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Eruption of solar flares is a complex nonlinear process, and the rays and high-energy particles generated by such an eruption are detrimental to the reliability of space-based or ground-based systems. So far, there are not reliable physical models to accurately account for the flare outburst mechanism, but a lot of data-driven models have been built to study a solar flare and forecast it. In the paper, the status of solar-flare forecasting is reviewed, with emphasis on the machine learning methods and data-processing techniques used in the models. At first, the essential forecast factors strongly relevant to solar flare outbursts, such as classification information of the sunspots and evolution pattern of the magnetic field, are reviewed and analyzed. Subsequently, methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare samples. Afterwards, typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models, and the forecast performances of the different models are analyzed. Finally, we herein summarize the current research on solar flare forecasting and outline its development trends.

The research of flare forecast based on the machine learning algorithm is an important content of space science. In order to improve the reliability of the data-driven model and weaken the impact of imbalanced data set on its forecast performance, we proposes a resampling method suitable for flare forecasting and a Particle Swarm Optimization (PSO)-based Support Vector Machine (SVM) regular term optimization method. Considering the problem of intra-class imbalance and inter-class imbalance in flare samples, we adopt the density clustering method combined with the Synthetic Minority Over-sampling Technique (SMOTE) oversampling method, and performs the interpolation operation based on Euclidean distance on the basis of analyzing the clustering space in the minority class. At the same time, for the problem that the objective function used for strong classification in SVM cannot adapt to the sample noise, In this research, on the basis of adding regularization parameters, the PSO algorithm is used to optimize the hyperparameters, which can maximize the performance of the classifier. Finally, through a comprehensive comparison test, it is proved that the method designed can be well applied to the flare forecast problem, and the effectiveness of the method is proved.

Increased life expectancy has resulted in an increase in osteoporosis incidence worldwide. The coupling of angiogenesis and osteogenesis is indispensable for bone repair. Although traditional Chinese medicine (TCM) exerts therapeutic effects on osteoporosis, TCM-related scaffolds, which focus on the coupling of angiogenesis and osteogenesis, have not yet been used for the treatment of osteoporotic bone defects. Panax notoginseng saponin (PNS), the active ingredient of Panax notoginseng, was added to a poly (L-lactic acid) (PLLA) matrix. Osteopractic total flavone (OTF), the active ingredient of Rhizoma Drynariae, was encapsulated in nano-hydroxyapatite/collagen (nHAC) and added to the PLLA matrix. Magnesium (Mg) particles were added to the PLLA matrix to overcome the bioinert character of PLLA and neutralize the acidic byproducts generated by PLLA. In this OTF-PNS/nHAC/Mg/PLLA scaffold, PNS was released faster than OTF. The control group had an empty bone tunnel; scaffolds containing OTF:PNS = 100:0, 50:50, and 0:100 were used as the treatment groups. Scaffold groups promoted new vessel and bone formation, increased the osteoid tissue, and suppressed the osteoclast activity around osteoporotic bone defects. Scaffold groups upregulated the expression levels of angiogenic and osteogenic proteins. Among these scaffolds, the OTF-PNS (50:50) scaffold exhibited a better capacity for osteogenesis than the OTF-PNS (100:0 and 0:100) scaffolds. Activation of the bone morphogenic protein (BMP)-2/BMP receptor (BMPR)-1A/runt-related transcription factor (RUNX)-2 signaling pathway may be a possible mechanism for the promotion of osteogenesis. Our study demonstrated that the OTF-PNS/nHAC/Mg/PLLA scaffold could promote osteogenesis via the coupling of angiogenesis and osteogenesis in osteoporotic rats with bone defects, and activating the BMP-2/BMPR1A/RUNX2 signaling pathway may be an osteogenesis-related mechanism. However, further experiments are necessary to facilitate its practical application in the treatment of osteoporotic bone defects.

The konjac polysaccharide aerogel filter rod has the functions of high filtration efficiency and cooling. The biodegradation rate of konjac polysaccharide aerogel filter rod prepared by vacuum freeze drying machine was studied in this paper. The results showed that at the end of the degradation experiment (the 106th day), the biodegradation rate of konjac polysaccharide gel filter rod reached 84.9%, which was close to the degradation rate of thin-layer chromatography grade cellulose, indicating that it had good biodegradability.

Nanoporous (NP) iron with large surface area is highly desired for wastewater degradation catalysis. However, it remains a challenge for the fabrication of NP-Fe because the conventional aqueous dealloying or liquid metal dealloying are not applicable. Herein, a novel and universal plasma-assisted electro-dealloying technique was utilized to fabricate NP-Fe. The NP-Fe demonstrates evenly distributed pore structure. The pore density can be tuned by the variation of the ratio of Fe and Zn in the precursor, and the average pore size can be tuned by the processing time. Owing to its large specific surface area, the NP-Fe shows excellent wastewater degradation performance, which is 26 times better than that of commercial zero-valent iron catalysts. This study provides a useful approach to fabricate NP active metals with enhanced catalytic performance.

All of the experimentally known electronic states of the Cr group metal monoxides (CrO, MoO, and WO) have been presented in the paper. The optical spectra of the CrO molecule have been investigated in the gas phase through a combination of the laser-induced fluorescence (LIF) excitation and single-vibronic-level (SVL) emission spectroscopy in the supersonic expansion. The rotational constants of the vibronic electronic states, including X5Π−1 (v″ = 0–3), B5Π−1 (v′ = 0–10), and B5Π1 (v′ = 1, 5), and the vibrational constants of the spin–orbit components X5Π−1,0,1 have been obtained. The molecular constants of the MoO and WO molecules have been summarized by reviewing the previous spectroscopic studies, and a comprehensive energy level diagram of the Cr group metal monoxides has been constructed. By comparing the electronic configurations, bond lengths, and vibrational frequencies of all the transition metal monoxides in the ground electronic state, the significance of the relativistic effect in the bonding of the 5d transition metal monoxides has been discussed. The related spectroscopic data of the CrO molecule are available at https://doi.org/10.57760/sciencedb.j00113.00085.

In order to explore the effect of calix[4]arene hetero-sulfidation on the capture ability of uranyl ions, computer simulations were used to predict that the B3LYP method in density functional theory, the perhydroxycalix[4]arene with different numbers of hetero-sulfur atoms effects on uranyl ion capture ability, and the compounds formed. We gradually replaced the methylene group "-CH2” in the perhydroxycalix[4]arene with "-S-", and combined the substituted perhydroxycalix[4]arene and the uranyl ion to form a complex. Structural optimization was carried out to further verify that the complexes can exist stably after structural optimization. The structural features of the optimized complexes were analyzed, and the molecules of infrared spectroscopy, the binding energy of calix[4]arene to uranyl ion after hybridization S, and the frontier molecular orbital energy levels of the complexes formed were studied. The number of calixarene-hetero-S with the strongest ability to capture uranyl ions and the number of calixarene-hetero-S with the best chemical stability of the complex formed after the capture of uranyl ions were found.

To explore the best hybrid calixarene for cadmium ion capture, the B3LYP method in density functional theory (DFT) was used to optimize the structure and infrared vibration data of the complexes formed by each fully hydroxylated heteroN and heteroS calixtetraarenes with Cd ions. The stability of the structure of each complex was verified. At the same time, the structural characteristics of each complex were analyzed. A comparative study on the binding ability of different numbers of hybrid calix [4] arene derivatives to Cd ions was carried out, and the complexes that best bound to Cd ions were obtained. For example, the binding capacity of hetero S-calix [4] arenes to Cd ions is greater than that of non-hybrid complexes and hetero-N complexes to Cd ions. More interestingly, as the number of S atoms in the hetero S increases, the binding ability to Cd becomes stronger.

Predicting the activity of solar flares is of great significance for studying its physical mechanism and the impact on human production and life. Problems such as class imbalance, high time-series sensitivity, and over-localization of important features exist in the sample data used for flare forecasting. We design a solar flare fusion method based on resampling and the CNN-GRU algorithm to try to solve the above problems. In order to verify the effectiveness of this fusion method, first, we compared the forecast performance of different resampling methods by keeping the forecast model unchanged. Then, we used the resampling algorithm with high performance to combine some single forecast models and fusion forecast models respectively. We use the 2010–2017 sunspot data set to train and test the performance of the flare model in predicting flare events in the next 48 h. Through the conclusion of the above steps, we prove that the resampling method SMOTE and its variant SMOTE-ENN are more advantageous in class imbalance problem of flare samples. In addition, after the fusion of one-dimensional convolution and recurrent network with “forget-gate” , combined with the SMOTE-ENN to achieve TSS = 61%, HSS = 61%, TPRate = 77% and TNRate = 83%. This proves that the fusion model based on resampling and the CNN-GRU algorithm is more suitable for solar flare forecasting.

We proposed a cold capacitively-coupled-plasma jet method to deposit the seed layer in the inner wall of Through-silicon-vias (TSVs) directly. Comparison experiments were carried out to optimize the process parameters. The testing results were discussed and proved the potential application of this technique in the metallization of TSVs in 2.5D integration technology.

Mechanical properties and micro morphology of acetate filter rod before and after partial degradation were studied. In this paper, the mechanical properties and micro morphology of acetate filter rod samples and 28 days soil burying were compared by means of Scanning Electronic Microscopy (SEM), texture analysis, infrared spectrum analysis and thermos-gravimetry (TG) analysis. The results showed that after degradation, the average compression modulus, hardness and elasticity of cellulose acetate filter rod decreased by 15.14%, 15.19% and 0.82%, respectively. The infrared spectrum analysis showed that cellulose acetate was degraded by soil burying method and carboxyl carbonyl was formed, but the degradation degree was not high. The degradation degree of cellulose acetate was lower than that of cellulose acetate before degradation. The weight loss zone between 110 °C and 230 °C is less, which may be due to the complete degradation of the small molecular assistant added to the cellulose acetate degraded by the soil burying method.

In this paper, Ag nanoparticles (Ag NPs) were loaded on pure g-C3N4 (CN) via two different methods of direct heating and indirect heating to form g-C3N4/Ag-DX and g-C3N4/Ag-IDX photocatalysts, respectively. Using methylene blue as the degradation dye, the photocatalytic performance of g-C3N4/Ag-DX and g-C3N4/Ag-IDX was studied through visible light photocatalysis experiments. The results demonstrated that the photocatalytic performance of g-C3N4/Ag-DX and g-C3N4/Ag-IDX both increases with the increase in content of Ag nanoparticles. It is obvious that g-C3N4/Ag-ID8 has the optimal photocatalytic activity. Meanwhile, the g-C3N4/Ag-ID8 has excellent stability and can be reused in photocatalysis experiments.