An Oral Mixed Fat Load Is Followed by a Modest Anti-inflammatory Adipocytokine Response in Overweight Patients with Metabolic Syndrome

We investigated the postprandial changes in plasma levels of adipocytokines in overweight patients with metabolic syndrome after an oral fat load. After an oral fat load and during a prolonged fast, blood was drawn at 0, 2, 3, 4 and 8 h for measurement of adiponectin, adipsin, cathepsin S, chemerin, hepatic growth factor, interferon‐γ‐inducible protein‐10, leptin, macrophage chemoattractant protein‐1, macrophage migration inhibitory factor, nerve growth factor, retinol binding protein‐4, resistin, serum amyloid A1, tissue inhibitor of metalloproteinase‐1 and thrombopoietin using a microbead‐based Luminex assay. Area under the curves (AUC) were calculated and compared. Plasma adiponectin levels were higher after an oral fat load compared to fasting at t = 2 h (950 ± 513 vs. ?1,881 ± 713 ng/ml) while the plasma levels for adipsin (?9 ± 5 vs. 16 ± 5 ng/ml), chemerin (?122 ± 35 vs. 13 ± 21 ng/ml), SAA‐1 (?391 ± 213 vs. 522 ± 173 ng/ml) and TPO (?335 ± 144 vs. 622 ± 216 ng/ml) were lower after an oral fat load compared to fasting. The baseline corrected AUC for IP‐10 was higher after fat load compared to fasting (median ?116 pg h/ml; IQR ?270 to 10 vs. ?21 pg h/ml; IQR ?136 to 418 (p = 0.047). In conclusion, in overweight male subjects with the metabolic syndrome, an oral fat load is accompanied with a modest anti‐inflammatory response of adipose tissue‐derived adipocytokines.     

Evaluation of the effects of sodium chloride,potassium sorbate,nisin and lysozyme on the probability of growth of Clostridium sporogenes

The aim of this study was to evaluate the combined effect of salt (sodium chloride, 0–8% w/v), sorbate (potassium sorbate, 0–4.5% w/v), nisin (0–500 ppm) and lysozyme (0–500 ppm) on the survival of Clostridium sporogenes as a non‐toxigenic surrogate of Clostridium botulinum in terms of the probability of growth by using a central composite rotatable design. The results indicated that salt and sorbate were the most effective factors in preventing the growth of Cl. sporogenes in high‐moisture (>95%) and low‐acid conditions. The probability of growth of Cl. sporogenes in broth was reduced by combinations of salt and sorbate. Nisin and lysozyme had insignificant effects on the probability of growth of Cl. sporogenes (P > 0.05). Lysozyme individually and in combination with nisin had no inhibitory effect on Cl. sporogenes. Overall, the addition of sorbate and lysozyme may allow the salt concentration to be reduced while preventing growth.     

Advances in machine learning applications for scenario intelligence: deep learning

In this paper, we discuss the inextricable link between automating training environment adaptation and deep understanding of the context surrounding specific decisions and actions executed in the performance environment. To enable deep contextual understanding, psychological measurement strategies are needed to more accurately and rapidly model the psychologically meaningful details of the trainee's interactions with events, objects, and people in the training environment. As these interactions often entail complex, nonlinear cue-action relationships, the underlying models must effectively capture the nuance, complexity, and largely intuitive nature of human decision-making. This paper discusses the promise of an emerging field of machine learning – deep neural networks – for supporting this requirement.     

Sub-microsecond X-ray crystallography: techniques,challenges, and applications for materials science

Dynamics of crystals is a subject of recent interest in solid-state physics and a challenge for modern X-ray crystallography. Time-dependent response of solids to an external perturbation on atomic and microstructural length scales is the key to understanding many physical properties. This paper reviews the challenges and opportunities for probing of sub-micro-, micro-, and millisecond dynamics of solids using the methods of X-ray crystallography. It starts with an overview of recent time-resolved X-ray diffraction techniques. It then focuses on the processes that are important for understanding functional materials: dynamics of ferroelectric and ferroelastic domain patterns, texture in piezoelectric ceramics, mechanical resonances in solids, and dynamics of structural disorder. Knowledge available from macroscopic experiments is summarized, and opportunities for X-ray crystallography to resolve existing controversies are presented. This paper suggests the possible synergy of macroscopic and X-ray crystallographic experimental techniques.     

Biosorption performance,combustion behavior,and leaching characteristics of olive solid waste during the removal of copper and nickel from aqueous solutions

Several researchers have proved that agricultural by-products constitute good adsorbents for removing heavy metals from aqueous solution. However, few investigations have identified efficient strategies for the adsorbent′s regeneration. Hence, a global methodology for the removal of copper and nickel metals from wastewater including metal biosorption, thermal treatment and residual ash landfill is proposed. In order to validate this strategy, olive solid waste (OSW), provided by an olive oil mill from Tunisia, were used to remove copper and nickel on batch experiments. Copper and nickel were adsorbed on a monolayer of OSW surface with maximal adsorption capacity (q _max) of 3.6 and 1.7 mg g^?1, respectively. Contaminated OSW with copper and nickel were combusted at 850 °C in an electrical furnace. About 96 % of each metal was recovered in residual ashes that present a good secondary raw material for copper and nickel production. Low leaching transfers (≤4 %) were observed for copper and nickel from residual ashes leading to the possibility to be landfilled. Therefore, the suggested process can be used as an alternative to the classical technologies for effluent decontamination.     

Intergranular Oxidation of Nickel-Base Alloys: Potentialities of Focused Ion Beam Tomography

Oxidation of Metals - The present work focuses on the intergranular oxidation of Alloy 600 and its weld material Alloy 82 after exposure in simulated primary water at 340–360 °C...     

Experimental and numerical study of a modified ASTM C633 adhesion test for strongly-bonded coatings

When coatings are strongly bonded to their substrates it is often difficult to measure the adhesion values. The proposed method, which is suggested naming “silver print test”, consists in covering the central part of the samples with a thin layer of silver paint, before coating. The process used for testing this new method was the Air plasma spraying (APS), and the materials used were alumina coatings on C35 steel substrates, previously pre-oxidized in CO₂. The silver painted area was composed of small grains that did not oxidize but that significantly sintered during the APS process. The silver layer reduced the surface where the coating was linked to the substrate, which allowed its debonding, using the classical adhesion test ASTM C633-13, while the direct use of this test (without silver painting) led to ruptures inside the glue used in this test. The numerical modelling, based on the finite element method with the ABAQUS software, provided results in good agreement with the experimental measurements. This concordance validated the used method and allowed accessing to the values of adherence when the experimental test ASTM C633-13 failed, because of ruptures in the glue. After standardization, the “silver print test” might be used for other kinds of deposition methods, such as PVD, CVD, PECVD.     

A two-pronged approach for springback variability assessment using sparse polynomial chaos expansion and multi-level simulations

In this study, we show that stochastic analysis of metal forming process requires both a high precision and low cost numerical models in order to take into account very small perturbations on inputs (physical as well as process parameters) and to allow for numerous repeated analysis in a reasonable time. To this end, an original semi-analytical model dedicated to plain strain deep drawing based on a Bending-Under-Tension numerical model (B-U-T model) is used to accurately predict the influence of small random perturbations around a nominal solution estimated with a full scale Finite Element Model (FEM). We introduce a custom sparse variant of the Polynomial Chaos Expansion (PCE) to model the propagation of uncertainties through this model at low computational cost. Next, we apply this methodology to the deep drawing process of U-shaped metal sheet considering up to 8 random variables.