Normalizing Behavior of Unsaturated Granular Pavement Materials

One of the important components of a flexible pavement structure is granular material layers. Unsaturated granular pavement materials (UGPMs) in these layers influence stresses and strains throughout the pavement structure, and have a large effect on asphalt concrete fatigue and pavement rutting (two of the primary failure mechanisms for flexible pavements). The behavior of UGPMs is dependent on water content, but this effect has been traditionally difficult to quantify using either empirical or mechanistic methods. This paper presents a practical mechanistic framework for determining the behavior of UGPMs within the range of water contents, densities, and stress states likely to be encountered under field conditions. Both soil suction and generated pore pressures are determined and compared to confinement under typical field loading conditions. The framework utilizes a simple soil suction model that has three density-independent parameters, and can be determined using conventional triaxial equipment that is available in many pavement engineering laboratories.     

Design of parts and manufacturing systems for reliability and maintainability

The design of parts and manufacturing systems can be viewed from different perspectives. This paper discusses the design of parts and manufacturing systems from reliability and maintainability perspectives. A convenient method of considering reliability and maintainability is through the use of design rules which are based on empirical and theoretical knowledge. Four design rules for improvement of reliability and maintainability of systems are presented. The design rules are proven and substantiated with numerical results. The relationship between the design for reliability and maintainability rules and design for manufacturing process rules is discussed.     

Characterization of residual stresses from cold expansion using spatial statistics

Residual stress fields from cold expansion have been widely used to extend the fatigue life of aircraft structures. However, the spatial statistical character of these residual stress fields has not been established and has not been incorporated in current analysis methods. The objective of this study was to establish a spatial statistical method to quantify the residual stress field around a cold expanded hole. A framework called the Spatial Analysis of Residual Stress (SpARS) was developed utilizing spatial correlation, response surface modelling techniques and statistical resampling methods to characterize the residual stress field. Our results showed that tolerance bounds on residual stress can be quantified using this method. We also demonstrated the SpARS method using recently published round robin case studies. The newly developed model will be useful for aircraft structural fatigue crack growth analyses to incorporate residual stress fields for extending inspection intervals for fatigue and fracture critical structures.     

The P2X4 Receptor: Cellular and Molecular Characteristics of a Promising Neuroinflammatory Target

The adenosine 5′-triphosphate-gated P2X4 receptor channel is a promising target in neuroinflammatory disorders, but the ability to effectively target these receptors in models of neuroinflammation has presented a constant challenge. As such, the exact role of P2X4 receptors and their cell signalling mechanisms in human physiology and pathophysiology still requires further elucidation. To this end, research into the molecular mechanisms of P2X4 receptor activation, modulation, and inhibition has continued to gain momentum in an attempt to further describe the role of P2X4 receptors in neuroinflammation and other disease settings. Here we provide an overview of the current understanding of the P2X4 receptor, including its expression and function in cells involved in neuroinflammatory signalling. We discuss the pharmacology of P2X4 receptors and provide an overview of P2X4-targeting molecules, including agonists, positive allosteric modulators, and antagonists. Finally, we discuss the use of P2X4 receptor modulators and antagonists in models of neuroinflammatory cell signalling and disease.     

Delving deeper into the whorl of flower segmentation

We describe an algorithm for automatically segmenting flowers in colour photographs. This is a challenging problem because of the sheer variety of flower classes, the variability within a class and within a particular flower, and the variability of the imaging conditions – lighting, pose, foreshortening, etc.     

Creation and control of high-dimensional multi-partite classically entangled light

Vector beams, non-separable in spatial mode and polarisation, have emerged as enabling tools in many diverse applications, from communication to imaging. This a...     

The Regulatory Role of H19/miR-181a/ATG5 Signaling in Perinatal Nicotine Exposure-Induced Development of Neonatal Brain Hypoxic-Ischemic Sensitive Phenotype

Nicotine exposure either from maternal cigarette smoking or e-cigarette vaping is one of the most common risk factors for neurodevelopmental disease in offspring. Previous studies revealed that perinatal nicotine exposure programs a sensitive phenotype to neonatal hypoxic-ischemic encephalopathy (HIE) in postnatal life, yet the underlying mechanisms remain undetermined. The goal of the present study was to determine the regulatory role of H19/miR-181a/ATG5 signaling in perinatal nicotine exposure-induced development of neonatal brain hypoxic-ischemic sensitive phenotype. Nicotine was administered to pregnant rats via subcutaneous osmotic minipumps. All experiments were conducted in offspring pups at postnatal day 9 (P9). Perinatal nicotine exposure significantly enhanced expression of miR-181a but attenuated autophagy-related protein 5 (ATG5) mRNA and protein levels in neonatal brains. Of interest, miR-181a mimicking administration in the absence of nicotine exposure also produced dose-dependent increased hypoxia/ischemia (H/I)-induced brain injury associated with a decreased ATG5 expression, closely resembling perinatal nicotine exposure-mediated effects. Locked nucleic acid (LNA)-miR-181a antisense reversed perinatal nicotine-mediated increase in H/I-induced brain injury and normalized aberrant ATG5 expression. In addition, nicotine exposure attenuated a long non-coding RNA (lncRNA) H19 expression level. Knockdown of H19 via siRNA increased the miR-181a level and enhanced H/I-induced neonatal brain injury. In conclusion, the present findings provide a novel mechanism that aberrant alteration of the H19/miR-181a/AGT5 axis plays a vital role in perinatal nicotine exposure-mediated ischemia-sensitive phenotype in offspring and suggests promising molecular targets for intervention and rescuing nicotine-induced adverse programming effects in offspring.     

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.