A case study of joint procurement and provision of legal services to a group of a universities in the midlands

A Group of 5 UK Universities in the Midlands undertook a joint procurement process for the provision of Legal Services. The objective was to put in place common Framework Agreements. The Legal Services procured were divided into six lots and one of these was 'Property and Construction'. The lots were assembled into three packages and the contract for each package was awarded to one or more Service Providers. Albeit a service provider is to work for all the collaborating Universities. A competitive 'restricted' two-stage tender process was administered in accordance with the Public Contracts Regulations 2006, SI 2006/5. The Framework Agreements were awarded in 2012 to the most economically advantageous Solicitors' Practices. The participating Universities are being interviewed about the reasons for the joint procurement exercise, any challenges faced in its implementation and lessons learnt so far. Two interviews have been conducted so far and evaluated via content analysis to reveal that advantages to be gained from 'economy of scale' were the main impetus for the collaborative procurement. The negotiations between the Universities which led to the establishment of the collaboration and its subsequent sustenance have been friendly. The challenge identified so far concerns how to distribute work more fairly to legal services providers

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers

Aerosol Data Sources and Their Roles within PARAGON

We briefly but systematically review major sources of aerosol data, emphasizing suites of measurements that seem most likely to contribute to assessments of global aerosol climate forcing. The strengths and limitations of existing satellite, surface, and aircraft remote sensing systems are described, along with those of direct sampling networks and ship-based stations. It is evident that an enormous number of aerosol-related observations have been made, on a wide range of spatial and temporal sampling scales, and that many of the key gaps in this collection of data could be filled by technologies that either exist or are expected to be available in the near future. Emphasis must be given to combining remote sensing and in situ active and passive observations and integrating them with aerosol chemical transport models, in order to create a more complete environmental picture, having sufficient detail to address current climate forcing questions. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative would provide an organizational framework to meet this goal

Mental and substance use disorders in sub-saharan Africa: predictions of epidemiological changes and mental health workforce requirements for the next 40 years

The world is undergoing a rapid health transition, with an ageing population and disease burden increasingly defined by disability. In Sub-Saharan Africa the next 40 years are predicted to see reduced mortality, signalling a surge in the impact of chronic diseases. We modelled these epidemiological changes and associated mental health workforce requirements. Years lived with a disability (YLD) predictions for mental and substance use disorders for each decade from 2010 to 2050 for four Sub-Saharan African regions were calculated using Global Burden of Disease 2010 study (GBD 2010) data and UN population forecasts. Predicted mental health workforce requirements for 2010 and 2050, by region and for selected countries, were modelled using GBD 2010 prevalence estimates and recommended packages of care and staffing ratios for low- and middle-income countries, and compared to current staffing from the WHO Mental Health Atlas. Significant population growth and ageing will result in an estimated 130% increase in the burden of mental and substance use disorders in Sub-Saharan Africa by 2050, to 45 million YLDs. As a result, the required mental health workforce will increase by 216,600 full time equivalent staff from 2010 to 2050, and far more compared to the existing workforce. The growth in mental and substance use disorders by 2050 is likely to significantly affect health and productivity in Sub-Saharan Africa. To reduce this burden, packages of care for key mental disorders should be provided through increasing the mental health workforce towards targets outlined in this paper. This requires a shift from current practice in most African countries, involving substantial investment in the training of primary care practitioners, supported by district based mental health specialist teams using a task sharing model that mobilises local community resources, with the expansion of inpatient psychiatric units based in district and regional general hospitals

Do frailty and comorbidity indices improve risk prediction of 28-day ED reattendance? Reanalysis of an ED discharge nomogram for older people

Background: In older people, quantification of risk of reattendance after emergency department (ED) discharge is important to provide adequate post ED discharge care in the community to appropriately targeted patients at risk. Methods: We reanalysed data from a prospective observational study, previously used for derivation of a nomogram for stratifying people aged 65 and older at risk for ED reattendance. We investigated the potential effect of comorbidity load and frailty by adding the Charlson or Elixhauser comorbidity index and a ten-item frailty measure from our data to develop four new nomograms. Model I and model F built on the original nomogram by including the frailty measure with and without the addition of the Charlson comorbidity score; model E adapted for efficiency in the time-constrained environment of ED was without the frailty measure; and model P manually constructed in a purposeful stepwise manner and including only statistically significant variables. Areas under the ROC curve of models were compared. The primary outcome was any ED reattendance within 28 days of discharge. Results: Data from 1357 patients were used. The point estimate of the respective areas under ROC were 0.63 (O), 0.63 (I), 0.68 (E), 0.71 (P) and 0.63 (F). Conclusion: Addition of a comorbidity index to our previous model improves stratifying elderly at risk of ED reattendance. Our frailty measure did not demonstrate any additional predictive benefit

Reply to ''Comments on 'Why Hasn't Earth Warmed as much as Expected?'''

In response to our article, Why Hasnt Earth Warmed as Much as Expected? (2010), Knutti and Plattner (2012) wrote a rebuttal. The term climate sensitivity is usually defined as the change in global mean surface temperature that is produced by a specified change in forcing, such as a change in solar heating or greenhouse gas concentrations. We had argued in the 2010 paper that although climate models can reproduce the global mean surface temperature history over the past century, the uncertainties in these models, due primarily to the uncertainty in climate forcing by airborne particles, mean that the models lack the confidence to actually constrain the climate sensitivity within useful limits for climate prediction. Knutti and Plattner are climate modelers, and they argued essentially that because the models could reproduce the surface temperature history, the issue we raised was moot. Our response amounts to straightening out this confusion; for the models to be constraining, they must be able to reproduce the surface temperature history with sufficient confidence, not just to match the measurements, but to exclude alternative histories. As before, we concluded that if we can actually make the aerosol measurements using currently available, state-of-the-art techniques, we can determine the aerosol climate forcing to the degree required to constrain that aspect of model climate sensitivity. A technical issue relating to the timescale over which a change in CO2 emissions would be equilibrated in the environmental energy balance was also discussed, again, a matter of differences in terminology

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

Microarray analysis of iron deficiency chlorosis in near-isogenic soybean lines

BACKGROUND: Iron is one of fourteen mineral elements required for proper plant growth and development of soybean (Glycine max L. Merr.). Soybeans grown on calcareous soils, which are prevalent in the upper Midwest of the United States, often exhibit symptoms indicative of iron deficiency chlorosis (IDC). Yield loss has a positive linear correlation with increasing severity of chlorotic symptoms. As soybean is an important agronomic crop, it is essential to understand the genetics and physiology of traits affecting plant yield. Soybean cultivars vary greatly in their ability to respond successfully to iron deficiency stress. Microarray analyses permit the identification of genes and physiological processes involved in soybean's response to iron stress. RESULTS: RNA isolated from the roots of two near isogenic lines, which differ in iron efficiency, PI 548533 (Clark; iron efficient) and PI 547430 (IsoClark; iron inefficient), were compared on a spotted microarray slide containing 9,728 cDNAs from root specific EST libraries. A comparison of RNA transcripts isolated from plants grown under iron limiting hydroponic conditions for two weeks revealed 43 genes as differentially expressed. A single linkage clustering analysis of these 43 genes showed 57% of them possessed high sequence similarity to known stress induced genes. A control experiment comparing plants grown under adequate iron hydroponic conditions showed no differences in gene expression between the two near isogenic lines. Expression levels of a subset of the differentially expressed genes were also compared by real time reverse transcriptase PCR (RT-PCR). The RT-PCR experiments confirmed differential expression between the iron efficient and iron inefficient plants for 9 of 10 randomly chosen genes examined. To gain further insight into the iron physiological status of the plants, the root iron reductase activity was measured in both iron efficient and inefficient genotypes for plants grown under iron sufficient and iron limited conditions. Iron inefficient plants failed to respond to decreased iron availability with increased activity of Fe reductase. CONCLUSION: These experiments have identified genes involved in the soybean iron deficiency chlorosis response under iron deficient conditions. Single linkage cluster analysis suggests iron limited soybeans mount a general stress response as well as a specialized iron deficiency stress response. Root membrane bound reductase capacity is often correlated with iron efficiency. Under iron-limited conditions, the iron efficient plant had high root bound membrane reductase capacity while the iron inefficient plants reductase levels remained low, further limiting iron uptake through the root. Many of the genes up-regulated in the iron inefficient NIL are involved in known stress induced pathways. The most striking response of the iron inefficient genotype to iron deficiency stress was the induction of a profusion of signaling and regulatory genes, presumably in an attempt to establish and maintain cellular homeostasis. Genes were up-regulated that point toward an increased transport of molecules through membranes. Genes associated with reactive oxidative species and an ROS-defensive enzyme were also induced. The up-regulation of genes involved in DNA repair and RNA stability reflect the inhospitable cellular environment resulting from iron deficiency stress. Other genes were induced that are involved in protein and lipid catabolism; perhaps as an effort to maintain carbon flow and scavenge energy. The under-expression of a key glycolitic gene may result in the iron-inefficient genotype being energetically challenged to maintain a stable cellular environment. These experiments have identified candidate genes and processes for further experimentation to increase our understanding of soybeans' response to iron deficiency stress