EQ-5D and the EuroQol Group: Past, Present and Future

Over the period 1987-1991 an inter-disciplinary five-country group developed the EuroQol instrument, a five-dimensional three-level generic measure subsequently termed the 'EQ-5D'. It was designed to measure and value health status. The salient features of its development and its consolidation and expansion are discussed. Initial expansion came, in particular, in the form of new language versions. Their development raised translation and semantic issues, experience with which helped feed into the design of two further instruments, the EQ-5D-5L and the youth version EQ-5D-Y. The expanded usage across clinical programmes, disease and condition areas, population surveys, patient-reported outcomes, and value sets is outlined. Valuation has been of continued relevance for the Group as this has allowed its instruments to be utilised as part of the economic appraisal of health programmes and their incorporation into health technology assessments. The future of the Group is considered in the context of: (1) its scientific strategy, (2) changes in the external environment affecting the demand for EQ-5D, and (3) a variety of issues it is facing in the context of the design of the instrument, its use in health technology assessment, and potential new uses for EQ-5D outside of clinical trials and technology appraisal

Panel III: Implications of the New Telecommunications Legislation

We present a method that employs a tree-based Neural Network (NN) for performing classification. The novel mechanism, apart from incorporating the information provided by unlabeled and labeled instances, re-arranges the nodes of the tree as per the laws of Adaptive Data Structures (ADSs). Particularly, we investigate the Pattern Recognition (PR) capabilities of the Tree-Based Topology-Oriented SOM (TTOSOM) when Conditional Rotations (CONROT) [8] are incorporated into the learning scheme. The learning methodology inherits all the properties of the TTOSOM-based classifier designed in [4]. However, we now augment it with the property that frequently accessed nodes are moved closer to the root of the tree. Our experimental results show that on average, the classification capabilities of our proposed strategy are reasonably comparable to those obtained by some of the state-of-the-art classification schemes that only use labeled instances during the training phase. The experiments also show that improved levels of accuracy can be obtained by imposing trees with a larger number of nodes

Lack of class I H-2 antigens in cells transformed by radiation leukemia virus is associated with methylation and rearrangement of H-2 DNA

Transformation of murine thymocytes by radiation leukemia virus is associated with reduced expression of the class I antigens encoded in the major histocompatibility complex (MHC) and increased methylation and altered restriction enzyme patterns of MHC DNA. These changes may play a role in host susceptibility to virus-induced leukemogenesis and accord with the notion that viral genomes play a regulatory function when they integrate adjacent to histocompatibiity genes

The Atacama Cosmology Telescope: Cross-Correlation of Cosmic Microwave Background Lensing and Quasars

We measure the cross-correlation of Atacama cosmology telescope cosmic microwave background (CMB) lensing convergence maps with quasar maps made from the Sloan Digital Sky Survey DR8 SDSS-XDQSO photometric catalog. The CMB lensing quasar cross-power spectrum is detected for the first time at a significance of 3.8σ, which directly confirms that the quasar distribution traces the mass distribution at high redshifts z\u3e1. Our detection passes a number of null tests and systematic checks. Using this cross-power spectrum, we measure the amplitude of the linear quasar bias assuming a template for its redshift dependence, and find the amplitude to be consistent with an earlier measurement from clustering; at redshift z≈1.4, the peak of the distribution of quasars in our maps, our measurement corresponds to a bias of b=2.5±0.6. With the signal-to-noise ratio on CMB lensing measurements likely to improve by an order of magnitude over the next few years, our results demonstrate the potential of CMB lensing cross-correlations to probe astrophysics at high redshifts

Can Forel–Ule Index Act as a Proxy of Water Quality in Temperate Waters? Application of Plume Mapping in Liverpool Bay, UK

The use of ocean colour classification algorithms, linked to water quality gradients, can be a useful tool for mapping river plumes in both tropical and temperate systems. This approach has been applied in operational water quality programs in the Great Barrier Reef to map river plumes and assess trends in marine water composition and ecosystem health during flood periods. In this study, we used the Forel–Ule colour classification algorithm for Sentinel-3 OLCI imagery in an automated process to map monthly, annual and long-term plume movement in the temperate coastal system of Liverpool Bay (UK). We compared monthly river plume extent to the river flow and in situ water quality data between 2017–2020. The results showed a strong positive correlation (Spearman’s rho = 0.68) between the river plume extent and the river flow and a strong link between the FUI defined waterbodies and nutrients, SPM, turbidity and salinity, hence the potential of the Forel–Ule index to act as a proxy for water quality in the temperate Liverpool Bay water. The paper discusses how the Forel–Ule index could be used in operational water quality programs to better understand river plumes and the land-based inputs to the coastal zones in UK waters, drawing parallels with methods that have been developed in the GBR and Citclops project. Overall, this paper provides the first insight into the systematic long-term river plume mapping in UK coastal waters using a fast, cost-effective, and reproducible workflow. The study created a novel water assessment typology based on the common physical, chemical and biological ocean colour properties captured in the Forel–Ule index, which could replace the more traditional eutrophication assessment regions centred around strict geographic and political boundaries. Additionally, the Forel–Ule assessment typology is particularly important since it identifies areas of the greatest impact from the land-based loads into the marine environment, and thus potential risks to vulnerable ecosystems

Power-law Template for Infrared Point-source Clustering

We perform a combined fit to angular power spectra of unresolved infrared (IR) point sources from the Planck satellite (at 217, 353, 545, and 857 GHz, over angular scales 100 ≾ ℓ ≾ 2200), the Balloon-borne Large-Aperture Submillimeter Telescope (BLAST; 250, 350, and 500μm; 1000 ≾ ℓ ≾ 9000), and from correlating BLAST and Atacama Cosmology Telescope (ACT; 148 and 218 GHz) maps. We find that the clustered power over the range of angular scales and frequencies considered is well fitted by a simple power law of the form C^(clust)_ℓ ∝ ℓ^(-n) with n = 1.25 ± 0.06. While the IR sources are understood to lie at a range of redshifts, with a variety of dust properties, we find that the frequency dependence of the clustering power can be described by the square of a modified blackbody, ν^(β)B(ν, T_(eff)), with a single emissivity index β = 2.20 ± 0.07 and effective temperature T_(eff) = 9.7 K. Our predictions for the clustering amplitude are consistent with existing ACT and South Pole Telescope results at around 150 and 220 GHz, as is our prediction for the effective dust spectral index, which we find to be α_(150–220) = 3.68±0.07 between 150 and 220 GHz. Our constraints on the clustering shape and frequency dependence can be used to model the IR clustering as a contaminant in cosmic microwave background anisotropy measurements. The combined Planck and BLAST data also rule out a linear bias clustering model

A probabilistic approach to mapping the contribution of individual riverine discharges into Liverpool Bay using distance accumulation cost methods on satellite derived ocean-colour data

Assessments of the water quality in coastal zones often rely on indirect indicators from contributing river inputs and the neighbouring ocean. Using a novel combination of distance accumulation cost methods and an ocean-colour product derived from SENTINEL-3 data, we developed a probabilistic method for the assessment of dissolved inorganic nitrogen (DIN) in Liverpool Bay (UK) for the period from 2017 to 2020. Using our approach, we showed the annual and monthly likelihood of DIN exposure from its 12 major contributory rivers. Furthermore, we generated monthly risk maps showing the probability of DIN exposure from all rivers, which revealed a seasonal variation of extent and location around the bay. The highest likelihood of high DIN exposure throughout the year was in the estuarine regions of the Dee, Mersey, and Ribble, along with near-shore areas along the north Wales coast and around the mouth of the rivers Mersey and Ribble. There were seasonal changes in the risk of DIN exposure, and this risk remained high all year for the Mersey and Dee estuary regions. In contrast, for the mouth and near the coastal areas of the Ribble, the DIN exposure decreased in spring, remained low during the summer and early autumn, before displaying an increase during winter. Our approach offers the ability to assess the water quality within coastal zones without the need of complex hydrodynamic models, whilst still having the potential to apportion nutrient exposure to specific riverine inputs. This information can help to prioritise how direct mitigation strategies can be applied to specific river catchments, focusing the limited resources for coastal zone and river basin management