Combination Of Filters Research Articles

An object detection method for catenary component images based on improved Faster R-CNN

Catenary components are an important part of electrified railways. Especially for catenary support devices, there are various types of components with significant differences in scale. According to statistical data, there is a high risk of failure for the catenary support device components during the operation of the catenary system. Therefore, in order to ensure the safe operation of the railways, it is critical to accurately locate and recognize the components in the catenary images. In this paper, we propose an improved method based on faster region-based convolutional neural networks (Faster R-CNN) framework to realize the detection and extraction of the components on the catenary support devices. Firstly, the anchor box parameters are reset using the K-means clustering method, which greatly improves the localization precision of the predicted box. Secondly, scaled exponential linear units activation function is introduced to improve the algorithm performance. Moreover, ResNet-34, the backbone of Faster R-CNN, is optimized. We design a transition structure for multi-scale filter combination convolution to avoid missing feature information and eliminate some redundant convolution structures. This modification substantially enhances the capability of the model to recognize a wide variety of component types. Finally, we conduct some control experiments comparing with single shot multibox detector and you only look once (YOLO) series (YOLOv3, YOLOv5 and YOLOv7) models. They are faster but less accurate, especially for small objects. The results show that the proposed method has better detection performance, achieving a mean average precision of 96.50% and running at 17.79 frames per second. In addition, our model has the highest average recall of 69.27%, which is 2.66% higher than the original model.

WITHDRAWN: An Investigation of a Hybrid Solar-Mineral Disinfection Technique Using Zeolite and Dead Sea Clay

Effluents from water treatment plants (WTP) can often contain a complex mixture of residual micro-contaminants and organisms, not removed during wastewater treatment. A combined trickling filter, activated sludge treatment, ozonation, membrane filtration, and suspended biofilm reactors have been shown to reduce these contaminants in waste effluent but at high capita cost. This study examined an inexpensive method of purifying water, which combines solar water disinfection with natural mineral clays (SOMIN-DIS). The study involved the addition of two types of mineral clays, Zeolite and Dead Sea minerals, to containers of polluted wastewater, at varying concentrations. The containers were then subjected to different durations of sunlight exposure. Then, samples were taken from all of the containers to quantify the overall numbers of Total Coliform, Pseudomonas aeruginosa (P.aeruginosa), and Escherichia coli (E.coli), utilizing the IDEXX system. The findings indicated that incorporating Dead Sea clay and Zeolite into SODIS-treated wastewater decreased the overall number of harmful microorganisms and shortened the disinfection duration, as compared to using natural minerals and solar water disinfection (SODIS) independently. Additionally, the study determined that the most effective concentration of Dead Sea minerals, resulting in the least amounts of harmful microorganisms and shortest purification duration, was 0.001g/ml. In contrast, the optimum concentration of Zeolite was 0.002g/ml. In general, the addition of Dead Sea and Zeolite minerals to the wastewater increased the inactivation of bacteria under SODIS from 40% to 65%.

Robust Bias Compensation Method for Sparse Normalized Quasi-Newton Least-Mean with Variable Mixing-Norm Adaptive Filtering

Input noise causes inescapable bias to the weight vectors of the adaptive filters during the adaptation processes. Moreover, the impulse noise at the output of the unknown systems can prevent bias compensation from converging. This paper presents a robust bias compensation method for a sparse normalized quasi-Newton least-mean (BC-SNQNLM) adaptive filtering algorithm to address these issues. We have mathematically derived the biased-compensation terms in an impulse noisy environment. Inspired by the convex combination of adaptive filters’ step sizes, we propose a novel variable mixing-norm method, BC-SNQNLM-VMN, to accelerate the convergence of our BC-SNQNLM algorithm. Simulation results confirm that the proposed method significantly outperforms other comparative works regarding normalized mean-squared deviation (NMSD) in the steady state.

Narrow linewidth fiber laser using compound-ring cavity filter and self-injection locked mechanism

Narrow linewidth erbium-doped fiber lasers (EDFLs) hold in significant potential optical fiber sensing, wavelength multiplexing transmission, and optical fiber communication. However, many EDFLs produced outputs with linewidth in several kHz level. Therefore, a high optical signal-to-noise ratio (OSNR), narrow linewidth single-longitudinal-mode (SLM) EDFL was proposed and investigated in this work. The EDFL utilized a combination of compound-ring cavity filter and a self-injection locked mechanism to generate a stable SLM output with an OSNR greater than 72 dB. The maximum wavelength drift and maximum peak power fluctuation over 60 min were maintained at low values of 0.0041 nm and 0.16 dB. Moreover, a narrow linewidth of 1.82 kHz at a measuring time of 0.002 s was realized. Furthermore, the research also investigated output power variations with different pump powers, relaxation oscillation, and the dependence of output central wavelength on the axial strain.

Assessing the Influences of Noise Suppression Filters on Ultrasonic Concrete Images Generated by an Innovative CMU-SAFT Algorithm

AbstractUltrasonic imaging is a useful nondestructive testing technology for visualizing internal structural defects in structures. Despite its utility, since synthetic aperture focusing technique (SAFT) algorithm demands using advanced equipment to superimpose the measurements, this paper introduces a novel approach named CMU-SAFT to broaden applicability of SAFT on conventional ultrasonic data obviating the necessity for matrix antenna array-equipped devices and preventing hyperbolic patterns. To validate the feasibility of the proposed algorithm, experimental tests were conducted on a laboratory-produced concrete specimen including delamination defects at varying depths. Since other reflectives causing distortion in the ultrasonic image can interfere with the signal, the study also evaluated the influences of different noise suppression filters along with their combinations (band pass, wavelet transform, Wiener, and Savitzky–Golay). CMU-SAFT images were constructed using eleven filter combinations, and their performances were quantitatively assessed using signal-to-noise ratio, signal-to-noise and distortion ratio, total harmonic distortion, root mean square, mean squared ratio, mean absolute error and cross-correlation. The most effective filters and performance indices aligning with CMU-SAFT images considering defect depth and scanning width were suggested. The findings of the study revealed the leading potential of CMU-SAFT algorithm to overcome the need for specialized equipment by utilizing recommended filters and indicators under specific conditions.

A Single-Longitudinal-Mode S + C Band Wavelength-Tunable Fiber Laser.

An external cavity wavelength-fiber ring laser (ECWTFL) based on a semiconductor optical amplifier and a combined wavelength scanning filter in the Littrow configuration is proposed and experimentally demonstrated. With the benefit of the combination of an external cavity wavelength filter and a Lyot filter, the laser achieves a single-mode narrow linewidth output with a linewidth of 1.75 kHz. The wavelength tuning range reaches 133 nm, covering the entire S + C band. The proposed ECWTFL is used for demodulation of a fiber EFPI sensor; the result shows that the proposed ECWTFL has the ability to demodulate the small cavity-length FPI sensor.

Analysis method and experimental study of ice accumulation detection signal based on Lamb waves

A quantitative identification method for in-flight icing has the capability to significantly enhance the safety of aircraft operations. Ultrasonic guided waves have the unique advantage of detecting icing in a relatively large area, but quantitative identification of ice layers is a challenge. In this paper, a quantitative identification method of ice accumulation based on ultrasonic guided waves is proposed. Firstly, a simulation model for the wave dynamics of piezoelectric coupling in three dimensions is established to analyze the propagation characteristics of Lamb waves in a structure consisting of an aluminum plate and an ice layer. The wavelet transform method is utilized to extract the Time of Flight (ToF) or Time of Delay (ToD) of S0/B1 mode waves, which serves as a characteristic parameter to precisely determine and assess the level of ice accumulation. Then, an experimental system is developed to evaluate the feasibility of Lamb waves-based icing real-time detection in the presence of spray conditions. Finally, a combination of the Hampel median filter and the moving average filter is developed to analyze ToF/ToD signals. Numerical simulation results reveal a positive correlation between geometric dimensions (length, width, thickness) of the ice layer and ToF/ToD of B1 mode waves, indicating their potential as indicators for quantifying ice accumulation. Experimental results of real-time icing detection indicate that ToF/ToD will reach greater peak values with the growth of the arbitrary-shaped ice layer until saturation to effectively predict the simulation results. This study lays a foundation for the practical application of quantitative icing detection via ultrasonic guided waves.

Evaluation of the mean glandular dose (MGD) for phantoms with different glandularity/adipose tissue ratios using MgB4O7:Dy,Na dosimeters in mammography

This study focuses on the use of MgB4O7:Dy,Na dosimeters in mammography measurements. The reproducibility measurement and dose-response curves were studied for the characterization of dosimeters. Next, variation in entrance surface dose (ESD) and mean glandular dose (MGD) was investigated according to different glandularity/adipose tissue ratios of 30%/70%, 50%/50% and 70%/30% for fixed anode and variable filter combinations (Mo/Mo, Mo/Rh) using BR-12 phantoms with thicknesses from 2 to 6 cm. The ESD and MGD values increased at varying rates with increasing phantom thicknesses and glandularity ratios. The increase rate in MGD is ∼30% for both Mo/Mo and Mo/Rh for the difference between (70%/30%) and (50%/50%), considering the thickness of 6 cm. On the other hand, the MGD value obtained for a glandular ratio of 70%/30% at 6 cm for Mo/Mo is ∼40% higher than that for Mo/Rh. A proportional comparison of MGD differences obtained according to glandularity and filter changes may provide valuable contributions to the literature. Within this study, it was shown that MgB4O7:Dy,Na dosimeters can be used as new alternative dosimeters in the field of mammography to perform ESD and MGD measurements. In further studies, MgB4O7:Dy,Na dosimeters can be used to determine the various organ doses, such as eye and thyroid, resulting from the scattered radiation dose using rando phantoms.

Experimental study on an enhanced integral force feedback controller for active damping

In this paper, an enhanced integral force feedback controller is proposed for implementing active damping. Compared with the classical integral force feedback, the pure integrator is replaced with a combination of a first-order low-pass filter and a proportional term. The control performance of the proposed controller is examined on a single-degree-of-freedom host system. In order to better understand the physics behind, a full equivalent mechanical model is derived. It is found that the first-order low-pass filter is mechanically equivalent to a spring and a damper connected in parallel. The proportional term mechanically represents a spring which is connected in series with the inherent actuator spring. The optimal control parameters are numerically obtained with the ℋ∞ optimisation criterion. The analysis shows that the optimal feedback gain can be practically taken the same as that of the classical integral force feedback controller in the sense that the difference between the resultant control performance is negligible. The numerical study is also experimentally validated. The obtained results are found to correspond well with the theoretical developments.

Lipid droplet detection in histopathological images using reinforcement learning

The identification and analysis of lipid droplets in pathological images are pivotal owing to the variations in their size, shading and shape. The development of an artificial intelligence-based automatic detection method can facilitate the analysis of complex pathological images and provide essential support to pathologists. In this paper, we introduce a novel approach for the automated detection of lipid droplets, employing a limited set of images and a modest application of reinforcement learning (RL). Several filters tailored to lipid droplet size and contrast are used in combination. Through the combination of multiple filters using RL, potential lipid droplet regions are identified within pathological images. Subsequently, a random forest classifier is employed to distinguish between normal and lipid droplet images. Evaluation guided by the expertise of two pathologists with over 10 years of clinical experience indicated the hierarchical extraction of lipid droplets with consistent size and shading in pathological tissue images utilizing RL. The proposed method successfully detected lipid droplets in pathological images and facilitated the determination of both the quantity and distribution of lipid droplets within cells. The results highlight the efficacy of the approach in lipid droplet detection. This method is also useful for small to medium-sized fat droplets, which are relatively difficult for humans to detect from their morphology.

Pa-Count: Passenger Counting in Vehicles Using Wi-Fi Signals

Passenger counting is crucial for many applications such as vehicle scheduling and traffic capacity assessment. However, most of the existing solutions are either high-cost, privacy invasive or not suitable for passengers the vehicle scenarios. In this work, we propose the <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Pa</u> - <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Count</u> , an effective real-time <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Pa</u> ssenger <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Count</u> ing system deployed inside the vehicle via using Wi-Fi <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CSI</i> (Channel State Information). Specifically, in Pa-Count, we design a set of combined filters to eliminate environmental interference and enhance CSI quality. In so doing, we can identify the fluctuation of weak CSI caused by passengers' subtle movement, i.e., the fidgeting, and then obtain the distribution of fidgeting period and silent period. Following that, we describe the subtle movements of passengers via power law with exponential cutoff distribution and establish a counting model based on the queuing theory. A mathematical inference method with a priori probability is devised to calculate the number of real-time passengers through CSI. We evaluate the performance of the Pa-Count by conducting a set of experiments in real-world vehicle scenarios (including private car and subway). Experimental results show that Pa-Count can achieve robust performance with an average accuracy of over 92 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Improvement of rejection band with Defected Microstrip Line and Ground plane Resonators

In this paper first a dual band bandstop filter is proposed using a unique spiral defect at the signal plane for Wi-Fi communication and remote sensing applications. The spiral defects is studied, simulated and measured. Next proposed spiral defect is combined with the hexagonal head defected resonators at ground plane to improve the rejection band. In addition a study is also done to observe the effects of the proposed defects at both signal plane and ground plane. A comparison is done among the response of individual defects filters and combined defect filter. It is observed that later shows improved overall bandwidth with compactness. The proposed combined defect filter with improved stopband displays 92.6% FBW and 112.5 dB/GHz sharpness factor with very compact in size as 0.26 λ0 × 0.25 λ0. All measurement results are in good agreement with the simulated results.

Compartmental anisotropy of filtered exchange imaging (FEXI) in human white matter: What is happening in FEXI?

To investigate the effects of compartmental anisotropy on filtered exchange imaging (FEXI) in white matter (WM). FEXI signals were measured using multiple combinations of diffusion filter and detection directions in five healthy volunteers. Additional filters, including a trace-weighted diffusion filter with trapezoidal gradients, a spherical b-tensor encoded diffusion filter, and a T2 filter, were tested with trace-weighted diffusion detection. A large range of apparent exchange rates (AXR) and both positive and negative filter efficiencies (σ) were found depending on the mutual orientation of the filter and detection gradients relative to WM fiber orientation. The data demonstrated that the fast-diffusion compartment suppressed by diffusional filtering is not exclusively extra-cellular, but also intra-cellular. While not comprehensive, a simple two-compartment diffusion tensor model with water exchange was able to account qualitatively for the trends in positive and negative filtering efficiencies, while standard model imaging (SMI) without exchange could not. This two-compartment diffusion tensor model also demonstrated smaller AXR variances across subjects. When employing trace-weighted diffusion detection, AXR values were on the order of the R1 (=1/T1) of water at 3T for crossing fibers, while being less than R1 for parallel fibers. Orientation-dependent AXR and σ values were observed when using multi-orientation filter and detection gradients in FEXI, indicating that WM FEXI models need to account for compartmental anisotropy. When using trace-weighted detection, AXR values were on the order of or less than R1, complicating the interpretation of FEXI results in WM in terms of biological exchange properties. These findings may contribute toward better understanding of FEXI results in WM.

Beta irradiation-induced thermoluminescence: Glow curve analysis and kinetic parameters in combustion-synthesized undoped Ca4YO(BO3)3

This study examines the thermoluminescent (TL) properties of undoped Ca4YO(BO3)3 phosphor, focusing on how it behaves under a variety of experimental conditions. The IRSL-TL 565 nm was chosen as the appropriate detection filter among various optical detection filter combinations. During the preheating trials conducted at a rate of 2 °C/s, the TL peak exhibited increased intensity, particularly around 200 °C. The experimental outcomes demonstrated a reliable linear relationship (R2 = 0.996 and b = 1.015) in the dose response of undoped preheated Ca4YO(BO3)3 within the range of 1–200 Gy. The investigation encompasses a range of techniques, including the TM-Tstop method, computerized glow curve deconvolution (CGCD) analysis, and theoretical modelling. The application of the TM-Tstop method to samples irradiated with a 5 Gy dose revealed distinct zones on the TM versus Tstop diagram, signifying the presence of at least two discernible components within the TL glow curve, specifically, a single general order kinetics peak and a continuous distribution. The analysis of activation energy versus preheated temperature exhibited a stepwise curve, indicating five trap levels with depths ranging between 1.13 eV and 1.40 eV. The CGCD method also revealed the superposition of at least five distinct TL glow peaks. It was observed that their activation energies were consistent with the Tm-Tstop experiment. Furthermore, the low Figure of Merit (FOM) value of 1.18% indicates high reliability in the goodness-of-fit measure. These findings affirm the reliability and effectiveness of the employed methods in characterizing the TL properties of the Ca4YO(BO3)3 phosphor under investigation. Theoretical models, including the semi-localized transition model, were introduced to explain anomalous observations in TL glow peak intensities and heating rate patterns. While providing a conceptual framework, these models may require adjustments to accurately capture the specific characteristics uncovered through CGCD analysis. As a potential application, the study suggests that the characterized TL properties of Ca4YO(BO3)3 phosphor could be utilized in dosimetric applications, such as radiation dose measurements, owing to its reliable linear response within a broad dose range.

Lightcurve Analysis of a Sample of Asteroids and Comets Observed with the Isaac Newton Telescope

We present an analysis of six asteroids and one comet using data from the Wide Field Camera on the Isaac Newton Telescope, La Palma. As part of this work we developed a pipeline to reduce and absolutely calibrate photometry of inactive small bodies. For three of the objects, there was sufficient data to measure their rotation periods. We report rotation periods of (2.7774 ± 0.0004) hr and (3.121 ± 0.003) hr for main belt asteroids (7891) Fuchie and 1999 CP29 respectively, neither of which to our knowledge currently have a well-constrained rotation period. We also measure a rotation period for Jupiter-family comet 169P/NEAT of (8.37 ± 0.04) hr which is consistent with previous works. Colours in various filter combinations (Sloan r′ , g′ , i′ and RGO Z) were also determined, and for the six observed asteroids we present an approximate taxonomic classification.

Evaluation of the photoprotective and antioxidant potential of an avobenzone derivative.

Solar radiation can cause damage to the skin, and the use of sunscreens is one of the main protective measures. However, photounstable ultraviolet (UV) filters can generate photoproducts and reactive oxygen species (ROS). Adding antioxidants, such as resveratrol, to enhance the action of UV filters in sunscreens is an interesting strategy for reducing the damage caused by UV radiation exposure. However, new compounds must have their stability, safety and efficacy guaranteed. Avobenzone, a commonly used UV filter, stands out as a promising candidate for structural modification to enhance its stability. Its molecular hybridization with other UV filters and antioxidants can lead to safer and more effective compounds. In this study, the photoprotective and antioxidant potential of a derivative of avobenzone, hybridized with resveratrol's molecule, was evaluated using in vitro models of cells in monolayer and reconstructed human skin (RHS). Phototoxic potential was assessed using fibroblasts, while the antioxidant activity was measured using the DCFH2-DA probe in HaCaT keratinocytes and in-house RHS. The derivative exhibited UV absorption and demonstrated photostability. It did not exhibit any phototoxic nor photoreactivity potential. Additionally, it was able to photo stabilize a combination of photounstable UV filters, avobenzone and octyl methoxycinnamate, and to reduce their phototoxic potential. In terms of antioxidant activity, the derivative successfully protected against UVA-induced ROS production in the HaCaT keratinocytes model, showing statistical equivalence to the antioxidant control, quercetin (10μg/mL). Furthermore, experiments conducted in the RHS model demonstrated a significant reduction of 30.7% in ROS generation compared to the irradiated control. This study demonstrated that structural modifications of avobenzone can lead to the development of a broad spectrum (absorbing UVB and UVA II radiation, as well as a portion of the UVA I radiation), non-phototoxic, non-photoreactive and photostable derivative for sunscreen and anti-aging formulations. This derivative enhances protection against oxidative stress induced by UV radiation and improves the effectiveness of sun protection. In addition to the monolayer model, the use of a standardized in-house RHS model was highly relevant for evaluating the effects of UV radiation and skin aging. This model closely mimics human physiological conditions and enables the testing of new compounds and the investigation of protective mechanisms against skin damage.

Computer-Aided Diagnosis System for Automated Detection of Mri Brain Tumors

Detection and classification of brain tumors in manual or traditional way is an area which could be improved by having such automated detection and clarification system for brain tumors. In this paper, enhanced Computer-Aided Diagnosis CAD software system is introduced for brain tumor detection and classification. Total of 229 brain MRI images was taken as dataset for the purpose of this research; those dataset images include 105 normal brain MRI images, and 124 abnormal brain MRI images. Proposed CAD system is specialized for Meningioma brain tumor detection and classification, and the technique could be generalized and implemented for Glioma, and Pituitary brain tumors as well, and the whole system was implemented using MATLAB software. We started by cropping the region of interest (ROI) of dataset images. Then, feature extraction was implemented using first order statistical features, as well as using of some wavelets filters in combination with the former. T-test is used to exclude features of no statistical significance (p-value &lt; 0.05). After that, different types of classifiers were used to separate the normal set from the abnormal one. Note that, we used an iterative approach to by changing features with many runs until we got best performance, where, best accuracy results were gotten with SVM-Kernel Function (Linear), KNN-1, KNN-3, and KNN-5 classifiers. Note also that, we used convolutional neural networks (CNN) from Deep Learning toolbox of MATLAB as a control method to compare, where the images were fed directly to the CNN. The results were evaluated using performance assessment techniques which are Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy, Error Rate, and Area Under the Curve (AUC) of Reciever Operator Characteristic (ROC). With SVM classifier, the best gotten accuracy results were 91 % with CNN classifier, 82% with SVM classifier, and 77 % with KNN classifier. Furthermore, it was very beneficial to find such feature extraction techniques which gave acceptable accuracy results with three different classifiers; this was the case two times as mentioned the study. All proposed CAD system areas was developed and implemented using MATLAB software.

Research on Analysis and Suppression Methods of the Bearing Current for Electric Vehicle Motor Driven by SiC Inverter

The silicon carbide (SiC) inverter brings great advantages to the motor drive systems of new energy vehicles; however, severe challenges to the bearings also happen. The high dc bus voltage and switching frequency of SiC inverter can increase the discharge frequency and energy when the bearing grease film collapses. As a result, the bearing suffers severe electric corrosion, and the service life of the motor drive system can be shortened. In this paper, the characteristics of common-mode voltage and bearing voltage are analyzed, firstly under space vector pulse width modulation (SVPWM). After that, the common-mode equivalent circuit model of the motor drive system is established. The frequency characteristics of bearing voltage are revealed, and the safe working area is determined. Then, the frequency characteristics of bearing voltage and current are verified based on IGBT and SiC inverters in experiments. After that, by designing a common-mode filter, the bearing voltage and current are significantly attenuated. Furthermore, the active zero state PWM (AZSPWM) is adopted to reduce the common-mode voltage from the inverter. At the same time, combined with the common-mode filter, the bearing voltage and current are further reduced. The experimental results show that the switching frequency has a decisive effect on the amplitude of bearing voltage and current. The bearing voltage can be attenuated to around half of the reference bearing voltage by using the common-mode filter and AZSPWM strategy, respectively. The combination of the common-mode filter and AZSPWM strategy can reduce the bearing voltage to around one-fourth of the reference bearing voltage, which can effectively reduce the breakdown time and discharge energy of the grease oil film.

High-efficiency low-power 13C-15N cross polarization in MAS NMR

Biomolecular solid-state magic angle spinning (MAS) NMR spectroscopy frequently relies on selective 13C-15N magnetization transfers, for various kinds of correlation experiments. Introduced in 1998, spectrally induced filtering in combination with cross polarization (SPECIFIC-CP) is a selective heteronuclear magnetization transfer experiment widely used for biological applications. At MAS frequencies below 20 kHz, commonly used for 13C-detected MAS NMR experiments, SPECIFIC-CP transfer between amide 15N and 13Cα atoms (NCA) is typically performed with radiofrequency (rf) fields set higher than the MAS frequency for both 13C and 15N channels, and high-power 1H decoupling rf field is simultaneously applied. Here, we experimentally explore a broad range of NCA zero-quantum (ZQ) SPECIFIC-CP matching conditions at the MAS frequency of 14 kHz and compare the best high- and low-power matching conditions with respect to selectivity, robustness, and sensitivity at lower 1H decoupling rf fields. We show that low-power NCA SPECIFIC-CP matching condition gives rise to 20% sensitivity enhancement compared to high-power conditions, in 2D NCA spectra of microcrystalline assemblies of HIV-1 CACTD-SP1 protein with inositol hexakis-phosphate (IP6).

Impact of modifiers on soil–water characteristics of graphite tailings

To achieve integrated resource utilization of graphite tailings to improve their water-holding capacity, river silt and cow dung powder were added to graphite tailings as organic matter improvers. Improver ratios were designed using 4 g cow dung powder and 20, 30, and 50 g river silt. Soil–water characterization tests were performed using a combined tensiometer and filter paper method based on optimum density measurements. Analysis of the influence of river silt dosing on the soil–water characteristic curves of improved graphite tailing specimens was performed with data fitting using the Van Genuchten model. Here, we investigated the effect of river silt dosing on the internal pore structure and water-holding capacity of modified graphite tailing samples and verified the applicability of the model to graphite tailings. Our results demonstrate that the organic matter improver incorporated into graphite tailings can improve the internal structural compactness of graphite tailings, improving the water holding capacity. With an increase in river silt dosage, the saturated water content is larger, and the residual water content increases and then decreases. When river silt dosage is 30 g, the residual water content is the highest at a value of 3.32%. The van Genuchten model was highly accurate for assessing the graphite tailings. With an increase in river silt doping, the internal pore space first decreased and then increased, and the internal structure gradually became compact and loosened. The internal structure was in the optimal state in the experimental study when the dosage of cow dung powder was 4 g and the dosage of river silt was 30 g. The water holding capacity was optimal at this time. The results of this study provide a theoretical foundation for graphite-tailing-based mine reclamation and play a guiding role in exploring the value of the hydraulic characteristic index parameters when applying graphite tailings engineering.