123 research outputs found
Fabrication and performance analysis of 4-sq cm indium tin oxide/InP photovoltaic solar cells
Large-area photovoltaic solar cells based on direct current magnetron sputter deposition of indium tin oxide (ITO) into single-crystal p-InP substrates demonstrated both the radiation hardness and high performance necessary for extraterrestrial applications. A small-scale production project was initiated in which approximately 50 ITO/InP cells are being produced. The procedures used in this small-scale production of 4-sq cm ITO/InP cells are presented and discussed. The discussion includes analyses of performance range of all available production cells, and device performance data of the best cells thus far produced. Additionally, processing experience gained from the production of these cells is discussed, indicating other issues that may be encountered when large-scale productions are begun
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Quaestor: Query web caching for database-as-a-service providers
Today, web performance is primarily governed by round-trip latencies between end devices and cloud services. To improve performance, services need to minimize the delay of accessing data. In this paper, we propose a novel approach to low latency that relies on existing content delivery and web caching infrastructure. The main idea is to enable application-independent caching of query results and records with tunable consistency guarantees, in particular bounded staleness. Q
uaestor
(Query Store) employs two key concepts to incorporate both expiration-based and invalidation-based web caches: (1) an Expiring Bloom Filter data structure to indicate potentially stale data, and (2) statistically derived cache expiration times to maximize cache hit rates. Through a distributed query invalidation pipeline, changes to cached query results are detected in real-time. The proposed caching algorithms offer a new means for data-centric cloud services to trade latency against staleness bounds, e.g. in a database-as-a-service. Q
uaestor
is the core technology of the backend-as-a-service platform Baqend, a cloud service for low-latency websites. We provide empirical evidence for Q
uaestor
's scalability and performance through both simulation and experiments. The results indicate that for read-heavy workloads, up to tenfold speed-ups can be achieved through Q
uaestor
's caching.
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Left Ventricle Quantification Using Direct Regression with Segmentation Regularization and Ensembles of Pretrained 2D and 3D CNNs
Cardiac left ventricle (LV) quantification provides a tool for diagnosing
cardiac diseases. Automatic calculation of all relevant LV indices from cardiac
MR images is an intricate task due to large variations among patients and
deformation during the cardiac cycle. Typical methods are based on segmentation
of the myocardium or direct regression from MR images. To consider cardiac
motion and deformation, recurrent neural networks and spatio-temporal
convolutional neural networks (CNNs) have been proposed. We study an approach
combining state-of-the-art models and emphasizing transfer learning to account
for the small dataset provided for the LVQuan19 challenge. We compare 2D
spatial and 3D spatio-temporal CNNs for LV indices regression and cardiac phase
classification. To incorporate segmentation information, we propose an
architecture-independent segmentation-based regularization. To improve the
robustness further, we employ a search scheme that identifies the optimal
ensemble from a set of architecture variants. Evaluating on the LVQuan19
Challenge training dataset with 5-fold cross-validation, we achieve mean
absolute errors of 111 +- 76mm^2, 1.84 +- 0.9mm and 1.22 +- 0.6mm for area,
dimension and regional wall thickness regression, respectively. The error rate
for cardiac phase classification is 6.7%.Comment: Accepted at the MICCAI Workshop STACOM 201
Comparison of Minority Carrier Lifetime Measurements in Superstrate and Substrate CdTe PV Devices: Preprint
We discuss typical and alternative procedures to analyze time-resolved photoluminescence (TRPL) measurements of minority carrier lifetime (MCL) with the hope of enhancing our understanding of how this technique may be used to better analyze CdTe photovoltaic (PV) device functionality. Historically, TRPL measurements of the fast recombination rate (t1) have provided insightful correlation with broad device functionality. However, we have more recently found that t1 does not correlate as well with smaller changes in device performance, nor does it correlate well with performance differences observed between superstrate and substrate CdTe PV devices. This study presents TRPL data for both superstrate and substrate CdTe devices where both t1 and the slower TRPL decay (t2) are analyzed. The study shows that changes in performance expected from small changes in device processing may correlate better with t2. Numerical modeling further suggests that, for devices that are expected to have similar drift field in the depletion region, effects of changes in bulk MCL and interface recombination should be more pronounced in t2. Although this technique may provide future guidance to improving CdS/CdTe device performance, it is often difficult to extract statistically precise values for t2, and therefore t2 data may demonstrate significant scatter when correlated with performance parameters
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ZnO:Al Doping Level and Hydrogen Growth Ambient Effects on CIGS Solar Cell Performance: Preprint
Cu(In,Ga)Se2 (CIGS) photovoltaic (PV) cells require a highly conducting and transparent electrode for optimum device performance. ZnO:Al films grown from targets containing 2.0 wt.% Al2O3 are commonly used for this purpose. Maximum carrier mobilities of these films grown at room temperature are ~20-25 cm2V-1s-1. Therefore, relatively high carrier concentrations are required to achieve the desired conductivity, which leads to free carrier absorption in the near infrared (IR). Lightly doped films (0.05 - 0.2 wt.% Al2O3), which show less IR absorption, reach mobility values greater than 50 cm2V-1s-1 when deposited in H2 partial pressure. We incorporate these lightly doped ZnO:Al layers into CIGS PV cells produced at the National Renewable Energy Laboratory (NREL). Preliminary results show quantum efficiency values of these cells rival those of a past world-record cell produced at NREL that used 2.0 wt.% Al-doped ZnO films. The highest cell efficiency obtained in this trial was 18.1%
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ZnO:Al Doping Level and Hydrogen Growth Ambient Effects on CIGS Solar Cell Performance
Human-computer collaboration for skin cancer recognition
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice
Mutation of pescadillo Disrupts Oligodendrocyte Formation in Zebrafish
Background: In vertebrates, the myelin sheath is essential for efficient propagation of action potentials along the axon shaft. Oligodendrocytes are the cells of the central nervous system that create myelin sheaths. During embryogenesis, ventral neural tube precursors give rise to oligodendrocyte progenitor cells, which divide and migrate throughout the central nervous system. This study aimed to investigate mechanisms that regulate oligodendrocyte progenitor cell formation. Methodology/Principal Findings: By conducting a mutagenesis screen in transgenic zebrafish, we identified a mutation, designated vu166, by an apparent reduction in the number of oligodendrocyte progenitor cells in the dorsal spinal cord. We subsequently determined that vu166 is an allele of pescadillo, a gene known to play a role in ribosome biogenesis and cell proliferation. We found that pescadillo function is required for both the proper number of oligodendrocyte progenitors to form, by regulating cell cycle progression, and for normal levels of myelin gene expression. Conclusions/Significance: Our data provide evidence that neural precursors require pes function to progress through th
Novel roles of the chemorepellent axon guidance molecule RGMa in cell migration and adhesion
The repulsive guidance molecule A (RGMa) is a contact-mediated axon guidance molecule that has significant roles in central nervous system (CNS) development. Here we have examined whether RGMa has novel roles in cell migration and cell adhesion outside the nervous system. RGMa was found to stimulate cell migration from Xenopus animal cap explants in a neogenin-dependent and BMP-independent manner. RGMa also stimulated the adhesion of Xenopus animal cap cells, and this adhesion was dependent on neogenin and independent of calcium. To begin to functionally characterize the role of specific domains in RGMa, we assessed the migratory and adhesive activities of deletion mutants. RGMa lacking the partial von Willebrand factor type D (vWF) domain preferentially perturbed cell adhesion, while mutants lacking the RGD motif affected cell migration. We also revealed that manipulating the levels of RGMa in vivo caused major migration defects during Xenopus gastrulation. We have revealed here novel roles of RGMa in cell migration and adhesion and demonstrated that perturbations to the homeostasis of RGMa expression can severely disrupt major morphogenetic events. These results have implications for understanding the role of RGMa in both health and disease
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