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The Global Precipitation Measurement (GPM) mission combines passive microwave (PMW) and infrared (IR) satellite data, together with other data to create the Integrated Multi-satellitE Retrievals for (IMERG) precipitation product on a (nearly) global 0.1° half-hour grid. Experience with Version 06 datasets revealed deficiencies that the algorithm team has addressed in creating the new Version 07 datasets.Input precipitation estimates from the Goddard Profiling (GPROF) algorithm (which retrieves precipitation from passive microwave sensor data), the GPM Combined Radar-Radiometer Algorithm (CORRA), and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm (retrieving precipitation from IR data) all represent advances over the V06 inputs. For V07, several issues have been addressed, and many algorithm improvements have been implemented. These include refining the Kalman filter to approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and applying the Kalman filter even when a PMW overpass occurs. Furthermore, a long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and climatological adjustment of the near-real-time Early and Late Runs to the Final Run (which includes monthly precipitation gauge analyses). Extensive development work was directed at unexpected biases in the V06 products, leading to 1) calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager (GMI) precipitation estimates (rather than spatially coincident data), and 2) coarsening the CORRA resolution to approximately match the GPROF-GMI footprint scale. The latter provides more consistent histograms for building the calibrations.It is anticipated that the retrospective analysis for V07 will be well underway at the time of the meeting. Changes between V06 and V07 will illustrate the cumulative result of the improvements implemented in V07. The current status of processing and plans for future development will also be discussed.

The overarching goal of this research work is to fabricate biocompatible, porous bone scaffolds that are not only mechanically robust but also dimensionally accurate for the treatment of osseous fractures, defects, and musculoskeletal diseases. In pursuit of this goal, the objective of the work is to develop an image-based intelligent platform, based on convolutional neural network, for prediction of the functional properties (such as porosity, stiffness, and compressive strength) of composite bone scaffolds (composed of polyamide, polyolefin, and cellulose fibers) fabricated using fused deposition modeling (FDM) process. FDM is a material extrusion additive manufacturing process, which has been extensively utilized for the fabrication of a wide range of biological tissues and constructs for tissue engineering applications. As a high-resolution method, FDM allows for deposition of composite materials with complex formulations as well as complex porous microstructures. Despite the advantages and engendered applications, the FDM process is inherently complex; the complexity of the process is, to a great extent, the result of complex physical phenomena (such as non-Newtonian material deposition, layer fusion, and phase change) in addition to unavoidable material-process interactions (e.g., molten polymer flow deposition and subsequent layer fusion vs. translation speed). Besides, there is a wide spectrum of scaffold design, composite material, and fabrication process parameters (such as molten polymer viscosity, scaffold morphology, nozzle diameter, deposition temperature, and forced convection rate influencing solidification rate) contributing to the complexity of the FDM process. As a result, investigation of the impact of consequential design, material, and process parameters as well as their interactions would be required for optimal fabrication of mechanically strong, dimensionally accurate, and porous composite bone scaffolds. In this study, an image-based convolutional neural network (CNN) platform is presented with the aim to intelligently learn the complex dynamics of composite material deposition and ultimately predict scaffold porosity. In this study, the CNN model is trained on the basis of monochromatic images acquired from FDM-fabricated bone scaffolds via a high-resolution charge-coupled device (CCD) camera. The bone scaffolds were fabricated based on a medical-grade composite material, deposited using a converging microcapillary nozzle having a diameter of 800 μm with a deposition temperature, translation speed, and layer height of 225 °C, 15 mm/s, and 400 μm, respectively. The CNN model is utilized for in-process prediction of the morphological properties of the fabricated bone scaffolds. Overall, the outcomes of this study pave the way for smart, patient-specific fabrication of robust and porous bone scaffolds with tunable medical and functional properties.

The current study-within-a-trial explored individuals’ decisions to decline participation in research trialling a chronic illness-focused therapy (i.e. multiple sclerosis). Four themes were identified from seven semi-structured interviews with participation decliners and were confirmed by the host trial’s Patient & Public Involvement (PPI) panel: acknowledgement of the value of research; ‘fit’ of the study; misinterpretation of participant information; and ‘ignorance is bliss’ – discussed in light of theory and research. This study-within-a-trial extends research on trial recruitment and participation decline; while also suggesting that PPI can be utilised in both a practical and impactful manner. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study-within-a-trial was conducted within research funded by the Health Research Board (Ireland) under a Definitive Interventions and Feasibility Award (DIFA-FA-2018-027). peer-reviewed

The goal of this research work is to fabricate mechanically robust, porous, and biocompatible bone scaffolds with textured surfaces (for cell/tissue adhesion) for the treatment of osseous fractures. The objective of the work is to investigate the mechanical properties of triply periodic minimal surface (TPMS) bone scaffolds, fabricated using fused deposition modeling (FDM) additive manufacturing process, based on a medical grade composite composed of polyamide, polyolefin, and cellulose fibers. FDM has emerged as a high-resolution method for the fabrication of biological tissues and constructs. FDM allows for non-contact, multi-material deposition of functional materials for tissue engineering applications. However, the FDM process is intrinsically complex; the complexity of the process, largely, stems from complex physical phenomena and material-process interactions, which may adversely influence the mechanical properties, the surface morphology, and ultimately the functional characteristics of fabricated bone scaffolds. Consequently, physics-based material and process characterization would be an inevitable need. In this study, seven TPMS bone scaffolds were fabricated, based on the medical-grade polymer composite. The compression properties of the fabricated bone scaffolds were measured using a compression testing machine. The outcomes of this study pave the way for the fabrication of complex composite bone scaffolds with tunable medical and functional properties.

We develop a measure of labour market opportunities for heterogenous types of worker, exploiting information on their suitability different jobs encoded in historical patterns of worker mobility.We provide a theoretical foundation for our measure, which features naturally in a general random search framework. Our measure is flexible in the sense that it admits general definitions of worker and job heterogeneity, and is easily implementable empirically with data on worker mobility and labour demand. We apply our measure to high-quality data on labour demand in the UK, based on the universe of 104.7 million job adverts posted online from January 2015 to June 2021. We demonstrate the utility of our measure with an analysis of worker prospects throughout the Covid-19 pandemic. First, while the direct impact of lockdown policies was concentrated on relatively few industries, labour demand fell much more broadly. And, as our measure highlights,the full effects were broader still because of the disruption to usual career progression, even for those in less -affected sectors such as healthcare. Second, despite aggregate labour demand returning to pre-pandemic levels by June 2021, 25% of the work force faced new job opportunities more than 10% below pre-pandemic levels. This is because of a change in the composition of vacancy postings (towards lower-paying occupations) which our measure of labour market opportunities is sensitive to. Finally,the majority (64%) of unemployed workers faced at least 10% more competition for jobs from unemployed job seekers than before the pandemic.

This paper examines the major changes to the face of poverty in Great Britain over the past few decades, assessing the role of policy, and compares and contrasts this with the patterns seen in the United States, using harmonised household survey data. There are various commonalities between the countries, including a shift in the composition of those in poverty towards working‐age households without children, who have not been the focus of policy attention. There are also big differences, with a steadily increasing share of poverty in Great Britain – but a stable share in the United States – found in households with an adult in paid work. This perhaps explains why the anti‐poverty focus in Great Britain is now squarely on the plight of working households, while in the United States it is focused on labour force participation among the low skilled – even though, as we show, the United States has, for decades, been accustomed to in‐work poverty comprising a significantly higher proportion of overall poverty than in Great Britain.

In this study, we document the evolution of the gender pay gap in the UK over the past three decades and its association with fertility, examining the role of various differences in career patterns between men and women and how they change with the arrival of the first child. We show that differences in accumulated years of labour market experience play an important role, while differences in industry, occupation, and job characteristics explain less, conditional on working experience. We develop an empirical wage model to estimate the causal effect of working experience on the wages of women. Estimates from this model are then used to simulate two counterfactual scenarios in which women who are employed always work full-time, or women’s rates of both part-time and full-time work are the same as men’s. We find that differences in working experience explain up to two-thirds of the gender pay gap of college graduates 20 years after the first childbirth, and that the gap is largely driven by differences in full-time experience. The role of working experience is more moderate for individuals with no college education, but it can still account for about one-third of the overall long-term gender wage gap.

In this Open Letter we present reflections from three different perspectives on the integration of public and patient involvement (PPI) in a research trial. We reflect on the experience of having a patient employed as a contract researcher, with no prior research experience, on a feasibility trial of cognitive rehabilitation in multiple sclerosis. This Open Letter is written by the PPI research team member with reflections from a researcher on the trial and the principle investigator. We will discuss some of the changes made and the impacts that have been resulted from of PPI input into the trial. We focus on PPI involvement in participant recruitment, the development of trial material, integration of PPI along the research cycle, and collaboration. We hope that this Open Letter will encourage principle investigators and groups to include PPI members as part of the research team and help patients and members of the public understand what the experience of PPI members is like We would like to thank the wider PPI advisory group to the COB-MS trial and PPI Ignite at NUI Galway for their ongoing support throughout the trial. Thank you also to MS Ireland for their continued support throughout. peer-reviewed

Inheritances have been growing as a share of national income in the UK since the 1970s. This trend looks set to continue as generations at older ages hold more wealth than their immediate predecessors but younger generations have no higher incomes than the generations born just before them. What will this mean for inequalities in living standards and wealth? Does the growth in inheritances mean people's living standards will increasingly be determined by who their parents are? If people anticipate that they are going to inherit in future, could that influence their decisions about how much to spend and save today? New IFS research, released today and funded by the Nuffield foundation, makes projections of the inheritances to be received by the 1960s, 1970s and 1980s-born generations in the UK.

This paper describes the development, evaluation, and applications of the CMORPH satellite global precipitation estimates.

This paper brings together evidence from various data sources and the most recent studies to describe what we know so far about the impacts of the COVID‐19 crisis on inequalities across several key domains of life, including employment and ability to earn, family life and health. We show how these new fissures interact with existing inequalities along various key dimensions, including socio‐economic status, education, age, gender, ethnicity and geography. We find that the deep underlying inequalities and policy challenges that we already had are crucial in understanding the complex impacts of the pandemic itself and our response to it, and that the crisis does in itself have the potential to exacerbate some of these pre‐existing inequalities fairly directly. Moreover, it seems likely that the current crisis will leave legacies that will impact inequalities in the long term. These possibilities are not all disequalising, but many are.

Interest in the issue of career progression has been growing, fuelled by a decade of stagnant productivity and pay growth (even before the [Coronavirus 2019] COVID-19 crisis) and concerns that changes in the labour market - such as the casualisation of work in the gig economy - are making it harder for some groups to progress. However, debate on this topic is taking place in the absence of much hard evidence on the question at its core; we actually know very little about how pay and career progression have been changing. Here we provide new evidence on how pay and occupational progression during the crucial early stages of careers have changed over the last few decades.

This report examines the inheritances that are likely to be received by those living in England who were born in the 1960s, 1970s and 1980s. We explore the age at which inheritances are likely to be received and the amounts that we expect to be inherited, focusing on key inequalities in each. All figures are in 2017-18 prices.

The COVID‐19 pandemic is having a dramatic economic impact in most countries. In the UK, it has led to sharp falls in labour demand in many sectors of the economy and to initial acute labour shortages in other sectors. Much more than in a typical downturn, the current crisis is not simply a general slowdown in economic activity but also a radical short‐term shift in the mix of economic activities – of which an unknown, but possibly significant, amount will be persistent. The initial policy response has focused on cushioning the blow to families’ finances and allowing the majority of workers and firms to resume their original activities once the crisis subsides. These are crucial priorities. But there should also be a focus on reallocating some workers, either temporarily if working in shut‐down sectors or permanently by facilitating transitions to sectors and jobs offering better prospects and facing labour shortages. The phasing‐out of the furlough subsidies, which is projected to happen in Autumn 2020, brings this into even sharper focus since the alternative for many workers will be unemployment. Active labour market policy will need to be front and centre.

There is growing evidence that economic consequences of the [Coronavirus Disease 2019] COVID-19 pandemic are particularly negative for young people. On the eve of the coronavirus outbreak, workers aged below 25 were more likely than other workers to be employed in sectors that have been effectively shut down as part of the UK lockdown and they are more likely to have lost their jobs since then. This note shows that the economic repercussions of the pandemic threaten to severely disrupt the career progression of young workers, which suggests negative economic impacts on this age group may last well beyond the easing of the lockdown.

Governments are starting to ease restrictions to economic activity. The risks of easing these measures too soon, or in misguided ways, are obvious, not only for public health but also for the economy. A world with no lockdown and a [Coronavirus Disease 2019 (COVID-19)] pandemic spreading rapidly through the population does not make for a healthy economy; nor, in all likelihood, does a world in which containment measures have to be repeatedly reinstated after being eased prematurely or in suboptimal ways. We discuss some key economic issues that the UK government needs to face when thinking about how best to get people back into work: we assemble some basic empirical evidence, identify some challenges that policymakers will need to confront, and discuss some policy considerations.

The Version 06 Global Precipitation Measurement (GPM) mission products were completed over the last year, capping five years of development since the launch of the GPM Core Observatory, and covering the joint Tropical Rainfall Measuring Mission (TRMM) and GPM eras with consistently processed algorithms. The U.S. GPM team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product enforces a consistent intercalibration for all precipitation products computed from individual satellites with the TRMM and GPM Core Observatory sensors as the TRMM- and GPM-era calibrators, respectively, and incorporates monthly surface gauge data in the Final (research) product. Mid-latitude calibrations during the TRMM era necessarily are more approximate because TRMM only covered the latitude band 35°N-S, while GPM covers 65°N-S. Starting in V06, IMERG employs precipitation motion vectors (used to drive the quasi-Lagrangian interpolation, or “morphing”) that are computed by tracking the vertically integrated vapor as analyzed in MERRA2 and GEOS FP. This approach covers the entire globe, expanding coverage beyond the 60°N-S latitude band provided by IR-based vectors in previous versions, although we choose to mask out microwave-based precipitation over snowy/icy surfaces as unreliable.We will provide examples of performance for the V06 IMERG products, including comparison with the long-term record of GPCP and TMPA, showing higher values by about 8% in the latitude band 50°N-S over oceans; diurnal cycle, demonstrating improvement over previous versions; and daily precipitation PDFs for the entire record, showing a shift at the TRMM/GPM boundary, as well as interannual variations. These analyses have important implications for the utility of V06 IMERG data for long-record calculations. Finally, we will review the retirement of the predecessor TMPA multi-satellite dataset.

Background Cognitive difficulties experienced by people with multiple sclerosis (MS) impact their quality of life and daily functioning, from childcare and work, to social and self-care activities. Despite the high prevalence of cognitive difficulties seen in MS, there is a lack of developed programmes that target cognition, while also supporting patients by helping them to function well in everyday life. The Cognitive Occupation-Based programme for people with MS (COB-MS) was developed as a holistic, individualised cognitive rehabilitation intervention. It addresses the wide-ranging symptoms and functional difficulties that present in MS, including the ability to maintain employment, social activities, home management and self-care. The aim of the current research is to evaluate the feasibility and preliminary efficacy of COB-MS for people with MS. The focus is on feasibility outcomes as well as functioning associated with cognitive difficulty and secondary outcomes related to cognition, fatigue and quality of life. Methods One hundred and twenty people with MS will be assigned to participate in either the COB-MS programme or a treatment as usual, wait-list control group as part of this single-blind, cluster-randomised controlled feasibility and preliminary efficacy trial of the COB-MS programme. The COB-MS group will participate in an eight-session occupational-based cognitive rehabilitation programme over 9 weeks. The primary outcome measure is the goal attainment scaling at 12 weeks. Participants will be assessed pre-intervention, post-intervention and at 12 weeks post-intervention and 6 months post-intervention. Qualitative evaluations of participants’ perspectives will also be examined as part of the feasibility study. Discussion Results will provide recommendations for a future definitive trial of COB-MS, with respect to both feasibility and preliminary, clinical efficacy. In the event that results indicate efficacy, study findings will suggest that COB-MS requires consideration as a means of enhancing cognitive and daily functioning in people living with MS. Trial registration ISRCTN: ISRCTN11462710. Registered on 9 September 2019.