Experimental evaluation of kaolin stabilised with class F fly ash

This study aims to investigate the effectiveness of fly ash (FA) in stabilising a kaolin soil through laboratory tests. Kaolin is an example of moderate plasticity clays that require stabilisation methods for construction purposes. The influence of FA on the improvement of kaolin is studied by varying its dosages in the mixtures (0%, 10% to 20%) as well as the cement content, used as an activator in different percentages (5 and 7%). The influence of the dry unit weight and the curing time of the soil mixture is also analysed through unconfined compressive strength and indirect tensile strength tests. The experimental results show that the strength increases linearly with both FA and cement contents. Moreover, higher initial dry unit weights also yield higher final strengths. To further assess the improvement, the application of the porosity over the volumetric cement content ratio, as the main variable, succeeded in attaining a relationship with the strength and the stiffness of the studied soil. Results for the combined effect of the porosity and the volumetric cement on the secant modulus were also determined. Furthermore, a unique relationship was obtained combining porosity, volumetric cement and FA content

Reaction of Tepary Beans to Eight Virulent Races of the Rust Pathogen that Overcomes All Known Common Bean Rust Resistance Genes

Bean rust, caused by Uromyces appendiculatus, is a major disease of common and snap bean (Phaseolus vulgaris) worldwide (Stavely, 1984). Although host resistance is an important component of rust management (Mmbaga et al., 1996), populations of the rust pathogen comprise an extensive and shifting virulence diversity that could render susceptible all known rust resistance genes in common bean. Conversely, it has been suggested that certain tepary bean (Phaseolus acutifolius) accessions are broadly resistant to bean rust (Miklas & Stavely, 1998). The objectives of this study were to verify if tepary beans are resistant to eight races of the bean rust pathogen, which overcome all known rust resistance genes in common bean. Then, to select the resistant genotypes to cross with common beans without embryo rescue

A Machine-Learning-Based Approach to Predict the Health Impacts of Commuting in Large Cities: Case Study of London

The daily commute represents a source of chronic stress that is positively correlated with physiological consequences, including increased blood pressure, heart rate, fatigue, and other negative mental and physical health effects. The purpose of this research is to investigate and predict the physiological effects of commuting in Greater London on the human body based on machine-learning approaches. For each participant, the data were collected for five consecutive working days, before and after the commute, using non-invasive wearable biosensor technology. Multimodal behaviour, analysis and synthesis are the subjects of major efforts in computing field to realise the successful human–human and human–agent interactions, especially for developing future intuitive technologies. Current analysis approaches still focus on individuals, while we are considering methodologies addressing groups as a whole. This research paper employs a pool of machine-learning approaches to predict and analyse the effect of commuting objectively. Comprehensive experimentation has been carried out to choose the best algorithmic structure that suit the problem in question. The results from this study suggest that whether the commuting period was short or long, all objective bio-signals (heat rate and blood pressure) were higher post-commute than pre-commute. In addition, the results match both the subjective evaluation obtained from the Positive and Negative Affect Schedule and the proposed objective evaluation of this study in relation to the correlation between the effect of commuting on bio-signals. Our findings provide further support for shorter commutes and using the healthier or active modes of transportation

On Safety Enhancement in IIoT Scenarios through Heterogeneous Localization Techniques

In the field of the Industrial Internet of Things (IIoT), strictly related to Industry 4.0, one of the main aspects to be carefully considered by the governing board of a manufacturing company is the safety level to be guaranteed to the workers inside production plants. This involves daily human activities, together with production machines to be used during the working hour (and periodically maintained), and mobile industrial vehicles moving around the production plant. To this end, a precise localization of both workers and vehicles is expedient to improve the safety level—avoiding that people move inside forbidden areas or perform dangerous actions—as well as allowing a more accurate control and reporting to national authorities in charge of verifying the compliance to safety regulations (e.g., aggregated data, not shared outside the company, used to fill injuries reports in case of official inspections), in the presence of accidents and anomalous events. In this paper, we present the design of IIoT-related localization mechanisms exploiting heterogeneous communication technologies, in turn analysing how the localization can cope with the adoption of wideband (e.g., Wi-Fi) and narrowband (e.g., Narrowband IoT, NB-IoT) communication protocols and discussing how these communication paradigms may impact existing and modern production plants

Health care providers’ perspectives on the content and structure of a culturally tailored antenatal care programme to expectant parents and family members in Nepal.

Background: In Nepal childbirth is one of the most vulnerable periods of a woman's life and knowledge about the normal birth process, as well as danger signs, could be a life-saving intervention. Antenatal care programmes are therefore particularly relevant in Nepal where women deliver on their own in rural areas as well as in facility and hospital settings. Aim: This study aimed to describe the relevant content and structure of a culturally tailored antenatal care programme in Nepal to be developed from the input of healthcare providers. Methods: Qualitative semi-structured interviews with 26 health care providers were analyzed using Elo and Kyngäs’ content analysis. This study received ethical approval from the research ethics committee at Dalarna University, Sweden, and the Nepal Health Research Council. Findings: The results present possible (1) content and (2) structure of a culturally tailored antenatal care programme. Content is comprised of (a) how pregnancy affects the mother and how her lifestyle affects the unborn child; (b) normal childbirth, complications, and preparations; and (c) postpartum period – parenthood, childcare, and breastfeeding. Structure is related to (a) programme leader and location; (b) participants; and (c) pedagogy. Conclusion: This antenatal care programme will be culturally tailored to empower women with self-confidence and their decision-making power may increase in the family system regarding their own and their children’s health and wellbeing. Clinical Application: This study can help those designing culturally sensitive antenatal care programs in Nepal

Ensemble Riemannian data assimilation over the Wasserstein space

In this paper, we present an ensemble data assimilation paradigm over a Riemannian manifold equipped with the Wasserstein metric. Unlike the Euclidean distance used in classic data assimilation methodologies, the Wasserstein metric can capture the translation and difference between the shapes of square-integrable probability distributions of the background state and observations. This enables us to formally penalize geophysical biases in state space with nonGaussian distributions. The new approach is applied to dissipative and chaotic evolutionary dynamics, and its potential advantages and limitations are highlighted compared to the classic ensemble data assimilation approaches under systematic errors

Screening and characterisation of CdTe/CdS quantum dot-binding peptides for material surface functionalisation

Quantum dots (QDs) are promising nanomaterials due to their unique photophysical properties. For them to be useful in biological applications, the particle surface generally needs to be conjugated to biological molecules, such as antibodies. In this study, we screened CdTe/CdS QD-binding peptides from a phage display library as linkers for simple and bio-friendly QD modification. Among five QD-binding peptide candidates, a series of truncated peptides designed from two high-affinity peptides were subjected to an array-based binding assay with QDs to assess their functional core sequences and characteristics. Linking these isolated, shortened peptides (PWSLNR and SGVYK) with an antibody-binding peptide (NKFRGKYK) created dual-functional peptides that are capable of QD surface functionalisation by antibodies. Consequently, the dual-functional peptides could mediate anti-CD9 antibody functionalisation onto CdTe/CdS QD surface; CD9 protein imaging of cancer cells was also demonstrated. Our proposed peptides offer an effective vehicle for QD surface functionalisation in biological applications