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BACKGROUND: Understanding the complex interactions between genes and their causal effects on diseases is crucial for developing targeted treatments and gaining insight into biological mechanisms. However, the analysis of molecular networks, especially in the context of high-dimensional data, presents significant challenges. METHODS: This study introduces MRdualPC, a computationally tractable algorithm based on the MRPC approach, to infer large-scale causal molecular networks. We apply MRdualPC to investigate the upstream causal transcriptomics influencing hypertension using a comprehensive dataset of kidney genome and transcriptome data. RESULTS: Our algorithm proves to be 100 times faster than MRPC on average in identifying transcriptomics drivers of hypertension. Through clustering, we identify 63 modules with causal driver genes, including 17 modules with extensive causal networks. Notably, we find that genes within one of the causal networks are associated with the electron transport chain and oxidative phosphorylation, previously linked to hypertension. Moreover, the identified causal ancestor genes show an over-representation of blood pressure-related genes. CONCLUSIONS: MRdualPC has the potential for broader applications beyond gene expression data, including multi-omics integration. While there are limitations, such as the need for clustering in large gene expression datasets, our study represents a significant advancement in building causal molecular networks, offering researchers a valuable tool for analyzing big data and investigating complex diseases.
Subject(s)
Algorithms , Gene Regulatory Networks , Hypertension , Machine Learning , Hypertension/genetics , Humans , Transcriptome/genetics , Gene Expression Profiling/methods , Computational Biology/methods , Cluster AnalysisABSTRACT
Lakes and wetlands play pivotal roles in global organic matter storage, receiving significant inputs of organic material. However, the co-metabolic processes governing the decomposition of these organic materials and their impact on greenhouse gas emissions remain inadequately understood. This study aims to assess the effects of mixed decomposition involving macrophytes and cyanobacteria on carbon emissions. A series of microcosms was established to investigate the decomposition of macrophyte residues and algae over a period of 216 days. A two-component kinetic model was utilized to estimate methane (CH4) production rates. Gas isotope technology was employed to discern the contributions of CH4 produced by macrophyte residues or algae. Quantitative PCR and analysis of 16S rRNA gene amplicons were employed to assess changes in functional genes and microbial communities. There were significant differences in the cumulative carbon release from the decomposition of different plant types due to the addition of carbon sources. After adding algae, the cumulative emission of CH4 increased significantly. The δ13C-CH4 partitioning indicated that CH4 originated exclusively from the fresh organic carbon of macrophyte residues, while it shifted to algae source after adding algae. The synergistic effect of the mixed decomposition on the CH4 emissions was greater than the sum of the individual decompositions. The microbial community richness was higher in the single plant residue treatment compared to the mixed treatment with algae addition, while microbial evenness in the sediment increased steadily in each treatment. Our findings emphasize the pronounced co-metabolic effect observed during the mixed decomposition of macrophytes and cyanobacteria.
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The continuous increase in sulfate (SO42-) concentrations discharged by anthropogenic activities lacks insights into their dynamics and potential impact on CH4 budgets in freshwater lakes. Here we conducted a field investigation in the lakes along the highly developed Yangtze River basin, China, additionally, we analyzed long-term data (1950-2020) from Lake Taihu, a typical eutrophic lake worldwide. We observed a gradual increase in SO42- concentrations up to 100 mg/L, which showed a positive correlation with the trophic state of the lakes. The annual variations indicated that eutrophication intensified the fluctuation of SO42- concentrations. A random forest model was applied to assess the impact of SO42- concentrations on CH4 emissions, revealing a significant negative effect. Synchronously, a series of microcosms with added SO42- were established to simulate cyanobacteria decomposition processes and explore the coupling mechanism between sulfate reduction and CH4 production. The results showed a strong negative correlation between CH4 concentrations and initial SO42- levels (R2 = 0.83), indicating that higher initial SO42- concentrations led to lower final CH4 concentrations. This was attributed to the competition for cyanobacteria-supplied substrates between sulfate reduction bacteria (SRB) and methane production archaea (MPA). Our study highlights the importance of considering the unexpectedly increasing SO42- concentrations in eutrophic lakes when estimating global CH4 emission budgets.
Subject(s)
Eutrophication , Lakes , Methane , Sulfates , Lakes/chemistry , China , Environmental Monitoring , Cyanobacteria/metabolismABSTRACT
Osteoarthritis (OA) is a prevalent disease, characterized by subchondral fractures in its initial stages, which has no precise and specific treatment now. Here, a novel multifunctional scaffold is synthesized by photopolymerizing glycidyl methacrylate-modified hyaluronic acid (GMHA) as the matrix in the presence of hollow porous magnetic microspheres based on hydroxyapatite. In vivo subchondral bone repairing results demonstrate that the scaffold's meticulous design has most suitable properties for subchondral bone repair. The porous structure of inorganic particles within the scaffold facilitates efficient transport of loaded exogenous vascular endothelial growth factor (VEGF). The Fe3O4 nanoparticles assembled in microspheres promote the osteogenic differentiation of bone marrow mesenchymal stem cells and accelerate the new bone generation. These features enable the scaffold to exhibit favorable subchondral bone repair properties and attain high cartilage repair scores. The therapy results prove that the subchondral bone support considerably influences the upper cartilage repair process. Furthermore, magnetic resonance imaging monitoring demonstrates that Fe3O4 nanoparticles, which are gradually replaced by new bone during osteochondral defect repair, allow a noninvasive and radiation-free assessment to track the newborn bone during the OA repair process. The composite hydrogel scaffold (CHS) provides a versatile platform for biomedical applications in OA treatment.
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Pollen is a promising material for water treatment owing to its renewable nature, abundant sources, and vast reserves. The natural polymer sporopollenin, found within pollen exine, possesses a distinctive layered porous structure, mechanical strength, and stable chemical properties, which can be utilized to prepare sporopollenin exine capsules (SECs). Leveraging these attributes, pollen or SECs can be used to develop water pollution remediation materials. In this review, the structure of pollen is first introduced, followed by the categorization of various methods for extracting SECs. Then, the functional expansion of pollen adsorbents, with an emphasis on their recyclability, reusability, and visual sensing capabilities, as opposed to mere functional group modification, is discussed. Furthermore, the progress made in utilizing pollen as a biological template for synthesizing catalysts is summarized. Intriguingly, pollen can also be engineered into self-propelled micromotors, enhancing its potential application in adsorption and catalysis. Finally, the challenges associated with the application of pollen in water pollution treatment are discussed. These challenges include the selection of environmentally friendly, non-toxic reagents in synthesizing pollen water remediation products and the large-scale application after synthesis. Moreover, the multifunctional synthesis and application of different water remediation products are prospected.
Subject(s)
Carotenoids , Pollen , Pollen/chemistry , Biopolymers/chemistry , Carotenoids/chemistry , Water Purification/methods , Adsorption , Water Pollutants, Chemical/chemistry , Catalysis , Water Pollution/prevention & controlABSTRACT
BACKGROUND: The contribution of gut microbiota to human high-altitude adaptation remains inadequately understood. METHODS: Here a comparative analysis of gut microbiota was conducted between healthy individuals living at sea level and high altitude using deep whole-metagenome shotgun sequencing, to investigate the adaptive mechanisms of gut microbiota in plateau inhabitants. RESULTS: The results showed the gut bacteriomes in high-altitude individuals exhibited greater within-sample diversity and significant alterations in both bacterial compositional and functional profiles when compared to those of sea-level individuals, indicating the potential selection of unique bacteria associated with high-altitude environments. The strain-level investigation revealed enrichment of Collinsella aerofaciens and Akkermansia muciniphila in high-altitude populations. The characteristics of gut virome and gut mycobiome were also investigated. Compared to sea-level subjects, high-altitude subjects exhibited a greater diversity in their gut virome, with an increased number of viral operational taxonomic units (vOTUs) and unique annotated genes. Finally, correlation analyses revealed 819 significant correlations between 42 bacterial species and 375 vOTUs, while no significant correlations were observed between bacteria and fungi or between fungi and viruses. CONCLUSION: The findings have significantly contributed to an enhanced comprehension of the mechanisms underlying the high-altitude geographic adaptation of the human gut microbiota.
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Shallow lakes, recognized as hotspots for nitrogen cycling, contribute to the emission of the potent greenhouse gas nitrous oxide (N2O), but the current emission estimates for this gas have a high degree of uncertainty. However, the role of N2O-reducing bacteria (N2ORB) as N2O sinks and their contribution to N2O reduction in aquatic ecosystems in response to N2O dynamics have not been determined. Here, we investigated the N2O dynamics and microbial processes in the nitrogen cycle, which included both N2O production and consumption, in five shallow lakes spanning approximately 500 km. The investigated sites exhibited N2O oversaturation, with excess dissolved N2O concentrations (ΔN2O) ranging from 0.55 ± 0.61 to 53.17 ± 15.75 nM. Sediment-bound N2O (sN2O) was significantly positively correlated with the nitrate concentration in the overlying water (p < 0.05), suggesting that nitrate accumulation contributes to benthic N2O generation. High N2O consumption activity (RN2O) corresponded to low ΔN2O. In addition, a significant negative correlation was found between RN2O and nir/nosZ, showing that bacteria encoding nosZ contributed to N2O consumption in the benthic sediments. Redundancy analysis indicated that benthic functional genes effectively reflected the variations in RN2O and ∆N2O. qPCR analysis revealed that the clade II nosZ gene was more sensitive to ΔN2O than the clade I nosZ gene. Furthermore, four novel genera of potential nondenitrifying N2ORB were identified based on metagenome-assembled genome analysis. These genera, which are affiliated with clade II, lack genes responsible for N2O production. Collectively, benthic N2ORB, especially for clade II-type N2ORB, harnesses N2O consumption activity leading to low N2O emissions from shallow lakes. This study advances our knowledge of the role of benthic clade II-type N2ORB in regulating N2O emissions in shallow lakes.
Subject(s)
Bacteria , Lakes , Nitrous Oxide , Nitrous Oxide/analysis , Lakes/chemistry , Bacteria/classification , Environmental Monitoring , Nitrogen Cycle , Air Pollutants/analysis , Geologic Sediments/chemistryABSTRACT
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
Subject(s)
Hypertension , Proteome , Humans , Blood Pressure/genetics , Proteome/genetics , Proteome/metabolism , Transcriptome/genetics , Multiomics , Hypertension/metabolism , Kidney/metabolism , Sodium-Glucose Transport Proteins/genetics , Sodium-Glucose Transport Proteins/metabolismABSTRACT
Aligned carbon nanotube (A-CNT) with high semiconducting purity and high-density have been considered as one of the most promising active channels for field-effect transistors (FETs), but conjugated polymer dispersant residues on the surface of A-CNT have become the main obstacle for its further development in electronics applications. In this work, a series of removable conjugated polymers (CPs) are designed and synthesized to achieve favorable purification and alignment for CNT arrays with a high density of ≈360 CNTs/µm. Furthermore, a removal process of CPs on the CNT array film is developed. Raman spectra show that the CNTs in array film are almost not damaged after the removal process, and the G/D ratio is as high as 35. The field-effect transistors (FETs) are fabricated with a saturation current density up to 600 µA µm-1 and a current on-off ratio of ≈105, even with a relatively long channel length of ≈3 µm.
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Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10-8), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.
Subject(s)
Genome-Wide Association Study , Renal Insufficiency, Chronic , Humans , Renal Insufficiency, Chronic/diagnosis , Glomerular Filtration Rate/genetics , Multifactorial Inheritance/genetics , Kidney/physiologyABSTRACT
Inland shallow lakes are recognized as an important source of greenhouse gases (GHGs), and their contribution is expected to increase due to global eutrophication. The generation and release of GHGs involved multiple variables, leading to many uncertain potential factors. This study examined the emission characteristics of GHGs at the water-air interface in 12 shallow lakes categorized into four eutrophic levels in the Yangtze River basin. The average emission rates of CH4, CO2 and N2O were 1.55, 3.43, 18.13 and 30.47 mg m-2 h-1, 4.12, 14.64, 25.11 and 69.84 mg m-2 h-1, and 0.2, 0.25, 0.43 and 0.79 mg m-2 day-1 in the oligotrophic, mesotrophic, eutrophic and hypereutrophic lakes, respectively. There were significant correlations between eutrophic levels and the emission rates of CH4 and CO2 (p < 0.05). Redundancy analysis and Mantel test were conducted to further examine the key factors influencing carbon emissions from eutrophic water. It was found that the presence of algae and nutrients in the overlying water played a crucial role in the release of GHGs, indicating the importance of ecosystem productivity in the carbon budget of the lake. In order to assess the bioavailability of organic matter, a new indicator called R(P/H) was proposed. This indicator represents the ratio of protein and humus-like components, which were obtained through EEMs-PARAFAC modeling. The relationship between R(P/H) and CH4 was found to be exponential (R2 = 0.90). Additionally, R(P/H) showed a linear relationship with CO2 and N2O (R2 = 0.68, R2 = 0.75). Therefore, it is crucial to consider R(P/H) as an important factor in accurately estimating global GHG emission fluxes in the future, especially with advancements in the database.
Subject(s)
Greenhouse Gases , Greenhouse Gases/analysis , Lakes/analysis , Ecosystem , Carbon Dioxide/analysis , Methane/analysis , Water/analysis , Carbon/analysis , ChinaABSTRACT
Lakes serve as vital reservoirs of dissolved organic matter (DOM) and play pivotal roles in biogeochemical carbon cycles. However, the sources and compositions of DOM in freshwater lakes and their potential effects on lake sediment carbon pools remain unclear. In this study, seven inflowing rivers in the Lake Taihu basin were selected to explore the potential effects of multi-source DOM inputs on the stability of the lake sediment carbon pool. The results showed the high concentrations of dissolved organic carbon in the Lake Taihu basin, accompanied by a high complexity level. Lignins constituted the majority of DOM compounds, surpassing 40% of the total, while the organic carbon content was predominantly composed of humic acids (1.02-3.01 g kg-1). The high amounts of lignin oxidative cleavage led to CHO being the main molecular structure in the DOM of the seven rivers. The carbon constituents within the sediment carbon reservoir exhibited a positive correlation with dissolved CH4 and CO2, with a notable emphasis on humic acid and dissolved CH4 (R2 = 0.86). The elevated concentration of DOM, coupled with its intricate composition, contributed to the increases in dissolved greenhouse gases (GHGs). Experiments showed that the mixing of multi-source DOM can accelerate the organic carbon mineralization processes. The unit carbon emission efficiency was highest in the mixed group, reaching reached 160.9 µmolâCg-1, which also exhibited a significantly different carbon pool. The mixed decomposition of DOM from different sources influenced the roles of the lake carbon pool as source and sink, indicating that the multi-source DOM of this lake basin was a potential driving factor for increased carbon emissions. These findings have improved our understanding of the sources and compositions of DOM in lake basins and revealed their impacts on carbon emissions, thereby providing a theoretical basis for improving assessments of lake carbon emissions.
Subject(s)
Dissolved Organic Matter , Greenhouse Gases , Lakes/analysis , Lakes/chemistry , Carbon , Rivers , Humic Substances/analysis , ChinaABSTRACT
Prolidase (PLD) plays a crucial role as a dipeptidase in various physiological processes, specifically involved in the cleavage of proline-containing dipeptides for efficient recycling of proline. The accurate determination of PLD activity holds significant importance in clinical diagnosis. Herein, a solid-state electrochemiluminescence (ECL) biosensor was developed to address the urgent need for PLD assay. The Ru(bpy)32+ was electrophoretically deposited within the nanochannels of vertically-ordered mesoporous silica film (VMSF) on indium tin oxide (ITO) electrodes. The Ru(bpy)32+-deposited VMSF/ITO (Ru-VMSF/ITO) exhibited a remarkable ECL response towards proline, attributed to the enhanced concentration of the reactants and improved electron transfer resulting from the nanoconfinement effect. As PLD specifically enzymolyzed the Gly-Pro dipeptide to release proline, a proline-mediated biosensor was developed for PLD assay. Increased PLD activity led to enhanced release of proline into the porous solid-state ECL sensors, resulting in a more robust ECL signal. There was a linear relationship between ΔECL intensity and logarithmic concentration of PLD in the range of 10-10000 U/L, with a detection limit of 1.98 U/L. Practical tests demonstrated the reliability and convenience of the proposed bioassay, making it suitable for widespread application in PLD assays.
Subject(s)
Biosensing Techniques , Silicon Dioxide , Reproducibility of Results , Luminescent Measurements/methods , Biosensing Techniques/methods , Proline , Electrochemical Techniques/methodsABSTRACT
The migration, transformation, and accumulation of dissolved organic matter (DOM) in pore water of sediment cores play a pivotal role in lacustrine carbon cycling. In order to understand the dynamics of DOM in the sediments of large shallow eutrophic lakes, we examined the vertical profiles of DOM and the benthic fluxes of dissolved organic carbon (DOC) in sediment cores located in algae accumulated, dredged, and central areas of eutrophic Lake Taihu, China. Optical properties showed the significant influence of terrestrial inputs on the DOM components of pore water in the algae accumulated area but an abundant accumulation of autochthonous DOM in the central area. The benthic fluxes of DOC ranging from -458.2 to -139.4 mg·m-2·d-1 in the algae accumulated area displayed an opposite diffusion direction to the other two areas. The flux ranges of 9.5-31.2 mg·m-2·d-1 in the dredged area and 14.6-48.0 mg·m-2·d-1 in the central area were relatively smaller than those in the previously reported lake ecosystems with low trophic levels. Dredging engineering disturbed the pre-dredging distribution patterns of DOM in sediment cores. The deposition, accumulation, and transformation of massive algae scums in eutrophic lakes probably promoted the humification degree of sediments.
Subject(s)
Dissolved Organic Matter , Lakes , Water , Ecosystem , China , Geologic SedimentsABSTRACT
Objective: To identify the relationship between patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and their fractional-exhaled nitric oxide (FeNO) levels. Methods: Patients diagnosed with AECOPD in the respiratory department of Beijing Chaoyang Hospital from June 2017 to August 2019 were recorded. The demographic data, FeNO value, peripheral blood eosinophil count, number of acute exacerbations in the past year, pulmonary function test, use of inhaled glucocorticoids (ICS) and other data were collected and analyzed. FeNO was measured again three months after discharge, the participants were assessed to determine if the stable period criteria were met. Results: A total of 214 patients met the requirements of this study. 25ppb for FeNO was used as the cutoff for further analysis. The proportion of males, number of acute exacerbations in the past year, number of ICS users, leukocyte count and eosinophil count in the high FeNO-level group was significantly higher than that in the low-level group (P < 0.05). The results showed that the number of acute exacerbations in the past year, number of ICS users, and eosinophil count were statistically significant in the model (P < 0.05). The study also showed that the level of FeNO in the acute exacerbation phase was significantly higher than that in the stable phase. The ROC curve that the area under the curve used by FeNO to predict ICS used is 0.631 (95% CI: 0.526-0.736), and the corresponding P value is 0.022. Conclusion: FeNO is closely related to activated T2 inflammation and eosinophil count in COPD patients. The FeNO levels can be used as an index to evaluate the severity of COPD and predict the recovery of activity after ICS treatment. FeNO can predict the use of ICS and is a beneficial supplement to eosinophils.
Subject(s)
Asthma , Pulmonary Disease, Chronic Obstructive , Male , Humans , Pulmonary Disease, Chronic Obstructive/diagnosis , Pulmonary Disease, Chronic Obstructive/drug therapy , Asthma/diagnosis , Fractional Exhaled Nitric Oxide Testing , Nitric Oxide/analysis , Eosinophils , Breath TestsABSTRACT
INTRODUCTION: An increased proclivity towards violence is often associated with those diagnosed with schizophrenia (SCZ), despite contradictory findings from prior studies exploring the association between violence and SCZ. Evidence has shown that certain comorbidities, specifically the presence of a substance use disorders, can result in increased aggression in those with SCZ. Copy number variation (CNV) load has also previously been implicated in the genetic vulnerability of individuals with SCZ. For this study, we aimed to determine whether CNV load correlates with increased violence in SCZ. METHODS: Community-dwelling patients diagnosed with SCZ spectrum disorders (n = 203) were recruited from a non-forensic population. The assessment for aggression was completed using a cross-sectional and retrospective design, and CNV analysis was conducted analysing genomic DNA using the Illumina Omni 2.5 array. RESULTS: No correlation between the number of CNV events (either deletion or duplication) and the severity of the physical violence episode index was found. However, there was a significant association between larger deletion events across the violent behaviours under investigation. DISCUSSION: These results need to be confirmed in more extensive studies using standardized tools developed for non-forensic populations, such as the Brown-Goodwin Scale of Aggression.
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Background: Through a survey and analysis of the population's present state of health, it is possible to give data support for improving the health status of inhabitants in Naqu, Tibet. Additionally, it is possible to provide specific recommendations for the development of medical and healthcare facilities in Tibet. Methods: The health scores of the participants were based on their responses to the four main sections of the questionnaire: dietary habits, living habits, health knowledge, and clinical disease history, and the variability of health status among groups with different characteristics was analyzed based on the scores. The four major sections were used to create classes of participants using latent class analysis (LCA). Using logistic regression, the factors influencing the classification of latent classes of health status were investigated. Results: A total of 995 residents from 10 counties in Naqu were selected as the study subjects. And their demographic characteristics were described. The mean health score of residents after standardization was 81.59 ± 4.68. With the exception of gender, health scores differed between groups by age, education level, different occupations, marital status, and monthly income. The health status in Naqu, Tibet, was divided into two groups (entropy = 0.29, BLRT = 0.001, LMRT = 0.001) defined as the "good health group" and the "general health group." A monthly income of more than ¥5000 adverse to good health in Naqu, Tibet. Discussion: Single, well-educated young adults in Naqu, Tibet, have outstanding health. The vast majority of people in Tibet's Naqu region were in good health. Furthermore, the population's latent health status was divided into two classes, each with good dietary and living habits choices, low health knowledge, and a history of several clinical diseases. Univariate and multivariate logistic regression analysis showed that monthly income more than ¥5000 was an independent risk factor for poor health status.
Subject(s)
Health Status , Young Adult , Humans , Tibet/epidemiology , Cross-Sectional Studies , Risk FactorsABSTRACT
In order to improve the driving performance of four-wheel drive electric vehicles and realize precise control of their speed, a Chaotic Random Grey Wolf Optimization-based PID in-wheel motor control algorithm is proposed in this paper. Based on an analysis of the structural principles of electric vehicles, mathematical and simulation models for the whole vehicle are established. In order to improve the control performance of the hub motor, the traditional Grey Wolf Optimization algorithm is improved. In particular, an enhanced population initialization strategy integrating sine and cosine random distribution factors into a Kent chaotic map is proposed, the weight factor of the algorithm is improved using a sine-based non-linear decreasing strategy, and the population position is improved using the random proportional movement strategy. These strategies effectively enhance the global optimization ability, convergence speed, and optimization accuracy of the traditional Grey Wolf Optimization algorithm. On this basis, the CR-GWO-PID control algorithm is established. Then, the software and hardware of an in-wheel motor controller are designed and an in-wheel motor bench test system is built. The simulation and bench test results demonstrate the significantly improved response speed and control accuracy of the proposed in-wheel motor control system.
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China is currently developing a green economy, and improving carbon productivity (CAP) is an important part of this process. The current study applied a minimum distance to strong efficient frontier (MinDS) model to measure China's CAP. The Dagum Gini coefficient and kernel density estimation methods were further used to reveal its spatial differences and dynamic evolution, while the coefficient of variation and spatial convergence models were employed to examine its convergence characteristics. The results showed significant spatial differences in China's CAP, with primarily high and low spatial distribution characteristics in the east and west, respectively. Between-regional differences were the main sources of the overall differences. Moreover, the differences between overall, eastern, central, and western regions of China all exhibited a widening trend. Although none showed σ convergence, all had significant absolute ß spatial convergence and conditional ß spatial convergence characteristics. Collectively, the findings of this study objectively reflect the real level, distribution characteristics, and spatial convergence characteristics of CAP in China as a whole and in each region, while also providing a reference basis for achieving peak carbon neutrality.
Subject(s)
Carbon , Social Conditions , China , Spatial Analysis , Economic DevelopmentABSTRACT
Vanadium dioxide (VO2) exhibits the most abrupt metal-to-insulator transition (MIT) property near room temperature among the representative 3d-orbital correlated oxides, and its structural variation during the MIT usually results in poor mechanical properties as bulk pellets. Moreover, compositing with highly resistive oxides has been reported to improve the mechanical strength of bulk VO2 since the generation and propagation of microcracks is suppressed upon thermocycling across the MIT; further, their respective impacts on electrical transportation are yet unclear. Herein, we demonstrate the role of these highly resistive oxide composites (e.g., HfO2, CoO and Al2O3) in reducing charge leakage along the microcracks within the insulating phase of VO2, leading to more abrupt MIT properties from the perspective of electrical transportation. This enables the possibility of simultaneously regulating the critical temperature and abrupt MIT transition, as well as the mechanical properties of the VO2 bulk pellets via compositing with oxides with different melting points using spark plasma-assisted reactive sintering (SPARS).