Pain in care home residents with dementia: an exploration of frequency, prescribing and relatives' perspectives

Objectives: This study aims to determine pain frequency amongst care home residents with dementia, to investigate variables associated with pain, to explore analgesic use among residents and to seek residents' relatives' views on provision of care and management of pain by the care home. Methods: Structured face-to-face interviews were conducted with residents, nursing staff and relatives from nine dementia care homes in Northern Ireland, between May 2010 and March 2012. Demographic information was collected from participants, neuropsychiatric tests were used to assess residents' cognitive functioning, medication use was determined from care home records and residents' pain was assessed using a verbal descriptor scale. Relatives' views were sought on care provision and management of pain. Results: Forty-two residents, 16 nurses/care assistants and 35 relatives participated; the participation rate of residents was low (27.6%). Most residents were suffering moderate-severe dementia, and some residents (26.2%) were unable to provide a self-report of pain. A significantly higher proportion of relatives (57.1%) deemed residents to be experiencing pain at the time of the interview, compared with residents (23.8%, p = 0.005) and nurses/care assistants (42.9%, p = 0.035). Most residents (88.1%) were prescribed with analgesia; non-opioid analgesics were most commonly prescribed. High proportions of residents were prescribed with psychoactive medications. Antipsychotic drug use was associated with presence of pain (p = 0.046). Conclusions: This study has reinforced the challenge of assessing and managing pain in this resident population and highlighted issues to be addressed by long-term care providers and clinicians. Participation of people with dementia, and their families, in healthcare research needs to be improved.

Just a matter of time: Fungi and roots significantly and rapidly aggregate soil over four decades along the Tagliamento River, NE Italy

Fluvial islands are emergent landforms which form at the interface between the permanently inundated areas of the river channel and the more stable areas of the floodplain as a result of interactions between physical river processes, wood and riparian vegetation. These highly dynamical systems are ideal to study soil structure development in the short to medium term, a process in which soil biota and plants play a substantial role. We investigated soil structure development on islands along a 40 year chronosequence within a 3 km island-braided reach of the Tagliamento River, Northeastern Italy. We used several parameters to capture different aspects of the soil structure, and measured biotic (e.g., fungal and plant root parameters) and abiotic (e.g. organic carbon) factors expected to determine the structure. We estimated models relating soil structure to its determinants, and, in order to confer statistical robustness to our results, we explicitly took into account spatial autocorrelation, which is present due to the space for time substitution inherent in the study of chronosequences and may have confounded results of previous studies. We found that, despite the eroding forces from the hydrological and geomorphological dynamics to which the system is subject, all soil structure variables significantly, and in some case greatly increased with site age. We interpret this as a macroscopic proxy for the major direct and indirect binding effects exerted by root variables and extraradical hyphae of arbuscular mycorrhizal fungi (AMF). Key soil structure parameters such as percentage of water stable aggregates (WSA) can double from the time the island landform is initiated (mean WSA = 30%) to the full 40 years (mean WSA = 64%) covered by our chronosequence. The study demonstrates the fundamental role of soil biota and plant roots in aggregating soils even in a system in which intense short to medium term physical disturbances are common.

Disturbance, neutral theory and patterns of beta diversity in soil communities

Beta diversity describes how local communities within an area or region differ in species composition/abundance. There have been attempts to use changes in beta diversity as a biotic indicator of disturbance, but lack of theory and methodological caveats have hampered progress. We here propose that the neutral theory of biodiversity plus the definition of beta diversity as the total variance of a community matrix provide a suitable, novel, starting point for ecological applications. Observed levels of beta diversity (BD) can be compared to neutral predictions with three possible outcomes: Observed BD equals neutral prediction or is larger (divergence) or smaller (convergence) than the neutral prediction. Disturbance might lead to either divergence or convergence, depending on type and strength. We here apply these ideas to datasets collected on oribatid mites (a key, very diverse soil taxon) under several regimes of disturbances. When disturbance is expected to increase the heterogeneity of soil spatial properties or the sampling strategy encompassed a range of diverging environmental conditions, we observed diverging assemblages. On the contrary, we observed patterns consistent with neutrality when disturbance could determine homogenization of soil properties in space or the sampling strategy encompassed fairly homogeneous areas. With our method, spatial and temporal changes in beta diversity can be directly and easily monitored to detect significant changes in community dynamics, although the method itself cannot inform on underlying mechanisms. However, human-driven disturbances and the spatial scales at which they operate are usually known. In this case, our approach allows the formulation of testable predictions in terms of expected changes in beta diversity, thereby offering a promising monitoring tool.

Vulnerability and robustness of SME supply chains: An empirical study of risk and disturbance management of fresh food processors in a developing market

The aim of this paper is to analyse vulnerability and robustness of small and medium size enterprises (SMEs) supply chains and to consider contextual factors that might influence the success of their disturbance management: Risky product and business environment. By using an exploratory case study it is shown how these contextual factors attribute vulnerability sources, contribute to the robustness of a company’s performance and supply chain vulnerability, as well as how a company seeks to manage internal and external vulnerability sources. The exploratory case is based on a fresh food supply chain of a manufacturing SME operating in a developing market.
Case findings suggest that fresh food supply chains of a manufacturing SME in developing markets are prone to disruptions of their logistics and production processes due to ‘riskiness’ of fresh food products, the ‘riskiness’ of developing markets, as well as ‘riskiness’ of SMEs themselves. However, this does not necessarily indicate the vulnerability of an SME and its entire supply chain. Findings indicate that SMEs can be very successful in disturbance management by selective use of redesign strategies that aim to prevent or reduce the impact of disturbances. More precise, it is likely that an SME can achieve robust performance by employing preventive redesign strategies in managing disturbances that result from internal, company related vulnerability sources, while impact reduction strategies are likely to contribute to robust performance of an SME if used to manage disturbances that result from internal, supply chain related vulnerability sources, as well as external vulnerability sources.

Untargeted Metabolomic Analysis of Human Plasma Indicates Differentially Affected Polyamine and L-Arginine Metabolism in Mild Cognitive Impairment Subjects Converting to Alzheimer’s Disease

This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer's disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients 'at risk' from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Development and Application of Medication Appropriateness Indicators for Persons with Advanced Dementia: A Feasibility Study

Background: No studies have been conducted in the UK context to date that categorise medications in terms of appropriateness for patients with advanced dementia, or that examine medication use in these vulnerable patients.

Objectives: The objectives of this study were to categorise the appropriateness of a comprehensive list of medications and medication classes for use in patients with advanced dementia; examine the feasibility of conducting a longitudinal prospective cohort study to collect clinical and medication use data; and determine the appropriateness of prescribing for nursing home residents with advanced dementia in Northern Ireland (NI), using the categories developed.

Methods: A three-round Delphi consensus panel survey of expert clinicians was used to categorise the appropriateness of medications for patients with advanced dementia [defined as having Functional Assessment Staging (FAST) scores ranging from 6E to 7F]. This was followed by a longitudinal prospective cohort feasibility study that was conducted in three nursing homes in NI. Clinical and medication use for participating residents with advanced dementia (FAST scores ranging from 6E to 7F) were collected and a short test of dementia severity administered. These data were collected at baseline and every 3 months for up to 9 months or until death. For those residents who died during the study period, data were also collected within 14 days of death. The appropriateness ratings from the consensus panel survey were retrospectively applied to residents’ medication data at each data collection timepoint to determine the appropriateness of medications prescribed for these residents.

Results: Consensus was achieved for 87 (90 %) of the 97 medications and medication classes included in the survey. Fifteen residents were recruited to participate in the longitudinal prospective cohort feasibility study, four of whom died during the data collection period. Mean numbers of medications prescribed per resident were 16.2 at baseline, 19.6 at 3 months, 17.4 at 6 months and 16.1 at 9 months. Fourteen residents at baseline were taking at least one medication considered by the consensus panel to be never appropriate, and approximately 25 % of medications prescribed were considered to be never appropriate. Post-death data collection indicated a decrease in the proportion of never appropriate medications and an increase in the proportion of always appropriate medications for those residents who died.

Conclusions: This study is the first to develop and apply medication appropriateness indicators for patients with advanced dementia in the UK setting. The Delphi consensus panel survey of expert clinicians was a suitable method of developing such indicators. It is feasible to collect information on quality of life, functional performance, physical comfort, neuropsychiatric symptoms and cognitive function for this subpopulation of nursing home residents with advanced dementia.

Urban high-density construction sites and their surrounding community:issues encountered and strategiesadopted by contractors

Inner city developments are a common feature within many urban environments. Where these construction sites are not managed effectively, they can negatively impact their surrounding community. The aim of this paper is to identify and document, in an urban context, the numerous issues encounter and subsequent strategies adopted by on-site contractors and local people, in the mitigation of factors which negatively impact their surrounding community. The objectives in achieving this aim are to identify what effect, if any, an urban construction site has on its surrounding environment, the issues and resulting strategies adopted by contractors on the factors identified, and also what measures are put in place to minimise such disturbances to the local community. In order to meet the requirements, a mixed methodology is adopted culminating in a literature review, case study analysis, contractor and community interviews, concluding in the development of two specific questions for both perspectives in question. The data is assessed using severity indices based on mean testing in the development of key findings. The results indicate that the main forms of disturbance to the local community from an urban development include noise, dust and traffic congestion. With respect to a contractor on-site, the key issues include damaging surrounding buildings, noise control and off-site parking. The resulting strategies identified in the mitigation of such issues include the implementation of noise and dust containment measures and minimising disruption to local infrastructure. It is envisaged that the results of this study will provide contractors operating in such environments, with the required information which can assist in minimising disruption and therefore, avoiding disputes with the local community members. By consulting with and surveying those most affected, this research will illustrate to on-site management, the difficulties faced by those who accommodate such developments within their living environment.

Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

Dynamic Modeling and Interaction of Hybrid Natural Gas and Electricity Supply System in Microgrid

Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.

An approach to determine the local boundary of small disturbance voltage stability region in a cut-set power space:基于微扰的割集电压稳定域局部边界求解方法

A new approach to determine the local boundary of voltage stability region in a cut-set power space (CVSR) is presented. Power flow tracing is first used to determine the generator-load pair most sensitive to each branch in the interface. The generator-load pairs are then used to realize accurate small disturbances by controlling the branch power flow in increasing and decreasing directions to obtain new equilibrium points around the initial equilibrium point. And, continuous power flow is used starting from such new points to get the corresponding critical points around the initial critical point on the CVSR boundary. Then a hyperplane cross the initial critical point can be calculated by solving a set of linear algebraic equations. Finally, the presented method is validated by some systems, including New England 39-bus system, IEEE 118-bus system, and EPRI-1000 bus system. It can be revealed that the method is computationally more efficient and has less approximation error. It provides a useful approach for power system online voltage stability monitoring and assessment. This work is supported by National Natural Science Foundation of China (No. 50707019), Special Fund of the National Basic Research Program of China (No. 2009CB219701), Foundation for the Author of National Excellent Doctoral Dissertation of PR China (No. 200439), Tianjin Municipal Science and Technology Development Program (No. 09JCZDJC25000), National Major Project of Scientific and Technical Supporting Programs of China During the 11th Five-year Plan Period (No. 2006BAJ03A06). ©2009 State Grid Electric Power Research Institute Press.

Electron-scale dissipative electrostatic solitons in multi-species plasmas

The linear and nonlinear properties of small-amplitude electron-acoustic solitary waves are investigated via the fluid dynamical approach. A three-component plasma is considered, composed of hot electrons, cold electrons, and ions (considered stationary at the scale of interest). A dissipative (wave damping) effect is assumed due to electron-neutral collisions. The background (hot) electrons are characterized by an energetic (excessively superthermal) population and are thus modeled via a κ-type nonthermal distribution. The linear characteristics of electron-acoustic excitations are discussed, for different values of the plasma parameters (superthermality index κ and cold versus hot electron population concentration β). Large wavelengths (beyond a threshold value) are shown to be overdamped. The reductive perturbation technique is used to derive a dissipative Korteweg de-Vries (KdV) equation for small-amplitude electrostatic potential disturbances. These are expressed by exact solutions in the form of dissipative solitary waves, whose dynamics is investigated analytically and numerically. Our results should be useful in elucidating the behavior of space and experimental plasmas characterized by a coexistence of electron populations at different temperatures, where electron-neutral collisions are of relevance.

Irish Power System Primary Frequency Response Metrics during Different System Non Synchronous Penetrations.

This paper discusses the use of primary frequency response metrics to assess the dynamics of frequency disturbance data with the presence of high system non synchronous penetration (SNSP) and system inertia variation. The Irish power system has been chosen as a study case as it experiences a significant level of SNSP from wind turbine generation and imported active power from HVDC interconnectors. Several recorded actual frequency disturbances were used in the analysis. These data were measured and collected from the Irish power system from October 2010 to June 2013. The paper has shown the impact of system inertia and SNSP variation on the performance of primary frequency response metrics, namely: nadir frequency, rate of change of frequency, inertial and primary frequency response.

Wide-Area Phase-Angle Measurements for Islanding Detection—An Adaptive Nonlinear Approach

The integration of an ever growing proportion of large scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to non-synchronous penetration in a power grid, system wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide area phase angle measurements. This is challenging, since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis is proposed to model the time-varying and nonlinear trends in the voltage phase angle data. The effectiveness of the technique is exemplified using both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.

Wide-ranging alterations in the brain fatty acid complement of subjects with late Alzheimer’s disease as detected by GC-MS

Disturbed lipid metabolism is a well-established feature of human Alzheimer’s disease (AD). The present study used gas chromatography-mass spectrometry (GC-MS) analysis of fatty acid methyl esters (FAMES) to profile all detectable fatty acid (FA) species present in post-mortem neocortical tissue (Brodmann 7 region). Quantitative targeted analysis was undertaken from 29 subjects (n=15 age-matched controls; n=14 late-stage AD). GC-MS analysis of FAMES detected a total of 24 FAs and of these, 20 were fully quantifiable. The results showed significant and wide ranging elevations in AD brain FA concentrations. A total of 9 FAs were elevated in AD with cis-13,16-docosenoic acid increased most (170%; P=0.033). Intriguingly, docosahexanoic acid (DHA; C22:6) concentrations were elevated (47%; P=0.018) which conflicts with the findings of others (unaltered or decreased) in some brain regions after the onset of AD. Furthermore, our results appear to indicate that subject gender influences brain FA levels in AD subjects (but not in age-matched control subjects). Among AD subjects 7 FA species were significantly higher in males than in females. These preliminary findings pinpoint FA disturbances as potentially important in the pathology of AD. Further work is required to determine if such changes are influenced by disease severity or different types of dementia.

Alzheimer's disease-like pathology has transient effects on the brain and blood metabolome

The pathogenesis of Alzheimer's disease (AD) is complex involving multiple contributing factors. The extent to which AD pathology impacts upon the metabolome is still not understood, nor is it known how disturbances change as the disease progresses. For the first time we have profiled longitudinally (6, 8, 10, 12 and 18 months) both the brain and plasma metabolome of APP/PS1 double transgenic and wild type (WT) mice. A total of 187 metabolites were quantified using a targeted metabolomics methodology. Multivariate statistical analysis produced models that distinguished APP/PS1 from WT mice at 8, 10 and 12 months.Metabolic pathway analysis found perturbed polyamine metabolism in both brain and blood plasma. There were other disturbances in essential amino acids,branched chain amino acids and also in the neurotransmitter serotonin.Pronounced imbalances in phospholipid and acylcarnitine homeostasis was evident in two age groups. AD-like pathology therefore impacts greatly on both the brain and blood metabolomes, although there appears to be a clear temporal sequence whereby changes to brain metabolites precede those in blood.