Search Results (447)

Reasoning-intensive multimodal retrieval suffers from a counter-intuitive bottleneck: on MM-BRIGHT multimodal-to-text (Query+Image → Documents), the strongest dense multimodal encoder reaches only 27.6 nDCG@10 and the rest of the dense vision–language retrievers cluster between 10.0 and 23.0. The visual signal, encoded as a dense vector, adds noise rather than evidence; even augmenting strong text retrievers with raw image captions degrades performance by up to 12.0 points. We propose VISA, a Visual Symbolic Agent that re-casts multimodal-to-text as text retrieval over three parallel streams. A Vision LLM is dispatched in three roles via separate prompts: a zero-shot router that classifies the query image into up to three parser types from a fixed taxonomy of nine (chart, circuit, equation, screenshot, code, figure, diagram, map, photograph); typed parsers that extract structured text per type; and a holistic captioner. The agent constructs three text streams (raw query, query ⊕ symbolic, query ⊕ caption), scores each with a single frozen 4B-parameter retrieval LLM, and fuses the per-document scores via Reciprocal Rank Fusion or a confidence-weighted linear combination. The whole agent contains no trainable parameters. The key novelty is a change of substrate: rather than projecting the query image into a dense multimodal vector that competes with text, VISA is, to our knowledge, the first retrieval system to convert the image into typed symbolic text and keep retrieval entirely text-side, so that a frozen text retriever can match the literal tokens (axis values, variable names, function signatures) that answering documents actually contain. Across all 29 MM-BRIGHT multimodal-to-text domains, VISA achieves 32.4 nDCG@10, an absolute improvement of +4.8 over the strongest dense multimodal encoder and substantially larger margins over the remaining six dense vision–language baselines. Per-domain analysis shows VISA maintains its margin across STEM and software domains where image content is structure-heavy. In practical terms, VISA is training-free and model-agnostic: it requires no fine-tuning, reuses any off-the-shelf vision LLM and text retriever, caches all per-image parsing so re-runs cost only three query encodes, and can therefore be dropped into an existing text-retrieval stack to add reasoning-intensive multimodal capability without building or training a multimodal encoder. Full article

Ionosphere status plays an important role in satellite communication and navigation systems. In this study, we developed an ANN model to predict the ionosphere status regarding the signal-to-noise ratio at non-line-of-sight, near-vertical incidence (NLOS-NVIS) at frequencies within the HF band. The channel sounding was performed by using two software-defined radios placed at a distance of 29 km apart. The databases regarding signal-to-noise ratio (SNR) data were collected for three ham radio bands: 30 m (10.140203 MHz), 40 m (7.040101 MHz) and 80 m (3.570101 MHz). Subsequently, each database was split into a 70% training set and a 30% testing set. In this configuration, the input vectors were represented by the exact time of day (hour and minute) at which the SNR value was predicted, which functioned as an output variable. Also, three error figures were used as indicators for predicting capability and comparing our ANN with other models. Full article

The well-known effect of stabilization by noise for Ito’s scalar linear stochastic differential equation was proven by R.Z. Khasminskii more than 50 years ago. Here, a similar statement is obtained for a system of linear stochastic differential equations. The obtained result is illustrated on the system of two linear stochastic differential equations via several special examples with numerical simulations and figures. Full article

Aggressive technology scaling has led to a significant increase in manufacturing process variations and transistor aging effects, which critically degrade the performance of radio frequency (RF) circuits. These reliability challenges are particularly pronounced in voltage-controlled oscillators (VCOs), where phase noise and operating frequency stability are compromised. While design strategies incorporating micro-electromechanical systems (MEMS) actuators enhance VCO performance by leveraging MEMS varactors or inductors with substantially higher quality factors (Q), this benefit is progressively undermined over time by process variations and aging-induced shifts in the threshold voltage and carrier mobility of the VCO’s transistors. This work presents an ultra-low-power current-reuse voltage-controlled oscillator (VCO) designed to maintain stable performance under process variability and reliability-induced parameter shifts. Robust operation is achieved using a self-detecting–correcting (SDC) bias scheme that senses performance drift and applies corrective feedback through body-bias control in the VCO core. Analytical relations are derived to describe the impact of threshold voltage and mobility variations, and the approach is validated via post-layout simulations in a 130 nm complementary metal-oxide semiconductor (CMOS). Under 18% variations in threshold voltage and carrier mobility, the proposed SDC scheme preserves oscillation frequency, phase noise, and figure of merit (FoM) while also mitigating the intrinsic output amplitude imbalance of conventional current-reuse VCOs. Monte Carlo analysis (500 runs) demonstrates low sensitivity to fabrication uncertainty, with a standard deviation below 0.14 dBc/Hz for phase noise, 210 kHz for oscillation frequency, and 0.4 dBc/Hz for FoM. The VCO operates from a 0.9 V supply, consumes 175 μW, and achieves −124 dBc/Hz phase noise at 1 MHz offset near 2.4 GHz (FoM ≈ −199 dBc/Hz). Full article

This study proposes a novel anti-resonant fiber sensing structure based on a composite “egg-shaped” configuration with surface plasmon resonance (SPR) effect. By designing a novel anti-resonant structure consisting of a semicircle and a semi-ellipse and coating its inner surface with a gold film, the optimal structural parameters are determined through three sets of simulation experiments using temperature sensitivity as the criterion. The optimal sensing structure was applied to the simulated detection and analysis of cancer cells, aiming to provide value and reference for the application of high-sensitivity optical fiber sensor in the field of cancer cell detection. Simulation results show that the proposed sensing structure achieves a maximum temperature sensitivity (TS) of 3.86 nm/°C. For the detection of six different types of cancer cells, the maximum wavelength sensitivity (WS), optimal resolution (R), maximum figure of merit (FOM), maximum signal-to-noise ratio (SNR), and best limit of detection (LOD) reach 12,142.86 nm/RIU, 8.24 × 10⁻⁶, 3035.72 RIU⁻¹, 65.50, and 0.94 nm, respectively. Owing to its unique detection mechanism, the proposed sensing structure exhibits label-free characteristics and demonstrates balanced and excellent performance across all metrics for both temperature and cancer cell detection, showing broad application prospects and great potential in the fields of environmental monitoring and medical prevention and treatment. Full article

This paper reports the development of a Class-A amplifier that operates at 50 MHz and 400 °C. The amplifier utilizes a commercially available 4H-SiC static induction transistor (SIT) as the active device and incorporates input/output-matching networks to optimize amplifier operation and DC bias networks, which comprise thin-film spiral inductors, metal–insulator–metal (MIM) capacitors, and thick-film chip resistors. All passive components were tested at frequency and temperature prior to amplifier development and are reported. A small-signal SiC SIT model that was developed in Keysight’s Advanced Design System (ADS 2023) software suite was used to design and optimize the amplifier’s performance. The SiC SIT amplifier’s S-parameters were recorded for frequencies between 20 and 100 MHz over a temperature range of 25 °C to 400 °C, exhibiting a gain (S₂₁) of approximately 15.8 and 5.80 dB at 25 °C and 400 °C, respectively. The input and output reflection coefficients at 50 MHz and 400 °C were −18.5 and −15.2 dB, respectively. The noise figure and phase noise were measured at temperatures between 25 °C and 400 °C. At 50 MHz, the noise figure increased by only 21% over the temperature range, while the 1 kHz offset of the phase noise remained below −110 dBc/Hz. The stability factor, K, calculated using both measured and simulated data, demonstrates unconditional stability over the frequency range at 400 °C. Lastly, the 1 dB compression point was measured at 50 MHz and 400 °C with an approximated output of 9.5 dB. Simulated and measured results are presented and show the model is within 10% error at 400 °C. Full article

This paper proposes a calibration-free Type-II fractional-N PLL that achieves high linearity by employing a time-averaged current DAC. By adopting a time-averaged current DAC, the proposed architecture inherently enables calibration-free operation and achieves superior linearity, successfully overcoming the fundamental limitations of conventional DTC- and PI-based approaches. The proposed time-averaged current DAC consists of two $G_m$ cells and a variable pulse-width generator. Interpolation is achieved by controlling the injection time of the $G_m$ cells’ output currents, effectively performing time-averaging between two current levels. By performing interpolation in the time domain instead of using conventional analog DAC implementations, the proposed approach simplifies the design and achieves improved linearity. The combination of the 3-bit time-averaged current DAC and the quad-phase divider reduces the quantization noise by 24 dB. The proposed PLL is designed in a 65 nm process. Simulation results show that it consumes 3.41 mW of power with a 25 MHz reference frequency and achieves an RMS jitter of 231.8 fs, integrated from 1 kHz to 100 MHz, and a figure-of-merit ($Fo{M}_N$) of −267.1 dB. Full article

This paper presents the design and fabrication of a wideband low-noise amplifier (LNA) covering C-band, using the 0.15 µm GaAs pHEMT process. To achieve both low noise performance and wide matching characteristics, a two-stage cascaded architecture is implemented. In the first stage, circular inductors and an inductive source degeneration technique are employed to minimize the noise figure (NF) while ensuring wideband input matching. Furthermore, an RC feedback structure is incorporated to effectively enhance the stability of the amplifier. The proposed LNA operates under a supply voltage of 3.3 V and a gate bias of 0.35 V, with a total DC power consumption of 69.3 mW. The fabricated MMIC occupies a total chip area of 1.98 mm², including the probing pads. Measurement results demonstrate that the LNA achieves an NF of 0.81–1.09 dB and a gain of over 20.1 dB in the frequency range of 3.3–8.0 GHz. The input and output return losses are maintained over 10 dB and 9.7 dB, respectively. Full article

This paper presents a current-reused vertically stacked (CRVS) topology for a high-dynamic-range amplifier (HDRA) implemented in a 0.1 μm GaAs pHEMT process, targeting wideband millimeter-wave (mm-wave) receiver front-ends. The proposed design breaks the inherent trade-off between noise figure (NF), linearity, and bandwidth, achieving simultaneous enhancement of transconductance efficiency, Miller effect suppression, and wideband matching. The fabricated prototype operates over a continuous 20–43 GHz bandwidth (covering K- and Ka-bands), demonstrating state-of-the-art performance: a flat gain of 24 ± 0.6 dB, a minimum NF of 2.2 dB, a maximum output 1 dB compression point (OP1dB) of 15.8 dBm and a low power consumption of 5 V/65 mA, with both input and output return losses better than −10 dB across the entire band. The results validate the effectiveness of the CRVS topology and highlight the competitiveness of GaAs pHEMT technology for high-performance wideband mm-wave front-ends, making the design suitable for applications including 5G/6G communication, satellite systems, and mm-wave test equipment. Full article

This study presents a measurement-driven comparison of LoRa communication performance in two tropical deployment scenarios at 923.2 MHz: an open line-of-sight (LOS) path and a forest-obstructed path. To ensure a controlled comparison, both scenarios were evaluated over the same transmission distance of 1.2 km using identical radio configuration, antenna heights, and hardware settings. Field measurements were conducted from 50 m to 1.2 km in 50 m increments, with three repeated measurements at each distance point. The measured RSSI decreased from −60.52 dBm to −89.48 dBm in the LOS case and from −77.62 dBm to −114.62 dBm in the forested case. Using a bandwidth of 125 kHz and a receiver noise figure of 6 dB, the corresponding estimated SNR at 1.2 km was 27.55 dB for the LOS path and 2.41 dB for the forested path. Relative to the free-space baseline, the measured LOS link showed a deviation of 31.14 dB at 1.2 km, while the forested link showed a deviation of 56.28 dB. The additional attenuation specifically associated with the forested environment was approximately 25.14 dB, with a mean excess loss of 24.70 dB over the full route. Regression analysis further yielded effective path-loss exponents of 2.31 for the LOS case and 3.22 for the forested case. Based on these results, a site-specific empirical correction approach and an approximate 25 dB first-order design margin are suggested for preliminary LoRa link-budget planning in similar tropical vegetated environments. The findings indicate that free-space-only prediction may be insufficient for practical deployment and that measurement-driven correction can improve the realism of wireless sensor network design in vegetation-rich environments. Full article

This paper presents the design and simulation of a dual-redundant broadband low-noise amplifier (LNA) module for inter-satellite communication links operating in the V-band (59–71 GHz). The growing demand for high-capacity space communication systems requires highly reliable, low-noise front-end architectures capable of maintaining performance over long mission lifetimes. To address these needs, a selectable dual-input receiver architecture is proposed, integrating a waveguide dual-probe, redundant switching, and a two-stage LNA within a single Gallium Arsenide (GaAs) MMIC. The design methodology accounts for the non-ideal behavior of the redundant branch and its impact on noise figure and insertion loss. The front-end is implemented using a 70 nm GaAs mHEMT technology optimized for millimeter-wave low-noise applications. Simulations show an insertion gain higher than 15 dB across the operational band, with gain ripple below 1.3 dB peak-to-peak. The simulated system noise figure is approximately 3.0 dB, closely matching the target specification. The results demonstrate that the proposed architecture provides improved reliability through redundancy while maintaining competitive noise and gain performance for future V-band inter-satellite links. Full article

We present the integration of an automated polarization control system into a figure-eight fiber laser with the aim of self-tuning noise-like pulses (NLPs). The system optimizes polarization adjustments by using adaptive control and predictive neural networks (NNs), enhancing temporal and spectral behavior. This approach enables precise control over pulse characteristics, achieving an average output power of 275.25 mW (302.8 nJ) for signal emission at ~1567 nm; adjustable NLP envelope durations from 13 ns to 48 ns, corresponding to spectral widths from 50 to more than 200 nm; and the ability to increase in a controllable way the repetition frequency up to 100 times the fundamental frequency, which corresponds to 909 kHz, through cavity harmonic pulse generation. A multiparameter pulsed regime-seeking algorithm stabilizes high-energy NLPs in the fundamental or harmonic regime while predictive networks optimize the cavity response, and the process is completed in an average time of 11.5 s. The automated polarization control system enables high cavity harmonic pulse generation, as well as broadband supercontinuum (SC) spectrum with high flatness. Full article

Conventional terahertz (THz) radio frequency (RF) frontends struggle to simultaneously balance the high performance and miniaturization of monolithic integrated designs with the excellent testability of discrete modular architectures. This paper presents a detachable 183 GHz terahertz RF frontend and completes the module design and system integration of a low-noise amplifier (LNA) and a second-order subharmonic mixer. Through optimization of the waveguide-to-microstrip transition, parasitic compensation for pad bonding, and the structural design of the chip shielding cavity, combined with a high-precision alignment scheme using positioning pins and screws, the integrated module achieves detachability, testability, and ease of maintenance. Measurement results show that across the 160–200 GHz frequency band, the amplifier achieves an average gain of 16.51 dB; the mixer exhibits a minimum conversion loss of 8.62 dB; and the full-link noise figure of the system reaches 6.68 dB. The proposed scheme effectively addresses the engineering challenges of conventional integrated architectures and provides a practical implementation pathway for terahertz communication and remote sensing detection frontends. Full article

Biosensors have emerged as a rapidly evolving area of research, offering transformative potential across biomedical diagnostics, environmental monitoring, and pharmaceutical applications. Among the diverse range of biosensing technologies, graphene-based surface plasmonic resonance (SPR) biosensors have attracted particular interest due to their exceptional sensitivity, scalability for mass production, and cost-effective fabrication processes. This study explores the operational principles and current design methodologies of graphene-based SPR biosensors, with a special emphasis on the role of electrolyte gating and its impact on sensor performance. Furthermore, the influence of graphene’s quantum capacitance is investigated as a critical parameter for improving the accuracy and reliability of performance predictions in the proposed sensor configuration. Computational analysis of sensitivity and key performance metrics was conducted. Notably, key performance metrics of the sensor improved upon incorporating quantum capacitance effects into the simulation framework. At a β₂-microglobulin concentration of 0.00118 g/L, the sensitivity increased to 174 GHz·g/L, the figure of merit reached 0.55 L/g, the quality factor was 0.01, the signal-to-noise ratio (SNR) rose to 0.008, and the detection accuracy (DA) reached 0.08 L/THz, demonstrating the significant impact of quantum capacitance on the sensor’s performance. These findings highlight the potential of quantum-electrostatic considerations to enhance the precision and efficacy of graphene-based SPR biosensors, paving the way for the development of next-generation biosensing platforms with improved analytical capabilities. Unlike conventional graphene SPR biosensors, which primarily detect refractive index changes near the graphene surface, our model explicitly considers the electrostatic effect of biomolecules on graphene’s Fermi energy. By modelling β2-microglobulin as a charged species, we compute the resulting electric double layer and incorporate quantum capacitance in series. This amplifies the charge-induced modulation of graphene’s optical conductivity, and, combined with a graphene perfect absorber design, leads to enhanced plasmonic resonance shifts. Consequently, our approach achieves higher sensitivity and more precise detection of biomolecular interactions compared to traditional simulations. Full article

In this paper, we present a study on the automated design optimization of a wideband low-noise amplifier (LNA) operating in Ku-band (12 to 18 GHz) using proximal policy optimization (PPO), one of the widely applied reinforcement learning (RL) algorithms for engineering problems. As a target microwave active circuit, we select a two-stage LNA architecture, where transmission lines (TLs) are dominantly used for impedance matching and gain/noise optimization. For simplicity, all widths of TLs were fixed so that the characteristic impedance is 50 Ω, with lengths of TLs being set as design parameters. In addition, dimension variables of capacitors were treated as design parameters and, in total, we optimized 29 parameters. For target specifications, we set both $S_{11}$ and $S_{22}$ to be below −10 dB over the 12–18 GHz band and the noise figure (NF) to be below 2 dB. A total of 20,140 simulations were performed for training and the overall process took about 24 h. The results show that both the reward and the loss converged appropriately, achieving the target specifications successfully. For the final results, we performed up to 25 predictions, and the prediction process was terminated early if a solution meeting all target specifications was found within the given number of attempts. The device model used was a commercial 150 nm GaN high-electron-mobility transistor (HEMT) process technology. Full article