Deep learning for automated river-level monitoring through river camera images: an approach based on water segmentation and transfer learning

River level estimation is a critical task required for the understanding of flood events, and is often complicated by the scarcity of available data. Recent studies have proposed to take advantage of large networks of river camera images to estimate the river levels, but currently, the utility of this approach remains limited as it requires a large amount of manual intervention (ground topographic surveys and water image annotation). We develop an approach using an automated water semantic segmentation method to ease the process of river level estimation from river camera images. Our method is based on the application of a transfer learning methodology to deep semantic neural networks designed for water segmentation. Using datasets of image series extracted from four river cameras and manually annotated for the observation of a flood event on the Severn and Avon rivers, UK (21 November - 5 December 2012), we show that this algorithm is able to automate the annotation process with an accuracy greater than 91%. Then, we apply our approach to year-long image series from the same cameras observing the Severn and Avon (from 1 June 2019 to 31 May 2020) and compare the results with nearby river-gauge measurements. Given the high correlation (Pearson's Correlation Coefficient >0.94) between these results and the river-gauge measurements, it is clear that our approach to automation of the water segmentation on river camera images could allow for straightforward, inexpensive observation of flood events, especially at ungauged locations

Long path monitoring of tropospheric O3, NO2, H2CO and SO2

Concentrations of tropospheric O3, NO2, H2CO, and SO2 have been measured on the Campus of the 'Universite Libre de Bruxelles' on a routine basis since October 1990. The long path system consists of a source lamp, a first 30 cm f/8 Cassegrain type telescope which collimates the light onto a slightly parabolic mirror placed on the roof of a building situated 394 m away from the laboratory. The light is sent back into a second 30 cm Cassegrain telescope. This telescope has been modified so that the output beam is a 5 cm diameter parallel beam. This beam is then focused onto the entrance aperture of the BRUKER IFS120HR fourier transform spectrometer. The two telescopes are mounted on alignment devices and the external mirror is equipped with a driving system operated from the laboratory. The choice of the light source (either a 1000 W high pressure 'ozone free' xenon lamp or a 250 W tungsten filament) and of the detector (either a solar blind UV-diode or a silicon diode) depended on the spectral region studied. These regions lie respectively from 26,000 cm(exp -1) to 30,000 cm(exp -1) (260-380 nm) and from 14,000 cm(exp -1) to 30,000 cm(exp -1) (330-700 nm). The spectra have been recorded at the resolution of 16 cm(exp -1) and with a dispersion of 7.7 cm(exp -1). They have been measured during the forward and the backward movements of the mobile mirror, in double sided mode; each spectrum is an average of 2000 scans. The time required to record a spectrum is about 45 minutes. The shape of the raw spectra in the two investigated regions are represented

Load-based generic polca: performance assessement using simulation

POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorization) is a card-based decision support system for production control, developed to support the adoption of Quick Response Manufacturing. Two variants of POLCA have been proposed in the literature to improve POLCA performance: Load Based POLCA and Generic POLCA. In this paper, we combine these two variants into a single production control system and analyse its performance for different backlog-sequencing rules. The results of a simulation study carried out for a make-to-order flow shop, support the strategy of combining these two POLCA variants and show that capacity-slack backlog sequencing based on corrected aggregate load have the potential for improving performance.info:eu-repo/semantics/publishedVersio

PACIFIC: the readout ASIC for the SciFi Tracker of the upgraded LHCb detector

The LHCb detector will be upgraded during the Long Shutdown 2 (LS2) of the LHC in order to cope with higher instantaneous luminosities and will switch to a 40 MHz readout rate using a trigger-less software based system. All front-end electronics will be replaced and several sub-detectors must be redesigned to cope with the higher detector occupancy and radiation damage. The current tracking detectors downstream of the LHCb dipole magnet will be replaced by the Scintillating Fibre (SciFi) Tracker. The SciFi Tracker will use scintillating fibres read out by Silicon Photomultipliers (SiPMs). State-of-the-art multi-channel SiPM arrays are being developed and a custom ASIC, called the low-Power ASIC for the sCIntillating FIbres traCker (PACIFIC), will be used to digitise the signals from the SiPMs. This article presents an overview of the R&D for the PACIFIC. It is a 64-channel ASIC implemented in 130 nm CMOS technology, aiming at a radiation tolerant design with a power consumption below 10 mW per channel. It interfaces directly with the SiPM anode through a current mode input, and provides a configurable non-linear 2-bit per channel digital output. The SiPM signal is acquired by a current conveyor and processed with a fast shaper and a gated integrator. The digitization is performed using a three threshold non-linear flash ADC operating at 40 MHz. Simulation and test results show the PACIFIC chip prototypes functioning well

the interplay of two wicked problems

Funding Information: This work was funded by VLIR-UOS, grant numbers TZ2019SIN263 and TZ2020JOI032A101. Publisher Copyright: ©Concern is justified observing the link between the AIDS and COVID-19 pandemics. COVID-19 outcomes are significantly worse in many people living with HIV (PLHIV), even when vaccinated, because of their impaired immune system. Moreover, CD4 T-cells are affected by both HIV and SARS-CoV-2.1-3 SARS-CoV-2 variants can evolve in immunosuppressed patients due to prolonged viral replication in the context of an inadequate immune response.4 Accelerated intrahost evolution of SARS-CoV-2 was reported in a South African HIV patient with antiretroviral therapy (ART) failure.5 6 With 25 million HIV patients in sub-Saharan Africa (SSA) of whom an estimated 8 million are not virologically suppressed, this potentially creates a reservoir for future variants. Such variants, arising in PLHIV anywhere in the world, can spread to other continents, as has been reported for variants of concern (VoCs) (Beta, Omicron) and variants of interest (B.1.6.20, B.1.640.2) that arose in Africa.7-9 Conversely, the COVID-19 pandemic impacts HIV treatment programmes, due to supply chain issues, overburdening of healthcare systems, limiting access to testing, treatment and prevention programmes and further increasing inequalities.10 Modelled COVID-19 disruptions of HIV programmes in SSA included decreased functionality of HIV prevention programmes, HIV testing and treatment, healthcare services such as viral load testing, adherence counselling, drug regimen switches and ART interruptions, which may lead to selection of drug-resistant HIV.11 A 6-month interruption affecting 50% of the population would lead to a median number of excess deaths of 296 000, during 1 year. Scientists advocate for the AIDS and COVID-19 pandemics in Africa to be addressed simultaneously, by increasing African access to COVID-19 vaccines, prioritising research on the interaction between HIV care and COVID-19, maintaining high-quality HIV services and integrating health services for both viruses.7 Both the COVID-19 and the AIDS pandemic, more specifically the issue of HIV drug resistance (HIVDR), have previously been described as wicked problems which are best studied as complex adaptive systems (CASs).12-15Wicked problems consist of diverse interconnected factors and require complexity-informed and locally adapted solutions rather than one solution that fits all. We recently designed a qualitative model of all known factors influencing HIVDR in SSA and analysed its complexity.13 Our detailed systems map featured three main feedback loops driving HIVDR, representing (1) the alternation between adherence and non-adherence, (2) the impact of an overburdened healthcare system and (3) the importance of sustaining global efforts of tackling HIVDR even when new antiretroviral drugs with high genetic barriers become available. These HIV-related feedback loops are interconnected with COVID-19 pandemic impact (in yellow, figure 1). The loop starts from PLHIV with an unsuppressed viral load, which weakens the immune system and may in turn slow down immune clearance of SARS-CoV-2, allowing prolonged replication and mutation of the virus in the context of an inadequate immune response. Prolonged viral clearance facilitates the selection of immune escape SARS-CoV-2 variants. Variants may emerge that have a selective advantage and therefore may spread through populations due to increased transmissibility (with possibly increased virulence), thereby creating an additional burden on the healthcare system, putting the overall healthcare system and the HIV care at risk. These stressors on the healthcare system lead to a higher risk of unsuppressed viral load in PLHIV, increasing the risk of HIVDR. Figure 1 shows the need to address both wicked problems simultaneously and to do so in a complexity-informed manner as they are inevitably linked and influence each other. Evidently, the exact interconnections between both pandemics need to be locally assessed. For instance, a study in South Africa showed that while lockdown severely impacted HIV testing and ART initiation, ART provision was largely maintained, indicating that the strength of the connection between the virological suppression-related loop and the pandemic, indicated in figure 1, are context-dependent.16publishersversionpublishe

Strong variability of Martian water ice clouds during dust storms revealed from ExoMars Trace Gas Orbiter/NOMAD

Observations of water ice clouds and aerosols on Mars can provide important insights into the complexity of the water cycle. Recent observations have indicated an important link between dust activity and the water cycle, as intense dust activity can significantly raise the hygropause, and subsequently increase the escape of water after dissociation in the upper atmosphere. Here present observations from NOMAD/TGO that investigate the variation of water ice clouds in the perihelion season of Mars Year 34 (April 2018‐19), their diurnal and seasonal behavior, and the vertical structure and microphysical properties of water ice and dust. These observations reveal the recurrent presence of a layer of mesospheric water ice clouds subsequent to the 2018 Global Dust Storm. We show that this layer rose from 45 to 80 km in altitude on a timescale of days from heating in the lower atmosphere due to the storm. In addition, we demonstrate that there is a strong dawn dusk asymmetry in water ice abundance, related to nighttime nucleation and subsequent daytime sublimation. Water ice particle sizes are retrieved consistently and exhibit sharp vertical gradients (from 0.1 to 4.0 μm), as well as mesospheric differences between the Global Dust Storm (<0.5 μm) and the 2019 regional dust storm (1.0 μm), which suggests differing water ice nucleation efficiencies. These results form the basis to advance our understanding of mesospheric water ice clouds on Mars, and further constrain the interactions between water ice and dust in the middle atmosphere