Copper adsorption onto calcium alginate encapsulated magnetic sorbent is studied in this paper. The objective of this study was to qualitatively and quantitatively elucidate the copper binding onto ...the sorbent. The adsorption increases from around 0 to almost 100% as the initial pH is increased from 2 to 5. A maximum adsorption capacity of 0.99 mmol g−1 is achieved. The FT-IR and XPS studies show that the CO in carboxyl group of alginate directly attaches to the copper ion that leads to most of the adsorption. A mathematical model is developed, and it includes ion exchange between the calcium and the copper, coordination reaction between the functional group and the copper, as well as surface complex formation between the iron oxide and the copper. The model is capable of describing and predicting effects of various key operational parameters on the adsorption process, such as initial pH, metal concentration, and dosage of sorbent.
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•An evolutionary algorithm named MOFOA is proposed, which is the first study that extends the relatively new fireworks optimization heuristic for multiobjective ...optimization.•Differential evolution operators are integrated into the algorithm to diversify the search.•The algorithm is successfully applied to a number of oil crop variable-rate fertilization (VFR) problems, including a real-world application in east China.
Variable-rate fertilization (VRF) decision is a key aspect of prescription generation in precision agriculture, which typically involves multiple criteria and objectives. This paper presents a multiobjective optimization problem model for oil crop fertilization, which takes into consideration not only crop yield and quality but also energy consumption and environmental effects. For efficiently solving the problem, we propose a hybrid multiobjective fireworks optimization algorithm (MOFOA) that evolves a set of solutions to the Pareto optimal front by mimicking the explosion of fireworks. In particular, it uses the concept of Pareto dominance for individual evaluation and selection, and combines differential evolution (DE) operators to increase information sharing among the individuals. The experimental tests and real-world applications in oil crop production in east China demonstrate the effectiveness and practicality of the algorithm.
Normal breathing in rodents requires activity of glutamatergic Dbx1-derived (Dbx1+) preBötzinger Complex (preBötC) neurons expressing somatostatin (SST). We combined in vivo optogenetic and ...pharmacological perturbations to elucidate the functional roles of these neurons in breathing. In transgenic adult mice expressing channelrhodopsin (ChR2) in Dbx1+ neurons, photoresponsive preBötC neurons had preinspiratory or inspiratory firing patterns associated with excitatory effects on burst timing and pattern. In transgenic adult mice expressing ChR2 in SST+ neurons, photoresponsive preBötC neurons had inspiratory or postinspiratory firing patterns associated with excitatory responses on pattern or inhibitory responses that were largely eliminated by blocking synaptic inhibition within preBötC or by local viral infection limiting ChR2 expression to preBötC SST+ neurons. We conclude that: (1) preinspiratory preBötC Dbx1+ neurons are rhythmogenic, (2) inspiratory preBötC Dbx1+ and SST+ neurons primarily act to pattern respiratory motor output, and (3) SST+-neuron-mediated pathways and postsynaptic inhibition within preBötC modulate breathing pattern.
•Preinspiratory preBötC Dbx1+ neurons are respiratory rhythmogenic•Inspiratory preBötC Dbx1+ and SST+ neurons shape motor output pattern•SST+-neuron-mediated inhibitory pathways modulate respiratory activity•Postsynaptic inhibition broadens dynamic range and stabilizes breathing pattern
Cui et al. combine in vivo optogenetic and pharmacological perturbations to dissect the neural microcircuits controlling breathing and to elucidate the functional role of preBötinger Complex Dbx1+ and SST+ neurons that underlie a microcircuit model for respiratory rhythm and pattern generation.
Haemorrhagic stroke accounts for approximately 31.52% of all stroke cases, and the most common origin is hypertension. However, little is known about the method to identify high-risk populations of ...hypertensive intracerebral haemorrhage.
The results showed that the angle between the middle cerebral artery and the internal carotid artery (AMIC), the distance between the beginning of the median artery and superior trunk (DMS), and the density (CT value) of the lenticulostriate artery (CTL) were statistically significant enough to cause intracerebral haemorrhage. In addition, we chose these three potential features for the ensemble learning classification model. Our developed ensemble-learning method outperforms not only previous work but also three other classic classification methods based on accuracy measurements.
The developed mathematical model in the present study is efficient in predicting the probability of intracerebral haemorrhage.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this study, the electrical performance and bending stress endurance of flexible low-temperature polycrystalline silicon thin film transistors (LTPS TFTs) are enhanced by increasing the helium ...concentration (1500 sccm) during gate insulator (GI) manufacture to create a high-quality GI device. Experimental results confirm that the subthreshold swing (S.S.) and mobility of these new "high-flow" devices are better than those with a lower helium concentration, which we term "low-flow" devices. The flow of helium gas is increased to achieve a better-quality oxide layer. The energy-dispersive X-ray spectroscopy (EDS) line data show a clear enhancement in oxygen content in the devices under this helium gas process. After mechanical compression and tensile bending stresses of 100000 iterations in the channel width-axis direction, perpendicular to the channel, with bending at <inline-formula> <tex-math notation="LaTeX">{R} = {2} </tex-math></inline-formula> mm, the modified GI devices with their more Si-O bond content exhibit less stress damage in the GI layer than do low-flow devices. As a result, this new manufacturing condition can effectively reduce the electrical degradation after negative-bias temperature stress (NBTS), and improve the overall electrical performance.
•Citric acid esterification can increase the SDS and RS contents of cassava starch.•Citric acid esterification does not change the crystalline pattern of cassava starch.•Citric acid esterification ...can improve the freeze-thaw stability of cassava starch.•Citric acid esterification changes the thermal properties of cassava starch.
In this study, citric acid was used to react with cassava starch in order to compare the digestibility, structural and physicochemical properties of citrate starch samples. The results indicated that citric acid esterification treatment significantly increased the content of resistant starch (RS) in starch samples. The swelling power and solubility of citrate starch samples were lower than those of native starch. Compared with native starch, a new peak at 1724cm−1 was appeared in all citrate starch samples, and crystalline peaks of all starch citrates became much smaller or even disappeared. Differential scanning calorimetry results indicated that the endothermic peak of citrate starches gradually shrank or even disappeared. Moreover, the citrate starch gels exhibited better freeze–thaw stability. These results suggested that citric acid esterification induced structural changes in cassava starch significantly affected its digestibility and it could be a potential method for the preparation of RS with thermal stability.
•A virtual ground-based PM2.5 observation network was constructed.•Daily estimations of PM2.5 concentrations at ~1000 sites in China were generated.•The model demonstrated good performance in ...hindcasting historical PM2.5 levels.•This virtual PM2.5 network can be used for reconstructing historical PM2.5 data.
With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM2.5 datasets. However, it was not until the end of 2012 that China established a national PM2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM2.5. Here, we constructed a virtual ground-based PM2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM2.5 across China in 2018, with R2, root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m3 (6.75 μg/m3) and 9.89 μg/m3 (4.53 μg/m3), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance.
We then use meteorological and PM2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM2.5 at monthly (R2 = 0.80, RMSE = 14.75 μg/m3), seasonal (R2 = 0.86, RMSE = 12.28 μg/m3), and annual (R2 = 0.81, RMSE = 10.10 μg/m3) mean levels. In general, the newly constructed virtual PM2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM2.5 data, as well as to other environmental studies including epidemiology.
(1 − x)CaTiO3–xLa(Mg2/3Nb1/3)O3 (CT–LMN; x = 0–1.0) solid solutions were prepared by a solid‐state reaction method. A phase transition from a disordered orthorhombic (Pbnm) structure to a 1:1 ordered ...monoclinic (P21/n) structure was observed when x increased from 0.5 to 0.6. Some new parameters, such as ionic polarizability in a polyhedron and ionic packing fraction in a polyhedron, were defined to explain the structure–property relationships of CT–LMN ceramics based on the Rietveld refinement results. The measured dielectric constant (εr‐mea) decreased monotonically with B‐site ionic polarizability in the BO6 octahedron (αDT(B)/VB$\alpha _{\rm{D}}^{\rm{T}}( {\rm{B}} )/{V_{ {\rm{B}} }}$) when the x value increased from 0 to 1.0. The quality factor (Qf) was dominated by the packing fraction of B‐site cations in the BO6 octahedron (PFB), and both presented an increasing trend. The temperature coefficient of resonant frequency (τf) decreased from +588.5 to −79.7 ppm/°C, and it was highly correlated to the tolerance factor (t), αDT(B)/αDT(B)VBVB${{\alpha _D^T( {\rm{B}} )} \mathord{/ {\vphantom {{\alpha _D^T( {\rm{B}} )} {{V_{ {\rm{B}} }}} \kern-\nulldelimiterspace} {{V_{ {\rm{B}} }}}$ and PFB. The highest Qf value is obtained at x = 1.0 when sintered at 1600°C for 10 h with εr = 23.65 ± 0.2, Qf = 33517 ± 2000 GHz (@7.8 GHz), and τf = −79.7 ± 2.0 ppm/°C. Moreover, a near‐zero τf value was achieved at x = 0.4 with εr = 43.52 ± 0.2, Qf = 17239 ± 2000 GHz (@5.2 GHz), and τf = −10.2 ± 2.0 ppm/°C.
Thick clouds in remote sensing (RS) images deteriorate the visual quality and hinder subsequent applications. The emerging multitemporal RS images with rich temporal information bring the opportunity ...for cloud removal. How to effectively exploit the rich temporal information of the multitemporal RS images remains challenging. As multitemporal RS images with the same geographic scene, the spatial gradient of RS images at different time nodes has a resemblance, which can guide the reconstruction of the cloudy region. Motivated by this, we suggest a gradient domain fidelity with respect to the guided gradient for thick cloud removal in multitemporal RS images, which faithfully preserves the fine edges and textures compared with the original pixel domain fidelity. Armed with the gradient domain fidelity, we propose a low-rank tensor ring decomposition model (termed as TRGFid) for the thick cloud removal problem. In the proposed model, the guided gradient of the cloudy region is availably estimated by using the Regression method from the cloud-free region of different time nodes. Moreover, we develop an efficient proximal alternating minimization (PAM)-based algorithm for solving the proposed nonconvex model. Extensive simulated and real experiments show that the proposed method outperforms its competitors and preserves fine edges and textures.
Weighted co-expression network analysis (WGCNA) is a powerful systems biology method to describe the correlation of gene expression based on the microarray database, which can be used to facilitate ...the discovery of therapeutic targets or candidate biomarkers in diseases.
To explore the key genes in the development of Alzheimer's disease (AD) by using WGCNA.
The whole gene expression data GSE1297 from AD and control human hippocampus was obtained from the GEO database in NCBI. Co-expressed genes were clustered into different modules. Modules of interest were identified through calculating the correlation coefficient between the module and phenotypic traits. GO and pathway enrichment analyses were conducted, and the central players (key hub genes) within the modules of interest were identified through network analysis. The expression of the identified key genes was confirmed in AD transgenic mice through using qRT-PCR.
Two modules were found to be associated with AD clinical severity, which functioning mainly in mineral absorption, NF-κB signaling, and cGMP-PKG signaling pathways. Through analysis of the two modules, we found that metallothionein (MT), Notch2, MSX1, ADD3, and RAB31 were highly correlated with AD phenotype. Increase in expression of these genes was confirmed in aged AD transgenic mice.
WGCNA analysis can be used to analyze and predict the key genes in AD. MT1, MT2, MSX1, NOTCH2, ADD3, and RAB31 are identified to be the most relevant genes, which may be potential targets for AD therapy.
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