Limiting process in shallow junction solar cells

In extending the violet and nonreflective cell technology to lower resistivities, several processes limiting output power were encountered. The most important was the dark diffusion current due to recombination at the front grid contacts. After removal of this problem by reduction of the silicon metal contact area (to 0.14 percent of the total area), the electric field enhanced junction recombination current J sub r was the main limitation. Alteration of the diffusion profile to reduce the junction field is shown to be an effective means of influencing J sub r. The remaining problems are the bulk recombination in the n+ layer and the surface recombination at the oxide-silicon interface; both of these problems are aggravated by band-narrowing resulting from heavy doping in the diffused layer. Experimental evidence for the main limitations is shown, where increased diffusion temperature is seen to reduce both the influence of the front grid contacts and the junction electric field by increasing the junction depth. The potential for further significant improvement in efficiency appears to be high

Probing the Upper Limit of Nonclassical Rotational Inertia

We study the effect of confinement on solid 4-He's nonclassical rotational inertia (NCRI) in a torsional oscillator by constraining it to narrow annular cells of various widths. The NCRI exhibits a broad maximum value of 20% for annuli of approximately 100 micrometer width. Samples constrained to porous media or to larger geometries both have smaller NCRI, mostly below about 1%. In addition, we extend Kim and Chan's blocked annulus experiment to solid samples with large supersolid fractions. Blocking the annulus suppresses the nonclassical decoupling from 17.1% below the limit of our detection of 0.8%. This result demonstrates the nonlocal nature of the supersolid phenomena. At 20 mK, NCRI depends on velocity history showing a closed hysteresis loop in different thin annular cells.Comment: 5 pages, 4 figure

Silver Standard Masks for Data Augmentation Applied to Deep-Learning-Based Skull-Stripping

The bottleneck of convolutional neural networks (CNN) for medical imaging is the number of annotated data required for training. Manual segmentation is considered to be the "gold-standard". However, medical imaging datasets with expert manual segmentation are scarce as this step is time-consuming and expensive. We propose in this work the use of what we refer to as silver standard masks for data augmentation in deep-learning-based skull-stripping also known as brain extraction. We generated the silver standard masks using the consensus algorithm Simultaneous Truth and Performance Level Estimation (STAPLE). We evaluated CNN models generated by the silver and gold standard masks. Then, we validated the silver standard masks for CNNs training in one dataset, and showed its generalization to two other datasets. Our results indicated that models generated with silver standard masks are comparable to models generated with gold standard masks and have better generalizability. Moreover, our results also indicate that silver standard masks could be used to augment the input dataset at training stage, reducing the need for manual segmentation at this step

Assessing environmental exposures. Air pollution in Scania, southern Sweden.

Background: The environment where we humans live provides the fundamental requirements we need to survive – food to eat, water to drink, and air to breathe. The quality of these elements has a major impact on human health, as they can contain substances that are detrimental to health. These we call environmental pollutants. This thesis explores the effects of exposure to air pollutants in particular. A large portion of the earth’s population is exposed to high levels of air pollution, and 7 million premature deaths worldwid are estimated to be attributed to air pollution. In order to study relationships between exposure to air pollution and health outcomes and to quantify associations, epidemiologic research is needed. From these, exposure-response functions, or in this case air pollution concentration-response functions, are established for diseases and mortality, which form a foundation for quantitative health impact assessments (HIA). HIAs then help stakeholders and the public understand health risks and make, broadly accepted, informed decisions about interventions needed to improve public health.Aim: To explore and evaluate methods to assess air pollution exposure in Scania for application in epidemiologic studies as well as health impact assessments. Methods: Using a detailed emission database covering Scania, dispersion modelling of concentrations of particles and nitrogen oxides was conducted at high temporal and spatial resolutions. Modelled concentrations were evaluated against measurements (Papers I and II) and subsequently used as exposure indicators in a health impact assessment (Paper III) on premature mortality, asthma, dementia, autism spectrum disorders, preeclampsia (PE) and low birth weight. The last paper included (Paper IV) is an epidemiological study on air pollution and preeclampsia.Results: Modelling of nitrogen dioxide (NO2) showed a correlation of RS = 0.8 with measurements at residence facades with a mean difference of 1.08 μg/m3. Results were poorer for modelled versus measured personal exposure. Efforts to compensate for time spent at workplace did not improve the results much. Modelling of particle concentrations also showed correlations with monitor measurements. However, a large proportion of particle concentrations in Scania consists of long-range background emissions, which likely results in a high correlation between different monitors themselves, which likely contributes to the high correlation with modelled concentrations. With a mean population exposure to particles with aerodynamic size of 2.5 μm or less (PM2.5) of 11.9 μg/m3, Scania experiences relatively low exposure levels from an international perspective. Still, we estimated 6% of premature deaths and 11% of low birth weight (LBW) births to be attributed to PM2.5. Reaching a maximum PM2.5 exposure of 10 μg/m3 for all residents would reduce deaths and LBW substantially but could not be achieved only by removing local emissions of PM2.5. Additional results include a positive association between air pollution exposure and preeclampsia among pregnant women. Conclusions: Dispersion modelling is a useful tool for assessing outdoor concentrations of ambient air pollution. It should be noted that concentrations recorded outdoors at the residence of study persons do not equal someone’s total personal exposure. Several alternative approaches exist, and future research will help demonstrate their respective strengths and weaknesses. It is likely that combined methods including remote sensing will prove favourable. Further, our results indicate substantial benefits for public health if the air pollution levels in Scania were reduced despite being comparatively low from an international perspective

Merchandising for a retail flower shop

Thesis (M.B.A.)--Boston University. This item was digitized by the Internet Archive