11 resultados para Clustering-Based Hybrid Evolutionary Algorithm, Identification, Rotor-Bearing System, Bearing Parameter

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The optical quality of the human eye mainly depends on the refractive performance of the cornea. The shape of the cornea is a mechanical balance between intraocular pressure and tissue intrinsic stiffness. Several surgical procedures in ophthalmology alter the biomechanics of the cornea to provoke local or global curvature changes for vision correction. Legitimated by the large number of surgical interventions performed every day, the demand for a deeper understanding of corneal biomechanics is rising to improve the safety of procedures and medical devices. The aim of our work is to propose a numerical model of corneal biomechanics, based on the stromal microstructure. Our novel anisotropic constitutive material law features a probabilistic weighting approach to model collagen fiber distribution as observed on human cornea by Xray scattering analysis (Aghamohammadzadeh et. al., Structure, February 2004). Furthermore, collagen cross-linking was explicitly included in the strain energy function. Results showed that the proposed model is able to successfully reproduce both inflation and extensiometry experimental data (Elsheikh et. al., Curr Eye Res, 2007; Elsheikh et. al., Exp Eye Res, May 2008). In addition, the mechanical properties calculated for patients of different age groups (Group A: 65-79 years; Group B: 80-95 years) demonstrate an increased collagen cross-linking, and a decrease in collagen fiber elasticity from younger to older specimen. These findings correspond to what is known about maturing fibrous biological tissue. Since the presented model can handle different loading situations and includes the anisotropic distribution of collagen fibers, it has the potential to simulate clinical procedures involving nonsymmetrical tissue interventions. In the future, such mechanical model can be used to improve surgical planning and the design of next generation ophthalmic devices.

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The discovery of the interaction of plant-derived N-alkylamides (NAAs) and the mammalian endocannabinoid system (ECS) and the existence of a plant endogenous N-acylethanolamine signaling system have led to the re-evaluation of this group of compounds. Herein, the isolation of seven NAAs and the assessment of their effects on major protein targets in the ECS network are reported. Four NAAs, octadeca-2E,4E,8E,10Z,14Z-pentaene-12-ynoic acid isobutylamide (1), octadeca-2E,4E,8E,10Z,14Z-pentaene-12-ynoic acid 2'-methylbutylamide (2), hexadeca-2E,4E,9Z-triene-12,14-diynoic acid isobutylamide (3), and hexadeca-2E,4E,9,12-tetraenoic acid 2'-methylbutylamide (4), were identified from Heliopsis helianthoides var. scabra. Compounds 2-4 are new natural products, while 1 was isolated for the first time from this species. The previously described macamides, N-(3-methoxybenzyl)-(9Z,12Z,15Z)-octadecatrienamide (5), N-benzyl-(9Z,12Z,15Z)-octadecatrienamide (6), and N-benzyl-(9Z,12Z)-octadecadienamide (7), were isolated from Lepidium meyenii (Maca). N-Methylbutylamide 4 and N-benzylamide 7 showed submicromolar and selective binding affinities for the cannabinoid CB1 receptor (Ki values of 0.31 and 0.48 μM, respectively). Notably, compound 7 also exhibited weak fatty acid amide hydrolase (FAAH) inhibition (IC50 = 4 μM) and a potent inhibition of anandamide cellular uptake (IC50 = 0.67 μM) that was stronger than the inhibition obtained with the controls OMDM-2 and UCM707. The pronounced ECS polypharmacology of compound 7 highlights the potential involvement of the arachidonoyl-mimicking 9Z,12Z double-bond system in the linoleoyl group for the overall cannabimimetic action of NAAs. This study provides additional strong evidence of the endocannabinoid substrate mimicking of plant-derived NAAs and uncovers a direct and indirect cannabimimetic action of the Peruvian Maca root.

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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

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The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

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PURPOSE : For the facilitation of minimally invasive robotically performed direct cochlea access (DCA) procedure, a surgical planning tool which enables the surgeon to define landmarks for patient-to-image registration, identify the necessary anatomical structures and define a safe DCA trajectory using patient image data (typically computed tomography (CT) or cone beam CT) is required. To this end, a dedicated end-to-end software planning system for the planning of DCA procedures that addresses current deficiencies has been developed. METHODS :    Efficient and robust anatomical segmentation is achieved through the implementation of semiautomatic algorithms; high-accuracy patient-to-image registration is achieved via an automated model-based fiducial detection algorithm and functionality for the interactive definition of a safe drilling trajectory based on case-specific drill positioning uncertainty calculations was developed. RESULTS :    The accuracy and safety of the presented software tool were validated during the conduction of eight DCA procedures performed on cadaver heads. The plan for each ear was completed in less than 20 min, and no damage to vital structures occurred during the procedures. The integrated fiducial detection functionality enabled final positioning accuracies of [Formula: see text] mm. CONCLUSIONS :    Results of this study demonstrated that the proposed software system could aid in the safe planning of a DCA tunnel within an acceptable time.

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In this paper we study the problem of blind deconvolution. Our analysis is based on the algorithm of Chan and Wong [2] which popularized the use of sparse gradient priors via total variation. We use this algorithm because many methods in the literature are essentially adaptations of this framework. Such algorithm is an iterative alternating energy minimization where at each step either the sharp image or the blur function are reconstructed. Recent work of Levin et al. [14] showed that any algorithm that tries to minimize that same energy would fail, as the desired solution has a higher energy than the no-blur solution, where the sharp image is the blurry input and the blur is a Dirac delta. However, experimentally one can observe that Chan and Wong's algorithm converges to the desired solution even when initialized with the no-blur one. We provide both analysis and experiments to resolve this paradoxical conundrum. We find that both claims are right. The key to understanding how this is possible lies in the details of Chan and Wong's implementation and in how seemingly harmless choices result in dramatic effects. Our analysis reveals that the delayed scaling (normalization) in the iterative step of the blur kernel is fundamental to the convergence of the algorithm. This then results in a procedure that eludes the no-blur solution, despite it being a global minimum of the original energy. We introduce an adaptation of this algorithm and show that, in spite of its extreme simplicity, it is very robust and achieves a performance comparable to the state of the art.

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A likelihood-based discriminant for the identification of quark- and gluon-initiated jets is built and validated using 4.7 fb−1 √ of proton–proton collision data at √s = 7 TeV collected with the ATLAS detector at the LHC. Data sampleswith enriched quark or gluon content are used in the construction and validation of templates of jet properties that are the input to the likelihood-based discriminant. The discriminating power of the jet tagger is established in both data and Monte Carlo samples within a systematic uncertainty of ≈ 10–20 %. In data, light-quark jets can be tagged with an efficiency of ≈ 50% while achieving a gluon-jet mis-tag rate of ≈ 25% in a pT range between 40 GeV and 360 GeV for jets in the acceptance of the tracker. The rejection of gluon-jets found in the data is significantly below what is attainable using a Pythia 6Monte Carlo simulation, where gluon-jet mis-tag rates of 10% can be reached for a 50% selection efficiency of light-quark jets using the same jet properties.

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A large family of bifunctional 1,2,4-triazole molecular tectons (tr) has been explored for engineering molybdenum(VI) oxide hybrid solids. Specifically, tr ligands bearing auxiliary basic or acidic groups were of the type amine, pyrazole, 1H-tetrazole, and 1,2,4-triazole. The organically templated molybdenum(VI) oxide solids with the general compositions [MoO3(tr)], [Mo2O6(tr)], and [Mo2O6(tr)(H2O)2] were prepared under mild hydrothermal conditions or by refluxing in water. Their crystal structures consist of zigzag chains, ribbons, or helixes of alternating cis-{MoO4N2} or {MoO5N} polyhedra stapled by short [N–N]-tr bridges that for bitriazole ligands convert the motifs into 2D or 3D frameworks. The high thermal (235–350 °C) and chemical stability observed for the materials makes them promising for catalytic applications. The molybdenum(VI) oxide hybrids were successfully explored as versatile oxidation catalysts with tert-butyl hydroperoxide (TBHP) or aqueous H2O2 as an oxygen source, at 70 °C. Catalytic performances were influenced by the different acidic–basic properties and steric hindrances of coordinating organic ligands as well as the structural dimensionality of the hybrid.

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BACKGROUND  Drug resistance is a major barrier to successful antiretroviral treatment (ART). Therefore, it is important to monitor time trends at a population level. METHODS  We included 11,084 ART-experienced patients from the Swiss HIV Cohort Study (SHCS) between 1999 and 2013. The SHCS is highly representative and includes 72% of patients receiving ART in Switzerland. Drug resistance was defined as the presence of at least one major mutation in a genotypic resistance test. To estimate the prevalence of drug resistance, data for patients with no resistance test was imputed based on patient's risk of harboring drug resistant viruses. RESULTS  The emergence of new drug resistance mutations declined dramatically from 401 to 23 patients between 1999 and 2013. The upper estimated prevalence limit of drug resistance among ART-experienced patients decreased from 57.0% in 1999 to 37.1% in 2013. The prevalence of three-class resistance decreased from 9.0% to 4.4% and was always <0.4% for patients who initiated ART after 2006. Most patients actively participating in the SHCS in 2013 with drug resistant viruses initiated ART before 1999 (59.8%). Nevertheless, in 2013, 94.5% of patients who initiated ART before 1999 had good remaining treatment options based on Stanford algorithm. CONCLUSION  HIV-1 drug resistance among ART-experienced patients in Switzerland is a well-controlled relic from the pre-combination ART era. Emergence of drug resistance can be virtually stopped with new potent therapies and close monitoring.