The moderating effect of gender on ideal-weight goals and exercise dependence symptoms

Background and aims: Exercise dependence is implicated in the development of eating disorders and muscle dysmorphic disorder. Although conceptually these disorders represent similar pathologies they largely affect different genders and result in opposite body composition, appearance, and ideal-weight goals (i.e., to gain or lose/maintain weight). Therefore, understanding individuals' ideal-weight goals related to engaging in exercise while simultaneously examining gender differences in exercise dependence symptoms may help to identify those whom may be most at-risk for eating disorders and muscle dysmorphic disorder. The purpose of our study was to examine the moderating effect of gender for exercise dependence symptoms in relation to weight gain, loss, or maintenance goals. Methods: Self-reported exercise behavior and exercise dependence symptoms (i.e., Exercise Dependence Scale) were assessed in 513 undergraduate students. Results: Our analysis revealed a moderating effect for gender on ideal-weight goals and a gender difference in exercise dependence symptoms. Specifically, men who were dissatisfied with their current weight reported more exercise dependence symptoms than women. Conclusions: These results support a growing body of research and extend our understanding of the relationships among exercise dependence and gender specific body-focused psychiatric disorders

Dynamic Behavioral Mixed-Membership Model for Large Evolving Networks

The majority of real-world networks are dynamic and extremely large (e.g., Internet Traffic, Twitter, Facebook, ...). To understand the structural behavior of nodes in these large dynamic networks, it may be necessary to model the dynamics of behavioral roles representing the main connectivity patterns over time. In this paper, we propose a dynamic behavioral mixed-membership model (DBMM) that captures the roles of nodes in the graph and how they evolve over time. Unlike other node-centric models, our model is scalable for analyzing large dynamic networks. In addition, DBMM is flexible, parameter-free, has no functional form or parameterization, and is interpretable (identifies explainable patterns). The performance results indicate our approach can be applied to very large networks while the experimental results show that our model uncovers interesting patterns underlying the dynamics of these networks

Automated Determination of [Fe/H] and [C/Fe] from Low-Resolution Spectroscopy

We develop an automated spectral synthesis technique for the estimation of metallicities ([Fe/H]) and carbon abundances ([C/Fe]) for metal-poor stars, including carbon-enhanced metal-poor stars, for which other methods may prove insufficient. This technique, autoMOOG, is designed to operate on relatively strong features visible in even low- to medium-resolution spectra, yielding results comparable to much more telescope-intensive high-resolution studies. We validate this method by comparison with 913 stars which have existing high-resolution and low- to medium-resolution to medium-resolution spectra, and that cover a wide range of stellar parameters. We find that at low metallicities ([Fe/H] < -2.0), we successfully recover both the metallicity and carbon abundance, where possible, with an accuracy of ~ 0.20 dex. At higher metallicities, due to issues of continuum placement in spectral normalization done prior to the running of autoMOOG, a general underestimate of the overall metallicity of a star is seen, although the carbon abundance is still successfully recovered. As a result, this method is only recommended for use on samples of stars of known sufficiently low metallicity. For these low-metallicity stars, however, autoMOOG performs much more consistently and quickly than similar, existing techniques, which should allow for analyses of large samples of metal-poor stars in the near future. Steps to improve and correct the continuum placement difficulties are being pursued.Comment: 8 pages, 7 figures; accepted for publication in A

The Aes protein and the monomeric alpha-galactosidase from Escherichia coli form a non-covalent complex. Implications for the regulation of carbohydrate metabolism.

Aes, a 36-kDa acetylesterase fromEscherichia coli, belongs to the hormone-sensitive lipase family, and it is involved in the regulation of MalT, the transcriptional activator of the maltose regulon. The activity of MalT is depressed through a direct protein-protein interaction with Aes. Although the effect is clear-cut, the meaning of this interaction and the conditions that trigger it still remain elusive. To perform a comparative thermodynamic study between the mesophilic Aes protein and two homologous thermostable enzymes, Aes was overexpressed in E. coli and purified. At the last step of the purification procedure the enzyme was eluted from a Mono Q HR 5/5 column as a major form migrating, anomalously, at 56 kDa on a calibrated Superdex 75 column. A minor peak that contains the Aes protein and a polypeptide of 50 kDa was also detected. By a combined analysis of size-exclusion chromatography and surface-enhanced laser desorption ionization-time of flight mass spectrometry, it was possible to demonstrate the presence in this peak of a stable 87-kDa complex, containing the Aes protein itself and the 50-kDa polypeptide in a 1:1 ratio. The homodimeric molecular species of Aes and of the 50-kDa polypeptide were also detected. The esterase activity associated with the 87-kDa complex, when assayed with p-nitrophenyl butanoate as substrate, proved 6-fold higher than the activity of the major Aes form of 56 kDa. Amino-terminal sequencing highlighted that the 50-kDa partner of Aes in the complex was the α-galactosidase from E. coli. TheE. coli cells harboring plasmid pT7-SCII-aesand, therefore, expressing Aes were hampered in their growth on a minimal medium containing raffinose as a sole carbon source. Because α-galactosidase is involved in the metabolism of raffinose, the above findings suggest a potential role of Aes in the regulation of carbohydrate metabolism in E. coli

Near-Infrared Spectroscopy of Carbon-Enhanced Metal-Poor Stars. I. A SOAR/OSIRIS Pilot Study

We report on an abundance analysis for a pilot study of seven Carbon-Enhanced Metal-Poor (CEMP) stars, based on medium-resolution optical and near-infrared spectroscopy. The optical spectra are used to estimate [Fe/H], [C/Fe], [N/Fe], and [Ba/Fe] for our program stars. The near-infrared spectra, obtained during a limited early science run with the new SOAR 4.1m telescope and the Ohio State Infrared Imager and Spectrograph (OSIRIS), are used to obtain estimates of [O/Fe] and 12C/13C. The chemical abundances of CEMP stars are of importance for understanding the origin of CNO in the early Galaxy, as well as for placing constraints on the operation of the astrophysical s-process in very low-metallicity Asymptotic Giant Branch (AGB) stars. This pilot study includes a few stars with previously measured [Fe/H], [C/Fe], [N/Fe],[O/Fe], 12C/13C, and [Ba/Fe], based on high-resolution optical spectra obtained with large-aperture telescopes. Our analysis demonstrates that we are able to achieve reasonably accurate determinations of these quantities for CEMP stars from moderate-resolution optical and near-infrared spectra. This opens the pathway for the study of significantly larger samples of CEMP stars in the near future. Furthermore, the ability to measure [Ba/Fe] for (at least the cooler) CEMP stars should enable one to separate stars that are likely to be associated with s-process enhancements (the CEMP-s stars) from those that do not exhibit neutron-capture enhancements (the CEMP-no stars).Comment: 27 pages, including 5 tables, 6 figures, accepted for publication in The Astronomical Journa

Randomized sham-controlled trial of repetitive transcranial magnetic stimulation in treatment-resistant obsessive–compulsive disorder

In open trials, 1-Hz repetitive transcranial magnetic stimulation (rTMS) to the supplementary motor area (SMA) improved symptoms and normalized cortical hyper-excitability of patients with obsessive–compulsive disorder (OCD). Here we present the results of a randomized sham-controlled double-blind study. Medication-resistant OCD patients (n=21) were assigned 4 wk either active or sham rTMS to the SMA bilaterally. rTMS parameters consisted of 1200 pulses/d, at 1 Hz and 100% of motor threshold (MT). Eighteen patients completed the study. Response to treatment was defined as a ≽25% decrease on the Yale–Brown Obsessive Compulsive Scale (YBOCS). Non-responders to sham and responders to active or sham rTMS were offered four additional weeks of open active rTMS. After 4 wk, the response rate in the completer sample was 67% (6/9) with active and 22% (2/9) with sham rTMS. At 4 wk, patients receiving active rTMS showed on average a 25% reduction in the YBOCS compared to a 12% reduction in those receiving sham. In those who received 8-wk active rTMS, OCD symptoms improved from 28.2±5.8 to 14.5±3.6. In patients randomized to active rTMS, MT measures on the right hemisphere increased significantly over time. At the end of 4-wk rTMS the abnormal hemispheric laterality found in the group randomized to active rTMS normalized. The results of the first randomized sham-controlled trial of SMA stimulation in the treatment of resistant OCD support further investigation into the potential therapeutic applications of rTMS in this disabling condition

Digitalizing Art: Transforming Marketing Efforts

This research is part of a semester-long project where the undergraduate Business students from Molloy College pitch their business and marketing recommendations to a local non-profit. The theme emerges from a pedagogical philosophy that it is essential to learn the significance that business has upon society while working with a neighborhood non-profit. For example, having students enter into the business world where profit is a healthy by-product and is not the main focus toward today’s career development is critical in developing tomorrow’s ethical and social leaders. The learning activity leading to this learning outcome requires the undergraduate business students to experience this type of real-world project. The students are presented with an opportunity to study the most prevalent issues their assigned non-profit is facing and they are to collectively make a set of solution-driven recommendations that will ultimately lead to social good

mPlane: an intelligent measurement plane for the internet

The Internet's universality is based on its decentralization and diversity. However, its distributed nature leads to operational brittleness and difficulty in identifying the root causes of performance and availability issues, especially when the involved systems span multiple administrative domains. The first step to address this fragmentation is coordinated measurement: we propose to complement the current Internet's data and control planes with a measurement plane, or mPlane for short. mPlane's distributed measurement infrastructure collects and analyzes traffic measurements at a wide variety of scales to monitor the network status. Its architecture is centered on a flexible control interface, allowing the incorporation of existing measurement tools through lightweight mPlane proxy components, and offering dynamic support for new capabilities. A focus on automated, iterative measurement makes the platform well-suited to troubleshooting support. This is supported by a reasoning system, which applies machine learning algorithms to learn from success and failure in drilling down to the root cause of a problem. This article describes the mPlane architecture and shows its applicability to several distributed measurement problems involving content delivery networks and Internet service roviders. A first case study presents the tracking and iterative analysis of cache selection policies in Akamai, while a second example focuses on the cooperation between Internet service providers and content delivery networks to better orchestrate their traffic engineering decisions and jointly improve their performance