Aerodynamic analysis of hypersonic waverider aircraft

The purpose of this study is to validate two existing codes used by the Systems Analysis Branch at NASA ARC, and to modify the codes so they can be used to generate and analyze waverider aircraft at on-design and off-design conditions. To generate waverider configurations and perform the on-design analysis, the appropriately named Waverider code is used. The Waverider code is based on the Taylor-Maccoll equations. Validation is accomplished via a comparison with previously published results. The Waverider code is modified to incorporate a fairing to close off the base area of the waverider configuration. This creates a more realistic waverider. The Hypersonic Aircraft Vehicle Optimization Code (HAVOC) is used to perform the off-design analysis of waverider configurations generated by the Waverider code. Various approximate analysis methods are used by HAVOC to predict the aerodynamic characteristics, which are validated via a comparison with experimental results from a hypersonic test model

Interview with Jo Pessin

Jo Pessin is a Filipina American who was born in Seattle, Washington. The youngest of four, her father migrated to the United States after joining the Navy and shortly after, her family moved to Oxnard, California, where she spent most of her life. She currently serves as the LA chapter lead of For Goodness Cakes, a non-profit organization that bakes birthday cakes for underprivileged youth and young adults. After the COVID-19 pandemic began, Pessin contributed to the supply van to Navajo Nation and joined the Auntie Sewing Squad. Shortly after, Pessin received a cancer diagnosis and found support in her community of Aunties. Today, Pessin still continues to make masks and provides support for the Auntie Sewing Squad.https://digitalcommons.csumb.edu/auntiesewing_interviews/1037/thumbnail.jp

Structural Health Monitoring of Composite Parts: A Review

Structural health monitoring has the potential to allow composite structures to be more reliable and safer, then by using more traditional damage assessment techniques. Structural health monitoring (SHM) utilizes individual sensor units that are placed throughout the load bearing sections of a structure and gather data that is used for stress analysis and damage detection. Statistical time based algorithms are used to analyze collected data and determine both damage size and probable location from within the structure. While traditional calculations and life span analysis can be done for structures made of isotropic materials such as steel or other metals, composites are highly orthotropic in nature. Composites must then be analyzed experimentally for more reliable results of the current damage state, or in-situ with SHM. Current research focuses on utilizing both piezoelectric sensor actuator pairs for damage detection, as well as fiber and particle based sensors for strain state awareness. While each method has its drawbacks due to incidental discontinuities reducing structural properties or difficulty in implementation and accuracy, SHM is vital for the successful wide spread implementation of composite structures. Piezoelectric based acousto-ultrasonic based sensor networks are ideal for damage detection and localization but are difficult to imbed within composites and can reduce their properties. Fiber and particle based strain sensors are ideal for detection of deformation and stress state, but are difficult to repair and to detect damage of the structure

A Descriptive Analysis of the Most Viewed YouTube Videos Related to Depression

Depression contributes to a host of health problems resulting in disability, pain, and death. An important aspect of preventing and reducing the harmful effects of depression is educating the public about this pervasive mental disorder, including the importance of early detection and effective treatment. During the past 20 years, many people have turned to the Internet in general and social media in particular to learn about health. Current research has examined YouTube coverage of some mental health topics, but no published research describing YouTube coverage of depression was identified. The purpose of this study was, therefore, to describe the most viewed YouTube about depression with respect to source, speaker, format, purpose, number of views, length, upload year, and content. A cross-sectional design was used to examine the 394 most viewed YouTube videos on depression. Collectively, these 394 videos were viewed 155,349,029 times. Three sources—consumers, internet-based video, and nongovernmental agencies—accounted for approximately 85% of the most frequently viewed videos and garnered 93% of the total views (n=144,506,467). Consumers uploaded almost half of all the most widely viewed videos (n=193, 48.98%), and these videos had the highest cumulative view count (74,391,500 views). Content mainly focused on signs and symptoms, which were covered in more than 75% of the videos (n=300, 76.14%), and promotion of healthful behaviors and protective factors, which was covered in 68.52% (n=270). Slightly more than one-half of the videos explicitly mentioned risk factors (n=200), and slightly less than one-half provided general information about depression (n=189). Between 20% and 35% of the videos included content related to suicide (23.10%), stigma (22.08%), psychotherapy (28.93%), medication (31.22%), and alternative therapies (30.96%). Content related to screening was only included in 9 of the most widely videos (2.28%). While good sleep hygiene was only mentioned in 28 videos (7.11%), collectively, these videos received over 16 million views. Another main finding was that governmental agencies have not produced videos that are among those most widely viewed. Given YouTube’s wide reach, they should, however, be using this media channel to help inform the public

Meaning in the noise: Neural signal variability in major depressive disorder

Clinical research has revealed aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions in major depressive disorder (MDD). Recent functional magnetic resonance imaging (fMRI) studies suggest that variability in brain activity, or blood oxygen level-dependent (BOLD) signal variability, may be an important novel predictor of psychopathology. However, to our knowledge, no studies have yet determined the relationship between resting-state BOLD signal variability and MDD nor applied BOLD signal variability features to the classification of MDD history using machine learning (ML). Thus, the current study had three aims: (i) to investigate the differences in the voxel-wise resting-state BOLD signal variability between varying depression histories; (ii) to examine the relationship between depressive symptom severity and resting-state BOLD signal variability; (iii) to explore the capability of resting-state BOLD signal variability to classify individuals by depression history. Using resting-state neuroimaging data for 79 women collected as a part of a larger NIH R01-funded study, we conducted (i) a one-way between-subjects ANCOVA, (ii) a multivariate multiple regression, and (iii) applied BOLD signal variability and average BOLD signal features to a supervised ML model. First, results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex in comparison to those with no depression history (pFWE \u3c .05). Second, and consistent with the results for depression history, depression severity was associated with reduced BOLD signal variability in the cerebellum. Lastly, a random forest model classified participant depression history with 76% accuracy, with BOLD signal variability features showing greater discriminative power than average BOLD signal features. These findings provide support for resting-state BOLD signal variability as a novel marker of neural dysfunction and implicate decreased neural signal variability as a neurobiological mechanism of depression

Atypical protein kinase C (PKCzeta/lambda) is a convergent downstream target of the insulin-stimulated phosphatidylinositol 3-kinase and TC10 signaling pathways.

Insulin stimulation of adipocytes resulted in the recruitment of atypical PKC (PKCzeta/lambda) to plasma membrane lipid raft microdomains. This redistribution of PKCzeta/lambda was prevented by Clostridium difficile toxin B and by cholesterol depletion, but was unaffected by inhibition of phosphatidylinositol (PI) 3-kinase activity. Expression of the constitutively active GTP-bound form of TC10 (TC10Q/75L), but not the inactive GDP-bound mutant (TC10/T31N), targeted PKCzeta/lambda to the plasma membrane through an indirect association with the Par6-Par3 protein complex. In parallel, insulin stimulation as well as TC10/Q75L resulted in the activation loop phosphorylation of PKCzeta. Although PI 3-kinase activation also resulted in PKCzeta/lambda phosphorylation, it was not recruited to the plasma membrane. Furthermore, insulin-induced GSK-3beta phosphorylation was mediated by both PI 3-kinase-PKB and the TC10-Par6-atypical PKC signaling pathways. Together, these data demonstrate that PKCzeta/lambda can serve as a convergent downstream target for both the PI 3-kinase and TC10 signaling pathways, but only the TC10 pathway induces a spatially restricted targeting to the plasma membrane

Qui produit la politique culturelle en matière de spectacles ? L’exemple de l’Ile de France ? (Avec Catherine Dutheil-Pessin)

article publié dans un cahier intitulé "Les Spectacles en Ile de France 2011/2012" et. publié par l'agence culturelle d'Ile de France ArcadiCe papier présente une des résultats de l'étude intitulée "la fabrique de la programmation culturelle" (financée par la région des Pays de la Loire, la ville de Nantes et le DEPS/Ministère de la Culture. À partir de données quantitatives, notamment d'une étude menée par l'agence culturelle d'Ile de France Arcadi, nous montrons qu'il est essentiel de prendre en compte l'apport des "petits" prograrmmateurs/trices de spectacles dans l'évaluation et la définition des politiques culturelles