Numerical simulation of heat transfer properties of large-sized biomass particles during pyrolysis process.

During the pyrolysis process of large particles, the conduction between particles cannot be ignored. In the present work, a numerical simulation model for the pyrolysis of biomass particles was established, which takes into account the conduction within the particles. Based on this model, the temperature distribution inside the particle during the pyrolysis process was determined and the effects of particle size, moisture content, and gas velocity on heat transfer characteristics were analyzed. The results showed that the temperatures at different positions of the particles along the inflow direction were quite different, and the maximum temperature difference inside the particles was about 146.7 K for a particle diameter of 10 mm and a velocity of 0.2 m/s. During the pyrolysis process of biomass particles, there were two peaks of Nusselt number. The increase of moisture content prolonged the pyrolysis time. The pyrolysis. time of particles with moisture content of 15 % was about 1.5 times longer than that of dry particles when the particle diameter was 10 mm. Increasing the particle size decreased the difference between the two peaks and increased the time interval between the two peaks. Increasing the gas velocity can improve the heat transfer, but the effect of too high gas velocity on improving the heat transfer is limited. The present study is of great importance for a detailed understanding of the pyrolysis process of biomass particles.

Deep learning for fast denoising filtering in ultrasound localization microscopy.

Objective.Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. However, previous image-denoising methods (e.g. block-matching 3D, BM3D) requires long data processing times, making ULM only able to be processed offline. This work introduces a new way to reduce data processing time through deep learning.Approach.In this study, we propose deep learning (DL) denoising based on contrastive semi-supervised network (CS-Net). The neural network is mainly trained with simulated MBs data to extract MB signals from noise. And the performances of CS-Net denoising are evaluated in bothin vitroflow phantom experiment andin vivoexperiment of New Zealand rabbit tumor.Main results.Forin vitroflow phantom experiment, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of single microbubble image are 26.91 dB and 4.01 dB, repectively. Forin vivoanimal experiment , the SNR and CNR were 12.29 dB and 6.06 dB. In addition, single microvessel of 24µm and two microvessels separated by 46µm could be clearly displayed. Most importantly,, the CS-Net denoising speeds forin vitroandin vivoexperiments were 0.041 s frame-1and 0.062 s frame-1, respectively.Significance.DL denoising based on CS-Net can improve the resolution of SR-US as well as reducing denoising time, thereby making further contributions to the clinical real-time imaging of ULM.

Individualized prediction of trait self-control from whole-brain functional connectivity.

Self-control is a core psychological construct for human beings and it plays a crucial role in the adaptation to society and achievement of success and happiness for individuals. Although progress has been made in behavioral studies examining self-control, its neural mechanisms remain unclear. In this study, we employed a machine-learning approach-relevance vector regression (RVR) to explore the potential predictive power of intrinsic functional connections to trait self-control in a large sample (N = 390). We used resting-state functional MRI (fMRI) to explore whole-brain functional connectivity patterns characteristic of 390 healthy adults and to confirm the effectiveness of RVR in predicting individual trait self-control scores. A set of connections across multiple neural networks that significantly predicted individual differences were identified, including the classic control network (e.g., fronto-parietal network (FPN), salience network (SAL)), the sensorimotor network (Mot), and the medial frontal network (MF). Key nodes that contributed to the predictive model included the dorsolateral prefrontal cortex (dlPFC), middle frontal gyrus (MFG), anterior cingulate and paracingulate gyri, inferior temporal gyrus (ITG) that have been associated with trait self-control. Our findings further assert that self-control is a multidimensional construct rooted in the interactions between multiple neural networks.

Progress and perspectives of enzymatic preparation of human milk fat substitutes.

Human milk fat substitutes (HMFS) with triacylglycerol profiles highly similar to those of human milk fat (HMF) play a crucial role in ensuring the supply in infant nutrition. The synthesis of HMFS as the source of lipids in infant formula has been drawing increasing interest in recent years, since the rate of breastfeeding is getting lower. Due to the mild reaction conditions and the exceptionally high selectivity of enzymes, lipase-mediated HMFS preparation is preferred over chemical catalysis especially for the production of lipids with desired nutritional and functional properties. In this article, recent researches regarding enzymatic production of HMFS are reviewed and specific attention is paid to different enzymatic synthetic route, such as one-step strategy, two-step catalysis and multi-step processes. The key factors influencing enzymatic preparation of HMFS including the specificities of lipase, acyl migration as well as solvent and water activity are presented. This review also highlights the challenges and opportunities for further development of HMFS through enzyme-mediated acylation reactions.

Intelligence correlates with the temporal variability of brain networks.

Intelligence is the ability to recognize and understand objective things, and use knowledge and experience to solve problems. Highly intelligent people show the ability to switch between different thought patterns and shift their mental focus. This suggests a link between intelligence and the dynamic interaction of brain networks. Thus, we investigated the relationships between resting-state dynamic brain network remodeling (temporal variability) and scores on the Wechsler Adult Intelligent Scale using a large dataset comprising 606 individuals. We found that performance intelligence was associated with greater temporal variability in the functional connectivity patterns of the dorsal attention network. High variability in these areas indicates flexible connectivity patterns, which may contribute to cognitive processes such as attention selection. In addition, performance intelligence was related to greater temporal variability in the functional connectivity patterns of the salience network. Thus, this study revealed a close relationship between performance intelligence and high variability in brain networks involved in attentional choice, spatial orientation, and cognitive control.

Effects of trans-resveratrol on hypertension-induced cardiac hypertrophy using the partially nephrectomized rat model.

trans-Resveratrol (resveratrol) has been shown to have beneficial effects on the cardiovascular system in a number of studies. It is, however, unclear whether this naturally occurring compound can protect against cardiac hypertrophy. The aim of the present study was to investigate the effects of resveratrol on cardiac hypertrophy in vivo and the potential underlying mechanisms involving endothelin (ET), angiotensin (Ang) II and nitric oxide (NO) in partially nephrectomized rats. Animal models bearing cardiac hypertrophy were replicated in male Sprague-Dawley rats following partial nephrectomy (PNX). Resveratrol (10 or 50 mg/kg) was administered to rats by gavage for 4 weeks. Simultaneous PNX and sham operation controls were simultaneously established in the present study. The systolic blood pressure (SBP) of rats was measured at baseline and, along with heart weight, after 4 weeks treatment. Serum ET-1, AngII and NO concentrations were determined. In the present study, it was shown that, compared with rats in the sham-operated group, rats in the PNX group had significantly higher SBP (154.1 +/- 22.7 mmHg), heart weight (1.69 +/- 0.24 g) and serum ET-1 (125.70 +/- 26.27 pg/mL) and AngII serum concentrations (743.63 +/- 86.50 pg/mL), whereas serum NO concentrations were lower (21.1 +/- 6.9 micromol/L; all P < 0.05). These values in the sham control group were 114 +/- 10 mmHg, 1.28 +/- 0.13 g, 52.44 +/- 21.85 pg/mL, 528.7 +/- 158.5 pg/mL and 53.21 +/- 23.87 micromol/L, respectively. After 4 weeks treatment with 50 mg/kg resveratrol, SBP, heart weight and ET-1 and AngII concentrations had decreased to 135.4 +/- 15.8 mmHg, 1.39 +/- 0.15 g, 97.11 +/- 26.74 pg/mL and 629.64 +/- 116.18 pg/mL, respectively. However, the serum NO concentration had increased to 40.1 +/- 14.6 micromol/L. These values were significantly different from those obtained for the PNX group. In conclusion, trans-resveratrol appears to be able to protect against the increase in SBP and subsequent cardiac hypertrophy in vivo and the mechanisms responsible may involve, at least in part, modulation of NO, AngII and ET-1 production.

[Preventive effect of trans-resveratrol on hypertension-induced cardiac hypertrophy in partially nephrectomized rats].

OBJECTIVE: To investigate the effect of trans-resveratrol on hypertension-induced cardiac hypertrophy and its potential mechanisms involving endothelin (ET), angiotensin II (AngII) and nitric oxide (NO). METHODS: Animal models bearing cardiac hypertrophy were replicated in male SD rats following partially nephrectomy (PNX). 10 mg/kg bw or 50 mg/kg bw of resveratrol was administered to rats by gavage, respectively, for 4 weeks. PNX control and sham-operation control (SHAM) were simultaneously established. Systolic pressure of rats was measured through tail at baseline and it, as well as heart weight, was measured after 4-week treatment. Serum ET-1 and AngII concentrations were determined using radioimmunological assay and NO using nitric acid reductase method. RESULTS: After 4-week treatment, animals in PNX control group had significantly higher systolic pressure and heart weight, higher ET-1 and AngII concentrations while lower NO concentrations, compared with those in SHAM group (P < 0.05). Rats treated with 50 mg/kg bw of resveratrol had significantly lower systolic pressure and heart weight, lower ET-1 concentrations while higher NO concentrations, compared with animals in PNX group (P < 0.05). CONCLUSION: Trans-resveratrol could protect against the increase of systonic pressure and subsequent cardiac hypertrophy in vivo, which mechanisms might, at least partly, involve with its modulation on NO, AngII and ET.