Explore the vast range of titles available.

The present study investigated the lipid oxidation degree of soybean oil during regularly discontinuous 40 h-deep-frying process. Electron spin resonance (ESR) spectroscopy technique was applied to identify and quantify the formed radicals, along with evaluation of physicochemical parameters including acid value (AV), peroxide value (PV), p-anisidine value (p-AnV), polar compounds (PC), fatty acid composition and volatile profile. Results showed the AV, p-AnV, PC and free radical of frying oil samples increased significantly with the increasing frying time. The results of fatty acids showed that unsaturated fatty acid such as C18:1 and C18:2 decreased by 19.98% and 14.58%, respectively, with prolonged frying time, while the content of C16:1, trans C18:1 and C18:2 increased by 20.38%, 425% and 42.86%, respectively, when compared to the fresh oil samples. In contrast, the content of saturated fatty acid had little change. In total, 37 volatile compounds were detected revealing a complex aroma profile of frying soybean oil, composed of 15 aldehydes, 8 alcohols, 4 ketones, 4 acids, 5 alkanes and 1 furan. Principal component analysis and hierarchical clustering analysis indicated that hexanal, heptanal, (E)-2-hexenal, octanal, (E)-2-heptenal, nonanal, (E)-2-octenal, undecanal, (E,E)-2,4-heptadienal, (E)-2-decenal, 2-undecenal, (E,E)-2,4-decadienal, 1-pentanol, 2,2-dimethyl-3-hexanol, (Z)-2-dodecenol, 1-octen-3-ol, pentanoic acid, octanoic acid, nonanoic acid and 2-pentyl-furan may be potential markers for evaluating lipid oxidation of frying soybean oil.

With the rapid development of the intelligent driving technology, achieving accurate path planning for unmanned vehicles has become increasingly crucial. However, path planning algorithms face challenges when dealing with complex and ever-changing road conditions. In this paper, aiming at improving the accuracy and robustness of the generated path, a global programming algorithm based on optimization is proposed, while maintaining the efficiency of the traditional A* algorithm. Firstly, turning penalty function and obstacle raster coefficient are integrated into the search cost function to increase the adaptability and directionality of the search path to the map. Secondly, an efficient search strategy is proposed to solve the problem that trajectories will pass through sparse obstacles while reducing spatial complexity. Thirdly, a redundant node elimination strategy based on discrete smoothing optimization effectively reduces the total length of control points and paths, and greatly reduces the difficulty of subsequent trajectory optimization. Finally, the simulation results, based on real map rasterization, highlight the advanced performance of the path planning and the comparison among the baselines and the proposed strategy showcases that the optimized A* algorithm significantly enhances the security and rationality of the planned path. Notably, it reduces the number of traversed nodes by 84%, the total turning angle by 39%, and shortens the overall path length to a certain extent.

The fuzzy controller is a popular choice for permanent magnet synchronous motor (PMSM) control systems because of its advantages, such as straightforward design, and no reliance on the precise mathematical model of the motor. But the existing pure PI-like fuzzy control strategy still has some disadvantages, such as poor adaptive ability and large overshooting. This work redevelops the structure and rules of the adaptive fuzzy controller, and proposes and proves an improved adaptive PI-like fuzzy control algorithm for the PMSM system. Firstly, a parallel dual fuzzy controller structure is constructed to facilitate the adaptive adjustment of the “PI-like fuzzy controller”. Secondly, the error acceleration parameter rv(k), which contains the PMSM speed information, is set and normalized to accurately identify the dynamic response stages of the PMSM system. Lastly, an adaptive fuzzy rule table is designed based on the dynamic response waveform of the PMSM system, and the control characterization is analyzed. The simulation and experimental results of the PMSM system show that the improved adaptive PI-like fuzzy controller has a broad dynamic adjustment range, the PMSM can rapidly and smoothly reach the given speed during the startup stage with small overshooting, the speed drop is low when the load is abruptly added, the PMSM system can quickly return to the steady state with a strong adaptive ability, and its dynamic performance indicators surpass those of the PID controller and traditional PI-like fuzzy controller.

Supercritical fluid carbon dioxide (SF-CO2) was used to extract oil from Elaeagnus mollis Diels (E. mollis Diels) seed and its antioxidant ability was also investigated. The effect of extraction pressure (20–35 MPa), extraction temperature (35–65 °C), extraction time (90–180 min) and seed particle size (40–100 mesh) on the oil yield were studied. An orthogonal experiment was conducted to determine the best operating conditions for the maximum extraction oil yield. Based on the optimum conditions, the maximum yield reached 29.35% at 30 MPa, 50 °C, 150 min, 80 mesh seed particle size and 40 g/min SF-CO2 flow rate. The E. mollis Diels seed (EDS) oil obtained under optimal SF-CO2 extraction conditions had higher unsaturated fatty acid content (91.89%), higher vitamin E content (96.24 ± 3.01 mg/100 g) and higher total phytosterols content (364.34 ± 4.86 mg/100 g) than that extracted by Soxhlet extraction (SE) and cold pressing (CP) methods. The antioxidant activity of the EDS oil was measured by DPPH and hydroxyl radical scavenging test. EDS oil extracted by different methods exhibited a dose-dependent antioxidant ability, with IC50 values of no significant differences. Based on the results of correlation between bioactive compounds, lupeol and γ-tocopherol was the most important antioxidant in EDS oil.

In this study, electron paramagnetic resonance (EPR) and gas chromatography-mass spectrometry (GC-MS) techniques were applied to reveal the variation of lipid free radicals and oxidized volatile products of four oils in the thermal process. The EPR results showed the signal intensities of linseed oil (LO) were the highest, followed by sunflower oil (SO), rapeseed oil (RO), and palm oil (PO). Moreover, the signal intensities of the four oils increased with heating time. GC-MS results showed that (E)-2-decenal, (E,E)-2,4-decadienal, and 2-undecenal were the main volatile compounds of oxidized oil. Besides, the oxidized PO and LO contained the highest and lowest contents of volatiles, respectively. According to the oil characteristics, an artificial neural network (ANN) intelligent evaluation model of free radicals was established. The coefficients of determination (R2) of ANN models were more than 0.97, and the difference between the true and predicted values was small, which indicated that oil profiles combined with chemometrics can accurately predict the free radical of thermal oxidized oil.

Given the complex powertrain of fuel cell electric vehicles (FCEVs) and diversified vehicle platooning synergy constraints, a control strategy that simultaneously considers inter-vehicle synergy control and energy economy is one of the key technologies to improve transportation efficiency and release the energy-saving potential of platooning vehicles. In this paper, an energy-oriented hybrid cooperative adaptive cruise control (eHCACC) strategy is proposed for an FCEV platoon, aiming to enhance energy-saving potential while ensuring stable car-following performance. The eHCACC employs a hybrid cooperative control architecture, consisting of a top-level centralized controller (TCC) and bottom-level distributed controllers (BDCs). The TCC integrates an eco-driving CACC (eCACC) strategy based on the minimum principle and random forest, which generates optimal reference velocity datasets by aligning the comprehensive control objectives of the platoon and addressing the car-following performance and economic efficiency of the platoon. Concurrently, to further unleash energy-saving potential, the BDCs utilize the equivalent consumption minimization strategy (ECMS) to determine optimal powertrain control inputs by combining the reference datasets with detailed optimization information and system states of the powertrain components. A series of simulation evaluations highlight the improved car-following stability and energy efficiency of the FCEV platoon.

Wheat germ (WG) is quite susceptible to deterioration due to the presence of lipase (LA) and lipoxygenase (LOX). Therefore it is indispensable to adopt a stabilization step to decrease the activity of LA and LOX while retaining a maximum level of nutrients. But over-drying can make foodstuffs more susceptible to autoxidation. So a stabilization protocol for inactivating LA and LOX of WG with a temperature- controlled short wave infrared (SIR) radiation system was adopted to retard its rancidity and retain a maximum level of fat-soluble nutrients. Meanwhile, the critical storage water activity (Aw) of WG for inhibiting both hydrolytic and oxidative rancidity was appraised. Results indicate that WG irradiated at 90°C for 20 min acquired the optimal stabilization effect, and its residual LA and LOX activity were 18.02% and 19.21%, respectively. At this condition, the free fatty acids (FFA) content and peroxide value (PV) increment of WG oil at 40°C remained below 5% and 2.24 meq O2/kg for 60 days, respectively. The residual Aw of this WG sample was 0.13, and it is near the Aw corresponding to its monolayer. No significant decrease of fatty acids was observed during SIR processing, while about 96.42% of its original tocopherols still retained in WG treated at 90°C for 20 min.

Type 2 diabetes (T2D) is a group of metabolic disorders characterized by chronic hyperglycemia and long-term carbohydrate, fat, and protein metabolism disruptions. This study aimed to identify biomarker of T2D and analyze immune cell infiltration in the islets of T2D patients. Using the GSE76895 dataset, 112 differentially expressed genes (DEGs) were identified between islet samples from T2D and non-diabetic (ND) individuals. Then, 112 DEGs were used for functional enrichment and Gene Set Enrichment Analyses (GSEA). Through the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), SLC2A2 emerged as the most likely candidate biomarker of T2D. Moreover, the distribution of tissue-infiltrating immune cells between T2D and ND islet samples was assessed using the CIBERSORT algorithm. The result revealed that resting CD4 + memory T cells might play an important role in T2D and exhibited a positive correlation with SLC2A2. Single-cell RNA sequencing (scRNA-seq) data indicated that SLC2A2 was highly expressed in beta cells of T2D islets and down-regulated in T2D group. Finally, in vivo studies confirmed decreased level of SLC2A2 expression in T2D models. To sum up, these findings highlight SLC2A2 as potential biomarkers, aiding early diagnosis and pharmaceutical advancements in T2D.

Ischemic stroke is a cerebrovascular disease that can cause long-term neurological impairment, dementia, or death. It is the third most common cause of disability and the second leading cause of death worldwide. The aim of this study was to explore the underlying molecular mechanisms and potentially effective therapeutic drugs for ischemic stroke. Single-cell seq data (GSE174574) were downloaded from the Gene Expression Omnibus (GEO) database, and dimensionality reduction clustering was performed after quality control. Eighteen cell clusters were identified, which were annotated into 9 cell types according to specific marker genes. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) enrichment analysis showed that apoptosis was significantly increased after ischemic brain injury, while p53 signaling pathway, TNF-a signaling pathway and mitogen-activated protein kinase (MAPK) signaling pathway may play an important role in ischemic stroke. Furthermore, Connectivity Map (CMap) analysis and molecular docking suggested that piperlongumine might be an effective drug for the treatment of ischemic stroke by binding to the proteins encoded by Actb and Cflar. Finally, in vitro and in vivo experiments conformed the effectiveness of piperlongumine. This study provided new ideas for the treatment of ischemic stroke.

Background Despite of the established effectiveness, the acceptance and adherence of cardiac rehabilitation (CR) remains sub-optimal. Mobile technologies are increasingly used in promoting CR without any firm evidence of their safety and efficacy. This systematic review and meta-analysis were aimed to assess the effect of mobile applications as an intervention for improving adherence to CR. Methods Relevant studies were searched in PubMed, the Cochrane Library, Embase and Web of Science from inception to 29th December 2018. Eligible studies were the ones which used mobile applications as a stand-alone intervention or as the primary component for the intervention directed at improving CR adherence, without any limitations on outpatient or home-based CR. Results Eight studies were eligible for the systematic review including four randomized controlled trials (RCTs) as well as four before-after studies of which only one had control group. Four RCTs and 185 patients in experimental group were included in meta-analysis, which had evaluated the effect of mobile health applications on CR completion and had reported that the adherence of patients using mobile applications was 1.4 times higher than the control group (RR = 1.38; CI 1.16 to 1.65; P  = 0.0003). Moreover, we also found mixed results in exercise capacity, mental health and quality of life. Conclusion The use of mobile applications for improving the adherence of the CR might be effective. However, it appears to be in the initial stage of implementing mobile applications in CR and more research is essential to validate their effectiveness.