403 research outputs found
The structure of gravel-bed flow with intermediate submergence: a laboratory study
The paper reports an experimental study of the flow structure over an immobile gravel bed in open channel at intermediate submergence, with particular focus on the near-bed region. The experiments consisted of velocity measurements using three-component (stereoscopic) Particle Image Velocimetry (PIV) in near-bed horizontal plane and two-component PIV in three vertical planes that covered three distinctly different hydraulic scenarios where the ratio of flow depth to roughness height (i.e., relative submergence) changes from 7.5 to 10.8. Detailed velocity measurements were supplemented with fine-scale bed elevation data obtained with a laser scanner. The data revealed longitudinal low-momentum and high-momentum "strips'' in the time-averaged velocity field, likely induced by secondary currents. This depth-scale pattern was superimposed with particle-scale patches of flow heterogeneity induced by gravel particle protrusions. A similar picture emerged when considering second-order velocity moments. The interaction between the flow field and gravel-bed protrusions is assessed using cross correlations of velocity components and bed elevations in a horizontal plane just above gravel particle crests. The cross correlations suggest that upward and downward fluid motions are mainly associated with upstream-facing and lee sides of particles, respectively. Results also show that the relative submergence affects the turbulence intensity profiles for vertical velocity over the whole flow depth, while only a weak effect, limited to the near-bed region, is noticed for streamwise velocity component. The approximation of mean velocity profiles with a logarithmic formula reveals that log-profile parameters depend on relative submergence, highlighting inapplicability of a conventional "universal'' logarithmic law for gravel-bed flows with intermediate submergence
Forecasting magma-chamber rupture at Santorini volcano, Greece
How much magma needs to be added to a shallow magma chamber to cause rupture, dyke injection, and a potential eruption? Models that yield reliable answers to this question are needed in order to facilitate eruption forecasting. Development of a long-lived shallow magma chamber requires periodic influx of magmas from a parental body at depth. This redistribution process does not necessarily cause an eruption but produces a net volume change that can be measured geodetically by inversion techniques. Using continuum-mechanics and fracture-mechanics principles, we calculate the amount of magma contained at shallow depth beneath Santorini volcano, Greece. We demonstrate through structural analysis of dykes exposed within the Santorini caldera, previously published data on the volume of recent eruptions, and geodetic measurements of the 2011–2012 unrest period, that the measured 0.02% increase in volume of Santorini’s shallow magma chamber was associated with magmatic excess pressure increase of around 1.1 MPa. This excess pressure was high enough to bring the chamber roof close to rupture and dyke injection. For volcanoes with known typical extrusion and intrusion (dyke) volumes, the new methodology presented here makes it possible to forecast the conditions for magma-chamber failure and dyke injection at any geodetically well-monitored volcano
Aging Skin: Nourishing from Out-In. Lessons from Wound Healing
Skin lesion therapy, peculiarly in the elderly, cannot be isolated from understanding that the skin is an important organ consisting of different tissues. Furthermore, dermis health is fundamental for epidermis
integrity, and so adequate nourishment is mandatory in maintaining skin integrity. The dermis nourishes the epidermis, and a healthy epidermis protects the dermis from the environment, so nourishing the dermis
through the epidermal barrier is a technical problem yet to be resolved. This is also a consequence of the laws and regulations restricting cosmetics, which cannot have properties that pass the epidermal layer.
There is higher investment in cosmetics than in the pharmaceutical industry dealing with skin therapies, because the costs of drug registration are enormous and the field is unprofitable. Still, wound healing may
be seen as an opportunity to “feed” the dermis directly. It could also verify whether providing substrates could promote efficient healing and test optimal skin integrity maintenance, if not skin rejuvenation, in an
ever aging population
Residential density classification for sustainable housing development using a machine learning approach
Using Machine Learning (ML) algorithms for classification of the existing residential neighbourhoods and their spatial characteristics (e.g. density) so as to provide plausible scenarios for designing future sustainable housing is a novel application. Here we develop a methodology using a Random Forests algorithm (in combination with GIS spatial data processing) to detect and classify the residential neighbourhoods and their spatial characteristics within the region between Oxford and Cambridge, that is, the 'Oxford-Cambridge Arc'. The classification model is based on four pre-defined urban classes, that is, Centre, Urban, Suburban, and Rural for the entire region. The resolution is a grid of 500 m × 500 m. The features for classification include (1) dwelling geometric attributes (e.g. garden size, building footprint area, building perimeter), (2) street networks (e.g. street length, street density, street connectivity), (3) dwelling density (number of housing units per hectare), (4) building residential types (detached, semi-detached, terraced, and flats), and (5) characteristics of the surrounding neighbourhoods. The classification results, with overall average accuracy of 80% (accuracy per class: Centre: 38%, Urban 91%, Suburban 83%, and Rural 77%), for the Arc region show that the most important variables were three characteristics of the surrounding area: residential footprint area, dwelling density, and number of private gardens. The results of the classification are used to establish a baseline for the current status of the residential neighbourhoods in the Arc region. The results bring data-driven decision-making processes to the level of local authority and policy makers in order to support sustainable housing development at the regional scale
How the Packing Density and Penetration Resistance is Influenced by Particle Shape: DEM Modelling of Plate Penetration in Granular Media
Granular materials play a crucial role in various geotechnical, mining, and bulk handling applications. Understanding their mechanical properties is essential for optimal use in these industries. Traditional experimental methods like Cone Penetration Test (CPT) and open pile testing have limitations on their repeatability and offer little insight into the contact mechanics. The Discrete Element Method (DEM) is a powerful tool for investigating and simulating granular material behaviour at the element scale and provides deeper understanding in geometry-material interactions. However, due to computational costs, spherical particles are often preferred, though they may not always capture realistic particle interactions. In the current study, the packing density and the penetration resistance of particle beds with different particle shapes, including sphere, multi-spheres and polyhedrons, are compared using a plate penetration test modelled in DEM. Sensitivity analyses are performed for sliding friction, consolidation pressure, and Particle Size Distribution (PSD). Results indicate that polyhedral shapes show lower penetration resistance compared to spherical and multi-spherical shapes. Sliding friction has the most significant impact on resistance, while consolidation pressure has minimal effect on porosity. The study highlights the importance of particle shape in granular media modelling and emphasizes the need for further research in this area
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Missense mutation of Brain Derived Neurotrophic Factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: a longitudinal study
The predictability of neurocognitive outcomes in patients with traumatic brain injury is not straightforward. The extent and nature of recovery in patients with mild traumatic brain injury (mTBI) are usually heterogeneous and not substantially explained by the commonly known demographic and injury-related prognostic factors despite having sustained similar injuries or injury severity. Hence, this study evaluated the effects and association of the Brain Derived Neurotrophic Factor (BDNF) missense mutations in relation to neurocognitive performance among patients with mTBI. 48 patients with mTBI were prospectively recruited and MRI scans of the brain were performed within an average 10.1 (SD 4.2) hours post trauma with assessment of their neuropsychological performance post full Glasgow Coma Scale (GCS) recovery. Neurocognitive assessments were repeated again at 6 months follow-up. The paired t-test, Cohen’s d effect size and repeated measure ANOVA were performed to delineate statistically significant differences between the groups [wildtype G allele (Val homozygotes) vs. minor A allele (Met carriers)] and their neuropsychological performance across the time point (T1 = baseline/ admission vs. T2 = 6th month follow-up). Minor A allele carriers in this study generally performed more poorly on neuropsychological testing in comparison wildtype G allele group at both time points. Significant mean differences were observed among the wildtype group in the domains of memory (M = -11.44, SD = 10.0, p = .01, d = 1.22), executive function (M = -11.56, SD = 11.7, p = .02, d = 1.05) and overall performance (M = -6.89 SD = 5.3, p = .00, d = 1.39), while the minor A allele carriers showed significant mean differences in the domains of attention (M = -11.0, SD = 13.1, p = .00, d = .86) and overall cognitive performance (M = -5.25, SD = 8.1, p = .01, d = .66).The minor A allele carriers in comparison to the wildtype G allele group, showed considerably lower scores at admission and remained impaired in most domains across the timepoints, although delayed signs of recovery were noted to be significant in the domains attention and overall cognition. In conclusion, the current study has demonstrated the role of the BDNF rs6265 Val66Met polymorphism in influencing specific neurocognitive outcomes in patients with mTBI. Findings were more detrimentally profound among Met allele carriers
Poor cognitive ageing:Vulnerabilities, mechanisms and the impact of nutritional interventions
The CUSSH programme: supporting cities’ transformational change towards health and sustainability [version 2; peer review: 2 approved]
This paper describes a global research programme on the complex systemic connections between urban development and health. Through transdisciplinary methods the Complex Urban Systems for Sustainability and Health (CUSSH) project will develop critical evidence on how to achieve the far-reaching transformation of cities needed to address vital environmental imperatives for planetary health in the 21st Century. CUSSH’s core components include: (i) a review of evidence on the effects of climate actions (both mitigation and adaptation) and factors influencing their implementation in urban settings; (ii) the development and application of methods for tracking the progress of cities towards sustainability and health goals; (iii) the development and application of models to assess the impact on population health, health inequalities, socio-economic development and environmental parameters of urban development strategies, in order to support policy decisions; (iv) iterative in-depth engagements with stakeholders in partner cities in low-, middle- and high-income settings, using systems-based participatory methods, to test and support the implementation of the transformative changes needed to meet local and global health and sustainability objectives; (v) a programme of public engagement and capacity building. Through these steps, the programme will provide transferable evidence on how to accelerate actions essential to achieving population-level health and global climate goals through, amongst others, changing cities’ energy provision, transport infrastructure, green infrastructure, air quality, waste management and housing
A family presenting with multiple endocrine neoplasia type 2B: A case report
<p>Abstract</p> <p>Introduction</p> <p>Multiple endocrine neoplasia 2B, a rare autosomal dominant syndrome, is characterized by early onset of medullary thyroid carcinoma, pheochromocytoma, marfanoid habitus and mucosal neuromas of the tongue, lips, inner cheeks and inner eyelids. Gangliomatosis of the gastrointestinal tract and its complications may also occur in patients with this disease.</p> <p>Case presentation</p> <p>We present the case of a 16-year-old Persian man diagnosed as having a non-invasive form of multiple endocrine neoplasia 2B (medullary thyroid cancer, mucosal neuroma of the tongue, lips and inner eyelids). Our patient, who had a positive family history of medullary thyroid cancer, was of normal height with no signs of marfanoid habitus.</p> <p>Conclusions</p> <p>Ophthalmological and oral manifestations of multiple endocrine neoplasia 2B, as in the case of our patient, are rare presentations of the disease; unfortunately in the case of our patient his condition had not been noted and acted upon until he presented to our department. The diagnosis in our patient's case was made only after his mother presented with the same condition. As a result, we emphasize that physicians should pay more attention to the oral and ocular signs of multiple endocrine neoplasia 2B in order to diagnose this fatal syndrome at an earlier phase.</p
The 2022 South America report of The Lancet Countdown on health and climate change: trust the science. Now that we know, we must act
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