Proline- and acidic amino acid-rich basic leucine zipper proteins modulate peroxisome proliferator-activated receptor alpha (PPAR alpha) activity.

In mammals, many aspects of metabolism are under circadian control. At least in part, this regulation is achieved by core-clock or clock-controlled transcription factors whose abundance and/or activity oscillate during the day. The clock-controlled proline- and acidic amino acid-rich domain basic leucine zipper proteins D-site-binding protein, thyrotroph embryonic factor, and hepatic leukemia factor have previously been shown to participate in the circadian control of xenobiotic detoxification in liver and other peripheral organs. Here we present genetic and biochemical evidence that the three proline- and acidic amino acid-rich basic leucine zipper proteins also play a key role in circadian lipid metabolism by influencing the rhythmic expression and activity of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα). Our results suggest that, in liver, D-site-binding protein, hepatic leukemia factor, and thyrotroph embryonic factor contribute to the circadian transcription of genes specifying acyl-CoA thioesterases, leading to a cyclic release of fatty acids from thioesters. In turn, the fatty acids act as ligands for PPARα, and the activated PPARα receptor then stimulates the transcription of genes encoding proteins involved in the uptake and/or metabolism of lipids, cholesterol, and glucose metabolism.

Classification of urban multi-angular image sequences by aligning their manifolds

When dealing with multi-angular image sequences, problems of reflectance changes due either to illumination and acquisition geometry, or to interactions with the atmosphere, naturally arise. These phenomena interplay with the scene and lead to a modification of the measured radiance: for example, according to the angle of acquisition, tall objects may be seen from top or from the side and different light scatterings may affect the surfaces. This results in shifts in the acquired radiance, that make the problem of multi-angular classification harder and might lead to catastrophic results, since surfaces with the same reflectance return significantly different signals. In this paper, rather than performing atmospheric or bi-directional reflection distribution function (BRDF) correction, a non-linear manifold learning approach is used to align data structures. This method maximizes the similarity between the different acquisitions by deforming their manifold, thus enhancing the transferability of classification models among the images of the sequence.

Privacy as a Tradeoff: Introducing the Notion of Privacy Calculus for Context-Aware Mobile Applications

Evidences collected from smartphones users show a growing desire of personalization offered by services for mobile devices. However, the need to accurately identify users' contexts has important implications for user's privacy and it increases the amount of trust, which users are requested to have in the service providers. In this paper, we introduce a model that describes the role of personalization and control in users' assessment of cost and benefits associated to the disclosure of private information. We present an instantiation of such model, a context-aware application for smartphones based on the Android operating system, in which users' private information are protected. Focus group interviews were conducted to examine users' privacy concerns before and after having used our application. Obtained results confirm the utility of our artifact and provide support to our theoretical model, which extends previous literature on privacy calculus and user's acceptance of context-aware technology.

Extension of ultrasound Fourier slice Imaging theory to sectorial acquisition

Ultrasound image reconstruction from the echoes received by an ultrasound probe after the transmission of diverging waves is an active area of research because of its capacity to insonify at ultra-high frame rate with large regions of interest using small phased arrays as the ones used in echocardiography. Current state-of-the-art techniques are based on the emission of diverging waves and the use of delay and sum strategies applied on the received signals to reconstruct the desired image (DW/DAS). Recently, we have introduced the concept of Ultrasound Fourier Slice Imaging (UFSI) theory for the reconstruction of ultrafast imaging for linear acquisition. In this study, we extend this theory to sectorial acquisition thanks to the introduction of an explicit and invertible spatial transform. Starting from a diverging wave, we show that the direct use of UFSI theory along with the application of the proposed spatial transform allows reconstructing the insonified medium in the conventional Cartesian space. Simulations and experiments reveal the capacity of this new approach in obtaining competitive quality of ultrafast imaging when compared with the current reference method.