The present paper proposes a novel approach for the representation of the imperfect plate geometry of ships structures and assess its impact on the probabilistic ultimate strength of plates and ...hull-girders. The description of the imperfect geometry is basically implemented using the theory of random fields. Evidence for the selection and robustness of the proposed model is documented from literature data and real measurement campaigns conducted on ships. A preliminary study is first presented upon the prediction of plates’ probabilistic ultimate strength comparing the efficiency of the proposed model with existing imperfection models from literature. Afterwards, a case study on a VLCC oil tanker for the prediction of hull-girder ultimate strength applying different imperfection models takes place. In order to evaluate the variability of ultimate strength under the effect of stochastic imperfections, artificial neural networks (ANNs), which trained appropriately with relatively limited results of non-linear finite element calculations, are used. The main objective of this research study is to provide a methodology for the evaluation of probabilistic-based ultimate strength assessment of plates and hull-girders in view of stochastic geometric imperfections. In doing so, and incorporating other sources of uncertainties, the designer/engineer should be able to perform a valuable reliability-based analysis of the structure.
•A newly proposed probabilistic-based imperfection model is introduced via the spectral representation method.•The impact of stochastic geometric imperfections on the ultimate strength of plates is assessed.•ANNs are used to predict the stochastic hull-girder ultimate strength replacing the time-consuming NLFEA.
Chronic limb-threatening ischemia (CLTI) represents one of the most severe forms of peripheral arterial disease implying impaired wound healing and tissue loss at the same time posing a significant ...impact on the quality of life of patients and a serious economic burden on healthcare systems around the world. A major challenge in the management of patients with CLTI is the validity and role of non-invasive hemodynamic parameters in assessing their clinical status before and after revascularization. Traditionally, the diagnosis of CLTI is routinely based on clinical symptoms and confirmed by measurements of non-invasive limb hemodynamics including ankle-brachial pressure index (ABPI) and toe-brachial pressure index (TBPI). However, whether these indices alone can provide definitive treatment or be used as adjunctive tool along with the implementation of novel techniques to help guide revascularization for CLI patients still remains unclear.
We consider the problem of estimating the density of observations taking values in classical or nonclassical spaces such as manifolds and more general metric spaces. Our setting is quite general but ...also sufficiently rich in allowing the development of smooth functional calculus with well localized spectral kernels, Besov regularity spaces, and wavelet type systems. Kernel and both linear and nonlinear wavelet density estimators are introduced and studied. Convergence rates for these estimators are established and discussed.
Purpose:
Thoracic endovascular aortic aneurysm repair (TEVAR) has emerged as an attractive alternative option in the treatment of thoracoabdominal aortic aneurysm (TAAA) diseases, reporting lower ...morbidity and mortality rates compared with open or hybrid repair. A challenging situation arises when the aneurysm involves the celiac artery (CA), precluding a safe distal landing zone. We investigated the safety and efficacy of CA coverage in the treatment of complex TAAA diseases during endovascular management.
Materials and Methods:
A review of the literature was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. The electronic bibliographic sources searched were MEDLINE and SCOPUS databases. Primary outcomes of interest were perioperative and 30-day mortality. Any type of endoleak, mesenteric ischemia, perioperative spinal cord ischemia, and reintervention rates were secondary end points. A random-effects meta-analysis was performed. Summary statistics of event risks were expressed as proportions and 95% confidence interval (CI).
Results:
Ten observational cohort studies published between 2009 and 2020, reporting a total of 175 patients, were eligible for quantitative synthesis. Indications for TEVAR were primary TAAAs in 82% of patients, aortic dissection in 14% of patients, type Ib endoleak after previous endograft deployment in 3% of patients, and penetrating aortic ulcer in 1 patient. Reintervention rate was 9% (95% CI, 4%–20%) and spinal cord ischemia was 7% (95% CI, 4%–-12%). Type II endoleak was the predominant type of endoleak in 10% of patients (95% CI, 4%–22%), followed by type I endoleak in 5% of patients (95% CI, 2%–12%) and type III endoleak in 1% (95% CI, 0%–16%) of patients. Mesenteric ischemia occurred in 6% of patients (95% CI, 3%–10%). Thirty-day mortality was 5% (95% CI, 2%–13%) and the pooled estimate for overall mortality was 21% (95% CI, 14%–31%).
Conclusions:
Celiac artery coverage during TEVAR is a challenging but feasible option for the treatment of TAAA diseases, providing acceptable morbidity and mortality rates. Demonstration of adequate visceral collateral pathways before definitive CA coverage is the sine quo non for the success of the technique.
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► Development of a multivariable nonlinear model predictive control (NMPC) scheme. ► Solution of a dynamic optimization problem using a nonlinear fuel cell model. ► Implementation of ...a supervisory control and monitoring automation infrastructure. ► Online deployment of the NMPC scheme to a small-scale fully automated fuel cell unit. ► Efficient set-point tracking in the presence of model mismatch and disturbances.
The aim of this work is to develop and deploy an advanced model-based control framework for a polymer electrolyte membrane (PEM) fuel cell system. The framework relies on nonlinear model predictive control (NMPC) using a reliable and efficient dynamic optimization approach which discretizes both manipulated and state variables. The optimization is performed using a direct transcription method that handles the optimal control problem as a nonlinear programming (NLP) problem. The motivation for the control is to ensure optimum power generation following a variable load demand with acceptable response time while avoiding oxygen starvation and minimizing hydrogen consumption. To validate the applicability, efficiency and robustness of the NMPC scheme a small-scale fully automated unit was used and an experimentally validated semi-empirical dynamic model was utilized at the core of the optimization scheme. The on-line application of the multivariable controller shows that the proposed framework can accomplish the desired objectives for power demand in the context of a safe operating region. Furthermore the controller exhibits excellent performance in terms of computational requirements and can follow load changes with a negligible error in its response, even at varying operating conditions.
Alzheimer's disease (AD) is a debilitating brain disorder that afflicts millions worldwide with no effective treatment. Currently, AD progression has primarily been characterized by abnormal ...accumulations of β-amyloid within plaques and phosphorylated tau within neurofibrillary tangles, giving rise to neurodegeneration due to synaptic and neuronal loss. While β-amyloid and tau deposition are required for clinical diagnosis of AD, presence of such abnormalities does not tell the complete story, and the actual mechanisms behind neurodegeneration in AD progression are still not well understood. Support for abnormal iron accumulation playing a role in AD pathogenesis includes its presence in the early stages of the disease, its interactions with β-amyloid and tau, and the important role it plays in AD related inflammation. In this review, we present the existing evidence of pathological iron accumulation in the human AD brain, as well as discuss the imaging tools and peripheral measures available to characterize iron accumulation and dysregulation in AD, which may help in developing iron-based biomarkers or therapeutic targets for the disease.
In situ detection of hybridization can be through changes in mass changes in the optical properties, or changes in the electrochemical properties of the interface. Many of these methods require prior ...labeling of the DNA target or probe with special isotopes, fluorescence markers, or redox-active tags. Surface plasmon resonance (SPR) spectroscopy is known to be sensitive to the presence of unlabeled DNA at an interface. We report here the first quantitative in situ SPR study of the hybridization and dehybridization of a tethered unlabeled DNA film on a passivated gold surface. For the passivated gold surfaces used in these studies, no nonspecific adsorption of ss-DNA is observed, whereas a bare or partially covered gold surface will readily adsorb ss-DNA. For these studies, we use a novel two-color SPR method that allows us to quantify the number of ss-DNA molecules per unit area for tethered DNA films. These two-component films containing a thiol-derivatized ss-DNA molecule and a diluent thiol, mercaptohexanol (HS(CH sub(2)CH sub(2)) sub(3)OH), were prepared using molecular self-assembly techniques developed by Herne and Tarlov. In these films, the 25 base oligomer is tethered to the gold surface via an alkanethiol covalently linked at the 5' position of the ss-DNA. The mercaptohexanol serves to prevent nonspecific adsorption of ss-DNA. Using in situ SPR, we monitored the kinetics of hybridization for these films, determined the total number and percentage of active binding sites, and measured the hybridization activity of the film through five hybridization--dehybridization (melting) cycles.
The performance of a new diagnostic test is frequently evaluated by comparison to a perfect reference test (i.e. a gold standard). In many instances, however, a reference test is less than perfect. ...In this paper, we review methods for estimation of the accuracy of a diagnostic test when an imperfect reference test with known classification errors is available. Furthermore, we focus our presentation on available methods of estimation of test characteristics when the sensitivity and specificity of both tests are unknown. We present some of the available statistical methods for estimation of the accuracy of diagnostic tests when a reference test does not exist (including maximum likelihood estimation and Bayesian inference). We illustrate the application of the described methods using data from an evaluation of a nested polymerase chain reaction and microscopic examination of kidney imprints for detection of
Nucleospora salmonis in rainbow trout.
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