Polytechnic University of Valencia

About: Polytechnic University of Valencia is a education organization based out in Valencia, Spain. It is known for research contribution in the topics: Catalysis & Population. The organization has 16282 authors who have published 40162 publications receiving 850234 citations.

Orchestration of Floral Initiation by APETALA1

Abstract: The MADS-domain transcription factor APETALA1 (AP1) is a key regulator of Arabidopsis flower development. To understand the molecular mechanisms underlying AP1 function, we identified its target genes during floral initiation using a combination of gene expression profiling and genome-wide binding studies. Many of its targets encode transcriptional regulators, including known floral repressors. The latter genes are down-regulated by AP1, suggesting that it initiates floral development by abrogating the inhibitory effects of these genes. Although AP1 acts predominantly as a transcriptional repressor during the earliest stages of flower development, at more advanced stages it also activates regulatory genes required for floral organ formation, indicating a dynamic mode of action. Our results further imply that AP1 orchestrates floral initiation by integrating growth, patterning, and hormonal pathways.

Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things

Abstract: A network traffic classifier (NTC) is an important part of current network monitoring systems, being its task to infer the network service that is currently used by a communication flow (e.g., HTTP and SIP). The detection is based on a number of features associated with the communication flow, for example, source and destination ports and bytes transmitted per packet. NTC is important, because much information about a current network flow can be learned and anticipated just by knowing its network service (required latency, traffic volume, and possible duration). This is of particular interest for the management and monitoring of Internet of Things (IoT) networks, where NTC will help to segregate traffic and behavior of heterogeneous devices and services. In this paper, we present a new technique for NTC based on a combination of deep learning models that can be used for IoT traffic. We show that a recurrent neural network (RNN) combined with a convolutional neural network (CNN) provides best detection results. The natural domain for a CNN, which is image processing, has been extended to NTC in an easy and natural way. We show that the proposed method provides better detection results than alternative algorithms without requiring any feature engineering, which is usual when applying other models. A complete study is presented on several architectures that integrate a CNN and an RNN, including the impact of the features chosen and the length of the network flows used for training.

Sound Attenuation by a Two-Dimensional Array of Rigid Cylinders

Abstract: In this Letter we present an experimental analysis of the acoustic transmission of a two-dimensional periodic array of rigid cylinders in air with two different geometrical configurations: square and triangular. In both configurations, and above a certain filling fraction, we observe an overlap, in the range of the audible frequencies, between the attenuation peaks measured along the two high-symmetry directions of the Brillouin zone. This effect is considered as the fingerprint of the existence of a full acoustic gap. Nevertheless, the comparison with our calculation of band structures shows that the triangular lattice has band states in that frequency range. We call them deaf bands. This contradictory result is explained by looking at the symmetry of the deaf bands; they cannot be excited by experiments of sound transmission. [S0031-9007(98)06295-4]

Edible and Biodegradable Starch Films: A Review

Abstract: Mainly due to environmental aims, petroleum-based plastics are being replaced by natural polymers. In the last decades, starch has been evaluated in its film-forming ability for applications in the food packaging area. Characteristics of the starch film matrices, the film formation methods, and physicochemical properties of the starch films are reviewed in this paper. The influences of different components added in casting methods and thermoplastic processes have been also analyzed. Comparison of mechanical properties of newly prepared starch films and stored films reveals that the recrystallization phenomenon made the films more rigid and less stretchable. These effects can be inhibited by adding other polymers to the starch matrix. Other approaches to improve the starch films’ properties are the reinforcement by adding organic or inorganic fillers to the starch matrix as well as the addition of functional compounds. In this way starch films have improved mechanical and barrier properties and can act as a bioactive packaging. Physicochemical properties of the starch films showed a great variability depending on the compounds added to the matrix and the processing method. Nevertheless, dry methods are more recommendable for film manufacturing because of the greater feasibility of the industrial process. In this sense, a better understanding of the nano and microstructural changes occurring in the matrices and their impact on the film properties is required.