Search Results (343)

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 introduces a cybersecurity framework that combines a deception-based ransomware detection system, called the Intrusion and Ransomware Detection System for Cloud (IRDS4C), with a blockchain-enabled Cyber Threat Intelligence platform (CTIB). The framework aims to improve the detection, reporting, and sharing of ransomware threats in cloud environments. IRDS4C uses deception techniques such as honeypots, honeytokens, pretender network paths, and decoy applications to identify ransomware behavior within cloud systems. Tests on 53 Windows-based ransomware samples from seven families showed an ordinary detection time of about 12 s, often quicker than tralatitious methods like file hashing or entropy analysis. These detection results are currently limited to Windows-based ransomware environments, and do not yet cover Linux, containerized, or hypervisor-level ransomware. Detected threats are formatted using STIX/TAXII standards and firmly shared through CTIB. CTIB applies a hybrid blockchain consensus of Proof of Stake (PoS) and Proof of Work (PoW) to ensure data integrity and protection from tampering. Security analysis shows that an attacker would need to control over 71% of the network to compromise the system. CTIB also improves trust, accuracy, and participation in intelligence sharing, while smart contracts control access to erogenous data. In a local prototype deployment (Hardhat devnet + FastAPI/Uvicorn), CTIB achieved 74.93–125.92 CTI submissions/min, The number of attempts or requests in each test was 100 with median end-to-end latency 455.55–724.99 ms (p95: 577.68–1364.17 ms) across PoW difficulty profiles (difficulty_bits = 8–16). Full article

The connectivity demands of high-performance computing (HPC), artificial intelligence (AI) and data centers are driving the development of a new generation of multimode optical components. This paper discusses the vertical cavity surface emitting laser (VCSEL) bandwidth and noise performance needed to support 106 Gbd line rates with PAM4 modulation for 200 Gbps per lane multimode optical links. A −3 dB bandwidth greater than 35 GHz and a RIN of less than −152 dB/Hz are demonstrated. No uncorrectable errors were observed over 50 m of OM4 fiber, demonstrating good link stability. VCSEL device performance and the associated wear-out life are presented. Leveraging good device reliability and low power consumption of VCSEL-based links, a novel VCSEL near-packaged optics (NPO) concept is proposed for optical interconnects in AI scale-up network applications. Optical interconnects allow for longer reaches, compared to copper interconnects, which facilitate larger AI clusters with network disaggregation. The proposed VCSEL NPO can achieve an energy efficiency of ~1 pJ/bit, which is the highest among optical interconnects. Full article

A novel wideband 1-bit reconfigurable transmitarray (RTA) is proposed, which is based on a substrate-integrated cavity-backed patch (SCIBP) element. The RTA element consists of a pair of SCIBP antennas, achieving wideband operational capability through the optimization of dielectric substrate thickness. To suppress surface-wave propagation between adjacent RTA elements, a substrate-integrated waveguide (SIW) is designed to function as a metallic isolation wall. A 180° phase shift is realized by dynamically manipulating p-i-n diodes embedded within the SCIBP antenna structure. When the dielectric substrate thickness is increased from 6 mm to 10 mm, the 3 dB transmission bandwidth is expanded from 10% to 33.6%. The simulation results confirm that the proposed element realizes a 3 dB transmission bandwidth of 33.6%. A prototype RTA with 100 elements is designed, fabricated, and measured. The prototype achieves a peak gain of 16.6 dBi at 4.6 GHz, accompanied by an aperture efficiency of 17.2% and a 3 dB gain bandwidth of 18.9%. Furthermore, measured scanned beams illustrate that the proposed RTA possesses good beamscanning performance. Owing to its many advantages, such as wideband operation, lightweight design, low cost, simple structure, and easy fabrication, it is particularly suitable for application in intelligent communication systems and radar systems. Full article

Background: It is well-known that rotating shift work disrupts the circadian rhythm and sleep quality in nurses. With this study, we aimed to compare subjectively and objectively measured sleep quality in nurses, specifically focusing on any differences that arose in relation to shift work. Methods: This prospective, observational, cross-sectional study was conducted in 2025 in Croatia; a total of 140 nurses participated. Sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI) and FitBit Charge 3 smartwatch, which monitored sleep over an eight-day period. Results: Most nurses rated their sleep as good or very good, but according to the PSQI questionnaire, all participants were classified as poor sleepers (PSQI > 5). Objective smartwatch measurements showed that nurses working only day shifts had higher sleep scores (median 77, IQR 75–80 vs. 73, IQR 68–76; p < 0.001), significantly longer total sleep duration (median 6.4, IQR 6.3–7.1 vs. 5.5, IQR 5.2–6.2 h; p < 0.001), and longer durations of all sleep stages compared with those working rotating shifts. Conclusions: Most nurses subjectively rated their sleep as good or very good; however, according to the PSQI questionnaire results, all were classified as poor sleepers, with no significant difference related to shift work. Objective measurements using the smartwatch indicated that rotating shift work is associated with significantly poorer sleep quality. Full article

Background/Objectives: Colombia harbors exceptional plant diversity, comprising over 31,000 formally identified species, of which approximately 6000 are classified as useful plants. Among these, 2567 species possess documented food and medicinal applications, with several traditionally utilized for managing febrile illnesses. Despite the global burden of dengue virus infection affecting millions annually, no specific antiviral therapy has been established. This study aimed to identify potential anti-dengue compounds from Colombian medicinal flora through machine learning-based quantitative structure–activity relationship (QSAR) modeling. Methods: An optimized XGBoost algorithm was developed through Bayesian hyperparameter optimization (Optuna, 50 trials) and trained on 2034 ChEMBL-derived activity records with experimentally validated anti-dengue activity (IC₅₀/EC₅₀). The model incorporated 887 molecular features comprising 43 physicochemical descriptors and 844 ECFP4 fingerprint bits selected via variance-based filtering. IC₅₀ and EC₅₀ endpoints were modeled independently based on their pharmacological distinction and negligible correlation (r = −0.04, p = 0.77). Through a systematic literature review, 2567 Colombian plant species from the Humboldt Institute’s official checklist were evaluated (2501 after removing duplicates and infraspecific taxa), identifying 358 with documented antiviral properties. Phytochemical analysis of 184 characterized species yielded 3267 unique compounds for virtual screening. A dual-endpoint classification strategy categorized compounds into nine activity classes based on combined potency thresholds (Low: pActivity ≤ 5.0, Medium: 5.0 < pActivity ≤ 6.0, High: pActivity > 6.0). Results: The optimized model achieved robust performance (Matthews correlation coefficient: 0.583; ROC-AUC: 0.896), validated through hold-out testing (MCC: 0.576) and Y-randomization (p < 0.01). Virtual screening identified 276 compounds (8.4%) with high predicted potency for both endpoints (“High-High”). Structural novelty analysis revealed that all 276 compounds exhibited Tanimoto similarity < 0.5 to the training set (median: 0.214), representing 145 unique Murcko scaffolds of which 144 (99.3%) were absent from the training data. Application of drug-likeness filtering (QED ≥ 0.5) and applicability domain assessment identified 15 priority candidates. In silico ADMET profiling revealed favorable pharmaceutical properties, with Incartine (pIC₅₀: 6.84, pEC₅₀: 6.13, QED: 0.83), Bilobalide (pIC₅₀: 6.78, pEC₅₀: 6.07, QED: 0.56), and Indican (pIC₅₀: 6.73, pEC₅₀: 6.11, QED: 0.51) exhibiting the highest predicted potencies. Conclusions: This systematic computational screening of Colombian medicinal flora demonstrates the untapped potential of regional biodiversity for anti-dengue drug discovery. The identified candidates, representing structurally novel chemotypes, are prioritized for experimental validation. Full article

To address the limitations of optical interferometry (strict environmental requirements, high cost) and piezoelectric methods (hysteresis, creep) in micro-displacement measurement, this study proposes a collaborative measurement approach based on the parallel plate capacitance principle—with its core innovation lying in integrated optimization rather than original principles. Unlike existing studies that separately optimize mechanics, hardware, or algorithms, this work achieves the first synergy of three components: a mechanical coupling mechanism (integrating a high-resolution optical mount and a micrometer) for parallel plate regulation, a 21-bit capacitance detection module based on the STM32-PCAP01 (with a resolution of 0.0001 pF), and a linear response model relating capacitance to the reciprocal of displacement. Experimental validation confirms its engineering feasibility for sub-nanometer-level precision: with a 10 cm plate radius and 3–20 mm initial spacing, the system achieves 277.215 ± 0.244 pF·mm sensitivity and <0.05 μm displacement resolution. The relative error of micro-displacement measurement in the 10 μm range is less than 1.56%. Based on the hardware resolution, the system possesses the theoretical capability to detect displacements as low as 10⁻⁸ to 10⁻⁹ m. Compared to laser interferometry, it operates stably in common industrial environments without vibration isolation or darkrooms, reducing costs by ~90% while maintaining comparable accuracy. This cost-effective solution enables online precision measurement in semiconductor manufacturing and MEMS testing, with its multi-physics collaborative design offering a new paradigm for intelligent sensor development. Full article

Background: Laryngeal and hypopharyngeal cancers (LHCs) exhibit heterogeneous outcomes after definitive radiotherapy (RT). Large language models (LLMs) may enhance prognostic stratification by integrating complex clinical and imaging data. This study validated two pre-trained LLMs—GPT-4o-2024-08-06 and Gemma-2-27b-it—for outcome prediction in LHC. Methods: Ninety-two patients with non-metastatic LHC treated with definitive (chemo)radiotherapy at Linkou Chang Gung Memorial Hospital (2006–2013) were retrospectively analyzed. First-order and 3D radiomic features were extracted from intra- and peritumoral regions on pre- and mid-RT CT scans. LLMs were prompted with clinical variables, radiotherapy notes, and radiomic features to classify patients as high- or low-risk for death, recurrence, and distant metastasis. Model performance was assessed using sensitivity, specificity, AUC, Kaplan–Meier survival analysis, and McNemar tests. Results: Integration of radiomic features significantly improved prognostic discrimination over clinical/RT plan data alone for both LLMs. For death prediction, pre-RT radiomics were the most predictive: GPT-4o achieved a peak AUC of 0.730 using intratumoral features, while Gemma-2-27b reached 0.736 using peritumoral features. For recurrence prediction, mid-RT peritumoral features yielded optimal performance (AUC = 0.703 for GPT-4o; AUC = 0.709 for Gemma-2-27b). Kaplan–Meier analyses confirmed statistically significant separation of risk groups: pre-RT intra- and peritumoral features for overall survival (for both GPT-4o and Gemma-2-27b, p < 0.05), and mid-RT peritumoral features for recurrence-free survival (p = 0.028 for GPT-4o; p = 0.017 for Gemma-2-27b). McNemar tests revealed no significant performance difference between the two LLMs when augmented with radiomics (all p > 0.05), indicating that the open-source model achieved comparable accuracy to its proprietary counterpart. Both models generated clinically coherent, patient-specific rationales explaining risk assignments, enhancing interpretability and clinical trust. Conclusions: This external validation demonstrates that pre-trained LLMs can serve as accurate, interpretable, and multimodal prognostic engines for LHC. Pre-RT radiomic features are critical for predicting mortality and metastasis, while mid-RT peritumoral features uniquely inform recurrence risk. The comparable performance of the open-source Gemma-2-27b-it model suggests a scalable, cost-effective, and privacy-preserving pathway for the integration of LLM-based tools into precision radiation oncology workflows to enhance risk stratification and therapeutic personalization. Full article

Emerging services such as artificial intelligence (AI), 5G, the Internet of Things (IoT), cloud data services and teleworking are growing exponentially, pushing bandwidth needs to the limit. Space Division Multiplexing (SDM) in the spatial domain, along with Ultra-Wide Band (UWB) transmission in the spectrum domain, represent two degrees of freedom that will play a crucial role in the evolution of backbone optical networks. SDM and UWB technologies necessitate the replacement of conventional Wavelength-Selective-Switch (WSS)-based architectures with innovative optical switching elements capable of handling both higher port counts and flexible switching across various granularities. In this work, we introduce a novel Photonic Integrated Circuit (PIC)-based switching element called flex-Waveband Selective Switch (WBSS), designed to provide flexible band switching across the UWB spectrum (~21 THz). The proposed flex-WBSS supports a hierarchical three-layered Multi-Granular Optical Node (MG-ON) architecture incorporating optical switching across various granularities ranging from entire fibers and flexibly defined bands down to individual wavelengths. To evaluate its performance, we develop a custom network simulator, enabling a thorough performance analysis on the critical performance metrics of the node. Simulations are conducted over an existing network topology evaluating three traffic-oriented switching policies: Full Fiber Switching (FFS), Waveband Switching (WBS) and Wavelength Switching (WS). Simulation results reveal high Optical-to-Signal Ratio (OSNR) and low Bit Error Rate (BER) values, particularly under the FFS policy. In contrast, the integration of the WBS policy bridges the gap between existing WSS- and future FFS-based architectures and manages to mitigate capacity bottlenecks, enabling rapid scalable network upgrades in existing infrastructures. Additionally, we propose a probabilistic framework to evaluate the node’s bandwidth utilization and scaling behavior, exploring trade-offs among scalability, component numbers and complexity. The proposed framework can be easily adapted for the design of future transport optical networks. Finally, we perform a SWaP-C (Size, Weight, Power and Cost) analysis. Results show that our novel MG-ON achieves strong performance, reaching a throughput exceeding 10 Pb/s with high OSNR values ≈14–20 dB and BER ≈10⁻⁹ especially under the FFS policy. Moreover, it delivers up to 7.5× cost reduction compared to alternative architectures, significantly reducing deployment/upgrade costs while maintaining low power consumption. Full article

Time-mode digital pixel sensors have several advantages in Internet-of-Things applications, which require a compact circuit and low-power operation under poorly illuminated environments. Although the time-mode digitization technique can theoretically achieve a wide dynamic range by overcoming the supply voltage limitation, its practical dynamic range is limited by the maximum clock frequency and device leakage. This study proposes an extended time-mode digitization technique and a low-leakage pixel circuit to accommodate a wide range of light intensities with a small number of digital bits. The prototype sensor was fabricated in a 0.18 μm standard CMOS process, and the measurement results demonstrate its capability to accommodate a 0.03 lx minimum light intensity, providing a dynamic range figure-of-merit of 1.6 and a power figure-of-merit of 37 pJ/frame·pixel. Full article

This study presents a high-speed, 9-bit integrating-mode phase interpolator (IMPI) in a 12 nm FinFET process. The proposed slew-rate-tolerant design accepts bandwidth-limited inputs, relaxing the stringent need for high-slew-rate clocks found in prior research. This is primarily achieved through an optimized switch design that converts the sinusoidal voltage input into a quasi-square-wave current. A detailed theoretical model identifies asymmetrical clock feedthrough as the dominant nonlinearity, which is suppressed by a cancellation circuit. Furthermore, an adaptive biasing loop is employed to compensate for Process, Voltage, and Temperature (PVT)-induced P/N mismatch. This work is validated through comprehensive post-layout simulations; operating from a 0.8 V supply at 16 GHz, the PI achieves a peak-to-peak Integral Nonlinearity (INL) of 4.3 LSB (530 fs) while consuming 6.56 mW. Full article

Arrhythmogenic cardiomyopathy (ACM) is a cardiac disorder manifesting through electrical and contractile dysfunction of the ventricles, characterized by fibro-fatty substitution of the myocardium. Cardiac mesenchymal stromal cells (CMSCs) are key contributors to this remodeling. In clinical management, several pharmacological approaches address ACM arrhythmias and heart failure, but, to date, none specifically target fibro-adipose replacement. Despite genetic origin, several studies have reported that non-genetic aspects influence ACM phenotype, including epigenetic factors. Little is known about their mechanisms in ACM and their potential therapeutic applications. In this work, we aimed to test whether, by perturbing the epigenetic landscape of ACM CMSCs, we could influence their propensity to fibro-fatty differentiation. We conducted a hypothesis-free screening of 157 epigenetic drugs on CMSCs, isolated from ACM patients. Through fluorescence assays, we evaluated lipid droplet accumulation, collagen deposition, and cell viability. Of the 157 drugs screened, five (splitomicin, suberohydroxamic acid, CPTH6, BVT-948, and PBIT) attenuated adipogenic differentiation of ACM CMSCs, with BVT-948 and CPTH6 also reducing collagen production. Overall, this study identified specific epigenetic drugs that were effective in reducing the fibro-fatty phenotype of ACM stromal cells, thus offering potential for adjunctive therapies in the clinical management of ACM patients. Full article

For the application of a high-performance shortwave infrared (SWIR) detector, a fully integrated analog front-end (AFE) circuit is proposed in this paper, which includes a readout integrated circuit (ROIC) and a 12-bit/100 kHz two-step single-slope analog-to-digital converter (TS-SS ADC). The ROIC adopts a direct injection (DI) structure with a pixel size of only 10 µm × 10 µm. The column processing circuit uses a passive correlated double-sampling (CDS) circuit to reduce noise and improve dynamic range. The comparator of four inputs in the ADC solves the problem of linearity reduction caused by charge redistribution during coarse quantization. In addition, the current steering digital-to-analog converter (DAC) is used to compensate for the non-ideal characteristics of the switch, which effectively optimizes the differential nonlinearity (DNL) and integral nonlinearity (INL). The AFE is implemented using SMIC 180 nm 1P6M technology. The post-simulation results show that at a power supply voltage of 3.3 V, the AFE has a frame rate of 100 Hz and a full well capacity (FWC) of 2.8 Me⁻. The linearity can reach 99.59%, and the equivalent output noise is 243 µV. The dynamic range is 73.8 dB. Meanwhile, the signal-to-noise distortion ratio (SNDR) and effective number of bits (ENOB) are 68.38 dB and 11.06 bits, respectively. Full article

In a botnet attack, significant damage can occur when an attacker gains control over a large number of compromised network devices. Botnets have evolved from traditional centralized architectures to decentralized Peer-to-Peer (P2P) and hybrid forms. Recently, a steganography-based botnet (Stego-botnet) has emerged, which conceals command and control (C&C) messages within cover media such as images or video files shared over social networking sites (SNS). This type of Stego-botnet can evade conventional detection systems, as identifying hidden messages embedded in media transmitted via SNS platforms is inherently challenging. However, the inherent file size limitations of SNS platforms restrict the achievable payload capacity of such Stego-botnets. Moreover, the centralized characteristics of conventional botnet architectures expose attackers to a higher risk of identification. To overcome these challenges, researchers have explored network steganography techniques leveraging P2P networks such as BitTorrent, Google Suggest, and Skype. Among these, a hidden communication method utilizing Bitfield messages in BitTorrent has been proposed, demonstrating improved concealment compared to prior studies. Nevertheless, existing approaches still fail to achieve sufficient payload capacity relative to traditional digital steganography techniques. In this study, we extend P2P-based network steganography methods—particularly within the BitTorrent protocol—to address these limitations. We propose a novel botnet C&C communication model that employs network steganography over BitTorrent and validate its feasibility through experimental implementation. Furthermore, our results show that the proposed Stego-botnet achieves a higher payload capacity and outperforms existing Stego-botnet models in terms of both efficiency and concealment performance. Full article

The implementation of K–12 engineering education presents significant challenges for current teachers. To strengthen the instructional readiness of elementary school teachers in Taiwan for engineering education, this study developed a STEM-oriented engineering design activity. It draws on international K–12 engineering education models and incorporates the computational thinking competencies prioritized by Taiwan’s national technology curriculum. The activity involves employing the micro:bit microcontroller to design an educational buzz wire game machine themed on energy education, integrating the engineering design process with knowledge from science, mathematics, and technology. The activity was implemented in an elementary teacher education course through a one-group pretest–posttest quasi-experimental design. The results indicate that participants completed engaging buzz wire game machines that incorporated energy concepts. Significant improvements were observed in participants’ engineering concepts, engineering design self-efficacy, computational thinking, and programming self-efficacy, with a considerable effect size noted in programming self-efficacy (N = 27, Cohen’s d = 1.84, p < 0.05). Most participants expressed highly positive attitudes toward the activity. The findings suggest that the engineering design activity developed in this study shows promising evidence of enhancing professional growth across multiple dimensions of engineering education for pre-service elementary teachers. The study serves as a valuable reference for future curriculum design in teacher education programs. Full article