Search Results (1,118)

Modern AI systems can strategically misreport information when incentives diverge from truthfulness, posing risks for oversight and deployment. Prior studies often examine this behavior within a single paradigm; systematic, cross-architecture evidence under a unified protocol has been limited. We introduce the Strategy Elicitation Battery (SEB), a standardized probe suite for measuring deceptive reporting across large language models (LLMs), reinforcement-learning agents, vision-only classifiers, multimodal encoders, state-space models, and diffusion models. SEB uses Bayesian inference tasks with persona-controlled instructions, schema-constrained outputs, deterministic decoding where supported, and a probe mix (near-threshold, repeats, neutralized, cross-checks). Estimates use clustered bootstrap intervals, and significance is assessed with a logistic regression by architecture; a mixed-effects analysis is planned once the per-round agent/episode traces are exported. On the latest pre-correction runs, SEB shows a consistent cross-architecture pattern in deception rates: ViT $80.0\%$, CLIP $15.0\%$, Mamba $10.0\%$, RL agents $10.0\%$, Stable Diffusion $10.0\%$, and LLMs $5.0\%$ (20 scenarios/architecture). A logistic regression on per-scenario flags finds a significant overall architecture effect (likelihood-ratio test vs. intercept-only: ${\chi }^2\left(5\right)=41.56$, $p=7.22\times {10}^{-8}$). Holm-adjusted contrasts indicate ViT is significantly higher than all other architectures in this snapshot; the remaining pairs are not significant. Post-correction acceptance decisions are evaluated separately using residual deception and override rates under SEB-Correct. Latency varies by architecture (sub-second to minutes), enabling pre-deployment screening broadly and real-time auditing for low-latency classes. Results indicate that SEB-Detect deception flags are not confined to any one paradigm, that distinct architectures can converge to similar levels under a common interface, and that reporting interfaces and incentive framing are central levers for mitigation. We operationalize “deception” as reward-sensitive misreport flags, and we separate detection from intervention via a correction wrapper (SEB-Correct), supporting principled acceptance decisions for deployment. Full article

Background/Objectives: Pelvic organ prolapse (POP) is a common condition that increases with age and affects up to 40% of women. Colpocleisis is a possible native-tissue repair used in elderly persons not interested in vaginally penetrative sex to correct advanced POP. This study aims to evaluate the recurrence and reoperation rate of a technique using purse-string sutures in a standardised way. Methods: This retrospective quality control study evaluated all women who underwent obliterative procedures for POP at the Department of Obstetrics and Gynaecology at the University Hospital of Bern from 2014 to 2023. Total Colpocleisis (TC) and Le-Fort Colpocleisis (LFC) were performed by a standardised technical procedure using purse-string sutures. The primary outcome was the recurrence rate measured by the POP-Q stage (stage 2 or higher). Reoperation rate, perioperative complications, bladder outlet disorders and incontinence symptoms were assessed as secondary outcomes. Results: We analysed eighty-eight patients who underwent obliterative surgery with TC or LFC in this study. The recurrence rate for all patients was 16%, and the reoperation rate was 9.2%. In patients without previous surgeries (52%), the recurrence rate was 7%. Thirteen patients (14.8%) had perioperative complications, mainly urinary tract infections (seven patients, 8%). Objective POP improved significantly (p < 0.001), as did the bladder voiding dysfunction in the rate of high postvoid residual volume (p < 0.05), stress urinary incontinence, overactive bladder and mixed urinary incontinence (p < 0.001). In three patients, de novo stress urinary incontinence developed postoperatively. Conclusions: Colpocleisis by the purse-string technique is an effective surgical treatment for advanced POP surgery. Recurrence and reoperation rates are similar to the previously mentioned techniques and are easy to learn due to the standardised procedure. Full article

To address the problem of the degraded positioning accuracy of the long-baseline undifferenced network RTK (URTK) under extreme space weather conditions, herein, we propose a user-side atmospheric delay estimation strategy based on the undifferenced network RTK concept to enhance positioning performance in geomagnetic storm environments. First, an ambiguity-resolution model that jointly estimates atmospheric error parameters is used to fix the carrier-phase integer ambiguities for long-baseline reference stations. The accurately fixed inter-station ambiguities are then linearly transformed to recover station-specific undifferenced integer ambiguities; undifferenced observation errors at each reference station are computed to generate corresponding undifferenced correction terms. Lastly, recognizing that ionospheric delays vary sharply during geomagnetic storms and can severely compromise the availability of regional undifferenced correction models, we estimate the residual atmospheric parameters on the user side after applying regional corrections. Experimental results show that the server side is not significantly impacted during geomagnetic storms and can continue operating normally. On the user side, augmenting the solution with atmospheric parameter estimation effectively improves positioning availability. Under strong geomagnetic storms, the proposed mode improves user-station positioning accuracy by 63.7%, 60.7%, and 64.4% in the east (E), north (N), and up (U) components, respectively, relative to the conventional user-side solution; under moderate storm conditions, the corresponding improvements are 16.7%, 10.0%, and 11.1%. Full article

The detection and characterization of exoplanets are central topics in astronomy, and high-contrast imaging techniques such nulling interferometry, coronagraphs, and extreme adaptive optics (ExAO) are key tools for the direct detection of exoplanets. This review synthesizes the pivotal role of these techniques in astronomical research and critically analyzes their role as key drivers of progress in the field. Nulling interferometry suppresses stellar light through the phase control of multiple telescopes, thereby enhancing the detection of faint planetary signals. This technology has evolved from the initial Bracewell concept to the LIFE (Large Interferometer For Exoplanets) technique, which will achieve a contrast ratio of 10⁻⁷ in the mid-infrared wavelength range in the future. Coronagraphs block starlight to create a “dark region” for direct observation of exoplanets. By leveraging innovative mask designs, theoretical contrast ratios of up to 4 × 10⁻⁹ can be achieved. ExAO systems achieve precise wavefront correction to optimize the high-contrast imaging performance and mitigate atmospheric disturbances. By leveraging wavefront sensing, thousand-element deformable mirrors, and real-time control algorithms, these systems suppress the turbulence correction residuals to 80 nm RMS, enabling ground-based telescopes to achieve a Strehl ratio exceeding 0.9. This work provides a comprehensive analysis of the underlying principles, prevailing challenges, and future application prospects of these technologies in astronomy. Full article

Background/Objectives: Juvenile hallux valgus (JHV) and flexible flatfoot (FFF) often coexist in children, yet their combined surgical management remains poorly explored. This study evaluates clinical and radiographic outcomes following a simultaneous approach using lateral hemiepiphysiodesis of the first metatarsal (LHFM) and calcaneal-stop (C-Stop) procedures in skeletally immature patients. Methods: A retrospective cohort of 24 bilateral patients (48 feet) aged 10–12 underwent LHFM and C-Stop between 2017 and 2023. Radiographic evaluation included Hallux Valgus Angle (HVA), Intermetatarsal Angle (IMA), Meary’s angle (MA), and transverse TaloCalcaneal (Kite’s) Angle (tTCA). The Foot and Ankle Disability Index (FADI) and the Tegner Activity Scale (TAS) were administered at the most recent follow-up and complications were recorded. Results: The mean follow-up was 3.7 years. Postoperative radiographs showed significant improvements in all parameters, with correction inversely correlated to baseline deformity severity. Full normalization of flatfoot parameters was achieved in 68.8% of feet, with mild residual deformity in the remainder. Males showed greater radiographic correction than females. IMA and HVA improved in most cases, reaching full normalization in 53.1% and 50% of feet, respectively. Clinically, all patients showed corrected hindfoot alignment and medial arch restoration; 90% achieved the maximum FADI score and 88% resumed recreational sports. Two cases of screw migration occurred, with one revision; no further complications were reported. Conclusions: Simultaneous correction of FFF and JHV using C-Stop and LHFM proved effective, yielding significant radiographic improvements and excellent functional outcomes in most cases, with minimal complications. However, full hallux alignment was achieved in only half of the cases, suggesting that additional distal metatarsal procedures may be needed for more severe deformities. Full article

Incomplete absorption correction procedures in single-crystal diffraction experiments leave a characteristic trace—a “fingerprint”—in the residuals. Specifically, weak intensities are systematically overestimated, contributing disproportionately and sometimes even dominantly to the chi-square sum in least squares refinements. An analysis of six published crystal structures spanning a wide range of absorption coefficients reveals a consistent positive shift of the weighted residuals, which were significant for crystals with $>5.02$ mm⁻¹. This shift is all the stronger the greater the absorption coefficient and is accompanied by a proportionally increasing fraction of positive excess residuals. The simultaneous increase in the mean value of the residuals and the fraction of positive excess residuals proves that the shift is not caused by strong reflections or isolated outliers, but rather by the systematic overestimation of many weak intensities. Diagnostic plots and statistical metrics are presented for additional published data sets, supporting the generality of the findings. These findings can support the development of improved methods for absorption correction, which lead to physically meaningful thermal motion parameters even with strong absorption. Full article

Considering the limited availability of meteorological data in practice, this paper investigates the short-term photovoltaic output prediction problem based on data decomposition and error correction to further improve prediction accuracy. Firstly, according to the analysis of the variation characteristics of photovoltaic output data, the Seasonal and Trend decomposition using Loess (STL) method is used to decompose the original data into three components: seasonal term, trend term, and residual term. Considering that the variation patterns of different components are different, based on the division of the dataset, temporal convolutional network (TCN)-based prediction models for each component are constructed separately, and the prediction results are superimposed to obtain the predicted value of the photovoltaic output. Secondly, an error dataset is constructed based on the prediction errors of the training set and validation set, and a TCN error prediction model is established. The error prediction value is used as compensation to correct the photovoltaic output prediction value, and the final photovoltaic output prediction value is obtained. Finally, based on the measured photovoltaic output data of a certain region in China, the effectiveness and advancement of the proposed method are demonstrated through the ablation and comparative experiments. Full article

Foam sound-absorbing materials develop a fine cellular structure during manufacturing, resulting in variations in porosity, cell size, and the proportion of naturally occurring thin membranes that obstruct skeletal openings. This membrane proportion significantly affects sound absorption. In this study, we utilized cross-sectional images obtained from a submicron resolution computer tomography (CT) scanner (nano-CT) that can capture membrane structures to theoretically assess the sound absorption of foam materials with membranes. We processed these cross-sectional images using techniques, including binarization, to extract the contours of the foam skeletons and the cross-sectional areas of the voids. By modeling the foam’s cross-section as the clearance between two planes, we were able to determine the propagation constant and characteristic impedance within this clearance. The effective density was adjusted based on measured tortuosity. The normal-incidence sound absorption coefficient (SAC), derived from the transfer matrix method, was then compared with experimental values obtained from a two-microphone impedance tube. Image processing techniques helped extract the skeleton cross-section and reduce residual noise, thereby minimizing the effect of variations in the binarization threshold on theoretical values. The accuracy of the theoretical model was enhanced by incorporating a correction factor for the skeleton surface area. Full article

Frequency-modulated continuous-wave (FMCW) LiDAR systems are extensively utilized in industrial metrology, autonomous navigation, and geospatial sensing due to their high precision and resilience to interference. However, the intrinsic nonlinear dynamics of laser systems introduce significant distortion, adversely affecting measurement accuracy. Although conventional iterative pre-distortion correction methods can effectively mitigate nonlinearities, their long-term reliability is compromised by factors such as temperature-induced drift and component aging, necessitating periodic recalibration. In light of recent advances in artificial intelligence, deep reinforcement learning (DRL) has emerged as a promising approach to adaptive nonlinear compensation. By continuously interacting with the environment, DRL agents can dynamically modify correction strategies to accommodate evolving system behaviors. Nonetheless, existing DRL-based methods often exhibit limited adaptability in rapidly changing nonlinear contexts and are constrained by inefficient uniform experience replay mechanisms that fail to emphasize critical learning samples. To address these limitations, this study proposes an enhanced Soft Actor-Critic (SAC) algorithm incorporating a hybrid prioritized experience replay framework. The prioritization mechanism integrates modulation frequency (MF) error and temporal difference (TD) error, enabling the algorithm to dynamically reconcile short-term nonlinear perturbations with long-term optimization goals. Furthermore, a time-varying delayed experience (TDE) injection strategy is introduced, which adaptively modulates data storage intervals based on the rate of change in modulation frequency error, thereby improving data relevance, enhancing sample diversity, and increasing training efficiency. Experimental validation demonstrates that the proposed method achieves superior convergence speed and stability in nonlinear correction tasks for FMCW LiDAR systems. The residual nonlinearity of the upward and downward frequency sweeps was reduced to $1.869\times {10}^{-5}$ and $1.9411\times {10}^{-5}$, respectively, with a spatial resolution of 0.0203m. These results underscore the effectiveness of the proposed approach in advancing intelligent calibration methodologies for LiDAR systems and highlight its potential for broad application in high-precision measurement domains. Full article

This paper presents a hybrid reinforcement learning framework for trajectory tracking control of a 5-degree-of-freedom (DOF) Mitsubishi RV-2AJ robotic arm by integrating model-free deep reinforcement learning (DRL) algorithms with classical control strategies. A novel hybrid PID + TD3 agent is proposed, combining a Proportional–Integral–Derivative (PID) controller with the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, and is compared against standalone TD3 and PID controllers. In this architecture, the PID controller provides baseline stability and deterministic disturbance rejection, while the TD3 agent learns residual corrections to enhance tracking accuracy, robustness, and control smoothness. The robotic system is modeled in MATLAB/Simulink with Simscape Multibody, and the agents are trained using a reward function inspired by artificial potential fields, promoting energy-efficient and precise motion. Extensive simulations are performed under internal disturbances (e.g., joint friction variations, payload changes) and external disturbances (e.g., unexpected forces, environmental interactions). Results demonstrate that the hybrid PID + TD3 approach outperforms both standalone TD3 and PID controllers in convergence speed, tracking precision, and disturbance rejection. This study highlights the effectiveness of combining reinforcement learning with classical control for intelligent, robust, and resilient robotic manipulation in uncertain environments. Full article

Distribution-level long-term load forecasting with hourly resolution is essential for modern power systems operation, yet it remains challenging due to complex temporal patterns and error accumulation over extended horizons. This study proposes a Multi-Resolution Residual LSTNet framework integrating Discrete Wavelet Transform (DWT), Long Short-Term Memory Networks (LSTNet), and Normalized Linear (NLinear) models for accurate one-year ahead hourly load forecasting. The methodology decomposes load time series into daily, weekly, and monthly components using multi-resolution DWT, applies direct forecasting with LSTNet to capture short-term and long-term dependencies, performs residual correction using NLinear models, and integrates predictions through dynamic weighting mechanisms. Validation using five years of Korean distribution feeder data (2015–2019) demonstrates significant performance improvements over benchmark methods including Autoformer, LSTM, and NLinear, achieving Mean Absolute Error of 0.5771, Mean Absolute Percentage Error of 17.29%, and Huber Loss of 0.2567. The approach effectively mitigates error accumulation common in long-term forecasting while maintaining hourly resolution, providing practical value for demand response, distributed resource control, and infrastructure planning without requiring external variables. Full article

Large-field-of-view (FOV) and high-resolution imaging have always been the goals pursued by imaging technology. A scale-adaptive high-resolution imaging architecture is established using a rotating-prism-embedded variable-boresight camera. By planning to prism motion, the multi-view images with rich information are combined to form a large-scale FOV image. The boresight is guided towards the region of interest (ROI) in the combined FOV to reconstruct super-resolution (SR) images with the desired information. A novel distortion correction method is proposed using virtual symmetrical prisms with rotation angles that are complementary. Based on light reverse tracing, the dispersion induced by monochromatic lights with different refractive indices can be eliminated by accurate pixel-level position compensation. For resolution enhancement, we provide a new scheme for SR imaging consisting of the residual removal network and information enhancement network by multi-view image fusion. The experiments show that the proposed architecture can achieve both large-FOV scene imaging for situational awareness and SR ROI display to acquire details, effectively perform distortion and dispersion correction, and alleviate the occlusion to a certain extent. It also provides higher image clarity compared to the traditional SR methods and overcomes the problem of balancing large-scale imaging and high-resolution imaging. Full article

Background/Objectives: Early-onset scoliosis (EOS) is often treated with growing rods, which use distraction-based correction to control deformity while allowing spinal growth. Although effective in the coronal plane, this technique may adversely affect sagittal alignment, particularly thoracic kyphosis and lumbar lordosis. Whether final fusion surgery is necessary after the growing rod treatment remains controversial. This study compared radiographic outcomes, including coronal and sagittal parameters, between patients with and without final fusion to clarify the value of final fusion. Methods: We retrospectively reviewed 19 EOS patients treated with growing rods between 2015 and 2019. Patients undergoing posterior spinal fusion after lengthening were classified as the final fusion group (n = 9), while those with more than 12 months of follow-up without fusion formed the graduated group (n = 10). Demographics, surgical variables, and radiographic parameters (Cobb angle, correction rate, coronal balance, clavicular angle, thoracic kyphosis, lumbar lordosis, sagittal vertical axis) were compared. Results: Baseline characteristics were similar. At final follow-up, the final fusion group had significantly better outcomes in Cobb angle (24.2° vs. 34.9°, p = 0.002), correction rate (66.6% vs. 40.1%, p = 0.001), and coronal balance (−1.5 mm vs. 19.7 mm, p = 0.004). Sagittal alignment did not differ significantly, but preservation of thoracic kyphosis tended to favor the fusion group. Conclusions: Final fusion surgery after growing rod treatment achieved superior coronal correction and balance compared with observation alone. Although sagittal alignment was not statistically different, a trend toward better thoracic kyphosis preservation was observed. Final fusion should be considered for larger residual curves or coronal imbalance, while observation may suffice in well-corrected cases. Full article

Background and Objectives: Iron deficiency anemia (IDA) is the most common cause of anemia in pregnant women and can adversely affect both maternal and fetal health. This study aimed to compare pregnancy outcomes between women with and without IDA in Northern Thailand, a region with a high prevalence of anemia. Methods: A retrospective cohort study was conducted on all singleton pregnancies attending antenatal care (ANC) and/or delivering at Maharaj Nakorn Chiang Mai Hospital between 2003 and 2024. The study group consisted of women diagnosed with IDA in the first half of pregnancy, while the control group comprised women with low-risk pregnancies during the same study period. Results: Of the 38,979 pregnancies, after applying exclusion criteria, 634 pregnancies (2.2%) with laboratory-confirmed IDA and 28,132 controls remained available for analysis. Women with IDA had significantly higher parity, lower socioeconomic status, and lower hemoglobin levels throughout pregnancy. Multivariate regression analysis revealed that IDA was significantly associated with increased risks of preterm birth (adjusted odds ratio; aOR 1.04; 95% CI: 1.01–1.07), fetal growth restriction (FGR) (aOR 1.02; 95% CI: 1.00–1.04), and low birth weight (aOR 1.05; 95% CI: 1.03–1.08). Conclusions: IDA, even with treatment, may still slightly increase the risk of adverse pregnancy outcomes, particularly preterm birth, fetal growth restriction, and low birth weight. The residual risk likely reflects incomplete correction of anemia. Optimizing management requires strict compliance, judicious use of parenteral iron, and attention to coexisting nutritional deficiencies, underscoring the need for closer monitoring and improved care strategies. Full article

Quantitative susceptibility mapping (QSM) is a powerful magnetic resonance imaging (MRI) technique for assessing tissue composition in the human body. For imaging short-T2 tissues in the musculoskeletal (MSK) system, ultrashort echo time (UTE) imaging plays a key role. However, UTE-based QSM (UTE-QSM) often involves repeated acquisitions, making it vulnerable to inter-scan motion. In this study, we investigate the effects of motion on UTE-QSM and introduce strategies to reduce motion-induced artifacts. Eight healthy male volunteers underwent UTE-QSM imaging of the knee joint, while an additional seven participated in imaging of the ankle joint. UTE-QSM was conducted using multiple echo acquisitions, including both UTE and gradient-recalled echoes, and processed using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) and morphology-enabled dipole inversion (MEDI) algorithms. To assess the impact of motion, datasets were reconstructed both with and without motion correction. Furthermore, we evaluated a two-step UTE-QSM approach that incorporates tissue boundary information. This method applies edge detection, excludes pixels near detected edges, and performs a two-step QSM reconstruction to reduce motion-induced streaking artifacts. In participants exhibiting substantial inter-scan motion, prominent streaking artifacts were evident. Applying motion registration markedly reduced these artifacts in both knee and ankle UTE-QSM. Additionally, the two-step UTE-QSM approach, which integrates tissue boundary information, further enhanced image quality by mitigating residual streaking artifacts. These results indicate that motion-induced errors near tissue boundaries play a key role in generating streaking artifacts in UTE-QSM. Inter-scan motion poses a fundamental challenge in UTE-QSM due to the need for multiple acquisitions. However, applying motion registration along with a two-step QSM approach that excludes tissue boundaries can effectively suppress motion-induced streaking artifacts, thereby improving the accuracy of musculoskeletal tissue characterization. Full article