Dynamic Correction Research Articles

A 96-well plate UV fluorometer based on micro fluorescence detector array and dynamic zero correction algorithm

A 96-well plate UV fluorometer was developed and evaluated. Eight micro fluorescence detectors close to each other were used as detector array for 8 channels. Each detector employed an UV light emitting diode (LED) as light source and a photodiode (PD) with an amplifier circuit as optoelectronic detector. The optical paths of the detectors were designed by ray tracing method to avoid crosstalk between wells. Simultaneously scanning and detecting of 8 channels saves scanning time and improves detection efficiency. The scanning time of the 96-well plate was about 80 s. A dynamic zero correction algorithm was proposed to solve the problem of measurement accuracy reduction caused by the background fluorescence differences between plates and wells under irradiation of UV light. The measurement repeatability (RSD) for 1 μg/L 7-Diethylamino-4-methylcoumarin sample was 2.25%. Compared with the fixed zero correction method, the limit of detection (LOD), measurement repeatability, and average relative error were improved by 3.3, 2.7, and 4.5 times, respectively. The proposed method is robust and can be applied to different analysis systems. The developed fluorometer has great potential in high-throughput rapid detection of food safety and life sciences.

An Integrated Framework for Real-Time Intelligent Traffic Management of Smart Highways

The new generation smart highways (NGSH) have emerged as irresistible trends to enhance the efficiency and safety of transportation systems. An integral component of the NGSH is the automation of the intelligent traffic management system (ITMS). This study investigates an integrated framework for the ITMS that incorporates the fine-grained microscopic simulation and deep learning technologies based on real-time traffic data. The framework commences by performing dynamic corrections based on the license plate, vehicle speed, location, and other information provided by the real-time bayonet data in order to simulate the realistic traffic flow along the highway. A deep learning model based on long short-term memory (LSTM) is then applied to predict the short-term traffic volume on major highway segments. Based on prediction results, a collaborative management method is constructed that combines variable speed limits and ramp metering. The case study on the Shanghai–Hangzhou–Ningbo Highway in China suggests the real-time simulation model can control the average error of the traffic volume on the main segments by 4.58%. The LSTM-based model can accurately predict the short-term traffic volume with a relative error of 85% below 15% in both offline and online modes. Consequently, the proposed collaborative framework improves the average speed and traffic volume of controlled sections by 3.62% and 4.35%, respectively, demonstrating its effectiveness in improving the operation and management of the smart highways.

Reflective Learning With Label Noise

Learning with noisy labels is one of the most challenging tasks in semi-supervised learning, and it poses significant problems in various practical applications. In the network learning process, the noisy labels concealed in the training dataset are easy to remember, resulting in poor generalization performance. To overcome this problem, inspired by the correction ability of humans – “think and learn from the past,” an end-to-end dynamic correction framework against label noise called Reflective Learning (RL) is proposed. This solution incorporates valuable knowledge from the past network training process to assist in correcting noisy labels. Specifically, during network training, a dynamic iterative function is implemented to adaptively correct noisy labels by employing the network’s predictive distribution information of all training epochs. This dynamic iterative function takes the form of a Standard Normal Distribution function to effectively match the changes of noisy label correction information contained in the network’s predictive probabilities. The proposed method is general and applicable to any backbone network and different types of noise without auxiliary information. Experiments are conducted on datasets with synthetic and real-world label noise datasets, including CIFAR-10, CIFAR-100, Tiny-ImageNet, and Clothing1M. They demonstrate that the proposed method is superior to the state-of-the-art results.

Need to assess the effect of therapy? Ask the patient!

Achieving a good treatment outcome in rheumatic diseases (RD) requires regular, dynamic patient monitoring and therapy correction if it is not effective or intolerant. The patient assessment must be based on clear criteria to objectify the main manifestations of the disease. For this purpose, the calculation of standard activity and severity indices (DAS28, CDAI, SDAI, BASDAI, ASDAS, DAPSA, PsARC, PASI, etc.) is used. However, this methodology does not always allow the assessment of the fundamentally important parameters of treatment outcome – patient satisfaction and well-being. According to a series of studies, poor therapy satisfaction may be observed in ≈25% of patients with systemic RD who are in remission/low disease activity according to standard indices. Moreover, in 20–30% of cases there is a major discrepancy in the assessment of therapy outcome between the patient and physician. Therefore, a more accurate assessment of the patient’s condition requires, in addition to the calculation of standard indices, the mandatory analysis of patient-reported outcomes – pain, functional impairment, general assessment of disease activity, fatigue, etc. A valuable tool for determining well-being and good therapy outcome from the patient’s point of view is the PASS (“patient acceptable symptom state”). This simple and quite informative index correlates well with core symptoms and indicators of remission/low disease activity. PASS analysis can be used in telemedicine follow-up of patients when an objective examination is not possible. The combined use of PASS and standardized indices can better assess treatment outcomes and improve the quality of life of patients with RD.

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

In order to ensure the continuity and endurance mileage requirements during sowing operations, it is necessary to establish accurate modeling for the working condition of the electric tractor sowing unit by adopting a reasonable energy management strategy and realizing accurate energy prediction. The existing electric tractor sowing unit battery energy management strategy is not optimal since it is mostly based on extensive rules. In this paper, according to the requirements of the sowing conditions, a precise model of electric energy consumption in the sowing cycle was established and an energy management strategy of sowing unit of extended-range electric tractor with power CD-CS was proposed. Fuzzy control rules of the dynamic SOC correction factor were established in the battery maintenance stage, and the NSGA-II algorithm was used to optimize the fuzzy control rules to optimize the battery charging and discharging efficiency. A hardware-in-the-loop simulation test platform was built, and the proposed CD-CS strategy was compared with the fuzzy improvement strategy. The simulation results show that the proposed fuzzy improvement strategy extended the battery life of the power consumption stage by 2131.9 s, which is a significant improvement. The field practical results showed that the SOC decreased by 7.21% and the simulation by 4.94% in terms of power consumption in a cycle. The power consumption variance was within a reasonable range, which further verifies the feasibility of the strategy.

Improved PPP-RTK by Considering the Non-Homogeneous Uncertainty of the ionosphere with a Spatial Three-Direction Model

The ultimate goal of PPP-RTK is to achieve rapid ambiguity resolution, which is influenced by the prior precision of the external ionospheric information. This study proposes a method for determining the precision of ionospheric corrections for each satellite. In this method, an 8 min piece-wise function linearly related to the spatial three-direction distance components (SDC) within the geocentric coordinate system is constructed. By exploiting the SDC model, the user can calculate the precision of the ionospheric corrections satellite by satellite. Using the German and French stations, we validate this method experimentally and compare it to a method with an 8 min piece-wise function constructed by the baseline length (BLL). The SDC model provides an accuracy better than 10 mm in modeling ionospheric correction precision for each GPS satellite, with an average improvement of 43% compared to the BLL model. In addition, the SDC model offers an accuracy of approximately 5 mm in the reference network with an inter-station distance of less than 100 km, which is about 15% better than that of the BLL model during the active ionospheric period. The SDC model exhibits advantages over ionospheric correction precision modeling, with an average improvement of 73.5% for a reference network with station spacing of 125–155 km. By adopting the adaptive ionospheric precision derived from the SDC model, the GPS/GPS + Galileo PPP-RTK achieves a horizontal error of 50 mm and a vertical error of 100 mm within an average of three to four epochs. Notably, the convergence time is significantly enhanced by 30% in reference networks with inter-station distances of 125–155 km, compared to that of the PPP-RTK solution generated with dynamic ionospheric correction precision from the BLL model for all observed satellites.

Anterior Dynamic Versus Posterior Transpedicular Spinal Fusion for Lenke Type 5 Idiopathic Scoliosis: A Comparison of Long-term Results

Background. Despite the active implementation of dynamic correction in case of idiopathic scoliosis, there are no comparative studies of results of posterior and anterior dynamic correction in patients with completed and near-completed growth.
 Aim of the study to compare clinical and radiological results of anterior dynamic correction and conventional posterior transpedicular correction of Lenke type 5 scoliotic defonnities in patients with completed or near-completed growth.
 Methods. Eighty-six patients with Lenke type 5 scoliotic deformities were enrolled in the study. The first group (54 patients) underwent deformity correction via posterior approach using a rigid transpedicular system; the second group (32 patients) using dynamic correction system. Mean patients age was 22.612.8 and 27.310.9 years, respectively. We studied radiological data before surgery, immediately after surgery, and 2 or more years after surgery. Blood loss volume, duration of hospital stay, and duration of narcotic analgesics intake in the early postoperative period were analyzed. Functional results were assessed using SRS-22 questionnaire.
 Results. Preoperative Cobb angle in the first group was 65.5, and 27.5 at the long-term follow-up. Junctional kyphosis of T10-L2 before surgery was 21.0 and 13.2 at the long-term follow-up. Preoperative Cobb angle of the initial curve in the second group was 52.5 and 24.5 at the long-term follow-up. Junctional kyphosis of T10-L2 before surgery was 19.5, and 19.0 at the long-term follow-up. Nash and Moe apical vertebral rotation in the first group before surgery was 1.62 and 0.17 at the last follow-up; in the second group, it was 1.80 and 0.81, respectively. Mean number of fixed levels was 6.41.0 in the first group and 5.61.5 in the second group. Mobility of the thoracolumbar/lumbai curve was higher in the second group, 28.29.1, compared with 36.0 7.2 in the first group. Preoperatively, lumbar lordosis in the second group was 42.5, in the long-tenn period 43.5, and in the first group 43.4 and 44.3, respectively.
 Conclusion. Both posterior rigid and anterior dynamic correction in case of Lenke type 5 idiopathic scoliosis can provide satisfactory radiological results with initially similar thoracolumbar deformities in patients with completed or nearcompleted growth. However, dynamic approach can reduce blood loss, duration of hospital stay, duration of narcotic analgesics intake after surgery, and improve quality of life in the long-term period.

Application of MPP database and artificial intelligence system in online evaluation of college students' mental health

Based on MPP database, we have conducted research and investigation on big data processing and analysis, and provided a good solution for big data. However, due to the large data storage requirements in the local file system may not be fully met. Therefore, the storage and management of big data, reliability, availability and scalability are more and more adopted by distributed file system. Therefore, MPP database based on distributed file system has become a research hotspot. In this paper, in the network control, through the control algorithm based on two kinds of artificial intelligence system, through the fuzzy PID controller to reduce the impact of system control performance. The dynamic BP network error correction and predictive PID controller are introduced into the system to reduce the influence. College Students' mental health education is an important part of the current training. Rapid and accurate online evaluation and analysis of College Students' mental health can provide reference for college students and effective help for the follow-up activities and consultation of the school, At the same time, it provides some basis for the balance of psychological scale and the revision of item setting. In this paper, MPP database and artificial intelligence system are introduced into the application of mental health assessment, which can effectively assess the mental health of college students, and thus promote the continuous development of assessment application.

Estimation of Seawater Hydrophysical Characteristics from Thermistor Strings and CTD Data in the Sea of Japan Shelf Zone

The knowledge of salinity in a specific sea area with high accuracy is required to solve several acoustic and hydrophysical problems on the ocean shelf. Unlike temperature, which can be measured continuously for a long time, with, for example, thermistor strings (thermostrings), salinity values of required accuracy can be obtained only using CTD profiling. This is why methods of estimating salinity from temperature could be helpful. In this paper, the authors propose using the regression method for solving this type of problem and demonstrate the efficiency of this method using examples of temperature measurements from anchored thermostrings. For the correct construction of regressions, the authors analyzed the errors of CTD measurements and suggested a method for the dynamic correction of raw CTD data. From CTD profiling datasets of 12 years (2011–2022), after their dynamic correction, the authors obtained regression polynomial formulas for calculating salinity from temperature and studied data stability in space and time at the hydrophysical test site, located in the shelf zone of the Sea of Japan. The authors consider this method efficient and applicable in solving a variety of acoustic and hydrophysical problems.

80‐1: Invited Paper: Tunable liquid crystal lens for dynamic Prescription (Rx) correction and Accommodation‐Convergence (AC) conflict correction in AR/VR/3D HMDs

While the near‐to‐eye HMDs are advancing in display resolution, there are active challenges related to accommodation‐convergence (AC) conflict correction as well as prescription correction (Rx). Many approaches are reported previously to solve AC conflict using variable focal lenses, however, very few of them included dynamic Rx correction. While AC correction requires only adjustment of focal plane, Rx correction requires simultaneous correction of focal length and astigmatism. In this report, we have shown concept, design, fabrication, and demonstration of liquid crystal based tunable lens that is capable of dynamic correction of both the issue without needing any mechanical moving parts. The device is lightweight, thin, flat, low voltage driven and has potential to replace the eyeglasses worn by the users with the HMDs.

Improvement on evaporation-condensation prediction of Lee model via a temperature deviation based dynamic correction on evaporation coefficient

Lee model has been commonly accepted for modelling the mass transfer processes subject to both evaporation or condensation. However, severe concern caused by improper setting of mass transfer relaxation coefficient exists for the high-accuracy prediction. The complicated influence factor and variable parameters result in the failure of definition on the mass transfer relaxation coefficient. In this paper, the temperature deviation based dynamic modification model to define the evaporation mass transfer relaxation coefficient (MTRC) is proposed. The MTRC is no longer needed to be manually adjusted and numerous human and computation resources could be saved, with better prediction accuracy. The hyperbolic tangent function is applied to describe the relationship between the evaporation MTRC and the product of temperature deviation and volume fraction. Compared with the commonly used Lee model, better prediction accuracy at the evaporation section can be achieved with the prediction error lowered by 38.79%, 16.24% and 4.38% under power input of 100.65, 49.61 and 19.88 W, and the maximum relative error decrement by 44.74% and the average reduction by 14.26%, which could be attributed to the elimination of liquid temperature deviation. Note that the liquid temperature deviations are strictly restrained within acceptable range 0–2 K all the time with the dynamic correction model while the temperature deviation by common Lee model would up to 13 K. Meanwhile, the proposed model is found to effectively save the computational time with reduction around 83.3% because of the quick match of the mass transfer rate impacted by the modified evaporation coefficient.

Automated dynamic motion correction improves repeatability and reproducibility of myocardial blood flow quantification with rubidium-82 PET imaging

BackgroundPatient motion reduces the accuracy of PET myocardial blood flow (MBF) measurements. This study evaluated the effect of automatic motion correction on test-retest repeatability and inter-observer variability in a clinically relevant population. MethodsPatients with known or suspected CAD underwent repeat rest 82Rb PET scans within minutes as part of their scheduled rest-stress perfusion study. Two trained observers evaluated the presence of heart motion in each scan. Global LV and per-vessel MBF were computed from the dynamic rest images before and after automatic motion correction. Test-retest and inter-observer variability were assessed using intra-class correlation and Bland-Altman analysis. Results140 pairs of test-retest scans were included, with visual motion noted in 18%. Motion correction decreased the global MBF values by 3.5% (0.80 ± 0.24 vs 0.82 ± 0.25 mL⋅min−1⋅g−1; P < 0.001) suggesting that the blood input function was underestimated in cases with patient motion. Test-retest repeatability of global MBF improved by 9.7% (0.25 vs 0.28 mL⋅min−1⋅g−1; P < 0.001) and inter-observer repeatability was improved by 7.1% (0.073 vs 0.079 mL⋅min−1⋅g−1; P = 0.012). There was a marked impact on both test-retest repeatability as well as inter-observer repeatability in the LCX territory, with improvements of 16.5% (0.30 vs 0.36 mL⋅min−1⋅g−1; P < 0.0000) and 18.4% (0.13 vs 0.16 mL⋅min−1⋅g−1; P < 0.001), respectively. ConclusionAutomatic motion correction improved test-retest repeatability and reduced differences between observers.

Improved droop control strategy for an MMC-MTDC connected to offshore wind farms with dynamic correction of the actual operating point

To solve the problems of overload of converter stations and to reduce operating loss of multi-terminal High-Voltage DC (MTDC) grids based on modular multilevel converters (MMC), an improved droop control strategy is proposed in this paper. The novelty of the suggested strategy is that two droop coefficients aimed at reducing system loss and saving power margin are non-linear weighted combined to realize multi-objective optimized operation in the full operating voltage range. First, a power allocation mechanism model of an MTDC system is built to show the influence of the droop coefficient on the DC voltage under the droop control strategy. Then, the droop coefficient under minimum operating loss is calculated and the adaptive droop coefficient is introduced to save enough power margin when the system meets large unbalanced power. In addition, a self-coordinating weight factor with a low-voltage acceleration factor is employed so that MMC can correct the operating point dynamically. Finally, a derived five-terminal MMC-MTDC is built in PSCAD/EMTDC and the effectiveness and feasibility of the proposed control method is validated by simulation.

Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising.

Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils. Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted images were acquired with 4 non-collinear directions, for which b = 50 s/mm 2 was used with 8 averages and b = 1000 s/mm 2 with 40 averages; 2 extra b = 50 s/mm 2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T. The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm 2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55-minute scan reconstructed with RMT. Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.

Nontrivial Topology Dynamical Corrections and the Magnetic Monopole-like Effect in Minkowski Spacetime

We investigate two physical systems within a spacetime region affected by the nontrivial topology. The set-up for our analysis is a Minkowski metric perturbed by elements reflecting the topological nontriviality. These elements arise when exploring Cartan’s spinorial approach along with the exotic spinors counterpart. This evinced nontrivial topology corrections in the free particle dynamics and charged particles coupled to an external electromagnetic field. As a complement, we show the appearance of a magnetic monopole-like effect.

Three-dimensional pressure field measurement on turbine guide vanes using a dynamic distortion correction endoscopic pressure-sensitive paint technique

Three-dimensional pressure field measurement on turbine guide vanes using a dynamic distortion correction endoscopic pressure-sensitive paint technique

Improving biome and climate modelling for a set of past climate conditions: evaluating bias correction using the CDF-t approach

Climate model simulations are inherently biased. It is a notably difficult problem when dealing with climate impact assessments and model-data integration. This is especially true when looking at derived quantities such as biomes, where not only climate but also vegetation dynamics biases come into play. To overcome such difficulties, we evaluate the performance of an existing methodology to correct climate model outputs, applied here for the first time to long past climate conditions. The proposed methodology relies on the ‘Cumulative Distribution Function-transform’ (CDF-t) technique, which allows to account for climate change within the bias-correction procedure. The results are evaluated in two independent ways: (i) using forward modelling, so that model results are directly comparable to reconstructed vegetation distribution; (ii) using climatic reconstructions based on an inverse modelling approach. The modelling is performed using the intermediate complexity model iLOVECLIM in the standard global and interactively downscaled over the Europe version. The combined effects of dynamical downscaling and bias correction resulted in significantly stronger agreement between the simulated results and pollen-based biome reconstructions (BIOME6000) for the pre-industrial (0.18 versus 0.44) and mid-Holocene (MH) (0.31 versus 0.40). Higher correlation is also observed between statistically modelled global gridded potential natural distribution and modelled biomes (0.36 versus 0.41). Similarly, we find higher correlation between the reconstructed and the modelled temperatures for the MH (0.02 versus 0.21). No significant difference is found for the Last Glacial Maximum when using temperature reconstructions, due to the low number of data points available. Our findings show that the application of the CDF-t method on simulated climate variables enables us to simulate palaeoclimate and vegetation distribution in better agreement with independent reconstructions.

Association of thyroidstimulating hormone, prolactin and leptin with metabolic status in young women 25-44 years old in Western Siberia

AIM: To study anthropometric, biochemical and hormonal characteristics of women aged 25-44 with different levels of thyroid- stimulating hormone, prolactin and leptin.MATERIALS AND METHODS: From a representative sample of the young population of the Oktyabrsky district of Novosibirsk aged 25-44 years (840 women), a group of women (n=655) was selected to study cardiometabolic and hormonal parameters. The design of the study was a cross-sectional, observational, single-centre study. All participants underwent determination of anthropometric parameters (weight, measurement of waist circumference (WC) and hips (HC), calculation of BMI), systolic and diastolic blood pressure (SBP, DBP), biochemical parameters (total cholesterol (TC), high-density lipoprotein cholesterol ( HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), fasting plasma glucose (FPG), creatinine, calculation of glomerular filtration rate (GFR).Statistical processing was carried out using the SPSS-13 package.RESULTS: The study included 655 women, mean age 36.3±5.4 years, mean BMI 25.0±5.7 kg/m2. Young women showed direct associations of TSH with HC (r=0.115, p&lt;0.05), TG (r=0.145, p&lt;0.010) and inverse association with GFR (r=-0.129, p&lt;0.05). PRL is inversely associated with HC (r=-0.109, p&lt;0.05). Of all the studied hormones, leptin is most associated with anthropometric and biochemical parameters in young women. Thus, leptin is directly associated with WC (r=0.562, p&lt;0.0001), HC (r=0.589, p&lt;0.0001), WC/HC index (r=0.309, p&lt;0.0001), BMI ( r=0.582, p&lt;0.0001), as well as levels of SBP (r=0.293, p&lt;0.0001), DBP (r=0.274, p&lt;0.0001), TC (r=0.123, p=0.018), TG (r=0.234, p&lt;0.0001), FPG (r=0.150, p=0.004), inversely related to HDL-C (r=-0.225, p&lt;0.0001).CONCLUSION: The metabolic status of women aged 25-44 is associated with the level of TSH, leptin. It is advisable to determine TSH, leptin in young women with abdominal obesity for the purpose of dynamic monitoring and correction.

Design and Parameter Optimization of Trajectory Correction Control Strategy for Air Duct Structure Projectile

In order to make the new air duct structure trajectory correction projectile have good dynamic correction control effect, the control strategy of the projectile’s correction mechanism is studied in this paper. A design method of trajectory correction control strategy based on particle swarm optimization-cuckoo search (PSO-CS) hybrid algorithm is proposed to obtain the optimal control parameters that can make the projectile flight stable and correct accurately. Firstly, the mathematical model of the air duct structure projectile is established. Secondly, the multiobjective optimization problem is analyzed. The projectile’s correction control strategy optimization model is established by taking the start control time, the number of corrections, the correction working time, and the interval time as the control variables. The optimization model innovatively considers the influence of the correction action on the flight stability of the projectile and the influence of the start control time on the correction range. Finally, the PSO-CS hybrid algorithm is used to design the calculation method of the optimization model and solve the optimal correction working parameters. The simulation results indicate that the control strategy optimization model can be solved by the proposed calculation method. Moreover, optimal correction working parameters of the correction mechanism in the current state can be obtained. Compared with the results of using single PSO algorithm and CS algorithm, the correction scheme calculated by PSO-CS hybrid optimization algorithm is better. This correction control scheme can effectively reduce the impact point deviation and make the projectile flight stable. At the same time, the circular error probable (CEP) of the projectile after correction is reduced from 42.3 m to 4.6 m while the impact point dispersion is lowered. The research results show that the design method of correction control strategy proposed in this paper is effective for trajectory correction of the new air duct structure projectile.

Quantum version of the integral equation theory-based dielectric scheme for strongly coupled electron liquids.

A novel dielectric scheme is proposed for strongly coupled electron liquids, which handles quantum mechanical effects beyond the random phase approximation level and treats electronic correlations within the integral equation theory of classical liquids. The self-consistent scheme features a complicated dynamic local field correction functional and its formulation is guided by abinitio path integral Monte Carlo simulations. Remarkably, our scheme is capable of providing unprecedently accurate results for the static structure factor with the exception of the Wigner crystallization vicinity, despite the absence of adjustable or empirical parameters.