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•NIR spectroscopy was used to predict the bioactive compounds of Sargassum fusiforme.•CARS was a powerful algorithm to select key wavelengths.•PLS and SVM were applied to construct ...the prediction models.•CARS-SVM combination model had the best prediction accuracy.
Edible marine algae, often referred to as sea vegetables, have attracted considerable attention as potential sources of nutrients and health-benefitting components. Quality assessment of sea vegetables is important for identifying commodity grades and ensuring nutritional and health effects. However, the conventional analytical methods to assess the quality of food are costly, time consuming, laborious, and destructive. Thus, in the present study, a simple, fast, and eco-friendly methodology of near-infrared (NIR) spectroscopy was investigated for its ability in the quality evaluation of a sea vegetable, namely, Sargassum fusiforme. To determine the contents of quality parameters (viz. mannitol, polysaccharide, fucosterol, and fucoxanthin) in S. fusiforme, a potential combined CARS-SVM model based on competitive adaptive reweighted sampling (CARS) and support vector machine (SVM) was proposed. The comparison between CARS-SVM and other partial least squares (PLS) models indicated that the wavelength selection method (CARS) and nonlinear regression tool (SVM) could significantly enhance model performance. Among the three types of calibration models (Full-PLS, CARS-PLS, CARS-SVM), CARS-SVM models obtained the best results in prediction of an independent test set. The coefficient of determination (Rp2) and root mean square error (RMSEP) for the prediction set were 0.81 and 3.87 g kg−1 for mannitol, 0.86 and 15.94 g kg−1 for polysaccharide, 0.84 and 0.14 g kg−1 for fucosterol, and 0.78 and 1.76 × 10−2 g kg−1 for fucoxanthin. Overall, NIR spectroscopy coupled with CARS-SVM model was demonstrated to be a potential alternative to the quality assessment of S. fusiforme. These results could provide a valuable reference for the quality assessment of other sea vegetables, such as Porphyratenera, Undariapinnatifida, and Laminaria japonica.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•NIR provides a comprehensive method for quality evaluation of Dendrobium officinale.•Rapid content determination and origin identification was performed.•CARS algorithm was ...outstanding in model optimization.•SVC model obtained satisfactory discrimination results.
Dendrobium officinale, often used as a kind of tea for daily drinks, has drawn increasing attention for its beneficial effects. Quality evaluation of D. officinale is of great significance to ensure its health care value and safeguard consumers’ interest. Given that traditional analytical methods for assessing D. officinale quality are generally time-consuming and laborious, this study developed a comprehensive strategy, with the advantages of being rapid and efficient, enabling the quality evaluation of D. officinale from different geographical origins using near-infrared (NIR) spectroscopy and chemometrics. As the quality indicators, polysaccharides, polyphenols, total flavonoids, and total alkaloids were quantified. Three types of wavelength selection methods were used for model optimization and these were synergy interval (SI), genetic algorithm (GA), and competitive adaptive reweighted sampling (CARS). From the qualitative perspective, the geographical origins of D. officinale were differentiated by NIR spectroscopy combined with partial least squares-discriminant analysis (PLS-DA) and support vector classification (SVC). The PLS models constructed based on the wavelengths selected by CARS yielded the best performance for prediction of the contents of quality indicators in D. officinale. The root mean square error (RMSEP) and coefficient of determination (Rp2) in the independent test sets were 12.7768 g kg−1 and 0.9586, 1.1346 g kg−1 and 0.9670, 0.3938 g kg−1 and 0.8803, 0.0825 and 0.7031 and for polysaccharides, polyphenols, total flavonoids, and total alkaloids, respectively. As for the origin identification, the nonlinear SVC was superior to the linear PLS-DA, with the correct recognition rates in calibration and prediction sets up to 100% and 100%, respectively. The overall results demonstrated the potential of NIR spectroscopy and chemometrics in the rapid determination of quality parameters and geographical origin. This study could provide a valuable reference for quality evaluation of D. officinale in a more rapid and comprehensive manner.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Seaweeds have attracted considerable attention as healthy and nutritious food. Harvest time is essential to ensure the quality and economic value of seaweeds. This study applied near-infrared (NIR) ...spectroscopy and chemometrics for quality grading of seaweed Sargassum fusiforme harvested at different times. S. fusiforme was identified according to harvest time by support vector machine (SVM), K-nearest neighbor (KNN), back propagation neural network (BPNN), and partial least squares-discriminant analysis (PLS-DA). NIR spectroscopy combined with PLS regression models was applied to quantify the vital quality indicator polyphenols. Herein, wavelength selection methods, including synergy interval (SI), genetic algorithm (GA), and competitive adaptive reweighted sampling (CARS), were used for model improvement. The SVM model performed better than the other models in the discrimination of harvest time, and the correct recognition rates in the calibration and prediction sets reached 100%. The CARS-PLS model achieved satisfactory results in predicting the contents of polyphenols, with a root mean square error (RMSEP) of 3.23 g kg−1 and a coefficient of determination (RP2) of 0.99 in an independent prediction set, respectively. Results suggest that S. fusiforme should be harvested at the middle maturity stage. The rapid and efficient NIR spectroscopy combined with chemometrics was proved to be an appropriate tool to assist the quality grading of S. fusiforme.
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•NIR spectroscopy was used to assist the quality grading of Sargassum fusiforme.•The middle maturity stage is the optimal harvesting time of Sargassum fusiforme.•SVM model obtained satisfactory discrimination results.•CARS algorithm was outstanding in model optimization.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Edible marine algae, often referred to as seaweeds, have health benefits and nutritional value. Origin discrimination of seaweeds is essential for quality assurance and traceability. As a rapid, ...easy, and economical method, near-infrared spectroscopy (NIR) was used in this study to investigate its ability to identify Sargassum fusiforme according to geographical origin, cultivar, and production method. A potential particle swarm optimization-support vector machine (PSO-SVM) identification model was constructed and exhibited its superiority in the origin determination of S. fusiforme. Results showed that the correct recognition rates were 90.00% for geographical origin, 100.00% for cultivar, and 100.00% for production method, when the PSO-SVM models were validated using the test sets. Overall, the results proved the potential of NIR spectroscopy combined with PSO-SVM models as a fast analytical method to trace the origin of S. fusiforme in terms of geographical origin, cultivar, and production method.
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•This work presents a novel approach for the discrimination of Sargassum fusiforme.•NIR spectroscopy was used to identify Sargassum fusiforme from different origins.•PSO-SVM model provided satisfactory discrimination performance.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•A comprehensive quality assessment strategy for Bupleuri Radix was developed.•NIR spectroscopy was used for origin identification and content determination.•SVM model provided ...satisfactory discrimination performance.•CARS-SVM model provided acceptable accuracy in the prediction of quality indicators.
The quality of popular Chinese herbal medicine Bupleuri Radix (BR) is essential to its curative effect and economic value and has become an issue for customers and dealers. Traditional analytical techniques for evaluating BR quality are generally time-consuming, laborious, and costly. In this regard, a rapid and efficient method is warranted to supplement existing approaches. This study developed a comprehensive strategy based on near-infrared (NIR) spectroscopy and chemometrics for quality assessment of BR. From qualitative perspective, BR was identified according to geographical origin by using principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and support vector machine (SVM). Saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids, which are vital quality indicators of BR, were quantified through NIR spectroscopy and calibration models. Herein, a CARS-SVM model was constructed based on competitive adaptive reweighted sampling and SVM algorithm, and its prediction performance was compared with other calibration models (Full-PLS, CARS-PLS, and Full-SVM). Results indicated that the SVM model performed better than PCA and PLS-DA and had correct recognition rates of 97.37% and 94.44% in the calibration and prediction sets, respectively. The contents of saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids were satisfactorily predicted through the CARS-SVM model. The coefficient of determination (Rp2) and root mean square error in the independent test sets (RMSEP) were 0.9135 and 0.0837%, 0.8132 and 0.1695%, 0.8810 and 0.7165%, and 0.7471 and 0.1766% for saikosaponin A, saikosaponin D, polysaccharides, and total flavonoids, respectively. The superiority of CARS-SVM compared with the other quantitative models demonstrated that CARS wavelength selection method and nonlinear SVM regression tool significantly improved the model performance. Overall the results demonstrated the potential of NIR spectroscopy and appropriate chemometrics for rapid quality evaluation of BR. The developed comprehensive quality assessment strategy could supplement existing methods for analysis of BR and is expected to provide reference for quality evaluation and control of other Chinese herbal medicines.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
6.
Multi-connection BP Decoding for Polar Codes Yang, Liuchang; Wang, Dianhong; Feng, Zhongxiu ...
2022 14th International Conference on Wireless Communications and Signal Processing (WCSP),
2022-Nov.-1
Conference Proceeding
In this paper, we develop a multi-connection belief propagation (BP) decoding algorithm for polar codes, which employs the idea of the residual neural network to accelerate the convergence. ...Specifically, multi-connection BP decoding builds on the standard BP decoding by fusing the soft information of the current decoding iteration and the past decoding iterations proportionally according to the damping factor during each iteration. Moreover, we adopt the particle swarm optimization algorithm to obtain the optimal value of the damping factor to balance a trade-off between the error rate performance and decoding complexity. The suggested approach can outperform the standard BP decoding with lower iterations, according to simulation findings, which demonstrate that it can reduce error rates.
Persistent heavy metal (HM) contaminated soil provides special habitat for microorganisms, HM stress and complex abiotic factors bring great uncertainty for the development of bacteria and eukaryotic ...microbes. Despite numerous studies about HMs’ effect on soil microorganisms, the key factors affecting microbial communities in severe HM contaminated soil and their interactions are still not definite. In this study, the effect of HM fractions and soil properties on the interaction between bacterial communities and eukaryotic microorganisms was studied by high-throughput Illumina sequencing and simplified continuous extraction of HM in severe HM contaminated soil. Based on amplification and sequencing of the 18S rRNA gene, this study revealed that protists and algae were the most predominant eukaryotic microorganisms, and the dominant phyla were SAR, Opisthokonta and Archaeplastida in HM seriously polluted soil. These results also showed that exchangeable As was negatively correlated with bacterial Shannon and Simpson indexes, while exchangeable Zn was positively correlated with Shannon and Simpson indexes of eukaryotic microbes. Moreover, the structural equation model illustrated that pH, moisture content, available potassium and phosphorus, and exchangeable Cd, As and Zn were the dominant factors shaping bacterial communities, while total organic carbon and exchangeable Zn made the predominant contributions to variations in eukaryotic microbes. In addition, eukaryotic microbes were intensely affected by the bacterial communities, with a standardized regression weight of 0.53, which exceeded the influence of other abiotic factors. It was suggested that community-level adaptions through cooperative interactions under serious HM stress in soil.
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•Eukaryotic microbes were highly resistant to exchangeable heavy metal.•TOC and exchangeable Zn were the main abiotic factors shaping eukaryotic microbes.•Bacteria had a powerful impact on eukaryotic microbes under severe heavy metal stress.•Community-level adaptions to severe heavy metal pollution were formed in soil.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Surface urban heat islands (SUHIs) are a global concern. Although their spatial pattern and the cooling effect of blue-green landscapes have been documented, exploring more accurate and quantitative ...results is still necessary. For Hangzhou, we combined nighttime light (NTL) data with LST images to investigate the spatial morphology of SUHIs and analyze the cooling effect of blue–green landscapes. The radiative transfer equation (RTE) method was used to derive the land surface temperature (LST). Then, based on the unique feature of Luojia1-01 NTL data, the concentric zone model (CZM) was proposed to depict the urban spatial structure. The CZM was applied to construct a number of equal-area concentric belts along the urban-rural gradient to determine the SUHI range and the corresponding blue–green landscape cooling effects. Finally, local Moran's I indices were adopted to identify the cold-hot spots of the SUHI and the relationship with land use. The minimum, average and maximum LSTs were 21.81 °C, 32.79 °C and 44.79 °C, respectively. Additionally, 59.16 % of the study area was affected by the SUHI, and the mean LST inside the SUHI was 36.4 °C, clearly higher than that of the rural area. The SUHI hotpots were clustered in regions with intensive human activities, forming archipelagos. Due to the different blue–green landscape densities, the cooling capacity had spatial heterogeneity in different urban rural belts (URBs), and the cooling capacity of URB16 was approximately 71 times that of URB1. The cooling efficiency increased with blue–green landscape density in general; hence, blue–green landscape density thresholds of 40 % and 70 % were recommended in the urban planning of different urban function zones. Relating the pattern of NTL data to LST images provide meaningful insight into the spatial pattern of SUHIs and the optimization of urban planning.
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•The concentric zone model from NTL data was proposed to depict the urban structure.•Relating the NTL data with LST map to accurately identify the SUHI range•The cooling capacity and efficiency varied in different urban rural belts.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Based on the density functional theory, Δ
2
E(n), De, E
gap
and EA of hydrogen germanide clusters were studied and discussed. The selective hydrogen absorption of the isomers and anions of Ge
m
H
n
...(m = 3-4, n = 0-10) was investigated. The relative stability, electrical properties, optimal geometry of Ge
x
H
y
clusters and their anions were systematically analysed. The results showed that the growth rule of Ge
m
H
n
(m = 3-4, n = 0-10) clusters was hydrogenation. The structure of quaternion ring expanded gradually and finally formed chain structures. The stability of clusters with even hydrogen atom was higher than that with odd hydrogen atom. The results showed that the most stable structure in Ge
4
H
n
(n = 0-10) cluster was Ge
4
H
10
. With the increasing number of hydrogen atoms, the stable structure of the cluster eventually tended to be chain-like. From the calculated results, we found that clusters with even hydrogen atoms existed larger energy gaps than that with odd hydrogen atoms, which indicated that the clusters with even hydrogen atoms had higher chemical stability than that with odd hydrogen atoms. And the result was consistent with its dissociation energy.
Highlights
Selected hydrogen absorption of Ge
3-4
H
n
(n = 0-10) isomers and their Ge
3-4
H
n
-
anions were theoretically investigated by DFT.
H -bridged structure and double H-bridged structures were found in the Ge
3-4
H
n
clusters in the range of n = 1-6.
The geometrical structure, relative stability, electronic properties and dissociation behaviour of Ge
3-4
H
n
(n = 0-10) cluster and their Ge
3-4
H
n
-
anions were systematically analysed by a series of methods.
The infrared spectra of the Ge
3-4
H
n
(n = 0-10) clusters was also simulated for further stimulated study.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
Mitochondrial dysfunction is an early event of Alzheimer's disease (AD), contributes the onset and progression of AD, and may represent an effective therapeutic target for AD intervention. Since ...mitochondria in central neurons are more susceptible to oxidative damage than non-neuronal cells, the specific delivery of the antioxidants to the mitochondria of impaired central neurons is crucial for achieving the therapeutic effect on AD. Here, we prepare the neuronal mitochondria-targeted micelles (CT-NM) through co-decoration with neural cell adhesion molecule (NCAM) mimetic peptide C3 for brain neuron specific binding and the triphenylphosphonium (TPP) for mitochondrial targeting. CT-NM significantly increase the encapsulated resveratrol's concentration in the neuronal mitochondria compared to the micelles modified with C3 only or the resveratrol solution. The resveratrol-loaded CT-NM alleviate the oxidative stress in the neuronal cells, resulting in stabilization of the dynamic balance of mitochondrial fission and fusion. The targeted micelles restore the cognitive performance in APP/PS1 transgenic mice to the level of wild-type mice characterized by up-regulation of sirtuin 1 expression, reduction of amyloid deposition and tau hyperphosphorylation, protection of synapses and inhibition of microglia proliferation. The results demonstrate the delay of the progression of AD through reversing neuronal mitochondrial dysfunction by the targeted delivery of antioxidants.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
