Rate Of Change Research Articles

Identification of Genetic Risk Factors Based on Disease Progression Derived From Longitudinal Brain Imaging Phenotypes.

Neurodegenerative disorders usually happen stage-by-stage rather than overnight. Thus, cross-sectional brain imaging genetic methods could be insufficient to identify genetic risk factors. Repeatedly collecting imaging data over time appears to solve the problem. But most existing imaging genetic methods only use longitudinal imaging phenotypes straightforwardly, ignoring the disease progression trajectory which might be a more stable disease signature. In this paper, we propose a novel sparse multi-task mixed-effects longitudinal imaging genetic method (SMMLING). In our model, disease progression fitting and genetic risk factors identification are conducted jointly. Specifically, SMMLING models the disease progression using longitudinal imaging phenotypes, and then associates fitted disease progression with genetic variations. The baseline status and changing rate, i.e., the intercept and slope, of the progression trajectory thus shoulder the responsibility to discover loci of interest, which would have superior and stable performance. To facilitate the interpretation and stability, we employ l2,1 -norm and the fused group lasso (FGL) penalty to identify loci at both the individual level and group level. SMMLING can be solved by an efficient optimization algorithm which is guaranteed to converge to the global optimum. We evaluate SMMLING on synthetic data and real longitudinal neuroimaging genetic data. Both results show that, compared to existing longitudinal methods, SMMLING can not only decrease the modeling error but also identify more accurate and relevant genetic factors. Most risk loci reported by SMMLING are missed by comparison methods, implicating its superiority in genetic risk factors identification. Consequently, SMMLING could be a promising computational method for longitudinal imaging genetics.

Geospatial analysis of shoreline changes in the Oman coastal region (2000-2022) using GIS and remote sensing techniques

This research introduces an innovative method employing the Canny edge detector for automatic and precise coastline extraction, aiming to analyze spatial and temporal variations in the Oman coastline from 2000 to 2022 using GIS and remote sensing (RS) techniques. Focusing on both multi-decadal and short-term periods, the study aims to detect accretion and erosion rates through the observation and interpretation of coastal changes. Utilizing the Digital Shoreline Analysis System and LANDSAT imageries, Shoreline changes have been quantitatively evaluated using three distinct approaches: Linear Regression Rate (LRR), End Point Rate (EPR), and Net Shoreline Movement (NSM). The dynamic nature of the Oman coastal region necessitates a comprehensive understanding of its evolving coastline. Our investigation applies digital shoreline analysis to discern shifts in the coastline’s position, employing a multiple regression approach for quantifying the rate of coastal change. To facilitate automatic shoreline extraction, various methods were experimented with, ultimately determining the Canny Edge algorithm’s superiority in yielding precise results. The paper outlines the monitoring procedures for the coastal area and analyzes coastline changes using geospatial techniques. This analysis provides valuable insights for the planning and management of the Oman shore. Furthermore, the proposed model’s applicability is rigorously tested against other generic edge detection algorithms, including Sobel, Prewitt, and Robert’s techniques. The conclusive findings demonstrate that our model outperforms these alternatives, particularly excelling in the accurate detection of the coastline. This research contributes to a deeper understanding of coastal dynamics and offers a robust methodology for coastal monitoring, with implications for effective planning and management strategies in the Oman shore region.

Use of a machine learning algorithm with a focus on spinopelvic parameters to predict development of symptomatic tethered cord after initial untethering surgery.

Among patients with a history of prior lipomyelomeningocele repair, an association between increased lumbosacral angle (LSA) and cord retethering has been described. The authors sought to build a predictive algorithm to determine which complex tethered cord patients will develop the symptoms of spinal cord retethering after initial surgical repair with a focus on spinopelvic parameters. An electronic medical record database was reviewed to identify patients with complex tethered cord (e.g., lipomyelomeningocele, lipomyeloschisis, myelocystocele) who underwent detethering before 12 months of age between January 1, 2008, and June 30, 2022. Descriptive statistics were used to characterize the patient population. The Caret package in R was used to develop a machine learning model that predicted symptom development by using spinopelvic parameters. A total of 72 patients were identified (28/72 [38.9%] were male). The most commonly observed dysraphism was lipomyelomeningocele (41/72 [56.9%]). The mean ± SD age at index MRI was 2.1 ± 2.2 months, at which time 87.5% of patients (63/72) were asymptomatic. The mean ± SD lumbar lordosis at the time of index MRI was 23.8° ± 11.1°, LSA was 36.5° ± 12.3°, sacral inclination was 30.4° ± 11.3°, and sacral slope was 23.0° ± 10.5°. Overall, 39.6% (25/63) of previously asymptomatic patients developed new symptoms during the mean ± SD follow-up period of 44.9 ± 47.2 months. In the recursive partitioning model, patients whose LSA increased at a rate ≥ 5.84°/year remained asymptomatic, whereas those with slower rates of LSA change experienced neurological decline (sensitivity 77.5%, specificity 84.9%, positive predictive value 88.9%, and negative predictive value 70.9%). This is the first study to build a machine learning algorithm to predict symptom development of spinal cord retethering after initial surgical repair. The authors found that, after initial surgery, patients who demonstrate a slower rate of LSA change per year may be at risk of developing neurological symptoms.

Numerical investigation on the exhaust gas combustion of an SOFC in a catalytic multichannel burner

The utilization of the exhaust gas of a solid oxide fuel cell is important to improve the energy efficiency and control pollutant emission. In this work, the combustion of solid oxide fuel cell exhaust gas (H2/CO) in a honeycomb ceramic catalytic burner is investigated numerically. A 2D numerical combustion model with 17 channels is built to analyze the influence of channel position on thermal performance and combustion characteristics. The high burnout of H2 and CO is obtained as 96.75% and 97.75%, respectively. The channels can be divided into three groups from the inside to the outside as follows: part 1, from the 9th channel to the 13th channel; part 2, from the 14th channel to the 16th channel; and part 3, the 17th channel. The channels in the same group presented the same results of flow, temperature, and combustion. Compared with the other channels, the outermost channel shows notable differences in depressing the temperature of the whole channel, moving the maximum temperature downstream, enlarging the temperature bias of the lower and upper walls, and enlarging the combustion zone. H2 and CO perform different combustion processes in the honeycomb ceramic catalytic burner. Compared with H2, the initial position of CO conversion is more affected by channel distribution. In the 17th channel, the CO oxidation rate is controlled mostly by the slower oxygen adsorption and the resulting low O(s) coverage. In the 9th channel, the CO oxidation rate is controlled mostly by the wall temperature and fuel-limited. The burnout rate of H2 changes from 95% to 99.9% with the channel position, but the burnout of CO varies little. The closer the channel to the outer wall, the higher the proportion of heterogeneous reaction and the more the generated heat. The generated heat by the channel can present a diversity of 4%.

<i>Gamitaeeumjowee-tang</i> for Weight Loss in Post-Menopausal Obese Women: A Retrospective Chart Review

Objectives: The purpose of this study is to evaluate weight change and analyze adverse events in post-menopausal obese women with <i>Gamitaeeumjowee-tang</i> for weight loss.Methods: A retrospective chart review was conducted for medical records of 115 post-menopausal obese women (body mass index, BMI≥25 kg/m<sup>2</sup>) who were administered with <i>Gamitaeeumjowee-tang</i> for 12 weeks for the purpose of weight loss. Weight, skeletal muscle ratio and BMI changes were compared before and after the program. Adverse events were evaluated by causality, severity and system-organ classes.Results: A total of 115 patients were included in this study. The average total weight loss in post-menopausal women was 5.72±2.04kg(p<0.001) and the average weight loss rate was 8.06±2.70%(p<0.001). After the 12-week program, the body fat rate was significantly decreased(3.76±2.20%)(p<0.001) and the skeletal muscle ratio was significantly increased(2.07±1.24%)(p<0.001). There were no significant differences in weight loss, skeletal muscle ratio change and body fat rate change depending on the number of hospital visits. Insomnia was frequently reported throughout the period, and no serious adverse events were reported.Conclusions: This study showed the potential that weight management treatment with <i>Gamitaeeumjowee-tang</i> could be a good way to lose weight of post-menopausal obese women without serious adverse events. Continuous well designed clinical studies are needed.

An optimal cyber–physical attack strategy on DC microgrids

This paper proposes an optimal attack strategy against Direct Current MGs (DCMGs). In the proposed strategy, attackers first eavesdrop on the data communicated between a target converter and the MG Control Center (MGCC) to model (i) the converter by its state-space representation using system identification techniques, and (ii) the rest of the system by its Thevenin equivalent circuit using the least-square method. Afterwards, the obtained model is used in an optimal control framework to design a False Data Injection Attack (FDIA) that controls the converter’s output to achieve the attackers’ objective, e.g., triggering the overcurrent or under-voltage protection of the converter. The proposed framework fulfills the objective while minimizing the rate of change of the converter’s voltage and the required control effort during the FDIA (to keep the attack stealthy) in the presence of the attack constraints. Such an attack strategy provides cyber-security experts with insight into potential attacks and their impacts on the operation and stability of DCMGs, and helps them to design and test their cyber-security measures more effectively. Simulation results in MATLAB/Simulink corroborates the effectiveness of the proposed attack strategy.

Inertial issues in renewable energy integrated systems and virtual inertia techniques

The global proliferation of renewable energy drastically altered the characteristics of power systems. Integration of clean energy sources reduces the inherent rotational inertia, making the system precarious and susceptible to various disturbances. The major challenges encountered are fast frequency fluctuations, voltage fluctuations, high rate of change of frequency (RoCoF), and frequency nadir. In order to address and adapt to a future low-inertia scenario, it is crucial to understand the effect of inertia on various parameters. This paper introduces a comprehensive review of the fundamental aspects of inertia and challenges that arise due to the reduction in inertia. Researchers have tackled this issue by employing various virtual inertia (VI) emulation techniques, which also have been extensively reviewed in the literature along with their merits, limitations, and recent developments. The impact of RES penetration on system dynamics is analyzed by simulating an IEEE-9 bus system with renewable energy source (RES) in MATLAB/Simulink. Furthermore, a three-phase fault is also introduced, to emphasize the effect of reduced inertia by observing the rotor angle and frequency deviation. The results validate that RES integration and fault location are observed to have a significant impact on stability parameters, making them extremely unstable.

Ultrasonic metrics for large-area rapid wrinkle detection and classification in composites

Due to their high strength-to-weight ratio, composite materials are now in use in many high-stress applications, particularly where light weight is also a requirement. In these situations, the detrimental knock-down in mechanical strength due to an out-of-plane wrinkle defect can have serious consequences and is the reason for a requirement to rapidly detect any such wrinkles at manufacture. Unfortunately, current ultrasonic inspection techniques used for quality control at manufacture are not sensitive enough to detect these wrinkles above coherent structural noise variations. This paper exploits the ply resonance that is a characteristic of multi-layer structures to generate two new metrics for both detection and classification of out-of-plane wrinkles, due to their perturbations of the ply spacing. These can be measured at every location on a structure using the instantaneous frequency, which is the rate of change of phase in the pulse-echo ultrasonic response. The proposed two new metrics for detection and classification of wrinkles are mean spacing and spacing difference and they can be applied to each waveform in real time, as it is acquired. Use of an analytical model to predict the ultrasonic response of the structure has allowed an understanding of how these metrics will be affected by various wrinkle types and how they can not only detect wrinkles but also classify the type of wrinkle and provide an approximate indication of severity. Three main types of wrinkle are considered: classic wrinkles near the mid-plane of a structure, back-surface wrinkles formed from a resin bulge near the back of a structure and folded wrinkles where several plies can be folded over completely in the bulk of the structure. Both simulations and experimental results demonstrate the effectiveness of these metrics on various types of structure, including carbon-fibre and hybrid carbon/glass-fibre composites with a range of ply thicknesses and wrinkle types.

Optimization of magnetic coupling mechanism of dynamic wireless power transfer based on NSGA-II algorithm

Optimization of magnetic coupling mechanism is an important way to improve the performance of a dynamic wireless power transfer system. Inspired by the common radial magnetic core for circular coils, a new radial magnetic core for rectangular coils is adopt. Through simulation and experimental results comparison, which has higher coupling coefficient with the same core area. Combined with the magnetic circuit analysis, the magnetic flux leakage and conduction regions are divided into magnetic fluxes with different shapes, which magnetic resistances are calculated respectively. Based on the simulation results, parameter distributions of fluxes under different conditions are obtained. Therefore, the expressions of the coupling coefficient k of the adopt magnetic cores and coils and the design parameters of coils and cores are obtained. Taking the maximum k and the minimum rate of change of coupling coefficient with 100 mm displacement as the optimization objectives, a multi-objective optimization solution is carried out by using NSGA-II algorithm. The coil optimization scheme is obtained and verified by experiments. k and Δk are 0.442 and 6.8% respectively, and the errors are less than 5%. In the optimization process, there is no simulation model constructed. The optimization modeling combined of magnetic field segmentation method and parameter fitting has lower complexity and calculation time of optimization.

Real-Time Detection and Localization of Line Trip Event via Relative Phase Angles

Line trip events widely exist in power systems. They can result in power outages and a huge economic loss if not promptly detected and localized. To provide a fast and precise solution, this paper presents a Complete Coverage of Voltage Measurement (CCVM)-based line trip event detection algorithm and a Relative Phase Angle (RPA)-based line trip event localization algorithm. First, frequency and relative phase angle features during a line trip event are calculated. Then, the CCVM-based algorithm is proposed from both frequency and rate of change of frequency estimation algorithm aspects. Additionally, the RPA-based algorithm is presented, and two cases are studied to demonstrate the uniqueness of the proposed algorithm. Various experiments are conducted, where the simulation results demonstrate that the proposed CCVM-based algorithm can detect a line trip event as short as 2.07 ms. In addition, the RPA-based algorithm has 1.26 times higher localization accuracy compared with the frequency magnitude-based and phase angle-based algorithms. The experiment results on the examples from two interconnected power systems in the U.S. verified the performance of the proposed algorithms in wide-area power systems.

Frequency Stability Constrained BESS Sizing Model for Microgrids

The grid integration of renewable energy sources necessitates using energy storage systems (ESSs) to provide more flexibility and controllability. This paper proposes a frequency stability-constrained battery energy storage system (BESS) sizing model for microgrids formulated as a mixed-integer linear programming (MILP) problem and decomposed using Benders decomposition. The optimal size of BESS is determined as a trade-off between minimizing the operating costs or maximizing the benefits and the high investment costs of BESS. Both the grid-connected and stand-alone operating modes are modeled for the microgrid along with the corresponding generation contingencies. The microgrid scheduling optimization model is built for cost-benefit analysis considering unit commitment and frequency stability (FS) constraints. The transient frequency dynamics are considered using an accurate time-domain model based on the discretized swing equation. The proposed method ensures frequency stability criteria, such as frequency nadir/overshoot, rate of change of frequency (RoCoF), and steady-state frequency, are within their allowable ranges following generation contingencies. Simulation results based on a medium-voltage microgrid test case with historical data of load, PV generation, and market price verify the effectiveness of the proposed method.

Burden of liver cancer mortality by county, race, and ethnicity in the USA, 2000–19: a systematic analysis of health disparities

Understanding how specific populations are affected by liver cancer is important for identifying priorities, policies, and interventions to mitigate health risks and reduce disparities. This study aims to provide comprehensive analysis of rates and trends in liver cancer mortality for different racial and ethnic populations in the USA nationally and at the county level from 2000 to 2019. We applied small-area estimation methods to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate liver cancer mortality rates by county, racial and ethnic population, and year (2000-19) in the USA. Race and ethnicity were categorised as non-Latino and non-Hispanic American Indian or Alaska Native (AIAN), non-Latino and non-Hispanic Asian or Pacific Islander (Asian), non-Latino and non-Hispanic Black (Black), Latino or Hispanic (Latino), and non-Latino and non-Hispanic White (White). Estimates were adjusted using published misclassification ratios to correct for inaccuracies in race or ethnicity as recorded on death certificates, and then age-standardised. Mortality rate estimates are presented for all county and racial and ethnic population combinations with a mean annual population greater than 1000. Nationally, the age-standardised liver cancer mortality rate increased between the years 2000 (4·2 deaths per 100 000 population [95% uncertainty interval 4·1-4·3]) and 2016 (6·0 per 100 000 [5·9-6·1]), followed by a stabilisation in rates from 2016 to 2019 (6·1 per 100 000 [6·0-6·2]). Similar trends were observed across the AIAN, Black, Latino, and White populations, whereas the Asian population showed an overall decrease across the 20-year study period. Qualitatively similar trends were observed in most counties; however, the mortality rate and the rate of change varied substantially across counties, both within and across racial and ethnic populations. For the 2016-19 period, mortality continued to increase at a substantial rate in some counties even while it stabilised nationally. Nationally, the White population had the lowest mortality rate in all years, while the racial and ethnic population with the highest rate changed from the Asian population in 2000 to the AIAN population in 2019. Racial and ethnic disparities were substantial: in 2019, mortality was highest in the AIAN population (10·5 deaths per 100 000 [9·1-12·0]), notably lower for the Asian (7·5 per 100 000 [7·1-7·9]), Black (7·6 per 100 000 [7·3-7·8]), and Latino (7·7 per 100 000 [7·5-8·0]) populations, and lowest for the White population (5·5 [5·4-5·6]). These racial and ethnic disparities in mortality were prevalent throughout the country: in 2019, mortality was higher in minoritised racial and ethnic populations than in the White population living in the same county in 408 (87·7%) of 465 counties with unmasked estimates for the AIAN population, 604 (90·6%) of 667 counties for the Asian population, 1207 (81·2%) of 1486 counties for the Black population, and 1073 (73·0%) of 1469 counties for the Latino population. Although the plateau in liver cancer mortality rates in recent years is encouraging, mortality remains too high in many locations throughout the USA, particularly for minoritised racial and ethnic populations. Addressing population-specific risk factors and differences in access to quality health care is essential for decreasing the burden and disparities in liver cancer mortality across racial and ethnic populations and locations. US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Zabramski classification in predicting the occurrence of symptomatic intracerebral hemorrhage in sporadic cerebral cavernous malformations.

The authors aimed to investigate the evolutionary characteristics of the Zabramski classification of cerebral cavernous malformations (CCMs) and the value of the Zabramski classification in predicting clinical outcome in patients with sporadic CCM. This retrospective study consecutively included cases of sporadic CCM that had been untreated from January 2001 through December 2021. Baseline and follow-up patient information was recorded. The evolution of the Zabramski classification of a sporadic CCM was defined as the initial lesion type changing into another type for the first time on MRI follow-up. The primary outcome was the occurrence of a hemorrhage event, which was defined as a symptomatic event with radiological evidence of overt intracerebral hemorrhage. Among the 255 included cases, 55 (21.6%) were classified as type I CCM, 129 (50.6%) as type II CCM, and 71 (27.8%) as type III CCM, based on initial MRI. During a mean follow-up of 58.8 ± 33.6 months, 51 (20.0%) patients had lesion classification transformation, whereas 204 (80.0%) patients maintained their initial type. Among the 51 transformed lesions, 29 (56.9%) were type I, 11 (21.6%) were type II, and 11 (21.6%) were type III. Based on all follow-up imaging, of the initial 55 type I lesions, 26 (47.3%) remained type I and 27 (49.1%) regressed to type III because of hematoma absorption; 91.5% of type II and 84.5% of type III lesions maintained their initial type during MRI follow-up. The classification change rate of type I lesions was statistically significantly higher than those of type II and III lesions. After a total follow-up of 1157.7 patient-years, new clinical hemorrhage events occurred in 40 (15.7%) patients. The annual cumulative incidence rate for symptomatic hemorrhage in all patients was 3.4 (95% CI 2.5-4.7) per 100 person-years. Kaplan-Meier survival analysis showed that the annual cumulative incidence rate for symptomatic hemorrhage of type I CCM (15.3 per 100 patient-years) was significantly higher than those of type II (0.6 per 100 patient-years) and type III (2.3 per 100 patient-years). This study suggests that the Zabramski classification is helpful in estimating clinical outcome and can assist with surgical decision-making in patients with sporadic CCM.

Magnetic field tuning of photoelectric and photoluminescence effects in BiFe0.9Co0.1O3 thin film

The reported BiFe0.9Co0.1O3 film presents an interesting magnetic field tunning effect on the photoelectric properties and photoluminescence spectra. The change rate of the photocurrent up to 123.6% was achieved when applying a 400 Oe magnetic field to the film, which is attributed to the spin scattering of photoelectrons in the film. The experimental result of the magnetic field tuning photoluminescence spectra indicates that the magnetic field inhibits the radiative transition of the photogenerated carriers in the thin film and therefore reduces the intensity of photoluminescence. This research provides a basis for the research and application of devices in the field of multifunctional photoelectric materials.

Enhanced hydrophilicity of low melting point polylactic acid by butenediol vinyl alcohol copolymer via melt blending

In order to solve the poor hydrophilicity of low melting point polylactic acid (LMPLA) limiting its application in absorbent sanitary products. LMPLA/butenediol vinyl alcohol copolymer (BVOH) blends with different ratios were manufactured by simple melt blending. The BVOH exhibited good compatibility and dispersity in LMPLA matrix without chemical reaction, and LMPLA/BVOH blends showed sea-island structure. The introduction of BVOH could promote the crystallization of LMPLA and improve the crystallinity, whereas the crystallization of BVOH were limited. Furthermore, the introduction of BVOH could also decrease the thermal stability of LMPLA without affecting its application, but the tensile stress of LMPLA could be significantly increased. The tensile stress of LMPLA/BVOH blends could reach 78.59 MPa (increased by 10.9%) when he BVOH content was 3 wt%. Most importantly, the introduction of BVOH could significantly improve the hydrophilicity of LMPLA. The initial water contact angle decreased from 68.5° to 51.4° with the increase of BVOH content, and the contact angle decreased from 63.7° to 44.6° at 60 s. Moreover, the contact angle change rate of LMPLA/BVOH blends increased with the increase of BVOH content at different contact time, which also indicated adding BVOH could sharply improve the hydrophilicity of LMPLA.

Non-linear electro-rheological model of a membrane immersed in Tanner-Power law fluids applied to outer hair cells: Shear-thinning mechanisms

Flexoelectric actuation employs an applied electric field to induce membrane curvature, which is the mechanism utilized by the outer hair cells (OHC) present in the inner ear. The model developed for this study, representing the OHC, integrates two key components: (i) an approximation of the flexoelectric membrane shape equation for circular membranes attached to the inner surface of a circular capillary, and (ii) the coupled capillary flow of contacting liquid viscoelastic phases characterized by the Tanner-Power law rheological equation of state. A second-order non-linear differential equation for average curvature has been derived, and a robust numerical method has been programmed. This model simplifies to a linear model used previously. The main challenge involves identifying and describing the enhancement in curvature change rate. It was observed that low symmetry, low viscosity, and soft membrane and shear-thickening behavior of the phases enhance the curvature change rate. Additionally, there exists a critical electric field frequency value that maximizes the curvature change rate (resonance effect). The current theory, model, and computational simulations add to the ongoing development comprehension of how biological membrane shape actuation through electromechanical couplings.

A Fuzzy Logic Control-Based Approach for Real-Time Energy Management of the Fuel Cell Electrical Bus Considering the Durability of the Fuel Cell System

The present study proposes a fuzzy logical control-based real-time energy management strategy (EMS) for a fuel cell electrical bus (FCEB), taking into account the durability of the fuel cell system (FCS), in order to enhance both the vehicle’s economic performance and the FCS’s service life. At first, the model of the FCEB is established whilst the power-following strategy is also formulated as a benchmark for the evaluation of the proposed strategy. Subsequently, a fuzzy logical controller is designed to improve the work efficiency of the FCS, in which the battery state-of-charge (SOC) and the vehicle’s desired power are considered the inputs, whilst the power of the FCS is the output. Then, a limitation method is integrated into the fuzzy logical controller to restrict the change rate of the FCS’s power to strengthen the FCS’s service life. At last, the evaluation is accessed based on the China city bus driving cycle (CCBC). The results indicate that the proposed fuzzy logical strategy can satisfy the dynamic performance of the FCEB well. Importantly, it also has a remarkable effectiveness in terms of promoting the FCEB’s economy. Despite a slight reduction in contrast to the fuzzy logical control, the improvements of the strategy in which the FCS’s durability is considered are still acceptable. The change rate of the FCS’s power can be confined to ±10 kW. Meanwhile, the promotion of economic performance can reach up to 8.43%, 7.69%, and 6.53% in the proposed durability consideration strategy in contrast to the power-following strategy under different battery SOCs. This will significantly benefit both the energy saving and the FCS’s durability.

Statistical analysis of the phase space density changes of radiation belt source, seed, and relativistic electrons in response to geomagnetic storms

The radiation belt “source” (a few to tens of keV), “seed” (hundreds of keV), and “relativistic” (>1 MeV) electrons are highly fabricated by geomagnetic storms or substorms. The present study statistically analyzed the phase-space density (PSD) of the radiation belt electrons at the first adiabatic invariant μ = 101–104 MeV/G between L* (the inversion of the third adiabatic invariant) from 2.5 to 5.5 in response to geomagnetic storms. The statistical results indicate that after the storms, more than 25% of the relativistic electron PSD were pumped at L* > ∼3.5, with a peak at approximately L* = 4.0, while approximately 25% of them also showed a clear loss at L* > 3.5. Comparably, the source electrons mainly increased within almost the whole outer radiation belt, and the seed electrons may serve as intermediary populations, in which source and loss processes engage in strong competition. As the dynamic pressure and substorm intensify, the primary “enhancement region” and “loss region” converge near a few 102 MeV/G. Furthermore, analysis that the magnetopause shadowing effect mainly contributed to the observed losses one day after the main phase, while the substorm-injected particles and the seceded acceleration processes likely accounted for the observed increase in the electron PSD three days after the main phase. The present study provides a new and comprehensive insight into the statistical understanding of the change rates of the electron PSD and the competition between source and loss processes in response to geomagnetic storms.

Power Advance Prediction to Improve the Energy Utilization Efficiency of Motor-Driven System Considering Multilink Time-Delay

In the motor-driven system, the utilization of a supercapacitor energy storage unit contributes to energy saving. However, the multi-link time-delay in the system makes the supercapacitor unable to immediately track and respond to the sharp change of motor power. This will cause the large DC bus voltage fluctuation, the peak current at the power grid side, and unnecessary energy loss. In this paper, a power advance prediction control strategy considering multi-link time-delay is proposed. The multi-link time-delay mechanism in the system is analyzed, in particular for the different conditions of motor power change. Afterward, with the motor speed, torque, and the inverter acceleration/deceleration rate obtained in advance, the motor steady power and power change rate are predicted. In the dynamic process, by adjusting the tracking rate in real time, the motor reference power function is derived. The reference current of the supercapacitor is given online, so as to match the power between the motor and the energy storage unit. Both simulation and experimental results verify the rationality and validity of the proposed control strategy. In the dynamic process, the system stability and energy utilization are successfully improved in comparison with multi-parameter collaborative power prediction control and double closed-loop control.

Spatio-Temporal Patterns of Land Use and Cover Change in the Lancang–Mekong River Basin during 2000–2020

Exploring the mechanisms that drive land use and cover change (LUCC) is essential for informing the formulation and implementation of effective policies aimed at optimizing land use patterns. In this study, we examined the spatial and temporal patterns of LUCC within the Lancang–Mekong River Basin (LMRB) using Globeland30 data for the years 2000, 2010, and 2020. Firstly, we analyzed the quantitative characteristics of LUCC within the LMRB in terms of the value of change and rate of change. Additionally, we investigated the converting characteristics of LUCC within the LMRB by employing land use transition matrices and land use transition probability matrices. Furthermore, we depicted the spatial distribution of LUCC within the LMRB through land use mapping and statistical analysis. The results indicate a substantial decline in forests, coupled with a notable expansion in cultivated land. Given the vital role of forests as carbon sinks, reforestation can enhance ecological services and address challenges related to climate change. Converting cultivated land to forests is an effective human intervention promoting forest transition. This study applies binary logistic models to explore the mechanisms that influence the conversion from cultivated land to forests. The results reveal that slopes ranging from 5° to 15° have the lowest probability of conversion, whereas distances between the cultivated land and the nearest tourist attraction ranging from 9 km to 18 km have the highest probability. Moreover, the conversion process is positively associated with traffic conditions and significantly influenced by human interventions. Within the study area, China, Laos, and Myanmar show a tendency to convert cultivated land into natural LULC types, while Cambodia, Thailand, and Vietnam tend to encroach on cultivated land and expand artificial surfaces. Promoting ecological restoration in the LMRB requires cooperation among these countries.