The current intelligent diagnosis and prediction methods for transformer faults are prone to low diagnostic accuracy and insufficient trend prediction ability when the fault categories are ...imbalanced. Therefore, a fault diagnosis and prediction model for transformers was constructed using a deep learning framework. The fault diagnosis model was constructed using a focus loss stack sparse noise reduction autoencoder on the deep learning framework. The prediction model was constructed by fusing long and short term memory networks on the basis of tree structure Parzen optimization, and the two models were validated. The results obtained through validation of the diagnostic model indicate that, when the actual hidden layer is set to 3 and the quantity of neurons is 58, the model accuracy during training and testing reaches 97.5% and 92.5% respectively. After adding 0.001 times the Gaussian white noise, the model accuracy was significantly lifted, so this study set the Gaussian noise coefficient to 0.001. In the comparison with baseline models, the actual classification ability of the research model samples is strong, significantly improving the fault diagnosis ability. In the validation of the prediction model, the three error index values of the research model in the single prediction step of CH4 concentration were 0.0699, 0.0540, and 0.8481%, respectively, and proved to be were lower than in the case of the baseline model. The three error values in the two-step prediction are 0.0194, 0.0161, and 0.6535%, which are also lower than in case of the baseline model. Overall, the diagnosis and prediction model proposed in this paper can provide real-time future numerical predictions of dissolved gas analysis and monitoring data in transformer oil. Furthermore, the research outilnes the future development trend of monitoring and measurement through application of tensor flow deep learning framework in transformer fault diagnosis. The attained prediction results are innovative, and could well complete the purpose of actual transformer fault diagnosis and early warning.
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•Higher As groundwater was found near the permanent wetland (PW) than dried wetland (DW).•PW sediments had more autochthonous or aquatic biological organic matter than DW ...sediments.•DOM in PW groundwater was more bioreactive than that in DW groundwater.•Higher dissolved As concentrations were related to higher bioreactivity of organic matter.•Bioreactive organic matter triggered As mobilization via reductive dissolution of Fe oxides.
Organic matter (OM) is widely accepted to be the trigger for arsenic (As) mobilization from sediments into groundwater. Identifications of reactivity and sources of organic matter responsible for driving As liberation remain unresolved. To address these issues, we provide the extensive characterization of OM in shallow groundwater, surface water, and sediments near a permanent wetland and a dried wetland in the Hetao basin with high As groundwater and low As groundwater, respectively, using fluorescence spectroscopy and parallel factor analysis (PARAFAC). Dissolved organic matter (DOM) of shallow groundwater and sediments near the permanent wetland had higher biological index (BIX), and more protein-like components and microbially-derived components relative to that near the dried wetland, showing higher bioreactivity. Fingerprint of water stable isotopes and higher water levels of wetland than shallow groundwater pointed to the recharge of wetland water into shallow groundwater. Laboratory incubations of the sediment with more bioreactive OM obtained near the permanent wetland mobilized more As. Both DOM properties and laboratory incubations indicate that OM with high bioreactivity promoted As mobility mainly by fuelling microbial respiration of Fe oxide reduction. Recharge of wetland water into shallow groundwater introduced bioreactive DOM into shallow aquifer. Groundwater DOM near the permanent wetland was typically sourced from both wetland DOM and sedimentary OM with high bioreactivity. However, sedimentary OM was the major source of groundwater DOM near the dried-wetland. It suggested that downward infiltration of surface-derived OM and perturbations of aquifer sediments by changing groundwater flow regimes increase bioreactivity of groundwater DOM and therefore enhance As mobility.
Tissue engineering (TE) has been used as an attractive and efficient process to restore the original tissue structures and functions through the combination of biodegradable scaffolds, seeded cells, ...and biological factors. As a unique type of scaffolds, hydrogels have been frequently used for TE because of their similar 3D structures to the native extracellular matrix (ECM), as well as their tunable biochemical and biophysical properties to control cell functions such as cell adhesion, migration, proliferation, and differentiation. Various types of hydrogels have been prepared from naturally derived biomaterials, synthetic polymers, or their combination, showing their promise in TE. This review summarizes the very recent progress of hydrogels used for TE applications. The strategies for tuning biophysical and biochemical properties, and structures of hydrogels are first introduced. Their influences on cell functions and promotive effects on tissue regeneration are then highlighted.
Evidence shows that a variety of macroeconomic and firm level factors have a positive impact on carbon emission mitigation. However, little is known regarding the comprehensive effect of research and ...development (R&D) input on a firm’s environmental performance. Using a data set comprised of public firms operating in 52 countries from 2002 to 2015, this paper investigates the effect of R&D input on carbon emission mitigation. Our finding shows that while R&D input remains one of the most important approaches for mitigating carbon emission, the marginal effect of technological progress on carbon emission reduction tends to decrease. Furthermore, there is an inverted U-shaped relationship between R&D input and carbon emission reduction, where the turning point is established when the R&D input reaches 22.91% of a firm’s operational expenses. To maintain a sustainable emission reduction effect, a dynamic technological progress model with sustainable marginal effects is developed and offers a new policy option for continued efforts to meet carbon emission reduction targets.
To improve the effectiveness of control of surrounding rock and the stability of supports on longwall topcoal caving faces in steeply inclined coal seams, the stability of the roof structure and ...hydraulic supports was studied with physical simulation and theoretical analysis. The results show that roof strata in the vicinity of the tail gate subside extensively with small cutting height, while roof subsidence near the main gate is relatively assuasive. With increase of the mining space, the caving angle of the roof strata above the main gate increases. The characteristics of the vertical and horizontal displacement of the roof strata demonstrate that caved blocks rotate around the lower hinged point of the roof structure, which may lead to sliding instability. Large dip angle of the coal seam makes sliding instability of the roof structure easier.A three-hinged arch can be easily formed above both the tail and main gates in steeply inclined coal seams. With the growth in the dip angle, subsidence of the arch foot formed above the main gate decreases significantly, which reduces the probability of the roof structure becoming unstable as a result of large deformation, while the potential of the roof structure＇s sliding instability above the tail gate increases dramatically.
Using the extended model of the Simple View of Reading, this study investigated how morphological awareness facilitated reading comprehension via phonetic decoding and listening comprehension among ...140 adult learners of English in China. The participants completed five computer-based tasks on working memory, morphological awareness, phonetic decoding, listening comprehension, and reading comprehension. The results of correlational analyses and path analyses show that 1) there are statistically significant correlations among phonetic decoding, listening comprehension and reading comprehension, though the correlation between phonetic decoding and listening comprehension has a relatively small effect size; 2) phonetic decoding and listening comprehension directly and significantly contribute to reading comprehension, while listening comprehension explains more variances of reading comprehension; and 3) morphological awareness does not directly predict reading comprehension; however, it has an indirect impact on
•The performance of biopolymers can be modified via molecular engineering.•Modified biopolymers are promising for advanced functional electronics.•Biopolymers are featured in low-cost, eco-friendly ...and large-scale fabrication.•Future challenges and developments of electronic biopolymers are proposed.
Biopolymers with excellent biocompatibility, biodegradability, and multiple active sites have been widely used in biomedical fields. Currently, the unique electronic properties of biopolymers have been continuously exploited for designing wearable, implantable and biodegradable electronics. In the view of molecular engineering including molecular design and assembly and structural modification, this review provides a comprehensive overview of advanced biopolymers related to energy, sensors, displays and bionic devices, and indicates the important roles of structural modification on tuning device performance. In addition, representative printing technologies are discussed to highlight their features in low-cost, eco-friendly and scalable-up fabrication of biopolymer electronics. Furthermore, the current challenges and future opportunities are prospected to point out how electronic biopolymers will be modified or developed for next-generation flexible and wearable bioelectronics.
Gelatin hydrogels can mimic the microenvironments of natural tissues and encapsulate cells homogeneously, which makes them attractive for cartilage tissue engineering. Both the mechanical and ...biochemical properties of hydrogels can affect the phenotype of chondrocytes. However, the influence of each property on chondrocyte phenotype is unclear due to the difficulty in separating the roles of these properties. In this study, we aimed to study the influence of hydrogel stiffness on chondrocyte phenotype while excluding the role of biochemical factors, such as adhesion site density in the hydrogels. By altering the degree of methacryloyl functionalization, gelatin hydrogels with different stiffnesses of 3.8, 17.1, and 29.9 kPa Young's modulus were prepared from the same concentration of gelatin methacryloyl (GelMA) macromers. Bovine articular chondrocytes were encapsulated in the hydrogels and cultured for 14 days. The influence of hydrogel stiffness on the cell behaviors including cell viability, cell morphology, and maintenance of chondrogenic phenotype was evaluated. GelMA hydrogels with high stiffness (29.9 kPa) showed the best results on maintaining chondrogenic phenotype. These results will be useful for the design and preparation of scaffolds for cartilage tissue engineering.
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•Exosomes are nanoscale membrane vesicles formed by dynamic multistep endocytosis processes, about 30–150 nm in diameter.•The crosstalk of exosomes between lung cancer cells and ...healthy cells accelerates the malignant process of lung cancer.•Exosomes play essential roles in the regulation of lung cancer immune suppression.•Exosomes can be used as a diagnostic and the prognostic biomarker for lung cancer.
The incidence and mortality of lung cancer account for first place all over the world. Lung cancer lacks early diagnostic biomarkers; lung cancer patients are usually diagnosed in both middle and advanced stages and have poor treatment outcomes. It is more important to find the first diagnostic tools for lung cancer with high specificity and sensitivity. Besides, exosomes are usually nanometer-sized bi-layered lipid vesicles formed and produced by various types of cells. As one of the main modes of intercellular communication, they can deliver multiple functional biomolecules, such as DNA, microRNAs, messenger RNA (mRNA), long non-coding RNA, and proteins, and the events as mentioned above affects different physiological processes of recipient cells. It has been reported that exosomes are involved in different types of cancer, including lung cancer. Various studies proved that exosomes are involved in multiple cancer processes such as cell proliferation, metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and the tumor microenvironment in lung cancer. Tumor-derived exosomes (TEX) contain a variety of stimulatory and inhibitory factors involved in regulating immune response, which can affect the tumor microenvironment (TME) and thus participate in the formation and progression of lung cancer. This review's primary purpose to review the latest research progress of exosomes in diagnosing and treating lung cancer.
Molecular weight (MW) is a fundamental property of dissolved organic matter (DOM) that may affect the interaction between DOM and metals/metalloids. However, understanding of MW property of ...groundwater DOM and its roles in arsenic (As) mobilization needs to be improved. In this study, two surface water samples and 12 groundwater samples with different concentrations of As and dissolved organic carbon (DOC) were taken to evaluate the effects of DOM MW on As mobilization by using sequential ultrafiltration technique under a N2 atmosphere. Concentrations of As, Fe, DOC, and spectroscopic properties of OM in each ultrafiltered sample were analyzed. Variations of As, Fe and DOC concentrations in different ultrafiltration fractions show that Fe colloids mainly exist in large size particles (10 kDa-0.45 μm fractions), while organic colloids are mainly present in middle size particles (5–10 kDa fractions). The positive correlations between As and Fe in 10 kDa-0.45 μm fractions (R2 = 0.76, p < 0.01) and between As and DOC in 5–10 kDa fractions (R2 = 0.61, p < 0.05) indicate that the complexation of As with large-size Fe colloids and middle-size DOM promotes As mobilization. Parallel factor analysis (PARAFAC) of the three-dimensional fluorescence spectra reveals that DOM in all size fractions comprises three major components, namely C1 (terrestrial humic-like component), C2 (microbial humic-like component), and C3 (protein-like component). The positive correlation between C1 (%) and As concentrations (R2 = 0.73, p < 0.05) possibly confirms that terrestrial-derived humic-like substance (HS) should be conducive to As enrichment. The spectroscopic indices of various fractions show that low MW DOM is characterized by more microbe-associated OM. Some samples have more than 90% of As in the ‘truly dissolved’ fractions, suggesting that microbial utilization of labile low MW DOM should lead to the enrichment of As, in addition to complexation reactions. Therefore, both As-Fe-HS complexation and microbial degradation of low MW DOM being related to the reductive dissolution of As-bearing Fe oxide minerals enhance As mobilization and enrichment in groundwater.
•Both Fe colloids and organic colloids are present in high As groundwater.•Arsenic complexes with large-size Fe colloids and middle-size organic colloids.•Terrestrial-derived humic-like substances participate in the complexation reaction.•Low molecular weight DOM is characterized by more microbe-associated OM.•Microbial degradation of low molecular weight DOM enhances As enrichment.
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