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ExoClock Project. IV. A Homogeneous Catalog of 620 Updated Exoplanet Ephemerides
Get PDFThe ExoClock project is an open platform aiming to monitor exoplanets by integrating observations from space- and ground-based telescopes. This study presents an updated catalog of 620 exoplanet ephemerides, integrating 30,000 measurements from ground-based telescopes (the ExoClock network), literature, and space telescopes (Kepler, K2 and TESS). The updated catalog includes 277 planets from TESS which require special observing strategies due to their shallow transits or bright host stars. This study demonstrates that data from larger telescopes, and the employment of new methodologies such as synchronous observations with small telescopes, are capable of monitoring special cases of planets. The new ephemerides show that 45% of the planets required an update while the results show an improvement of 1 order of magnitude in prediction uncertainty. The collective analysis also enabled the identification of new planets showing transit-timing variations, highlighting the importance of extensive observing coverage. Developed in the context of the ESA’s Ariel space mission, with the goal of delivering a catalog with reliable ephemerides to increase the mission efficiency, ExoClock’s scope and service have grown well beyond the remit of Ariel. The ExoClock project has been operating in the framework of open science, and all tools and products are accessible to everyone within academia and beyond, to support efficient scheduling of future exoplanet observations, especially from larger telescopes where the pressure for time allocation efficiency is higher (Ariel, JWST, VLT, ELT, Subaru etc.). The inclusion of diverse audiences in the process and the collaborative mode not only foster democratization of science but also enhance the quality of the results
Systematic review of the Lancet Commission on Global Surgery indicators with quality assessment of modelled estimates
Get PDFBACKGROUND: The Lancet Commission on Global Surgery (LCoGS) defined six indicators with 2030 targets to track national surgical system performance. The aim of this systematic review was to evaluate national reporting and attainment of benchmarks for each indicator and to assess the quality of modelling studies used to fill data gaps.METHODS: Seven bibliographic databases (1 April 2015-24 July 2024) and government domains of 48 countries committed to National Surgical, Obstetric, and Anaesthesia Plans were searched. Records providing national estimates of any LCoGS indicator were eligible. The primary outcome was the proportion of World Bank-classified countries meeting indicator benchmarks and the secondary outcome was the quality of modelled national estimates. This systematic review was prospectively registered in PROSPERO, the international prospective register of systematic reviews (CRD420250650890).RESULTS: Of 4245 records retrieved, 44 studies were included (35 research articles and 9 policy documents). Among 217 World Bank-classified countries, access to timely essential surgery (indicator 1) was reported for 94 countries (39% meeting benchmark), specialist surgical workforce density (indicator 2) was reported for 167 countries (50.3% meeting benchmark), surgical volume (indicator 3) was reported for 124 countries (31.5% meeting benchmark), perioperative mortality (indicator 4) was reported for 74 countries (no benchmark was set at country level), and financial risk protection indicators (indicators 5 and 6) were reported for five countries, with none meeting either benchmark. Across indicators, high-income countries were more likely to meet benchmarks. Most modelled studies lacked transparency in data sources, statistical methods, or model validation.CONCLUSION: Reporting of LCoGS indicators remains sparse and uneven, particularly in low- and middle-income countries. Without standardized, routine measurement and minimum quality standards for modelled estimates, progress towards 2030 cannot be credibly tracked. Integrating surgical metrics into national health information systems should be a policy priority.</p
Potential for scientific drilling of sediment drifts adjacent to Denmark Strait oceanic gateway
Get PDFDenmark Strait between Greenland and Iceland is an important gateway within the Atlantic Meridional Overturning Circulation system. Flow of bottom water through Denmark Strait, called Denmark Strait Overflow Water (DSOW), carries over half of deep Arctic-to-Atlantic flow at present but cannot be reconstructed directly from existing or proposed sediment cores for times prior to 240 thousand years. Here we assess whether sedimentary contourite drifts in Denmark Strait might be used to reconstruct a complete DSOW record, which exceeds 10 million years. Within the Blosseville Basin in the north of Denmark Strait lies a previously undescribed contourite drift that we name the Freydis Drift, of likely early Miocene-Recent age and up to about 1350 m thick. On the southern flank of the Greenland-Iceland Ridge and in the northern Irminger Basin lies the Snorri Drift, which is thinner and has more complex structure than Freydis Drift. By drilling Freydis Drift, there is good potential for recovering a continuous early Miocene-Recent sedimentary succession, with mean solid sedimentation rate comparable with the Eirík Drift to the south, that would show when Denmark Strait opened and the history of fluctuations in DSOW thereafter. A seismic site survey is required to fully realize this goal
Unmanned Aerial Vehicle (UAV)-Based, K-Band Interferometric Synthetic Aperture Radar (SAR)
No full textThis article proposes the study and development of interferometric synthetic aperture radar (InSAR) from compact, high-frequency radar sensors onboard commercial uncrewed aerial vehicles (UAVs), (often referred to as “drones”) to create precision digital elevation models (DEMs). The potential of such InSAR systems, due to the higher operating frequency and target proximity, is quantified, but it is also shown how the same features, combined with the instability of UAV platforms, lead to motion errors that either deteriorate or altogether deny capability. This article thus quantifies acceptable motion error limits and shows how complex autofocus can restore height estimation performance, through analytical modeling that is verified by simulation and validated through outdoor experiments with a 24 GHz UAV-based demonstrator. To our knowledge, this is the first demonstration of a UAV-based InSAR system in this high-frequency band
Dc-link voltage regulation in all-DC offshore wind farms
No full textOffshore wind farms located far from the shore currently use AC-based collection systems with bulky line frequency transformers. Due to limited space, this approach is challenging and expensive. As an alternative, Medium Voltage DC (MVDC) collector systems have been proposed as a cost-effective solution for integrating offshore wind farms. One crucial area of research for these systems is DC-link voltage regulation to ensure safe, reliable, and stable operation of the entire system. In this study, an adaptive voltage regulator is designed to stabilize the DC-link voltage at its nominal value against disturbances. Additionally, current observers are suggested to eliminate the need for current sensors, increasing reliability and reducing implementation costs. To validate the control method and test the observer’s performance, simulations and Hardware-in-theLoop tests (HIL) were conducted on a 10-MW wind turbine
Exposure to dynamic social norm messages increases plant-based food choice:An online and field-based experiment
Get PDFQuick-service restaurants (QSRs) are increasing the availability of plant-based options. However, there is a gap between the availability of these items and consumer demand. One strategy to promote plant-based food consumption is social norm messages which provide information about others' behaviour. This remains to be fully examined in a QSR setting, hence, across two experimental studies, we examined the effectiveness of social norm messages on increasing plant-based food choices. The effectiveness of social norm messages may vary by individual characteristics; thus, collectivism was examined as a potential moderator. Study 1 comprised an online experimental study with participants from eight countries (N = 892). Participants were asked to select a plant- or meat-based meal following exposure to either a descriptive, dynamic, or injunctive social norm message, or a no-norm control message. Questionnaire data was used to examine collectivism as a moderator. The dynamic and injunctive norm messages, but not the descriptive norm message, increased plant-based food choices in Study 1. Collectivism did not significantly moderate the relationship between plant-based food choices and social norm messages. A field study (Study 2) was also conducted. Participants were exposed to a social norm message (descriptive or dynamic) or standard-control message at order terminals in real-world QSRs. Only dynamic norms were found to increase plant-based food choices. Overall, these findings suggest that implementing dynamic social norms into real-world QSRs could be an effective strategy for increasing plant-based food consumption to improve human and planetary health. Further research examining the long-term effects on food choice is needed.</p
Disassembly from scratch:An object-centric approach for robotic autonomous disassembly with zero contact/interference information
Get PDFDisassembly is important to circular economy, yet it remains challenging to be robotised due to the inherent uncertainty of end-of-life (EoL) products (e.g., corrosion, rust and missing part). A key challenge in robotising disassembly is that the interference information (e.g., spatial relations of components and assembly methods) is usually unavailable or inaccurate. To address this core problem, this paper presents an object-centric disassembly (OCD) framework, allowing robots to adapt dynamically to varying conditions without requiring prior knowledge of component contacts or interferences. In this framework, an OCD model is constructed in which individual disassembly tasks and their associated conditions are represented as modular units that are continuously refined through autonomous exploration. The performance of the framework is evaluated using a robotic platform integrating intelligent perception, planning, and execution modules for autonomous disassembly under uncertain environments. Experimental evaluations provide evidence that the proposed method enhances the flexibility and adaptability of robotic disassembly. Our approach and this new capability allow disassembly robots to handle real-world uncertainties effectively, eliminating the need for pre-defined interference information.</p
A semi-automated modelling pipeline to predict the mechanics of multiple sclerosis lesion afflicted brains from magnetic resonance images
Get PDFMultiple Sclerosis (MS) is a demyelinating and degenerative autoimmune disease that affects the brain and spinal cord. Its causes, mechanisms, and outcomes are yet to be fully understood. One relatively unexplored area is the understanding of changes in brain biomechanics during MS disease progression, despite the likelihood that demyelination significantly alters the overall mechanical structure of the brain. Such changes have the potential to hinder the propagation of nerve signals essential for cognition and motor function. The aim of this work was to create a computational model to explore the mechanics of brains with MS, separating the brain into grey matter, white matter and lesions. Changes were observed when the surface of the brain was subjected to a ramped uniform pressure tangential to the faces of a finite element model, generated from patient- and time-specific MRI scans. The resulting displacements, stresses and strains can all be gauged using the model. The key benefit of this study was to observe the impact of changes in tissue morphology in real brains using non-invasive methods. Ensuring the accuracy of the axiomatic input tissue parameters of the models was critically important, as exploring the range of values from literature, adjusted by their error margins, revealed a significant variability in outcomes, especially in the case of volumetric strain of lesions. The model has the potential to track changes in mechanical tissue properties assuming the availability of a longitudinal dataset, and if further developed, has the potential to serve as the foundation for creating a digital twin. This could enhance medical practice and provide a non-invasive approach to advancing the understanding of MS and its progression on a patient-specific basis.</p
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