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The ‘person of moral growth’: a model of moral development based on personalist virtue ethics
Get PDFMoral development is crucial for a meaningful life. Many well-founded approaches and models are present in the moral development literature, which is a very diverse and populated field. The model of a ‘person of moral growth’ presented in this paper is a contribution to moral growth research based on personalist virtue ethics. Personalist virtue ethics puts the person at the centre of the moral reflection, addressing the holistic interplay of the person’s dimensions in the process of moral growth. The model is an operationalization of the person’s dimensions for educational and research purposes in the field of moral development. In this paper, the four components of the model are presented: emotional-cognitive, decisional (free commitment to moral growth), practical (moral growth through personal action), and self-understanding (the moral growth identity), and the process of the elaboration of the model is explained. For enhancing the construct validity of the model, its components and pedagogical implications are discussed in the light of recent moral education literature. This model is a contribution to a more cogent moral education and is helping to design and deliver moral educational experiences which address personal moral development in a clear, convincing, and well-structured way
Highlighting some of the issues with multicurrency numéraires
Get PDFMulticurrency numéraires are weighted baskets of currencies, in which the weights are positive and sum to one. Some popular multicurrency numéraires are: trade-weighted, the IMF's Special Drawing Right (SDR), equally-weighted, risk-weighted, and GDP-weighted. But which multicurrency numéraire should be used to model systems of currencies? This paper highlights some of the issues that arise when using multicurrency numéraires by utilising two conditions, namely, a consistency condition and a no-arbitrage condition. It is shown that both the consistency condition and the no-arbitrage condition are satisfied by common equally-weighted multicurrency numéraires. As a consequence, it is recommended that common equally-weighted multicurrency numéraires be used to model systems of currencies
A radar backscatter simulation of a forest canopy using 3D physical structures derived from LiDAR scanning
Get PDFThis study aims to explore the forest aboveground biomass relationship to C-band backscatter. A one-hectare area in Wytham Woods, located west of Oxford, was selected for this research. The area has a total of 525 trees of seven different tree species. The Michigan Microwave Canopy Scattering Model (MIMICS), a two-layer radiative transfer model, was applied to simulate canopy backscatter responses in this deciduous UK forest. Model parameters related to forest structure were derived from previously published terrestrial laser (LiDAR) data. Simulated backscatter was performed for co-polarized and cross-polarized modes at a C-band frequency range and incidence angles (20° to 45° at 5° increments). The research includes five objectives: i) backscatter sensitivity analysis from the variation of different model parameters; ii) backscatter seasonal effect under spring–summer (leaf-on) and autumn–winter (leaf-off) periods; iii) backscatter comparison between species as well as between simulated and satellite observations in a spatial pattern; iv) relationship between simulated backscatter and aboveground biomass; and v) relationship between MIMICS forest structure parameters and simulated backscatter. Sensitivity analysis results showed significant differences in backscatter from changes in leaf distribution, leaf thickness and water content (leaf, trunk and soil) for both polarization modes in leaf-on scenarios. Leaf-off scenarios presented significant differences from changes in branch distribution but only for the co-polarized mode. Seasonal variations presented significant backscatter differences between spring–summer and autumn–winter scenarios; additionally, backscatter differences among species for each seasonality in the co-polarized mode were observed. The computation of the grid resolution (20 m × 20 m) showed a range of backscatter values depending on the grid and incidence angle. Higher backscatter values were observed for the satellite data than for the simulated data. Finally, the aboveground biomass and the MIMICS input parameters presented high random variability and little systematic co-variation with the total backscatter on both simulated seasons, suggesting that more robust allometric equations for biomass estimation are required
Effects of a diverse prebiotic fibre blend on inflammation, the gut microbiota and affective symptoms in metabolic syndrome: a pilot open-label randomised controlled trial
Get PDFEmerging evidence suggests that low-grade systemic inflammation plays a key role in altering brain activity, behaviour and affect. Modulation of the gut microbiota using prebiotic fibre offers a potential therapeutic tool to regulate inflammation, mediated via the production of short-chain fatty acids (SCFA). However, the impact of prebiotic consumption on affective symptoms and the possible contribution from inflammation, gut symptoms and the gut microbiome are currently underexamined. In this 12-week study, the effects of a diverse prebiotic blend on inflammation, gut microbiota profiles and affective symptoms in a population with metabolic syndrome (MetS) were examined. Sixty males and females with MetS meeting the criteria for MetS were randomised into a treatment group (n 40), receiving 10 g per day of a diverse prebiotic blend and healthy eating advice, and a control group (n 20), receiving healthy eating advice only. Our results showed a significant reduction in high sensitivity C-reactive protein (hs-CRP) in the treatment (–0·58 [–9·96 to–2·63]) compared with control (0·37 [–3·64 to–3·32]), alongside significant improvements in self-reported affective scores in the treatment compared with the control group. While there were no differences in relative abundance between groups at week 12, there was a significant increase from baseline to week 12 in fecal Bifidobacterium and Parabacteroides in the treatment group, both of which are recognised as SCFA producers. Multivariate regression analyses further revealed an association between gastrointestinal symptoms and hs-CRP with affective scores. Together, this study provides preliminary support for a diverse prebiotic blend for mood, stress and anxiety
An authentic confrontation or a picturesque scene? Theodor W. Adorno and Alexander Kluge on film, the cinema, and television
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Development and investigation of mucoadhesive polymers based on chitosan for intravesical therapy
Get PDFIntravesical drug delivery (IDD) refers to the administration of therapeutic agents directly into the urinary bladder through a catheter. Low permeability of the urinary bladder epithelium, poor retention of the thera-peutic agents due to dilution and periodic urine voiding as well as frequent catheterizations (with potential risk of infections) are the major limitations of IDD used in the treatment of bladder-related disorders, such as bladder cancer. In this work, the mucoadhesive properties of polymeric materials based on chitosan, chitosan-gellan gum, and chitosan-Carbopol™ 940 containing sodium fluorescein (NaFI) were investigated for their potential application in intravesical drug delivery. The evaluation of mucoadhesive properties was carried out using an in vitro flow-through method with fluorescent detection that simulates the interaction conditions of polymers with the urinary bladder mucosa. Additionally, the release kinetics of NaFI from polymer composi-tions under conditions mimicking the physiological environment of the bladder was studied using a fluores-cence spectrometry. The acquired data confirm the promise of using chitosan-based mucoadhesive polymers in developing systems for intravesical drug delivery, which could significantly enhance the efficacy of IDD therapy to treat urinary bladder-related disorders
Deep learning in automated worm identification and tracking for C. elegan mating behaviour analysis
Get PDFThis study is concerned with computer vision technologies applied in C. elegans (diminutive nematodes) mating behaviour analysis, more specifically object detection and tracking to find contacts of male and female worms in worm mating videos. Advanced deep learning algorithms, such as YOLOv8 and DeepSORT, are adapted in the automated worm identification and tracking system. A modified DeepSORT algorithm is developed to cope with appearance similarity of C. elegans for improving the tracking accuracy. In addition, a male worm detection and tracking algorithm, utilising the male worm’s mobility characteristic, assists the modified DeepSORT in accurate male worm tracking. Finally, worm contact detection is implemented by calculating the Euclidean distance between the male and female worms. The developed system, named as M1 and M2, is trained and evaluated under two sets of data, bounding boxes and segmented worms, respectively. Furthermore, we compared the effectiveness of including SAM segmentation optional module in experiments. The evaluation results have shown that YOLOv8 has excellent performance in worm detection to cope with deformable worm shape, and the modified DeepSORT significantly outperforms the default DeepSORT in worm tracking