Understanding the information dynamics of medication administration in residential aged care facilities (RACFs): A prerequisite for design of effective ICT systems

Medication information is a critical part of the information required to ensure residents' safety in the highly collaborative care context of RACFs. Studies report poor medication information as a barrier to improve medication management in RACFs. Research exploring medication work practices in aged care settings remains limited. This study aimed to identify contextual and work practice factors contributing to breakdowns in medication information exchange in RACFs in relation to the medication administration process. We employed non-participant observations and semi-structured interviews to explore information practices in three Australian RACFs. Findings identified inefficiencies due to lack of information timeliness, manual stock management, multiple data transcriptions, inadequate design of essential documents such as administration sheets and a reliance on manual auditing procedures. Technological solutions such as electronic medication administration records offer opportunities to overcome some of the identified problems. However these interventions need to be designed to align with the collaborative team based processes they intend to support.

Online learning an effective means for developing small business owner-managers’ capabilities?

Purpose If owner-managers engage in management development activities then chances of success may be improved for small businesses. But small business owner-managers (SBOMs) are a difficult group to engage in management development activities. While practitioners worry about timing, content and location of development activities, the purpose of this paper is to examine what drives SBOMs to participate in an online discussion forum (ODF) as a form of management development. An ODF was run with SBOMs and the factors affecting their participation are reported from this exploratory study. Design/methodology/approach A qualitative methodology was used where data gathered from three sources, the ODF posts, in-depth interviews with participants and a focus group with non-participants. These were analysed to evaluate factors affecting participation of SBOMs in an ODF. Findings The findings point to the importance of owner-managers’ attitudes. Attitudes that positively affected SBOMs participation in the ODF included; appreciating that learning leads to business success; positive self-efficacy developed through prior online experience; and an occupational identity as a business manager. Research limitations/implications Few SBOMs participated in the ODF, which is consistent with research finding that they are a difficult group to engage in management development learning activities. Three forms of data were analysed to strengthen results. Practical implications Caution should be exercised when considering investment in e-learning to develop the managerial capabilities of SBOMs. Originality/value Evidence of the factors important for participation in an informal voluntary ODF. The findings suggest greater emphasis should be placed on changing attitudes if SBOMs are to be encouraged to participate in management development activities.

Effective earth and space science analogies

There are several good reasons why Earth and Space Science should be a part of any science curriculum. Nearly everything we do each day is connected in some way to the Earth: to its land, oceans, atmosphere, plants and animals. By 2025, eight billion people will live on Earth. If we are to continue extracting resources to maintain a high quality of life, then it is important that our children are scientifically literate in a way that allows them to exploit the Earth’s resources in a sustainable way. People who understand how earth systems work can make informed decisions and may be able to help resolve issues surrounding clean water, urban planning and development, global climate change and the use and management of natural resources.

Developing effective fumigation protocols to manage strongly phosphine-resistant Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae)

BACKGROUND The emergence of high levels of resistance in Cryptolestes ferrugineus (Stephens) in recent years threatens the sustainability of phosphine, a key fumigant used worldwide to disinfest stored grain. We aimed at developing robust fumigation protocols that could be used in a range of practical situations to control this resistant pest. RESULTS Values of the lethal time to kill 99.9% (LT99.9, in days) of mixed-age populations, containing all life stages, of a susceptible and a strongly resistant C. ferrugineus population were established at three phosphine concentrations (1.0, 1.5 and 2.0 mg L−1) and three temperatures (25, 30 and 35 °C). Multiple linear regression analysis revealed that phosphine concentration and temperature both contributed significantly to the LT99.9 of a population (P < 0.003, R2 = 0.92), with concentration being the dominant variable, accounting for 75.9% of the variation. Across all concentrations, LT99.9 of the strongly resistant C. ferrugineus population was longest at the lowest temperature and shortest at the highest temperature. For example, 1.0 mg L−1 of phosphine is required for 20, 15 and 15 days, 1.5 mg L−1 for 12, 11 and 9 days and 2.0 mg L−1 for 10, 7 and 6 days at 25, 30 and 35 °C, respectively, to achieve 99.9% mortality of the strongly resistant C. ferrugineus population. We also observed that phosphine concentration is inversely proportional to fumigation period in regard to the population extinction of this pest. CONCLUSION The fumigation protocols developed in this study will be used in recommending changes to the currently registered rates of phosphine in Australia towards management of strongly resistant C. ferrugineus populations, and can be repeated in any country where this type of resistance appears. © 2014 Commonwealth of Australia. Pest Management Science © 2014 Society of Chemical Industry

A novel and effective technology for mitigating nitrous oxide emissions from land-applied manures

Land-applied manures produce nitrous oxide (N2O), a greenhouse gas (GHG). Land application can also result in ammonia (NH3) volatilisation, leading to indirect N2O emissions. Here, we summarise a glasshouse investigation into the potential for vermiculite, a clay with a high cation exchange capacity, to decrease N2O emissions from livestock manures (beef, pig, broiler, layer), as well as urea, applied to soils. Our hypothesis is that clays adsorb ammonium, thereby suppressing NH3 volatilisation and slowing N2O emission processes. We previously demonstrated the ability of clays to decrease emissions at the laboratory scale. In this glasshouse work, manure and urea application rates varied between 50 and 150 kg nitrogen (N)/ha. Clay : manure ratios ranged from 1 : 10 to 1 : 1 (dry weight basis). In the 1-year trial, the above-mentioned N sources were incorporated with vermiculite in 1 L pots containing Sodosol and Ferrosol growing a model pasture (Pennisetum clandestinum or kikuyu grass). Gas emissions were measured periodically by placing the pots in gas-tight bags connected to real-time continuous gas analysers. The vermiculite achieved significant (P ≤ 0.05) and substantial decreases in N2O emissions across all N sources (70% on average). We are currently testing the technology at the field scale; which is showing promising emission decreases (~50%) as well as increases (~20%) in dry matter yields. This technology clearly has merit as an effective GHG mitigation strategy, with potential associated agronomic benefits, although it needs to be verified by a cost–benefit analysis.

Towards an understanding of the information dynamics of the handover process in aged care settings: A prerequisite for the safe and effective use of ICT

Background Poor clinical handover has been associated with inaccurate clinical assessment and diagnosis, delays in diagnosis and test ordering, medication errors and decreased patient satisfaction in the acute care setting. Research on the handover process in the residential aged care sector is very limited. Purpose The aims of this study were to: (i) Develop an in-depth understanding of the handover process in aged care by mapping all the key activities and their information dynamics, (ii) Identify gaps in information exchange in the handover process and analyze implications for resident safety, (iii) Develop practical recommendations on how information communication technology (ICT) can improve the process and resident safety. Methods The study was undertaken at a large metropolitan facility in NSW with more than 300 residents and a staff including 55 registered nurses (RNs) and 146 assistants in nursing (AINs). A total of 3 focus groups, 12 interviews and 3 observation sessions were conducted over a period from July to October 2010. Process mapping was undertaken by translating the qualitative data via a five-category code book that was developed prior to the analysis. Results Three major sub-processes were identified and mapped. The three major stages are Handover process (HOP) I “Information gathering by RN”, HOP II “Preparation of preliminary handover sheet” and HOP III “Execution of handover meeting”. Inefficient processes were identified in relation to the handover including duplication of information, utilization of multiple communication modes and information sources, and lack of standardization. Conclusion By providing a robust process model of handover this study has made two critical contributions to research in aged care: (i) a means to identify important, possibly suboptimal practices; and (ii) valuable evidence to plan and improve ICT implementation in residential aged care. The mapping of this process enabled analysis of gaps in information flow and potential impacts on resident safety. In addition it offers the basis for further studies into a process that, despite its importance for securing resident safety and continuity of care, lacks research.

Effective 20 newsgroups dataset cleaning

The rapid increase in the number of text documents available on the Internet has created pressure to use effective cleaning techniques. Cleaning techniques are needed for converting these documents to structured documents. Text cleaning techniques are one of the key mechanisms in typical text mining application frameworks. In this paper, we explore the role of text cleaning in the 20 newsgroups dataset, and report on experimental results.

Researching effective approaches to cleaning in hospitals: Protocol of the REACH study, a multi-site stepped-wedge randomised trial

Background The Researching Effective Approaches to Cleaning in Hospitals (REACH) study will generate evidence about the effectiveness and cost-effectiveness of a novel cleaning initiative that aims to improve the environmental cleanliness of hospitals. The initiative is an environmental cleaning bundle, with five interdependent, evidence-based components (training, technique, product, audit and communication) implemented with environmental services staff to enhance hospital cleaning practices. Methods/design The REACH study will use a stepped-wedge randomised controlled design to test the study intervention, an environmental cleaning bundle, in 11 Australian hospitals. All trial hospitals will receive the intervention and act as their own control, with analysis undertaken of the change within each hospital based on data collected in the control and intervention periods. Each site will be randomised to one of the 11 intervention timings with staggered commencement dates in 2016 and an intervention period between 20 and 50 weeks. All sites complete the trial at the same time in 2017. The inclusion criteria allow for a purposive sample of both public and private hospitals that have higher-risk patient populations for healthcare-associated infections (HAIs). The primary outcome (objective one) is the monthly number of Staphylococcus aureus bacteraemias (SABs), Clostridium difficile infections (CDIs) and vancomycin resistant enterococci (VRE) infections, per 10,000 bed days. Secondary outcomes for objective one include the thoroughness of hospital cleaning assessed using fluorescent marker technology, the bio-burden of frequent touch surfaces post cleaning and changes in staff knowledge and attitudes about environmental cleaning. A cost-effectiveness analysis will determine the second key outcome (objective two): the incremental cost-effectiveness ratio from implementation of the cleaning bundle. The study uses the integrated Promoting Action on Research Implementation in Health Services (iPARIHS) framework to support the tailored implementation of the environmental cleaning bundle in each hospital. Discussion Evidence from the REACH trial will contribute to future policy and practice guidelines about hospital environmental cleaning. It will be used by healthcare leaders and clinicians to inform decision-making and implementation of best-practice infection prevention strategies to reduce HAIs in hospitals. Trial registration Australia New Zealand Clinical Trial Registry ACTRN12615000325​505

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

How Effective Is The Data On Co-Occurrence Of Domains In Multi-Domain Proteins In Prediction Of Protein-Protein Interactions?

We explore the fuse of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template dataset of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.

Selecting rainfall events for effective Water Sensitive Urban Design: A case study in Gold Coast City, Australia

The current approach for protecting the receiving water environment from urban stormwater pollution is the adoption of structural measures commonly referred to as Water Sensitive Urban Design (WSUD). The treatment efficiency of WSUD measures closely depends on the design of the specific treatment units. As stormwater quality is influenced by rainfall characteristics, the selection of appropriate rainfall events for treatment design is essential to ensure the effectiveness of WSUD systems. Based on extensive field investigations in four urban residential catchments based at Gold Coast, Australia, and computer modelling, this paper details a technically robust approach for the selection of rainfall events for stormwater treatment design using a three-component model. The modelling results confirmed that high intensity-short duration events produce 58.0% of TS load while they only generated 29.1% of total runoff volume. Additionally, rainfall events smaller than 6-month average recurrence interval (ARI) generates a greater cumulative runoff volume (68.4% of the total annual runoff volume) and TS load (68.6% of the TS load exported) than the rainfall events larger than 6-month ARI. The results suggest that for the study catchments, stormwater treatment design could be based on the rainfall which had a mean value of 31 mm/h average intensity and 0.4 h duration. These outcomes also confirmed that selecting smaller ARI rainfall events with high intensity-short duration as the threshold for treatment system design is the most feasible approach since these events cumulatively generate a major portion of the annual pollutant load compared to the other types of events, despite producing a relatively smaller runoff volume. This implies that designs based on small and more frequent rainfall events rather than larger rainfall events would be appropriate in the context of efficiency in treatment performance, cost-effectiveness and possible savings in land area needed.

Tendency toward crossover of the effective susceptibility exponent from its doubled Ising value to its doubled mean-field value near a double critical point

The critical behavior of osmotic susceptibility in an aqueous electrolyte mixture 1-propanol (1P)+water (W)+potassium chloride is reported. This mixture exhibits re-entrant phase transitions and has a nearly parabolic critical line with its apex representing a double critical point (DCP). The behavior of the susceptibility exponent is deduced from static light-scattering measurements, on approaching the lower critical solution temperatures (TL’s) along different experimental paths (by varying t) in the one-phase region. The light-scattering data analysis substantiates the existence of a nonmonotonic crossover behavior of the susceptibility exponent in this mixture. For the TL far away from the DCP, the effective susceptibility exponent γeff as a function of t displays a nonmonotonic crossover from its single limit three-dimensional (3D)-Ising value ( ∼ 1.24) toward its mean-field value with increase in t. While for that closest to the DCP, γeff displays a sharp, nonmonotonic crossover from its nearly doubled 3D-Ising value toward its nearly doubled mean-field value with increase in t. The renormalized Ising regime extends over a relatively larger t range for the TL closest to the DCP, and a trend toward shrinkage in the renormalized Ising regime is observed as TL shifts away from the DCP. Nevertheless, the crossover to the mean-field limit extends well beyond t>10−2 for the TL’s studied. The observed crossover behavior is attributed to the presence of strong ion-induced clustering in this mixture, as revealed by various structure probing techniques. As far as the critical behavior in complex or associating mixtures with special critical points (like the DCP) is concerned, our results indicate that the influence of the DCP on the critical behavior must be taken into account not only on the renormalization of the critical exponent but also on the range of the Ising regime, which can shrink with decrease in the influence of the DCP and with the extent of structuring in the system. The utility of the field variable tUL in analyzing re-entrant phase transitions is demonstrated. The effective susceptibility exponent as a function of tUL displays a nonmonotonic crossover from its asymptotic 3D-Ising value toward a value slightly lower than its nonasymptotic mean-field value of 1. This behavior in the nonasymptotic, high tUL region is interpreted in terms of the possibility of a nonmonotonic crossover to the mean-field value from lower values, as foreseen earlier in micellar systems.

Simulations of dimensionally reduced effective theories of high temperature QCD

Quantum chromodynamics (QCD) is the theory describing interaction between quarks and gluons. At low temperatures, quarks are confined forming hadrons, e.g. protons and neutrons. However, at extremely high temperatures the hadrons break apart and the matter transforms into plasma of individual quarks and gluons. In this theses the quark gluon plasma (QGP) phase of QCD is studied using lattice techniques in the framework of dimensionally reduced effective theories EQCD and MQCD. Two quantities are in particular interest: the pressure (or grand potential) and the quark number susceptibility. At high temperatures the pressure admits a generalised coupling constant expansion, where some coefficients are non-perturbative. We determine the first such contribution of order g^6 by performing lattice simulations in MQCD. This requires high precision lattice calculations, which we perform with different number of colors N_c to obtain N_c-dependence on the coefficient. The quark number susceptibility is studied by performing lattice simulations in EQCD. We measure both flavor singlet (diagonal) and non-singlet (off-diagonal) quark number susceptibilities. The finite chemical potential results are optained using analytic continuation. The diagonal susceptibility approaches the perturbative result above 20T_c$, but below that temperature we observe significant deviations. The results agree well with 4d lattice data down to temperatures 2T_c.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.