Strong fisheries management and governance positively impact ecosystem status

Fisheries have had major negative impacts on marine ecosystems, and effective fisheries management and governance are needed to achieve sustainable fisheries, biodiversity conservation goals and thus good ecosystem status. To date, the IndiSeas programme (Indicators for the Seas) has focussed on assessing the ecological impacts of fishing at the ecosystem scale using ecological indicators. Here, we explore fisheries Management Effectiveness' and Governance Quality' and relate this to ecosystem health and status. We developed a dedicated expert survey, focused at the ecosystem level, with a series of questions addressing aspects of management and governance, from an ecosystem-based perspective, using objective and evidence-based criteria. The survey was completed by ecosystem experts (managers and scientists) and results analysed using ranking and multivariate methods. Results were further examined for selected ecosystems, using expert knowledge, to explore the overall findings in greater depth. Higher scores for Management Effectiveness' and Governance Quality' were significantly and positively related to ecosystems with better ecological status. Key factors that point to success in delivering fisheries and conservation objectives were as follows: the use of reference points for management, frequent review of stock assessments, whether Illegal, Unreported and Unregulated (IUU) catches were being accounted for and addressed, and the inclusion of stakeholders. Additionally, we found that the implementation of a long-term management plan, including economic and social dimensions of fisheries in exploited ecosystems, was a key factor in successful, sustainable fisheries management. Our results support the thesis that good ecosystem-based management and governance, sustainable fisheries and healthy ecosystems go together.IOC-UNESCO; EuroMarine; European FP7 MEECE research project; European Network of Excellence Eur-Oceans; FRB EMIBIOS project [212085]info:eu-repo/semantics/publishedVersio

Additive Manufactured Scaffolds for Bone Tissue Engineering: Physical Characterization of Thermoplastic Composites with Functional Fillers

Thermoplastic polymer–filler composites are excellent materials for bone tissue engineering (TE) scaffolds, combining the functionality of fillers with suitable load-bearing ability, biodegradability, and additive manufacturing (AM) compatibility of the polymer. Two key determinants of their utility are their rheological behavior in the molten state, determining AM processability and their mechanical load-bearing properties. We report here the characterization of both these physical properties for four bone TE relevant composite formulations with poly(ethylene oxide terephthalate)/poly(butylene terephthalate (PEOT/PBT) as a base polymer, which is often used to fabricate TE scaffolds. The fillers used were reduced graphene oxide (rGO), hydroxyapatite (HA), gentamicin intercalated in zirconium phosphate (ZrP-GTM) and ciprofloxacin intercalated in MgAl layered double hydroxide (MgAl-CFX). The rheological assessment showed that generally the viscous behavior dominated the elastic behavior (G″ > G′) for the studied composites, at empirically determined extrusion temperatures. Coupled rheological–thermal characterization of ZrP-GTM and HA composites showed that the fillers increased the solidification temperatures of the polymer melts during cooling. Both these findings have implications for the required extrusion temperatures and bonding between layers. Mechanical tests showed that the fillers generally not only made the polymer stiffer but more brittle in proportion to the filler fractions. Furthermore, the elastic moduli of scaffolds did not directly correlate with the corresponding bulk material properties, implying composite-specific AM processing effects on the mechanical properties. Finally, we show computational models to predict multimaterial scaffold elastic moduli using measured single material scaffold and bulk moduli. The reported characterizations are essential for assessing the AM processability and ultimately the suitability of the manufactured scaffolds for the envisioned bone regeneration application.The work was supported by a Horizon 2020 Research and Innovation Programme grant from the European Union, called the FAST project (grant no. 685825, project website: http:// project-fast.eu). The authors acknowledge the support of the FAST project consortium for the various aspects of this wor

First bounds on the high-energy emission from isolated Wolf-Rayet binary systems

High-energy gamma-ray emission is theoretically expected to arise in tight binary star systems (with high mass loss and high velocity winds), although the evidence of this relationship has proven to be elusive so far. Here we present the first bounds on this putative emission from isolated Wolf-Rayet (WR) star binaries, WR 147 and WR 146, obtained from observations with the MAGIC telescope.Comment: (Authors are the MAGIC Collaboration.) Manuscript in press at The Astrophysical Journal Letter

Upper limit for gamma-ray emission above 140 GeV from the dwarf spheroidal galaxy Draco

The nearby dwarf spheroidal galaxy Draco with its high mass to light ratio is one of the most auspicious targets for indirect dark matter searches. Annihilation of hypothetical DM particles can result in high-energy gamma-rays, e.g. from neutralino annihilation in the supersymmetric framework. With the MAGIC telescope a search for a possible DM signal originating from Draco was performed during 2007. The analysis of the data results in a flux upper limit of 1.1x10^-11 photons cm^-2 sec^-1 for photon energies above 140 GeV, assuming a point like source. Furthermore, a comparison with predictions from supersymmetric models is given. While our results do not constrain the mSUGRA phase parameter space, a very high flux enhancement can be ruled out.Comment: Accepted for publication by Astrophysical Journa

MAGIC Upper Limits for two Milagro-detected, Bright Fermi Sources in the Region of SNR G65.1+0.6

We report on the observation of the region around supernova remnant G65.1+0.6 with the stand-alone MAGIC-I telescope. This region hosts the two bright GeV gamma-ray sources 1FGL J1954.3+2836 and 1FGL J1958.6+2845. They are identified as GeV pulsars and both have a possible counterpart detected at about 35 TeV by the Milagro observatory. MAGIC collected 25.5 hours of good quality data, and found no significant emission in the range around 1 TeV. We therefore report differential flux upper limits, assuming the emission to be point-like (<0.1 deg) or within a radius of 0.3 deg. In the point-like scenario, the flux limits around 1 TeV are at the level of 3 % and 2 % of the Crab Nebula flux, for the two sources respectively. This implies that the Milagro emission is either extended over a much larger area than our point spread function, or it must be peaked at energies beyond 1 TeV, resulting in a photon index harder than 2.2 in the TeV band.Comment: 8 pages, 3 figures, 1 tabl

Observation of Pulsed Gamma-rays Above 25 GeV from the Crab Pulsar with MAGIC

One fundamental question about pulsars concerns the mechanism of their pulsed electromagnetic emission. Measuring the high-end region of a pulsar's spectrum would shed light on this question. By developing a new electronic trigger, we lowered the threshold of the Major Atmospheric gamma-ray Imaging Cherenkov (MAGIC) telescope to 25 GeV. In this configuration, we detected pulsed gamma-rays from the Crab pulsar that were greater than 25 GeV, revealing a relatively high cutoff energy in the phase-averaged spectrum. This indicates that the emission occurs far out in the magnetosphere, hence excluding the polar-cap scenario as a possible explanation of our measurement. The high cutoff energy also challenges the slot-gap scenario.Comment: Slight modification of the analysis: Fitting a more general function to the combined data set of COMPTEL, EGRET and MAGIC. Final result and conclusion is unchange

Probing quantum gravity using photons from a flare of the active galactic nucleus Markarian 501 observed by the MAGIC telescope

We analyze the timing of photons observed by the MAGIC telescope during a flare of the active galactic nucleus Mkn 501 for a possible correlation with energy, as suggested by some models of quantum gravity (QG), which predict a vacuum refractive index \simeq 1 + (E/M_{QGn})^n, n = 1,2. Parametrizing the delay between gamma-rays of different energies as \Delta t =\pm\tau_l E or \Delta t =\pm\tau_q E^2, we find \tau_l=(0.030\pm0.012) s/GeV at the 2.5-sigma level, and \tau_q=(3.71\pm2.57)x10^{-6} s/GeV^2, respectively. We use these results to establish lower limits M_{QG1} > 0.21x10^{18} GeV and M_{QG2} > 0.26x10^{11} GeV at the 95% C.L. Monte Carlo studies confirm the MAGIC sensitivity to propagation effects at these levels. Thermal plasma effects in the source are negligible, but we cannot exclude the importance of some other source effect.Comment: 12 pages, 3 figures, Phys. Lett. B, reflects published versio

Simultaneous multi-frequency observation of the unknown redshift blazar PG 1553+113 in March-April 2008

The blazar PG 1553+113 is a well known TeV gamma-ray emitter. In this paper, we determine its spectral energy distribution using simultaneous multi-frequency data in order to study its emission processes. An extensive campaign was carried out between March and April 2008, where optical, X-ray, high-energy (HE) gamma-ray, and very-high-energy (VHE) gamma-ray data were obtained with the KVA, Abastumani, REM, RossiXTE/ASM, AGILE and MAGIC telescopes, respectively. This is the first simultaneous broad-band (i.e., HE+VHE) gamma-ray observation, though AGILE did not detect the source. We combine data to derive source's spectral energy distribution and interpret its double peaked shape within the framework of a synchrotron self compton modelComment: 5 pages, 2 figures, publishe

Gene co-expression architecture in peripheral blood in a cohort of remitted first-episode schizophrenia patients

A better understanding of schizophrenia subtypes is necessary to stratify the patients according to clinical attributes. To explore the genomic architecture of schizophrenia symptomatology, we analyzed blood co-expression modules and their association with clinical data from patients in remission after a first episode of schizophrenia. In total, 91 participants of the 2EPS project were included. Gene expression was assessed using the Clariom S Human Array. Weighted-gene co-expression network analysis (WGCNA) was applied to identify modules of co-expressed genes and to test its correlation with global functioning, clinical symptomatology, and premorbid adjustment. Among the 25 modules identified, six modules were significantly correlated with clinical data. These modules could be clustered in two groups according to their correlation with clinical data. Hub genes in each group showing overlap with risk genes for schizophrenia were enriched in biological processes related to metabolic processes, regulation of gene expression, cellular localization and protein transport, immune processes, and neurotrophin pathways. Our results indicate that modules with significant associations with clinical data showed overlap with gene sets previously identified in differential gene-expression analysis in brain, indicating that peripheral tissues could reveal pathogenic mechanisms. Hub genes involved in these modules revealed multiple signaling pathways previously related to schizophrenia, which may represent the complex interplay in the pathological mechanisms behind the disease. These genes could represent potential targets for the development of peripheral biomarkers underlying illness traits in clinical remission stages after a first episode of schizophrenia

Fetal Brain Tissue Annotation and Segmentation Challenge Results

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.Comment: Results from FeTA Challenge 2021, held at MICCAI; Manuscript submitte