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Greater treatment choice and the associated flexibility in regimens has necessitated new conversations with people with haemophilia about their personal goals. Innovations in haemophilia treatment drive the need for innovation in care service delivery. Supported by Sobi™, CATCH (Collaborate & Address Treatment Challenges in Haemophilia) is an annual, non-promotional, medical education meeting that brings together members of the haemophilia multidisciplinary team from across the UK and Ireland to discuss all aspects of haemophilia care and management. This report summarises the key issues that were explored and discussed during the CATCH 2024 meeting, including understanding the personal motivations of people with haemophilia and how these influence treatment choices and support; facilitating behaviour change to improve outcomes; reviewing the practicalities and possibilities for eliminating bleeds and new arthropathy in people with haemophilia; and developing new models of care to elevate haemophilia services.

The radiative perturbation of the Earth's energy balance caused by all aerosols, the direct radiative effect (DRE), and anthropogenic aerosols, the direct radiative forcing (DRF), remain major sources of uncertainty in climate projections. Here we propose a method for determining DRE and DRF that makes use of the High Spectral Resolution Lidar (HSRL)-retrieved aerosol loading and derived aerosol types (i.e. dust, marine, urban, smoke, etc.) in combination with aerosol-type specific optical properties. As the global spatiotemporal distributions of HSRL-derived aerosol types are not currently available, the methodology is tested here using a global 3-D model of atmospheric chemistry (GEOS-Chem) along with Creating Aerosols from CHemistry (CATCH) algorithm-generated aerosol types analogous to ones derived by HSRL. In this method, the Rapid Radiative Transfer Model for General Circulation Models (RRTMG) is used to perform radiative transfer calculations with the single scattering albedo (SSA) and asymmetry parameter (g) of atmospheric particles assigned based on the aerosol type in each grid box. Average GEOS-Chem/CATCH-derived all-sky DRE and DRF across the North American domain are estimated to be −1.98 W/m² and − 0.77 W/m², respectively between mid-January and early February 2013 and − 4.20 W/m² and − 1.41 W/m² respectively between mid-July and early August 2014. Sensitivity studies revealed that the scheme may produce up to about ±0.42 W/m² and ± 0.21 W/m² uncertainty in DRE and DRF, respectively, related to variability in aerosol type-specific optical properties. This study presents a new way of determining DRE and DRF estimates once global retrievals of aerosol intensive parameters by HSRL become available.

Due to the increasing demand for fish consumption, sustainable fishery become more and more challenging. To prevent from overfishing, massive data in open sea fishing have been collected and analyzed to achieve efficient management of fishery. Still, it is extremely difficult for fishers and fishery managers to exploit available data for accurate prediction, because of their limited data processing capacities, and the overall lack of adequate database systems [1].The goal of this work is therefore to analyze the relationship between data collected from all sensors installed on-board fishing vessels and catch weight, to better support generating a map showing likely fishing effort allocation. To do so, we train neural networks to predict catch weight using all available data from sensors on fishing vessels. The raw data are pre-processed using random sampling techniques to be fed into a neural network for training. A multi-layer perceptron (MLP) neural network is proposed as the baseline. We propose a data augmentation method and a training strategy in order to optimize the prediction accuracy of the model. Our data augmentation method conducts random sampling of the original data multiple times, which reduces the root mean square error (RMSE) by 15.8%, as compared with the results obtained by the model trained without data augmentation. Our training strategy works well to further optimize the prediction accuracy of the model trained with an augmented dataset, which significantly decreased the RMSE by 11. 2%. To the best of our knowledge, this is the first study on the catch weight prediction using neural networks.

The article reports on the television adaptation of "The Catch," the first novel by poet Yrsa Daley-Ward, published in summer 2025.

Seattle locals and tourists alike flock to Pike Place each day to watch the fish fly. But Pike Place Fish is about more than just crowd-pleasing entertainment --- there is an underlying philosophy at work that has made the market both wildly successful and internationally renowned. In an unusual combination of oral biography and practical business blueprint, Crother and the fishmongers take you behind the scenes at the famous market to illustrate the PPF philosophy and reveal the underlying assumptions that have made PPF the international phenomenon it is today. Catch! shows that to be'ordinary'is to be a victim of circumstances, responding to whatever comes one's way. To be'great'is to realize that anyone can live an extraordinary life. At Pike Place Fish, everyone is responsible for transforming themselves from ordinary to great by creating their own reality. The authors explore the issues of goals --- financial, personal and humanitarian --- and intention, showing how the crew itself creates these goals and works towards them in collaboration. Most importantly, Catch! examines the power of possibility and shows how you can achieve greatness in your own life. Catch! explores such guiding principles as coaching and acknowledgment that are lacking in many businesses, and shows that you, too, can be the prime mover in your own experience.

Objectives Comorbidities negatively influence remission rates in RA. This study estimated the effects of comorbidities on components of disease activity in early RA (ERA). Methods Using the Rheumatic Disease Comorbidity Index (RDCI), the influence of comorbidities on trajectories of components of the SDAI (Simple Disease Activity Index) was assessed in participants with ERA enrolled in Canadian Early Arthritis Cohort (CATCH) over the first year of treatment. Adjusted effects of RDCI scores categorized 0, 1, 2 and ≥3 on SDAI trajectories over time were analysed using multivariable generalized estimating equations (GEEs) models adjusted for multiple confounders. Results ERA participants (N  = 2248) had a mean (S.D.) symptom duration of 5.7 (3) months; mean age 55 (15) years and 72% were female. Baseline SDAI was 29 (15), with 90% having moderate-high SDAI. Baseline RDCI scores were 0 in 888 (40%), 1 in 547 (24%), 2 in 451 (20%) and ≥3 in 362 (16%). While baseline disease activity was similar across comorbidity groups, patients with higher RDCI scores showed worse SDAI trajectories over the first year of RA treatment. Higher RDCI scores were independently associated with pain, patient and physician global assessments over time. Conclusion This large real-world analysis of ERA patients seen in routine rheumatology practice across Canada showed that while RA disease activity across comorbidity groups at diagnosis was similar, higher comorbidity was associated with slower improvement in RA disease activity over the first year of treatment, likely driven by independent associations with patient and physician global assessments and pain.