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Multichannel Photoluminescence of Graphene Quantum Dots Across Femtosecond to Cryogenic Timescales
Full text linkGraphene quantum dots (GQDs) exhibit complex photoluminescence (PL) originating from intrinsic sp2 carbon domains, surface functional groups, and structural defects. Yet the spectral overlap among these emissive channels hinders clear identification of their recombination pathways. Here, we investigate multichannel PL dynamics of commercial GQDs using time‐resolved and cryogenic PL spectroscopy. PL spectra reveal three distinct peaks: Peak I (443 nm) from π–π* transitions, Peak II (520 nm) from surface‐dominated contribution functional states, and Peak III (583 nm) from pyrrolic N‐related defects. Time‐correlated single‐photon counting detects only a 460 nm emission linked to graphitic N traps, indicating that Peaks I–III decay faster than the nanosecond window. Ultrafast optical Kerr‐gate measurements further resolve distinct lifetimes for hydroxyl (<5 ps), carboxyl (5–10 ps), amine (20–30 ps), and carbonyl (40–80 ps) groups. The transient evolution displays cascade relaxation from deep to shallow traps, evidenced by a progressive blue‐shift of Peak II. Cryogenic PL shows stable emission of Peak I, whereas Peak III red‐shifts and broadens with temperature, revealing strong electron–phonon coupling and deep‐level trapping. These results clarify the multichannel emission mechanisms of GQDs and provide design principles for tuning their optical properties
Flight rules for clinical AI: lessons from aviation for human-AI collaboration in medicine
Full text linkThe parallels between medicine and aviation are well-recognised. The aviation industry’s early experience with automation improved safety and efficiency, but simultaneously introduced new vulnerabilities and occasionally created misplaced trust in complex systems. Aviation has developed a robust safety framework in response to these costly lessons. In this Perspective, which draws from the experiences of clinicians and aviation experts, we argue that it is now time for the medical community to consider how we can learn from these lessons as artificial intelligence (AI) becomes increasingly integrated into clinical care. We propose that this requires a shift in perspective from AI as “autopilot” to collaboration with a “digital copilot”, as well as considerations of practicalities such as scenario-based training, clinician benchmarking, and minimum unaided practice, with the ultimate aim of optimising human-AI collaboration to improve patient care
ISDE guidelines on the management of cT2N0 esophageal cancer
Full text linkEsophageal cancer incidence is rising globally, with at least 500,000 new cases diagnosed annually. Management options for non-metastatic disease include primary resection, neoadjuvant or perioperative therapies, or definitive non-surgical treatment, with the choice being guided by tumor staging, histology, patient fitness, and available resources. However, even with the use of advanced diagnostic modalities, preoperative clinical staging is challenging with respect to accuracy of both tumor and nodal assessment. Early-stage esophageal cancer may be managed with local therapies, such as endoscopic mucosal resection or submucosal dissection, while for more advanced tumors managed with curative intent neoadjuvant oncologic therapy is commonly recommended. However, between these two groups lies an infrequent but important subgroup of patients, clinically staged cT2N0M0 esophageal cancer. Guidelines such as the NIH’s National Cancer Institute recommends either surgery alone or neoadjuvant therapy followed by surgery for AJCC Stage I cancers, and add the option of definitive chemoradiation for Stage II disease. With cT2N0 disease straddling both AJCC classifications, management guidance is lacking. This guideline will provide an evidence-based recommendation from the International Society For Disease Of The Esophagus on the management of cT2N0 esophageal cancer, of all types. The recommendations are intended to support surgeons, oncologists, and patients in decisions about the best practice preoperative oncologic management of cT2N0M0 esophageal cancer. A Working Group within the International Society for Diseases of the Esophagus (ISDE) Guidelines Committee performed a systematic review of the literature. Results of the systematic review were presented to a panel of experts and these results informed the panel discussion about the guideline. This panel used Grading of Recommendations Assessment, Development, and Evaluation approach to deliberate and formulate recommendations. The panel agreed on a conditional recommendation for the use of neoadjuvant therapy followed by surgery over primary surgical resection (PSR) for adult patients with cT2N0M0 esophageal cancer. Preoperative clinical staging of esophageal cancer is uncertain, with deficiencies in all diagnostic modalities. However, when all modern staging techniques are utilized, the ISDE recommends neoadjuvant therapy followed by surgical resection as the favored treatment of cT2N0 esophageal cancer. Certain patient groups may still be offered PSR, particularly those unable to tolerate neoadjuvant therapies, or those patients with very low risk of lymph node metastasis as suggested by histological features, small tumor size, and other features
Enforcing energy conservation in ML-based approximations of nonlinear four-wave interactions
No full textAccurate and efficient approximation of nonlinear four-wave interactions remains one of the longstanding challenge in spectral wave modeling, as exact calculations are extremely computationally too demanding for practical models. Consequently, most operational wave models employ simplified parameterizations such as the Discrete Interaction Approximation (DIA), for fast computational speed despite known deficiencies. Recent advances in machine learning offer a promising alternative, but standard neural networks do not inherently conserve fundamental physical quantities such as energy, wave action, and momentum, potentially leading to unphysical energy shifts and numerical instability during predictions with these physically inconsistent parameterizations. This study develops two energy-conserving machine learning approaches: a soft constraint that penalizes energy imbalance in the loss function and a hard constraint implemented as a custom network layer that enforces energy conservation within the network architecture. Both approaches substantially reduce energy imbalance compared with unconstrained model, with the hard-constrained approach achieving exact conservation, while also improving numerical stability and generalization to unseen sea states, providing a physically consistent framework for computing nonlinear four-wave interactions
Landscapes of the witches' sabbath: space, place, and fantasy in early modern Europe, 1500-1750
Full text linkAmidst the early modern European witch craze, fantasies of the witches’ sabbath spread across the continent, spurred by the terrors and anxieties of people across the social strata. Believed to be the gathering of diabolic witches who would worship the Devil, feast, dance, and engage in demonic orgies, the sabbath inverted early modern customs and rites to play a central role in witchcraft belief. While the belief in the sabbath may seem rooted in fantasy, those constructing the sabbath narratives needed to place their stories in a real setting to make them believable. This thesis explores the landscapes associated with the witches’ sabbath across early modern Europe, using these spaces and narratives to understand the relationship between people and landscape over time. Delving into the mentalités of common people and learned demonologists alike, this thesis explores the landscapes of the sabbath from Portugal to Poland to uncover how different cultural and geographic contexts moulded the sabbath belief to fit their local landscape.Using two specific case studies – Zug, Switzerland and the Pays de Labourd, France – and other examples from the European witch craze, this thesis argues that the sabbath narratives are indicative of local perceptions of landscape, reflecting personal and societal values, emotions, and anxieties tied to space. This thesis explores mountains, forests, cemeteries, and many more landscapes tied to the sabbath myth, analyzing each landscape using spatial historical methodologies and a boots-on-the-ground approach, walking through the world of early modern witchcraft belief. Moreover, through the examination of the legacies of the sabbath in the world of art, it investigates how the perception of landscape changed across time, and how early modern relationships with space have shifted and carried on into the modern world, long after the end of the witch craze
Diffusion-based inverse model of a distributed tactile sensor for object pose estimation
Full text linkTactile sensing provides a promising sensing modality for object pose estimation in manipulation settings where visual information is limited due to occlusion or environmental effects. However, efficiently leveraging tactile data for estimation remains a challenge due to partial observability, with single observations corresponding to multiple possible contact configurations. This limits conventional estimation approaches largely tailored to vision. We propose to address these challenges by learning an inverse tactile sensor model using denoising diffusion. The model is conditioned on tactile observations from a distributed tactile sensor and trained in simulation using a geometric sensor model based on signed distance fields. Contact constraints are enforced during inference through single-step projection using distance and gradient information from the signed distance field. For online pose estimation, we integrate the inverse model with a particle filter through a proposal scheme that combines generated hypotheses with particles from the prior belief. Our approach is validated in simulated and real-world planar pose estimation settings, without access to visual data or tight initial pose priors. We further evaluate robustness to unmodeled contact and sensor dynamics for pose tracking in a box-pushing scenario. Compared to local sampling baselines, the inverse sensor model improves sampling efficiency and estimation accuracy while preserving multimodal beliefs across objects with varying tactile discriminability
Technical skills simulation for postgraduate surgical training
Full text linkTechnical skills are a fundamental component of surgical training. Traditionally, these skills are learnt in an operating theatre under supervision. Access to surgical theatres have been unfavourably affected by several factors, including shift working, demand for service provision, consultant-led operating and working hour restrictions. Opportunities for surgical technical skills training further deteriorated during the COVID-19 pandemic.Simulation is an effective modality for learning technical skills outside of the operating theatre. Evidence, however, shows the inadequate and inconsistent implementation of simulation into surgical training with barriers such as limited faculty availability, resources, and time constraints for trainees. My research focussed on this gap by exploring how technical skill simulation can be implemented alongside conventional surgical training.In part I, I explored the evolution of surgical training and simulation, reviewing the evidence available for modalities that could develop technical skills. In part II, I identified the deficiencies in technical skill training and the lack of instruction for the use of simulation through a curriculum review and two systematic reviews. Additionally, I explored the barriers to implementing simulation through a scoping literature review. In part III, I used qualitative methodologies to understand general surgical and obstetrics and gynaecology trainees’ experiences when engaging with simulation as part of their routine training. Finally, in part IV, I discussed the broader implications of my findings for both training and further research and the limitations of the research.My thesis emphasises the importance of innovation in implementing simulation as an adjunct to conventional training for technical skills. I propose a pragmatic approach that enhances the training experience without unduly increasing the trainee or educator burden and aligns with national interests for training and healthcare workforce development
Geographic atrophy in age-related macular degeneration: phenotypic characterisation for clinical trial consideration
Full text linkGeographic atrophy (GA) is an advanced form of age-related macular degeneration (AMD) and a leading cause of central vision loss. Advances in multimodal imaging for GA have improved its phenotypic characterisation, enabling more precise assessment of disease. This is increasingly important for identifying features predictive of progression to inform prognosis and guide patient counselling, enable selection for clinical trials and for disease monitoring both in routine clinical practice and in a research setting. In addition, accurately determining foveal involvement is crucial for selection of patients suitable for emerging therapies. High-resolution imaging is also important to recognise and distinguish GA subtypes such as pachychoroid GA from conventional GA, given their genetic and phenotypic differences and possible variation in response to therapy. Imaging modalities include colour fundus photography, which is widely available and allows an initial assessment of GA lesions. Fundus autofluorescence imaging permits clear visualisation of GA borders and provides an accurate topographical map of GA pattern and extent, whereas near-infrared reflectance imaging may be superior for evaluation of foveal involvement. Optical coherence tomography (OCT) allows for measurement of the ellipsoid zone which may correlate to visual function and permits differentiation between biomarkers such as nascent GA, incomplete and complete retinal pigment epithelium and outer retinal atrophy (iRORA and cRORA respectively), and identification of pachychoroid GA. Each of these have important prognostic implications and enable accurate selection for clinical trials, monitoring progression and treatment response. Emerging approaches such as red excitation light and high-resolution OCT, may provide more accurate and reliable assessment of atrophic changes. Alongside these advances, artificial intelligence-based tools show great potential in automating GA detection, characterising of structural biomarkers, measuring progression rates and screening patients for clinical trials, increasingly reliability and reproducibility. A better understanding of the important role of multimodal imaging in the classification and assessment of GA, and detection of factors that affect progression will enable clinicians to advise, monitor and, where possible, appropriately treat this major cause of sight loss
Resistance training and subcortical vascular cognitive impairment: A 12‐month randomized trial
Full text linkINTRODUCTION: It is unknown whether progressive resistance training (PRT) improves cognitive function in adults with cerebral small vessel disease and mild cognitive impairment (i.e., subcortical vascular cognitive impairment [SVCI]). METHODS: We conducted a 12‐month randomized trial comparing PRT versus balance and tone exercises (BAT) on the Alzheimer's Disease Assessment Scale Cognitive Plus (ADAS‐Cog‐Plus). RESULTS: Ninety‐one participants were randomized (PRT = 45; BAT = 46); 76 completed the trial. Adherence was not different between groups (p = 0.18). At 12 months, PRT significantly improved ADAS‐Cog‐Plus scores (estimated mean difference: −0.18; 95% confidence interval [CI: −0.35, −0.01]; p = 0.04). Planned contrasts stratified by sex showed a significant PRT effect on ADAS‐Cog‐Plus scores for females (mean difference: −0.27; 95% CI: [−0.49, −0.05]; p = 0.02), but not for males. PRT also significantly reduced C‐reactive protein (estimated mean difference: −2.93; 95% CI: [−5.36, −0.49]; p = 0.02). No significant differences were observed for other secondary outcomes. DISCUSSION: PRT may have a small beneficial effect on cognitive function in SVCI. CLINICAL TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT02669394)