Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
6,140
result(s) for
"Conrad, J"
Sort by:
Exploring space
\"Simple text and full-color photos present information about the past and future of space exploration\"--Provided by publisher.
Book
Recommended conventions for reporting results from direct dark matter searches
The field of dark matter detection is a highly visible and highly competitive one. In this paper, we propose recommendations for presenting dark matter direct detection results particularly suited for weak-scale dark matter searches, although we believe the spirit of the recommendations can apply more broadly to searches for other dark matter candidates, such as very light dark matter or axions. To translate experimental data into a final published result, direct detection collaborations must make a series of choices in their analysis, ranging from how to model astrophysical parameters to how to make statistical inferences based on observed data. While many collaborations follow a standard set of recommendations in some areas, for example the expected flux of dark matter particles (to a large degree based on a paper from Lewin and Smith in 1995), in other areas, particularly in statistical inference, they have taken different approaches, often from result to result by the same collaboration. We set out a number of recommendations on how to apply the now commonly used Profile Likelihood Ratio method to direct detection data. In addition, updated recommendations for the Standard Halo Model astrophysical parameters and relevant neutrino fluxes are provided. The authors of this note include members of the DAMIC, DarkSide, DARWIN, DEAP, LZ, NEWS-G, PandaX, PICO, SBC, SENSEI, SuperCDMS, and XENON collaborations, and these collaborations provided input to the recommendations laid out here. Wide-spread adoption of these recommendations will make it easier to compare and combine future dark matter results.
Journal Article
Engaging the online learner, updated : activities and resources for creative instruction
\"This is a revision of the first title in Jossey-Bass' Online Teaching & Learning series. This series helps higher education professionals improve the practice of online teaching and learning by providing concise, practical resources focused on particular areas or issues they might confront in this new learning environment. This revision includes updated activities and resources for instructors teaching online. Based on changes in technology and best practices learned from the field the revision provides new information for even seasoned online instructors.\" -- Provided by publisher.
Book
Machine learning in medicine: a practical introduction to natural language processing
Background
Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of written text into interpretable datasets that can be analysed by statistical and machine learning (ML) models. The purpose of this paper is to provide a practical introduction to contemporary techniques for the analysis of text-data, using freely-available software.
Methods
We performed three NLP experiments using publicly-available data obtained from medicine review websites. First, we conducted lexicon-based sentiment analysis on open-text patient reviews of four drugs: Levothyroxine, Viagra, Oseltamivir and Apixaban. Next, we used unsupervised ML (latent Dirichlet allocation, LDA) to identify similar drugs in the dataset, based solely on their reviews. Finally, we developed three supervised ML algorithms to predict whether a drug review was associated with a positive or negative rating. These algorithms were: a regularised logistic regression, a support vector machine (SVM), and an artificial neural network (ANN). We compared the performance of these algorithms in terms of classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity and specificity.
Results
Levothyroxine and Viagra were reviewed with a higher proportion of positive sentiments than Oseltamivir and Apixaban. One of the three LDA clusters clearly represented drugs used to treat mental health problems. A common theme suggested by this cluster was drugs taking weeks or months to work. Another cluster clearly represented drugs used as contraceptives. Supervised machine learning algorithms predicted positive or negative drug ratings with classification accuracies ranging from 0.664, 95% CI [0.608, 0.716] for the regularised regression to 0.720, 95% CI [0.664,0.776] for the SVM.
Conclusions
In this paper, we present a conceptual overview of common techniques used to analyse large volumes of text, and provide reproducible code that can be readily applied to other research studies using open-source software.
Journal Article
Baseline filtering and peak reconstruction for haloscope-like axion searches
A
bstract
Axions are well-motivated dark matter particles. Many experiments are looking for their experimental evidence. For haloscopes, the problem reduces to the identification of a peak above a noisy baseline. Its modeling, however, may be problematic. State-of-the-art analyses rely on the Savitzky-Golay (SG) filtering, which is intrinsically affected by any possible over fluctuation, leading to biased results. In this paper we study the efficiency that different extensions of SG can provide in the peak reconstruction in a standard haloscope-like experiment. We show that, once the correlations among bins are taken into account, there is no appreciable difference. The standard SG remains the advisable choice because of its numerical efficiency.
Journal Article
Constraining Characteristic Morphological Wavelengths for Venus Using Baltis Vallis
One of Venus' most enigmatic landforms is Baltis Vallis, the longest channel on the surface (∼7,000 km long). We identify a possible mid‐channel island that implies a south to north flow direction during formation. However, since the flow direction of Baltis Vallis is otherwise not well constrained, we analyze topographic conformity in both flow directions. In either case, topography appears to be altered across most analyzed wavelengths after the formation of Baltis Vallis. Fourier analysis shows two ranges of prominent wavelengths, 225 ± 15 km and ∼3,500 ± 1,200 km. The shorter wavelengths correspond to deformation belts that cross Venus' low plains. The longest is plausibly associated with the dynamic uplift wavelength of the crust by mantle plumes, but is less robustly detected. Higher resolution observations provided by the VERITAS and EnVision missions can help resolve the source location of Baltis Vallis and constrain if the longest wavelength postdated the canale's formation.
Plain Language Summary
Venus' surface is covered in a plethora of strange landforms, at least from the perspective of Earth. One of the longest is an about 7,000 km channel named Baltis Vallis, comparable to the Amazon and Nile rivers, but instead likely formed by volcanic processes. Baltis Vallis serves as a unique opportunity on Venus due to its length. The channel recorded surface altering processes in its topography, but we first check if the channel retained topographic information from when it initially formed. Our test shows that the topography has been altered by later processes and those processes should dominate the signal in analysis of the current topography. That analysis shows 2 length‐scales are overrepresented in the topography. The shorter length‐scale correspond to thin mountain range‐like features that cross Venus' low plains. The longest wavelength is plausibly associated with uplift of the crust by mantle plumes and this value will be useful when creating models of Venus' interior.
Key Points
A possible mid‐channel island in the longest channel on Venus implies a south to north flow direction
We show that the topography and morphology of this channel was modified along most of its length
Fourier analysis of the channel's topography shows a group of prominent wavelengths at ∼210–240 km, that we link to deformation belts
Journal Article
Britannica's encyclopedia infographica : 1,000s of facts & figures : about Earth, space, animals, the body, technology, & more : revealed in pictures
\"This authoritative encyclopedia is perfect for visual learners: it reveals astonishing information about space, Earth, animals, humans and technology through 200 infographics, including maps, charts, timelines and more! Grasp facts at a glance as you turn every page: discover the size of our Sun in comparison to the largest star in the universe; find out which animal can leap 200 times its body length; learn how many cups of snot your body makes a day; compare the sizes of the biggest beasts that have ever lived; witness what happens in a single second across the world\"--Provided by publisher.
Book
A Framework for Resolving Cryptic Species
As we collect range-wide genetic data for morphologically-defined species, we increasingly unearth evidence for cryptic diversity. Delimiting this cryptic diversity is challenging, both because the divergences span a continuum and because the lack of overt morphological differentiation suggests divergence has proceeded heterogeneously. Herein, we address these challenges as we diagnose and describe species in three co-occurring species groups of Australian lizards. By integrating genomic and morphological data with data on hybridization and introgression from contact zones, we explore several approaches—and their relative benefits and weaknesses—for testing the validity of cryptic lineages. More generally, we advocate that genetic delimitations of cryptic diversity must consider whether these lineages are likely to be durable and persistent through evolutionary time.
Journal Article