Three-dimensional electromagnetic cross-well inversion

An inversion algorithm for a vertical magnetic dipole source and a vertical magnetic field component receiver is presented. A three-dimensional integral equation algorithm is used for calculating the electromagnetic response of a particular trial reservoir model. The inversion formalism used is the Marquardt technique of nonlinear least-squares optimization. The system derivatives are calculated using an exact expression derived from reciprocity. The derivative calculation involves introducing sources at the receiver locations with subsequent back-substitution into the impedance matrix equation. The inversion algorithm was tested on data gathered with a laboratory scale model. Convergence to the neighborhood of the correct model from distant initial trial models is good     

Cellular Senescence: Pathogenic Mechanisms in Lung Fibrosis

Pulmonary fibrosis is a chronic and fatal lung disease that significantly impacts the aging population globally. To date, anti-fibrotic, immunosuppressive, and other adjunct therapy demonstrate limited efficacies. Advancing our understanding of the pathogenic mechanisms of lung fibrosis will provide a future path for the cure. Cellular senescence has gained substantial interest in recent decades due to the increased incidence of fibroproliferative lung diseases in the older age group. Furthermore, the pathologic state of cellular senescence that includes maladaptive tissue repair, decreased regeneration, and chronic inflammation resembles key features of progressive lung fibrosis. This review describes regulatory pathways of cellular senescence and discusses the current knowledge on the senescence of critical cellular players of lung fibrosis, including epithelial cells (alveolar type 2 cells, basal cells, etc.), fibroblasts, and immune cells, their phenotypic changes, and the cellular and molecular mechanisms by which these cells contribute to the pathogenesis of pulmonary fibrosis. A few challenges in the field include establishing appropriate in vivo experimental models and identifying senescence-targeted signaling molecules and specific therapies to target senescent cells, known collectively as “senolytic” or “senotherapeutic” agents.     

Determination of particle size distribution in a modified hop extract emulsion by electrical resistivity

A procedure has been developed which is suitable for the evaluation of particle size distribution in emulsions of modified hop extracts. A Coulter Counter Model A and a Coulter Counter Model B equipped with a Model M Data Converter were used to assess the weight percent distribution of particles smaller than 10 μm in diameter. The influences of electrolyte concentration, length of analysis, and concentration of the hop extract particles were factors affecting the reproducibility of the study. It was found that identical distribution curves could be obtained with either instrument. The Model B Coulter Counter with the Model M Data Converter is preferred since weight fractions are provided directly and lengthy calculation procedures are eliminated. Coincidence correction on particle counts was unnecessary under the controlled conditions of the analysis.     

Improved methods for evaluating the molar mass distributions of cellulose in kraft pulp

Multi‐angle laser light scattering (MALLS) was used to characterize birch kraft pulps with respect to their absolute molecular mass distributions (MMDs). The pulps were dissolved in lithium chloride/N,N‐dimethylacetamide and separated by size exclusion chromatography (SEC). The weight‐average and number‐average molecular masses of the cellulose fractions of the pulps obtained from the absolute MALLS measurements were compared with the molar masses obtained by direct‐standard‐calibration relative pullulan standards. Discrepancies between the two detection methods were found, and two ways of correlating the relative pullulan molar masses to the absolute molar masses were examined. In the first method, the correlation was made over a large range of molecular masses. The second method correlated the molecular masses of the standards to the molecular masses of samples by the calculation of fictitious, cellulose‐equivalent molar masses of the standards. With the preferred second method, a more correct MMD of kraft pulp samples could, therefore, be obtained from an SEC system calibrated with narrow standards. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 1170–1179, 2003     

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

Objective

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

Materials and methods

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader’s subjective confidence to assess the images (not confident, confident, very confident).

Results

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as ‘perfusion deficit’, 113 vs. 109 as ‘dark rim artifacts’, 9 vs. 7 as ‘uncertain signal loss’, and 817 vs. 824 as ‘normal’. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as ‘good’ or ‘excellent’ (92 vs. 63%), and the diagnostic confidence more often as “very confident” (71 vs. 45%) compared to non-MoCo.

Conclusions

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader’s subjective confidence to assess the images were rated more favorably for MoCo.

     

Frequency of migrants and migratory activity are genetically correlated in a bird population: evolutionary implications

Most migratory bird populations are composed of individuals that migrate and individuals that remain resident. While the role of ecological factors in maintaining this behavioral dimorphism has received much attention, the importance of genetic constraints on the evolution of avian migration has not yet been considered. Drawing on the recorded migratory activities of 775 blackcaps (Sylvia atricapilla) from a partially migratory population in southern France, we tested two alternative genetic models about the relationship between incidence and amount of migratory activity. The amount of migratory activity could be the continuous variable "underlying" the phenotypic expression of migratory urge, or, alternatively, the expression of both traits could be controlled by two separate genetic systems. The distributions of migratory activities in five different cohorts and the inheritance pattern derived from selective breeding experiments both indicate that incidence and amount of migratory activity are two aspects of one trait. Thus, all birds without measurable activity have activity levels at the low end of a continuous distribution, below the limit of expression or detection. The phenotypic dichotomy "migrant-nonmigrant" is caused by a threshold which may not be fixed but influenced both genetically and environmentally. This finding has profound implications for the evolution of migration: the transition from migratoriness to residency should not only be driven by selection favoring resident birds but also by selection for lower migratory activity. This potential for selection on two aspects, residency and migration distance, of the same trait may enable extremely rapid evolutionary changes to occur in migratory behavior.     

The double-edged effects of explanation prompts

Explanation prompts usually foster conceptual understanding. However, it has been claimed within cognitive load theory that prompts can take cognitive load to the upper limit when learning complex contents. Under such circumstances, prompts focusing the learners’ attention on specific aspects (e.g., conceptual aspects such as elaborations on domain principles) might have some costs: Other important aspects (e.g., procedural aspects such as how to calculate) cannot be processed deeply. Thus, we expected that conceptually-oriented explanation prompts would foster the detailedness of explanations, the number of elaborations on domain principles, and conceptual knowledge. In addition, we tested the influence of such prompts on the number of calculations performed during learning and procedural knowledge. We conducted an experiment in which we employed conceptually-oriented explanation prompts in a complex e-learning module on tax law. Tax law university students (N = 40) worked on this e-learning module under two conditions: (a) conceptually-oriented explanation prompts, (b) no prompts. The prompts led to double-edged effects: positive effects on the detailedness of explanations and on the number of elaborations on domain principles, as well as on conceptual knowledge and simultaneously negative effects on the number of calculations performed during learning as well as on procedural knowledge.     

Input features' impact on fuzzy decision processes

Many real-world applications have very high dimensionality and require very complex decision borders. In this case, the number of fuzzy rules can proliferate, and the easy interpretability of fuzzy models can progressively disappear. An important part of the model interpretation lies on the evaluation of the effectiveness of the input features on the decision process. In this paper, we present a method that quantifies the discriminative power of the input features in a fuzzy model. The separability among all the rules of the fuzzy model produces a measure of the information available in the system. Such measure of information is calculated to characterize the system before and after each input feature is used for classification. The resulting information gain quantifies the discriminative power of that input feature. The comparison among the information gains of the different input features can yield better insights into the selected fuzzy classification strategy, even for very high dimensional cases, and can lead to a possible reduction of the input space dimension. Several artificial and real-world data analysis scenarios are reported as examples in order to illustrate the characteristics and potentialities of the proposed method.