Temperature-stable Gunn-diode oscillator

Oscillator consisting of Gunn diode embedded in coaxial circuit has excellent temperature stability and low fabrication costs as compared with automatic-frequency-control crystal oscillators

Extractable nitrogen and microbial community structure respond to grassland restoration regardless of historical context and soil composition.

Grasslands have a long history of invasion by exotic annuals, which may alter microbial communities and nutrient cycling through changes in litter quality and biomass turnover rates. We compared plant community composition, soil chemical and microbial community composition, potential soil respiration and nitrogen (N) turnover rates between invaded and restored plots in inland and coastal grasslands. Restoration increased microbial biomass and fungal : bacterial (F : B) ratios, but sampling season had a greater influence on the F : B ratio than did restoration. Microbial community composition assessed by phospholipid fatty acid was altered by restoration, but also varied by season and by site. Total soil carbon (C) and N and potential soil respiration did not differ between treatments, but N mineralization decreased while extractable nitrate and nitrification and N immobilization rate increased in restored compared with unrestored sites. The differences in soil chemistry and microbial community composition between unrestored and restored sites indicate that these soils are responsive, and therefore not resistant to feedbacks caused by changes in vegetation type. The resilience, or recovery, of these soils is difficult to assess in the absence of uninvaded control grasslands. However, the rapid changes in microbial and N cycling characteristics following removal of invasives in both grassland sites suggest that the soils are resilient to invasion. The lack of change in total C and N pools may provide a buffer that promotes resilience of labile pools and microbial community structure

High-performance Schottky diodes endure high temperatures

Fabrication process and aluminum/GaAs (gallium arsenide) coupling are used to produce Schottky diodes that have high cutoff frequencies and can withstand operating temperatures in excess of 500 C

A Markov chain model to enhanced the weather simulation capabilities of an operations and maintenance tool for a wave energy array

Operations and maintenance is a vital area of research in the push to make wave energy a commercial reality. A tool has previously been developed by Pelamis Wave Power to obtain reliable estimates for operational expenditure and ensure smooth running of wave energy arrays. Wave Energy Scotland is now tasked with the future development of this operations and maintenance tool. One of its key inputs is the wave and wind data used to simulate weather windows suitable for marine access. This paper details the creation and validation of a Markov Chain Model to enhance the weather simulation capabilities of the tool. This will ensure that the operations and maintenance strategy of wave energy arrays is modelled more realistically, resulting in an increased confidence in cost estimates and logistical arrangements.The author would like to thank the academic supervisors of this IDCORE project for their contributions, advice and support. Similar thanks must go to the engineers, past and present, who have dedicated their time to the Pelamis project. The industrial supervisor deserves a special mention, without her experience and guidance this study would not have been a success. The author would also like the IDCORE programme and its funding bodies, in particular the ETP (Energy Technology Partnership), for their support

Mathematical model of welding parameters for rapid prototyping using robot welding

Rapid Prototyping is a relatively new technology that allows the creation of prototypes in a very short period of time compared with traditional manufacturing techniques. First, a model of the prototype is drawn, using a computer aided design program, which is then mathematically ‘sliced’ and used to build the prototype layer by layer, using material such as paper, resins, or thermoplastics, depending on the process. The main disadvantage of these processes is that they do not allow metal as a raw material. Rapid Prototyping using Robot welding is another approach that overcomes this problem by using a welding robot that deposits metal. As the success of the final component quality depends very much on the welding parameters, it is important to automate their calculation. To automate the task of determining the welding parameters and to generate welded components with consistent quality, a very simple mathematical algorithm was created. The tests carried out to gather the necessary information to generate this model, the mathematical model itself, the limitations of the equations, and the tests to check their feasibility are described. At the time the work was carried out, the authors were in the welding Engineering Groups, SIMS, Cranfield University, Cranfield, Beds. MK43 0SY, UK. Dr Ribeiro is now in the Department of Industrial Electronics, University of Minho, 4800 Guimarães, Portugal and Professor Norrish is in the Faculty of Engineering, University of Wollongong, Wollongong, NSW 2522, Australia. Manuscript received 12 May 1997; in final form 20 June 1997

Does anxiety predict the use of urgent care by people with long term conditions? A systematic review with meta-analysis

Objective: The role of anxiety in the use of urgent care in people with long term conditions is not fully understood. A systematic review was conducted with meta-analysis to examine the relationship between anxiety and future use of urgent healthcare among individuals with one of four long term conditions: diabetes; coronary heart disease, chronic obstructive pulmonary disease and asthma. Methods: Electronic searches of MEDLINE, EMBASE, PSYCINFO, CINAHL, the British Nursing Library and the Cochrane Library were conducted These searches were supplemented by hand-searching bibliographies, citation tracing eligible studies and asking experts within the field about relevant studies. Studies were eligible for inclusion if they: a) used a standardised measure of anxiety, b) used prospective cohort design, c) included adult patients diagnosed with coronary heart disease (CHD), asthma, diabetes or chronic obstructive pulmonary disease (COPD), d) assessed urgent healthcare use prospectively. Data regarding participants, methodology, and association between anxiety and urgent care use was extracted from studies eligible for inclusion. Odds ratios were calculated for each study and pooled using random effects models. Results: 8 independent studies were identified for inclusion in the meta-analysis, with a total of 28,823 individual patients. Pooled effects indicate that anxiety is not associated with an increase in the use of urgent care (OR. =. 1.078, p. =. 0.476), regardless of the type of service, or type of medical condition. Conclusions: Anxiety is not associated with increased use of urgent care. This finding is in contrast to similar studies which have investigated the role of depression as a risk factor for use of urgent care.This paper summarises independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0707-10162)

Working with Children with Learning Disabilities and/or who Communicate Non-verbally: Research experiences and their implications for social work education, increased participation and social inclusion

Social exclusion, although much debated in the UK, frequently focuses on children as a key 'at risk' group. However, some groups, such as disabled children, receive less consideration. Similarly, despite both UK and international policy and guidance encouraging the involvement of disabled children and their right to participate in decision-making arenas, they are frequently denied this right. UK based evidence suggests that disabled children's participation lags behind that of their non-disabled peers, often due to social work practitioners' lack of skills, expertise and knowledge on how to facilitate participation. The exclusion of disabled children from decision-making in social care processes echoes their exclusion from participation in society. This paper seeks to begin to address this situation, and to provide some examples of tools that social work educators can introduce into pre- and post-qualifying training programmes, as well as in-service training. The paper draws on the experiences of researchers using non-traditional qualitative research methods, especially non-verbal methods, and describes two research projects, focusing on the methods employed to communicate with and involve disabled children, the barriers encountered and lessons learnt. Some of the ways in which these methods of communication can inform social work education are explored alongside wider issues of how and if increased communication can facilitate greater social inclusion

The use of reinforcement learning algorithms to meet the challenges of an artificial pancreas

Blood glucose control, for example, in diabetes mellitus or severe illness, requires strict adherence to a protocol of food, insulin administration and exercise personalized to each patient. An artificial pancreas for automated treatment could boost quality of glucose control and patients' independence. The components required for an artificial pancreas are: i) continuous glucose monitoring (CGM), ii) smart controllers and iii) insulin pumps delivering the optimal amount of insulin. In recent years, medical devices for CGM and insulin administration have undergone rapid progression and are now commercially available. Yet, clinically available devices still require regular patients' or caregivers' attention as they operate in open-loop control with frequent user intervention. Dosage-calculating algorithms are currently being studied in intensive care patients [1] , for short overnight control to supplement conventional insulin delivery [2] , and for short periods where patients rest and follow a prescribed food regime [3] . Fully automated algorithms that can respond to the varying activity levels seen in outpatients, with unpredictable and unreported food intake, and which provide the necessary personalized control for individuals is currently beyond the state-of-the-art. Here, we review and discuss reinforcement learning algorithms, controlling insulin in a closed-loop to provide individual insulin dosing regimens that are reactive to the immediate needs of the patient

Roughening of the (1+1) interfaces in two-component surface growth with an admixture of random deposition

We simulate competitive two-component growth on a one dimensional substrate of $L$ sites. One component is a Poisson-type deposition that generates Kardar-Parisi-Zhang (KPZ) correlations. The other is random deposition (RD). We derive the universal scaling function of the interface width for this model and show that the RD admixture acts as a dilatation mechanism to the fundamental time and height scales, but leaves the KPZ correlations intact. This observation is generalized to other growth models. It is shown that the flat-substrate initial condition is responsible for the existence of an early non-scaling phase in the interface evolution. The length of this initial phase is a non-universal parameter, but its presence is universal. In application to parallel and distributed computations, the important consequence of the derived scaling is the existence of the upper bound for the desynchronization in a conservative update algorithm for parallel discrete-event simulations. It is shown that such algorithms are generally scalable in a ring communication topology.Comment: 16 pages, 16 figures, 77 reference

Observations of chemical differentiation in clumpy molecular clouds

We have extensively mapped a sample of dense molecular clouds (L1512, TMC-1C, L1262, Per 7, L1389, L1251E) in lines of HC3N, CH3OH, SO and C^{18}O. We demonstrate that a high degree of chemical differentiation is present in all of the observed clouds. We analyse the molecular maps for each cloud, demonstrating a systematic chemical differentiation across the sample, which we relate to the evolutionary state of the cloud. We relate our observations to the cloud physical, kinematical and evolutionary properties, and also compare them to the predictions of simple chemical models. The implications of this work for understanding the origin of the clumpy structures and chemical differentiation observed in dense clouds are discussed.Comment: 20 pages, 7 figures. Higher quality figures appear in the published journal articl