12508 research outputs found
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Services for people with young onset dementia: The 'Angela' project national UK survey of service use and satisfaction
Get PDFYesObjectives: Young onset dementia is associated with distinctive support needs but
existing research on service provision has been largely small scale and qualitative.
Our objective was to explore service use, cost and satisfaction across the UK.
Methods: Information about socio‐demographic characteristics, service use and
satisfaction were gathered from people with young onset dementia (YOD) and/or a
family member/supporter via a national survey.
Results: Two hundred and thirty‐three responses were analysed. Diagnosis was
most commonly received through a Memory Clinic or Neurology. The type of
service delivering diagnosis impacted on post‐diagnostic care. Those diagnosed in
specialist YOD services were more likely to receive support within the first 6 weeks
and receive ongoing care in the service where they were diagnosed. Ongoing care
management arrangements varied but generally care was lacking. Around 42%
reported no follow‐up during 6‐weeks after diagnosis; over a third reported seeing
no health professional within the previous 3 months; just over a third had a key
worker and just under a third had a care plan. Satisfaction and quality of care were
highest in specialist services. Almost 60% of family members spent over 5 h per day
caring; median costs of health and social care, 3 months, 2018, were £394 (interquartile range £389 to 640).
Conclusions: Variation across diagnostic and post‐diagnostic care pathways for
YOD leads to disparate experiences, with specialist young onset services being
associated with better continuity, quality and satisfaction. More specialist services
are needed so all with YOD can access age‐appropriate care.Alzheimer's Society. Grant Number: 278 AS-PG-15b-03
Gender inequality in education: An Investigation into the effects of School Management Practices on Health Behaviours of Female Students. (A Study of Selected Senior Secondary Schools in Lagos State)
Get PDFThis research explores gender inequality in education, with a focus to examine the
implications of gender disparities in schools on girls’ health and education. The study sought
to investigate whether school management practices is a possible factor impacting the
health behaviours of female students in senior secondary schools in Lagos, Nigeria. The
study employed mixed methods design and gathered primary data in two consecutive
phases, in line with sequential explanatory design. Data in Phase one was gathered through
the use of questionnaire while phase 2 gathered primary data using semi-structured
interviews to complement survey data. The sample frame included 2 public secondary
schools, 42 students, 9 teachers, 1 vice principal and 2 principals. Quantitative data were
analyzed using Statistical Package for Social Sciences (SPSS), while qualitative data were
analyzed with help of ATLAS.ti. The findings of the study revealed school related barriers
that influence high absenteeism and dropout among girls. Further findings also show the
schools lack appropriate school management policies that promote healthful behaviours and
encourage positive learning environment for girls. The researcher recommends leadership
and school management training for school principals and their deputies, improving quality of health instruction in the curriculum, developing strict policy against school-related gender-based violence and adopting health-promoting policies
Fast and Accurate Image Feature Detection for On-The-Go Field Monitoring Through Precision Agriculture. Computer Predictive Modelling for Farm Image Detection and Classification with Convolution Neural Network (CNN)
No full textThis study aimed to develop a novel end-to-end plant diagnosis model for the
analysis of plant health conditions in near real-time to optimize the rate of
production on farmlands for an intensive, yet environmentally safe farming
production to preserve the natural environment.
First, field research was conducted to determine the extent of the problems
faced by farmers in agricultural production. This allowed us to refine the
research statement and the level of technology involved in the production
processes. The advantages of unmanned aerial systems were exploited in the
continuous monitoring of farm plantations to develop automated and accurate
measures of farm conditions.
To this end, this thesis applies the Precision Agricultural technology as a data based management system that takes into account spatial variations by using
the Global Positioning System, Geographical Information System, remote
sensing, yield monitors, mapping, and guidance system for variable rate
applications.
An unmanned aerial vehicle embedded with an optic and radiometric sensor
was used to obtain high spectral resolution images of plantation status during
normal production/growth cycle. Then, an ensemble of classifiers with Convolution Neural Networks (CNN) was used as off the shelf feature extractor
to train images to develop an end-to-end feature detection and multiclass
classification system for plant overall health’s conditions. Whereby previous
works have concentrated on using CNN as off the shelf feature extractor and
model training to detect only plant diseases from plants.
To date, no research has yet been carried out to develop an end-to-end model
for the overall plant diagnosis system. Previous studies focused on the
detection of diseases at any given time, making it difficult to implement
comprehensive real-time PA systems.
Applying the pretrained model to the new images showed that the model can
accurately predict any plant condition with an average of 97% accuracy
Supervised classification of bradykinesia in Parkinson’s disease from smartphone videos
No full textNoBackground: Slowness of movement, known as bradykinesia, is the core clinical sign of Parkinson's and fundamental to its diagnosis. Clinicians commonly assess bradykinesia by making a visual judgement of the patient tapping finger and thumb together repetitively. However, inter-rater agreement of expert assessments has been shown to be only moderate, at best.
Aim: We propose a low-cost, contactless system using smartphone videos to automatically determine the presence of bradykinesia.
Methods: We collected 70 videos of finger-tap assessments in a clinical setting (40 Parkinson's hands, 30 control hands). Two clinical experts in Parkinson's, blinded to the diagnosis, evaluated the videos to give a grade of bradykinesia severity between 0 and 4 using the Unified Pakinson's Disease Rating Scale (UPDRS). We developed a computer vision approach that identifies regions related to hand motion and extracts clinically-relevant features. Dimensionality reduction was undertaken using principal component analysis before input to classification models (Naïve Bayes, Logistic Regression, Support Vector Machine) to predict no/slight bradykinesia (UPDRS = 0–1) or mild/moderate/severe bradykinesia (UPDRS = 2–4), and presence or absence of Parkinson's diagnosis.
Results: A Support Vector Machine with radial basis function kernels predicted presence of mild/moderate/severe bradykinesia with an estimated test accuracy of 0.8. A Naïve Bayes model predicted the presence of Parkinson's disease with estimated test accuracy 0.67.
Conclusion: The method described here presents an approach for predicting bradykinesia from videos of finger-tapping tests. The method is robust to lighting conditions and camera positioning. On a set of pilot data, accuracy of bradykinesia prediction is comparable to that recorded by blinded human experts
Ritual and Funerary Rites in Later Prehistoric Scotland: An Analysis of Faunal Assemblages from the Covesea Caves
No full textThe Covesea Caves are a series of later prehistoric sites that form a complex
mortuary landscape. Previous excavations of the caves have provided evidence for
the decapitation, disarticulation, and intentional deposition of human remains.
Although there has been substantial analysis of the human remains, there has been
little consideration of the significant number of faunal remains recovered during
numerous excavations. This research represents the first focused examination of the
extensive zooarchaeological record from the Covesea Caves, with an emphasis on
investigating characteristics of the faunal bone related to taphonomy and processing
in order to provide a proxy for the complex funerary treatments to which the human
remains were subject.
Analysis of Covesea Cave 2 revealed a narrative of ritual and funerary activities,
from the Neolithic to the Post-Medieval Period. Zooarchaeological analysis has
illustrated how certain species were significant in ritual activity, and thus utilised
specifically in funerary rites. The results from this research shed more light on past
cosmologies and the importance of non-human species to humans in both life and
death.Funding for fieldwork was provided by Historic Environment Scotland and Aberdeenshire Council.
Lab work and species confirmation was funded by a generous grant from the British Cave Research Association.
Funding for this [comparative] analysis was provided by the following organisations:
The Prehistoric Society,
The Society of Antiquaries of Scotland,
The Natural History Society of Glasgo
Prevalence and drivers of false-positive rifampicin-resistant Xpert MTB/RIF results: a prospective observational study in Rwanda
Get PDFYesBackground: The Xpert MTB/RIF (Xpert) assay is used globally to rapidly diagnose tuberculosis and resistance to rifampicin. We investigated the frequency and predictors of false-positive findings of rifampicin resistance with Xpert. Methods: We did a prospective, observational study of individuals who were enrolled in a Rwandan nationwide diagnostic cohort study (DIAMA trial; NCT03303963). We included patients identified to have rifampicin resistance on initial Xpert testing. We did a repeat Xpert assay and used rpoB Sanger and deep sequencing alongside phenotypic drug susceptibility testing (pDST) to ascertain final rifampicin susceptibility status, with any (hetero)resistant result overriding. We used multivariable logistic regression to assess predictors of false rifampicin resistance on initial Xpert testing, adjusted for HIV status, tuberculosis treatment history, initial Xpert semi-quantitative bacillary load, and initial Xpert probe. Findings: Between May 4, 2017, and April 30, 2019, 175 people were identified with rifampicin resistance at initial Xpert testing, of whom 154 (88%) underwent repeat Xpert assay. 54 (35%) patients were confirmed as rifampicin resistant on repeat testing and 100 (65%) were not confirmed with resistance. After further testing and sequencing, 121 (79%) of 154 patients had a final confirmed status for rifampicin susceptibility. 57 (47%) of 121 patients were confirmed to have a false rifampicin resistance result and 64 (53%) had true rifampicin resistance. A high pretest probability of rifampicin resistance did not decrease the odds of false rifampicin resistance (adjusted odds ratio [aOR] 6·0, 95% CI 1·0–35·0, for new tuberculosis patients vs patients who needed retreatment). Ten (16%) of the 64 patients with true rifampicin resistance did not have confirmed rifampicin resistance on repeat Xpert testing, of whom four had heteroresistance. Of 63 patients with a very low bacillary load on Xpert testing, 54 (86%) were falsely diagnosed with rifampicin-resistant tuberculosis. Having a very low bacillary load on Xpert testing was strongly associated with false rifampicin resistance at the initial Xpert assay (aOR 63·6, 95% CI 9·9–410·4). Interpretation: The Xpert testing algorithm should include an assessment of bacillary load and retesting in case rifampicin resistance is detected on a paucibacillary sputum sample. Only when rifampicin resistance has been confirmed on repeat testing should multidrug-resistant tuberculosis treatment be started. When rifampicin resistance has not been confirmed on repeat testing, we propose that patients should be given first-line anti-tuberculosis drugs and monitored closely during treatment, including by baseline culture, pDST, and further Xpert testing.The European & Developing Countries Clinical Trials Partnership 2 programme, and Belgian Directorate General for Development Cooperation
Glycosyl disulfides: importance, synthesis and application to chemical and biological systems
Get PDFYesThe disulfide bond plays an important role in the formation and stabilisation of higher order structures of peptides and proteins, while in recent years interest in this functional group has been extended to carbohydrate chemistry. Rarely found in nature, glycosyl disulfides have attracted significant attention as glycomimetics, with wide biological applications including lectin binding, as key components of dynamic libraries to study carbohydrate structures, the study of metabolic and enzymatic studies, and even as potential drug molecules. This interest has been accompanied and fuelled by the continuous development of new methods to construct the disulfide bond at the anomeric centre. Glycosyl disulfides have also been exploited as versatile intermediates in carbohydrate synthesis, particularly as glycosyl donors. This review focuses on the importance of the disulfide bond in glycobiology and in chemistry, evaluating the different methods available to synthesise glycosyl disulfides. Furthermore, we review the role of glycosyl disulfides as intermediates and/or glycosyl donors for the synthesis of neoglycoproteins and oligosaccharides, before finally considering examples of how this important class of carbohydrates have made an impact in biological and therapeutic contexts.The authors thank the Institute of Cancer Therapeutics (University of Bradford) Doctoral Training Centre for financial support
A study proposing a data model for a dementia care mapping (DCM) data warehouse for potential secondary uses of dementia care data
No full textNoCopying or distributing in print or electronic forms without written permission of IGI Global is prohibited. There is growing emphasis on sharing and reusing dementia care-related datasets to improve the quality of dementia care. Consequently, there is a need to develop data management solutions for collecting, integrating and storing these data in formats that enhance opportunities for reuse. Dementia Care Mapping (DCM) is an observational tool that is in widespread use internationally. It produces rich, evidence-based data on dementia care quality. Currently, that data is primarily used locally, within dementia care services, to assess and improve quality of care. Information-rich DCM data provides opportunities for secondary use including research into improving the quality of dementia care. But an effective data management solution is required to facilitate this. A rationale for the warehousing of DCM data as a technical data management solution is suggested. The authors also propose a data model for a DCM data warehouse and present user-identified challenges for reusing DCM data within a warehouse
A Critical Review of the Role of Indicators in Implementing the Sustainable Development Goals
Get PDFYesThe 17 Sustainable Development Goals (SDGs) bring together environmental, social and economic concerns. They therefore have the potential to move society away from the dominant model of prosperity as purely economic toward a more holistic and ‘sustainable’ prosperity. But, the success of such a transformative agenda rests on its implementation. At the heart of planned implementation of the SDGs is a set of 230 indicators. Indicators have been strongly critiqued in a range of literatures. However, in the context of the SDGs, indicators have been described as ‘essential’ with little critical assessment of their role in implementation. Therefore, this chapter aims to provide this critical voice. To do this, the chapter reviews critiques of indicators from sustainability science, anthropology and sociology and provides illustrative cases of indicators implementation. From this review we are able to draw lessons for the use of indicators in SDG implementation. Specifically, the chapter argues that indicators are reductionist and struggle with contested concepts. Nevertheless, by making the operationalisation of concepts visible and enabling quantified analysis, indicators can have a useful role in SDG implementation. However, this requires that indicator critiques are taken seriously and inform indicator use.ESRC Research Centre for the Understanding of Sustainable Prosperity, Grant Number ES/M010163/
Wellbeing and productivity: a review of the literature
Get PDFYesESRC funded project Powering Productivity (ES/S015124/1