A Sensitivity Matrix Methodology for Inverse Problem Formulation

We propose an algorithm to select parameter subset combinations that can be estimated using an ordinary least-squares (OLS) inverse problem formulation with a given data set. First, the algorithm selects the parameter combinations that correspond to sensitivity matrices with full rank. Second, the algorithm involves uncertainty quantification by using the inverse of the Fisher Information Matrix. Nominal values of parameters are used to construct synthetic data sets, and explore the effects of removing certain parameters from those to be estimated using OLS procedures. We quantify these effects in a score for a vector parameter defined using the norm of the vector of standard errors for components of estimates divided by the estimates. In some cases the method leads to reduction of the standard error for a parameter to less than 1% of the estimate

Parameter Estimation and Uncertainty Quantication for an Epidemic Model

We examine estimation of the parameters of Susceptible-Infective-Recovered (SIR) models in the context of least squares. We review the use of asymptotic statistical theory and sensitivity analysis to obtain measures of uncertainty for estimates of the model parameters and the basic reproductive number (R0 )—an epidemiologically significant parameter grouping. We find that estimates of different parameters, such as the transmission parameter and recovery rate, are correlated, with the magnitude and sign of this correlation depending on the value of R0. Situations are highlighted in which this correlation allows R0 to be estimated with greater ease than its constituent parameters. Implications of correlation for parameter identifiability are discussed. Uncertainty estimates and sensitivity analysis are used to investigate how the frequency at which data is sampled affects the estimation process and how the accuracy and uncertainty of estimates improves as data is collected over the course of an outbreak. We assess the informativeness of individual data points in a given time series to determine when more frequent sampling (if possible) would prove to be most beneficial to the estimation process. This technique can be used to design data sampling schemes in more general contexts

System Identification Methods for Dynamic Testing of Fluid-Film Bearings

There are various system identification approaches typically used to extract the rotordynamic coefficients from simultaneously measured dynamic force and motion signals. Since the coefficient values extracted can vary significantly as a function of the system identification approach used, more attention is needed to treat this issue than is typically included in the rotor dynamics literature. This paper describes system identification and data reduction methods used for extracting rotordynamic coefficients of fluid-film journal bearings. Data is used from a test apparatus incorporating a double-spoolshaft spindle which permits independent control over the journal spin speed and the frequency of an adjustable-magnitude circular orbit, for both forward and backward whirling. For example, a least squares linear regression on the force-displacement equations of the experiment provides only one of the rational approaches to extract the anisotropic rotordynamic coefficients (stiffness, damping and fluid inertia effects). Rotordynamic coefficients are also extracted with both first and second order orbital frequency dependencies. To assess the quality of the measured signals, coherence functions are calculated to relate the time-averaged input motion signals and the time-averaged output force signals

X-ray evidence of a native state with increased compactness populated by tryptophan-less B. licheniformis β-lactamase

β-lactamases confer antibiotic resistance, one of the most serious world-wide health problems, and are an excellent theoretical and experimental model in the study of protein structure, dynamics and evolution. Bacillus licheniformis exo-small penicillinase (ESP) is a Class-A β-lactamase with three tryptophan residues located in the protein core. Here, we report the 1.7-Å resolution X-ray structure, catalytic parameters, and thermodynamic stability of ESPΔW, an engineered mutant of ESP in which phenylalanine replaces the wild-type tryptophan residues. The structure revealed no qualitative conformational changes compared with thirteen previously reported structures of B. licheniformis β-lactamases (RMSD = 0.4-1.2 Å). However, a closer scrutiny showed that the mutations result in an overall more compact structure, with most atoms shifted toward the geometric center of the molecule. Thus, ESPΔW has a significantly smaller radius of gyration (Rg) than the other B. licheniformis β-lactamases characterized so far. Indeed, ESPΔW has the smallest Rg among 126 Class-A β-lactamases in the Protein Data Bank (PDB). Other measures of compactness, like the number of atoms in fixed volumes and the number and average of noncovalent distances, confirmed the effect. ESPΔW proves that the compactness of the native state can be enhanced by protein engineering and establishes a new lower limit to the compactness of the Class-A β-lactamase fold. As the condensation achieved by the native state is a paramount notion in protein folding, this result may contribute to a better understanding of how the sequence determines the conformational variability and thermodynamic stability of a given fold.Fil: Risso, Valeria Alejandra. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Acierno, Juan Pablo. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Capaldi, Stefano. Universita di Verona; ItaliaFil: Monaco, Hugo L.. Universita di Verona; ItaliaFil: Ermacora, Mario Roberto. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; Argentin

Flourishing in nature: A review of the benefits of connecting with nature and its application as a wellbeing intervention

From the increasing number of people living in urban areas to the continued degradation of the natural environment, many of us appear to be physically and psychologically disconnected from nature. We consider the theoretical explanations and present evidence for why this state of affairs might result in suboptimal levels of hedonic and eudaimonic wellbeing by reviewing the large body of research on the mental health benefits of connecting with nature. The advantages of contact with nature as a potential wellbeing intervention are discussed, and examples of how this research is being applied to reconnect individuals to nature and improve wellbeing are given. We conclude by considering the limitations of, and proposing future directions for, research in this area. Overall, evidence suggests that connecting with nature is one path to flourishing in life

Transcriptomic Responses of the Honey Bee Brain to Infection with Deformed Wing Virus

Managed colonies of European honey bees (Apis mellifera) are under threat from Varroa destructor mite infestation and infection with viruses vectored by mites. In particular, deformed wing virus (DWV) is a common viral pathogen infecting honey bees worldwide that has been shown to induce behavioral changes including precocious foraging and reduced associative learning. We investigated how DWV infection of bees affects the transcriptomic response of the brain. The transcriptomes of individual brains were analyzed using RNA-Seq after experimental infection of newly emerged adult bees with DWV. Two analytical methods were used to identify differentially expressed genes from the ~15,000 genes in the Apis mellifera genome. The 269 genes that had increased expression in DWV infected brains included genes involved in innate immunity such as antimicrobial peptides (AMPs), Ago2, and Dicer. Single bee brain NMR metabolomics methodology was developed for this work and indicates that proline is strongly elevated in DWV infected brains, consistent with the increased presence of the AMPs abaecin and apidaecin. The 1361 genes with reduced expression levels includes genes involved in cellular communication including G-protein coupled, tyrosine kinase, and ion-channel regulated signaling pathways. The number and function of the downregulated genes suggest that DWV has a major impact on neuron signaling that could explain DWV related behavioral changes

Pulmonary Imaging Phenotypes of Chronic Obstructive Pulmonary Disease Using Multiparametric Response Maps

Background Pulmonary imaging of chronic obstructive pulmonary disease (COPD) has focused on CT or MRI measurements, but these have not been evaluated in combination. Purpose To generate multiparametric response map (mPRM) measurements in ex-smokers with or without COPD by using volume-matched CT and hyperpolarized helium 3

Psychologizing indexes of societal progress: Accounting for cultural diversity in preferred developmental pathways

Since the Second World War, the dominating paradigm of societal development has focused on economic growth. While economic growth has improved the quality of human life in a variety of ways, we posit that the identification of economic growth as the primary societal goal is culture-blind because preferences for developmental pathways likely vary between societies. We argue that the cultural diversity of developmental goals and the pathways leading to these goals could be reflected in a culturally sensitive approach to assessing societal development. For the vast majority of post-materialistic societies, it is an urgent necessity to prepare culturally sensitive compasses on how to develop next, and to start conceptualizing growth in a more nuanced and culturally responsive way. Furthermore, we propose that cultural sensitivity in measuring societal growth could also be applied to existing development indicators (e.g. the Human Development Index). We call for cultural researchers, in cooperation with development economists and other social scientists, to prepare a new cultural map of developmental goals, and to create and adapt development indexes that are more culturally sensitive. This innovation could ultimately help social planners understand the diverse pathways of development and assess the degree to which societies are progressing in a self-determined and indigenously valued manner.info:eu-repo/semantics/acceptedVersio