Evaluating Static and Dynamic Impacts of Geomagnetic Disturbances on Interconnected Power Grids

Geomagnetic disturbances (GMDs) can potentially impose operational challenges on power systems and cause damage to essential grid assets through geomagnetically induced currents (GICs). Therefore, to maintain power system efficiency and reliability, it is essential to study how GMDs impact power systems. This work contains two separate research topics related to GMDs. The first research topic is associated with a spatially non-uniform GMD event called localized geomagnetic field enhancement. Characterized by geomagnetic fields substantially increasing in some areas, localized geomagnetic field enhancements cause the localized augmentation of geoelectric fields and flow of “extra” GICs in power grids. Considering that the distribution of the “extra” GICs directly affects the planning and operations of the grids, this work utilizes the superposition principle and defines a sensitivity associated with the “extra” GICs to study the impact scopes of localized geomagnetic field enhancements. Sensitivity analysis is performed on a small 20-bus benchmark system and a large 10k-bus synthetic network, respectively. The results show that the impact scope of a square localized geomagnetic field enhancement area is generally less than one and a half times its width. In other words, the “extra” GICs are localized. The second research topic focuses on studying the impacts of GMDs/GICs on power system transient stability under different contingent conditions. In the work, various contingencies are applied to the 10k-bus synthetic network individually in the presence of time-invariant GMDs, while the changes in the transient stability margin are evaluated using different metrics. Several case studies are presented as examples of the potential effects of GMDs. The results show that GMDs can alter power system transient margin. Therefore, this work suggests that relevant transient stability studies may need to be conducted to ensure secure power system operations under the effect of GMDs

Elasticity-Controlled Jamming Criticality in Soft Composite Solids

Soft composite solids are made of dispersed inclusions within soft matrices. They are ubiquitous in nature and form the basis of many biological tissues. In the field of materials science, synthetic soft composites are promising candidates for constructing various engineering devices due to their highly programmable features. However, when the volume fraction of inclusions increases, predicting the mechanical properties of these materials poses a significant challenge for the classical theories in composite mechanics. The difficulty arises from the inherently disordered, multi-scale interactions between the inclusions and matrix. To address this challenge, we conducted systematic investigations on the mechanics of densely-filled soft elastomers containing stiff microspheres. We experimentally demonstrated how the strain-stiffening response of the soft composites is governed by the critical scalings in the vicinity of a continuous phase transition, which depend on both the elasticity of the elastomer matrix and the particles. The critical points signify a shear-jamming transition of the included particles in the absence of matrix elasticity. The proposed criticality framework quantitatively predicts diverse mechanical responses observed in experiments across a wide range of material parameters. The findings uncover a novel design paradigm of composite mechanics that relies on engineering the jamming-criticality of the embedded inclusions

Metabonomic analysis of follicular fluid in patients with diminished ovarian reserve

BackgroundOvarian reserve is an important factor determining female reproductive potential. The number and quality of oocytes in patients with diminished ovarian reserve (DOR) are reduced, and even if in vitro fertilization-embryo transfer (IVF-ET) is used to assist their pregnancy, the clinical pregnancy rate and live birth rate are still low. Infertility caused by reduced ovarian reserve is still one of the most difficult clinical problems in the field of reproduction. Follicular fluid is the microenvironment for oocyte survival, and the metabolic characteristics of follicular fluid can be obtained by metabolomics technology. By analyzing the metabolic status of follicular fluid, we hope to find the metabolic factors that affect the quality of oocytes and find new diagnostic markers to provide clues for early detection and intervention of patients with DOR.MethodsIn this research, 26 infertile women with DOR and 28 volunteers with normal ovarian reserve receiving IVF/ET were recruited, and their follicular fluid samples were collected for a nontargeted metabonomic study. The orthogonal partial least squares discriminant analysis model was used to understand the separation trend of the two groups, KEGG was used to analyze the possible metabolic pathways involved in differential metabolites, and the random forest algorithm was used to establish the diagnostic model.Results12 upregulated and 32 downregulated differential metabolites were detected by metabolic analysis, mainly including amino acids, indoles, nucleosides, organic acids, steroids, phospholipids, fatty acyls, and organic oxygen compounds. Through KEGG analysis, these metabolites were mainly involved in aminoacyl-tRNA biosynthesis, tryptophan metabolism, pantothenate and CoA biosynthesis, and purine metabolism. The AUC value of the diagnostic model based on the top 10 metabolites was 0.9936.ConclusionThe follicular fluid of patients with DOR shows unique metabolic characteristics. These data can provide us with rich biochemical information and a research basis for exploring the pathogenesis of DOR and predicting ovarian reserve function

Correlation model between mesostructure and gradation of asphalt mixture based on statistical method

Asphalt mixture has complex gradation and mesostructure. Accurate prediction of the relationship between gradation and mesostructure is of great significance for the establishment of mesostructure numerical simulation model and image-based gradation detection. In this paper, featurization, stepwise regression, econometric hypothesis test are utilized for establishing the predicting models. Firstly, asphalt mixtures with 64 kinds of gradation are scanned by Computed Tomography (CT) to obtain the mesostructure images; Then a series of mesostructure parameters of voids and aggregates are put forward. On this basis, the relationship model between gradation and mesostructure is established and verified by featurization and statistical modeling method. The results show that for predicting the passing percentage of the 4.75 mm sieve and the mean value of average distance between aggregate centroids for 9.5–4.75 mm aggregates, the prediction error of passing percentage is acceptable. It illustrates that the relationship model between gradation and mesostructure established by statistical method is effective, and it is significance for material design and testing under the condition of big data in the future

Angiography-Based Computational Modeling for In Vivo Assessment of Endothelial Dynamic Strain in Coronary Arteries with De Novo Lesions: Comparison of Treatment Effects of Drug-Coated Balloons Between Small and Large Arteries

Acute morphological changes in de novo coronary lesions after drug-coated balloon (DCB) angioplasty can affect endothelial mechanics and consequently clinical outcomes. Angiography-based computational modeling has been validated to assess endothelial dynamic strain (EDS) in coronary arteries in vivo. The EDS was calculated on the basis of pre- and post-DCB angiography. Parameters of quantitative coronary angiography and EDS were quantified at cross-sections in the treated segments. A total of 336 and 348 lesion cross-sections were included in the small/large vessel groups, respectively. The acute lumen gain after DCB was significantly higher in large than small vessels (relative changes: 21.3% [17.4%, 25.1%] vs. 7.4% [4.8%, 10.1%], P < 0.001). Before treatment, three indices of EDS were significantly higher in small than large vessels (for ED-EDS: 29.2% [19.8%, 44.8%] vs. 20.4% [14.3%, 30.2%]; for ES-EDS: 26.8% [18.9%, 37.7%] vs. 18.3% [13.9%, 25.4%]; for TA-EDS: 19.1% [13.9%, 27.8%] vs. 14.3% [10.5%, 20.1%], P < 0.001). After treatment, the EDS in small vessels significantly decreased (P < 0.001). ED-EDS showed the highest correlation with pre-DCB DSP (r = 0.43, P < 0.001) and post-DCB MLD (r = 0.35, P < 0.001). The levels of EDS parameters for small or large vessel lesions significantly differed. Further study is required to examine the clinical value of EDS in predicting cardiac events after DCB treatment

Rapid evaluation of earthquake-induced landslides by PGA and Arias intensity model: insights from the Luding Ms6.8 earthquake, Tibetan Plateau

On September 5, 2022, a magnitude 6.8 earthquake occurred along the Xianshuihe Fault Zone in Luding County, Tibetan Plateau, China, leading to a significant outbreak of landslides. The urgent need for a swift and accurate evaluation of earthquake-induced landslides distribution in the affected area prompted this study. This research delves into regional geological data, scrutinizes post-earthquake Peak Ground Acceleration (PGA) and Arias Intensity (Ia) associated with the Luding earthquake, and conducts earthquake-induced landslides risk assessments within the Luding earthquake zone using the Newmark model. Validation of the earthquake-induced landslides risk assessment outcomes rooted in PGA and Ia relies on an earthquake-induced landslides database, revealing Area Under the Curve (AUC) values of 0.73 and 0.84 in respective ROC (Receiver Operating Characteristic) curves. These results unequivocally affirm the exceptional accuracy of earthquake-induced landslides evaluation using Ia calculations, emphasizing its suitability for the swift prediction and evaluation of earthquake-induced landslides. The earthquake-induced landslides risk assessment based on Ia computation reveals the area with extremely high-risk and high-risk of earthquake-induced landslides encompass 0.71% of the entire study area. Notably, these areas are predominantly clustered within seismic intensity VII zones and primarily trace the Moxi fault zone, extending from the southern portion of the middle east along the Dadu River and the Moxi fault, with reach up to Dewei Township in the north and Caoke Township in the south. Hazard-prone regions predominantly align with slopes featuring gradients of 30°–45° and bear a strong correlation with fault activity. Furthermore, the results of this evaluation are harmonious with the findings from remote sensing interpretation and on-site field investigations pertaining to the earthquake-induced landslides. This body of knowledge can serve as a crucial reference for expedited assessment, emergency response and subsequent supplementation of earthquake-induced landslide databases when confronting similar earthquake-induced landslide scenarios