Work stress in NHS employees: a mixed-methods study

The United Kingdom’s National Health Service (NHS) has a higher-than-average level of stress-related sickness absence of all job sectors in the country. It is important that this is addressed as work stress is damaging to employees and the organisation, and subsequently impacts patient care. The aim of this study was to gain an in-depth understanding of working conditions and wellbeing in NHS employees from three employing NHS Trusts through a mixed-methods investigation. First, a cross-sectional organisational survey was completed by 1644 respondents. Questions examined working conditions, stress, psychological wellbeing, job satisfaction, and presenteeism. This was followed by 33 individual semistructured interviews with NHS staff from a variety of clinical and nonclinical roles. Quantitative findings revealed that working conditions were generally positive, although most staff groups had high levels of workload. Regression outcomes demonstrated that a number of working conditions influenced mental wellbeing and stress. Three themes were generated from thematic analysis of the interview data: wellbeing at work, relationships, and communication. These highlight areas which may be contributing to workplace stress. Suggestions are made for practical changes which could improve areas of difficulty. Such changes could improve staff wellbeing and job satisfaction and reduce sickness absence

Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008) vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI) and the recently developed passive-microwave-based Vegetation Optical Depth (VOD). The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO₂ level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics

Blending Landsat and MODIS Data to Generate Multispectral Indices: A Comparison of “Index-then-Blend” and “Blend-then-Index” Approaches

The objective of this paper was to evaluate the accuracy of two advanced blending algorithms, Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to downscale Moderate Resolution Imaging Spectroradiometer (MODIS) indices to the spatial resolution of Landsat. We tested two approaches: (i) "Index-then-Blend" (IB); and (ii) "Blend-then-Index" (BI) when simulating nine indices, which are widely used for vegetation studies, environmental moisture assessment and standing water identification. Landsat-like indices, generated using both IB and BI, were simulated on 45 dates in total from three sites. The outputs were then compared with indices calculated from observed Landsat data and pixel-to-pixel accuracy of each simulation was assessed by calculating the: (i) bias; (ii) R; and (iii) Root Mean Square Deviation (RMSD). The IB approach produced higher accuracies than the BI approach for both blending algorithms for all nine indices at all three sites. We also found that the relative performance of the STARFM and ESTARFM algorithms depended on the spatial and temporal variances of the Landsat-MODIS input indices. Our study suggests that the IB approach should be implemented for blending of environmental indices, as it was: (i) less computationally expensive due to blending single indices rather than multiple bands; (ii) more accurate due to less error propagation; and (iii) less sensitive to the choice of algorithm

Wind speed variability over the Canary Islands, 1948-2014: focusing on trend differences at the land-ocean interface and below-above the trade-wind inversion layer

This study simultaneously examines wind speed trends at the land?ocean interface, and below?above the trade-wind inversion layer in the Canary Islands and the surrounding Eastern North Atlantic Ocean: a key region for quantifying the variability of trade-winds and its response to large-scale atmospheric circulation changes. Two homogenized data sources are used: (1) observed wind speed from nine land-based stations (1981?2014), including one mountain weather station (Izaña) located above the trade-wind inversion layer; and (2) simulated wind speed from two atmospheric hindcasts over ocean (i.e., SeaWind I at 30 km for 1948?2014; and SeaWind II at 15 km for 1989?2014). The results revealed a widespread significant negative trend of trade-winds over ocean for 1948?2014, whereas no significant trends were detected for 1989?2014. For this recent period wind speed over land and ocean displayed the same multi-decadal variability and a distinct seasonal trend pattern with a strengthening (late spring and summer; significant in May and August) and weakening (winter?spring?autumn; significant in April and September) of trade-winds. Above the inversion layer at Izaña, we found a predominance of significant positive trends, indicating a decoupled variability and opposite wind speed trends when compared to those reported in boundary layer. The analysis of the Trade Wind Index (TWI), the North Atlantic Oscillation Index (NAOI) and the Eastern Atlantic Index (EAI) demonstrated significant correlations with the wind speed variability, revealing that the correlation patterns of the three indices showed a spatio-temporal complementarity in shaping wind speed trends across the Eastern North Atlantic.C. A. -M. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 703733 (STILLING project). This research was also supported by the Research Projects: Swedish BECC, MERGE, VR (2014–5320), PCIN-2015-220, CGL2014-52135-C03-01 and Red de variabilidad y cambio climático RECLIM (CGL2014-517221-REDT). M.M is indebted to the Spanish Government for funding through the “Ramón y Cajal” program and supported by Grant PORTIO (BIA2015-70644-R

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

Mutational and Structural Analysis of KIR3DL1 Reveals a Lineage-Defining Allotypic Dimorphism That Impacts Both HLA and Peptide Sensitivity

Killer Ig-like receptors (KIRs) control the activation of human NK cells via interactions with peptide-laden HLAs. KIR3DL1 is a highly polymorphic inhibitory receptor that recognizes a diverse array of HLA molecules expressing the Bw4 epitope, a group with multiple polymorphisms incorporating variants within the Bw4 motif. Genetic studies suggest that KIR3DL1 variation has functional significance in several disease states, including HIV infection. However, owing to differences across KIR3DL1 allotypes, HLA-Bw4, and associated peptides, the mechanistic link with biological outcome remains unclear. In this study, we elucidated the impact of KIR3DL1 polymorphism on peptide-laden HLA recognition. Mutational analysis revealed that KIR residues involved in water-mediated contacts with the HLA-presented peptide influence peptide binding specificity. In particular, residue 282 (glutamate) in the D2 domain underpins the lack of tolerance of negatively charged C-terminal peptide residues. Allotypic KIR3DL1 variants, defined by neighboring residue 283, displayed differential sensitivities to HLA-bound peptide, including the variable HLA-B*57:01-restricted HIV-1 Gag-derived epitope TW10. Residue 283, which has undergone positive selection during the evolution of human KIRs, also played a central role in Bw4 subtype recognition by KIR3DL1. Collectively, our findings uncover a common molecular regulator that controls HLA and peptide discrimination without participating directly in peptide-laden HLA interactions. Furthermore, they provide insight into the mechanics of interaction and generate simple, easily assessed criteria for the definition of KIR3DL1 functional groupings that will be relevant in many clinical applications, including bone marrow transplantation

Rapid urbanization induced daily maximum wind speed decline in metropolitan areas: A case study in the Yangtze River Delta (China)

Wind extremes cause many environmental and natural hazard related problems globally, particularly in heavily populated metropolitan areas. However, the underlying causes of maximum wind speed variability in urbanized regions remain largely unknown. Here, we investigated how rapid urbanization in the Yangtze River Delta (YRD), China, impacted daily maximum wind speed (DMWS) between 1990 and 2015, based on near-surface (10 m height) DMWS observations, reanalysis datasets, and night-time lighting data (a proxy for urbanization). The station observation shows that annual DMWS in the YRD significantly (p 0.1) positive trends were found in NCEP-NCAR1 (+0.048 m s−1 decade−1) and ERA5 (+0.027 m s−1 decade−1). An increasing divergence between the reanalysis output and the station observation since 2005 was found, and those stations located in areas with high rates of urbanization show the strongest negative annual DMWS trend, implying the key role of urbanization in weakening DMWS. This finding is supported by sensitivity experiments conducted using a regional climate model (RegCM4) forced with both 1990 and 2015 land-use and land-cover (LULC) data, where the simulated DMWS using the 2015 LULC data was lower than that simulated using the 1990 LULC data.This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, Grant No. 2019QZKK0606), the National Natural Science Foundation of China (Grant No. 42101027 and No.41621061). This work was also supported by a Swedish Research Council (2017-03780) and a Swedish Research Council for Sustainable Development (2019-00509) grant, and by the IBER-STILLING project, funded by the Spanish Ministry of Science, Innovation and Universities (RTI2018-095749-A-I00; MCIU/AEI/FEDER, UE). C.A.M. was supported by a Ramon y Cajal fellowship (RYC-2017-22830). L.M. was founded by the International Postdoc grant from the Swedish Research Council (2021-00444)

Exploring the feasibility of a 6-week electric-bike intervention with behavioural support in Australia.

Background: Physical inactivity increases the risk of non-communicable disease development and healthcare-associated burden. Research suggests electric bikes (e-bikes) can support individuals in meeting recommended physical activity (PA) guidelines. This study assessed the feasibility of an e-bike plus a tailored behavioural support intervention for physically inactive overweight or obese adults. Methods: This non-randomized single-group pre-post study saw participants provided with an e-bike free of charge for six weeks. Feasibility was assessed across five domains: 1) feasibility of recruitment, 2) participant retention, 3) intervention adherence, 4) acceptability of questionnaires and lab-based outcome measures and 5) intervention acceptability. Participants completed self-reported measures of PA and self-efficacy for exercise. Lab-based measurements were completed pre-and post-intervention, this included blood pressure, body composition [anthropometrics and dual-energy X-ray absorptiometry (DEXA)], venous blood glucose, insulin, cholesterol, triglycerides, and cardiorespiratory fitness. Results: Our recruitment strategy saw a total of eight participants (three males and five females) complete the intervention (88.9% retention rate). Participants utilised the e-bike for the intervention duration and rode a mean distance of 299.8 km (SD ± 172.2) over the 6-week intervention period. Participants completed all outcomes with minimal data points missing. Participants’ moderate PA levels and self-efficacy for exercise increased post intervention. Lab-based measures showed a downward trend in body fat percentage, fasting blood glucose and brachial diastolic blood pressure. Conclusion: The recruitment strategy, retention, adherence and acceptability of this study support future research. E-bikes are an acceptable way to help people who are physically inactive increase their PA levels. Furthermore, sustained use may contribute to health benefits and improve overall self-efficacy for exercise