Effects of Prior Acute Exercise on Circulating Cytokine Concentration Responses to a High-fat Meal

High-fat meal consumption alters the circulating cytokine profile and contributes to cardiometabolic diseases. A prior bout of exercise can ameliorate the triglyceride response to a high-fat meal, but the interactive effects of exercise and high-fat meals on cytokines that mediate cardiometabolic risk are not fully understood. We investigated the effects of prior exercise on the responses of circulating tumor necrosis factor-a (TNF-a), interleukin-6 (IL-6), IL-8, leptin, retinol-binding protein 4 (RBP4), vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF), placental growth factor (PlGF), and soluble fms-like tyrosine kinase-1 (sFlt-1) to a high-fat meal. Ten healthy men were studied before and 4 h after ingestion of a high-fat meal either with or without ~50 min of endurance exercise at 70% of VO2 max on the preceding day. In response to the high-fat meal, lower leptin and higher VEGF, bFGF, IL-6, and IL-8 concentrations were evident (P \u3c 0.05 for all). There was no effect of the high-fat meal on PlGF, TNF-a, or RBP4 concentrations. We found lower leptin concentrations with prior exercise (P \u3c 0.05) and interactive effects of prior exercise and the high-fat meal on sFlt-1 (P \u3c 0.05). The high-fat meal increased IL-6 by 59% without prior exercise and 218% with prior exercise (P \u3c 0.05). In conclusion, a prior bout of endurance exercise does not affect all high-fat meal–induced changes in circulating cytokines, but does affect fasting or postprandial concentrations of IL-6, leptin, and sFlt-1. These data may reflect a salutary effect of prior exercise on metabolic responses to a high-fat meal

Drifting inwards in protoplanetary discs I Sticking of chondritic dust at increasing temperatures

Sticking properties rule the early phases of pebble growth in protoplanetary discs in which grains regularly travel from cold, water-rich regions to the warm inner part. This drift affects composition, grain size, morphology, and water content as grains experience ever higher temperatures. In this study we tempered chondritic dust under vacuum up to 1400 K. Afterwards, we measured the splitting tensile strength of millimetre-sized dust aggregates. The deduced effective surface energy starts out as $\gamma_e = 0.07\,\rm J/m^2$. This value is dominated by abundant iron-oxides as measured by M\"ossbauer spectroscopy. Up to 1250 K, $\gamma_e$ continuously decreases by up to a factor five. Olivines dominate at higher temperature. Beyond 1300 K dust grains significantly grow in size. The $\gamma_e$ no longer decreases but the large grain size restricts the capability of growing aggregates. Beyond 1400 K aggregation is no longer possible. Overall, under the conditions probed, the stability of dust pebbles would decrease towards the star. In view of a minimum aggregate size required to trigger drag instabilities it becomes increasingly harder to seed planetesimal formation closer to a star

Brood patch and sex-ratio observations indicate breeding provenance and timing in New Zealand storm petrel (Fregetta maoriana)

We used measurements of brood patch and moult status to estimate the breeding phenology of New Zealand Storm-Petrel, using birds caught at sea within the Hauraki Gulf Marine Park near Auckland, New Zealand. Birds caught October–January had completely downy brood patches, whereas birds caught February–April had bare brood patches with an observed male bias in the February sex-ratio, consistent with a female pre-laying exodus typical of petrels and with the existence of an unknown colony in the region. No birds captured exhibited primary moult, which is known to occur in storm-petrels during their non-breeding season. Our data support the conclusion that the New Zealand storm-petrel breeds during January–June in northern New Zealand and that field surveys for the species on offshore islands in this region during this period are warrante

State of AI-based monitoring in smart manufacturing and introduction to focused section

Over the past few decades, intelligentization, supported by artificial intelligence (AI) technologies, has become an important trend for industrial manufacturing, accelerating the development of smart manufacturing. In modern industries, standard AI has been endowed with additional attributes, yielding the so-called industrial artificial intelligence (IAI) that has become the technical core of smart manufacturing. AI-powered manufacturing brings remarkable improvements in many aspects of closed-loop production chains from manufacturing processes to end product logistics. In particular, IAI incorporating domain knowledge has benefited the area of production monitoring considerably. Advanced AI methods such as deep neural networks, adversarial training, and transfer learning have been widely used to support both diagnostics and predictive maintenance of the entire production process. It is generally believed that IAI is the critical technologies needed to drive the future evolution of industrial manufacturing. This article offers a comprehensive overview of AI-powered manufacturing and its applications in monitoring. More specifically, it summarizes the key technologies of IAI and discusses their typical application scenarios with respect to three major aspects of production monitoring: fault diagnosis, remaining useful life prediction, and quality inspection. In addition, the existing problems and future research directions of IAI are also discussed. This article further introduces the papers in this focused section on AI-based monitoring in smart manufacturing by weaving them into the overview, highlighting how they contribute to and extend the body of literature in this area

Fiber-Fed Laser-Heated Process for Printing Transparent Glass

This paper presents the Additive Manufacturing (AM) of glass using a fiber-fed process. Glass fiber with a diameter of 100 μm is fed into a laser generated melt pool. A CO2 laser beam is focused on the intersection between the fiber and the work piece which is positioned on a four-axis computer controlled stage. The laser energy at λ=10.6 μm is directly absorbed by the silica and locally heats the glass above the working point. By carefully controlling the laser power, scan speed, and feed rate, bubble free shapes can be deposited including trusses and basic lenses. Issues unique to the process are discussed, including the thermal breakdown of the glass, buckling of the fiber against an inadequately heated stiff molten region, and dimensional control when depositing viscous material