Glycerol metabolism and bitterness producing lactic acid bacteria in cidermaking

Several lactic acid bacteria were isolated from bitter tasting ciders in which glycerol was partially removed. The degradation of glycerol via glycerol dehydratase pathway was found in 22 out of 67 isolates. The confirmation of glycerol degradation by this pathway was twofold: showing their glycerol dehydratase activity and detecting the presence of the corresponding gene by a PCR method. 1,3-propanediol (1,3-PDL) and 3-hydroxypropionic acid (3-HP) were the metabolic end-products of glycerol utilization, and the accumulation of the acrolein precursor 3-hydroxypropionaldehyde (3-HPA) was also detected in most of them. The strain identification by PCR-DGGE rpoB showed that Lactobacillus collinoides was the predominant species and only 2 belonged to Lactobacillus diolivorans. Environmental conditions conducting to 3-HPA accumulation in cidermaking were studied by varying the fructose concentration, pH and incubation temperature in L. collinoides 17. This strain failed to grow with glycerol as sole carbon source and the addition of fructose enhanced both growth and glycerol degradation. Regarding end-products of glycerol metabolism, 1,3-PDL was always the main end-product in all environmental conditions assayed, the only exception being the culture with 5.55 mM fructose, where equimolar amounts of 1,3-PDL and 3-HP were found. The 3-HPA was transitorily accumulated in the culture medium under almost all culture conditions, the degradation rate being notably slower at 15 degrees C. However, no disappearance of 3-HPA was found at pH 3.6, a usual value in cider making. After sugar exhaustion, L. collinoides 17 oxidated lactic acid and/or mannitol to obtain energy and these oxidations were accompanied by the removal of the toxic 3-HPA increasing the 1,3-PDL, 3-HP and acetic acid contents.     

The effects of salt concentration on conformational changes in cod (Gadus morhua) proteins during brine salting

The effects of different salt concentrations (6%, 15%, 18% and 24% NaCl (w/w)) on the conformational changes of cod muscle proteins during brine salting were examined in this study. Proteins were extracted from the brine salted samples with solutions of 1 M (5.9%) and 4 M (23.4%) NaCl and the quantity of salt soluble proteins (SSP), disulfide bond (S–S), total sulfhydryl (SH) and available SH content in the soluble fraction were determined. Increased salt concentration in cod muscle promoted protein denaturation and aggregation. The SSP and total SH content decreased, whereas the S–S bond and available SH content increased with increased salt concentration in cod muscle. Disulfide bond formation correlated (r = −0.6) with a decrease in total SH groups. Higher SSP and available SH groups of the samples at lower brine concentrations was explained by smaller concentration gradients and salt diffusion rates, resulting in stronger salting-in at early stages of the brining process. There was a significant difference in conformational changes in proteins extracted with a salt solution of 1 and 4 M, mainly due to a different degree of protein aggregation.     

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Glioblastoma multiforme (GBM) is a highly invasive primary brain tumour that has poor prognosis despite aggressive treatment. A hallmark of these tumours is diffuse invasion into the surrounding brain, necessitating a multi-modal treatment approach, including surgery, radiation and chemotherapy. We have previously demonstrated the ability of our model to predict radiographic response immediately following radiation therapy in individual GBM patients using a simplified geometry of the brain and theoretical radiation dose. Using only two pre-treatment magnetic resonance imaging scans, we calculate net rates of proliferation and invasion as well as radiation sensitivity for a patient''s disease. Here, we present the application of our clinically targeted modelling approach to a single glioblastoma patient as a demonstration of our method. We apply our model in the full three-dimensional architecture of the brain to quantify the effects of regional resistance to radiation owing to hypoxia in vivo determined by [¹⁸F]-fluoromisonidazole positron emission tomography (FMISO-PET) and the patient-specific three-dimensional radiation treatment plan. Incorporation of hypoxia into our model with FMISO-PET increases the model–data agreement by an order of magnitude. This improvement was robust to our definition of hypoxia or the degree of radiation resistance quantified with the FMISO-PET image and our computational model, respectively. This work demonstrates a useful application of patient-specific modelling in personalized medicine and how mathematical modelling has the potential to unify multi-modality imaging and radiation treatment planning.     

Classification of shoreline vegetation in the Western Basin of Lake Erie using airborne hyperspectral imager HSI2, Pleiades and UAV data

Mapping land and aquatic vegetation of coastal areas using remote sensing for better management and conservation has been a long-standing interest in many parts of the world. Due to natural complexity and heterogeneity of vegetation cover, various remote sensing sensors and techniques are utilized for monitoring coastal ecosystems. In this study, two unsupervised and two supervised standard pixel-based classifiers were tested to evaluate the mapping performance of the second-generation airborne NASA Glenn Hyperspectral Imager (HSI2) over the narrow coastal area along the Western Lake Erie’s shoreline. Furthermore, the classification results of HSI2 (using the whole Visible-Near Infrared (VIS+ NIR) hyperspectral dataset, and also the spectral subset of Visible (VIS) spectral bands) were compared to multispectral Pleiades (VIS+ NIR) and Unmanned Aerial Vehicle (UAV) VIS classified images. The goal was to explore how different spectral ranges, and spatial and spectral resolutions impact the unsupervised and supervised classifiers. While the unsupervised classifiers depended more on the spectral range, spectral or spatial resolutions were important for the supervised classifiers. The Support Vector Machine (SVM) was found to perform better than other classification methods for the HSI2 images over all twenty-two study sites with the overall accuracy (OA) ranging from 82.6%–97.5% for VIS, and 81.5%–95.6 % for VIS + NIR. Considerably better performance of the supervised classifiers for the HSI2 VIS data over the Pleiades data (OA = 74.8–83.4%) suggested the importance of spectral resolution over spectral range (VIS vs. VIS+ NIR) for the supervised methods. The unsupervised classifiers exhibited low accuracy for both HSI2 VIS and UAV VIS imagery (OA< 30.0%) while the overall accuracy for the HSI2 VIS+ NIR and Pleiades data ranged from 60.4%–78.4 % and 42.1%–66.4%, respectively, suggesting the importance of spectral range for the unsupervised classifiers.     

Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

The underwater swimming manipulator (USM) is a snake‐like, multi‐articulated, underwater robot that is equipped with thrusters. One of the main purposes of the USM is to act like an underwater floating base manipulator. As such, it is essential to achieve good station‐keeping and trajectory tracking performance for the USM by using the thrusters and by using the joints to attain the desired position and orientation of the head and tail of the USM. In this ‘paper, we propose a sliding mode control (SMC) law, specifically the super‐twisting algorithm with adaptive gains, for the trajectory tracking of the USM's centre of mass. A higher‐order sliding mode observer is proposed for state estimation. Furthermore, we show the ultimate boundedness of the tracking errors. We demonstrate the applicability of the proposed control law and show that it leads to better performance than a linear PD‐controller.     

Theory‐Guided Synthesis of a Metastable Lead‐Free Piezoelectric Polymorph

Many technologically critical materials are metastable under ambient conditions, yet the understanding of how to rationally design and guide the synthesis of these materials is limited. This work presents an integrated approach that targets a metastable lead‐free piezoelectric polymorph of SrHfO₃. First‐principles calculations predict that the previous experimentally unrealized, metastable P4mm phase of SrHfO₃ should exhibit a direct piezoelectric response (d₃₃) of 36.9 pC N^?1 (compared to d₃₃ = 0 for the ground state). Combining computationally optimized substrate selection and synthesis conditions lead to the epitaxial stabilization of the polar P4mm phase of SrHfO₃ on SrTiO₃. The films are structurally consistent with the theory predictions. A ferroelectric‐induced large signal effective converse piezoelectric response of 5.2 pm V^?1 for a 35 nm film is observed, indicating the ability to predict and target multifunctionality. This illustrates a coupled theory‐experimental approach to the discovery and realization of new multifunctional polymorphs.     

The growing complexity in invention process

Technological and design process complexities may pose challenges to engineering design and related outcomes through invention. Understanding the trends related to the complexity of inventions and invention processes is crucial for informing engineering design research and education for invention, but has not been formally developed in the design literature. Herein, we utilize a set of patent-based metrics, drawn from complex systems research and engineering design research, to detect various aspects of the complexity in invention processes. By an analysis of U.S. patents from 1975 to 2011, our results suggest that technology inventions have been increasingly (1) requiring larger teams and more distant collaboration, (2) integrating a growing base of prior technologies, and (3) delivering more systemic and integrative new technologies. These trends may positively reinforce each other so as to contribute to a continual growth of the complexity in invention processes. Individual productivity for invention is also in decline, as we measured from the patent data. These findings suggest the increasing importance of research, education and application of complex system analysis methods and tools to control and manage the complexity in invention processes.