Discovering implicit intention-level knowledge from natural-language texts

In this paper, we propose a new approach to automatic discovery of implicit rhetorical information from texts based on evolutionary computation methods. In order to guide the search for rhetorical connections from natural-language texts, the model uses previously obtained training information which involves semantic and structural criteria. The main features of the model and new designed operators and evaluation functions are discussed, and the different experiments assessing the robustness and accuracy of the approach are described. Experimental results show the promise of evolutionary methods for rhetorical role discovery.     

Influence of pressurised cryogenic nitrogen technology on Arthrospira platensis (spirulina) preservation during storage

In this study, preservation of spirulina using the new pressurised cryogenic nitrogen technology (PCN) was compared to classical methods used in laboratories and industry. Spirulina morphology was better preserved by PCN compared to unpressurised cryogeny and classical freezing at −20 °C that led to cells fragmentation. A 25% loss of Phycocyanin-C content against 60% were measured after 98 days storage for 6-Bar PCN process and frozen samples, respectively. The Total AntiOxidant Power (PAOT Liquid Technology^®) was used for determination of total antioxidant and oxidant power of spirulina extracts. PAOT value of PCN samples was 50% higher than the frozen sample. From ABTS measurements on PCN spirulina fractions sonicated or not, it was suggested that pressurisation at 6 bars allowed a better preservation of free antioxidants (outside the cells) due to replacement of oxygen by nitrogen in the frozen beads. After dehydration, phycocyanin-C content variation during storage at 20 °C and 33% RH showed higher loss for freeze-dried spirulina treated at 0 compared to 6 Bars.     

Mathematical programming synthesis of non-isothermal water networks by using a compact/reduced superstructure and an MINLP model

The synthesis problems of non-isothermal water networks, combining heat exchanger network and water network (WN), usually consist of a significant number of constraints and variables, namely, flow rates, contaminant concentrations, temperatures and a large number of non-linear terms. In most cases, solving medium and large-scale synthesis problems is computationally too expensive and challenging. In order to circumvent that problem, we propose a compact superstructure and mixed-integer non-linear programming model for the simultaneous synthesis of non-isothermal WNs. The proposed superstructure includes heat integration stages enabling direct and indirect heat exchanges with a manageable number of hot and cold streams. This reduces the models size enabling easier solutions of the synthesis problems using local solvers. In addition, a superstructure reduction strategy is proposed making the superstructure flexible and adaptable for different types of problems, namely, pinched and threshold, and providing additional reduction of connections within the proposed superstructure. The proposed model is solved using a two-step solution strategy including initialisation and design steps. The model is applied to the examples of different complexities including single and multiple contaminant problems, and water-using and wastewater treatment units. Using the proposed iterative strategy, the improved locally optimal solutions are identified for most examples, minimising the total annual cost of the overall network.     

Protein Kinases and Parkinson’s Disease

Currently, the lack of new drug candidates for the treatment of major neurological disorders such as Parkinson’s disease has intensified the search for drugs that can be repurposed or repositioned for such treatment. Typically, the search focuses on drugs that have been approved and are used clinically for other indications. Kinase inhibitors represent a family of popular molecules for the treatment and prevention of various cancers, and have emerged as strong candidates for such repurposing because numerous serine/threonine and tyrosine kinases have been implicated in the pathobiology of Parkinson’s disease. This review focuses on various kinase-dependent pathways associated with the expression of Parkinson’s disease pathology, and evaluates how inhibitors of these pathways might play a major role as effective therapeutic molecules.     

Bisphenol S Impairs Invasion and Proliferation of Extravillous Trophoblasts Cells by Interfering with Epidermal Growth Factor Receptor Signaling

The placenta supports fetal growth and is vulnerable to exogenous chemical exposures. We have previously demonstrated that exposure to the emerging chemical bisphenol S (BPS) can alter placental endocrine function. Mechanistically, we have demonstrated that BPS interferes with epidermal growth factor receptor (EGFR) signaling, reducing placenta cell fusion. Extravillous trophoblasts (EVTs), a placenta cell type that aids with vascular remodeling, require EGF to invade into the maternal endometrium. We hypothesized that BPS would impair EGF-mediated invasion and proliferation in EVTs. Using human EVTs (HTR-8/SVneo cells), we tested whether BPS could inhibit the EGF response by blocking EGFR activation. We also evaluated functional endpoints of EGFR signaling, including EGF endocytosis, cell invasion and proliferation, and endovascular differentiation. We demonstrated that BPS blocked EGF-induced phosphorylation of EGFR by acting as a competitive antagonist to EGFR. Transwell assay and a three-dimensional microfluidic chip invasion assay revealed that BPS exposure can block EGF-mediated cell invasion. BPS also blocked EGF-mediated proliferation and endovascular differentiation. In conclusion, BPS can prevent EGF-mediated EVT proliferation and invasion through EGFR antagonism. Given the role of EGFR in trophoblast proliferation and differentiation during placental development, our findings suggest that maternal exposure to BPS may contribute to placental dysfunction via EGFR-mediated mechanisms.     

Association of digital cushion thickness with sole temperature measured with the use of infrared thermography

The main objective of this study was to investigate the association between digital cushion thickness and sole temperature measured by infrared thermography. Data were collected from 216 lactating Holstein cows at 4 to 10 d in milk (DIM). Cows were locomotion scored and sole temperature was measured after claw trimming (a minimum delay of 3 min was allowed for the hoof to cool) using an infrared thermography camera. Temperature was measured at the typical ulcer site of the lateral digit of the left hind foot. Immediately after the thermographic image was obtained, the thickness of the digital cushion was measured by ultrasonography. Rumen fluid samples were collected with a stomach tube and sample pH was measured immediately after collection. Additionally, a blood sample was obtained and used for measurements of serum concentrations of β-hydroxybutyrate (BHBA), nonesterified fatty acids (NEFA), and haptoglobin. To evaluate the associations of digital cushion thickness with sole temperature, a linear regression model was built using the GLIMMIX procedure in SAS software (SAS Institute Inc., Cary, NC). Sole temperature was the response variable, and digital cushion thickness quartiles, locomotion score group, rumen fluid pH, rumen fluid sample volume, environmental temperature, age in days, and serum levels of NEFA, BHBA, and haptoglobin were fitted in the model. Only significant variables were retained in the final model. Simple linear regression scatter plots were used to illustrate associations between sole temperature (measured by infrared thermography at the typical ulcer site) and environmental temperature and between NEFA and BHBA serum levels and haptoglobin. One-way ANOVA was used to compare rumen fluid pH for different locomotion score groups and for different digital cushion quartiles. Results from the multivariable linear regression model showed that sole temperature increased as locomotion scores increased and decreased as digital cushion thickness increased. These results were adjusted for environmental temperature, which was significantly associated with sole temperature. Serum levels of NEFA, BHBA, and haptoglobin were not associated with sole temperature. However, significant correlations existed between serum levels of NEFA and haptoglobin and between serum levels of BHBA and haptoglobin. Rumen fluid pH was not associated with either locomotion score or digital cushion thickness. In conclusion, we show here that digital cushion thickness was associated with sole temperature in cows at 4 to 10 DIM.     

Non-intrusive experimental investigation of flow behavior inside a 5 × 5 rod bundle with spacer grids using PIV and MIR

The validity of the simulation results from computational fluid dynamics (CFD) is still under scrutiny. Some existing CFD closure models for complex flow produce results that are generally recognized as being inaccurate. Development of improved models for complex flow simulation requires an improved understanding of the detailed flow structure evolution with dynamic interaction of the flow multi-scales. Thus, the goal of this work is to contribute to a better understanding of presupposed and existent events that could affect the safety of nuclear power plants. The fundamental phenomena of fluid flow in rod bundles with spacer grids can be elucidated by using state-of-the-art measurement techniques. This study aims to develop an experimental data base with high spatial and temporal resolution of fluid flow velocity inside a 5 × 5 rod bundles with spacer grids. The full-field detailed data base is intended to validate CFD codes at various temporal-spatial scales. Measurements are carried out using dynamic particle image velocimetry (DPIV) technique inside an optically transparent rod bundle utilizing the matching index of refraction (MIR) approach. This work presents full field velocity vectors and turbulence statistics for a rod bundle under single phase flow conditions.     

Parameter identification and computational simulation of polyurethane foaming process by finite pointset method

Numerical simulation of the polyurethane foaming process is a valuable method to analyze the molding process at an early stage of product development to shorten time-to-market cycles and cut costs by using fewer prototypes. However, this process involves highly coupled thermo-chemo-rheological modeling and needs adequate model parameters’ identification. A theoretical model including chemical reactions and thermo-rheological coupling of conservation equations was developed. Based on the theoretical model, three-dimensional numerical simulation for mold filling of the polyurethane foam was carried out by using Finite Pointset Method (FPM) to predict flow field, flow front advancement, temperature and density distributions during mold filling. A FOAMAT system was used to monitor foam height rise and reaction temperature on a cylindrical test tube and foam viscosity was measured by using a dynamic rotational rheometer with parallel-plate system. The parameters of the model were identified by an inverse analysis method which consists in determining the parameters by comparing the computed quantities to those measured experimentally. The overall modeling was validated by using short shot foams obtained with a panel mold cavity. Mold filling of an automotive underlay carpet cavity was investigated numerically. Flow front results were successfully compared to short shot foams obtained with the industrial mold cavity.     

Investigation of optical properties of iron, chromium, and nickel oxide based coatings

The reflectance behaviour of coatings obtained by chemical treatment of stainless steels are investigated with the help of a simple model. The spectral selectivity of solar absorbers and solar absorbance of whitened coatings can be explained and predicted taking chemical composition, texture and depth of the coatings into account. The model is effective in spite of the complexity of the material.     

Syntheses of 12-aminododecanoic and 11-aminoundecanoic acids from vernolic acid

12-Aminododecanoic acid and 11-aminoundecanoic acid, monomer precursors for nylon-12 and nylon-11, respectively, have been synthesized from vernolic (cis-12,13-epoxy-cis-9-octadecenoic) acid via a reaction sequence that includes the formation of 12-oxododecanoic acid oxime. Saponification of vernonia oil, followed by a low-temperature recrystallization at −20°C, gave 51% vernolic acid (97% purity, m.p. 23–25°C). Hydrogenation afforded cis-12,13-epoxystearic acid (m.p. 52–54°C, lit. m.p. 52–54°C), which upon oxidation with periodic acid in tertiary butyl alcohol gave 12-oxododecanoic acid with an isolated yield of 71.0%. Reaction of the oxoacid with hydroxylamine hydrochloride gave 12-oxododecanoic acid oxime, which was catalytically reduced to give 12-aminododecanoic acid with a yield greater than 85% and a melting point of 184–186°C (lit. m.p. 185–187°C). 11-Aminoundecanoic acid was prepared from the 12-oxododecanoic acid oxime via a three-step reaction sequence that involved a Beckmann rearrangement, Hofmann degradation, and hydrolysis. Thus, the aldoxime acid was hydrolyzed in the presence of nickel acetate tetrahydrate to give 11-carbamoylundecanoic acid (48% yield, m.p. 129–131°C, lit. m.p. 129–130°C). The amide was then treated with a solution of sodium methoxide and bromine at 70–80°C to give 11-(methoxycarbonylamino)undecanoic acid at 75% yield (m.p. 84–86°C; elemental analysis, calculated for C₁₃H₂₅NO₄: C, 60.19; H, 9.73; N, 5.40; O, 24.68%; found C, 60.02; H, 9.81; N, 5.26; O, 24.91%), which upon alkaline hydrolysis and subsequent neutralization gave 11-aminoundecanoic acid at 34% yield (m.p. 189–192°C, lit. m.p. 190°C). Mass spectrometric and ¹³C nuclear magnetic resonance data of the previously unreported 11-(methoxycarbonylamino)undecanoic acid is provided.