Perceptions from the highline

Perceptions from the Highline is a concerto for electric guitar and chamber ensemble. As a composer and a guitarist, I am constantly searching for new and compelling ways to compose for the electric guitar in conjunction with acoustic instruments. The time-based effect known as delay or echo is commonly utilized in the sonic milieu of the electric guitar. This paper will examine the process of scoring musical ideas generated by the use of electric guitar and delay for an acoustic chamber ensemble within the context of Perceptions from the Highline. Many of the electric guitar sounds utilizing delay were initially observed in the context of rock and popular music. This paper will briefly examine three examples of electric guitar playing featuring the use of delay that were influential to the composition of this piece. Analyzing these delay textures generates new models for scoring and orchestration, which in turn creates a series of ensemble-wide composite textures and melodic lines. Perceptions From the Highline is a one-movement concerto for electric guitar and chamber ensemble featuring electronic delay textures scored for acoustic instruments. The composition is the main focus of this thesis, while the accompanying paper further details the compositional process. The score for Perceptions From the Highline is presented in Appendix A

Comparing two evolutionary algorithm based methods for layout generation: Dense packing versus subdivision

We present and compare two evolutionary algorithm based methods for rectangular architectural layout generation: dense packing and subdivision algorithms. We analyze the characteristics of the two methods on the basis of three floor plan scenarios. Our analyses include the speed with which solutions are generated, the reliability with which optimal solutions can be found, and the number of different solutions that can be found overall. In a following step, we discuss the methods with respect to their different user interaction capabilities. In addition, we show that each method has the capability to generate more complex L-shaped layouts. Finally, we conclude that neither of the methods is superior but that each of them is suitable for use in distinct application scenarios because of its different propertie

Telling the Story of Stepfamily Beginnings: The Relationship between Young-adult Stepchildren’s Stepfamily Origin Stories and their Satisfaction with the Stepfamily

The current study adopts a narrative perspective in examining the content of 80 stepchildren’s stepfamily origin stories. Results reveal five types of stepfamily origin stories: Sudden, Dark-sided, Ambivalent, Idealized, and Incremental. Results support the hypothesis that story type would predict differences in family satisfaction; stepchildren who described their stepfamily origins as Idealized were more satisfied than those whose origins were Dark-sided or Sudden. Overall, participants framed their stepfamily identity more positively when their stepfamily beginnings were characterized by closeness, friendship, and even expected ups and downs, rather than when they were left out of the process of negotiating or forming the stepfamily and when the beginnings were tainted by issues they considered to be dark. Stepparents or practitioners may benefit from these findings by examining the means by which stepparents may involve stepchildren in the process of stepfamily courtship, facilitate closeness, and set up realistic expectations for negotiating stepfamily life

Machine Learning Facial Emotion Classifiers in Psychotherapy Research: A Proof-of-Concept Study.

BACKGROUND New advances in the field of machine learning make it possible to track facial emotional expression with high resolution, including micro-expressions. These advances have promising applications for psychotherapy research, since manual coding (e.g., the Facial Action Coding System), is time-consuming. PURPOSE We tested whether this technology can reliably identify in-session emotional expression in a naturalistic treatment setting, and how these measures relate to the outcome of psychotherapy. METHOD We applied a machine learning emotion classifier to video material from 389 psychotherapy sessions of 23 patients with borderline personality pathology. We validated the findings with human ratings according to the Clients Emotional Arousal Scale (CEAS) and explored associations with treatment outcomes. RESULTS Overall, machine learning ratings showed significant agreement with human ratings. Machine learning emotion classifiers, particularly the display of positive emotions (smiling and happiness), showed medium effect size on median-split treatment outcome (d = 0.3) as well as continuous improvement (r = 0.49, p < 0.05). Patients who dropped out form psychotherapy, showed significantly more neutral expressions, and generally less social smiling, particularly at the beginning of psychotherapeutic sessions. CONCLUSIONS Machine learning classifiers are a highly promising resource for research in psychotherapy. The results highlight differential associations of displayed positive and negative feelings with treatment outcomes. Machine learning emotion recognition may be used for the early identification of drop-out risks and clinically relevant interactions in psychotherapy

Shaping a mental health curriculum for Canada\u27s teacher education programs: Rationale and brief overview

It is a well-known and accepted statistic that one in five Canadian children will experience a significant mental health challenge prior to their 18th birthday; this is a conservative estimate given the many who suffer ‘under the radar’ with transient sadness, depression, and anxiety (Flett & Hewitt, 2013). And if we have yet to be sensitized to this critical period of childhood and adolescence, longitudinal studies indicate that 70% of adults who experience an emotional disorder report having their first onset episode prior to the age of 18 (Kessler et al., 2009)

Ten Simple Rules for Responsible Big Data Research

The use of big data research methods has grown tremendously over the past five years in both academia and industry. As the size and complexity of available datasets has grown, so too have the ethical questions raised by big data research. These questions become increasingly urgent as data and research agendas move well beyond those typical of the computational and natural sciences, to more directly address sensitive aspects of human behavior, interaction, and health. The tools of big data research are increasingly woven into our daily lives, including mining digital medical records for scientific and economic insights, mapping relationships via social media, capturing individuals’ speech and action via sensors, tracking movement across space, shaping police and security policy via “predictive policing,” and much more

A Pan-Carina YSO Catalog: Intermediate-Mass Young Stellar Objects in the Carina Nebula Identified Via Mid-Infrared Excess Emission

We present a catalog of 1439 young stellar objects (YSOs) spanning the 1.42 deg^2 field surveyed by the Chandra Carina Complex Project (CCCP), which includes the major ionizing clusters and the most active sites of ongoing star formation within the Great Nebula in Carina. Candidate YSOs were identified via infrared (IR) excess emission from dusty circumstellar disks and envelopes, using data from the Spitzer Space Telescope Vela--Carina survey and the Two-Micron All Sky Survey. We model the 1--24 /mu m IR spectral energy distributions of the YSOs to constrain physical properties. Our Pan-Carina YSO Catalog (PCYC) is dominated by intermediate-mass (2 Msun < m < 10 Msun) objects with disks, including Herbig Ae/Be stars and their less evolved progenitors. The PCYC provides a valuable complementary dataset to the CCCP X-ray source catalogs, identifying 1029 YSOs in Carina with no X-ray detection. We also catalog 410 YSOs with X-ray counterparts, including 62 candidate protostars. Candidate protostars with X-ray detections tend to be more evolved than those without. In most cases, X-ray emission apparently originating from intermediate-mass, disk-dominated YSOs is consistent with the presence of low-mass companions, but we also find that X-ray emission correlates with cooler stellar photospheres and higher disk masses. We suggest that intermediate-mass YSOs produce X-rays during their early pre-main sequence evolution, perhaps driven by magnetic dynamo activity during the convective atmosphere phase, but this emission dies off as the stars approach the main sequence. Extrapolating over the stellar initial mass function scaled to the PCYC population, we predict a total population of >2x10^4 YSOs and a present-day star formation rate (SFR) of >0.008 Msun/yr. The global SFR in the Carina Nebula, averaged over the past ~5 Myr, has been approximately constant.Comment: 23 pages, 11 figures, accepted for the ApJS Special Issue on the Chandra Carina Complex Project (CCCP), scheduled for publication in May 2011. All 16 CCCP Special Issue papers, including a version of this article with high-quality figures and full electronic tables, are available at http://cochise.astro.psu.edu/Carina_public/special_issue.html (through 2011 at least

Process Robustness in Lipid Nanoparticle Production: A Comparison of Microfluidic and Turbulent Jet Mixing

The recent clinical and commercial success of lipid nanoparticles (LNPs) for nucleic acid delivery has incentivized the development of new technologies to manufacture LNPs. As new technologies emerge, researchers must determine which technologies to assess and how to perform comparative evaluations. In this article, we use a quality-by-design approach to systematically investigate how the mixer technology used to form LNPs influences LNPstructure. Specifically, a coaxial turbulent jet mixer and a staggered herringbone microfluidic mixer were systematically compared via matched formulation and process conditions. A full-factorial design-of-experiments study with three factors and three levels was executed for each mixer to compare process robustness in the production of antisense oligonucleotide (ASO) LNPs. ASO-LNPs generated with the coaxial turbulent jet mixer were consistently smaller, had a narrower particle size distribution, and had a higher ASO encapsulation as compared to the microfluidic mixer, but had a greater variation in internal structure with less ordered cores. A subset of the study was replicated for mRNA-LNPs with comparable trends in particle size and encapsulation, but more frequent bleb features for LNPs produced by the coaxial turbulent jet mixer. The study design used here provides a road map for how researchers may compare different mixer technologies (or process changes more broadly) and how such studies can inform process robustness and manufacturing control strategies

Resource partitioning by insectivorous bats in Jamaica

In this investigation, we use variation in wing morphology, echolocation behaviour, patterns of habitat use and molecular diet analysis to demonstrate that six species of sympatric insectivorous bats in Jamaica show significant differences that could explain resource partitioning among the species. High-intensity echolocating species that used shorter, broadband signals and had shorter, broader wings (Pteronotus macleayii, Pteronotus quadridens, Mormoops blainvillii) foraged most in edge habitats, but differed in timing of peak activity. P. macleayii and M. blainvillii differed in diet, but low sample size precluded diet analysis for P. quadridens. High-intensity echolocating species that used longer, more narrowband signals and had longer, narrower wings (Molossus molossus, Tadarida brasiliensis) foraged most in open areas and differed in diet from the other species. Two disparate species were most active in clutter (dense vegetation). Pteronotus parnellii used high-duty-cycle echolocation apparently specialized for detecting fluttering targets in clutter. Macrotus waterhousii used low-intensity, broadband echolocation calls and presumably uses prey-generated sounds when foraging. These two species also differed in diet. Our data show that differences in morphology and echolocation behaviour coincide with differences in habitat use and diet, resulting in minimal overlap in resource use among species