The experiences of lesbian, gay and bisexual people with dementia

The subjective experience of dementia for lesbian, gay and bisexual individuals is largely absent from the extant literature. This study aimed to explore what it means to experience dementia in this context given the documented psychosocial influences facing this population. A second aim was to develop understanding of these experiences within dyadic relationships. Ten semi-structured interviews were conducted with lesbian, gay and bisexual individuals with dementia and people with whom they had a significant relationship. Interpretative Phenomenological Analysis of transcripts identified three superordinate themes reflecting characteristics of participants’ experience: Duality in managing dementia; Giving yourself away vs. holding onto yourself; and Relationships as sheltered harbours. Ten subthemes indicate processes these individuals adopt to adjust and make sense of their experience of dementia. This included decisions around concealment, ensuring safety and the promotion of personhood and couplehood. In line with findings for heterosexual couples, partners had an important role in maintaining the identity of the person with dementia. Results suggest additional and distinct challenges, including experienced and perceived discrimination and heterosexism. In response to these conditions, interviewees worked to resist a ‘double stigma’ of dementia and sexuality. Findings indicated areas of improvement for dementia services, including training in inclusive practice

The association between herd- and cow-level factors and somatic cell count of Irish dairy cows

peer-reviewedSomatic cell count (SCC) is an indicator of both udder health and milk quality and is measured at an animal level through national milk recording schemes. The objective of this study was to assess the animal and herd factors contributing to elevated SCC (i.e. poorer milk quality). Test day records (n = 2,658,928) from 519,456 cow lactations obtained between 2007 and 2011 were included in the analyses. Herd factors tested included the geographical region of the herd and production system operated (spring calving or mixed calving system). Animal factors tested included breed, parity and age nested within parity. Four definitions of normalised SCC (i.e. SCS) were considered: 1) average test-day SCS within a 24 hour period (TD_SCS), 2) maximum SCS (peak_SCS), 3) minimum SCS (min_SCS), and 4) average SCS (avg_SCS) recorded across cow lactation; in addition, the proportion of test day records with an SCC count >200,000 (prop_200) or >250,000 (prop_250) within cow lactation were included. Following adjustment for fixed effects, average TD_SCS was 179,308 cells per mL while avg_SCS, and average min_SCS and peak_SCS were 119,481, 50,992 and 298,813 cells per mL, respectively. All animal and herd factors had a significant effect on SCC. Older animals, animals which were younger at calving than contemporaries and Holstein animals had higher SCC than younger alternative breed animals who calved at the median age. In addition, mixed calving production systems and herds in Connaught had higher SCC than spring calving herds in the other regions of Ireland.The authors gratefully acknowledge funding for this work from the Department of Agriculture, Fisheries and Food under the Joint FIRM / RSF Initiative (Project Number: 10/RD/AAQUALITYMILK/ TMFRC713)

Clustering South African households based on their asset status using latent variable models

The Agincourt Health and Demographic Surveillance System has since 2001 conducted a biannual household asset survey in order to quantify household socio-economic status (SES) in a rural population living in northeast South Africa. The survey contains binary, ordinal and nominal items. In the absence of income or expenditure data, the SES landscape in the study population is explored and described by clustering the households into homogeneous groups based on their asset status. A model-based approach to clustering the Agincourt households, based on latent variable models, is proposed. In the case of modeling binary or ordinal items, item response theory models are employed. For nominal survey items, a factor analysis model, similar in nature to a multinomial probit model, is used. Both model types have an underlying latent variable structure - this similarity is exploited and the models are combined to produce a hybrid model capable of handling mixed data types. Further, a mixture of the hybrid models is considered to provide clustering capabilities within the context of mixed binary, ordinal and nominal response data. The proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD). The MFA-MD model is applied to the survey data to cluster the Agincourt households into homogeneous groups. The model is estimated within the Bayesian paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings result, providing insight to the different socio-economic strata within the Agincourt region.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS726 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees

Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made

Analysis of cybersecurity threats in Industry 4.0: the case of intrusion detection

Nowadays, industrial control systems are experiencing a new revolution with the interconnection of the operational equipment with the Internet, and the introduction of cutting-edge technologies such as Cloud Computing or Big data within the organization. These and other technologies are paving the way to the Industry 4.0. However, the advent of these technologies, and the innovative services that are enabled by them, will also bring novel threats whose impact needs to be understood. As a result, this paper provides an analysis of the evolution of these cyber-security issues and the requirements that must be satis ed by intrusion detection defense mechanisms in this context.Springer ; Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Risk factors associated with detailed reproductive phenotypes in dairy and beef cows

peer-reviewedThis article was first published in animal, Volume 8, Issue 05, May 2014, pp 695-703, © The Animal Consortium 2014The objective of this study was to identify detailed fertility traits in dairy and beef cattle from transrectal ultrasonography records and quantify the associated risk factors. Data were available on 148 947 ultrasound observations of the reproductive tract from 75 949 cows in 843 Irish dairy and beef herds between March 2008 and October 2012. Traits generated included (1) cycling at time of examination, (2) cystic structures, (3) early ovulation, (4) embryo death and (5) uterine score; the latter was measured on a scale of 1 (good) to 4 (poor) characterising the tone of the uterine wall and fluid present in the uterus. After editing, 72 773 records from 44 415 dairy and beef cows in 643 herds remained. Factors associated with the logit of the probability of a positive outcome for each of the binary fertility traits were determined using generalised estimating equations; linear mixed model analysis was used for the analysis of uterine score. The prevalence of cycling, cystic structures, early ovulation and embryo death was 84.75%, 3.87%, 7.47% and 3.84%, respectively. The occurrence of the uterine heath score of 1, 2, 3 and 4 was 70.63%, 19.75%, 8.36% and 1.26%, respectively. Cows in beef herds had a 0.51 odds (95% CI = 0.41 to 0.63, P<0.001) of cycling at the time of examination compared with cows in dairy herds; stage of lactation at the time of examination was the same in both herd types. Furthermore, cows in dairy herds had an inferior uterine score (indicating poorer tone and a greater quantity of uterine fluid present) compared with cows in beef herds. The likelihood of cycling at the time of examination increased with parity and stage of lactation, but was reduced in cows that had experienced dystocia in the previous calving. The presence of cystic structures on the ovaries increased with parity and stage of lactation. The likelihood of embryo/foetal death increased with parity and stage of lactation. Dystocia was not associated with the presence of cystic structures or embryo death. Uterine score improved with parity and stage of lactation, while cows that experienced dystocia in the previous calving had an inferior uterine score. Heterosis was the only factor associated with increased likelihood of early ovulation. The fertility traits identified, and the associated risk factors, provide useful information on the reproductive status of dairy and beef cows.Funding from the Department of Agriculture, Food and Marine Research Stimulus Fund (RSF 11/S/133) and the OptiMIR project is gratefully acknowledged

Mid-infrared spectrometry of milk as a predictor of energy intake and efficiency in lactating dairy cows

peer-reviewedInterest is increasing in the feed intake complex of individual dairy cows, both for management and animal breeding. However, energy intake data on an individual-cow basis are not routinely available. The objective of the present study was to quantify the ability of routinely undertaken mid-infrared (MIR) spectroscopy analysis of individual cow milk samples to predict individual cow energy intake and efficiency. Feed efficiency in the present study was described by residual feed intake (RFI), which is the difference between actual energy intake and energy used (e.g., milk production, maintenance, and body tissue anabolism) or supplied from body tissue mobilization. A total of 1,535 records for energy intake, RFI, and milk MIR spectral data were available from an Irish research herd across 36 different test days from 535 lactations on 378 cows. Partial least squares regression analyses were used to relate the milk MIR spectral data to either energy intake or efficiency. The coefficient of correlation (REX) of models to predict RFI across lactation ranged from 0.48 to 0.60 in an external validation data set; the predictive ability was, however, strongest (REX = 0.65) in early lactation (<60 d in milk). The inclusion of milk yield as a predictor variable improved the accuracy of predicting energy intake across lactation (REX = 0.70). The correlation between measured RFI and measured energy balance across lactation was 0.85, whereas the correlation between RFI and energy balance, both predicted from the MIR spectrum, was 0.65. Milk MIR spectral data are routinely generated for individual cows throughout lactation and, therefore, the prediction equations developed in the present study can be immediately (and retrospectively where MIR spectral data have been stored) applied to predict energy intake and efficiency to aid in management and breeding decisions

The MGB Challenge: Evaluating Multi-genre Broadcast Media Recognition

This paper describes the Multi-Genre Broadcast (MGB) Challenge at ASRU 2015, an evaluation focused on speech recognition, speaker diarization, and "lightly supervised" alignment of BBC TV recordings. The challenge training data covered the whole range of seven weeks BBC TV output across four channels, resulting in about 1,600 hours of broadcast audio. In addition several hundred million words of BBC subtitle text was provided for language modelling. A novel aspect of the evaluation was the exploration of speech recognition and speaker diarization in a longitudinal setting - i.e. recognition of several episodes of the same show, and speaker diarization across these episodes, linking speakers. The longitudinal tasks also offered the opportunity for systems to make use of supplied metadata including show title, genre tag, and date/time of transmission. This paper describes the task data and evaluation process used in the MGB challenge, and summarises the results obtained

Bacterial metabolites and cardiovascular risk in children with chronic kidney disease

Cardiovascular complications are the major cause of the marked morbidity and mortality associated with chronic kidney disease (CKD). The classical cardiovascular risk factors such as diabetes and hypertension undoubtedly play a role in the development of cardiovascular disease (CVD) in adult CKD patients; however, CVD is just as prominent in children with CKD who do not have these risk factors. Hence, the CKD-specific pathophysiology of CVD remains incompletely understood. In light of this, studying children with CKD presents a unique opportunity to analyze CKD-associated mechanisms of CVD more specifically and could help to unveil novel therapeutic targets.Here, we comprehensively review the interaction of the human gut microbiome and the microbial metabolism of nutrients with host immunity and cardiovascular end-organ damage. The human gut microbiome is evolutionary conditioned and modified throughout life by endogenous factors as well as environmental factors. Chronic diseases, such as CKD, cause significant disruption to the composition and function of the gut microbiome and lead to disease-associated dysbiosis. This dysbiosis and the accompanying loss of biochemical homeostasis in the epithelial cells of the colon can be the result of poor diet (e.g., low-fiber intake), medications, and underlying disease. As a result of dysbiosis, bacteria promoting proteolytic fermentation increase and those for saccharolytic fermentation decrease and the integrity of the gut barrier is perturbed (leaky gut). These changes disrupt local metabolite homeostasis in the gut and decrease productions of the beneficial short-chain fatty acids (SCFAs). Moreover, the enhanced proteolytic fermentation generates unhealthy levels of microbially derived toxic metabolites, which further accumulate in the systemic circulation as a consequence of impaired kidney function. We describe possible mechanisms involved in the increased systemic inflammation in CKD that is associated with the combined effect of SCFA deficiency and accumulation of uremic toxins. In the future, a more comprehensive and mechanistic understanding of the gut-kidney-heart interaction, mediated largely by immune dysregulation and inflammation, might allow us to target the gut microbiome more specifically in order to attenuate CKD-associated comorbidities