Computação

We investigated in vitro skin penetration and permeation of fluconazole from emulsions containing different penetration enhancers. Fluconazole permeation was high (15-65% of the applied dose) across hairless mouse skin and low (8-9%) across pig ear skin. Permeation across mice skin from a formulation containing propyleneglycol and isopropyl myristate was significantly higher than that observed with the paraffin oil and propyleneglycol or Transcutol emulsions. With pig skin, the paraffin oil or isopropyl myristate and propyleneglycol emulsions showed similar skin permeation and penetration. However, these emulsions provided epidermal concentrations higher than the minimal inhibitory concentrations for most dermatophytes.

The growth of Social Networks has fueled the habit of people logging their day-to-day activities, and long First-Person Videos (FPVs) are one of the main tools in this new habit. Semantic-aware fast-forward methods are able to decrease the watch time and select meaningful moments, which is key to increase the chances of these videos being watched. However, these methods can not handle semantics in terms of personalization. In this paper, we present a new approach to automatically creating personalized fast-forward videos for FPVs. Our approach explores the availability of text-centric data from the user’s social networks such as status updates to infer her/his topics of interest and assigns scores to the input frames according to her/his preferences. Extensive experiments are conducted on three different datasets with simulated and real-world users as input. Our method achieved an average F1 score of up to 12.8 percentage points higher than the best competitors. We also present a us...

The emergence of low-cost, high-quality personal wearable cameras combined with a large and increasing storage capacity of video-sharing websites have evoked a growing interest in first-person videos. A First-Person Video is usually composed of monotonous long-running unedited streams captured by a device attached to the user body, which makes it visually unpleasant and tedious to watch. Thus, there is a rise in the need to provide quick access to the information therein. In the last few years, a popular approach to retrieve the information from videos is to produce a short version of the input video by creating a video summary; however, this approach disrupts the temporal context of the recording. Fast-Forward is another approach that creates a shorter version of the video preserving the video context by increasing its playback speed. Although Fast-Forward methods keep the recording story, they do not consider the semantic load of the input video. The Semantic Fast-Forward approach...

The emergence of low-cost, high-quality personal wearable cameras combined with a large and increasing storage capacity of video-sharing websites have evoked a growing interest in first-person videos. A First-Person Video is usually composed of monotonous long-running unedited streams captured by a device attached to the user body, which makes it visually unpleasant and tedious to watch. Thus, there is a rise in the need to provide quick access to the information therein. In the last few years, a popular approach to retrieve the information from videos is to produce a short version of the input video by creating a video summary; however, this approach disrupts the temporal context of the recording. Fast-Forward is another approach that creates a shorter version of the video preserving the video context by increasing its playback speed. Although Fast-Forward methods keep the recording story, they do not consider the semantic load of the input video. The Semantic Fast-Forward approach creates a shorter version of First-Person Videos dealing with both video context and emphasis of the relevant portions to keep the semantic load of the input video. In this paper, we present a review of the representative methods in both fast-forward and semantic fast-forward methods and discuss the future directions of the area.

Social media applications have assumed an important role in decision-making process of users, affecting their choices about products and services. In this context, understanding and modeling opinions, as well as opinion-leaders, have implications for several tasks, such as recommendation, advertising, brand evaluation etc. Despite the intrinsic relation between opinions and opinion-leaders, most recent works focus exclusively on either understanding the opinions, by Sentiment Analysis (SA) proposals, or identifying opinion-leaders using Influential Users Detection (IUD). This paper presents a preliminary evaluation about a combined analysis of SA and IUD. In this sense, we propose a methodology to quantify factors in real domains that may affect such analysis, as well as the potential benefits of combining SA Methods with IUD ones. Empirical assessments on a sample of tweets about the Brazilian president reveal that the collective opinion and the set of top opinion-leaders over time are inter-related. Further, we were able to identify distinct characteristics of opinion propagation, and that the collective opinion may be accurately estimated by using a few top-k opinion-leaders. These results point out the combined analysis of SA and IUD as a promising research direction to be further exploited.