Search Results (8)

The discovery of hypertrophic cardiomyopathy (HCM) dates back to 1958, when the pathologist Donald Teare of the St. George’s Hospital in London performed autopsies in eight cases with asymmetric hypertrophy of the ventricular septum and bizarre disorganization (disarray) at histology, first interpreted as hamartoma. Seven had died suddenly. The cardiac specimens were cut along the long axis, similar to the 2D echo. In the same year, at the National Institute of Health U.S.A., Eugene Braunwald, a hemodynamist, and Andrew Glenn Morrow, a cardiac surgeon, clinically faced a patient with an apparently similar morbid entity, with a systolic murmur and subaortic valve gradient. “Discrete” subaortic stenosis was postulated. However, at surgery, Dr. Morrow observed only hypertrophy and performed myectomy to relieve the obstruction. This first Braunwald–Morrow patient underwent a successful cardiac transplant later at the disease end stage. The same Dr. Morrow was found to be affected by the familial HCM and died suddenly in 1992. The term “functional subaortic stenosis” was used in 1959 and “idiopathic hypertrophic subaortic stenosis” in 1960. Years before, in 1957, Lord Brock, a cardiac surgeon at the Guy’s Hospital in London, during alleged aortic valve surgery in extracorporeal circulation, did not find any valvular or discrete subaortic stenoses. In 1980, John F. Goodwin of the Westminster Hospital in London, the head of an international WHO committee, put forward the first classification of heart muscle diseases, introducing the term cardiomyopathy (dilated, hypertrophic, and endomyocardial restrictive). In 1995, the WHO classification was revisited, with the addition of two new entities, namely arrhythmogenic and purely myocardial restrictive, the latter a paradox of a small heart accounting for severe congestive heart failure by ventricular diastolic impairment. A familial occurrence was noticed earlier in HCM and published by Teare and Goodwin in 1960. In 1989–1990, the same family underwent molecular genetics investigation by the Seidman team in Boston, and a missense mutation of the β-cardiac myosin heavy chain in chromosome 14 was found. Thus, 21 years elapsed from HCM gross discovery to molecular discoveries. The same original family was the source of both the gross and genetic explanations of HCM, which is now named sarcomere disease. Restrictive cardiomyopathy, characterized grossly without hypertrophy and histologically by myocardial disarray, was found to also have a sarcomeric genetic mutation, labeled “HCM without hypertrophy”. Sarcomere missense mutations have also been reported in dilated cardiomyopathy (DCM) and non-compaction cardiomyopathy. Moreover, sarcomeric gene defects have been detected in some DNA non-coding regions of HCM patients. The same mutation in the family may express different phenotypes (HCM, DCM, and RCM). Large ischemic scars have been reported by pathologists and are nowadays easily detectable in vivo by cardiac magnetic resonance with gadolinium. The ischemic arrhythmic substrate enhances the risk of sudden death. Full article

The accumulation of years imbues historical buildings within universities with a profound sense of heritage, evident not only in the temporal imprints within their internal spaces but also in the evolution of their external surroundings. This cultural legacy subtly enriches students’ spatial awareness of history and fosters a collective memory of campus context. Current scholarly inquiry into university historical buildings primarily revolves around comprehensive considerations encompassing the preservation of these edifices, the overarching planning of academic institutions, and the safeguarding of the distinctive features inherent to historical structures. However, the predominant focus lies on qualitative analyses, leaving a pressing need for quantitative assessments and the establishment of an evaluation framework to gauge the efficacy of historical building preservation in academia. Addressing this gap, this study employs the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) to formulate the University Historical Building Protection Evaluation Framework (UHBPEF). Drawing from the examination and categorization of the primary instructional edifices within the Yujiatou campus of Wuhan University of Technology through the Research Classification Method (RCM), along with the consolidation of insights from experts and academic stakeholders, this study underscores the imperative of enhancing the scientific precision and pertinence of the university’s strategy for preserving historical buildings. By employing both qualitative and quantitative methodologies, this study offers innovative insights into the challenges facing historical building preservation in university settings, therefore propounding effective preservation strategies and offering a roadmap for future endeavors in this domain. Full article

This study presents an investigation focusing on the advancement of a robot designed for subretinal injections in the context of macular degeneration treatment. The technique of subretinal injection surgery stands as the most efficacious approach for the successful transplantation of stem cells into the retinal pigment epithelium layer. This particular procedure holds immense significance in advancing research and implementing therapeutic strategies involving retinal stem cell transplantation. The execution of artificial subretinal surgery poses considerable challenges which can be effectively addressed through the utilization of subretinal injection surgery robots. The development process involved a comprehensive modeling phase, integrating computer-aided design (CAD) and finite element analysis (FEA) techniques. These simulations facilitated iterative enhancements of the mechanical aspects pertaining to the robotic arm. Furthermore, MATLAB was employed to simulate and visualize the robot’s workspace, and independent verification was conducted to ascertain the range of motion for each degree of freedom. Full article

The changing climate is a concern with regard to sustainable water resources. Projections of the runoff in future climate conditions are needed for long-term planning of water resources and flood protection. In this study, we evaluate the possible climate change impacts on the runoff regime in eight selected basins located in the whole territory of Slovakia. The projected runoff in the basins studied for the reference period (1981–2010) and three future time horizons (2011–2040, 2041–2070, and 2071–2100) was simulated using the HBV (Hydrologiska Byråns Vattenbalansavdelning) bucket-type model (the TUW (Technische Universität Wien) model). A calibration strategy based on the selection of the most suitable decade in the observation period for the parameterization of the model was applied. The model was first calibrated using observations, and then was driven by the precipitation and air temperatures projected by the KNMI (Koninklijk Nederlands Meteorologisch Instituut) and MPI (Max Planck Institute) regional climate models (RCM) under the A1B emission scenario. The model’s performance metrics and a visual inspection showed that the simulated runoff using downscaled inputs from both RCM models for the reference period represents the simulated hydrological regimes well. An evaluation of the future, which was performed by considering the representative climate change scenarios, indicated that changes in the long-term runoff’s seasonality and extremality could be expected in the future. In the winter months, the runoff should increase, and decrease in the summer months compared to the reference period. The maximum annual daily runoff could be more extreme for the later time horizons (according to the KNMI scenario for 2071–2100). The results from this study could be useful for policymakers and river basin authorities for the optimum planning and management of water resources under a changing climate. Full article

This study uses the quantile mapping bias correction (QMBC) method to correct the bias in five regional climate models (RCMs) from the latest output of the Rossby Center Climate Regional Model (RCA4) over Kenya. The outputs were validated using various scalar metrics such as root-mean-square difference (RMSD), mean absolute error (MAE), and mean bias. The study found that the QMBC algorithm demonstrates varying performance among the models in the study domain. The results show that most of the models exhibit reasonable improvement after corrections at seasonal and annual timescales. Specifically, the European Community Earth-System (EC-EARTH) and Commonwealth Scientific and Industrial Research Organization (CSIRO) models depict remarkable improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model shows little improvement across the rainfall seasons (i.e., March–May (MAM) and October–December (OND)). The projections forced with bias-corrected historical simulations tallied observed values demonstrate satisfactory simulations as compared to the uncorrected RCMs output models. This study has demonstrated that using QMBC on outputs from RCA4 is an important intermediate step to improve climate data before performing any regional impact analysis. The corrected models may be used in projections of drought and flood extreme events over the study area. Full article

A prequel study showed that dynamic downscaling using a regional climate model (RCM) over Africa improved the Goddard Institute for Space Studies Atmosphere-Ocean Global Climate Model (GISS AOGCM: ModelE) simulation of June–September rainfall patterns over Africa. The current study applies bias corrections to the lateral and lower boundary data from the AOGCM driving the RCM, based on the comparison of a 30-year simulation to the actual climate. The analysis examines the horizontal pattern of June–September total accumulated precipitation, the time versus latitude evolution of zonal mean West Africa (WA) precipitation (showing monsoon onset timing), and the latitude versus altitude cross-section of zonal winds over WA (showing the African Easterly Jet and the Tropical Easterly Jet). The study shows that correcting for excessively warm AOGCM Atlantic sea-surface temperatures (SSTs) improves the simulation of key features, whereas applying 30-year mean bias corrections to atmospheric variables driving the RCM at the lateral boundaries does not improve the RCM simulations. We suggest that AOGCM climate projections for Africa should benefit from downscaling by nesting an RCM that has demonstrated skill in simulating African climate, driven with bias-corrected SST. Full article

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (E_g↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in E_g↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of E_g↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover. Full article

Global and regional climate model simulations are frequently used for regional climate change assessments and in climate impact modeling studies. To reflect the inherent and methodological uncertainties in climate modeling, the assessment of regional climate change requires ensemble simulations from different global and regional climate model combinations. To interpret the spread of simulated results, it is useful to understand how the climate change signal is modified in the GCM-RCM modelmodelgeneral circulation model-regional climate model (GCM-RCM) chain. This kind of information can also be useful for impact modelers; for the process of experiment design and when interpreting model results. In this study, we investigate how the simulated historical and future climate of the Max-Planck-Institute earth system model (MPI-ESM) is modified by dynamic downscaling with the regional model REMO in different world regions. The historical climate simulations for 1950–2005 are driven by observed anthropogenic forcing. The climate projections are driven by projected anthropogenic forcing according to different Representative Concentration Pathways (RCPs). The global simulations are downscaled with REMO over the Coordinated Regional Climate Downscaling Experiment (CORDEX) domains Africa, Europe, South America and West Asia from 2006–2100. This unique set of simulations allows for climate type specific analysis across multiple world regions and for multi-scenarios. We used a classification of climate types by Köppen-Trewartha to define evaluation regions with certain climate conditions. A systematic comparison of near-surface temperature and precipitation simulated by the regional and the global model is done. In general, the historical time period is well represented by the GCM and the RCM. Some different biases occur in the RCM compared to the GCM as in the Amazon Basin, northern Africa and the West Asian domain. Both models project similar warming, although somewhat less so by the RCM for certain regions and climate types. A common feature in regions of tropical climate types is that REMO shows dryer climate conditions than forMax Planck Institute for Meteorology-Earth System Model (MPI-ESM) for RCP 4.5 and RCP 8.5, leading to an opposing sign in the climate change signal. With an increase in radiative forcing from RCP 2.6 to RCP 8.5 and towards the end of the 21st century, some of the detected differences between GCM and RCM are more pronounced. Full article