Pseudomorphic growth of InAs on misoriented GaAs for extending quantum cascade laser wavelength

The authors have studied the impact of epilayer strain on the deposition of InAs/GaAs on (100) and (111)B with 2 degrees offset toward 2-1-1 surfaces. Consequences of a 7% lattice mismatch between these orientations in the form of three-dimensional growth are less apparent for (111)B with 2 degrees offset toward 2-1-1 surfaces compared to (100). By exploring a range of molecular beam epitaxy process parameters for InAs/GaAs growth and utilizing scanning electron microscopy, atomic force microscopy, and Raman spectroscopy to evaluate the quality of these strained layers, the authors develop empirical models that describe the influence of the process conditions in regards to surface roughness with \u3e92% accuracy. The smoothest InAs/GaAs samples demonstrated average surface roughness of 0.08 nm for 10 um-squre areas, albeit at very low deposition rates. The authors have found the most important process conditions to be substrate temperature and deposition rate, leading us to believe that controlling diffusion length may be the key to reducing defects in severely strained structures. InGaAs/AlGaAs quantum cascade laser structures were also produced on (111)B with 2 degrees offset toward 2-1-1 to take advantage of the piezoelectric effect, and the modified laser transitions due to these effects were observed

A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity

Pretraining is the preliminary and fundamental step in developing capable language models (LM). Despite this, pretraining data design is critically under-documented and often guided by empirically unsupported intuitions. To address this, we pretrain 28 1.5B parameter decoder-only models, training on data curated (1) at different times, (2) with varying toxicity and quality filters, and (3) with different domain compositions. First, we quantify the effect of pretraining data age. A temporal shift between evaluation data and pretraining data leads to performance degradation, which is not overcome by finetuning. Second, we explore the effect of quality and toxicity filters, showing a trade-off between performance on standard benchmarks and risk of toxic generations. Our findings indicate there does not exist a one-size-fits-all solution to filtering training data. We also find that the effects of different types of filtering are not predictable from text domain characteristics. Lastly, we empirically validate that the inclusion of heterogeneous data sources, like books and web, is broadly beneficial and warrants greater prioritization. These findings constitute the largest set of experiments to validate, quantify, and expose many undocumented intuitions about text pretraining, which we hope will help support more informed data-centric decisions in LM development

SRTR Program-Specific Reports on Outcomes: A Guide for the New Reader

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72405/1/j.1600-6143.2008.02178.x.pd

Increasing the electrolyte capacity of alkaline Zn-air fuel cells by scavenging zincate with Ca(OH)2

The use of calcium hydroxide for scavenging zincate species is demonstrated to be a highly effective approach for increasing the electrolyte capacity and improving the performance of the zinc-air fuel cell system. A fundamental approach is established in this study to quantify the formation of calcium zincate as the product of scavenging and the amount of water compensation necessary for optimal performance. The good agreement between predicted and experimental results proves the validity of the proposed theoretical approach. By applying the results of theoretical predictions, both the electrolyte capacity and the cell longevity have been increased by more than 40%. It is also found that, using Ca(OH)2 to scavenge zincate species in concentrated KOH solutions, affects mostly the removal of zincate, rather than ZnO, from the electrolyte, whereas the presence of excess, free, mobile H2O plays a key role in dissolving ZnO and forming zincate. The results obtained in this study demonstrate that the proposed approach can widely and effectively be applied to all zinc-air cell systems during their discharge cycle

The SCF Slimb ubiquitin ligase regulates Plk4/Sak levels to block centriole reduplication

Restricting centriole duplication to once per cell cycle is critical for chromosome segregation and genomic stability, but the mechanisms underlying this block to reduplication are unclear. Genetic analyses have suggested an involvement for Skp/Cullin/F box (SCF)-class ubiquitin ligases in this process. In this study, we describe a mechanism to prevent centriole reduplication in Drosophila melanogaster whereby the SCF E3 ubiquitin ligase in complex with the F-box protein Slimb mediates proteolytic degradation of the centrosomal regulatory kinase Plk4. We identified SCFSlimb as a regulator of centriole duplication via an RNA interference (RNAi) screen of Cullin-based ubiquitin ligases. We found that Plk4 binds to Slimb and is an SCFSlimb target. Both Slimb and Plk4 localize to centrioles, with Plk4 levels highest at mitosis and absent during S phase. Using a Plk4 Slimb-binding mutant and Slimb RNAi, we show that Slimb regulates Plk4 localization to centrioles during interphase, thus regulating centriole number and ensuring the block to centriole reduplication

Defining Components of the ßcatenin Destruction Complex and Exploring Its Regulation and Mechanisms of Action during Development

A subset of signaling pathways play exceptionally important roles in embryonic and post-embryonic development, and mis-regulation of these pathways occurs in most human cancers. One such pathway is the Wnt pathway. The primary mechanism keeping Wnt signaling off in the absence of ligand is regulated proteasomal destruction of the canonical Wnt effector ßcatenin (or its fly homolog Armadillo). A substantial body of evidence indicates that SCF(βTrCP) mediates βcat destruction, however, an essential role for Roc1 has not been demonstrated in this process, as would be predicted. In addition, other E3 ligases have also been proposed to destroy βcat, suggesting that βcat destruction may be regulated differently in different tissues.Here we used cultured Drosophila cells, human colon cancer cells, and Drosophila embryos and larvae to explore the machinery that targets Armadillo for destruction. Using RNAi in Drosophila S2 cells to examine which SCF components are essential for Armadillo destruction, we find that Roc1/Roc1a is essential for regulating Armadillo stability, and that in these cells the only F-box protein playing a detectable role is Slimb. Second, we find that while embryonic and larval Drosophila tissues use the same destruction complex proteins, the response of these tissues to destruction complex inactivation differs, with Armadillo levels more elevated in embryos. We provide evidence consistent with the possibility that this is due to differences in armadillo mRNA levels. Third, we find that there is no correlation between the ability of different APC2 mutant proteins to negatively regulate Armadillo levels, and their recently described function in positively-regulating Wnt signaling. Finally, we demonstrate that APC proteins lacking the N-terminal Armadillo-repeat domain cannot restore Armadillo destruction but retain residual function in negatively-regulating Wnt signaling.We use these data to refine our model for how Wnt signaling is regulated during normal development

Bayesian Methods for Exoplanet Science

Exoplanet research is carried out at the limits of the capabilities of current telescopes and instruments. The studied signals are weak, and often embedded in complex systematics from instrumental, telluric, and astrophysical sources. Combining repeated observations of periodic events, simultaneous observations with multiple telescopes, different observation techniques, and existing information from theory and prior research can help to disentangle the systematics from the planetary signals, and offers synergistic advantages over analysing observations separately. Bayesian inference provides a self-consistent statistical framework that addresses both the necessity for complex systematics models, and the need to combine prior information and heterogeneous observations. This chapter offers a brief introduction to Bayesian inference in the context of exoplanet research, with focus on time series analysis, and finishes with an overview of a set of freely available programming libraries.Comment: Invited revie

Cloud feedbacks in extratopical cyclones: insight from long-term satellite data and high-resolution global simulations

A negative extratropical shortwave cloud feedback driven by changes in cloud optical depth is a feature of global climate models (GCMs). A robust positive trend in observed liquid water path (LWP) over the last two decades across the warming Southern Ocean supports the negative shortwave cloud feedback predicted by GCMs. This feature has been proposed to be due to transitions from ice to liquid with warming. To gain insight into the shortwave cloud feedback we examine extratropical cyclone variability and the response of extratropical cyclones to transient warming in GCM simulations. Multi-Sensor Advanced Climatology Liquid Water Path (MAC-LWP) microwave observations of cyclone properties from the period 1992–2015 are contrasted with GCM simulations, with horizontal resolutions ranging from 7 km to hundreds of kilometers. We find that inter-cyclone variability in LWP in both observations and models is strongly driven by the moisture flux along the cyclone's warm conveyor belt (WCB). Stronger WCB moisture flux enhances the LWP within cyclones. This relationship is replicated in GCMs, although its strength varies substantially across models. It is found that more than 80 % of the enhancement in Southern Hemisphere (SH) extratropical cyclone LWP in GCMs in response to a transient 4 K warming can be predicted based on the relationship between the WCB moisture flux and cyclone LWP in the historical climate and their change in moisture flux between the historical and warmed climates. Further, it is found that that the robust trend in cyclone LWP over the Southern Ocean in observations and GCMs is consistent with changes in the moisture flux. We propose two cloud feedbacks acting within extratropical cyclones: a negative feedback driven by Clausius–Clapeyron increasing water vapor path (WVP), which enhances the amount of water vapor available to be fluxed into the cyclone, and a feedback moderated by changes in the life cycle and vorticity of cyclones under warming, which changes the rate at which existing moisture is imported into the cyclone. Both terms contribute to increasing LWP within the cyclone. While changes in moisture flux predict cyclone LWP trends in the current climate and the majority of changes in LWP in transient warming simulations, a portion of the LWP increase in response to climate change that is unexplained by increasing moisture fluxes may be due to phase transitions. The variability in LWP within cyclone composites is examined to understand what cyclonic regimes the mixed-phase cloud feedback is relevant to. At a fixed WCB moisture flux cyclone LWP increases with increasing sea surface temperature (SST) in the half of the composite poleward of the low and decreases in the half equatorward of the low in both GCMs and observations. Cloud-top phase partitioning observed by the Atmospheric Infrared Sounder (AIRS) indicates that phase transitions may be driving increases in LWP in the poleward half of cyclones