60419 research outputs found
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Do voluntary environmental management systems improve environmental performance? Evidence from waste management by Kenyan firms
No full textWe examine whether the adoption of global voluntary environmental management systems - United Nations Global Compact and ISO 14001 - lead to more effective environmental performance. Previous studies have presented inconclusive findings of voluntary environmental management systems on environmental performances. Possible reasons for conflicting results are the influence of observable and unobservable factors that affect environmental performance as well as the use of different measures of environmental performance indicators. Using primary data from Kenyan firms in 2019, waste management defined by wastewater recycling, solid waste reusing and use of environmentally safe disposal methods, we determine the effects of voluntary environmental management systems (VEMS) on firm-level environmental performance. We conclude that the adoption of VEMS are associated with significant improvement in environmental performance in developing economies. Our conclusions provide insights to corporate management and policy makers in developing countries on decisions regarding better environmental management. VEMS forms an environmental management tool suitable in confronting wastewater and physical refuse challenges as well as conducive waste disposal methods
Persistently elevated early warning scores and lactate identifies patients at high risk of mortality in suspected sepsis
No full textObjective
In the UK, the National Early Warning Score (NEWS) is recommended as part of screening for suspicion of sepsis. Is a change in NEWS a better predictor of mortality than an isolated score when screening for suspicion of sepsis?.
Methods
A prospectively gathered cohort of 1233 adults brought in by ambulance to two UK nonspecialist hospitals, with suspicion of sepsis at emergency department (ED) triage (2015–2017) was analysed. Associations with 30-day mortality and ICU admission rate were compared between groups with an isolated NEWS ≥5 points prehospital and those with persistently elevated NEWS prehospital, in ED and at ward admission. The effect of adding the ED (venous or arterial) lactate was also assessed.
Results
Mortality increased if the NEWS persisted ≥5 at ED arrival 22.1% vs. 10.2% [odds ratio (OR) 2.5 (1.6–4.0); P < 0.001]. Adding an ED lactate ≥2 mmol/L was associated with an increase in mortality greater than for NEWS alone [32.2% vs. 13.3%, OR 3.1 (2.2–4.1); P < 0.001], and increased ICU admission [13.9% vs. 3.7%, OR 3.1 (2.2–4.3); P < 0.001]. If NEWS remained ≥5 at ward admission (predominantly within 4 h of ED arrival), mortality was 32.1% vs. 14.3%, [OR 2.8 (2.1–3.9); P < 0.001] and still higher if accompanied by an elevated ED lactate [42.1% vs. 16.4%, OR 3.7 (2.6–5.3); P < 0.001].
Conclusion
Persistently elevated NEWS, from prehospital through the ED to the time of ward admission, combined with an elevated ED lactate identifies patients with suspicion of sepsis at highest risk of in-hospital mortality
The contribution of diabetic micro-angiopathy to adverse outcomes in COVID-19
No full textIncreasing evidence points to endothelial cell dysfunction as a key pathophysiological factor in severe coronavirus disease-19 (COVID-19), manifested by platelet aggregation, microthrombi and altered vasomotor tone. This may be driven by direct endothelial cell entry by the virus, or indirectly by activated inflammatory cascade. Major risk groups identified for adverse outcomes in COVID-19 are diabetes, and those from the Black, Asian and ethnic minority (BAME) populations. Hyperglycaemia (expressed as glycated haemoglobin or mean hospital glucose) correlates with worse outcomes in COVID-19. It is not known whether hyperglycaemia is causative or is a surrogate marker - persistent hyperglycaemia is well known as an aetiological agent in microangiopathy. In this article, we propose that pre-existing endothelial dysfunction of microangiopathy, more commonly evident in diabetes and BAME groups, makes an individual vulnerable to the subsequent ‘endothelitis’ of COVID-19 infection
Delegating home visits in general practice: a realist review on the impact on GP workload and patient care
No full textBackground:
UK general practice is being shaped by new
ways of working. Traditional GP tasks are
being delegated to other staff with the intention
of reducing GPs’ workload and hospital
admissions, and improving patients’ access
to care. One such task is patient-requested
home visits. However, it is unclear what impact
delegated home visits may have, who might
benefit, and under what circumstances.
Aim:
To explore how the process of delegating home
visits works, for whom, and in what contexts.
Design and setting
A review of secondary data on home visit
delegation processes in UK primary care
settings.
Method
A realist approach was taken to reviewing data,
which aims to provide causal explanations
through the generation and articulation of
contexts, mechanisms, and outcomes. A range
of data has been used including news items,
grey literature, and academic articles.
Results:
Data were synthesised from 70 documents.
GPs may believe that delegating home visits
is a risky option unless they have trust and
experience with the wider multidisciplinary
team. Internal systems such as technological
infrastructure might help or hinder the
delegation process. Healthcare professionals
carrying out delegated home visits might
benefit from being integrated into general
practice but may feel that their clinical
autonomy is limited by the delegation process.
Patients report short-term satisfaction when
visited by a healthcare professional other than
a GP. The impact this has on long-term health
outcomes and cost is less clear.
Conclusion:
The delegation of home visits may require a shift
in patient expectation about who undertakes
care. Professional expectations may also require
a shift, having implications for the balance of
staffing between primary and secondary care,
and the training of healthcare professionals
Nonparametric Analysis of Time-Inconsistent Preferences
No full textThis paper provides a revealed preference characterisation of quasi-hyperbolic discounting
which is designed to be applied to readily-available expenditure surveys. We describe
necessary and sufficient conditions for the leading forms of the model and also study the
consequences of the restrictions on preferences popularly used in empirical lifecycle consumption
models. Using data from a household consumption panel dataset we explore the prevalence of time-inconsistent behaviour. The quasi-hyperbolic model provides a significantly more successful account of behaviour than the alternatives considered. We estimate the joint distribution of time preferences and the distribution of discount functions at various
time horizons
Sealing Performance of a Turbine Rim Chute Seal Under Rotationally-Induced Ingestion
No full textThis study focuses on the sealing capability of a turbine rim seal subject to hot gas ingestion driven purely by the rotor disc pumping effect rather than that induced by mainstream features such as vane and rotor blade passing. The aim is to provide useful data for conditions
in which rotation dominates, and to clarify the flow physics involved in rim sealing.
Experimental measurements of sealing effectiveness for a chute seal are presented for the first
time without and with an axial, axisymmetric mainstream flow external to the seal. The test
matrix covers a range of rotational Reynolds number, Re , from 1.5x106 to 3x106, and nondimensional
flow rate, C , from 0 to 4x104 with the mainstream flow (when present) scaled to match engine representative conditions of axial Reynolds number, Re . Results from steady pressure and gas concentration measurements within the rotor-stator disc cavity and the rim
seal gap are presented and compared to published data for other seal designs. Sealing
performance of the chute seal is somewhat similar to that of axial clearance seals with the same
minimum clearance
Novel approaches for assessing circadian rhythmicity in humans A review
No full textTemporal organisation of molecular and physiological processes is driven by environmental and
behavioural cycles, as well as by self-sustained molecular circadian oscillators. Quantification of
phase, amplitude, period, and disruption of circadian rhythms is essential for understanding their
contribution to sleep-wake disorders, social jet-lag, inter-individual differences in entrainment and
the development of chrono-therapeutics.
Traditionally, assessment of the human circadian system, and the output of the SCN in particular,
required collection of long time series of univariate markers such as melatonin or core body
temperature. Data were collected in specialised laboratory protocols designed to control for
environmental and behavioural influences on rhythmicity. These protocols are time-consuming,
expensive, and are not practical for assessing circadian status in patients or in participants in
epidemiologic studies.
Novel approaches for assessment of circadian parameters of the SCN or peripheral oscillators have
been developed. They are based on machine learning or mathematical model-informed analyses of
features extracted from one or a few samples of high dimensional data such as transcriptomes,
metabolomes, long term simultaneous recording of activity, light exposure, skin temperature, and
heart rate, or in vitro approaches. Here, we review whether these approaches successfully quantify
parameters of central and peripheral circadian oscillators as indexed by gold standard markers.
While several approaches perform well under entrained conditions when sleep occurs at night, the
methods either perform worse in other conditions such as shift work, or they have not been
assessed under any conditions other than entrainment and thus we do not yet know how robust
they are.
Novel approaches for the assessment of circadian parameters hold promise for circadian medicine,
chrono-therapeutics, and chrono-epidemiology. There remains a need to validate these approaches
against gold standard markers, in individuals of all sexes and ages, in patient populations, and, in
particular, under conditions in which behavioural cycles are displaced.</p
A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks
No full textMetabolism underpins the pathogenic strategy of the causative agent of TB, Mycobacterium tuberculosis (Mtb), and therefore metabolic pathways have recently re-emerged as attractive drug targets. A powerful approach to study Mtb metabolism as a whole, rather than just individual enzymatic components, is to use a systems biology framework, such as a Genome-Scale Metabolic Network (GSMN) that allows the dynamic interactions of all the components of metabolism to be interrogated together. Several GSMNs networks have been constructed for Mtb and used to study the complex relationship between the Mtb genotype and its phenotype. However, the utility of this approach is hampered by the existence of multiple models, each with varying properties and performances. Here we systematically evaluate eight recently published metabolic models of Mtb-H37Rv to facilitate model choice. The best performing models, sMtb2018 and iEK1011, were refined and improved for use in future studies by the TB research community
Complex Stability and an Irrevertible Transition Reverted by Peptide and Fibroblasts in a Dynamic Model of Innate Immunity
No full textWe here apply a control analysis and various types of stability analysis to an in silico model of innate immunity that addresses the management of inflammation by a therapeutic peptide. Motivation is the observation, both in silico and in experiments, that this therapy is not robust. Our modeling results demonstrate how (1) the biological phenomena of acute and chronic modes of inflammation may reflect an inherently complex bistability with an irrevertible flip between the two modes, (2) the chronic mode of the model has stable, sometimes unique, steady states, while its acute-mode steady states are stable but not unique, (3) as witnessed by TNF levels, acute inflammation is controlled by multiple processes, whereas its chronic-mode inflammation is only controlled by TNF synthesis and washout, (4) only when the antigen load is close to the acute mode's flipping point, many processes impact very strongly on cells and cytokines, (5) there is no antigen exposure level below which reduction of the antigen load alone initiates a flip back to the acute mode, and (6) adding healthy fibroblasts makes the transition from acute to chronic inflammation revertible, although (7) there is a window of antigen load where such a therapy cannot be effective. This suggests that triple therapies may be essential to overcome chronic inflammation. These may comprise (1) anti-immunoglobulin light chain peptides, (2) a temporarily reduced antigen load, and (3a) fibroblast repopulation or (3b) stem cell strategies
SP-GAN: Self-growing and Pruning Generative Adversarial Networks
No full textThis paper presents a new Self-growing and Pruning
Generative Adversarial Network (SP-GAN) for realistic image
generation. In contrast to traditional GAN models, our SPGAN
is able to dynamically adjust the size and architecture
of a network in the training stage, by using the proposed selfgrowing and pruning mechanisms. To be more specific, we first train two seed networks as the generator and discriminator, each only contains a small number of convolution kernels. Such small-scale networks are much easier and faster to train than large-capacity networks. Second, in the self-growing step,we replicate the convolution kernels of each seed network to
augment the scale of the network, followed by fine-tuning the augmented/expanded network. More importantly, to prevent the excessive growth of each seed network in the self-growing stage, we propose a pruning strategy that reduces the redundancy of an augmented network, yielding the optimal scale of the network. Last, we design a new adaptive loss function that is treated as a variable loss computational process for the training of the proposed SP-GAN model. By design, the hyperparameters of the loss function can dynamically adapt to different training stages. Experimental results obtained on a set of datasets
demonstrate the merits of the proposed method, especially in
terms of the stability and efficiency of network training. The source code of the proposed SP-GAN method is publicly available at https://github.com/Lambert-chen/SPGAN.git
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