Characterization of tandem aerosol classifiers for selecting particles: implication for eliminating multiple charging effect

Accurate particle classification plays a vital role in aerosol studies. Differential mobility analyzer (DMA), centrifugal particle mass analyzer (CPMA) and aerodynamic aerosol classifier (AAC) are commonly used to select particles with a specific size or mass. However, multiple charging effect cannot be entirely avoided either using individual technique or using tandem system such as DMA-CPMA, especially when selecting soot particles with fractal structures. In this study, we demonstrate the transfer functions of DMA-CPMA and DMA-AAC systems, as well as the potential multiple charging effect. Our results show that the ability to remove multiply charged particles mainly depends on particles morphology and instruments setups of DMA-CPMA system. Using measurements from soot experiments and literature data, a general trend in the appearance of multiple charging effect with decreasing size when selecting aspherical particles was observed. Otherwise, our results indicated that the ability of DMA-AAC to resolve particles with multiple charges is mainly related to the resolutions of classifiers. In most cases, DMA-AAC can eliminate multiple charging effect regardless of the particle morphology, while particles with multiple charges can be selected when decreasing resolutions of DMA and AAC. We propose that the multiple charging effect should be reconsidered when using DMA-CPMA or DMA-AAC system in estimating size and mass resolved optical properties in the field and lab experiments.

New results from testing relativistic gravity with radio pulsars

We experience a golden era in testing and exploring relativistic gravity. Whether it is results from gravitational-wave detectors, satellite or lab experiments, radio astronomy plays an important complementary role. Here, one can mention the cosmic microwave background, black hole imaging and, obviously, binary pulsars. This talk will concentrate on the latter and new results from studies of strongly self-gravitating bodies with unrivalled precision. This presentation compares the results to other methods, discusses implications for other areas of relativistic astrophysics and will give an outlook of what we can expect from new instruments in the near future.

Transient evolution of basal drag during glacier slip

Glacier slip is usually described using steady-state sliding laws that relate drag, slip velocity and effective pressure, but where subglacial conditions vary rapidly transient effects may influence slip dynamics. Here we use results from a set of laboratory experiments to examine the transient response of glacier slip over a hard bed to velocity perturbations. The drag and cavity evolution from lab experiments are used to parameterize a rate-and-state drag model that is applied to observations of surface velocity and ice-bed separation from the Greenland ice sheet. The drag model successfully predicts observed lags between changes in ice-bed separation and sliding speed. These lags result from the time (or displacement) required for cavities to evolve from one steady-state condition to another. In comparing drag estimates resulting from applying rate-and-state and steady-state slip laws to transient data, we find the peaks in drag are out of phase. This suggests that in locations where subglacial conditions vary on timescales shorter than those needed for cavity adjustment transient slip processes control basal drag.

Bioinformatics Storing Databases

An exceptional branch of data that requires huge databases has been shown lately from genome sequencing projects which is a field that employs computational approaches to answer biological questions. With this huge sequence of information that is available for researchers, bioinformatics plays a big role in studying basic medical-biological problems. The challenge that faces bioinformatical scientists is to help in discovering genes and designing molecular models, site-directed mutagenesis, and other experiments that reveal the unknown relationships concerning the structure and function of genes and proteins. This become a big challenge especially with the huge amount of data that is generated using the human genome and other systematic sequencing efforts up till now. Bioinformatics solves biological problems depending on available data. It is concerned with creating databases and predicting the outcome of lab experiments.

Improving replicability using interaction with laboratories: a multi-lab experimental assessment

Phenotyping inbred and genetically-engineered mouse lines has become a central strategy for discovering mammalian gene function and evaluating pharmacological treatment. Yet the utility of any findings critically depends on their replicability in other laboratories. In previous publications we proposed a statistical approach for estimating the inter-laboratory replicability of novel discoveries in a single laboratory, and demonstrated that previous phenotyping results from multi-lab databases can be used to derive a Genotype-by-Lab (GxL) adjustment factor to ensure the replicability of single-lab results, for similarly measured phenotypes, even before making the effort of replicating the new finding in additional laboratories.The demonstration above, however, still raised several important questions that could only be answered by an additional large-scale prospective experiment: Does GxL-adjustment works in single-lab experiments that were not intended to be standardized across laboratories? With genotypes that were not included in the previous experiments? And can it be used to adjust the results of pharmacological treatment experiments? We replicated results from five studies in the Mouse Phenome Database (MPD), in three behavioral tests, across three laboratories, offering 212 comparisons including 60 involving a pharmacological treatment: 18 mg/kg/day fluoxetine. In addition, we define and use a dimensionless GxL factor, derived from dividing the GxL variance by the standard deviation between animals within groups, as the more robust vehicle to transfer the adjustment from the multi-lab analysis to very different labs and genotypes.For genotype comparisons, GxL-adjustment reduced the rate of non-replicable discoveries from 60% to 12%, for the price of reducing the power to make replicable discoveries from 87% to 66%. Another way to look at these results is noting that the adjustment could have prevented 23 failures to replicate, for the price of missing only three replicated ones. The tools and data needed for deployment of this method across other mouse experiments are publicly available in the Mouse Phenome Database.Our results further point at some phenotypes as more prone to produce non-replicable results, while others, known to be more difficult to measure, are as likely to produce replicable results (once adjusted) as the physiological body weight is.

Online data collection to address language sampling bias: Lessons from the COVID-19 pandemic

The COVID-19 pandemic has massively limited how linguists can collect data, and out of necessity, researchers across several disciplines have moved data collection online. Here we argue that this rising popularity of remote web-based experiments also provides an opportunity for widening the context of linguistic research by facilitating data collection from understudied populations. We discuss collecting production data from adult native speakers of Tagalog using an unsupervised web-based experiment. Compared to equivalent lab experiments, data collection went quicker, and the sample was more diverse, without compromising data quality. However, there were also technical and human issues that come with this method. We discuss these challenges and provide suggestions on how to overcome them.

How statically-typed functional programmers write code

How working statically-typed functional programmers write code is largely understudied. And yet, a better understanding of developer practices could pave the way for the design of more useful and usable tooling, more ergonomic languages, and more effective on-ramps into programming communities. The goal of this work is to address this knowledge gap: to better understand the high-level authoring patterns that statically-typed functional programmers employ. We conducted a grounded theory analysis of 30 programming sessions of practicing statically-typed functional programmers, 15 of which also included a semi-structured interview. The theory we developed gives insight into how the specific affordances of statically-typed functional programming affect domain modeling, type construction, focusing techniques, exploratory and reasoning strategies, and expressions of intent. We conducted a set of quantitative lab experiments to validate our findings, including that statically-typed functional programmers often iterate between editing types and expressions, that they often run their compiler on code even when they know it will not successfully compile, and that they make textual program edits that reliably signal future edits that they intend to make. Lastly, we outline the implications of our findings for language and tool design. The success of this approach in revealing program authorship patterns suggests that the same methodology could be used to study other understudied programmer populations.