Anxiety and depressive symptoms are common in patients with inflammatory demyelinating diseases (IDDs), but low-burden digital behavioral tools remain underexplored. This study examined whether digital tree drawing and person-in-the-rain tasks contain machine learning-assisted phenotyping signals associated with anxiety and depression in IDD. We analyzed 86 patients (84 for MADRS) with valid digital drawing trajectories and emotional assessments. A total of 257 demographic, trajectory, pressure, pause, content, bounding-box, and cross-task features were extracted. Continuous HAMA, HAMD, and MADRS scores and exploratory binary labels (scores of 7 or higher) were evaluated across eight prespecified candidate pipelines, defined by four feature sets crossed with ridge and elastic net models. All pipelines used identical repeated five-fold outer cross-validation splits, with preprocessing, repeated subsampling supervised univariate feature ranking, and model fitting confined to the outer training folds. Predictive performance was limited and varied by outcome. For continuous outcomes, HAMA showed modest signal across candidate pipelines (R2 = 0.082–0.133), whereas HAMD and MADRS remained close to the null baseline (R2 = −0.089 to −0.068 and −0.025 to −0.011, respectively). For binary labels, ROC-AUC ranges were 0.564–0.643 for HAMA ≥ 7, 0.590–0.609 for HAMD ≥ 7, and 0.685–0.733 for MADRS ≥ 7. Outer-fold feature-recurrence summaries most consistently identified person bounding-box dimensions and cross-task path length measures for HAMA and pause-related timing features for HAMD and MADRS. These findings suggest that digital drawing may capture limited but interpretable emotional symptom-related behavioral variation within IDD cohorts. Further multicenter and external validation is needed to evaluate its role as a complementary behavioral assessment paradigm.

We report an efficient quantum digital signature system using coherent states that achieves a signature rate of 1144 times per second for a 1 Mbit message over 50 km fiber with information-theoretic security.

Continuous-variable quantum key distribution holds the potential to generate high secret key rates, making it a prime candidate for high-rate metropolitan quantum network applications. However, despite these promising opportunities, the realization of high-rate continuous-variable quantum key distribution systems with composable security remains an elusive goal. Here, we report a discrete-modulated continuous-variable quantum key distribution system with a composable secret key rate of 18.93 Mbps against collective attacks over a 25 km fiber channel. This record-breaking rate is achieved through the probability shaped 16QAM-modulated protocol, which employs semidefinite programming to ensure its composable security. Furthermore, we have employed a fully digital and precise quantum signal processing technique to reduce excess noise to extremely low levels, thereby facilitating efficient broadband system operation. While ensuring low complexity and cost, our system achieves a performance advantage of over an order of magnitude compared to previous continuous-variable quantum key distribution systems, providing a promising solution for future deployment of quantum key distribution.

In precision frequency transfer systems, stringent requirements are imposed on the phase stability of transmitted signals. Throughout the transmission process, the inherent challenges of long-haul signal propagation inevitably introduce multiple noise components, including, but not limited to, thermal noise, phase fluctuations, and environmental interference. The system is inclined to use the conventional evaluation index - Allan deviation (ADEV) to reflect the system stability in order to evaluate the noise level. Whereas, ADEV can only provide numerical expression and lacks the time-frequency details, a complete evaluation system is therefore required by the system. In this paper, we present a groundbreaking integration of ADEV and wavelet-transformed empirical mode decomposition (EMD-WT), establishing a novel analytical framework that enables simultaneous characterization of noise types and time-frequency domain properties. This synergistic approach achieves unprecedented dual-domain resolution in noise discrimination in frequency transfer systems.

Purpose: The virtual reality (VR) game has been considered an emerging and promising method for non-pharmaceutical intervention for dementia. However, previous works lack sufficient discussion of accessible design when games with different intervening purposes are applied to users at different stages of cognitive impairment. Methods: We conducted a user study with 11 participants in three stages of cognitive impairment by using a designed cognitive training game developed through the participatory design approach and a commercial recreational game. Video recordings, semi-structured interviews, caregiver feedback, and observation notes were analysed through thematic analysis. Results: Three themes were refined for understanding the accessibility of different virtual reality games. Firstly, the virtual reality game with a single intervening purpose may be limited because cognitive training and recreational games have differentiated usefulness to people with different degrees of cognitive impairment. Secondly, the personalized difficulty-matching strategy is crucial for cognitive training games. Thirdly, recreational virtual reality games integrated with social interaction could stimulate positive emotions in users with cognitive impairment. Conclusion: Three design implications are extracted for future design: multi-component or multi-dimensional intervention, artificial-intelligence-empowered difficulty matching, and emotionally intelligent virtual agents for social interaction.

Continuous-variable quantum key distribution is a practical solution for secure communication, compatible with classical optical networks. The discrete modulation scheme simplifies implementation but complicates security analysis, where the shot-noise unit is a critical parameter. Traditional two-step shot-noise unit calibration is experimentally cumbersome and unsuitable for real-time systems. Here, we propose a one-time shot-noise unit calibration method for discrete-modulated continuous-variable quantum key distribution, which determines the shot-noise unit in a single step. Our approach introduces a revised detector model that treats electrical noise loss as untrusted, incorporating it into the channel. We establish the equivalence between the entanglement-based and prepare-and-measure schemes under this model and derive the corresponding positive operator-valued measure for heterodyne detection. Combining trusted-source-noise model, a complete practical security model can be achieved. Security analysis and simulations show that the proposed method achieves performance close to traditional protocols, facilitating the deployment of discrete-modulated continuous-variable quantum key distribution systems with automated, real-time calibration.

Fully integrated photonic continuous-variable quantum key distribution is a promising route toward compact and scalable secure optical links, yet the achievable transmission distance has been limited by the performance of integrated receiver chips and excess noise suppression methods. Here, we demonstrate a Gaussian-modulated continuous-variable quantum key distribution system with an integrated silicon photonic receiver, operating over 60 km. Enabled by a high-clearance, broadband silicon photonic receiver, in conjunction with a robust digital signal processing framework that utilizes a time-domain superposition algorithm and secure dynamic single-tap equalization, the system effectively achieves an asymptotic secret key rate of 1.68 Mbps, and a finite-size secret key rate of 0.80 Mbps at a data block length of 1.55×109. This work extends chip-based continuous-variable quantum key distribution to metropolitan-scale distances, confirming the viability of integrated receivers for large-scale quantum networks.

We report a 16QAM-modulated continuous-variable quantum key distribution system with a record-breaking composable secret key rate of 8.93 Mb/s over 25 km fiber channel, surpassing previous systems by an order of magnitude in performance while remaining low-complexity and cost-effective. (c) 2025 The Author(s)

Employing an advanced security analysis method, we experimentally demonstrated a local local oscillator continuous-variable quantum key distribution system over 126.56 km of single mode fiber with probabilistic shaped 16QAM, achieving a secret key rate of 169.37 kbps.

Quantum key distribution (QKD), providing a way to generate secret keys with information-theoretic security,is arguably one of the most significant achievements in quantum information. The continuous-variable QKD (CV-QKD) offers the potential advantage of achieving a higher secret key rate (SKR) within a metro area, as well as being compatible with the mature telecom industry. However, the SKR and transmission distance of state-of-the-art CV-QKD systems are currently limited. Here, based on the novelly proposed orthogonal-frequency-division-multiplexing (OFDM) CV-QKD protocol, we demonstrate for the first time a high-rate multi-carrier (MC) CV-QKD with a 10 GHz symbol rate that chieves Gbps SKR within 10km and Mbps SKR over 100 km in the finite-size regime under composable security against collective attacks. The record-breaking results are achieved by suitable optimization of subcarrier number and modulation variance, well-controlled excess noise induced by both OFDM mechanism and efficient DSP scheme, and high-performance post-processing capacity realized by heterogeneous computing scheme. The composable finite-size SKR reaches 1779.45 Mbps@5km, 1025.49 Mbps@10km, 370.50 Mbps@25km, 99.93 Mbps@50km, 25.70 Mbps@75km,and 2.25 Mbps@100km, which improves the SKR by two orders of magnitude and quintuples the maximal transmission distance compared to most recently reported CV-QKD results [Nature Communications, 13, 4740 (2022)]. Interestingly, it is experimentally verified that the SKR of the proposed MC CV-QKD can approach five times larger than that of the single-carrier CV-QKD with the same symbol rate without additional hardware costs. Our work constitutes a critical step towards future high-speed quantum metropolitan and access networks.

This work boosts the robustness of machine-learning based multimode fiber single-pixel imaging against fiber bending by adding Gaussian noise in training data. Training on single-configuration data improves cross-configuration generalization, reducing data complexity versus multi-configuration methods.

Cognitive impairment is common but often overlooked in patients with inflammatory demyelinating diseases such as multiple sclerosis and neuromyelitis optica spectrum disorder. The conventional assessments may fail to detect subtle deficits and require substantial time and expertise. We collected neuropsychological scores and real-time handwriting data across nine drawing tasks and tasks from the Symbol Digit Modalities Test in 93 patients. Temporal, pressure, and kinematic features were extracted, and machine learning classifiers were trained using five-fold cross-validation with bootstrap confidence intervals. The response timing and pen pressure metrics correlated significantly with global cognitive scores (|r| = 0.30–0.37, p < 0.01). A support vector machine using eight selected features achieved an area under the receiver-operating characteristic curve (AUC) of 0.910, and a streamlined five-feature variant maintained an equivalent performance (AUC = 0.921) while reducing the assessment time by 35%. These results indicate that digital handwriting metrics can complement the standard screening by capturing fine motor and temporal characteristics overlooked in conventional testing. Validation in larger, disease-balanced, and longitudinal cohorts is needed to confirm their clinical utility.

We propose a theoretical upper limit for truncation thresholds in TSVD-based MMF-SPI, revealing that incorporating the smaller singular values which were oft-overlooked not only aligns with the proposed bound but also enhances image recovery significantly.

Truncated singular value decomposition (TSVD) is a popular recovery algorithm for multimode fiber single-pixel imaging (MMF-SPI), and it uses truncation thresholds to suppress noise influences. However, due to the sensitivity of MMF relative to stochastic disturbances, the threshold requires frequent re-determination as noise levels dynamically fluctuate. In response, we design an adaptive truncation threshold determination (ATTD) method for TSVD-based MMF-SPI in disturbed environments. Simulations and experiments reveal that ATTD approaches the performance of ideal clairvoyant benchmarks, and it corresponds to the best possible image recovery under certain noise levels and surpasses both traditional truncation threshold determination methods with less computation—fixed threshold and Stein’s unbiased risk estimator (SURE)—specifically under high noise levels. Moreover, target insensitivity is demonstrated via numerical simulations, and the robustness of the self-contained parameters is explored. Finally, we also compare and discuss the performance of TSVD-based MMF-SPI, which uses ATTD, and machine learning-based MMF-SPI, which uses diffusion models, to provide a comprehensive understanding of ATTD.

Long-distance radio frequency (RF) synchronization through fiber link is attracting more attention in recent years. The repeater becomes increasingly important with the increase of the transmission distance. In this article, we analyze the three main relay methods principally including single-span, signal relay, and cascade connection frequency transmission and compare their frequency instability. The proof-of-concept experiments are also conducted along a 3009.8 km fiber link in the laboratory environment. The system used for comparison is a combination of phase conjugation and phase-locked loop (PLL) designed for long-distance frequency transmission. The best transfer preference can be obtained by using the cascade connection, whose frequency instabilities of 8.8x10(-14)@1sand8.4x10(-17) @ 10 000 s have been measured for phase-stable RF signal. Our study can be useful for the calibration and comparison of ultra-long-distance atomic clocks.

The present study evaluated the performance of the digital clock drawing test (dCDT) signature variable in assessing cognitive function in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) compared to healthy controls (HC). Thirty-three participants, including 18 patients with MS or NMOSD and 15 HCs, underwent dCDT and Montreal Cognitive Assessment (MOCA) testing. The cognitive functions of the patients were further evaluated using a neuropsychological test battery. Global features based on time, space, and motion in the dCDT process were collected. ANOVA showed that consistent with MOCA scores, the three groups (HC, cognitively impaired patients, and cognitively normal patients) exhibited differences in CDT scores, clock digit placement, line length, and pen trajectory velocity characteristics (all p < 0.004). The follow-up work used correlation analysis and stepwise regression to assess the correlation between dCDT parameters and EDSS scores as well as neuropsychological tests. Notably, the vibration amplitude of pen movement during drawingly correlated with the EDSS score (p < 0.001), indicating that it reflects clinical status. Other variables, such as the characteristic variable that characterizes the degree of spectral dispersion in pen movement trajectories, trajectory length, test duration, and average stress, significantly correlate with neuropsychological test results involving memory, language, and information processing speed at different levels (all p < 0.04). Our findings suggest that dCDT's complex features link to cognitive abilities and physiological impairments in MS/NMOSD patients. Kinematic, temporal, and visual space-based global and process characteristics serve as valuable neurocognitive biomarkers. This offers the potential for dCDT to serve as a cognitive assessment tool for MS/NMOSD patients in the future.

We report the amplitude-boosting attack against 256QAM continuous-variable quantum key distribution system, which could lead to an inflated estimation of secret key rate by communication parties, thereby compromising the security of practical system.

Discrete-modulated continuous-variable quantum key distribution offers a pragmatic solution, greatly simplifying experimental procedures while retaining robust integration with classical optical communication. Theoretical analyses have progressively validated the comprehensive security of this protocol, paving the way for practical experimentation. However, imperfect source in practical implementations introduce noise. The traditional approach is to assume that eavesdroppers can control all of the source noise, which overestimates the ability of eavesdroppers and underestimates secret key rate. In fact, some parts of source noise are intrinsic and cannot be manipulated by eavesdropper, so they can be seen as trusted noise. We tailor a trusted model specifically for the discrete-modulated protocol and upgrade the security analysis accordingly. Simulation results demonstrate that this approach successfully mitigates negative impact of imperfect source on system performance while maintaining security of the protocol. Furthermore, our method can be used in conjunction with trusted detector noise model, effectively reducing the influence of both source and detector noise in experimental setup. This is a meaningful contribution to the practical deployment of discrete-modulated continuous-variable quantum key distribution systems.

Discrete-modulated continuous-variable quantum key distribution offers significant practical deployment advantages due to its straightforward state preparation and high compatibility with coherent optical communication systems. However, security analysis and parameter estimation of discrete-modulated protocol are different with Gaussian-modulated protocols, which could cause different practical security problems. Herein, we investigate the amplitude- boosting attack against discrete-modulated continuous-variable quantum key distribution systems and assess its impact on system performance. Our findings reveal that this attack could cause overestimation of secret key rate perceived by Alice and Bob, thereby opening a security loophole, and the vulnerability could be severer than Gaussian modulation. Additionally, we summarize defensive countermeasures, marking a crucial step towards enhancing the practical security of discrete-modulated continuous-variable quantum key distribution.