Assessing knee OA severity with CNN attention-based end-to-end architectures

This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules acting as unsupervised fine-grained detectors of the region of interest (ROI). The proposed attention modules can be applied at different levels and scales across any CNN pipeline helping the network to learn relevant attention patterns over the most informative parts of the image at different resolutions. We test the proposed attention mechanism on existing state-of-the-art CNN architectures as our base models, achieving promising results on the benchmark knee OA datasets from the osteoarthritis initiative (OAI) and multicenter osteoarthritis study (MOST). All code from our experiments will be publicly available on the github repository: https://github.com/marc-gorriz/KneeOA-CNNAttentio

Chroma intra-prediction with attention-based CNN architectures

Neural networks can be used in video coding to im- prove chroma intra-prediction. In particular, usage of fully- connected networks has enabled better cross-component pre- diction with respect to traditional linear models. Nonetheless, state-of-the-art architectures tend to disregard the location of individual reference samples in the prediction process. This paper proposes a new neural network architecture for cross-component intra-prediction. The network uses a novel attention module to model spatial relations between reference and predicted samples. The proposed approach is integrated into the Versatile Video Coding (VVC) prediction pipeline. Experimental results demonstrate compression gains over the latest VVC anchor compared with state-of-the-art chroma intra-prediction methods based on neural networks

Uncertainty-Aware Semi-supervised Method using Large Unlabelled and Limited Labeled COVID-19 Data

This work was partly supported by the MINECO/ FEDER under the RTI2018-098913-B100, CV20-45250 and A-TIC-080-UGR18 projects.The new coronavirus has caused more than 1 million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. The X-ray or computed tomography (CT) images of lungs can reveal whether the patient is infected with COVID-19 or not. Many researchers are trying to improve COVID-19 detection using artificial intelligence. In this paper, relying on Generative Adversarial Networks (GAN), we propose a Semi-supervised Classification using Limited Labelled Data (SCLLD) for automated COVID-19 detection. Our motivation is to develop learning method which can cope with scenarios that preparing labelled data is time consuming or expensive. We further improved the detection accuracy of the proposed method by applying Sobel edge detection. The GAN discriminator output is a probability value which is used for classification in this work. The proposed system is trained using 10,000 CT scans collected from Omid hospital. Also, we validate our system using the public dataset. The proposed method is compared with other state of the art supervised methods such as Gaussian processes. To the best of our knowledge, this is the first time a COVID-19 semi-supervised detection method is presented. Our method is capable of learning from a mixture of limited labelled and unlabelled data where supervised learners fail due to lack of sufficient amount of labelled data. Our semi-supervised training method significantly outperforms the supervised training of Convolutional Neural Network (CNN) in case labelled training data is scarce. Our method has achieved an accuracy of 99.60%, sensitivity of 99.39%, and specificity of 99.80% where CNN (trained supervised) has achieved an accuracy of 69.87%, sensitivity of 94%, and specificity of 46.40%.Spanish Government RTI2018-098913-B100 CV20-45250 A-TIC-080UGR1

Assessing the correlation between location and size of catastrophic breakdown events in high-K MIM capacitors

The connection between the spatial location of catastrophic breakdown spots occurring in metal-insulator-metal capacitors with a high-permittivity dielectric film (HfO 2 ) and their respective sizes is investigated. Large area structures (10 4 -10 5 μm 2 ) are used for this correlation assessment since, for statistical considerations, a large number of spots in the same device is imperatively required. The application of ramped or constant voltage stress across the capacitor generates defects inside the dielectric that result in the formation of multiple failure sites. High power dissipation takes place locally, leaving a permanent mark on the top electrode of the device. The set of marks constitutes a point pattern with attributes that can be analyzed from a statistical viewpoint. The correlation between the spot locations and their sizes is assessed through the mark correlation function and the method of reverse conditional moments. The study reveals that for severely damaged devices, there exists a link between the spot location and size that leads to a short range departure from a complete spatial randomness (CSR) process. It is shown that the affected region around each failure site is actually larger than the visible area of the spot. A structural modification of the dielectric layer in the vicinity of the spot caused by the huge thermal effects occurring just before the microexplosion might be the reason behind this extension of the damage

Effects of Nutrient Management Scenarios on Marine Eutrophication Indicators: A Pan-European, Multi-Model Assessment in Support of the Marine Strategy Framework Directive

A novel pan-European marine model ensemble was established, covering nearly all seas under the regulation of the Marine Strategy Framework Directive (MSFD), with the aim of providing a consistent assessment of the potential impacts of riverine nutrient reduction scenarios on marine eutrophication indicators. For each sea region, up to five coupled biogeochemical models from institutes all over Europe were brought together for the first time. All model systems followed a harmonised scenario approach and ran two simulations, which varied only in the riverine nutrient inputs. The load reductions were evaluated with the catchment model GREEN and represented the impacts due to improved management of agriculture and wastewater treatment in all European river systems. The model ensemble, comprising 15 members, was used to assess changes to the core eutrophication indicators as defined within MSFD Descriptor 5. In nearly all marine regions, riverine load reductions led to reduced nutrient concentrations in the marine environment. However, regionally the nutrient input reductions led to an increase in the non-limiting nutrient in the water, especially in the case of phosphate concentrations in the Black Sea. Further core eutrophication indicators, such as chlorophyll-a, bottom oxygen and the Trophic Index TRIX, improved nearly everywhere, but the changes were less pronounced than for the inorganic nutrients. The model ensemble displayed strong consistency and robustness, as most if not all models indicated improvements in the same areas. There were substantial differences between the individual seas in the speed of response to the reduced nutrient loads. In the North Sea ensemble, a stable plateau was reached after only three years, while the simulation period of eight years was too short to obtain steady model results in the Baltic Sea. The ensemble exercise confirmed the importance of improved management of agriculture and wastewater treatments in the river catchments to reduce marine eutrophication. Several shortcomings were identified, the outcome of different approaches to compute the mean change was estimated and potential improvements are discussed to enhance policy support. Applying a model ensemble enabled us to obtain highly robust and consistent model results, substantially decreasing uncertainties in the scenario outcom

Frequency and Longitudinal Course of Motor Signs in Genetic Frontotemporal Dementia

Appendix 1: Authors. Appendix 2: Coinvestigators: Coinvestigators are listed at https://cdn-links.lww.com/permalink/wnl/c/wnl_2022_07_12_levin_1_sdc1.pdf . Supplement at https://cdn-links.lww.com/permalink/wnl/c/wnl_2022_06_26_levin_1_sdc2.pdf .Copyright © 2022 The Author(s). Background and Objectives: Frontotemporal dementia (FTD) is a highly heritable disorder. The majority of genetic cases are caused by autosomal dominant pathogenic variants in the chromosome 9 open reading frame 72 (c9orf72), progranulin (GRN), and microtubule-associated protein tau (MAPT) gene. As motor disorders are increasingly recognized as part of the clinical spectrum, the current study aimed to describe motor phenotypes caused by genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy. Methods: We analyzed baseline visit data of known carriers of a pathogenic variant in the c9orf72, GRN, or MAPT gene from the Genetic Frontotemporal Dementia Initiative cohort study. Principal component analysis with varimax rotation was performed to identify motor sign clusters that were compared with respect to frequency and severity between groups. Associations with cross-sectional atrophy patterns were determined using voxel-wise regression. We applied linear mixed effects models to assess whether groups differed in the association between motor signs and estimated time to symptom onset. Results: A total of 322 pathogenic variant carriers were included in the analysis: 122 c9orf72 (79 presymptomatic), 143 GRN (112 presymptomatic), and 57 MAPT (43 presymptomatic) pathogenic variant carriers. Principal component analysis revealed 5 motor clusters, which we call progressive supranuclear palsy (PSP)-like, bulbar amyotrophic lateral sclerosis (ALS)-like, mixed/ALS-like, Parkinson disease (PD) like, and corticobasal syndrome–like motor phenotypes. There was no significant group difference in the frequency of signs of different motor phenotypes. However, mixed/ALS-like motor signs were most frequent, followed by PD-like motor signs. Although the PSP-like phenotype was associated with mesencephalic atrophy, the mixed/ALS-like phenotype was associated with motor cortex and corticospinal tract atrophy. The PD-like phenotype was associated with widespread cortical and subcortical atrophy. Estimated time to onset, genetic group and their interaction influenced motor signs. In c9orf72 pathogenic variant carriers, motor signs could be detected up to 25 years before expected symptom onset. Discussion: These results indicate the presence of multiple natural clusters of motor signs in genetic FTD, each correlated with specific atrophy patterns. Their motor severity depends on time and the affected gene. These clinicogenetic associations can guide diagnostic evaluations and the design of clinical trials for new disease-modifying and preventive treatments.This work is cofunded by the UK Medical Research Council (MR/M023664/1), Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy–ID 390857198), the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant, a Canadian Institutes of Health Research operating grant and the Bluefield Project, as well as a JPND grant GENFIprox. Nonfinancial support was also provided through the European Reference Network for Rare Neurological Diseases (ERN-RND), 1 of 24 ERNs funded by the European Commission (ERN-RND: 3HP 767231). J.-M. Gorriz Saez is supported by the Ministerio de Ciencia e Innovación (España)/FEDER under the RTI2018-098913-B100 project and the Consejería de Economía, Innovación, Ciencia y Empleo (Junta de Andalucía) and FEDER under the CV20-45250 and A-TIC-080-UGR18 projects. M. Masellis was also funded by a Canadian Institutes of Health Research operating grant (MOP 327387) and funding from the Weston Brain Institute. J. Rowe is supported by the Medical Research Council (SUAG/051 G101400) and NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care

PESFOR-W: Improving the design and environmental effectiveness of woodlands for water Payments for Ecosystem Services

ABSTRACT: The EU Water Framework Directive aims to ensure restoration of Europe?s water bodies to ?good ecological status? by 2027. Many Member States will struggle to meet this target, with around half of EU river catchments currently reporting below standard water quality. Diffuse pollution from agriculture represents a major pressure, affecting over 90% of river basins. Accumulating evidence shows that recent improvements to agricultural practices are benefiting water quality but in many cases will be insufficient to achieve WFD objectives. There is growing support for land use change to help bridge the gap, with a particular focus on targeted tree planting to intercept and reduce the delivery of diffuse pollutants to water. This form of integrated catchment management offers multiple benefits to society but a significant cost to landowners and managers. New economic instruments, in combination with spatial targeting, need to be developed to ensure cost effective solutions - including tree planting for water benefits - are realised. Payments for Ecosystem Services (PES) are flexible, incentive-based mechanisms that could play an important role in promoting land use change to deliver water quality targets. The PESFOR-W COST Action will consolidate learning from existing woodlands for water PES schemes in Europe and help standardize approaches to evaluating the environmental effectiveness and cost-effectiveness of woodland measures. It will also create a European network through which PES schemes can be facilitated, extended and improved, for example by incorporating other ecosystem services linking with aims of the wider forestscarbon policy nexus

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42\ub74% vs 44\ub72%; absolute difference \u20131\ub769 [\u20139\ub758 to 6\ub711] p=0\ub767; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5\u20138] vs 6 [5\u20138] cm H2O; p=0\ub70011). ICU mortality was higher in MICs than in HICs (30\ub75% vs 19\ub79%; p=0\ub70004; adjusted effect 16\ub741% [95% CI 9\ub752\u201323\ub752]; p<0\ub70001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0\ub780 [95% CI 0\ub775\u20130\ub786]; p<0\ub70001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status. Funding: No funding

Intravenous alteplase for stroke with unknown time of onset guided by advanced imaging: systematic review and meta-analysis of individual patient data

Background: Patients who have had a stroke with unknown time of onset have been previously excluded from thrombolysis. We aimed to establish whether intravenous alteplase is safe and effective in such patients when salvageable tissue has been identified with imaging biomarkers. Methods: We did a systematic review and meta-analysis of individual patient data for trials published before Sept 21, 2020. Randomised trials of intravenous alteplase versus standard of care or placebo in adults with stroke with unknown time of onset with perfusion-diffusion MRI, perfusion CT, or MRI with diffusion weighted imaging-fluid attenuated inversion recovery (DWI-FLAIR) mismatch were eligible. The primary outcome was favourable functional outcome (score of 0–1 on the modified Rankin Scale [mRS]) at 90 days indicating no disability using an unconditional mixed-effect logistic-regression model fitted to estimate the treatment effect. Secondary outcomes were mRS shift towards a better functional outcome and independent outcome (mRS 0–2) at 90 days. Safety outcomes included death, severe disability or death (mRS score 4–6), and symptomatic intracranial haemorrhage. This study is registered with PROSPERO, CRD42020166903. Findings: Of 249 identified abstracts, four trials met our eligibility criteria for inclusion: WAKE-UP, EXTEND, THAWS, and ECASS-4. The four trials provided individual patient data for 843 individuals, of whom 429 (51%) were assigned to alteplase and 414 (49%) to placebo or standard care. A favourable outcome occurred in 199 (47%) of 420 patients with alteplase and in 160 (39%) of 409 patients among controls (adjusted odds ratio [OR] 1·49 [95% CI 1·10–2·03]; p=0·011), with low heterogeneity across studies (I2=27%). Alteplase was associated with a significant shift towards better functional outcome (adjusted common OR 1·38 [95% CI 1·05–1·80]; p=0·019), and a higher odds of independent outcome (adjusted OR 1·50 [1·06–2·12]; p=0·022). In the alteplase group, 90 (21%) patients were severely disabled or died (mRS score 4–6), compared with 102 (25%) patients in the control group (adjusted OR 0·76 [0·52–1·11]; p=0·15). 27 (6%) patients died in the alteplase group and 14 (3%) patients died among controls (adjusted OR 2·06 [1·03–4·09]; p=0·040). The prevalence of symptomatic intracranial haemorrhage was higher in the alteplase group than among controls (11 [3%] vs two [<1%], adjusted OR 5·58 [1·22–25·50]; p=0·024). Interpretation: In patients who have had a stroke with unknown time of onset with a DWI-FLAIR or perfusion mismatch, intravenous alteplase resulted in better functional outcome at 90 days than placebo or standard care. A net benefit was observed for all functional outcomes despite an increased risk of symptomatic intracranial haemorrhage. Although there were more deaths with alteplase than placebo, there were fewer cases of severe disability or death. Funding: None