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The expression of polysialic acid (polySia) on the neuronal cell adhesion molecule (NCAM) is called NCAM-polysialylation, which is strongly related to the migration and invasion of tumor cells and aggressive clinical status. Thus, it is important to select a proper drug to block tumor cell migration during clinical treatment. In this study, we proposed that lactoferrin (LFcinB11) may be a better candidate for inhibiting NCAM polysialylation when compared with CMP and low-molecular-weight heparin (LMWH), which were determined based on our NMR studies. Furthermore, neutrophil extracellular traps (NETs) represent the most dramatic stage in the cell death process, and the release of NETs is related to the pathogenesis of autoimmune and inflammatory disorders, with proposed involvement in glomerulonephritis, chronic lung disease, sepsis, and vascular disorders. In this study, the molecular mechanisms involved in the inhibition of NET release using LFcinB11 as an inhibitor were also determined. Based on these results, LFcinB11 is proposed as being a bifunctional inhibitor for inhibiting both NCAM polysialylation and the release of NETs. [ABSTRACT FROM AUTHOR]

A new method for automatic volume determination of loose engineering deposits (LEDs) using point clouds collected by terrestrial laser scanning is proposed. The method starts with a problem of lacking bottom surface point clouds when scanning LEDs, assuming that the bottom surface is flat, a spatial plane is generated based on the plane fitting to the bottom surface. Then the sample point cloud is projected on this fitted plane to construct the subface point clouds, which, together with the initial point cloud data, are stitched into complete point cloud data with good closure, integrity, and accuracy. The 3D surface model established by introducing the alpha shape algorithm calculates the volume, and the validation experiments on three soil mound models and one field experiment on LEDs with a minimum average error of only 1.69% fully validate the effectiveness and accuracy of the method. The encouraging results show that effective volume calculation can be performed on realistic LEDs using the proposed method. [ABSTRACT FROM AUTHOR]

Due to the complex mesostructure and components of composite active layers in lithium-ion battery (LIB) electrodes, coupled with the concentration-dependent material properties and eigenstrains, efficiently estimating the effective modulus of the active layers remains a great challenge. In this work, the classic Mori–Tanaka method is found to be unable to estimate the modulus of the active layer. By realizing the importance of the mesostructure feature, a rod-rod model is proposed. The resulting modulus is expressed analytically. It is shown that the rod-rod model can accurately estimate the modulus evolution of the active layer if the material properties of the components and the evolution of volume fractions are known in advance. Moreover, a simplified rod-rod model is also developed to reduce the complexity of the proposed method. By knowing the volume fractions at two arbitrary states of charge and subsequently determining two constants, the simplified model can estimate the modulus efficiently. Considering both its accuracy and its simplicity, the simplified rod-rod model is the most suitable for the estimation. Thus, the methods developed in this work provide a new perspective for analyzing the material properties of composite active layers in LIB electrodes. [ABSTRACT FROM AUTHOR]

The lyophylloid agarics are a group of ecologically highly diversified macrofungi, some of which are very popular edible mushrooms. However, we know little about lyophylloid species diversity in China. In this study, we described four new species from China: Lyophyllum atrofuscum, L. subalpinarum, L. subdecastes, and Ossicaulis sichuanensis. We conducted molecular phylogenetic analyses of Lyophyllaceae based on the nuclear ribosomal RNA gene (nLSU) and the internal transcribed spacer regions (ITS). Phylogenetic analyses by the maximum likelihood method and Bayesian inference showed that the four new species are unique monophyletic species. A key to the species of Lyophyllum from China and a key to Ossicaulis worldwide were given. [ABSTRACT FROM AUTHOR]

Grains located on different positions of the panicle differed in grain weight and quality performance, however, the comprehensive effect of sowing dates on physiological and quantitative characteristics of grains located on different positions still remains unclear. In this study, a field experiment was conducted with two japonica rice cultivars, Nanjing 9108 and Ningjing 7, under 3 sowing dates (S1, 30th April; S2, 30th May; S3, 30th June). Delayed sowing treatments increased before-heading mean temperature (Tmean), day temperature (Tday), night temperature (Tnight) and mean solar radiation (Smean) for 0.94 °C, 0.99 °C, 1.23 °C, and 1.04 MJ, respectively, while decreased growth duration (GD) for 13.4 days, with 30 days delaying sowing date. Elevated before heading thermal resources and shortened GD contributed to enlarged panicle size via enhancing number of grains on secondary branches (SG) and led to higher ratio of SG per unit area (SG%). Meanwhile, delayed sowing decreased after heading Tmean, Tday, Tnight and Smean by 0.84 °C, 1.23 °C, 1.13 °C, and 2.12 MJ, respectively, with 30 days delaying sowing, and further enhanced rice stickiness (ST), peak viscosity (PKV) and breakdown (BD), but suppressed hardness (HD), amylose content (AC), cold pasting viscosity (CPV), hot pasting viscosity (HPV) and setback (SB) of SG, whilst grains on primary branches (PG) di no significant differences. Elevated taste and cooking quality of SG under delayed sowing was regulated by slower grain filling rate, which is largely regulated by AGPase and GBSS. Compared to PG, SG has better physiochemical, texture properties and RVA profiles due to its slower starch biosynthesis. The above results suggested that physiological (starch biosynthesis of SG) and quantitative parameters (amount of SG) of the rice population should be referred simultaneously to improve rice cooking and taste quality. [ABSTRACT FROM AUTHOR]

Hypoxia not only plays a critical role in multiple disease conditions; it also influences the growth and development of cells, tissues and organs. To identify novel hypoxia-related mechanisms involved in cell and tissue growth, studying a precise hypoxia-sensitive time window can be an effective approach. Drosophila melanogaster has been a useful model organism for studying a variety of conditions, and we focused in this study on the life cycle stages of Drosophila to investigate their hypoxia sensitivity. When normoxia-grown flies were treated with 4% O2 at the pupa stage for 3, 2 and 1 day/s, the eclosion rates were 6.1%, 66.7% and 96.4%, respectively, and, when 4% O2 was kept for the whole pupa stage, this regimen was lethal. Surprisingly, when our hypoxia-adapted flies who normally live in 4% O2 were treated with 4% O2 at the pupa stage, no fly eclosed. Within the pupa stage, the pupae at 2 and 3 days after pupae formation (APF), when treated for 2 days, demonstrated 12.5 ± 8.5% and 23.6 ± 1.6% eclosion, respectively, but this was completely lethal when treated for 3 days. We conclude that pupae, at 2 days APF and for a duration of a minimum of 2 days, were the most sensitive to hypoxia. Our data from our hypoxia-adapted flies clearly indicate that epigenetic factors play a critical role in pupa-stage hypoxia sensitivity. [ABSTRACT FROM AUTHOR]

The beetle, of the order Coleoptera, possesses outstanding flight capabilities. After completing flight, they can fold their hindwings under the elytra and swiftly unfold them again when they take off. This sophisticated hindwing structure is a result of biological evolution, showcasing the strong environmental adaptability of this species. The beetle's hindwings can provide biomimetic inspiration for the design of flapping-wing micro air vehicles (FWMAVs). In this study, the Asian ladybird (Harmonia axyridis Pallas) was chosen as the bionic research object. Various kinematic parameters of its flapping flight were analyzed, including the flight characteristics of the hindwings, wing tip motion trajectories, and aerodynamic characteristics. Based on these results, a flapping kinematic model of the Asian ladybird was established. Then, three bionic deployable wing models were designed and their structural mechanical properties were analyzed. The results show that the structure of wing vein bars determined the mechanical properties of the bionic wing. This study can provide a theoretical basis and technical reference for further bionic wing design. [ABSTRACT FROM AUTHOR]

A major advantage of the use of passive sonar in the tracking multiple underwater targets is that they can be kept covert, which reduces the risk of being attacked. However, the nonlinearity of the passive Doppler and bearing measurements, the range unobservability problem, and the complexity of data association between measurements and targets make the problem of underwater passive multiple target tracking challenging. To deal with these problems, the cardinalized probability hypothesis density (CPHD) recursion, which is based on Bayesian information theory, is developed to handle the data association uncertainty, and to acquire existing targets' numbers and states (e.g., position and velocity). The key idea of the CPHD recursion is to simultaneously estimate the targets' intensity and the probability distribution of the number of targets. The CPHD recursion is the first moment approximation of the Bayesian multiple targets filter, which avoids the data association procedure between the targets and measurements including clutter. The Bayesian-filter-based extended Kalman filter (EKF) is applied to deal with the nonlinear bearing and Doppler measurements. The experimental results show that the EKF-based CPHD recursion works well in the underwater passive multiple target tracking system in cluttered and noisy environments. [ABSTRACT FROM AUTHOR]

The multilayer coextrusion process is known to be a reliable technique for the continuous fabrication of high-performance micro-/nanolayered polymeric products. Using laminar flow conditions to combine polymer pairs, one can produce multilayer films and composites with a large number of interfaces at the polymer-polymer boundary. Interfacial phenomena, including interlayer diffusion, interlayer reaction, interfacial instabilities, and interfacial geometrical confinement, are always present during multilayer coextrusion depending on the processed polymers. They are critical in defining the microstructural development and resulting macroscopic properties of multilayered products. This paper, therefore, presents a comprehensive review of these interfacial phenomena and illustrates systematically how these phenomena develop and influence the resulting physicochemical properties. This review will promote the understanding of interfacial evolution in the micro-/nanolayer coextrusion process while enabling the better control of the microstructure and end use properties. [ABSTRACT FROM AUTHOR]

Polysialic acid (polySia) is an unusual glycan that posttranslational modifies neural cell adhesion molecule (NCAM) proteins in mammalian cells. The up-regulated expression of polySia-NCAM is associated with tumor progression in many metastatic human cancers and in neurocognitive processes. Two members of the ST8Sia family of α2,8-polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST) both catalyze synthesis of polySia when activated cytidine monophosphate(CMP)-Sialic acid (CMP-Sia) is translocate into the lumen of the Golgi apparatus. Two key polybasic domains in the polySTs, the polybasic region (PBR) and the polysialyltransferase domain (PSTD) areessential forpolysialylation of the NCAM proteins. However, the precise molecular details to describe the interactions required for polysialylation remain unknown. In this study, we hypothesize that PSTD interacts with both CMP-Sia and polySia to catalyze polysialylation of the NCAM proteins. To test this hypothesis, we synthesized a 35-amino acid-PSTD peptide derived from the ST8Sia IV gene sequence and used it to study its interaction with CMP-Sia, and polySia. Our results showed for the PSTD-CMP-Sia interaction, the largest chemical-shift perturbations (CSP) were in amino acid residues V251 to A254 in the short H1 helix, located near the N-terminus of PSTD. However, larger CSP values for the PSTD-polySia interaction were observed in amino acid residues R259 to T270 in the long H2 helix. These differences suggest that CMP-Sia preferentially binds to the domain between the short H1 helix and the longer H2 helix. In contrast, polySia was principally bound to the long H2 helix of PSTD. For the PSTD-polySia interaction, a significant decrease in peak intensity was observed in the 20 amino acid residues located between the N-and C-termini of the long H2 helix in PSTD, suggesting a slower motion in these residues when polySia bound to PSTD. Specific features of the interactions between PSTD-CMP-Sia, and PSTD-polySia were further confirmed by comparing their 800 MHz-derived HSQC spectra with that of PSTD-Sia, PSTD-TriSia (DP 3) and PSTD-polySia. Based on the interactions between PSTD-CMP-Sia, PSTD-polySia, PBR-NCAM and PSTD-PBR, these findingsprovide a greater understanding of the molecular mechanisms underlying polySia-NCAM polysialylation, and thus provides a new perspective for translational pharmacological applications and development by targeting the two polysialyltransferases. [ABSTRACT FROM AUTHOR]

Smart agriculture utilizes Internet of Things (IoT) technologies to enable low-cost electrical conductivity (EC) sensors to support farming intelligence. Due to aging and changes in weather and soil conditions, EC sensors are prone to long-term drift over years of operation. Therefore, regular recalibration is necessary to ensure data accuracy. In most existing solutions, an EC sensor is calibrated by using the standard sensor to build the calibration table. This paper proposes SensorTalk3, an ensemble approach of machine learning models including XGBOOST and Random Forest, which can be executed at an edge device (e.g., Raspberry Pi) without GPU acceleration. Our study indicates that the soil information (both temperature and moisture sensor data) plays an important role in SensorTalk3, which significantly outperforms the existing calibration approaches. The MAPE of SensorTalk3 can be as low as 1.738%, compared to the 7.792% error of the original sensor. Our study indicates that when the errors of uncalibrated moisture and temperature sensors are not larger than 8.3%, SensorTalk3 can accurately calibrate EC. SensorTalk3 can perform model training during data collection at the edge node. When all training data are collected, AI training is also finished at the edge node. Such an AI training approach has not been found in existing edge AI approaches. We also proposed the dual-sensor detection solution to determine when to conduct recalibration. The overhead of this solution is less than twice the optimal detection scenario (which cannot be achieved practically). If the two non-standard sensors are homogeneous and stable, then the optimal detection scenario can be approached. Conventional methods require training calibration AI models in the cloud. However, SensorTalk3 introduces a significant advancement by enabling on-site transfer learning in the edge node. Given the abundance of farming sensors deployed in the fields, performing local transfer learning using low-cost edge nodes proves to be a more cost-effective solution for farmers. [ABSTRACT FROM AUTHOR]

Simple Summary: Proton beam therapy delivered via pencil beam scanning is an advanced method for treating cancer. Two types of scanning modes are available for this method: discrete spot scanning (DSS) and continuous scanning. Continuous scanning has some advantages over DSS including improved proton beam delivery efficiency and reduced delivery time. However, continuous scanning delivers a dose between consecutive spots, and currently commercially available treatment planning systems do not account for this. Consequently, the continuous scanning delivered dose is inherently different from the planned one, which is discrete spot based. We conducted a proof-of-concept study of the ability of a prediction model to reduce the dose discrepancy between continuous scanning and discrete spot plan. Our findings suggest that selecting planning parameters with the prediction model reduces the dose discrepancy and therefore may permit relaxed dose delivery constraint, which further improves the benefits of continuous scanning. Pencil beam scanning delivered with continuous scanning has several advantages over conventional discrete spot scanning. Such advantages include improved beam delivery efficiency and reduced beam delivery time. However, a move dose is delivered between consecutive spots with continuous scanning, and current treatment planning systems do not take this into account. Therefore, continuous scanning and discrete spot plans have an inherent dose discrepancy. Using the operating parameters of the state-of-the-art particle therapy system, we conducted a proof-of-concept study in which we systematically generated 28 plans for cubic targets with different combinations of plan parameters and simulated the dose discrepancies between continuous scanning and a planned one. A nomograph to guide the selection of plan parameters was developed to reduce the dose discrepancy. The effectiveness of the nomograph was evaluated with two clinical cases (one prostate and one liver). Plans with parameters guided by the nomograph decreased dose discrepancy than those used standard plan parameters. Specifically, the 2%/2 mm gamma passing rate increased from 96.3% to 100% for the prostate case and from 97.8% to 99.7% for the liver case. The CTV DVH root mean square error decreased from 2.2% to 0.2% for the prostate case and from 1.8% to 0.9% for the liver case. The decreased dose discrepancy may allow the relaxing of the delivery constraint for some cases, leading to greater benefits in continuous scanning. Further investigation is warranted. [ABSTRACT FROM AUTHOR]

In this paper, an effective method for preparing poly (p-phenylene terephthalamide) -co- poly (dodecanedioyl) decylamine (PA10T/1012)/graphene oxide (GO) composites by pre-dispersion and one-step in situ polymerization was proposed for the first time. During the process of polycondensation, the condensation between the terminal amino groups of PA10T/1012 chains and the oxygen-containing functional groups of GO allowed nylon to be grafted onto graphene sheets. The effects of polymer grafting on the thermal and mechanical properties of (PA10T/1012)/GO composites were studied in detail. Due to the interaction between PA10T/1012 grafted graphene sheets and its matrix, GO is well dispersed in the PA10T/1012 matrix and physically entangled with it, forming a cross-linked network structure of polymer bridged graphene, thus obtaining enhanced tensile strength, tensile modulus and impact strength. More importantly, benefiting from the cross-linked network structure, the heat distortion temperature (HDT) of the composite is greatly increased from 77.3 °C to 144.2 °C. This in situ polycondensation method opens a new avenue to prepare polycondensate graphene-based composites with high strength and high heat distortion temperatures. [ABSTRACT FROM AUTHOR]

Background: Patients with Crohn's disease (CD) undergoing bowel resection often suffer from depression and acute pain, which severely impairs their recovery. We aimed to investigate the effects of S-ketamine preconditioning on postoperative depression in patients with CD undergoing a bowel resection with mild to moderate depression and to observe whether it can relieve postoperative pain and anti-inflammation. Methods: A total of 124 adult patients were randomized into one of the two groups. Patients in the S-ketamine group received a 0.25 mg/kg S-ketamine intravenous drip under general anesthesia induction, followed by a continuous infusion of S-ketamine with 0.12 mg/kg/h for more than 30 min through target-controlled infusion. Patients in the placebo group received 0.9% saline at an identical volume and rate. The primary outcome measure was the 17-item Hamilton depression Scale (HAMD-17). The secondary outcomes were scores on the following questionnaires: a nine-item patient health questionnaire (PHQ-9); a quality of recovery (QoR-15) form; and a numeric rating scale (NRS). Additional secondary outcomes included the levels of C-reactive protein (CRP) and interleukin 6 (IL-6) on postoperative days (PODs) 1, 3, and 5, the length of hospital stay, and opioid use throughout the hospital stay. Results: The scores of PHQ-9 and HAMD-17 in the S-ketamine group were lower than those in the placebo group on postoperative days (PODs) 1, 2, and 7 (p < 0.05). The scores of QoR-15 in the S-ketamine group were higher than those in the placebo group on postoperative days (PODs) 3 and 5 (p < 0.05). The NRS scores of PACU, postoperative days 1 and 2 in the S-ketamine group were lower than those in the placebo group (p < 0.05). There was no significant difference in the CRP and IL-6 levels on postoperative days (PODs) 1, 3, and 5, postoperative complications, and hospital stay between the two groups (p > 0.05). Conclusions: The trial indicated that the intraoperative administration of low-dose S-ketamine could alleviate mild-to-moderate depressive symptoms and postoperative pain in patients with Crohn's disease undergoing bowel resection without worsening their safety. [ABSTRACT FROM AUTHOR]

Not enough attention has been paid to the comparison in yield performance and N responsiveness between hybrid rice and inbred rice using the large number of new cultivars released after 2000 under machine transplanting. Field experiments were conducted in 2017 and 2018; 48 widely planted rice cultivars included four groups, namely indica hybrids (IHs), japonica inbreds (JIs), indica-japonica hybrids (IJHs), and indica inbreds (IIs) that were transplanted by machine with three nitrogen fertilizer levels (0, 150, 300 kg ha−1). The average yield of the hybrids (IHs, IJHs) was higher than that of JIs or IIs with a higher crop-growing rate (CGR) during the total growth duration, regardless of the N application level; moreover, longer total growth duration was responsible for the higher yield in IJHs than in IHs. The IHs had a large gap yield which mainly came from the genetic improvement in the CGR during the grain-filling stage. The yield gap was relatively small in JIs, and longer growth duration combined with optimal daily mean temperature during the grain-filling stage was the critical factor for high yield. The JIs or IJHs had higher yield under the N300 level, while the response of IHs to nitrogen varied with different cultivars. Cultivars with higher CGR during the grain-filling stage had higher yield under the N300 level. In conclusion, this study suggests that high CGR during the grain-filling stage may be a vital trait for the development of rice with high yield and high N responsiveness at machine transplanting. [ABSTRACT FROM AUTHOR]

Owing to the complexity of the climate system and limitations of numerical dynamical models, machine learning based on big data has been used for climate forecasting in recent years. In this study, we attempted to use an artificial neural network (ANN) for summer precipitation forecasts in the Yangtze-Huaihe River Basin (YHRB), eastern China. The major ANN employed here is the standard backpropagation neural network (BPNN), which was modified for application to the YHRB. Using the analysis data of precipitation and the predictors/factors of atmospheric circulation and sea surface temperature, we calculated the correlation coefficients between precipitation and the factors. In addition, we sorted the top six factors for precipitation forecasts. In order to obtain accurate forecasts, month (factor)-to-month (precipitation) forecast models were applied over the training and validation periods (i.e., summer months over 1979–2011 and 2012–2019, respectively). We compared the standard BPNN with the BPNN using a genetic algorithm-based backpropagation (GABP), support vector machine (SVM) and multiple linear regression (MLR) for the summer precipitation forecast after the model training period, and found that the GABP method is the best among the above methods for precipitation forecasting, with a mean absolute percentage error (MAPE) of approximately 20% for the YHRB, which is substantially lower than the BPNN, SVM and MLR values. We then selected the best summer precipitation forecast of the GABP month-to-month models by summing up monthly precipitation, in order to obtain the summer scale forecast, which presents a very successful performance in terms of evaluation measures. For example, the basin-averaged MAPE and anomaly rate reach 4.7% and 88.3%, respectively, for the YHRB, which can be a good recommendation for future operational services. It appears that sea surface temperatures (SST) in some key areas dominate the factors for the forecasts. These results indicate the potential of applying GABP to summer precipitation forecasts in the YHRB. [ABSTRACT FROM AUTHOR]

Under increased greenhouse gas (GHG) forcing, climate models tend to project a warmer sea surface temperature in the eastern equatorial Pacific than in the western equatorial Pacific. This El Niño-like warming pattern may induce an increase in the projected occurrence frequency of extreme El Niño events. The current models, however, commonly suffer from an excessive westward extension of the equatorial Pacific cold tongue accompanied by insufficient equatorial western Pacific precipitation. By comparing the Representative Concentration Pathway (RCP) 8.5 experiments with the historical simulations based on the Coupled Model Intercomparison Project phase 5 (CMIP5), a "present–future" relationship among climate models was identified: models with insufficient equatorial western Pacific precipitation error would have a weaker mean El Niño-like warming pattern as well as a lower increase in the frequency of extreme El Niño events under increased GHG forcing. Using this "present–future" relationship and the observed precipitation in the equatorial western Pacific, this study calibrated the climate projections in the tropical Pacific. The corrected projections showed a stronger El Niño-like pattern of mean changes in the future, consistent with our previous study. In particular, the projected increased occurrence of extreme El Niño events under RCP 8.5 forcing are underestimated by 30–35% in the CMIP5 multi-model ensemble before the corrections. This implies an increased risk of the El Niño-related weather and climate disasters in the future. [ABSTRACT FROM AUTHOR]

γ-Glutamyl transpeptidase (GGT) catalyzes the transfer of glutathione's γ-glutamyl group and related γ-glutamyl amides to water, amino acids or peptides, and utilizes a conserved Thr residue to process its own polypeptide chain into a large and a small subunit that then assemble to produce a catalytically competent enzyme. In this study, the magnetic cross-linked enzyme aggregates (mCLEAs) of a transpeptidase-specialized variant (N450D) of Bacillus licheniformis GGT were successfully prepared with optimized process parameters viz.1.25:1 (v/v) of isopropanol to N450D (0.3 mg/mL) ratio/0.02:1 (w/w) of enzyme to 3-aminopropyl triethoxysilane (APTES)-coated magnetic nanoparticle ratio/20 mM of glutaraldehyde. The prepared magnetic nanoparticles and immobilized enzyme (N450D-mCLEAs) were characterized by X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy, field-emission scanning electron microscope integrated with energy dispersive X-ray spectroscopy (FESEM/EDS), and superparamagnetic analysis. As compared with free enzyme, N450D-mCLEAs displayed significantly higher heat resistance at temperatures of 55 and 60 °C, and had a greater stability over a storage period of one month. The immobilized enzyme could also be reused for 10 consecutive biocatalytic cycles with no significant reduction in the percent yield of l-theanine. Conclusively, this immobilization strategy surely provides a meaningful glance of developing N450D-mediated biocatalysis for the production of physiologically important γ-glutamyl compounds. [ABSTRACT FROM AUTHOR]

An understanding of the structural evolution in micro-/nano-layer co-extrusion process is essential to fabricate high-performance multilayered products. Therefore, in this work, we reveal systematically the multiscale structural development, involving both the layer architecture and microstructure within layers of micro-/nano-layer coextruded polymer films, as well as its relationship to dielectric properties, based on poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)/polycarbonate (PC) system. Interestingly, layer architecture and morphology show strong dependences on the nominal layer thicknesses. Particularly, with layer thickness reduced to nanometer scale, interfacial instabilities triggered by viscoelastic differences between components emerge with the creation of micro-droplets and micro-sheets. Films show an enhanced crystallization with the formation of two-dimensional (2D) spherulites in microlayer coextruded systems and the oriented in-plane lamellae in nanolayer coextruded counterparts, where layer breakup in the thinner layers further changes the crystallization behaviors. These macro- and microscopic structures, developed from the co-extrusion process, substantially influence the dielectric properties of coextruded films. Mechanism responsible for dielectric performance is further proposed by considering these effects of multiscale structure on the dipole switching and charge hopping in the multilayered structures. This work clearly demonstrates how the multiscale structural evolution during the micro-/nano-layer coextrusion process can control the dielectric properties of multilayered products. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is an important parameter that affects the water cycle, environmental changes, and energy balance at global and regional scales. Herein, a time series analysis was conducted to estimate the monthly, seasonal, and interannual variations in LST during 2001–2019 in the Tarim Basin, China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, air temperature, air pressure, relative humidity, wind speed, precipitation, elevation, and land-cover type data, we analyzed the spatio-temporal change characteristics of LST and the influencing factors. High LSTs occurred in the desert and plains and low LSTs occurred in surrounding mountain regions. The highest LST was recorded in July (25.1 °C) and the lowest was in January (−9.5 °C). On a seasonal scale, LST decreased in the order: summer > spring > autumn > winter. Annual LST showed an increasing trend of 0.2 °C/10 a in the desert and mountain areas, while the plains indicated a decreasing trend. In spring and autumn, western regions were dominated by a downward trend, whereas in winter a downward trend occurred in eastern regions. In summer, areas covered by vegetation were dominated by a downward trend, and desert and bare lands were dominated by an upward trend. Random forest (RF) model analysis showed that elevation was the most significant influencing factor (22.1%), followed by mean air temperature (20.1%). Correlation analysis showed that the main climatic factors air temperature, relative humidity, and elevation have a good correlation with the LST. Land-cover type also affected LST; during February–December the lowest LST was observed for permanent glacier snow and the highest was observed in the desert. El Nino and La Nina greatly influenced the LST variations. The North Atlantic Oscillation and Pacific Decadal Oscillation indices were consistent with the mean LST anomaly, indicating their considerable influence on LST variations. [ABSTRACT FROM AUTHOR]

This paper proposes a new stochastic model updating method to update structural models based on the improved cross-model cross-mode (ICMCM) technique. This new method combines the stochastic hybrid perturbation-Galerkin method with the ICMCM method to solve the model updating problems with limited measurement data and uncertain measurement errors. First, using the ICMCM technique, a new stochastic model updating equation with an updated coefficient vector is established by considering the uncertain measured modal data. Then, the stochastic model updating equation is solved by the stochastic hybrid perturbation-Galerkin method so as to obtain the random updated coefficient vector. Following that, the statistical characteristics of the updated coefficients can be determined. Numerical results of a continuous beam show that the proposed method can effectively cope with relatively large uncertainty in measured data, and the computational efficiency of this new method is several orders of magnitude higher than that of the Monte Carlo simulation method. When considering the rank deficiency, the proposed stochastic ICMCM method can achieve more accurate updating results compared with the cross-model cross-mode (CMCM) method. An experimental example shows that the new method can effectively update the structural stiffness and mass, and the statistics of the frequencies of the updated model are consistent with the measured results, which ensures that the updated coefficients are of practical significance. [ABSTRACT FROM AUTHOR]

Al matrix composite, reinforced with the in situ synthesized 3C–SiC, MgAl2O4, and MgO grains, was produced via the casting process using phenolic resin pyrolysis products in flash mode. The contents and microstructure of the composites' fracture characteristics were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Mechanical properties were tested by universal testing machine. Owing to the strong propulsion formed in turbulent flow in the pyrolysis process, nano-ceramic grains were formed in the resin pyrolysis process and simultaneously were homogeneously scattered in the alloy matrix. Thermodynamic calculation supported that the gas products, as carbon and oxygen sources, had a different chemical activity on in situ growth. In addition, ceramic (3C–SiC, MgAl2O4, and MgO) grains have discrepant contents. Resin pyrolysis in the molten alloy decreased oxide slag but increased pores in the alloy matrix. Tensile strength (142.6 ± 3.5 MPa) had no change due to the cooperative action of increased pores and fine grains; the bending and compression strength was increasing under increased contents of ceramic grains; the maximum bending strength was 378.2 MPa in 1.5% resin-added samples; and the maximum compression strength was 299.4 MPa. Lath-shaped Si was the primary effect factor of mechanical properties. The failure mechanism was controlled by transcrystalline rupture mechanism. We explain that the effects of the ceramic grains formed in the hot process at the condition of the resin exist in mold or other accessory materials. Meanwhile, a novel ceramic-reinforced Al matrix was provided. The organic gas was an excellent source of carbon, nitrogen, and oxygen to in situ ceramic grains in Al alloy. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polycarbonate (CF/PC) composites have attracted attention for their excellent performances. However, their performances are greatly affected by environmental factors. In this work, the composites were exposed to hydrothermal aging to investigate the effects of a hot and humid environment. The mechanical properties of CF/PC composites with different aging times (0, 7, 14, 21, 28, 35, and 42 days) were analyzed. It was demonstrated that the storage modulus of CF/PC composites with hot water aged for seven days has the highest value in this sampling period and frequency. Through the solid particle erosion experiment, it was found that the hydrothermal aging causes the deviation of the maximum erosion angle of composites, indicating the composites underwent ductile–brittle transformation. Furthermore, the crack and cavity resulting from the absorption of water was observed via the scanning electron microscope (SEM). This suggested that the hydrothermal aging leads to the plasticization and degradation of CF/PC composites, resulting in a reduction of corrosion resistance. [ABSTRACT FROM AUTHOR]