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We propose a nonlinear auto regressive neural network Markov model (NARMKM) to predict the annual Huizhou resident population, Guangdong resident population and elderly population in China, and improve the accuracy of population forecasting. The new model is built upon the traditional neural network model and utilized matrix perturbation theory to study the natural and response characteristics of a system when the structural parameters change slightly. The delay order and hidden layer number of neurons has a greater effect the prediction result of NAR neural network model. Therefore, we make full use of prior information to constrain and test when making predictions. We choose reasonable parameter settings to obtain more reliable prediction results. Three experiments are conducted to validate the high prediction accuracy of the NARMKM model, with mean absolute percentage error (MAPE), root mean square error (RMSE), STD and R2. These results demonstrate the superior fitting performance of the NARMKM model when compared to other six competitive models, including GM (1, 1), ARIMA, Multiple regression, FGM (1, 1), FANGBM and NAR. Our study provides a scientific basis and technical references for further research in the finance as well as population fields.

In this paper, we propose an optimal fractional-order accumulative Grey Markov model with variable parameters (FOGMKM (1, 1)) to predict the annual total energy consumption in China and improve the accuracy of energy consumption forecasting. The new model is built upon the traditional Grey model and utilized matrix perturbation theory to study the natural and response characteristics of a system when the structural parameters change slightly. The particle swarm optimization algorithm (PSO) is used to determine the number of optimal fractional order and nonlinear parameters. An experiment is conducted to validate the high prediction accuracy of the FOGMKM (1, 1) model, with mean absolute percentage error (MAPE) and root mean square error (RMSE) values of 0.51% and 1886.6, respectively, and corresponding fitting values of 0.92% and 6108.8. These results demonstrate the superior fitting performance of the FOGMKM (1, 1) model when compared to other six competitive models, including GM (1, 1), ARIMA, Linear, FAONGBM (1, 1), FGM (1, 1) and FOGM (1, 1). Our study provides a scientific basis and technical references for further research in the finance as well as energy fields and can serve well for energy market benchmark research.

Rail-cum-road truss bridges are rapidly developing, and frequent cracking in freshly poured concrete is of great concern. For the performance of such a load-bearing deck, it is necessary to understand its stress status due to short-term shrinkage. In this study, a newly constructed railway-cum-highway truss bridge in Guangdong Province was used to analyze the stress distribution in the concrete deck under short-term shrinkage. In-situ tests were performed to measure the shrinkage of one deck panel and two companion specimens shortly after the concrete pouring. It was found that the free shrinkage of companion specimens at 42 days was 140–150 microstrains, which was significantly higher than that indicated by current codes or standards. An exponential form of shrinkage development curve was proposed based on shrinkage test results. The measured shrinkage of the deck panel varied with locations, with a relatively large concrete shrinkage between grillages, reaching 45–55 microstrains at the end of the shrinkage test. The resulting mechanical strain due to restraints, taken as the difference in measured strains between the deck panel and companion specimen, was consistent with numerical simulation results, demonstrating the validity of the analysis method adopted. Under short-term shrinkage, the secondary tensile stress of 1.5–3.5 MPa was present in the deck above the main trusses and cross beams, triggering potential cracking. The stress is primarily attributed to the external restraint from connecting steel members, whose degree of restraint dramatically exceeds that of internal restraint from reinforcement. Although creep tends to reduce such shrinkage stress slightly, the effect of short-term shrinkage requires significant attention.

In this work, a novel optimal weighted combination Markov model (OWCMM) is proposed to forecast the public financial budget expenditure of Dongguan, China, from 2016 to 2020. The new model is constructed based on the optimal combination, which includes the fractional grey model, the Fourier function regression model and the autoregressive integrated moving average model (ARIMA), and modifies this optimal combination by the Markov model. The number of the optimal fractional order is determined by particle swarm optimization algorithm. One example is provided to verify the high fitting accuracy of the new model, the results show that the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the optimal weighted combination Markov model are smaller than that of the quadratic function model (QFM), the classical combinatorial model and its three sub-models, which proves the robustness of the optimal weighted combination Markov model. This work will provide a scientific basis and technical reference for the further research in finance field.

In this paper, a fractional opposite-direction accumulating nonlinear grey Bernoulli Markov model (FOANGBMKM) is established to forecast the annual GDP of Huizhou city from 2017 to 2021. The optimal fractional order number and nonlinear parameters of the model are determined by particle swarm optimization (PSO) algorithm. An experiment is provided to validate the high fitting accuracy of this model, and the effect of prediction is better than that of the other four competitive models such as autoregressive integrated moving average model (ARIMA), grey model (GM (1, 1)), fractional accumulating nonlinear grey Bernoulli model (FANGBM (1, 1)) and fractional opposite-direction accumulating nonlinear grey Bernoulli model (FOANGBM (1, 1)), which proves the robustness of the opposite-direction accumulating nonlinear Bernoulli Markov model. This research will provide a scientific basis and technical references for the economic planning industries.

Marigold oleoresin is an oil-soluble natural colorant mainly extracted from marigold flowers. Xinjiang of China, India, and Zambia of Africa are the three main production areas of marigold flowers. Therefore, this study utilized ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS) technology, combined with Global Natural Products Social Molecular Networking (GNPS) and multivariate statistical analysis, for the qualitative and discriminant analysis of marigold oleoresin obtained from three different regions. Firstly, 83 compounds were identified in these marigold oleoresin samples. Furthermore, the results of a principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) indicated significant differences in the chemical compositions of the marigold oleoresin samples from different regions. Finally, 12, 23, and 38 differential metabolites were, respectively, identified by comparing the marigold oleoresin from Africa with Xinjiang, Africa with India, and Xinjiang with India. In summary, these results can be used to distinguish marigold oleoresin samples from different regions, laying a solid foundation for further quality control and providing a theoretical basis for assessing its safety and nutritional aspects.

Fractional order imply the idea of "in between", the grey model generated by fractional accumulation has better prediction and adaptability than that generated by first-order accumulation. General grey model of the differential equation of the left is a cumulative function derivative of time, in order to improve the adaptability of the model and prediction ability, general fractional order differential equation model is presented. In this paper, on the basis of the derivation of time $ t $ extensions to the derivation of $ {t^u} $, added a variable coefficient, and through the integral differential equation and tectonic background value. We establish an optimized fractional order cumulative grey model with variable parameters, i.e., optimized fractional order accumulated grey model (FOGM (1, 1)). By using the Particle swarm optimization (PSO) algorithm, we search for the order and variable parameters of the optimal fractional order. Then we apply the proposed model to predict the total energy consumption of Jiangsu province and the consumption level of Chinese residents. The results indicate that the proposed model has high fitting and prediction accuracy compared to other classical grey prediction models, such as grey model (GM (1, 1)), non-homogeneous grey model (NGM (1, 1)) and fractional order accumulated grey model (FGM (1, 1)). It also validates that the proposed model is a practical and promising model for forecasting the energy consumption as well as the consumption level of Chinese residents.

Multi-metric indicators based on fish assemblages have been widely applied to assess aquatic ecosystem biotic integrity. However, many of these were not detailed or standardized in metrics selection and reference status for a reservoir ecosystem under the long-term effects of hydro-electrical dam development. This makes it very difficult to determine the reference status and metrics because fish assemblages have been affected by human activities such as large reservoir operations. Based on long-term fish assemblage data, there were significant differences in fish composition between backwater and reservoir areas 10 years after the Three Gorges Reservoir (TGR) formation in China. We conducted this study to develop a new fish index of biotic integrity (IBI) to evaluate a large river reservoir ecosystem based on long-term monitoring data by establishing subregional habitat reference and selecting sensitive and concise metrics. In the Three Gorges Reservoir, we found that: 1) dynamic change is an important feature of fish assemblages in a relatively dynamic state after a decade of intensive disturbance caused by reservoir operations; 2) reference conditions for the reservoir evaluation should be selected in different stages for two different ecological habitats (lotic backwater and lentic reservoir reaches); 3) two core metrics and five sensitive metrics were selected to reflect fish assemblage degradation based on long term observations; and 4) overall fish biological integrity is generally “fair-poor,” in the reservoir area it is “fair” and “poor,” and in the reservoir lotic backwater it is “fair.” The long-term effects of large canyon reservoirs on biological integrity require long-term observation, and reasonable recovery targets should be set at different stages in reservoir management. In this study, a new biological integrity index was developed to screen and evaluate the ecological status of a semi-artificial reservoir ecosystem. Our results support reservoir biologically integrated management and green sustainable development goals.

The summer hypoxia off the Changjiang Estuary is one of the largest coastal hypoxic systems in the world and has displayed spatial heterogeneity in recent years. Based on observation data in the summer of 2014, hypoxia was identified both in the bottom and mid-layers. Except for the typical bottom hypoxia in the submarine canyon, the subsurface oxygen minima (SOM) were captured in the mid-layer of 10~15 m, with lower dissolved oxygen in the mid-layer than at the bottom (30–50 m). This SOM phenomenon was located in the lower boundary of the pycnocline and above the Taiwan warm current (TWC) and Kuroshio subsurface water (KSSW). Due to the southern expansion of Changjiang diluted water (CDW), a high phytoplankton biomass (the maximum chlorophyll a of 25 μg L−1, pH of 8.6, and DO of 11 mg L−1) band occupied the surface area along 123°E. By analyzing the 24-h continuous observation and high-resolution profile data, we revealed that the subsurface oxygen minima were predominantly controlled by remineralization and bottom-flushing effects. Fast local consumption occurred near the pycnocline layer, while the lateral transport of oxygen-rich ambient water replenished the bottom oxygen deficit from south to north. We summarize and contextualize three hot spots of hypoxia into a conceptual diagram and emphasize the influences of advection, mixing, and respiration on their location and severity. Overall, compared with the discussion about the low DO background of TWC/KSSW, this research highlights the flushing effects of TWC/KSSW that will reshape the hypoxia structure and alleviate the hypoxia severity in the south hypoxia area off the Changjiang Estuary.

Wind mixing is important in regulating dissolved oxygen (DO) variability; however, the transect response of DO dynamics to wind disturbance has seldom been documented with field data. In the summer of 2017, repeat transect observations off the Changjiang Estuary were conducted throughout a fresh wind (the maximum wind speed was 9.8 m s–1) event to reveal the role of physical mixing and biological activity in DO variations. After the wind event, hypoxia was alleviated presenting as the hypoxia thickness decreased from 30 m to 20 m. However, poorly ventilated near-bottom hypoxia was aggravated with a further decrease in DO. Generally, the saturation of dissolved oxygen (DOs) in depth-integrated water column increased by 9%–49% through physical diffusion with a weakened stratification and enhanced phytoplankton bloom. However, in this case, the wind-induced physical water mass mixing by transporting DO downward had a limited contribution to the water-column DO budget, while upwards nutrients induced by mixing fueled the larger vertical area of algae bloom and subsequent substantial oxygen consumption. As the wind speed increased, the air-sea exchange would be important in supplying DO, especially in nearshore areas, which could effectively offset the DO deficiency. In summary, frequently occurring fresh wind-mixing events off the Changjiang Estuary would alleviate hypoxia in the water column but probably exacerbate hypoxia at the bottom, as determined by competing ventilation and respiration roles. Such complex interactions likely occur and perform differently as wind stress varies. Thus, high-spatial and long-term process observations are required to better understand the net effects of bottom hypoxia evolution.

Flood events significantly increase water discharges and terrigenous material inputs to coastal waters. Riverine nutrients in the Changjiang Estuary are transported by the dispersion of Changjiang Diluted Water (CDW) plumes and detached low-salinity water patches. However, the effects of flooding on nutrient offshore transports have not been well explored. Here, we present the nutrient conditions in the Changjiang Estuary and adjacent East China Sea in the historical flooding year 2020. Comparisons of nutrient distributions between flooding years, drought year and non-flooding years were also made. Our results showed that nitrate flux from the Changjiang River in August 2020 was 1.5 times that of the multi-year averaged flux in non-flooding years. Enormous riverine nutrient input resulted in much higher nutrient concentrations in the outer estuary than those in non-flooding years. In addition, a detached low-salinity water patch was observed, which made the salinity of the northern estuary even lower than that in the historical flooding year 1998. Surface dissolved inorganic nitrate (DIN) level in the low-salinity water patch was even ~16 times of that at nearby station in the drought year 2006. While phosphate (PO43−) concentrations were less than 0.1 μmol L−1 east of 123°E, which was probably caused by intensive biological uptake, as indicated by a high Chlorophyll a (Chl a) concentration (29.08 μg L−1). The depleted PO43− and high N/P of the low-salinity water patch suggested PO43− limitation even under flood conditions. A three end-member mixing model was adopted to identify the contributions of the CDW end-member (CDWend-member) and biological process to nutrient distributions. Our model results showed that the nutrient contribution of the CDWend-member to the estuary (122–124°E, 31–32.5°N) in flooding year 2020 was over double that in drought year 2006. Model-derived biological DIN uptake was as high as 24.65 μmol L−1 at the low-salinity water patch. Accordingly, the estimated net community production was 566–1131 mg C m−2 d−1 within the euphotic zone. The offshore transport of a low-salinity, high-DIN water patch during flooding could probably have a significant influence on biogeochemical cycles in the broad shelf, and even the adjacent Japan Sea.

The nitrate ion (NO3−) is a typical pollutant in environmental samples, posing a threat to the aquatic ecosystem and human health. Therefore, rapid and accurate detection of NO3− is crucial for both the aquatic sciences and government regulations. Here we report the fabrication of an amino-functionalized, vertically ordered mesoporous silica film (NH2-VMSF) confining localized copper nanoparticles (CuNPs) for the electrochemical detection of NO3−. NH2-VMSF-carrying amino groups possess an ordered perpendicular nanochannel structure and ultrasmall nanopores, enabling the confined growth of CuNPs through the electrodeposition method. The resulting CuNPs/NH2-VMSF-modified indium tin oxide (ITO) electrode (CuNPs/NH2-VMSF/ITO) combines the electrocatalytic reduction ability of CuNPs and the electrostatic attraction capacity of NH2-VMSF towards NO3−. Thus, it is a rapid and sensitive electrochemical method for the determination of NO3− with a wide linear detection range of 5.0–1000 μM and a low detection limit of 2.3 μM. Direct electrochemical detection of NO3− in water samples (tap water, lake water, seawater, and rainwater) with acceptable recoveries ranging from 97.8% to 109% was performed, demonstrating that the proposed CuNPs/NH2-VMSF/ITO sensor has excellent reproducibility, regeneration, and anti-interference abilities.

Abstract The inadequate hole injection limits the efficiency and lifetime of the blue quantum dot light‐emitting diodes (QLEDs), which severely hampers their commercial applications. Here a new discotic molecule of 3,6,10,11‐tetrakis(pentyloxy)triphenylene‐2,7‐diyl bis(2,2‐dimethylpropanoate) (T5DP‐2,7) is introduced, in which the hole transport channels with superior hole mobility (2.6 × 10–2 cm2 V–1 s–1) is formed by stacking. The composite hole transport material (HTM) is prepared by blending T5DP‐2,7 with the cross‐linked 4,4′‐ bis(3‐vinyl‐9H‐carbazol‐9‐yl)‐1,1′biphenyl (CBP‐V) which shows the deep highest occupied molecular orbital energy level. The increased hole mobility of the target composite HTM from 10–4 to 10–3 cm2 V–1 s–1 as well as the stepwise energy levels facilitates the hole transport, which would be beneficial for more balanced carrier injection. This composite hole transport layer (HTL) has improved the deep‐blue‐emission performances of Commission International de I'Eclairage of (0.14, 0.04), luminance of 44080 cd m−2, and external quantum efficiency of 18.59%. Furthermore, when L0 is 100 cd m−2, the device lifetime T50 is extended from 139 to 502 h. The state‐of‐the‐art performance shows the successful promotion of the high‐efficiency for deep blue QLEDs, and indicates that the optimizing HTL by discotic molecule stacking can serve as an excellent alternative for the development of HTL in the future.

Details of the development of coastal hypoxia in response to the passage of Typhoon Bavi (2020) in the East China Sea were reconstructed by numerical modeling using a three-dimensional coupled physical–biogeochemical model. The model was validated via repeated surveys along a transect across a submerged river valley off the Changjiang Estuary before and after the passage of Typhoon Bavi. Before Bavi’s arrival, survey data indicated that the coastal hypoxia had formed off the Changjiang Estuary. However, the hypoxia was not eliminated but instead migrated and aggravated along the observed transect after the typhoon passage. This phenomenon cannot be attributed to the typhoon-induced mixing. Simulation results reveal that the observed development and spatial migration of hypoxia was mainly controlled by typhoon-induced oceanic advection. Results show that Bavi stimulated a regional quasi-barotropic cyclonic loop circulation and coastal downwelling reversing general summer circulation patterns. The onshore transport of the warmer shelf water and subsequent downwelling resulted in a warming of coastal water. The southward coastal current and downwelling induced by the typhoon also led to a migration of the hypoxic zone. Meanwhile, a massive transport of resuspended planktonic detritus from the steep inner shelf and the shallow Changjiang bank toward the submerged river valley occurred. This study reveals that the typhoon-driven currents can play an important role in the development of hypoxia and redistribution of deposited organic matter in coastal shelf seas, which may have both short- and long-term effects on the regional marine biogeochemical environment.

Water quality is directly linked to drinking water safety for millions of people receiving the water. The Danjiangkou Reservoir is the main water source for the Middle Route of the South-to-North Water Diversion Project (MR-SNWDP), located in the vicinity of Henan and Hubei provinces in China. Aquatic microorganisms are key indicators of biologically assessing and monitoring the water quality of the reservoir as they are sensitive to environmental and water quality changes. This study aimed to investigate the spatiotemporal variations in bacterioplankton communities during wet (April) and dry (October) seasons at eight monitoring points in Hanku reservoir and five monitoring points in Danku reservoir. Each time point had three replicates, labeled as wet season Hanku (WH), wet season Danku (WD), dry season Hanku (DH), and dry season Danku (DD) of Danjiangkou Reservoir in 2021. High-throughput sequencing (Illumina PE250) of the 16S rRNA gene was performed, and alpha (ACE and Shannon) and beta (PCoA and NDMS) diversity indices were analyzed. The results showed that the dry season (DH and DD) had more diverse bacterioplankton communities compared to the wet season (WH and WD). Proteobacteria, Actinobacteria, and Firmicutes were the most abundant phyla, and Acinetobacter, Exiguobacterium, and Planomicrobium were abundant in the wet season, while polynucleobacter was abundant in the dry season. The functional prediction of metabolic pathways revealed six major functions including carbohydrate metabolism, membrane transport, amino acid metabolism, signal transduction, and energy metabolism. Redundancy analysis showed that environmental parameters greatly affected bacterioplankton diversity during the dry season compared to the wet season. The findings suggest that seasonality has a significant impact on bacterioplankton communities, and the dry season has more diverse communities influenced by environmental parameters. Further, the relatively high abundance of certain bacteria such as Acinetobacter deteriorated the water quality during the wet season compared to the dry season. Our findings have significant implications for water resource management in China, and other countries facing similar challenges. However, further investigations are required to elucidate the role of environmental parameters in influencing bacterioplankton diversity in order to devise potential strategies for improving water quality management in the reservoir.

The partial pressure of CO2 (pCO2) in the sea and the air-sea CO2 flux in plume waters are subject to interactions among biological production, horizontal advection, and upwelling under wind events. In this study, time series of pCO2 and other biogeochemical parameters in the dynamic Changjiang plume were presented to illuminate the controlling factors of pCO2 and the air-sea CO2 flux after a strong south wind event (July 23–24, maximum of 11.2 ms–1). The surface pCO2 decreased by 310 μatm (to 184 μatm) from July 24 to 26. Low-pCO2 waters (

In this paper, the optimal weighted combination model and fractional grey model are constructed. The coefficients of the optimal weighted combination model are determined by minimizing the sum of squares of resists of each model. On the other hand, the optimal conformable fractional order and dynamic background value coefficient are determined by the quantum inspired evolutionary algorithm (QIEA). Taking the resident population from 2008 to 2018 as the research object, the optimal weighted combination model and fractional grey model were used to study the estimated and predicted values. The results are compared and analyzed. The results show that the fractional grey model is better than the optimal weighted combination model in the estimation of the values. The optimal weighted combination model is better than the fractional grey model in predicting. Meanwhile, the fractional grey model is found to be very suitable for the data values that are large, and the changes between the data are relatively small. The research results expand the application of the fractional grey model and have important implications for the policy implementation activities of Huizhou government according to the population growth trend in Huizhou.

The data presented in this article are related to the research article entitled “Atmospheric transport of nutrient matter during a harmful algal bloom”[1]. These data provide the concentration of nutrients (nitrate, ammonium and FeⅡ) in the atmosphere and their deposited flux in the East China Sea prior to the harmful algal bloom on May 3–8, 2006. They can be helpful for analyzing the source of nutrients causing the harmful algal blooms.

Pif1 is a conserved SF1B DNA helicase involved in maintaining genome stability through unwinding double-stranded DNAs (dsDNAs), DNA/RNA hybrids, and G quadruplex (G4) structures. Here, we report the structures of the helicase domain of human Pif1 and Bacteroides sp Pif1 (BaPif1) in complex with ADP-AlF4– and two different single-stranded DNAs (ssDNAs). The wedge region equivalent to the β hairpin in other SF1B DNA helicases folds into an extended loop followed by an α helix. The Pif1 signature motif of BaPif1 interacts with the wedge region and a short helix in order to stabilize these ssDNA binding elements, therefore indirectly exerting its functional role. Domain 2B of BaPif1 undergoes a large conformational change upon concomitant binding of ATP and ssDNA, which is critical for Pif1’s activities. BaPif1 cocrystallized with a tailed dsDNA and ADP-AlF4–, resulting in a bound ssDNA bent nearly 90° at the ssDNA/dsDNA junction. The conformational snapshots of BaPif1 provide insights into the mechanism governing the helicase activity of Pif1.

Biaxial fatigue testing is an effective way to verify the performance of large wind turbine blades. The test process will generate a large amount of transient strain data, which needs to be peak detection to control the loading system and provided it to third-party organizations for type certification. Peak detection is challenging due to the long test cycle and severe signal noise pollution. The objective of this article is to propose a strain data processing method based on morphological filtering. It is found that morphological filtering + three-point smoothing has a better filtering effect. In addition, a peak detection algorithm is designed and proved its effectiveness. In order to validate the proposed method, a principle prototype of biaxial fatigue testing is built for testing. The results show that the method can not only effectively filter out noise, but also accurately and quickly detect the strain peaks, improve the efficiency of damage calculation and effectively control the test process. The method can also be used in the practical engineering field to process strain data generated during fatigue testing of wind turbine blades and improve overall testing efficiency. [ABSTRACT FROM AUTHOR]

We focus on developing the finite difference (i.e., backward Euler difference or second-order central difference)/local discontinuous Galerkin finite element mixed method to construct and analyze a kind of efficient, accurate, flexible, numerical schemes for approximately solving time-space fractional subdiffusion/superdiffusion equations. Discretizing the time Caputo fractional derivative by using the backward Euler difference for the derivative parameter (0

Rub-impact fault model for dual-rotor system was further developed, in which rubbing board is regarded as elastic sheet. Sheet elastic deformation, contact penetration, and elastic damping support during rubbing of sheet and wheel disk were considered. Collision force and friction were calculated by utilizing Hertz contact theory and Coulomb model and introducing nonlinear spring damping model and friction coefficient. Then kinetic differential equations of rub-impact under dry rubbing condition were established. Based on one-dimensional finite element model of dual-rotor system, dynamic transient response of overall structure under rub-impact existing between rotor wheel and sheet was obtained. Meanwhile, fault dynamic characteristics and impact of rubbing clearance on rotor vibration were analyzed. The results show that, during the process of rub-impact, the spectrums of rotor vibration are complicated and multiple combined frequency components of inner and outer rotor fundamental frequencies are typical characteristic of rub-impact fault for dual-rotor system. It also can be seen from rotor vibration response that the rubbing rotor’s fundamental frequency is modulated by normal rotor double frequency.

A solvent-free liquid-like nanocrystal-functionalized graphene oxide was successfully prepared. Its morphology, chemical structure and multifunction were extensively characterized by various analysis technologies. It was found that the liquid-like nanocrystal-functionalized graphene oxide could flow at room temperature without any solvents and remained magnetic with a saturation magnetization about 2.57 emu/g. Moreover, it exhibited good dispersion in various solvents and polymer matrix. Subsequently, it was incorporated into epoxy matrix to investigate the toughness and glass transition temperature of the resulting nanocomposites. The results indicated that it could simultaneously improve the impact toughness and glass transition temperature of neat epoxy by 138.12% and 33.05 °C at the 1.0 wt.% fraction. [ABSTRACT FROM AUTHOR]