Search Results (82)

To address the high demand for precise low-current measurements at the Sirius’ beamlines, a quad-channel high-resolution Ethernet picoammeter has been designed. The instrument can measure currents ranging from femtoampere to milliampere across eight selectable ranges, featuring integrated analog-to-digital converters (ADCs), enabling sampling rates of up to 2 ksps and synchronization capabilities. This work describes the hardware design, the hardware handling procedures to achieve sub-picoampere resolution, and the characterization results of the instrument, considering the experimental results from Sirius beamlines. The designed device provides noise performance and gain accuracy that is comparable to high-end commercial solutions, proving its suitability for critical applications like on-the-fly scanning experiments. Special attention will be given to evaluating trigger latency, synchronization outcomes, as well as the device’s installation and commissioning at beamlines. Furthermore, we will deeply explore the interplay between the trigger period, digital filter bandwidth, and front-end analog bandwidth to optimize the signal-to-noise ratio in specific applications. The hardware project is publicly available in CERN’s open hardware repository. Full article

Background: Gynecological cancers include collections of cancers with diverse cellular and molecular characteristics that often develop drug resistance, making them treatment-resistant. Biomolecule–drug conjugates (BDCs), especially antibody–drug conjugates (ADCs), have revolutionized the targeted therapy of cancer; however, the creation of these entities has so far been achieved by empirical, resource-intensive design methods. Objective: The aim of this review is to critically analyze how AI can be used for the rational design and optimization of high-affinity BDCs for gynecological cancer treatment. Methods and discussion: Recent advances in machine learning (ML)- and deep learning (DL)-based methods to predict biomolecule-target binding affinity, structural compatibility, linker stability, payload selection, trafficking in the cell, and biomolecule resistance mechanisms are summarized. The review also explores the possibilities for incorporation of structural, chemical, biological, and multi-omics data to enhance specificity, efficacy, and safety of conjugates. Besides antibody-based systems, AI-assisted design approaches with peptides, aptamers, and hybrid biomolecular systems are also included. This review also highlights parameters and experimental/numerical validation restrictions related to data quality, interpretability of models, regulatory aspects, etc. Conclusions: AI-based conjugate engineering is increasingly moving BDC development from a largely ‘trial and error’ approach to a more predictive and data-driven approach. While there are still challenges to be addressed in terms of translations and validations, the potential of AI approaches in the field of precision oncology and the development of more personalized treatment is promising in the context of gynecological cancers. Full article

This paper proposes a digital potentiometer-based adaptive gas sensor interface for stable detection without signal saturation under extreme environmental fluctuations. Conventional fixed-gain circuits often suffer from limited dynamic range, leading to data loss when severe baseline drifts exceed ADC input limits. To address this, we developed a real-time control algorithm that actively adjusts attenuator and amplifier gains, maintaining the ADC input voltage (V_ADC) near the common-mode voltage (V_CM). Experimental results demonstrate that the interface remains stable even when the buffer voltage reaches 2.75 V, significantly surpassing the 1.2 V ADC limit. Sensor resistance data, reconstructed by inversely calculating updated circuit parameters, achieved high accuracy with a Mean Absolute Percentage Error (MAPE) of 1.628% and a maximum relative error under 4.8%. Consequently, this study proves that logically extending the physically limited ADC dynamic range enables high-precision gas sensing in diverse environments without requiring high-performance computing devices. This approach provides a cost-effective and robust solution for compact IoT-based gas monitoring systems. Full article

High-precision time and frequency references are essential for satellite navigation, deep-space exploration, and space science missions. To address the large size, high power consumption, and limited integration of conventional Passive Hydrogen Maser (PHM) servo electronics based on discrete analog chains, this paper proposes a miniaturized digital servo architecture for PHMs based on software-defined radio (SDR) and a field-programmable gate array (FPGA). The AD9364 is used as an integrated RF front end for microwave interrogation signal generation, receiver down-conversion, and analog-to-digital conversion (ADC), while digital demodulation, discriminator construction, and closed-loop control are implemented in the FPGA. A dual-frequency interrogation and time-division multiplexing scheme is introduced to separate the atomic and cavity responses, and an oversampling-based processing method combining outlier rejection and averaging decimation is adopted to improve the observation accuracy and noise immunity of weak error signals. Experimental results demonstrate stable closed-loop locking of the atomic transition spectrum, achieving a frequency stability of 1.46 × 10⁻¹² at 1 s, while significantly improving the compactness and integration level of the servo electronics. Full article

Current research on the participation of inverter-based air conditioners in demand response often prioritizes system performance during regulation periods yet frequently overlooks the prolonged high indoor temperatures that follow. Furthermore, oversimplified user comfort constraints limit the accurate evaluation of peak-shaving potential. To address these limitations, this paper proposes a novel control framework. First, a differential user comfort evaluation model is established to quantify the adjustable temperature range under varying scenarios. Second, an analog duty cycle grouped rotation control model is developed. By leveraging the variable-frequency characteristics of inverter ACs, this method optimized peak-shaving potential while preventing indoor temperatures from remaining at their upper limits for extended durations. Third, to ensure fairness, a user selection model incorporating a User Impact Factor is introduced as a dynamic ranking criterion for participation priority. Finally, to address the inevitable parameter mismatch in practical engineering, the control strategy is upgraded to a feedforward–feedback closed-loop framework. Simulation results demonstrate the superiority of the proposed ADC strategy over existing methods. Specifically, compared to existing methods, it achieved a 45–50% reduction in the high-temperature influence factor and a 67% decrease in the standard deviation of user impact, indicating significantly improved thermal comfort and fairness. Furthermore, the framework exhibits strong robustness; even under 20% parameter uncertainty, it restricted the duration of temperature exceedance to within 0.8%, strictly outperforming traditional open-loop approaches in preventing user discomfort. These improvements ensure a more uniform distribution of comfort impacts among users, thereby enhancing both the precision and sustainability of demand-side peak shaving. Full article

The von Neumann architecture faces severe bottlenecks in energy efficiency. Computing-in-Memory (CiM) addresses this by performing computations within memory arrays, yet analog CiM solutions suffer from precision loss and high overhead from analog-to-digital converters and digital-to-analog converters (ADCs/DACs). This paper proposes a novel ADC-free CiM architecture based on Ferroelectric Field-Effect Transistors (FeFETs). Logic circuits (NOR, NAND, XNOR) that store weight vectors within FeFETs were designed. Compared with analog CiM circuits, the FeFETs-CiM circuits proposed in this paper can reduce power consumption by 901.1 times and latency by 272.7 times. Furthermore, the design of 3-bit FeFETs-CiM gates was extended, demonstrating flexible configurability for scalable edge computing applications. Finally, an application specific FeFETs-CiM subtractor for k-nearest neighbor (kNN) distance calculation was designed, which energy consumption is as low as 85.02 fJ/OP and latency is as low as 0.56 ns under 500 MHz operation frequency. The calculation robustness of the FeFETs-CiM kNN distance calculator was ensured by simulating under different process corners and temperatures. The performance improvements owing to the proposed FeFETs-CiM CMOS circuits were evaluated by taking the kNN algorithm as an example, which can ensure the data access reduction by more than 300 times compared to von Neumann architecture. Full article

High-precision detection of rice targets in precision agriculture is crucial for yield assessment and field management. However, existing models still face challenges, such as high rates of missed detections and insufficient localization accuracy, particularly when dealing with small targets and dynamic changes in scale and morphology. This paper proposes an accurate rice detection model for UAV images based on Adaptive Aware Dynamic Convolution, named Adaptive Dynamic Convolution YOLO (ADC-YOLO), and designs the Adaptive Aware Dynamic Convolution Block (ADCB). The ADCB employs a “Morphological Parameterization Subnetwork” to learn pixel-specific kernel shapes and a “Spatial Modulation Subnetwork” to precisely adjust sampling offsets and weights—realizing for the first time the adaptive dynamic evolution of convolution kernel morphology with variations in rice scale. Furthermore, ADCB is embedded into the interaction nodes of the YOLO backbone and neck; combined with depthwise separable convolution in the neck, it synergistically enhances multi-scale feature extraction from rice images. Experiments on public datasets show that ADC-YOLO comprehensively outperforms state-of-the-art algorithms in terms of AP50 and AP75 metrics and maintains stable high performance in scenarios such as small targets at the seedling stage and leaf overlap. This work provides robust technical support for intelligent rice field monitoring and advances the practical application of computer vision in precision agriculture. Full article

This paper introduces the design of a reference voltage buffer (RVB) for pipelined analog-to-digital converters (ADCs) in a 180 nm CMOS process with a 1.8 V supply voltage. The loop stability of the proposed RVB is verified by the theoretical calculations. The driving capability of the proposed RVB is demonstrated by its large driving current, and the transient response simulation results reveal its impressive speed and precision in the reference voltage settling process. Moreover, the power supply rejection ratio (PSRR) performance indicates that the proposed RVB is insensitive to the variation in power supply voltage, meeting the application requirements for high-speed and high-precision pipelined ADCs. Full article

This paper presents a low-power high-precision Discrete-Time Delta–Sigma (DT-DS) analog-to-digital converter (ADC) for a Battery Management System (BMS), which is critical for monitoring key battery parameters such as voltage, current, and temperature. This design employs a second-order Cascade of Integrators FeedForward (CIFF) architecture using a hybrid chopping technique to effectively suppress 1/f noise and offset. Fabricated in a 180 nm Bipolar-CMOS-DMOS (BCD) process, the ADC achieves a peak signal-to-noise ratio (SNR) of 91.2 dB and a peak signal-to-noise-and-distortion ratio (SNDR) of 90.6 dB within a 600 Hz bandwidth, while consuming only 35 µA from a 1.8 V supply. This corresponds to a figure-of-merit (FoM) of 160.4 dB, calculated based on the SNDR, bandwidth, and power dissipation. Full article

For microradian-level phasemeters aimed at space-based gravitational wave detection, the analog front-end circuitry plays a critical role in determining the system’s phase noise. This paper focuses on the symmetric differential structure-based operational amplifier analog front-end between the Quadrant Photodiode output and the high-resolution ADC input. An equivalent additive noise model is established, and the mechanism of noise conversion into phase noise is derived. The noise performance within the target 5–25 MHz band is evaluated through LTspice simulations and experimental verification. Experimental results show that, after suppressing sampling timing jitter with a 37.5 MHz pilot tone, the noise contribution of the front-end analog circuit to the phasemeter system is significantly better than the phase measurement noise requirement of 2π $\mathsf{\mu }\mathrm{r}\mathrm{a}\mathrm{d}/{\mathrm{H}\mathrm{z}}^{1/2}$ in the 0.1 mHz–1 Hz band for space-based gravitational wave detection. Compared with a transformer-based front-end, the differential amplifier solution exhibits significant advantages in low-frequency noise suppression and signal stability. Further analysis using the digital phase-locked loop closed-loop transfer function confirms that the noise amplitude is proportional to phase noise and inversely proportional to signal amplitude, providing a theoretical basis for analog front-end circuit optimization and system-level noise budgeting. The results offer a reliable reference for the design of high-precision phasemeters and the engineering implementation of space-based gravitational wave detection missions. Full article

The hadron calorimeter is a central component of the CMS detector, vital for measuring hadron energies and reconstructing missing transverse momentum. This paper reviews its performance before and after the Phase 1 upgrade (completed in 2019), which upgraded both back-end and front-end electronics, including photodetectors and charge-integrating ADC with precise-timing TDC, as well as its depth segmentation in the barrel and endcaps. This paper describes energy reconstruction algorithms that suppress out-of-time signals, along with high-precision timing alignment and multi-step energy calibration procedures to mitigate radiation damage and improve energy resolution Performance evaluations using proton–proton collision data demonstrate that the upgraded detector and reconstruction techniques achieve good resolution and robust operation under high-luminosity conditions. Full article

This work presents an experimental evaluation of a high-speed analog-to-digital conversion method based on passive reference waveform crossings combined with time-to-digital converter (TDC) time-tagging. Unlike conventional level-crossing event-driven analog-to-digital converters (ADCs) that require dynamically updated digital-to-analog converters (DACs), the proposed architecture compares the input waveform against a broadband periodic sampling function without active threshold control. Crossing instants are detected by a high-speed comparator and converted into rising and falling edge timestamps using a multi-channel TDC. A commercial ScioSense GPX2-based time-tagger with 30 ps single-shot precision was used for validation. A range of test signals—including 5 MHz sine, sawtooth, damped sine, and frequency-modulated chirp waveforms—were acquired using triangular, sinusoidal, and sawtooth sampling functions. Stroboscopic sampling was demonstrated using reference frequencies lower than the signal of interest, enabling effective undersampling of periodic radio frequency (RF) waveforms. The method achieved effective bandwidths approaching 100 MHz, with amplitude reconstruction errors of 0.05–0.30 RMS for sinusoidal signals and 0.15–0.40 RMS for sawtooth signals. Timing jitter showed strong dependence on the relative slope between the acquired waveform and sampling function: steep regions produced jitter near 5 ns, while shallow regions exhibited jitter up to 20 ns. The study has several limitations, including the bandwidth and dead-time constraints of the commercial TDC, the finite slew rate and noise of the comparator front-end, and the limited frequency range of the generated sampling functions. These factors influence the achievable timing precision and reconstruction accuracy, especially in low-gradient signal regions. Overall, the passive waveform-crossing method demonstrates strong potential for wideband, sparse, and rapidly varying signals, with natural scalability to multi-channel systems. Potential application domains include RF acquisition, ultra-wideband (UWB) radar, integrated sensing and communication (ISAC) systems, high-speed instrumentation, and wideband timed antenna arrays. Full article

This paper presents a precision, wide-dynamic-range leakage current sensor tailored for in-situ monitoring of aging mechanisms such as Time-Dependent Dielectric Breakdown (TDDB) in both active and passive components. The proposed architecture supports high-voltage stress and is fully monolithic, integrating a current-to-voltage front-end, tunable-gain amplifier, and a successive approximation register (SAR) analog-to-digital converter (ADC). To validate the concept, a discrete-component prototype was implemented and evaluated across a leakage current range of 1 nA to 1 $\mathsf{\mu }$A. The sensor achieves 12-bit resolution with measured integral non-linearity (INL) and differential non-linearity (DNL) within $\pm 1.5$ LSB and $\pm 0.3$ LSB, respectively. Compared to prior monitors, the design enables linear current digitization and supports high-voltage stress, features essential for accurate and scalable TDDB characterization. Applications include embedded reliability monitoring in power converters, analog building blocks, and large-scale aging test arrays. Full article

Background/Objectives: Antibody–Drug Conjugates (ADCs) have rapidly evolved from early, rudimentary conjugates to highly targeted and precisely engineered molecules. Despite notable clinical successes, ADCs continue to face significant challenges, including aggregation and high hydrophobicity driven by high drug-to-antibody ratios (DARs), premature payload release, dose-limiting toxicities, and suboptimal pharmacokinetics. While site-specific linker–payload conjugation has improved ADC homogeneity and stability, the structural basis of antibody–linker interactions at specific sites remains underexplored. Methods: In this work, we present the crystal structures of trastuzumab Fab and Fc domains site-specifically conjugated with a cleavable linker–payload. Results: Our findings suggest that pockets within both Fab and Fc regions may interact with and shield the linker portion of the conjugate. Conclusions: These insights highlight the previously underappreciated potential of structure-based design to drive the optimization of ADC linker chemistry and facilitate the co-design of bespoke linker–payloads tailored to individual antibody conjugation sites. Full article

High-precision implantable multi-channel neural recording systems are considered as having a crucial role in the diagnosis and treatment of neurological disorders. However, it is a significant design challenge to achieve an optimal trade-off among linear parameters, signal fidelity, power consumption, and circuit area. To address this challenge, a Simulink-based modeling approach has been proposed to incorporate adjustable non-linear parameters across the front-end circuits and analog-to-digital converter (ADC) stages. The model evaluates non-linearity impacts on system performance through both quantitative spike detection accuracy analysis and a neural decoding paradigm based on Chinese handwriting reconstruction. Simulated results show that total harmonic distortion (THD) can be set to −34.32 dB for the low-noise amplifier (LNA), −33.73 dB for the programmable gain amplifier (PGA), and −57.95 dB for the ADC in order to achieve reliable detection accuracy with minimal design cost. Moreover, ADC non-linearity has a greater influence on system performance than that of the LNA and PGA. The proposed approach offers quantitative and systematic hardware design guidance to balance signal fidelity and resource efficiency for future low-power, high-accuracy neural recording systems. Full article