Fashion Conversation Data on Instagram

The fashion industry is establishing its presence on a number of visual-centric social media like Instagram. This creates an interesting clash as fashion brands that have traditionally practiced highly creative and editorialized image marketing now have to engage with people on the platform that epitomizes impromptu, realtime conversation. What kinds of fashion images do brands and individuals share and what are the types of visual features that attract likes and comments? In this research, we take both quantitative and qualitative approaches to answer these questions. We analyze visual features of fashion posts first via manual tagging and then via training on convolutional neural networks. The classified images were examined across four types of fashion brands: mega couture, small couture, designers, and high street. We find that while product-only images make up the majority of fashion conversation in terms of volume, body snaps and face images that portray fashion items more naturally tend to receive a larger number of likes and comments by the audience. Our findings bring insights into building an automated tool for classifying or generating influential fashion information. We make our novel dataset of {24,752} labeled images on fashion conversations, containing visual and textual cues, available for the research community.Comment: 10 pages, 6 figures, This paper will be presented at ICWSM'1

Computational analysis of expressed sequence tags for understanding gene regulation.

High-throughput sequencing has provided a myriad of genetic data for thousands of organisms. Computational analysis of one data type, expressed sequence tags (ESTs) yields insight into gene expression, alternative splicing, tissue specificity gene functionality and the detection and differentiation of pseudogenes. Two computational methods have been developed to analyze alternative splicing events and to detect and characterize pseudogenes using ESTs. A case study of rat phosphodiesterase 4 (PDE4) genes yielded more than twenty-five previously unreported isoforms. These were experimentally verified through wet lab collaboration and found to be tissue specific. In addition, thirteen cytochrome-like gene and pseudogene sequences from the human genome were analyzed for pseudogene properties. Of the thirteen sequences, one was identified as the actual cytochrome gene, two were found to be non-cytochrome-related sequences, and eight were determined to be pseudogenes. The remaining two sequences were identified to be duplicates. As a precursor to applying the two new methods, the efficiency of three BLAST algorithms (NCBI BLAST, WU BLAST and mpiBLAST) were examined for comparing large numbers of short sequences (ESTs) to fewer large sequences (genomic regions). In general, WU BLAST was found to be the most efficient sequence comparison tool. These approaches illustrate the power of ESTs in understanding gene expression. Efficient computational analysis of ESTs (such as the two tools described) will be vital to understanding the complexity of gene expression as more high-throughput EST data is made available via advances in molecular sequencing technologies, such as the current next-generation approaches

The Distance to the Vela Supernova Remnant

We have obtained high resolution Ca II and Na I absorption line spectra toward 68 OB stars in the direction of the Vela Supernova Remnant. The stars lie at distances of 190 -- 2800 pc as determined by Hipparcos and spectroscopic parallax estimations. The presence of high velocity absorption attributable to the remnant along some of the sight lines constrains the remnant distance to 250+/-30 pc. This distance is consistent with several recent investigations that suggest that the canonical remnant distance of 500 pc is too large.Comment: To be published in The Astrophysical Journal Letters Figure 1 y-axis labels correcte

SciRecSys: A Recommendation System for Scientific Publication by Discovering Keyword Relationships

In this work, we propose a new approach for discovering various relationships among keywords over the scientific publications based on a Markov Chain model. It is an important problem since keywords are the basic elements for representing abstract objects such as documents, user profiles, topics and many things else. Our model is very effective since it combines four important factors in scientific publications: content, publicity, impact and randomness. Particularly, a recommendation system (called SciRecSys) has been presented to support users to efficiently find out relevant articles

Localized ferromagnetic resonance force microscopy in permalloy-cobalt films

We report Ferromagnetic Resonance Force Microscopy (FMRFM) experiments on a justaposed continuous films of permalloy and cobalt. Our studies demonstrate the capability of FMRFM to perform local spectroscopy of different ferromagnetic materials. Theoretical analysis of the uniform resonance mode near the edge of the film agrees quantitatively with experimental data. Our experiments demonstrate the micron scale lateral resolution in determining local magnetic properties in continuous ferromagnetic samples.Comment: 7 pages, 3 figure

The Medium and the Backlash: The Disparagement of the #MeToo Movement in Online Public Discourse in South Korea

This study examines the #MeToo movement in South Korea to understand the role of online platforms in the development of a backlash discourse. We apply computational methods to analyze how the #MeToo movement was discussed by citizens on Twitter and in online news comments, in contrast to the traditional news media. Our findings show that the public discourse in user-driven online platforms enabled the proliferation of a disparaging narrative that challenged the movement, while the patterns of the backlash differed across platforms. Using word-embedding techniques and network analyses, we illustrate the shift in frames around #MeToo movement and highlight how platform affordances meaningfully shaped the way the backlash unfolded

Presence of \u3cem\u3ePorphyromonas gingivalis\u3c/em\u3e in gingival squamous cell carcinoma

Periodontal disease has been recently linked to a variety of systemic conditions such as diabetes, cardiovascular disease, preterm delivery, and oral cancer. The most common bacteria associated with periodontal disease, Porphyromonas gingivalis (P. gingivalis) has not yet been studied in the malignant gingival tissues. The objective of this study was to investigate the presence of P. gingivalis in specimens from squamous cell carcinoma patients. We have performed immunohistochemical staining to investigate the presence of P. gingivalis and Streptococcus gordonii (S. gordonii), a non invasive oral bacteria, in paraffin embedded samples of gingival squamous cell carcinoma (n=10) and normal gingiva (n=5). Staining for P. gingivalis revealed the presence of the bacteria in normal gingival tissues and gingival carcinoma, with higher levels (more than 33%,P\u3c0.05) detected in the carcinoma samples. The staining intensity was also significantly enhanced in the malignant tissue by 2 folds (P\u3c0.023) compared to specimens stained for the non‐invasive S. gordonii. P. gingivalis is abundantly present in malignant oral epithelium suggesting a potential association of the bacteria with gingival squamous cell carcinoma

Characteristic molecular properties of one-electron double quantum rings under magnetic fields

The molecular states of conduction electrons in laterally coupled quantum rings are investigated theoretically. The states are shown to have a distinct magnetic field dependence, which gives rise to periodic fluctuations of the tunnel splitting and ring angular momentum in the vicinity of the ground state crossings. The origin of these effects can be traced back to the Aharonov-Bohm oscillations of the energy levels, along with the quantum mechanical tunneling between the rings. We propose a setup using double quantum rings which shows that Aharonov-Bohm effects can be observed even if the net magnetic flux trapped by the carriers is zero.Comment: 16 pages (iopart format), 10 figures, accepted in J.Phys.Cond.Mat

Global optimization of hybrid systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2006.Includes bibliographical references (p. 339-353).Systems that exhibit both discrete state and continuous state dynamics are called hybrid systems. In most nontrivial cases, these two aspects of system behavior interact to such a significant extent that they cannot be decoupled effectively by any kind of abstraction and must be analyzed simultaneously. Hybrid system models are important in many areas of science and engineering, including flip-flops and latching relays, manufacturing systems, air-traffic management systems, controller synthesis, switched systems, chemical process systems, signaling and decision making mechanisms in (biological) cells, robotic systems, safety interlock systems, and embedded systems. The primary focus of this thesis is to explore deterministic methods for the global optimization of hybrid systems. While the areas of modeling, simulation and sensitivity analysis of hybrid systems have received much attention, there are many challenging difficulties associated with the optimization of such systems. The contents of this thesis represent the first steps toward deterministic global optimization of hybrid systems in the continuous time domain. There are various reasons for wanting to solve optimization problems globally.(cont.) In particular, there are many applications which demand that the global solution be found, for example, formal safety verification problems and parameter estimation problems. In the former case, a suboptimal local solution could falsely indicate that all safety specifications are met, leading to disastrous consequences if, in actuality, a global solution exists which provides a counter example that violates some safety specification. In the latter case, a suboptimal local solution could falsely indicate that a proposed model structure did not match experimental data in a statistically significant manner, leading to the false rejection of a valid model structure. In addition, for many optimization problems in engineering, the presence of nonlinear equality constraints makes the optimization problem nonconvex such that local optimization methods can often fail to produce a single feasible point, even though the problem is indeed feasible. The control parameterization framework is employed for the solution of the optimization problem with continuous time hybrid systems embedded. A major difficulty of such a framework lies in the fact that the mode sequence of the embedded hybrid system changes in the space of the optimization decision variables for most nontrivial problems.(cont.) This makes the resulting optimization problem nonsmooth because the parametric sensitivities of the hybrid system do not exist everywhere, thus invalidating efficient gradient based optimization solvers. In this thesis, the general optimization problem is decomposed into three subproblems, and tackled individually: (a) when the mode sequence is fixed, and the transition times are fixed; (b) when the mode sequence is allowed to vary, and the transition times are fixed; and (c) when the mode sequence is fixed, and the transition times are allowed to vary. Because even these subproblems are nontrivial to solve, this thesis focuses on hybrid systems with linear time varying ordinary differential equations describing the continuous dynamics, and proposes various methods to exploit the linear structure. However, in the course of solving the last subproblem, a convexity theory for general, nonlinear hybrid systems is developed, which can be easily extended for general, nonlinear hybrid systems. Subproblem (a) is the easiest to solve. A convexity theory is presented that allows convex relaxations of general, nonconvex Bolza type functions to be constructed for the optimization problem. This allows a deterministic branch-and-bound framework to be employed for the global optimization of the subproblem.(cont.) Subproblems (b) and (c) are much more difficult to solve, and require the exploitation of structure. For subproblem (b), a hybrid superstructure is proposed that enables the linear structure to be retained. A branch-and-cut framework with a novel dynamic bounds tightening heuristic is proposed, and it is shown that the generation of cuts from dynamic bounds tightening can have a dramatic impact on the solution of the problem. For subproblem (c), a time transformation is employed to transform the problem into one with fixed transition times, but nonlinear dynamics. A convexity theory is developed for constructing convex relaxations of general, nonconvex Bolza type functions with the nonlinear hybrid system embedded, along with the development of bounding methods, based on the theory of differential inequalities. A novel bounding technique that exploits the time transformation is also introduced, which can provide much tighter bounds than that furnished utilizing differential inequalities.by Cha Kun Lee.Ph.D