Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry

Reconstructing the topography of shallow underwater environments using Structure-from-Motion—Multi View Stereo (SfM-MVS) techniques applied to aerial imagery from Unmanned Aerial Vehicles (UAVs) is challenging, as it involves nonlinear distortions caused by water refraction. This study presents an experiment with aerial photographs collected with a consumer-grade UAV on the shallow-water reef of Fuvahmulah, the Maldives. Under conditions of rising tide, we surveyed the same portion of the reef in ten successive flights. For each flight, we used SfM-MVS to reconstruct the Digital Elevation Model (DEM) of the reef and used the flight at low tide (where the reef is almost entirely dry) to compare the performance of DEM reconstruction under increasing water levels. Our results show that differences with the reference DEM increase with increasing depth, but are substantially larger if no underwater ground control points are taken into account in the processing. Correcting our imagery with algorithms that account for refraction did not improve the overall accuracy of reconstruction. We conclude that reconstructing shallow-water reefs (less than 1 m depth) with consumer-grade UAVs and SfM-MVS is possible, but its precision is limited and strongly correlated with water depth. In our case, the best results are achieved when ground control points were placed underwater and no refraction correction is used

Separase prevents genomic instability by controlling replication fork speed

Proper chromosome segregation is crucial for preserving genomic integrity, and errors in this process cause chromosome mis-segregation, which may contribute to cancer development. Sister chromatid separation is triggered by Separase, an evolutionary conserved protease that cleaves the cohesin complex, allowing the dissolution of sister chromatid cohesion. Here we provide evidence that Separase participates in genomic stability maintenance by controlling replication fork speed. We found that Separase interacted with the replication licensing factors MCM2-7, and genome-wide data showed that Separase co-localized with MCM complex and cohesin. Unexpectedly, the depletion of Separase increased the fork velocity about 1.5-fold and caused a strong acetylation of cohesin's SMC3 subunit and altered checkpoint response. Notably, Separase silencing triggered genomic instability in both HeLa and human primary fibroblast cells. Our results show a novel mechanism for fork progression mediated by Separase and thus the basis for genomic instability associated with tumorigenesis

Separase prevents genomic instability by controlling replication fork speed

Proper chromosome segregation is crucial for preserving genomic integrity, and errors in this process cause chromosome mis-segregation, which may contribute to cancer development. Sister chromatid separation is triggered by Separase, an evolutionary conserved protease that cleaves the cohesin complex, allowing the dissolution of sister chromatid cohesion. Here we provide evidence that Separase participates in genomic stability maintenance by controlling replication fork speed. We found that Separase interacted with the replication licensing factors MCM2-7, and genome-wide data showed that Separase co-localized with MCM complex and cohesin. Unexpectedly, the depletion of Separase increased the fork velocity about 1.5-fold and caused a strong acetylation of cohesin's SMC3 subunit and altered checkpoint response. Notably, Separase silencing triggered genomic instability in both HeLa and human primary fibroblast cells. Our results show a novel mechanism for fork progression mediated by Separase and thus the basis for genomic instability associated with tumorigenesis

DOPAL derived alpha-synuclein oligomers impair synaptic vesicles physiological function

Parkinson's disease is a neurodegenerative disorder characterized by the death of dopaminergic neurons and by accumulation of alpha-synuclein (aS) aggregates in the surviving neurons. The dopamine catabolite 3,4-dihydroxyphenylacetaldehyde (DOPAL) is a highly reactive and toxic molecule that leads to aS oligomerization by covalent modifications to lysine residues. Here we show that DOPAL-induced aS oligomer formation in neurons is associated with damage of synaptic vesicles, and with alterations in the synaptic vesicles pools. To investigate the molecular mechanism that leads to synaptic impairment, we first aimed to characterize the biochemical and biophysical properties of the aS-DOPAL oligomers; heterogeneous ensembles of macromolecules able to permeabilise cholesterol-containing lipid membranes. aS-DOPAL oligomers can induce dopamine leak in an in vitro model of synaptic vesicles and in cellular models. The dopamine released, after conversion to DOPAL in the cytoplasm, could trigger a noxious cycle that further fuels the formation of aS-DOPAL oligomers, inducing neurodegeneration

Towards Exoscope Automation in Neurosurgery: A Markerless Visual-Servoing Approach

Exoscopes are a promising tool for neurosurgeons, offering improved visualisation and ergonomics compared with traditional surgical microscopes. They consist of an external scope that projects the surgical field onto a 2D or 3D monitor, providing a wider field of view and better access to the surgical site. Despite the advantages, exoscopes present some limitations, such as the need for manual or foot joystick repositioning, which can disrupt the flow of the procedure and increase the risk of user error. In this study, a markerless visual-servoing approach for autonomous exoscope control is proposed to address these limitations and enhance the ergonomics and reduce the physical and cognitive load compared with traditional joystick control. The system uses visual information from the operating field to control the exoscope, eliminating the need for markers or additional tracking devices. The proposed approach was validated using a 7-DOF robotic manipulator with a stereo camera in an eyein-hand configuration. Results showed that the system achieved 89% accuracy in detecting the target and tracking its movement with a tracking error ranging from 0.50 +/- 0.17 cm for lowspeed movements to 1.38 +/- 0.73 cm for high-speed movements. The proposed system also demonstrated improved efficiency, with a shorter execution time of 72.07 +/- 19.36 s compared with 106.52 +/- 18.50 s for the foot-joystick control. Additionally, the time out of the FoV was significantly higher in the joystick control mode and the frequency of appearance of the instrument in the centre of the image was higher when using the proposed system. The NASA TLX results indicated lower physical and cognitive load compared with the joystick control-based modality

Extreme Rainfall in the Mediterranean: What Can We Learn from Observations?

Abstract Flash floods induced by extreme rainfall events represent one of the most life-threatening phenomena in the Mediterranean. While their catastrophic ground effects are well documented by postevent surveys, the extreme rainfall events that generate them are still difficult to observe properly. Being able to collect observations of such events will help scientists to better understand and model these phenomena. The recent flash floods that hit the Liguria region (Italy) between the end of October and beginning of November 2011 give us the opportunity to use the measurements available from a large number of sensors, both ground based and spaceborne, to characterize these events. In this paper, the authors analyze the role of the key ingredients (e.g., unstable air masses, moist low-level jets, steep orography, and a slow-evolving synoptic pattern) for severe rainfall processes over complex orography. For the two Ligurian events, this role has been analyzed through the available observations (e.g., Meteosat Second Generation, Moderate Resolution Imaging Spectroradiometer, the Italian Radar Network mosaic, and the Italian rain gauge network observations). The authors then address the possible role of sea–atmosphere interactions and propose a characterization of these events in terms of their predictability

Very high resolution mapping of coral reef state using airborne bathymetric LiDAR surface-intensity and drone imagery

International audienceVery high resolution (VHR) airborne data enable detection and physical measurements of individual coral reef colonies. The bathymetric LiDAR system, as an active remote sensing technique, accurately computes the coral reef ecosystem’s surface and reflectance using a single green wavelength at the decimetre scale over 1-to-100 km2 areas. A passive multispectral camera mounted on an airborne drone can build a blue-green-red (BGR) orthorectified mosaic at the centimetre scale over 0.01-to-0.1 km2 areas. A combination of these technologies is used for the first time here to map coral reef ecological state at the submeter scale. Airborne drone BGR values (0.03 m pixel size) serve to calibrate airborne bathymetric LiDAR surface and intensity data (0.5 m pixel size). A classification of five ecological states is then mapped through an artificial neural network (ANN). The classification was developed over a small area (0.01 km2) in the lagoon of Moorea Island (French Polynesia) at VHR (0.5 m pixel size) and then extended to the whole lagoon (46.83 km2). The ANN was first calibrated with 275 samples to determine the class of coral state through LiDAR-based predictors; then, the classification was validated through 135 samples, reaching a satisfactory performance (overall accuracy = 0.75)

The high energy Universe at ultra-high resolution: the power and promise of X-ray interferometry

We propose the development of X-ray interferometry (XRI), to reveal the Universe at high energies with ultra-high spatial resolution. With baselines which can be accommodated on a single spacecraft, XRI can reach 100 μ as resolution at 10 Å (1.2 keV) and 20 μ as at 2 Å (6 keV), enabling imaging and imaging-spectroscopy of (for example) X-ray coronae of nearby accreting supermassive black holes (SMBH) and the SMBH ‘shadow’; SMBH accretion flows and outflows; X-ray binary winds and orbits; stellar coronae within ∼100 pc and many exoplanets which transit across them. For sufficiently luminous sources XRI will resolve sub-pc scales across the entire observable Universe, revealing accreting binary SMBHs and enabling trigonometric measurements of the Hubble constant with X-ray light echoes from quasars or explosive transients. A multi-spacecraft ‘constellation’ interferometer would resolve well below 1 μ as, enabling SMBH event horizons to be resolved in many active galaxies and the detailed study of the effects of strong field gravity on the dynamics and emission from accreting gas close to the black hole

Determinants of long COVID among adults hospitalized for SARS-CoV-2 infection: A prospective cohort study

Rationale: Factors associated with long-term sequelae emerging after the acute phase of COVID-19 (so called "long COVID") are unclear. Here, we aimed to identify risk factors for the development of COVID-19 sequelae in a prospective cohort of subjects hospitalized for SARS-CoV-2 infection and followed up one year after discharge. Methods: A total of 324 subjects underwent a comprehensive and multidisciplinary evaluation one year after hospital discharge for COVID-19. A subgroup of 247/324 who consented to donate a blood sample were tested for a panel of circulating cytokines. Results: In 122 patients (37.8%) there was evidence of at least one persisting physical symptom. After correcting for comorbidities and COVID-19 severity, the risk of developing long COVID was lower in the 109 subjects admitted to the hospital in the third wave of the pandemic than in the 215 admitted during the first wave, (OR 0.69, 95%CI 0.51-0.93, p=0.01). Univariable analysis revealed female sex, diffusing capacity of the lungs for carbon monoxide (DLCO) value, body mass index, anxiety and depressive symptoms to be positively associated with COVID-19 sequelae at 1 year. Following logistic regression analysis, DLCO was the only independent predictor of residual symptoms (OR 0.98 CI 95% (0.96-0.99), p=0.01). In the subgroup of subjects with normal DLCO (> 80%), for whom residual lung damage was an unlikely explanation for long COVID, the presence of anxiety and depressive symptoms was significantly associated to persistent symptoms, together with increased levels of a set of pro-inflammatory cytokines: interferon-gamma, tumor necrosis factor-alpha, interleukin (IL)-2, IL-12, IL-1β, IL-17. In logistic regression analysis, depressive symptoms (p=0.02, OR 4.57 [1.21-17.21]) and IL-12 levels (p=0.03, OR 1.06 [1.00-1.11]) 1-year after hospital discharge were independently associated with persistence of symptoms. Conclusions: Long COVID appears mainly related to respiratory sequelae, prevalently observed during the first pandemic wave. Among patients with little or no residual lung damage, a cytokine pattern consistent with systemic inflammation is in place