A vibrationally compensated far infrared laser interferometer for plasma density measurements

A modulated far-infrared laser interferometer which is presently operating on the PDX experiment at Princeton is described. The interferometer geometry permits the characterization of inside D, outside D as well as circular discharges. To achieve this versatility, a titanium corner cube reflector, mounted inside the PDX vacuum vessel is used in conjunction with a second visible wavelength interferometer for vibration corrections. In addition, the use of room temperature quasi-optical Schottky diodes in the far-infrared interferometer is reported. The minimum detectable line average density of the system is 5×10¹¹ cm^–3.     

热辐射驱动烧蚀平面金靶的数值定标定律

利用一维辐射流体力学编码数值研究了辐射烧蚀波在平面金靶中的传播情况,并在常温边界条件下得到了辐射流、烧蚀压、质量烧蚀率和特征等离子体密度的定标定律。     

Ultrasound-assisted facile one-pot synthesis of ternary MWCNT/MnO2/rGO nanocomposite for high performance supercapacitors with commercial-level mass loadings

Commercial application of supercapacitors (SCs) requires high mass loading electrodes simultaneously with high energy density and long cycle life. Herein, we have reported a ternary multi-walled carbon nanotube (MWCNT)/MnO₂/reduced graphene oxide (rGO) nanocomposite for SCs with commercial-level mass loadings. The ternary nanocomposite was synthesized using a facile ultrasound-assisted one-pot method. The symmetric SC fabricated with ternary MWCNT/MnO₂/rGO nanocomposite demonstrated marked enhancement in capacitive performance as compared to those with binary nanocomposites (MnO₂/rGO and MnO₂/MWCNT). The synergistic effect from simultaneous growth of MnO₂ on the graphene and MWCNTs under ultrasonic irradiation resulted in the formation of a porous ternary structure with efficient ion diffusion channels and high electrochemically active surface area. The symmetric SC with commercial-level mass loading electrodes (∼12 mg cm⁻²) offered a high specific capacitance (314.6 F g⁻¹) and energy density (21.1 W h kg⁻¹ at 150 W kg⁻¹) at a wide operating voltage of 1.5 V. Moreover, the SC exhibits no loss of capacitance after 5000 charge−discharge cycles showcasing excellent cycle life.     

Optimisation of the ultrasound-assisted extraction of betalains and polyphenols from Amaranthus hypochondriacus var. Nutrisol

The present study optimised the ultrasound-assisted extraction (UAE) of bioactive compounds from Amaranthus hypochondriacus var. Nutrisol. Influence of temperature (25.86–54.14 °C) and ultrasonic power densities (UPD) (76.01–273.99 mW/mL) on total betalains (BT), betacyanins (BC), betaxanthins (BX), total polyphenols (TP), antioxidant activity (AA), colour parameters (L*, a*, and b*), amaranthine (A), and isoamaranthine (IA) were evaluated using response surface methodology. Moreover, betalain extraction kinetics and mass transfer coefficients (K_La) were determined for each experimental condition. BT, BC, BX, TP, AA, b*, K_La, and A were significantly affected (p < 0.05) by temperature extraction and UPD, whereas L*, a*, and IA were only affected (p < 0.05) by temperature. All response models were significantly validated with regression coefficients (R²) ranging from 87.46 to 99.29%. BT, A, IA, and K_La in UAE were 1.38, 1.65, 1.50, and 29.93 times higher than determined using conventional extraction, respectively. Optimal UAE conditions were obtained at 41.80 °C and 188.84 mW/mL using the desired function methodology. Under these conditions, the experimental values for BC, BX, BT, TP, AA, L*, a*, b*, K_La, A, and IA were closely related to the predicted values, indicating the suitability of the developed quadratic models. This study proposes a simple and efficient UAE method to obtain betalains and polyphenols with high antioxidant activity, which can be used in several applications within the food industry.     

Reducing Occupational Noise Propagated from Centrifugal Fan through Dissipative Silencers: A Field Study

Acoustic performance of dissipative silencer was evaluated to determine the effectiveness of perforated duct porosity and absorbent material density in reducing occupational noise exposure propagated from centrifugal fan. Design charts were applied to predict noise reduction and length of a dissipative silencer. Dissipative silencers with various punched duct porosity (14%, 30% and 40%) and sound absorbent density (80 Kg/m³, 120 Kg/m³, and 140 Kg/m³) were designed and fabricated. According to ISO9612 and ISO11820, noise level was measured before and after installing all nine test silencers at fixed workstations around the discharge side of a centrifugal fan in a manufacturing plant. On average, the noise level at the discharge side of a fan without silencer was measured to be 93.6 dBA, whereas it was significantly mitigated by 67.4 dBA to 70.1 dBA after installing all silencers. Dynamic insertion loss for a dissipative silencer with 100 cm length was predicted to be 27.9 dB, which was in agreement with experimental ones. Although, there was no significant differences between insertion loss of silencers, the one with 30% porosity and 120 Kg/m³ rock wool density had the highest insertion loss of 26.2 dBA. Dissipative silencers noticeably reduced centrifugal fan noise exposures. Increasing sound absorbent density and duct porosity up to a certain limit could probably be effective in noise reduction of dissipative silencers.     

Research on a Rice Counting Algorithm Based on an Improved MCNN and a Density Map

The thousand grain weight is an index of size, fullness and quality in crop seed detection and is an important basis for field yield prediction. To detect the thousand grain weight of rice requires the accurate counting of rice. We collected a total of 5670 images of three different types of rice seeds with different qualities to construct a model. Considering the different shapes of different types of rice, this study used an adaptive Gaussian kernel to convolve with the rice coordinate function to obtain a more accurate density map, which was used as an important basis for determining the results of subsequent experiments. A Multi-Column Convolutional Neural Network was used to extract the features of different sizes of rice, and the features were fused by the fusion network to learn the mapping relationship from the original map features to the density map features. An advanced prior step was added to the original algorithm to estimate the density level of the image, which weakened the effect of the rice adhesion condition on the counting results. Extensive comparison experiments show that the proposed method is more accurate than the original MCNN algorithm.     

Small shower CORSIKA simulations

Extensive Air Showers (EAS) induced by cosmic ray particles of very low energies, owing to the significantly steep cosmic ray energy spectrum, dominate the secondary particle flux measured by single detectors and small shower arrays. Such arrays connected in extended networks can be used to determine potentially interesting spatial correlations between showers, which may shed new light on the nature of ultra high-energy cosmic rays. The quantitative interpretation of showers recorded by small local arrays requires a methodology that differs from that used by ordinary large EAS arrays operating in the "knee" region and above. We present "small EAS generator," a semi-analytical method for integrating cosmic ray spectra over energies of interest and summing over the mass spectra of primary nuclei in arbitrary detector configurations. Furthermore, we provide results on the EAS electron and muon fluxes and particle density spectra.     

Some remarks on X(6900)

The analysis of the LHCb data on \begin{document}$X(6900)$\end{document} found in the di-\begin{document}$J/\psi$\end{document} system was performed using a momentum-dependent Flatté-like parameterization. The use of the pole counting rule and spectral density function sum rule provides consistent evidence that both confining and molecular states are possible. Alternatively, the nature of \begin{document}$X(6900)$\end{document} cannot be distinguished if only the di-\begin{document}$J/\psi$\end{document} experimental data with current statistics are available. Nevertheless, we found that the lowest state in the di-\begin{document}$J/\psi$\end{document} system likely has the same quantum numbers as \begin{document}$X(6900)$\end{document}, and \begin{document}$X(6900)$\end{document} is probably not interpreted as a \begin{document}$J/\psi-\psi(2S)$\end{document} molecular state.     

Significance Support Vector Regression for Image Denoising

As an extension of the support vector machine, support vector regression (SVR) plays a significant role in image denoising. However, due to ignoring the spatial distribution information of noisy pixels, the conventional SVR denoising model faces the bottleneck of overfitting in the case of serious noise interference, which leads to a degradation of the denoising effect. For this problem, this paper proposes a significance measurement framework for evaluating the sample significance with sample spatial density information. Based on the analysis of the penalty factor in SVR, significance SVR (SSVR) is presented by assigning the sample significance factor to each sample. The refined penalty factor enables SSVR to be less susceptible to outliers in the solution process. This overcomes the drawback that the SVR imposes the same penalty factor for all samples, which leads to the objective function paying too much attention to outliers, resulting in poorer regression results. As an example of the proposed framework applied in image denoising, a cutoff distance-based significance factor is instantiated to estimate the samples’ importance in SSVR. Experiments conducted on three image datasets showed that SSVR demonstrates excellent performance compared to the best-in-class image denoising techniques in terms of a commonly used denoising evaluation index and observed visual.