73 research outputs found
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How to Tailor My ProcessâBased Hydrological Model? Dynamic Identifiability Analysis of Flexible Model Structures
In the field of hydrological modeling, many alternative representations of natural processes exist. Choosing specific process formulations when building a hydrological model is therefore associated with a high degree of ambiguity and subjectivity. In addition, the numerical integration of the underlying differential equations and parametrization of model structures influence model performance. Identifiability analysis may provide guidance by constraining the a priori range of alternatives based on observations. In this work, a flexible simulation environment is used to build an ensemble of semidistributed, process-based hydrological model configurations with alternative process representations, numerical integration schemes, and model parametrizations in an integrated manner. The flexible simulation environment is coupled with an approach for dynamic identifiability analysis. The objective is to investigate the applicability of the framework to identify the most adequate model. While an optimal model configuration could not be clearly distinguished, interesting results were obtained when relating model identifiability with hydro-meteorological boundary conditions. For instance, we tested the Penman-Monteith and Shuttleworth & Wallace evapotranspiration models and found that the former performs better under wet and the latter under dry conditions. Parametrization of model structures plays a dominant role as it can compensate for inadequate process representations and poor numerical solvers. Therefore, it was found that numerical solvers of high order of accuracy do often, though not necessarily, lead to better model performance. The proposed coupled framework proved to be a straightforward diagnostic tool for model building and hypotheses testing and shows potential for more in-depth analysis of process implementations and catchment functioning
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Controlling the Youngâs modulus of a Ă-type Ti-Nb alloy via strong texturing by LPBF
The Ă-type Ti-42Nb alloy was processed by laser powder bed fusion (LPBF) with an infrared top hat laser configuration aiming to control the Youngâs modulus by creating an adapted crystallographic texture. Utilizing a top hat laser, a microstructure with a strong ă0 0 1ă texture parallel to the building direction and highly elongated grains was generated. This microstructure results in a strong anisotropy of the Youngâs modulus that was modeled based on the single crystal elastic tensor and the experimental texture data. Tensile tests along selected loading directions were conducted to study the mechanical anisotropy and showed a good correlation with the modeled data. A Youngâs modulus as low as 44 GPa was measured parallel to the building direction, which corresponds to a significant reduction of over 30% compared to the Youngâs modulus of the Gaussian reference samples (67â69 GPa). At the same time a high 0.2% yield strength of 674 MPa was retained. The results reveal the high potential of LPBF processing utilizing a top hat laser configuration to fabricate patient-specific implants with an adapted low Youngâs modulus along the main loading direction and a tailored mechanical biofunctionality
Fingerprint Identification Using Noise in the Horizontal-to-Vertical Spectral Ratio: Retrieving the Impedance Contrast Structure for the Almaty Basin (Kazakhstan)
Detailed knowledge of the 3D basin structure underlying urban areas is of major importance for improving the assessment of seismic hazard and risk. However, mapping the major features of the shallow geological layers becomes expensive where large areas need to be covered. In this study, we propose an innovative tool, based mainly on single station noise recordings and the horizontal-to-vertical spectral ratio (H/V), to identify and locate the depth of major impedance contrasts. The method is based on an identification of so-called fingerprints of the major impedance discontinuities and their migration to depth by means of an analytical procedure. The method is applied to seismic noise recordings collected in the city of Almaty (Kazakhstan). The estimated impedance contrasts vs. depth profiles are interpolated in order to derive a three-dimensional (3D) model, which after calibration with some available boreholes data allows the major tectonic features in the subsurface to be identified
Pursuing More Aggressive Timelines in the Surgical Treatment of Traumatic Spinal Cord Injury (TSCI): A Retrospective Cohort Study with Subgroup Analysis
Background: The optimal timing of surgical therapy for traumatic spinal cord injury (TSCI) remains unclear. The purpose of this study is to evaluate the impact of âultra-earlyâ (<4 h) versus âearlyâ (4â24 h) time from injury to surgery in terms of the likelihood of neurologic recovery. Methods: The effect of surgery on neurological recovery was investigated by comparing the assessed initial and final values of the American Spinal Injury Association (ASIA) Impairment Scale (AIS). A post hoc analysis was performed to gain insight into different subgroup regeneration behaviors concerning neurological injury levels. Results: Datasets from 69 cases with traumatic spinal cord injury were analyzed. Overall, 19/46 (41.3%) patients of the âultra-earlyâ cohort saw neurological recovery compared to 5/23 (21.7%) patients from the âearlyâ cohort (p = 0.112). The subgroup analysis revealed differences based on the neurological level of injury (NLI) of a patient. An optimal cutpoint for patients with a cervical lesion was estimated at 234 min. Regarding the prediction of neurological improvement, sensitivity was 90.9% with a specificity of 68.4%, resulting in an AUC (area under the curve) of 84.2%. In thoracically and lumbar injured cases, the estimate was lower, ranging from 284 (thoracic) to 245 min (lumbar) with an AUC of 51.6% and 54.3%. Conclusions: Treatment within 24 h after TSCI is associated with neurological recovery. Our hypothesis that intervention within 4 h is related to an improvement in the neurological outcome was not confirmed in our collective. In a clinical context, this suggests that after TSCI there is a time frame to get the right patient to the right hospital according to advanced trauma life support (ATLS) guidelines
Adenosine-stress cardiac magnetic resonance imaging in suspected coronary artery disease: a net cost analysis and reimbursement implications
The health and economic implications of new imaging technologies are increasingly relevant policy issues. Cardiac magnetic resonance imaging (CMR) is currently not or not sufficiently reimbursed in a number of countries including Germany, presumably because of a limited evidence base. It is unknown, however, whether it can be effectively used to facilitate medical decision-making and reduce costs by serving as a gatekeeper to invasive coronary angiography. We investigated whether the application of CMR in patients suspected of having coronary artery disease (CAD) reduces costs by averting referrals to cardiac catheterization. We used propensity score methods to match 218 patients from a CMR registry to a previously studied cohort in which CMR was demonstrated to reliably identify patients who were low-risk for major cardiac events. Covariates over which patients were matched included comorbidity profiles, demographics, CAD-related symptoms, and CAD risk as measured by Morise scores. We determined the proportion of patients for whom cardiac catheterization was deferred based upon CMR findings. We then calculated the economic effects of practice pattern changes using data on cardiac catheterization and CMR costs. CMR reduced the utilization of cardiac catheterization by 62.4%. Based on estimated catheterization costs of ⏠619, the utilization of CMR as a gatekeeper reduced per-patient costs by a mean of ⏠90. Savings were realized until CMR costs exceeded ⏠386. Cost savings were greatest for patients at low-risk for CAD, as measured by baseline Morise scores, but were present for all Morise subgroups with the exception of patients at the highest risk of CAD. CMR significantly reduces the utilization of cardiac catheterization in patients suspected of having CAD. Per-patient savings range from ⏠323 in patients at lowest risk of CAD to ⏠58 in patients at high-risk but not in the highest risk stratum. Because a negative CMR evaluation has high negative predictive value, its application as a gatekeeper to cardiac catheterization should be further explored as a treatment option
Methylxanthines Induce a Change in the AD/Neurodegeneration-Linked Lipid Profile in Neuroblastoma Cells
Alzheimerâs disease (AD) is characterized by an increased plaque burden and tangle
accumulation in the brain accompanied by extensive lipid alterations. Methylxanthines (MTXs) are
alkaloids frequently consumed by dietary intake known to interfere with the molecular mechanisms
leading to AD. Besides the fact that MTX consumption is associated with changes in triglycerides
and cholesterol in serum and liver, little is known about the effect of MTXs on other lipid classes,
which raises the question of whether MTX can alter lipids in a way that may be relevant in AD.
Here we have analyzed naturally occurring MTXs caffeine, theobromine, theophylline, and the
synthetic MTXs pentoxifylline and propentofylline also used as drugs in different neuroblastoma cell
lines. Our results show that lipid alterations are not limited to triglycerides and cholesterol in the
liver and serum, but also include changes in sphingomyelins, ceramides, phosphatidylcholine, and
plasmalogens in neuroblastoma cells. These changes comprise alterations known to be beneficial,
but also adverse effects regarding AD were observed. Our results give an additional perspective
of the complex link between MTX and AD, and suggest combining MTX with a lipid-altering diet
compensating the adverse effects of MTX rather than using MTX alone to prevent or treat AD
Targeting Mental Models of Climate Change Risk to Facilitate Climate Action - Lagos Data Brief
This report summarises the background and topline findings from the Lagos case study of the Targeting Mental models of Climate change risk to facilitate Climate Action (MECCA) project. The research was conducted between 2019 and 2022 with the aim of integrating natural and social science expertise to develop an understanding of the bio-physical risks posed to Lagos by ongoing changes in the climate, how climate change and the associated risks are understood by Lagos residents, and how risk perceptions relate to peopleâs actions
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