Multiple Evidence for Climate Patterns Influencing Ecosystem Productivity across Spatial Gradients in the Venice Lagoon

Effects of climatic changes in transitional ecosystems are often not linear, with some areas likely experiencing faster or more intense responses, which something important to consider in the perspective of climate forecasting. In this study of the Venice lagoon, time series of the past decade were used, and primary productivity was estimated from hourly oxygen data using a published model. Temporal and spatial patterns of water temperature, salinity and productivity time series were identified by applying clustering analysis. Phytoplankton and nutrient data from long-term surveys were correlated to primary productivity model outputs. pmax, the maximum oxygen production rate in a given day, was found to positively correlate with plankton variables measured in surveys. Clustering analysis showed the occurrence of summer heatwaves in 2008, 2013, 2015 and 2018 and three warm prolonged summers (2012, 2017, 2019) coincided with lower summer pmax values. Spatial effects in terms of temperature were found with segregation between confined and open areas, although the patterns varied from year to year. Production and respiration differences showed that the lagoon, despite seasonality, was overall heterotrophic, with internal water bodies having greater values of heterotrophy. Warm, dry years with high salinity had lower degrees of summer autotrophy

Digital twins for land-based aquaculture: A case study for rainbow trout (Oncorhynchus mykiss)

The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout (Oncorhynchus mykiss) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments

Development of a Multivariate Prediction Model for Early-Onset Bronchiolitis Obliterans Syndrome and Restrictive Allograft Syndrome in Lung Transplantation.

Chronic lung allograft dysfunction and its main phenotypes, bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS), are major causes of mortality after lung transplantation (LT). RAS and early-onset BOS, developing within 3 years after LT, are associated with particularly inferior clinical outcomes. Prediction models for early-onset BOS and RAS have not been previously described. LT recipients of the French and Swiss transplant cohorts were eligible for inclusion in the SysCLAD cohort if they were alive with at least 2 years of follow-up but less than 3 years, or if they died or were retransplanted at any time less than 3 years. These patients were assessed for early-onset BOS, RAS, or stable allograft function by an adjudication committee. Baseline characteristics, data on surgery, immunosuppression, and year-1 follow-up were collected. Prediction models for BOS and RAS were developed using multivariate logistic regression and multivariate multinomial analysis. Among patients fulfilling the eligibility criteria, we identified 149 stable, 51 BOS, and 30 RAS subjects. The best prediction model for early-onset BOS and RAS included the underlying diagnosis, induction treatment, immunosuppression, and year-1 class II donor-specific antibodies (DSAs). Within this model, class II DSAs were associated with BOS and RAS, whereas pre-LT diagnoses of interstitial lung disease and chronic obstructive pulmonary disease were associated with RAS. Although these findings need further validation, results indicate that specific baseline and year-1 parameters may serve as predictors of BOS or RAS by 3 years post-LT. Their identification may allow intervention or guide risk stratification, aiming for an individualized patient management approach

Prognosis of hyperviscosity syndrome in newly diagnosed multiple myeloma in modern-era therapy: A real-life study

Hyperviscosity syndrome (HVS) is a rare complication of newly diagnosed multiple myeloma (NDMM) related to high tumour burden. Studies about the prognosis of HVS in modern-era therapy for NDMM are missing. We investigated a retrospective cohort study of NDMM with HVS between 2011-2021. Thirty-nine NDMM patients with HVS were included. HVS presentation was heterogeneous, with asymptomatic, mild, and neurological forms in 23%, 59%, and 18% of cases, respectively. No thrombosis or major bleeding was observed. Therapeutic plasma exchanges were used in 92% of patients, which were effective and well tolerated. No rebound effect was observed. All patients except one had at least one CRAB criterion. Most of the patients received bortezomib and high-dose steroids (95%) associated with an immunomodulatory drug (43%) or alkylating agents (42%). HVS in NDMM patients had dismal overall survival matched to multiple myeloma patient controls (without HVS) in our center (median: 3.6 vs. 7.7 years, p=0.01), as confirmed by multivariate analysis. Early deaths (in the first two months) occurred in 21% of older patients (>65 years). HVS in NDMM patients is a rare but life-threatening complication associated with high lethality in older patients and be a potential dismal prognosis factor in the modern treatment era

The wide-field, multiplexed, spectroscopic facility WEAVE : survey design, overview, and simulated implementation

Funding for the WEAVE facility has been provided by UKRI STFC, the University of Oxford, NOVA, NWO, Instituto de Astrofísica de Canarias (IAC), the Isaac Newton Group partners (STFC, NWO, and Spain, led by the IAC), INAF, CNRS-INSU, the Observatoire de Paris, Région Île-de-France, CONCYT through INAOE, Konkoly Observatory (CSFK), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Lund University, the Leibniz Institute for Astrophysics Potsdam (AIP), the Swedish Research Council, the European Commission, and the University of Pennsylvania.WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366-959 nm at R ∼ 5000, or two shorter ranges at R ∼ 20,000. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for ∼ 3 million stars and detailed abundances for ∼ 1.5 million brighter field and open-cluster stars; (ii) survey ∼ 0.4 million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey  ∼ 400 neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in z 1 million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at z > 2. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.PostprintPeer reviewe

The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366$-$959\,nm at $R\sim5000$, or two shorter ranges at $R\sim20\,000$. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for $\sim$3 million stars and detailed abundances for $\sim1.5$ million brighter field and open-cluster stars; (ii) survey $\sim0.4$ million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey $\sim400$ neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in $z<0.5$ cluster galaxies; (vi) survey stellar populations and kinematics in $\sim25\,000$ field galaxies at $0.3\lesssim z \lesssim 0.7$; (vii) study the cosmic evolution of accretion and star formation using $>1$ million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at $z>2$. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.Comment: 41 pages, 27 figures, accepted for publication by MNRA

The wide-field, multiplexed, spectroscopic facility WEAVE: Survey design, overview, and simulated implementation

WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366−959\,nm at R∼5000, or two shorter ranges at R∼20000. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for ∼3 million stars and detailed abundances for ∼1.5 million brighter field and open-cluster stars; (ii) survey ∼0.4 million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey ∼400 neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in z1 million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at z>2. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator

ESTIMATION OF RAINBOW TROUT (ONCORHYNCHUS MYKISS) RESPIRATION RATE WITHIN A COMMERCIAL RACEWAY USING A DATA ASSIMILATION APPROACH

Innovations and decrease in costs of sensors are making it possible to apply to aquaculture the concept of “Precision Livestock Farming”, introduced in the agrifood sector in early 2000. The implementation of the “Precision Fish Farming” (PFF) framework (Fore et. al., 2018) is likely to revolutionize the aquaculture industry, leading to a new generation of softwares and decision support tools, based on dynamic data driven models. In a previous work (Royer et al., 2021), we proposed a PFF based model of oxygen mass-balance for rainbow trout within a commercial raceway, showing that it is possible to dynamically estimate hourly fish respiration rate in commercial farming condition and, on this basis, to improve current control systems. In this study, the estimation method was improved by introducing a data assimilation procedure (Kalman Filter) that allows one to correct the respiration rate as data acquisition goes by and, on this basis, to obtain more accurate short-term predictions of DO concentration

TESTING A REAL TIME WEIGHT MEASUREMENT SYSTEM IN A TROUT RACEWAY

The Precision Fish Farming framework (Fore et al. 2018) was recently applied to the online estimation of DO demand in a trout raceway (Royer&amp;al., 2020) Key to the implementation of this novel approach is the availability of real time or quasi real time data concerning the evolution of the external forcings, the environmental variables within the farming systems and the so called “animal variables”, e.g. fish size,. In this study, a commercial real-time weight monitoring system, designed for salmon cages, was tested in a rainbow trout farm in Northern Italy, in order to monitor the weight evolution within a raceway

DISSOLVED OXYGEN CONSUMPTION AND INTRA-TANK DISTRIBUTION OF TROUT BIOMASS

Precision fish farming (PFF) aims at improving accuracy, precision, and repeatability in farming operations by delivering reliable decision-making support tools to farmers (Føre et al. 2018). It is centred on 1) large quantitative datasets provided from sensors which feed 2) data driven models and algorithms and finally supply 3) decision-supporting tools and smart management systems based on the Internet of Things (Banhazi et al., 2012). These datasets concern both environmental variables and fish bio-responses. Here we focus on the dissolved oxygen (DO) flux along an 8m-wide 200m-long raceway tank for rainbow trout cultivation located in Trentino Alto-Adige, Italy. Along the production cycle, liquid oxygen is supplied at constant rates into the raceway. A previous assessment (Royer el al. 2021) has demonstrated that a DO transport model can be used to implement a cost-effective automatic control of oxygen supply in this fish farm, based on short-term predictions of oxygen demand. As a step further, here we address the intra-tank spatial variability of DO, associated with a liquid oxygen supply, fish metabolism, and atmospheric exchange. By analysing the streamwise variation of DO consumption, the biomass distribution along the raceway can be estimated, allowing the assessment of preferential movements of fishes along the tank. Furthermore, assessing the DO values at different downstream positions at the raceway is suitable for improving fish growth and respiration models