The Prophet Elijah as an Agent of Change for Community Development

Modern christian leaders can become involved as agents of change in their communities, specifically in ways demonstrated by principles of community development seen in the Old testament prophet Elisha’s miracles. According to christ’s teachings (Luke 12:32-34), the mission of christians is not just going to church every weekend and participating in internal church programs; it involves taking care of the needs of the community outside the church as well. 2 Kings 1-8 details the Prophet Elisha’s actions as he dealt with different issues that occurred in his community—some involving only individuals and others affecting the whole community

Understanding the training and education needs of homecare workers supporting people with dementia and cancer: a systematic review of reviews

Many people with dementia, supported by family carers, prefer to live at home and may rely on homecare support services. People with dementia are also often living with multimorbidities, including cancer. The main risk factor for both cancer and dementia is age and the number of people living with dementia and cancer likely to rise. Upskilling the social care workforce to facilitate more complex care is central to national workforce strategies and challenges. Training and education development must also respond to the key requirements of a homecare workforce experiencing financial, recruitment and retention difficulties. This systematic review of reviews provides an overview of dementia and cancer training and education accessible to the homecare workforce. Findings reveal there is a diverse range of training and education available, with mixed evidence of effectiveness. Key barriers and facilitators to effective training and education are identified in order to inform future training, education and learning development for the homecare workforce supporting people with dementia and cancer

The Effect of Medicare Eligibility on Spousal Insurance Coverage

A majority of married couples in the United States take advantage of the fact that employers often provide health insurance coverage to spouses. When the older spouses become eligible for Medicare, however, many of them can no longer provide their younger spouses with coverage. In this paper, we study how spousal eligibility for Medicare affects the health insurance and health care access of the younger spouse. We find spousal eligibility for Medicare results in the younger spouse having worse insurance coverage and reduced access to health care services

Firms’ knowledge search and local knowledge externalities in innovation performance

We use an augmented version of the UK Innovation Surveys 4–7 to explore firm-level and local area openness externalities on firms’ innovation performance. We find strong evidence of the value of external knowledge acquisition both through interactive collaboration and non-interactive contacts such as demonstration effects, copying or reverse engineering. Levels of knowledge search activity remain well below the private optimum, however, due perhaps to informational market failures. We also find strong positive externalities of openness resulting from the intensity of local interactive knowledge search—a knowledge diffusion effect. However, there are strong negative externalities resulting from the intensity of local non-interactive knowledge search—a competition effect. Our results provide support for local initiatives to support innovation partnering and counter illegal copying or counterfeiting. We find no significant relationship between either local labour quality or employment composition and innovative outputs

A comparison of five surface mixed layer models with a year of observations in the North Atlantic

Five upper ocean mixed layer models driven by ERA-Interim surface forcing are compared with a year of hydrographic observations of the upper 1000 m, taken at the Porcupine Abyssal Plain observatory site using profiling gliders. All the models reproduce sea surface temperature (SST) fairly well, with annual mean warm biases of 0.11  ° C (PWP model), 0.24  ° C (GLS), 0.31  ° C (TKE), 0.91  ° C (KPP) and 0.36  ° C (OSMOSIS). The main exception is that the KPP model has summer SSTs which are higher than the observations by nearly 3 ° . Mixed layer salinity (MLS) is not reproduced well by the models and the biases are large enough to produce a non-trivial density bias in the Eastern North Atlantic Central Water which forms in this region in winter. All the models develop mixed layers which are too deep in winter, with average winter mixed layer depth (MLD) biases between 160 and 228 m. The high variability in winter MLD is reproduced more successfully by model estimates of the depth of active mixing and/or boundary layer depth than by model MLD based on water column properties. After the spring restratification event, biases in MLD are small and do not appear to be related to the preceding winter biases. There is a very clear relationship between MLD and local wind stress in all models and in the observations during spring and summer, with increased wind speeds leading to deepening mixed layers, but this relationship is not present during autumn and winter. We hypothesize that the deepening of the MLD in autumn is so strongly driven by the annual cycle in surface heat flux that the winds are less significant in the autumn. The surface heat flux drives a diurnal cycle in MLD and SST from March onwards, though this effect is much more significant in the models than in the observations. We are unable to identify one model as definitely better than the others. The only clear differences between the models are KPP’s inability to accurately reproduce summer SSTs, and the OSMOSIS model’s more accurate reproduction of MLS

A MHz X-ray diffraction set-up for dynamic compression experiments in the diamond anvil cell

An experimental platform for dynamic diamond anvil cell (dDAC) research has been developed at the High Energy Density (HED) Instrument at the European X-ray Free Electron Laser (European XFEL). Advantage was taken of the high repetition rate of the European XFEL (up to 4.5 MHz) to collect pulse-resolved MHz X-ray diffraction data from samples as they are dynamically compressed at intermediate strain rates (≤103 s−1), where up to 352 diffraction images can be collected from a single pulse train. The set-up employs piezo-driven dDACs capable of compressing samples in ≥340 µs, compatible with the maximum length of the pulse train (550 µs). Results from rapid compression experiments on a wide range of sample systems with different X-ray scattering powers are presented. A maximum compression rate of 87 TPa s−1 was observed during the fast compression of Au, while a strain rate of ∼1100 s−1 was achieved during the rapid compression of N2 at 23 TPa s−1

The IASLC Early Lung Imaging Confederation (ELIC) Open-Source Deep Learning and Quantitative Measurement Initiative.

BackgroundWith global adoption of CT lung cancer screening, there is increasing interest to use artificial intelligence (AI) deep learning methods to improve the clinical management process. To enable AI research using an open source, cloud-based, globally distributed, screening CT imaging dataset and computational environment that are compliant with the most stringent international privacy regulations that also protects the intellectual properties of researchers, the International Association of the Study of Lung Cancer (IASLC) sponsored development of the Early Lung Imaging Confederation (ELIC) resource in 2018. The objective of this report is to describe the updated capabilities of ELIC and illustrate how this resource can be utilized for clinically relevant AI research.MethodsIn this second Phase of the initiative, metadata and screening CT scans from two time points were collected from 100 screening participants in seven countries. An automated deep learning AI lung segmentation algorithm, automated quantitative emphysema metrics, and a quantitative lung nodule volume measurement algorithm were run on these scans.ResultsA total of 1,394 CTs were collected from 697 participants. The LAV950 quantitative emphysema metric was found to be potentially useful in distinguishing lung cancer from benign cases using a combined slice thickness ≥ 2.5 mm. Lung nodule volume change measurements had better sensitivity and specificity for classifying malignant from benign lung nodules when applied to solid lung nodules from high quality CT scans.ConclusionThese initial experiments demonstrated that ELIC can support deep learning AI and quantitative imaging analyses on diverse and globally distributed cloud-based datasets

Integrated genomic characterization of pancreatic ductal adenocarcinoma

We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine