as the mode evolution mechanisms in different types of photonic lanterns. It elaborates in detail on the structural design, algorithm implementation, and experimental validation of the adaptive control system based on photonic lanterns. Furthermore, it explores the application prospects of this technology in areas such as suppressing transverse mode instability, mode-division multiplexing communications, particle manipulation, and high-resolution spectral measurements. The results demonstrate that the all-fiber adaptive mode control system based on photonic lanterns offers advantages such as compact structure, low loss, fast response, and strong scalability. Full article

Active metasurfaces, whose optical properties can be tuned by an external stimulus such as electric or laser pulses, have attracted great research interest recently. The phase change material (PCM), antimony sulfide (Sb₂S₃), has been reported to modulate resonance wavelengths from the visible to the infrared. Here, we present a purely numerical study of an active and nonvolatile narrow-band perfect absorber in the infrared region based on a nanostructured metal–insulator–metal (MIM) metasurface incorporating Sb₂S₃. The proposed absorber exhibits a high quality factor and achieves near-unity absorption at resonance wavelengths. In addition, the absorption spectrum can be dynamically modulated by the phase transition of Sb₂S₃, with a modulation range approaching 1 μm. Moreover, the designed absorber shows insensitivity to the angle of incidence. This study offers a feasible strategy for developing Sb₂S₃-integrated metasurface perfect absorbers with potential applications in selective thermal emitters and bolometers. Full article

A terahertz band-switchable photonic topological insulator (PTI) composed of a C₃-symmetric rod-type photonic crystal is designed. By tuning the size of the central cylinder in the lattice, a topological phase transition can occur in the PTI, and the topological nontrivial bandgap can be switched from the first to the second bandgap. In both cases, before and after switching, topological edge-state transport of terahertz waves along zigzag topological domain walls, as well as terahertz corner-state localization in constructed resonant cavities, are numerically demonstrated. In addition, an existence of the topological phase transition is also confirmed when tuning the central unit in the lattice of another C₃-symmetric hole-type photonic crystal. This work provides a new approach for flexible terahertz waveguiding and lasing applications. Full article