Optimal coding through divisive normalization models of V1 neurons

Current models of the primary visual cortex (V1) include a linear filtering stage followed by a gain control mechanism that explains some of the nonlinear behaviour of neurons. This nonlinear stage consists of a divisive normalization in which each linear response is squared and then divided by a weighted sum of squared linear responses in a certain neighbourhood plus a constant. Simoncelli and Schwartz (1999 Adv. Neural Inform. Process. Syst. 11 153-9) have suggested that divisive normalization reduces the statistical dependence between neuron responses when the weights are adapted to the statistics of natural images, which is consistent with the efficient coding hypothesis. Nevertheless, there are still important open issues, such as, for example, how to obtain the values for the parameters that minimize statistical dependence? Does divisive normalization give a total independence between responses? In this paper, we present the general mathematical formulation of the first of these two questions. We arrive at an expression which permits us to compute, numerically, the parameters of a quasi-optimal solution adapted to an input set of natural images. This quasi-optimal solution is based on a Gaussian model of the conditional statistics of the coefficients resulting from projecting natural images onto an orthogonal linear basis. Our results show, in general, lower values of mutual information, that is, responses are more independent than those provided by previous approximations.     

Wavelet-Based Multiresolution with

Multiresolution methods are a common technique used for dealing with large-scale data and representing it at multiple levels of detail. We present a multiresolution hierarchy construction based on subdivision, which has all the advantages of a regular data organization scheme while reducing the drawback of coarse granularity. The -subdivision scheme only doubles the number of vertices in each subdivision step regardless of dimension n. We describe the construction of 2D, 3D, and 4D hierarchies representing surfaces, volume data, and time-varying volume data, respectively. The 4D approach supports spatial and temporal scalability. For high-quality data approximation on each level of detail, we use downsampling filters based on n-variate B-spline wavelets. We present a B-spline wavelet lifting scheme for -subdivision steps to obtain small or narrow filters. Narrow filters support adaptive refinement and out-of-core data exploration techniques.     

Structure of Ego‐Alter Relationships of Politicians in Twitter

We analyze the ego‐alter Twitter networks of 300 Italian MPs and 18 European leaders, and of about 14,000 generic users. We find structural properties typical of social environments, meaning that Twitter activity is controlled by constraints that are similar to those shaping conventional social relationships. However, the evolution of ego‐alter ties is very dynamic, which suggests that they are not entirely used for social interaction, but for public signaling and self‐promotion. From this standpoint, the behavior of EU leaders is much more evident, while Italian MPs are in between them and generic users. We find that politicians – more than generic users – create relationships as a side effect of tweeting on discussion topics, rather than by contacting specific alters.     

Ultra-low-power components for an RFID Tag with physical and chemical sensors

In this work the development and optimization of the main components for a multisensing flexible Tag with RFID communication capabilities and integrated physical and chemical sensors for logistic datalogging applications will be reported. For this specific scenario, several constraints must be considered: power consumption must be limited for long-term operation, reliable ISO compliant RFID communication must be implemented, and special encapsulation issues must be faced for reliable sensor integration. In this work, the developments on application specific electronic interfaces and on ultra-low-power Metal OXdide semiconductor (MOX) gas sensors will be reported. The electronics for sensor control and readout as well as for RFID communication are based on an ultra-low-power MSP430 microcontroller from Texas Instruments together with a custom RFID front-end based on analog circuitry and a CPLD digital device, and are designed to guarantee a passive ISO15693 compliant RFID communication in a range up to 6 cm. A thin film battery for sensor operation is included, thus data acquisition and storage can be accomplished when no reader field is present. This design allows the user to access both the traceability and sensor information even when the on-board battery is exhausted. The physical sensors for light, temperature and humidity are commercially available devices, while for chemical gas sensing innovative MOX sensors are developed, based on ultra-low-power micromachined hotplate arrays specifically designed for flexible Tag integration purposes. A single MOX sensor requires only 8.9 mW for continuous operation, while temperature modulation and discontinuous sensor operation modes are implemented to further reduce the overall power consumption. The development of the custom control and RFID front-end electronics, together with innovative ultra-low-power MOX sensor arrays with flexible circuit encapsulation techniques will be described.     

Analysis of an accident at a solvent recovery plant.

An accident in a plant for solvent recovery from solvent-contaminated wastes was examined. An experimental investigation of the accident was carried out using calorimetric and thermogravimetric techniques. The immediate cause of the accident was an unforeseen exothermic decomposition reaction. The main underlying cause of the accident was the absence of safety culture in the plant management, that resulted in the lack of a testing procedure to evaluate the thermal stability of the process feed. A simplified screening procedure based on differential scanning calorimetry was used in order to test the thermal stability of the nonvolatile fraction of the solvent-contaminated wastes present on the plant in order to be processed. More than 75% of the samples examined showed exothermal decomposition phenomena starting at temperatures higher than 100 degrees C. These phenomena were common to solvent wastes that originated from a number of different industrial activities. Thus, the thermal instability of the process feed is one of the main problems in solvent recovery operations. Our analysis of the accident suggested that the safe operation of waste solvent recovery processes requires an accurate characterization of the thermal stability of the process feed. Process safety is also increased by an adequate emergency vent and an accurate control of operating temperature, that may be reduced operating under vacuum. Safety devices may also include a water supply for emergency quench.     

Effects of murta (Ugni molinae Turcz) extract on gas and water vapor permeability of carboxymethylcellulose-based edible films

The effect of murta (Ugni molinae Turcz) leaves extract on water vapor permeability (WVP) and gas permeability (GP) of carboxymethylcellulose (CMC)-based films was studied. Two ecotypes of murta leaves “Soloyo Grande” (SG) and “Soloyo Chico” (SC), were analyzed for their composition (HPLC-MS) and SC extract revealed a higher concentration of flavonols than the SG extract. The film forming solution was prepared with 2 g of CMC, 0.4 ml of glycerol and 0.5 ml of sunflower oil in 100 ml of water (Control), 50 ml of water and 50 ml of each exctract (SC50 or SG50) and 100 ml of each extract (SC 100 or SG 100). The addition of murta leaves extract modified the WVP and GP of the films. The WVP decreased significantly (P?0.05) with the incorporation of SG extract in the film but not with the SC extract (P>0.05). The CO₂ and O₂ permeability of the films were influenced by the kind and concentration of murta leaves extract used. The CO₂ permeability, with SG extract was higher than without extract (P?0.05) and with SC extract was not modified. The O₂ permeability with murta leaves extract were lower than without extract. Therefore, it is possible to consider that films with SC acts only as barrier to the oxygen, but with SG the water vapor and gas barrier properties were modified, being more permeable to the CO₂ and acting as barrier to O₂ and water vapor.     

Monthly Hydrological Indicators to Assess Possible Alterations on Rivers’ Flow Regime

Assessing potential deviations of the fundamental river basins’ hydrological processes and streamflow characteristics from the “natural trajectory” represents a high-priority objective to understand the biological impact of altered flow regime on river ecosystems. Existing approaches are mainly based on the analysis of daily-based indicators of hydrologic alteration, which requires wide database, including “pre-impact” and “post-impact” daily flow data frequently unavailable. The hydrological modeling is commonly used to face data missing problems or reconstruct natural conditions, even if models, especially at the daily scales, are often complex and computationally intensive. The use of simpler and more parsimonious models results, sometimes, essential for practical applications, also in consideration of the typical scarce availability of some data. This paper proposes an alternative approach for the evaluation of rivers flow regime alterations, based on different monthly hydrological indicators that are first computed and then combined to provide a global index of alteration. The procedure, conceptually derived from the Range of Variability Approach (RVA), is applied and tested on two Sicilian river basins (Italy) subject to anthropogenic influence. Streamflow regime for both the basins results differently disturbed by upstream human pressures. An alteration index is computed using available observations as “post-impact” monthly flow time-series, while time-series relative to “pre-impact” conditions have been reconstructed by the Tri.Mo.Ti.S. model, an innovative monthly and high-performing regional regressive hydrological model. The methodology, easily transferable to other regions, has revealed particularly efficacious in identifying and quantifying the existing human pressures and can be considered as a suitable tool for water resource management and policy planning activities.