115 research outputs found

    Composing with Sounds: Designing an Object-Oriented DAW for the Teaching of Sound-Based Composition

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    This paper presents and discusses the ComposeWith Sounds (CwS) Digital AudioWorkstation (DAW) and its approach to sequencing musical materials. The system is designed to facilitate the composition within the realm of Sound-based music wherein sound objects (real or synthesised) are main musical unit of construction over traditional musical notes. Unlike traditional DAW’s or graphical audio programming environments (such as Pure Data, Max MSP etc.) that are based around interactions with sonic materials within tracks or audio graphs, the implementation presented here is based solely around sound objects. To achieve this a bespoke cross-platform audio engine known FSOM (Free Sound Object Mixer) was created in C++. To enhance the learning experience, imagery, dynamic 3D animations and models are used to allow for efficient exploration and learning. All tools within the system are controlled by a flexible permissions system that allows users or workshop leaders to create sessions with specific features based on their requirements. The system is part of a suite of pedagogical tools currently in development for the creation of experimental electronic music

    The Luminosity Function of Galaxies in the Las Campanas Redshift Survey

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    We present the RR-band luminosity function for a sample of 18678 galaxies, with average redshift z=0.1z = 0.1, from the Las Campanas Redshift Survey. The luminosity function may be fit by a Schechter function with M=20.29±0.02+5loghM^* = -20.29 \pm 0.02 + 5 \log h, α=0.70±0.05\alpha = -0.70 \pm 0.05, and $\phi^* = 0.019 \pm 0.001 \ h^3 Mpc~Mpc^{-3},forabsolutemagnitudes, for absolute magnitudes -23.0 \leq M - 5 \log h \leq -17.5.Wecompareourluminosityfunctiontothatfromotherredshiftsurveys;inparticularournormalizationisconsistentwiththatoftheStromloAPMsurvey,andisthereforeafactoroftwobelowthatimpliedbythe. We compare our luminosity function to that from other redshift surveys; in particular our normalization is consistent with that of the Stromlo-APM survey, and is therefore a factor of two below that implied by the b_J \approx 20brightgalaxycounts.Ournormalizationthusindicatesthatmuchmoreevolutionisneededtomatchthefaintgalaxycountdata,comparedtominimalevolutionmodelswhichnormalizeat bright galaxy counts. Our normalization thus indicates that much more evolution is needed to match the faint galaxy count data, compared to minimal evolution models which normalize at b_J \approx 20.Also,weshowthatourfaintendslope. Also, we show that our faint-end slope \alpha = -0.7,thoughshallowerthantypicalpreviousvalues, though ``shallower'' than typical previous values \alpha = -1,resultsprimarilyfromfittingthedetailedshapeoftheLCRSluminosityfunction,ratherthanfromanyabsenceofintrinsicallyfaintgalaxiesfromoursurvey.Finally,using[OII]3727equivalentwidth, results primarily from fitting the detailed shape of the LCRS luminosity function, rather than from any absence of intrinsically faint galaxies from our survey. Finally, using [OII] 3727 equivalent width W_{\lambda} = 5 A˚ asthedividingline,wefindsignificantdifferencesintheluminosityfunctionsofemissionandnonemissiongalaxies,particularlyintheir~\AA \ as the dividing line, we find significant differences in the luminosity functions of emission and non-emission galaxies, particularly in their \alphavalues.EmissiongalaxieshaveSchechterparameters values. Emission galaxies have Schechter parameters M^* = -20.03 \pm 0.03 + 5 \log hand and \alpha = -0.9 \pm 0.1,whilenonemissiongalaxiesaredescribedby, while non-emission galaxies are described by M^* = -20.22 \pm 0.02 + 5 \log hand and \alpha = -0.3 \pm 0.1$. (abridged abstract)Comment: 41 pages, including 13 postscript figures, uses AASTEX v4.0 style files. Important clarification of R-band definition, plus correction of luminosity densities and updated references. Main conclusions unchanged. Final version to appear in Ap

    Increasing Multiyear Sea Ice Loss in the Beaufort Sea: A New Export Pathway for the Diminishing Multiyear Ice Cover of the Arctic Ocean

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    Historically, multiyear sea ice (MYI) covered a majority of the Arctic and circulated through the Beaufort Gyre for years. However, increased ice melt in the Beaufort Sea during the early 2000s was proposed to have severed this circulation. Constructing a regional MYI budget from 1997 to 2021 reveals that MYI import into the Beaufort Sea has increased year-round, yet less MYI now survives through summer and is transported onwards in the Gyre. Annual average MYI loss quadrupled over the study period and increased from ∼7% to ∼33% of annual Fram Strait MYI export, while the peak in 2018 (385,000 km2) was similar in magnitude to Fram Strait MYI export. The ice-albedo feedback coupled with the transition toward younger thinner MYI is responsible for the increased MYI loss. MYI transport through the Beaufort Gyre has not been severed, but it has been reduced so severely to prevent it from being redistributed throughout the Arctic Ocean

    Loose Groups of Galaxies in the Las Campanas Redshift Survey

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    A ``friends-of-friends'' percolation algorithm has been used to extract a catalogue of dn/n = 80 density enhancements (groups) from the six slices of the Las Campanas Redshift Survey (LCRS). The full catalogue contains 1495 groups and includes 35% of the LCRS galaxy sample. A clean sample of 394 groups has been derived by culling groups from the full sample which either are too close to a slice edge, have a crossing time greater than a Hubble time, have a corrected velocity dispersion of zero, or contain a 55-arcsec ``orphan'' (a galaxy with a mock redshift which was excluded from the original LCRS redshift catalogue due to its proximity to another galaxy -- i.e., within 55 arcsec). Median properties derived from the clean sample include: line-of-sight velocity dispersion sigma_los = 164km/s, crossing time t_cr = 0.10/H_0, harmonic radius R_h = 0.58/h Mpc, pairwise separation R_p = 0.64/h Mpc, virial mass M_vir = (1.90x10^13)/h M_sun, total group R-band luminosity L_tot = (1.30x10^11)/h^2 L_sun, and R-band mass-to-light ratio M/L = 171h M_sun/L_sun; the median number of observed members in a group is 3.Comment: 32 pages of text, 27 figures, 7 tables. Figures 1, 4, 6, 7, and 8 are in gif format. Tables 1 and 3 are in plain ASCII format (in paper source) and are also available at http://www-sdss.fnal.gov:8000/~dtucker/LCLG . Accepted for publication in the September 2000 issue of ApJ

    Willingness to Use a Wearable Device Capable of Detecting and Reversing Overdose Among People Who Use Opioids in Philadelphia

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    Background: The incidence of opioid-related overdose deaths has been rising for 30 years and has been further exacerbated amidst the COVID-19 pandemic. Naloxone can reverse opioid overdose, lower death rates, and enable a transition to medication for opioid use disorder. Though current formulations for community use of naloxone have been shown to be safe and effective public health interventions, they rely on bystander presence. We sought to understand the preferences and minimum necessary conditions for wearing a device capable of sensing and reversing opioid overdose among people who regularly use opioids. Methods: We conducted a combined cross-sectional survey and semi-structured interview at a respite center, shelter, and syringe exchange drop-in program in Philadelphia, Pennsylvania, USA during the COVID-19 pandemic in August and September 2020. The primary aim was to explore the proportion of participants who would use a wearable device to detect and reverse overdose. Preferences regarding designs and functionalities were collected via a questionnaire with items having Likert-based response options and a semi-structured interview intended to elicit feedback on prototype designs. Independent variables included demographics, opioid use habits, and previous experience with overdose. Results: A total of 97 adults with an opioid-use history of at least 3 months were interviewed. A majority of survey participants (76%) reported a willingness to use a device capable of detecting an overdose and automatically administering a reversal agent upon initial survey. When reflecting on the prototype, most respondents (75.5%) reported that they would wear the device always or most of the time. Respondents indicated discreetness and comfort as important factors that increased their chance of uptake. Respondents suggested that people experiencing homelessness and those with low tolerance for opioids would be in greatest need of the device. Conclusions: The majority of people sampled with a history of opioid use in an urban setting were interested in having access to a device capable of detecting and reversing an opioid overdose. Participants emphasized privacy and comfort as the most important factors influencing their willingness to use such a device. Trial Registration: NCT0453059
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