Novel Mullite Synthesis Based on Alumina Nanoparticles and a Preceramic Polymer

Heating in air of a selected mixture of a silicone resin and alumina nanoparticles in the temperature range 1200°–1500°C yielded dense, crack-free mullite samples. Al₂O₃, due to its nanometric size, proved to be very reactive toward silica, deriving from the ceramization of the preceramic polymer, leading to the formation of a large volume fraction of mullite crystals even at low firing temperatures (1250°C). Because of the homogeneity of the distribution of alumina nanoparticles in the starting system, the ceramized samples exhibited a very fine microstructure consisting of crystals with an average dimension in the range of 50–300 nm.     

Modulation of Geraniol Metabolism During Alcohol Fermentation

Geraniol is the main monoterpenol present in Gewurtztraminer white grapes and in some red aromatic grapes from northern Italy. During fermentation, the geraniol concentration showed a dramatic drop and a small amount was transformed into linalool and α‐terpineol by an acid catalysed chemical reaction. Yeast are responsible for changing most of the geraniol to citronellol through enzymatic reactions. The final aroma of wine is due mainly to both the untransformed geraniol and the formed citronellol. In this study, competition between the geraniol‐citronellol transformation and another metabolic process, in which according to our hypothesis sterol biosynthesis is involved, was investigated. Geraniol, in the active form of geranyl pyrophosphate, is one of intermediates in that metabolic pathway. The addition of ergosterol, one of final products of sterol biosynthesis, to the fermentation medium, appeared to reduce the amount of geraniol involved in this metabolic pathway; as a result geraniol‐citronellol transformation was favoured. The result was a higher production of citronellol with the same geraniol consumption. The relationships between oxygen and regulation of the metabolic pathways involving geraniol were also studied. Results showed that aerobic conditions could improve citronellol production. Finally, it was observed that metabolism of geraniol also depended on the physiological state of the yeast during fermentation.     

Modulated CMOS camera for fluorescence lifetime microscopy

Widefield frequency‐domain fluorescence lifetime imaging microscopy (FD‐FLIM) is a fast and accurate method to measure the fluorescence lifetime of entire images. However, the complexity and high costs involved in construction of such a system limit the extensive use of this technique. PCO AG recently released the first luminescence lifetime imaging camera based on a high frequency modulated CMOS image sensor, QMFLIM2. Here we tested and provide operational procedures to calibrate the camera and to improve the accuracy using corrections necessary for image analysis. With its flexible input/output options, we are able to use a modulated laser diode or a 20 MHz pulsed white supercontinuum laser as the light source. The output of the camera consists of a stack of modulated images that can be analyzed by the SimFCS software using the phasor approach. The nonuniform system response across the image sensor must be calibrated at the pixel level. This pixel calibration is crucial and needed for every camera settings, e.g. modulation frequency and exposure time. A significant dependency of the modulation signal on the intensity was also observed and hence an additional calibration is needed for each pixel depending on the pixel intensity level. These corrections are important not only for the fundamental frequency, but also for the higher harmonics when using the pulsed supercontinuum laser. With these post data acquisition corrections, the PCO CMOS‐FLIM camera can be used for various biomedical applications requiring a large frame and high speed acquisition. Microsc. Res. Tech. 78:1075–1081, 2015. © 2015 Wiley Periodicals, Inc.     

Functional Characterization of E. coli LptC: Interaction with LPS and a Synthetic Ligand

Lipopolysaccharide (LPS), the main cell‐surface molecular constituent of Gram‐negative bacteria, is synthesized in the inner membrane (IM) and transported to the outer membrane (OM) by the Lpt (lipopolysaccharide transport) machinery. Neosynthesized LPS is first flipped by MsbA across the IM, then transported to the OM by seven Lpt proteins located in the IM (LptBCFG), in the periplasm (LptA), and in the OM (LptDE). A functional OM is essential to bacterial viability and requires correct placement of LPS in the outer leaflet. Therefore, LPS biogenesis represents an ideal target for the development of novel antibiotics against Gram‐negative bacteria. Although the structures of Lpt proteins have been elucidated, little is known about the mechanism of LPS transport, and few data are available on Lpt–LPS binding. We report here the first determination of the thermodynamic and kinetic parameters of the interaction between LptC and a fluorescent lipo‐oligosaccharide (fLOS) in vitro. The apparent dissociation constant (K_d) of the fLOS–LptC interaction was evaluated by two independent methods. The first was based on fLOS capture by resin‐immobilized LptC; the second used quenching of LptC intrinsic fluorescence by fLOS in solution. The K_d values by the two methods (71.4 and 28.8 μm, respectively) are very similar, and are of the same order of magnitude as that of the affinity of LOS for the upstream transporter, MsbA. Interestingly, both methods showed that fLOS binding to LptC is mostly irreversible, thus reflecting the fact that LPS can be released from LptC only when energy is supplied by ATP or in the presence of a higher‐affinity LptA protein. A fluorescent glycolipid was synthesized: this also interacted irreversibly with LptC, but with lower affinity (apparent K_d=221 μM ). This compound binds LptC at the LPS binding site and is a prototype for the development of new antibiotics targeting LPS transport in Gram‐negative bacteria.     

Modelling total evacuation strategies for high-rise buildings

This paper focuses on the use of egress models to assess the optimal strategy in the case of total evacuation in high-rise buildings. The model case study consists of two identical twin towers linked with two sky-bridges at different heights. Each tower is a 50-floor office building. The use of either horizontal or vertical egress components or a combination of them is simulated. The egress components under consideration are stairs (either 2 or 3 stairs), occupant evacuation elevators, service elevators (available or not for the evacuation of the occupants), transfer floors and sky-bridges. Seven different evacuation strategies have been tested which consider the total evacuation of a single tower. The evacuation scenarios have been simulated with a continuous spatial representation evacuation model (Pathfinder). In order to perform a cross validation of the model results, two strategies involving the evacuation using stairs or occupant evacuation elevators have also been simulated using a fine network model (STEPS). Results refer to the analysis of total evacuation times. The simulation work highlights the assumptions required to represent the possible behaviours of the occupants in order to qualitatively rank the strategies. The lowest evacuation times are obtained simulating strategies involving the sole use of occupant evacuation elevators and the combined use of transfer floors and sky-bridges. This study suggests that the effectiveness of evacuation strategies involving the combination of stairs and elevators significantly decreases in high-rise buildings if they are not combined with appropriate messaging/signage to guide occupants in their behaviours.     

Cogeneration planning under uncertainty: Part I: Multiple time frame approach

Cogeneration system planning spans a multi-year time interval and is affected by various sources of uncertainty, mainly depending on the evolution of energy loads and prices. The high level of uncertainty requires assessing the convenience of adopting predefined technological alternatives in different scenarios of variation of the uncertain variables. This paper introduces an original framework based on identifying the characteristics of small-scale and large-scale uncertainties, whereby a comprehensive approach based on multiple (long-, medium- and short-term) time frames is formulated. Medium-term time periods exhibiting small variations of both electrical and thermal load patterns are grouped together and represented through electrical/thermal load and electricity price correlated random variables (RVs). A Monte Carlo simulation of the cogeneration plant operation is carried out in the short-term by extracting the RVs for each group from multivariate Normal probability distributions. Multi-year scenarios in the long-term time frame are addressed in the companion paper (Part II). The proposed approach is applied to a real energy system.     

Transparent encryption techniques for H.264/AVC and H.264/SVC compressed video

Transparent encryption of video content requires to provide a video preview that is left in plaintext, while the enhancement information is encrypted. In this paper we propose three algorithms that provide transparent encryption. The first two ones are based on the idea of generating controlled drift in such a way as to obtain the desired quality level, while the third algorithm employs scalable video coding. We provide experimental results on several video sequences, as well as a security analysis, showing that the proposed algorithms provide an effective framework to perform transparent encryption.     

On the electrospinning of PVDF: influence of the experimental conditions on the nanofiber properties

The characteristics of poly(vinylidene fluoride) (PVDF) nanofibers, prepared by applying the electrospinning technique from N,N‐dimethylformamide/acetone mixtures, were studied by varying the experimental conditions. The nanofiber morphology was assessed by scanning electron microscopy, while wide angle X‐ray diffraction and infrared spectroscopy were performed to study the crystallinity. The influence of the electrospinning conditions, such as kind of solvent mixture, polymer concentration, voltage tension, airflow and humidity, on nanofiber morphology was studied. In particular, the latter parameter, generally not considered, was found to modify the electrospun mat structure in a relevant way. Generally, the above technique turns out to be capable of strongly affecting the polymorphism of the polymer, namely β phase formation was higher in the electrospun mats compared with cast films, which displayed a non‐polar α crystal phase. As far as the influence of the electrospinning conditions on PVDF crystal structure is concerned, modification of the experimental parameters did not affect the α/β ratio. Nevertheless, comparing the behavior of two commercial PVDF samples with similar molecular masses, our results show that the polymer which forms a higher content of β phase in its cast films allowed electrospun mats characterized by almost complete formation of β phase to be obtained. Copyright © 2012 Society of Chemical Industry     

Predicting time series of railway speed restrictions with time-dependent machine learning techniques

In this paper, a hybrid approach to combine conditional restricted Boltzmann machines (CRBM) and echo state networks (ESN) for binary time series prediction is proposed. Both methods have demonstrated their ability to extract complex dynamic patterns from time-dependent data in several applications and benchmark studies. To the authors’ knowledge, it is the first time that the proposed combination of algorithms is applied for reliability prediction.The proposed approach is verified on a case study predicting the occurrence of railway operation disruptions based on discrete-event data, which is represented by a binary time series. The case study concerns speed restrictions affecting railway operations, caused by failures of tilting systems of railway vehicles. The overall prediction accuracy of the algorithm is 99.93%; the prediction accuracy for occurrence of speed restrictions within the foresight period is 98% (which corresponds to the sensitivity of the algorithm). The prediction results of the case study are compared to the prediction with a MLP trained with a Newton conjugate gradient algorithm. The proposed approach proves to be superior to MLP.     

Exploring free-energy profiles through ion channels: Comparison on a test case

The calculation of free-energy profiles in proteins, and, more specifically, in ion channels, is a challenge for modern numerical simulations due both to the convergence problems associated with the electrostatics of the environment and to the difficulties in modeling the fields acting on the permeating ions. The present study is aims at comparing three different simulation techniques available in the literature on a nanometric channel protein chosen as a test case, with the purpose of establishing their real predictivity and limits.