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Construction and evaluation of a mindfulness-based quality of life and well-being program (MQW) in a randomized trial
Get PDFDue to the multi-factorial nature of the self-report of happiness, an enhancement program was designed that focused on mental style (subjective processes), and relationships, work, money, health, and leisure (objective life domains). An examination of interventions revealed mindfulness training (subjective factors) and goal setting (objective factors) as effective change modalities. To address this, the Mindfulness-based Quality of Life and Well-being Program (MQW) was developed and evaluated against the Mindfulness Attention Awareness Scale, Quality of Life Index, Personal Wellbeing Index–Adult, Positive and Negative Affect Scale, the Satisfaction with Life scale, and the newly developed Clinical Quality of Life Scale (CLINQOL). To explore training protocol effects, the program was delivered in a graduated (6 weekly sessions x 2 hours) and intensive (2 consecutive days x 6 hours) format. Using a randomized trial, participants were allocated across these conditions and a control. A total of 191 participants completed the study and were assessed at pre, post and follow up time points. Increases in mindfulness, quality of life, subjective well-being, and positive and negative affect (not life satisfaction), were greater in treated (combined formats) than control participants at post-test, and for mindfulness at follow up. Other than an increase in mindfulness for the 2 day condition at follow up, changes were similar in both intervention formats. Finally, to investigate what unique difference the MQW might have in comparison to teaching just mindfulness, the full version of the program was compared to an expanded section of the mindfulness component of the program. A total of 74 subjects began the program and filled out assessments across the three time periods. There was no difference between groups or an interaction between group and time. Overall, the findings provide preliminary evidence that a multi-dimensional training approach, using mindfulness and goal setting, may be a beneficial intervention model to enhance subjective and objective components in the perception of quality of life and well-being. However, further investigation into its added benefit to mindfulness alone is required
Age of eruption of the first permanent incisors varies between Merino genotypes and is related to liveweight
No full textThe eruption of the first permanent incisors in sheep determines the classification of lamb and hogget and impacts the sale value of animals in Australia. This study tested the hypothesis that the age of incisor eruption would differ between progeny from different Merino sires and would occur earlier for progeny that were heavier at 12 months of age. The study utilised wether progeny at a site in Western Australia from 29 sires born in 2016 (n = 347) or 2017 (n = 553), and ewe and wether (castrated male) progeny at a second site in New South Wales from 29 sires born in 2017 (n = 713 ewes and 343 wethers) or 2018 (n = 638 ewes and 457 wethers). Classing of incisor eruption commenced at 10–11 months of age and was recorded monthly until 19 or 20 months of age at the two sites. The average age of incisor eruption varied by up to 2.5 months between sire groups (P < 0.001) and incisor eruption was completed for all progeny within a sire group over three months for some sires but over 6 months for other sires. Incisor eruption occurred earlier for animals that were heavier at 12 months of age (P < 0.001). The period when animals gained weight up to 12 months also influenced incisor eruption, as differences in liveweight at weaning had twice the effect on age of incisor eruption compared with differences in liveweight gain post-weaning at both sites. Estimated stage of maturity at 12 months of age had minimal effects on subsequent age of incisor eruption, and regardless, the large variation in age of incisor eruption between sires were not accounted for by liveweight or stage of maturity at 12 months. In addition to selecting Merino sires that produce progeny that can be sold as lamb at an older age, farmers may also benefit from understanding the pattern of the first permanent incisors eruption specific to their genotype and monitoring liveweights and liveweight change to optimise the time and value of animals at sale
Margin-based approach for outlier detection of industrial design data using a modified general regression neural network
No full textThe choice of components in industrial design involves setting design parameters that typically must reside inside permissible ranges called “design margins”. This paper proposes a novel automated method called the Margin-Based General Regression Neural Network (MB-GRNN) that classifies design errors for design parameters that are outside of permissible ranges as outliers, directly from industrial design data, using an unsupervised machine learning approach. The method is based on a modified GRNN that estimates extremal margin boundaries of design parameters by self-learning the features from datasets. These extremal permissible margin boundaries are determined by “stretching out” the upper and lower GRNN surfaces using an iterative application of stretch factors (a second kernel weighting factor). The method creates a variable insensitive band surrounding the data cloud, interlinked with the normal regression function, providing upper and lower margin boundaries. These boundaries can then be used to determine outliers and to predict a range of permissible values of design parameters during design. Pushing out extremal margin boundaries reduce the false identification of outliers. This classification technique could be used by industrial engineers to detect likely outliers and to predict a range of permissible output limits for chosen design parameters. The efficacy of this method has been validated against the widespread Parzen window method by comparing experimental results from three multivariate datasets. It was found that the two methods have different but complementary capabilities. The MB-GRNN also uses a modified algorithm for estimating the smoothing parameter using a combination of clustering, k-nearest neighbor, and localized covariance matrix
Simulation platforms in initial teacher education: Past practice informing future potentiality
No full textDespite evidence promoting simulation platforms as effective modes of learning, virtual simulation is underutilised in Australian Initial Teacher Education (ITE) programs, and as such, casts doubt on the sustainability of next generation simulation platforms. As a case example, we present findings from a systematic review of the literature on the benefits and limitations of Second Life as one of the most widely adopted simulation platforms used in ITE. We reveal salient issues from the literature on Second Life in teacher education that may provide key insight into the sustainability of future simulation platforms in ITE. Grossman's (2009) Pedagogies of practice are used to frame the discussion and offer insight into the opportunities and challenges for educators facilitated by simulation platforms. We recommend broad-based research to capture the transformative pedagogical qualities of simulation platforms and call for an exploration into education policies that both hinder and help the adaptation of next generation simulation platforms within initial teacher education
Metal(loid) pollution, not urbanisation nor parasites predicts low body condition in a wetland bioindicator snake
No full textUrban ecosystems and remnant habitat 'islands' therein, provide important strongholds for many wildlife species including those of conservation significance. However, the persistence of these habitats can be undermined if their structure and function are too severely disrupted. Urban wetlands, specifically, are usually degraded by a monoculture of invasive vegetation, disrupted hydrology, and chronic-contamination from a suite of anthropogenic pollutants. Top predators—as bioindicators—can be used to assess and monitor the health of these ecosystems. We measured eight health parameters (e.g., parasites, wounds and scars, tail loss and body condition) in a wetland top predator, the western tiger snake, Notechis scutatus occidentalis. For three years, snakes were sampled across four wetlands along an urban gradient. For each site, we used GIS software to measure the area of different landscapes and calculate an urbanisation–landscape score. Previously published research on snake contamination informed our calculations of a metal-pollution index for each site. We used generalised linear mixed models to assess the relationship between all health parameters and site variables. We found the metal-pollution index to have the most significant association with poor body condition. Although parasitism, tail loss and wounds differed among sites, none of these parameters influenced body condition. Additionally, the suite of health parameters suggested differing health status among sites; however, our measure of contemporary landscape urbanisation was never a significant predictor variable. Our results suggest that the health of wetland predators surrounding a rapidly growing city may be offset by higher levels of environmental pollution
Predictive modelling and optimization of HVAC systems using neural network and particle swarm optimization algorithm
No full textThe concept of maintaining indoor environmental quality comprising building indoor temperature, relative humidity, CO2, and volatile organic compound (VOC) level poses new challenges to the optimal operation of heating, ventilation and air-conditioning (HVAC) systems. While existing case studies demonstrate the energy-saving potentials for efficient HVAC operation, there is a lack of studies quantifying energy savings whilst considering indoor environmental conditions. This study proposes a state-of-the-art modelling and optimization approach to minimize the energy consumption of the HVAC systems without compromising indoor environmental quality. While the primary objective of ensuring optimal operation of HVAC systems is to minimize energy consumption, controlling indoor environmental parameters to remain within the acceptable range imposes excess energy use. These two conflicting objectives constitute a multi-variable constrained optimization problem that has been solved using a particle swarm optimization (PSO) algorithm. Real-time predictive models are developed for the individual indoor environmental parameters and HVAC energy consumption using a Nonlinear Autoregressive Exogenous (NARX) neural network (NN). During model development, models' performance is optimized in terms of complexity, predictive accuracy, and ease of application to a real system. The proposed predictive models are then optimized to provide an optimal control setting for the HVAC systems considering seasonal variations. The results indicate that it is possible to reduce 7.8% of total energy, without negotiating indoor environmental conditions, e.g., air temperature 19.60–28.20°C and relative humidity 30–65% as per ASHRAE Standard 55, and CO2 ≤ 800 ppm and VOC ≤1000 ppm as per AS 1668.2
Janssen COVID-19 vaccine tolerated in 10 patients with confirmed polyethylene glycol allergy
Get PDFPolyethylene glycols (PEGs) and the structurally related polysorbates (PEG sorbitans—PEG molecular weight, 880-1056 g/mol) are excipients commonly used in small-molecule pharmaceutical drugs, as well as in some vaccines and most mAbs..
Phytochemical control of poultry coccidiosis: A review
Get PDFAvian coccidiosis is a major parasitic disorder in chickens resulting from the intracellular apicomplexan protozoa Eimeria that target the intestinal tract leading to a devastating disease. Eimeria life cycle is complex and consists of intra- and extracellular stages inducing a potent inflammatory response that results in tissue damage associated with oxidative stress and lipid peroxidation, diarrheal hemorrhage, poor growth, increased susceptibility to other disease agents, and in severe cases, mortality. Various anticoccidial drugs and vaccines have been used to prevent and control this disorder; however, many drawbacks have been reported. Drug residues concerning the consumers have directed research toward natural, safe, and effective alternative compounds. Phytochemical/herbal medicine is one of these natural alternatives to anticoccidial drugs, which is considered an attractive way to combat coccidiosis in compliance with the “anticoccidial chemical-free” regulations. The anticoccidial properties of several natural herbal products (or their extracts) have been reported. The effect of herbal additives on avian coccidiosis is based on diminishing the oocyst output through inhibition or impairment of the invasion, replication, and development of Eimeria species in the gut tissues of chickens; lowering oocyst counts due to the presence of phenolic compounds in herbal extracts which reacts with cytoplasmic membranes causing coccidial cell death; ameliorating the degree of intestinal lipid peroxidation; facilitating the repair of epithelial injuries; and decreasing the intestinal permeability induced by Eimeria species through the upregulation of epithelial turnover. This current review highlights the anticoccidial activity of several herbal products, and their other beneficial effects
Essential oils and their nanoemulsions as green alternatives to antibiotics in poultry nutrition: A comprehensive review
Get PDFIncreasing market pressure to reduce the use of antibiotics and the Veterinary Feed Directive of 2019 have led to expanded research on alternate antibiotic solutions. This review aimed to assess the benefits of using essential oils (EOs) and their nanoemulsions (NEs) as feed supplements for poultry and their potential use as antibiotic alternatives in organic poultry production. Antibiotics are commonly used to enhance the growth and prevent diseases in poultry animals due to their antimicrobial activities. EOs are a complex mixture of volatile compounds derived from plants and manufactured via various fermentation, extraction, and steam distillation methods. EOs are categorized into 2 groups of compounds: terpenes and phenylpropenes. Differences among various EOs depend on the source plant type, physical and chemical soil conditions, harvest time, plant maturity, drying technology used, storage conditions, and extraction time. EOs can be used for therapeutic purposes in various situations in broiler production as they possess antibacterial, antifungal, antiparasitic, and antiviral activities. Several studies have been conducted using various combinations of EOs or crude extracts of their bioactive compounds to investigate their complexity and applications in organic poultry production. NEs are carrier systems that can be used to overcome the volatile nature of EOs, which is a major factor limiting their application. NEs are being progressively used to improve the bioavailability of the volatile lipophilic components of EOs. This review discusses the use of these nonantibiotic alternatives as antibiotics for poultry feed in organic poultry production
Characterising splicing defects of ABCA4 variants within exons 13–50 in patient-derived fibroblasts
Get PDFThe ATP-binding cassette subfamily A member 4 gene (ABCA4)-associated retinopathy, Stargardt disease, is the most common monogenic inherited retinal disease. Given the pathogenicity of numerous ABCA4 variants is yet to be examined and a significant proportion (more than 15%) of ABCA4 variants are categorized as splice variants in silico, we therefore established a fibroblast-based splice assay to analyze ABCA4 variants in an Australian Stargardt disease cohort and characterize the pathogenic mechanisms of ABCA4 variants. A cohort of 67 patients clinically diagnosed with Stargardt disease was recruited. Genomic DNA was analysed using a commercial panel for ABCA4 variant detection and the consequences of ABCA4 variants were predicted in silico. Dermal fibroblasts were propagated from skin biopsies, total RNA was extracted and the ABCA4 transcript was amplified by RT-PCR. Our analysis identified a total of 67 unique alleles carrying 74 unique variants. The most prevalent splice-affecting complex allele c.[5461-10T > C; 5603A > T] was carried by 10% of patients in a compound heterozygous state. ABCA4 transcripts from exon 13 to exon 50 were readily detected in fibroblasts. In this region, aberrant splicing was evident in 10 out of 57 variant transcripts (18%), carried by 19 patients (28%). Patient-derived fibroblasts provide a feasible platform for identification of ABCA4 splice variants located within exons 13–50. Experimental evidence of aberrant splicing contributes to the pathogenic classification for ABCA4 variants. Moreover, identification of variants that affect splicing processes provides opportunities for intervention, in particular antisense oligonucleotide-mediated splice correction