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As carbon capture and storage (CCS) technologies mature, the concept of a low-carbon or net-zero-carbon economy becomes more and more feasible. While many chemical and energy products do not contain carbon in their compounds, the upstream production process does. An added CCS module allows the removal of carbon emissions from the production process, which expands the value chain. This paper focuses on one of such commodities—low-carbon-intensity ammonia (LCIA). Even though ammonia is carbon-free in its final product, it is commonly made from natural gas, and the production process could generate significant carbon emissions. The idea of LCIA is to reduce the carbon footprint of the ammonia production process (e.g., blue ammonia) or eliminate carbon from the production process (e.g., green ammonia via electrolysis) so that the entire supply chain is decarbonized. The goal of this paper is two-fold. We first explore the US domestic market and the international market for LCIA. We then discuss relevant federal and local policies that could help grow markets for LCIA. The agricultural sector will be the center of the discussion, which consumes an estimated 70–90% of the global ammonia supply as fertilizers. The paper also examines other potential uses of LCIA, such as alternative fuels for decarbonizing agricultural machinery and transportation sectors. Finally, we argue that developing a comprehensive LCIA value chain, supported by dedicated policy measures and broad stakeholder engagement, is critical for materializing the potential of LCIA in contributing to a climate-resilient and sustainable economy.

Abstract Glioblastoma multiforme (GBM) is the most therapeutically challenging primary brain tumor owing to the unique physiological structure of the blood–brain barrier. Lately, research on targeted therapy for gliomas has shifted focus toward the tumor microenvironment and local immune responses. Pyroptosis is a newly identified cellular demise characterized by the release of numerous inflammatory factors. While pyroptosis shows promise in impeding the occurrence and progression of GBM, the regulatory mechanisms governing this process in gliomas still require further investigation. The function of the Enhancer of zeste homolog 2 (EZH2) in pyroptosis remains unexplored. In this study, we discovered that 3-Deazaneplanocin A (DZNep), an inhibitor of EZH2, can induce pyroptosis in GBM in vitro experiments. Moreover, our investigation unveiled that the signal transducer and activator of transcription (STAT3) could serve as a downstream regulator influenced by EZH2, impacting pyroptosis in GBM. Following treatment with DZNep and the STAT3 inhibitor (SH-4–54), there was an elevation in the levels of pyroptosis-related factors, namely NOD-like receptor thermal protein domain-associated protein 3 (NLRP3) and Gasdermin D (GSDMD). Moreover, simultaneous inhibition of both EZH2 and STAT3 led to the expression of inflammatory factors such as IL-1β and IL-18. In summary, we have identified that EZH2 regulates pyroptosis in GBM through STAT3, and pyroptosis could potentially be targeted for immunotherapy in GBM.

Abstract Epitope binning, an approach for grouping antibodies based on epitope similarities, is a critical step in antibody drug discovery. However, conventional methods are complex, involving individual antibody production. Here, we established Epitope Binning-seq, an epitope binning platform for simultaneously analyzing multiple antibodies. In this system, epitope similarity between the query antibodies (qAbs) displayed on antigen-expressing cells and a fluorescently labeled reference antibody (rAb) targeting a desired epitope is analyzed by flow cytometry. The qAbs with epitope similar to the rAb can be identified by next-generation sequencing analysis of fluorescence-negative cells. Sensitivity and reliability of this system are confirmed using rAbs, pertuzumab and trastuzumab, which target human epidermal growth factor receptor 2. Epitope Binning-seq enables simultaneous epitope evaluation of 14 qAbs at various abundances in libraries, grouping them into respective epitope bins. This versatile platform is applicable to diverse antibodies and antigens, potentially expediting the identification of clinically useful antibodies.

Traumatic brain injury (TBI) is a leading cause of disability and death. Thus, timely and effective secondary brain injury intervention is crucial, with potential to improve the prognosis of TBI. Oxidative stress contributes to post-traumatic secondary cognitive impairment, and the reduction of post-traumatic oxidative stress effectively enhances cognitive function. Phosphoglycerate-mutating enzyme 5 (PGAM5), a member of the phosphoglycerate transporter enzyme family, is upregulated in TBI and induces mitochondrial autophagy. This further exacerbates damage following TBI. The present study focused on the small molecule drug, LFHP-1c, which is a novel inhibitor of PGAM5. The present study used an in vivo mouse model incorporating a controlled cortical impact-induced TBI, to examine the impact of LFHP-1c on oxidative stress and cognitive function. The present study aimed to determine the impact of LFHP-1c on the PGAM5-Kelch-like ECH-associated protein 1 (KEAP1)- nuclear factor erythroid 2-related factor 2 (NRF2) ternary complex within the TBI context. Results of the present study indicated that LFHP-1c suppresses PGAM5 expression and inhibits the development of the PGAM5-KEAP1-NRF2 ternary complex, thereby promoting the release of NRF2 and KEAP1. This in turn promotes the entry of NRF2 into the nucleus following TBI, leading to increased expression of anti-oxidative stress downstream factors, such as heme oxygenase-1, glutathione peroxidase 1 and superoxide dismutase 1. In addition, LFHP-1c also released KEAP1, leading to mitochondrial Rho GTPase 2 degradation and reducing perinuclear aggregation of mitochondria in the cell, which reduced oxidative stress and ultimately improved cognitive function after TBI.

Colleges and universities are the key stage of transition connecting schools and society. Since college students are important talents supporting the economic and social development, it is necessary to promote science literacy and awareness among them. Specialized archives have archival, professional and cultural attributes, and can systematically record scientific research and management work in professional fields. As a base for cultural dissemination and patriotic education, specialized archives contribute to the promotion and education of knowledge and culture in various fields. Starting from the discussion of the cultural education and cultural transmission functions of specialized archives, the paper expounds the basic conditions for the marine culture education work of China Marine Archives, explores the original creation path, talent team path, spiritual path, transmission path and application path of marine culture education and transmission, and summarizes the experience and realization paths for reference in the industry.

Artificial intelligence for graph‐structured data has achieved remarkable success in applications such as recommendation systems, social networks, drug discovery, and circuit annotation. Graph convolutional networks (GCNs) are an effective way to learn representations of various graphs. The increasing size and complexity of graphs call for in‐memory computing (IMC) accelerators for GCN to alleviate massive data transmission between off‐chip memory and processing units. However, GCN implementation with IMC is challenging because of the large memory consumption, irregular memory access, and device nonidealities. Herein, a fully binarized GCN (BGCN) accelerator based on computational resistive random‐access memory (RRAM) through software–hardware codesign is presented. The essential operations including aggregation and combination in GCN are implemented on the RRAM crossbar arrays with cooperation between multiply‐and‐accumulation and content‐addressable memory operations. By leveraging the model quantization and IMC on the RRAM, the BGCN accelerator demonstrates less RRAM usage, high robustness to the device variations, high energy efficiency, and comparable classification accuracy compared to the current state‐of‐the‐art GCN accelerators on both graph classification task using the MUTAG and PTC datasets and node classification task using the Cora and CiteSeer datasets. These results provide a promising approach for edge intelligent systems to efficiently process graph‐structured data.

BackgroundCerebral aneurysm is a high-risk cerebrovascular disease with a poor prognosis, potentially linked to multiple factors. This study aims to explore the association between mitochondrial-associated proteins and the risk of cerebral aneurysms using Mendelian randomization (MR) methods.MethodsWe used GWAS summary statistics from the IEU Open GWAS project for mitochondrial-associated proteins and from the Finnish database for cerebral aneurysms (uIA, aSAH). The association between mitochondrial-associated exposures and cerebral aneurysms was evaluated using MR-Egger, weighted mode, IVW, simple mode and weighted median methods. Reverse MR assessed reverse causal relationship, while sensitivity analyses examined heterogeneity and pleiotropy in the instrumental variables. Significant causal relationship with cerebral aneurysms were confirmed using FDR correction.ResultsThrough MR analysis, we identified six mitochondrial proteins associated with an increased risk of aSAH: AIF1 (OR: 1.394, 95% CI: 1.109–1.752, p = 0.0044), CCDC90B (OR: 1.318, 95% CI: 1.132–1.535, p = 0.0004), TIM14 (OR: 1.272, 95% CI: 1.041–1.553, p = 0.0186), NAGS (OR: 1.219, 95% CI: 1.008–1.475, p = 0.041), tRNA PusA (OR: 1.311, 95% CI: 1.096–1.569, p = 0.003), and MRM3 (OR: 1.097, 95% CI: 1.016–1.185, p = 0.0175). Among these, CCDC90B, tRNA PusA, and AIF1 demonstrated a significant causal relationship with an increased risk of aSAH (FDR q

Integration of renewable energy is increasingly prevalent, yet its stochasticity may compromise the stability of the power system. In this paper, a high-voltage dc (HVDC) link model based on the modular multilevel converter with embedded energy storage (MMC-EES) is presented and, utilizing the massively parallel computing feature of the graphics processing unit (GPU), its efficacy in compensating a varying wind energy generation is studied. Constant power is oriented in the inverter control by incorporating a DC-DC converter with EES into its submodules. High-fidelity electromagnetic transient modeling is conducted for insights into converter control and energy management. A fully iterative solution is carried out for the nonlinear model for high accuracy. Since the sequential data processing manner of the central processing unit (CPU) is prone to an extremely long simulation following an increase of component quantity with even one order of magnitude, the massively concurrent threading of the GPU is exploited. The computational challenges posed by the complexity of the MMC circuit are effectively tackled by circuit partitioning which separates nonlinearities. In the meantime, components of an identical attribute are designed as one kernel despite inhomogeneity. The proposed modeling and computing method is applied to a multi-terminal DC system with wind farms, and significant speedups over CPU-based simulation are achieved, with the accuracy validated by the offline simulation tool PSCAD.

Background Hepatocellular carcinoma (HCC) is characterized by high morbidity and mortality. Early diagnosis and timely intervention in the precancerous stage can effectively reduce the incidence of HCC, which is of great significance for its prevention and treatment. Modern medical treatment of precancerous lesions of HCC has problems such as difficulties to grasp the timing of intervention and single treatment method, traditional Chinese medicine (TCM) may be a simple and effective new approach to prevent and treat precancerous lesion of HCC. Objective To observe the clinical efficacy and safety of Qizhuhuaji formula in the treatment of precancerous lesion of HCC (liver-depression and spleen-deficiency, phlegm and blood stasis syndrome) . Methods Patients with precancerous lesion of HCC who met the TCM syndrome type "liver-depression and spleen-deficiency, phlegm and blood stasis syndrome" admitted in the hepatology clinic of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Weihai Hospital of Traditional Chinese Medicine and Taian Hospital of Traditional Chinese Medicine from October 2019 to March 2020 were included as the study subjects. General information (gender, age, history of HBV-related cirrhosis, family history of HCC, history of alcohol consumption for more than 10 years), the TCM syndrome score, liver function indicators [alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), albumin (ALB), glutamyl transpeptidase (GGT), alkaline phosphatase (ALP) ], tumor marker indexes [alpha-fetoprotein (AFP), alpha-fetoprotein variants-L3 (AFP-L3), des-γ-carboxy-prothrombin (DCP) ], imaging indexes (lesion type, lesion nature, lesion length diameter), safety indexes and adverse reactions were collected. The 64 patients who met the inclusion criteria and completed the study were divided into the observation group (n=34) and the control group (n=30) using the random number tables. The patients in the control group were treated with conventional therapy such as antiviral, anti-inflammatory and liver-protective therapy; the observation group was treated with conventional therapy combined with Qizhuhuaji formula. The treatment course was 48 weeks, and the follow-up period was 48 weeks after drug withdrawal. The incidence of HCC and complications in the treatment cycle and follow-up period of the two group were observed, and the differences in the improvement indexes of TCM syndrome (TCM syndrome scores, total effective rate), liver function indicators, tumor marker indexes, imaging indexes (lesion length diameter, lesion stability rate, lesion improvement rate), and safety index (safety rate) between the two groups before and after treatment. Results After treatment, the TCM syndrome scores, ALT, AST, TBIL, GGT, ALP, and AFP-L3 were lower than those before treatment in both groups, and the ALB level was higher than that before treatment (P0.05) in the rates of lesion improvement (35.3%) and lesion stability (50.0%) in the observation group compared with the control group (20.0%, 43.3%). There was no statistically significant difference in the incidence of HCC between the observation group (8.8%) and the control group (16.7%) at the end of the follow-up period (P>0.05) ; the incidence of complications (8.8%) in the observation group was lower than that of the control group (30.0%) (P0.05) in the safety rate between the observation group (94.1%) and the control group (90.0%) . Conclusion The treatment of precancerous lesions of HCC (liver depression and spleen deficiency, phlegm and blood stasis syndrome) with Qizhuhuaji formula has better clinical efficacy and higher safety in improving TCM syndrome, improving liver function, shrinking lesion nodules, reducing the incidence of long-term HCC and complications of liver cirrhosis.

AIM: To analyze the global scientific output concerning myopic traction maculopathy (MTM) and to summarize the research frontiers and hot topics of MTM related researches. METHODS: Data were collected for bibliometric and visualization analyses from Web of Science (WOS) Core Collection. Exported records were analyzed for titles, publication years, research institutions, journal names, authors, keywords, and abstracts using CiteSpace software version 6.1. RESULTS: A total of 839 related studies were analyzed, the publication volume increased annually, with Asia the most active region of MTM research. Optical coherence tomography angiography, optical coherence tomography, macular hole, high myopia, macular buckling were identified as the focus of the current research. Progression, association, classification and shape were identified as the major research frontiers. CONCLUSION: MTM is a major cause of visual loss in pathological myopic eyes. During the preceding 17y, the number of annual publications in MTM research increased gradually. Studies on the progression nature of MTM, genome-wide association study and proper classification of MTM might still be the frontiers of MTM researches.

With the continuous depletion of fossil resources and the deterioration of the global climate, it is particularly urgent to find green and sustainable renewable resources to replace non-renewable resources. Renewable biomass, which converts and stores light energy into chemical energy through photosynthesis by green plants, has received widespread attention due to its simultaneous resource and energy properties. Therefore, this article focuses on lignocellulose, an important component of biomass, in the fields of chemical conversion and high-value-added chemical preparation. A detailed review was conducted on the application of catalysts in biomass bio-char, bio-oil, bio-gas, and high-value added chemicals and their derivatives, represented by 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA). At the same time, the difficulties and challenges encountered by catalysts in biomass conversion were analyzed, and new ideas were proposed for future development directions, so as to provide new development pathways for efficient and green conversion of biomass into biomass energy and high-value-added chemicals.

Background: In the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination. Methods: Download glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes. Results: The expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model. Conclusions: Our study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

Abstract Tropical cyclones (TCs) that undergo rapid intensification (RI) before landfall are notoriously difficult to predict and have caused tremendous damage to coastal regions in the United States. Using downscaled synthetic TCs and physics‐based models for storm tide and rain, we investigate the hazards posed by TCs that rapidly intensify before landfall under both historical and future mid‐emissions climate scenarios. In the downscaled synthetic data, the percentage of TCs experiencing RI is estimated to rise across a significant portion of the North Atlantic basin. Notably, future climate warming causes large increases in the probability of RI within 24 hr of landfall. Also, our analysis shows that RI events induce notably higher rainfall hazard levels than non‐RI events with equivalent TC intensities. As a result, RI events dominate increases in 100‐year rainfall and storm tide levels under climate change for most of the US coastline.

Despite the significant progress made in deep learning on digital computers, their energy consumption and computational speed still fall short of meeting the standards for brain-like computing. To address these limitations, reservoir computing (RC) has been gaining increasing attention across communities of electronic devices, computing systems, and machine learning, notably with its in-memory or in-sensor implementation on the hardware–software co-design. Hardware regarded, in-memory or in-sensor computers leverage emerging electronic and optoelectronic devices for data processing right where the data are stored or sensed. This technology dramatically reduces the energy consumption from frequent data transfers between sensing, storage, and computational units. Software regarded, RC enables real-time edge learning thanks to its brain-inspired dynamic system with massive training complexity reduction. From this perspective, we survey recent advancements in in-memory/in-sensor RC, including algorithm designs, material and device development, and downstream applications in classification and regression problems, and discuss challenges and opportunities ahead in this emerging field.

Abstract Penthorum chinense Pursh (P. chinense) has been traditionally used as hepatoprotective food and medicine for hundreds of years due to its significant antioxidant and anti-inflammatory activities. However, the efficacy and mechanisms of action of P. chinense in type 2 diabetes mellitus were not fully understood. In this study, we found that P. chinense extract (PCP) supplementation resulted in reduced body weight and hyperglycemia, improved pancreatic tissue injury and insulin sensitivity, and decreased inflammatory cytokines expression in spontaneously diabetic db/db mice. 16S rRNA gene sequencing of fecal samples showed that PCP administration decreased the abundance of Firmicutes and increased the proportion of Bacteroidetes at the phylum level. Moreover, Muribaculum, Barnesiella, Prevotella, and Mucinivorans were enriched, with Desulfovibrio and Lactobacillus lowered at the genus level in db/db mice with PCP supplementation. These results suggested that PCP may ameliorate hyperglycemia, insulin resistance, and inflammation by remodeling the gut microbiota in db/db mice.

Abstract The NFAT1-mediated IL6/JAK-STAT signaling pathway has been observed to contribute to malignant progression in glioma patients. To predict the overall survival (OS) rate of these patients, a prognostic model was developed based on this pathway. Two datasets, mRNAseq_325 and mRNAseq_693, were obtained from the China Glioma Genome Atlas (CGGA), excluding some patients with a lack of survival information, resulting in the inclusion of 684 glioma cases. The two groups were randomly divided into training and validation groups to analyze the differential expression of NFAT1 in pan-cancer and investigate the relationship between differential NFAT1 expression and glioma clinicopathological factors and Transcriptional subtypes. A prediction model based on the IL6/JAK/STAT signaling pathway was constructed using the LASSO-COX dimension reduction analysis to predict the OS of glioma patients. Pearson correlation analysis was utilized to identify gene sets associated with patient risk scores and to perform GO and KEGG analyses. NFAT1 is differentially expressed in a variety of cancers and is enriched in the more malignant potential glioma subtypes. It is an independent prognostic factor in glioma patients, and its expression is significantly positively correlated with the IL6/JAK/STAT signalling pathway in glioma patients. The final prediction model incorporating the seven candidate genes together with other prognostic factors showed strong predictive performance in both the training and validation groups. Risk scores of glioma patients were correlated with processes such as NF-κB and protein synthesis in glioma patients. This individualized prognostic model can be used to predict the OS rate of patients with glioma at 1, 2, 3, 5, and 10 years, providing a reference value for the treatment of glioma patients.

Highlights Proposing a one-step pyrolysis strategy to fabricate a novel bilayer-shelled N, O-doped hollow porous carbon microspheres (NOHPC) anode. The optimized NOHPC anode displays a high K-storage capacity of 325.9 mAh g−1 at 0.1 A g−1 and excellent rate performance (201.1 mAh g−1 at 5 A g−1 after 6000 cycles). The assembled NOHPC//hollow porous activated carbon microspheres (HPAC) potassium ion hybrid capacitors deliver a high energy density of 90.1 Wh kg−1 at a power density of 939.6 W kg−1 even over 6000 cycles.

Pancreatic β-cell failure is a pathological feature in type 1 diabetes. One promising approach involves inducing transdifferentiation of related pancreatic cell types, specifically α cells that produce glucagon. The chemokine stromal cell-derived factor-1 alpha (SDF-1α) is implicated in pancreatic α-to-β like cell transition. Here, the serum level of SDF-1α was lower in T1D with C-peptide loss, the miR-23a was negatively correlated with SDF-1α. We discovered that exosomal miR-23a, secreted from β cells, functionally downregulates the expression of SDF-1α, leading to increased Pax4 expression and decreased Arx expression in vivo. Adenovirus-vectored miR-23a sponge and mimic were constructed to further explored the miR-23a on pancreatic α-to-β like cell transition in vitro, which yielded results consistent with our cell-based assays. Suppression of miR-23a upregulated insulin level and downregulated glucagon level in STZ-induced diabetes mice models, effectively promoting α-to-β like cell transition. Our findings highlight miR-23a as a new therapeutic target for regenerating pancreatic β cells from α cells.

Background: Cerebral aneurysms (CAs) are a significant cerebrovascular ailment with a multifaceted etiology influenced by various factors including heredity and environment. This study aimed to explore the possible link between different types of immune cells and the occurrence of CAs.Methods: We analyzed the connection between 731 immune cell signatures and the risk of CAs by using publicly available genetic data. The analysis included four immune features, specifically median brightness levels (MBL), proportionate cell (PC), definite cell (DC), and morphological attributes (MA). Mendelian randomization (MR) analysis was conducted using the instrumental variables (IVs) derived from the genetic variation linked to CAs.Results: After multiple test adjustment based on the FDR method, the inverse variance weighted (IVW) method revealed that 3 immune cell phenotypes were linked to the risk of CAs. These included CD45 on HLA DR+NK (odds ratio (OR), 1.116; 95% confidence interval (CI), 1.001–1.244; p = 0.0489), CX3CR1 on CD14− CD16− (OR, 0.973; 95% CI, 0.948–0.999; p = 0.0447). An immune cell phenotype CD16− CD56 on NK was found to have a significant association with the risk of CAs in reverse MR study (OR, 0.950; 95% CI, 0.911–0.990; p = 0.0156).Conclusion: Our investigation has yielded findings that support a substantial genetic link between immune cells and CAs, thereby suggesting possible implications for future clinical interventions.

This paper delves into the critical role of tax credits, specifically Sections 45Q and 45V, in the financing and economic feasibility of low-carbon-intensity hydrogen projects, with a focus on natural-gas-based hydrogen production plants integrated with carbon capture and storage (CCS). This study covers the current clean energy landscape, underscoring the importance of low-carbon hydrogen as a key component in the transition to a sustainable energy future, and then explicates the mechanics of the 45Q and 45V tax credits, illustrating their direct impact on enhancing the economic attractiveness of such projects through a detailed net present value (NPV) model analysis. Our analysis reveals that the application of 45Q and 45V tax credits significantly reduces the levelized cost of hydrogen production, with scenarios indicating a reduction in cost ranging from USD 0.41/kg to USD 0.81/kg of hydrogen. Specifically, the 45Q tax credit demonstrates a slightly more advantageous impact on reducing costs compared to the 45V tax credit, underpinning the critical role of these fiscal measures in enhancing project returns and feasibility. Furthermore, this paper addresses the inherent limitations of utilizing tax credits, primarily the challenge posed by the mismatch between the scale of tax credits and the tax liability of the project developers. The concept and role of tax equity investments are discussed in response to this challenge. These findings contribute to the broader dialogue on the financing of sustainable energy projects, providing valuable insights for policymakers, investors, and developers in the hydrogen energy sector. By quantifying the economic benefits of tax credits and elucidating the role of tax equity investments, our research supports informed decision-making and strategic planning in the pursuit of a sustainable energy future.

Gliomas, the most prevalent primary tumors in the central nervous system, are marked by their immunosuppressive properties and consequent poor patient prognosis. Current evidence emphasizes the pivotal role of the tumor microenvironment in the progression of gliomas, largely attributed to tumor-associated macrophages (brain-resident microglia and bone marrow-derived macrophages) that create a tumor microenvironment conducive to the growth and invasion of tumor cells. Yet, distinguishing between these two cell subgroups remains a challenge. Thus, our review starts by analyzing the heterogeneity between these two cell subsets, then places emphasis on elucidating the complex interactions between microglia and glioma cells. Finally, we conclude with a summary of current attempts at immunotherapy that target microglia. However, given that independent research on microglia is still in its initial stages and has many shortcomings at the present time, we express our related concerns and hope that further research will be carried out to address these issues in the future.

Abstract Intrinsic plasticity of neurons, such as spontaneous threshold lowering (STL) to modulate neuronal excitability, is key to spatial attention of biological neural systems. In‐memory computing with emerging memristors is expected to solve the memory bottleneck of the von Neumann architecture commonly used in conventional digital computers and is deemed a promising solution to this bioinspired computing paradigm. Nonetheless, conventional memristors are incapable of implementing the STL plasticity of neurons due to their first‐order dynamics. Here, a second‐order memristor is experimentally demonstrated using yttria‐stabilized zirconia with Ag doping (YSZ:Ag) that exhibits STL functionality. The physical origin of the second‐order dynamics, i.e., the size evolution of Ag nanoclusters, is uncovered through transmission electron microscopy (TEM), which is leveraged to model the STL neuron. STL‐based spatial attention in a spiking convolutional neural network (SCNN) is demonstrated, improving the accuracy of a multiobject detection task from 70% (20%) to 90% (80%) for the object within (outside) the area receiving attention. This second‐order memristor with intrinsic STL dynamics paves the way for future machine intelligence, enabling high‐efficiency, compact footprint, and hardware‐encoded plasticity.

Abstract Background Corrected QT (QTc) interval has been reported to be associated with type 2 diabetes. This study aimed to explore the relationship between different glucose tolerance and QTc intervals among middle-aged and older Chinese individuals. Methods We conducted a cross-sectional analysis that included 9898 subjects (3194 men and 6704 women) in a Chinese population. Glucose tolerance was studied during the oral glucose tolerance test (OGTT). Insulin, blood pressure, hemoglobin A1c (HbA1c), serum lipids, hepatic transaminases and waist-to-hip ratio were assessed. The QTc interval was derived from ECG recordings, and the subjects were stratified based on different glucose tolerance. Results QTc interval levels were increased significantly in the subjects with abnormal glucose metabolism compared with the normal glucose regulation group. Multiple regression analyses showed that the QTc interval was significantly associated with fasting plasma glucose, 2-h OGTT plasma glucose and HbA1c. The odds ratio of prolonged QTc was 1.396 for impaired glucose regulation (IFG)/impaired fasting glucose (IGT) (95% CI 0.126–1.730), and 1.342 for type 2 diabetes (95% CI 0.142–1.577) after all potential confounders were adjusted. Conclusions Impaired glucose tolerance (IGR) and diabetes are associated with prolonged QTc intervals among middle-aged and older Chinese individuals. Abnormal glucose regulation can be used to monitor the QTc interval in the population.

Enhanced environmental standards are leading to an increasing proportion of microgrids (MGs) being integrated with renewable energy resources in modern power systems, which brings new challenges to simulate such a complex system. In this work, comprehensive modeling of a grid of microgrids for faster-than-real-time (FTRT) emulation is proposed, which can be utilized in the energy control center for contingencies analysis and dynamic security assessment. Electromagnetic transient (EMT) modeling is applied to the microgrid in order to reflect the detailed device processes of the converter and renewable energy sources, while the AC grid utilizes the transient stability modeling to reduce the computational burden and obtain a high acceleration value over real-time execution. Consequently, a dynamic power injection interface is proposed for the coexistence of the two simulation types. The reconfigurability and parallelism of the field-programmable gate arrays (FPGAs) enable the whole system to be executed in FTRT mode with 51 times acceleration over real-time. Meanwhile, three case studies are emulated and the results are validated by the off-line simulation tool Matlab/Simulink®.

Abstract Despite a variety of studies on the tropical cyclone (TC) response to climate change, few of them have examined the projected damages of future TCs. Here we quantify the impact of anthropogenic warming on TC-induced damages in the late twenty-first century along the coasts of Southeast China based on convection-permitting TC simulations and machine-learning-based damage models. We found that if the area’s 10 super typhoons between 2013 and 2019 were to occur at the end of the century under the high emissions RCP8.5 scenario, they would have on average a 12% ± 4% increase in landfall intensity, 25% ± 23% increase in precipitation, and 128% ± 70% increase in economic losses, compared to historical simulations. We also found a significant increase in the full risk profile. The estimated typhoon loss with a 50-year return period for Zhejiang, Fujian, Guangdong, and Hainan (four most typhoon-prone provinces among the seven provinces in the region) would increase by 71%, 170%, 20%, and 85%, respectively, towards the end of the century even under the lower emissions RCP4.5 pathway. Our findings imply the need to design effective local hazard mitigation measures to reduce future typhoon risks.

Hepatocellular carcinoma (HCC) has developed into one of the most lethal, aggressive, and malignant cancers worldwide. Although HCC treatment has improved in recent years, the incidence and lethality of HCC continue to increase yearly. Therefore, an in-depth study of the pathogenesis of HCC and the search for more reliable therapeutic targets are crucial to improving the survival quality of HCC patients. Currently, miRNAs have become one of the hotspots in life science research, which are widely present in living organisms and are non-coding RNAs involved in regulating gene expression. MiRNAs exert their biological roles by suppressing the expression of downstream genes and are engaged in various HCC-related processes, including proliferation, apoptosis, invasion, and metastasis. In addition, the expression status of miRNAs is related to the drug resistance mechanism of HCC, which has important implications for the systemic treatment of HCC. This paper reviews the regulatory role of miRNAs in the pathogenesis of HCC and the clinical applications of miRNAs in HCC in recent years.

As the global impact of climate change intensifies, there is an urgent need for equitable and efficient climate adaptation policies. Traditional approaches for allocating public resources for climate adaptation that are based on economic benefit-cost analysis often overlook the resulting distributional inequalities. In this study, we apply equity weightings to mitigate the distributional inequalities in two key building and household level adaptation strategies under changing coastal flood hazards: property buyouts and building retrofit in New York City (NYC). Under a mid-range emissions scenario, we find that unweighted benefit cost ratios applied to residential buildings are higher for richer and non-disadvantaged census tracts in NYC. The integration of income-based equity weights alters this correlation effect, which has the potential to shift investment in mitigation towards poorer and disadvantaged census tracts. This alteration is sensitive to the value of elasticity of marginal utility, the key parameter used to calculate the equity weight. Higher values of elasticity of marginal utility increase benefits for disadvantaged communities but reduce the overall economic benefits from investments, highlighting the trade-offs in incorporating equity into adaptation planning.

The study found that long-duration heatwaves are much more likely to follow power-damaging tropical cyclones in the future RCP8.5 climate, with the impact of longer-than-5-day tropical cyclone-blackout-heatwave compound hazard increasing by a factor of 23 over the 21st century.

Abstract Levator ani defect (LAD) closely correlates with pelvic floor disorders (PFD). In general, LAD was graded by three-dimensional ultrasonography (3D-US) and MRI, which could be used hardly in some developing area. Our objective was to determine whether two-dimensional ultrasonography (2D-US), a method that is almost universally accessible, could be used to diagnose the LAD. 129 Chinese women with PFD were recruited for the LAD grading by 2D-US and 3D-US and MRI. LAD was classified into intact, partial and complete avulsions. The puborectalis attachment width (PAW) was measured by 2D-US and with the software on the three-dimensional MRI-based LAD models. The results were compared and analyzed using the weighted kappa and the Pearson’s coefficient. Of the 119 patients, 64 were diagnosed with LAD by 2D-US, 70 were identified by 3D-US while 68 were confirmed by MRI. The LAD grading of 2D-US showed good agreement with MRI (kappa = 0.78, 95% CI 0.71–0.86) and 3D-US (kappa = 0.77, 95% CI 0.70–0.84). In regard to the consensus of partial or complete avulsions, 2D-US showed excellent good agreement with MRI (kappa = 0.86, 95% CI 0.73–0.97), superior than 3D-US with MRI (kappa = 0.55, 95% CI 0.36–0.71). Additionally, iliococcygeus avulsions detected by MRI (n = 7) were accompanied by complete puborectalis avulsions. The averaged PAW was 10.42 ± 5.57 mm measured by 2D-US, which correlated well with the results measured by MRI (Pearson’s coefficient = 0.90). 2D-US, 3D-US and MRI showed the good agreement on LAD diagnosis. Compared with MRI and 3D-US, 2D-US was comparable in grading LAD, especially complete avulsions.

Abstract Background To evaluate the diagnostic value of American College of Radiology (ACR) score and ACR Thyroid Imaging Report and Data System (TI-RADS) for benign nodules, medullary thyroid carcinoma (MTC) and papillary thyroid carcinoma (PTC) through comparing with Kwak TI-RADS. Methods Five hundred nine patients diagnosed with PTC, MTC or benign thyroid nodules were included and classified into the benign thyroid nodules group (n = 264), the PTC group (n = 189) and the MTC group (n = 56). The area under the curve (AUC) values were analyzed and the receiver operator characteristic (ROC) curves were drawn to compare the diagnostic efficiencies of ACR score, ACR TI-RADS and KWAK TI-RADS on benign thyroid nodules, MTC and PTC. Results The AUC values of ACR score, ACR TI-RADS and Kwak TI-RADS for distinguishing malignant nodules from benign nodules were 0.914 (95%CI: 0.886–0.937), 0.871 (95%CI: 0.839–0.899) and 0.885 (95%CI: 0.854–0.911), respectively. In distinguishing of patients with MTC from PTC, the AUC values of ACR score, ACR TI-RADS and Kwak TI-RADS were 0.650 (95%CI: 0.565–0.734), 0.596 (95%CI: 0.527–0.664), and 0.613 (95%CI: 0.545–0.681), respectively. The AUC values of ACR score, ACR TI-RADS and Kwak TI-RADS for the discrimination of patients with MTC, PTC or benign nodules from patients without MTC, PTC or benign nodules were 0.899 (95%CI: 0.882–0.915), 0.865 (95%CI: 0.846–0.885), and 0.873 (95%CI: 0.854–0.893), respectively. Conclusion The ACR score performed the best, followed ex aequo by the ACR and Kwak TI-RADS in discriminating patients with malignant nodules from benign nodules and patients with MTC from PTC.

Introduction Patients with active cancer face an increased risk for stroke. Randomized trials studying the efficacy of endovascular therapy for patients with large vessel occlusions generally excluded patients with cancer. Herein, we sought to better understand predictors of outcome for active cancer patients undergoing mechanical thrombectomy for acute ischemic stroke. Methods We conducted a retrospective cohort study of stroke thrombectomy cases performed at our institution from January 2010 to November 2021. Baseline clinical characteristics (age, gender, cancer type, use of anticoagulation, NIHSS, use of tPA, time to reperfusion) were recorded. Study outcomes were successful endovascular reperfusion (≥ TICI 2b) and poor clinical outcome, defined as inpatient death or disposition to hospice. Pearson Chi‐square test and Fisher’s exact test were used to analyze categorical variables, and Mann‐Whitney U tests were used for continuous variables. Multivariable logistic regression analyses were performed to evaluate for independent associations between baseline characteristics and study outcomes. Results Between 2010–2021, we identified 49 patients with active cancer who underwent mechanical thrombectomy for stroke. Their mean age was 63 years (SD, 12), and 43% were men. The leading cancer types were lung (33%) and colorectal (14%). Successful reperfusion was achieved in 78% (95% CI, 66–90%) of patients, and 49% (95% CI, 34–63%) ultimately had a poor clinical outcome. Multivariable analyses yielded no significant predictors for successful reperfusion, while higher NIHSS (1.03, 95% CI, 1.01‐1.06, p = 0.011) and higher cancer stage (1.19, 95% CI, 1.04‐1.34, p = 0.014) were found to be predictors for poor clinical outcome. Conclusions The link between cancer and stroke has become increasingly appreciated. As tPA is often contraindicated in cancer patients with stroke because of recent bleeding or anticoagulant use, thrombectomy may be the only intervention to preserve one’s quality of life. However, we found that despite a high successful reperfusion rate, nearly half of these patients died or were made hospice during the index hospitalization. Future studies should investigate the reasons for poor clinical outcomes in these patients and whether different antithrombotic, blood pressure, or anti‐neoplastic strategies after thrombectomy could improve outcomes.

IntroductionThe thyroid ultrasound guidelines include the American College of Radiology Thyroid Imaging Reporting and Data System, Chinese-Thyroid Imaging Reporting and Data System, Korean Society of Thyroid Radiology, European-Thyroid Imaging Reporting and Data System, American Thyroid Association, and American Association of Clinical Endocrinologists/American College of Endocrinology/Associazione Medici Endocrinologi guidelines. This study aimed to compare the efficiency of the six ultrasound guidelines vs. an artificial intelligence system (AI-SONICTM) in differentiating thyroid nodules, especially medullary thyroid carcinoma.MethodsThis retrospective study included patients with medullary thyroid carcinoma, papillary thyroid carcinoma, or benign nodules who underwent nodule resection between May 2010 and April 2020 at one hospital. The diagnostic efficacy of the seven diagnostic tools was evaluated using the receiver operator characteristic curves.ResultsFinally, 432 patients with 450 nodules were included for analysis. The American Association of Clinical Endocrinologists/American College of Endocrinology/Associazione Medici Endocrinologi guidelines had the best sensitivity (88.1%) and negative predictive value (78.6%) for differentiating papillary thyroid carcinoma or medullary thyroid carcinoma vs. benign nodules, while the Korean Society of Thyroid Radiology guidelines had the best specificity (85.6%) and positive predictive value (89.6%), and the American Thyroid Association guidelines had the best accuracy (83.7%). When assessing medullary thyroid carcinoma, the American Thyroid Association guidelines had the highest area under the curve (0.78), the American College of Radiology Thyroid Imaging Reporting and Data System guidelines had the best sensitivity (90.2%), and negative predictive value (91.8%), and AI-SONICTM had the best specificity (85.6%) and positive predictive value (67.5%). The Chinese-Thyroid Imaging Reporting and Data System guidelines had the best under the curve (0.86) in diagnosing malignant tumors vs. benign tumors, followed by the American Thyroid Association and Korean Society of Thyroid Radiology guidelines. The best positive likelihood ratios were achieved by the Korean Society of Thyroid Radiology guidelines and AI-SONICTM (both 5.37). The best negative likelihood ratio was achieved by the American Association of Clinical Endocrinologists/American College of Endocrinology/Associazione Medici Endocrinologi guidelines (0.17). The highest diagnostic odds ratio was achieved by the American Thyroid Association guidelines (24.78).DiscussionAll six guidelines and the AI-SONICTM system had satisfactory value in differentiating benign vs. malignant thyroid nodules.

In this paper, nano-silica particles were prepared from chlorosilane residue liquid using an inverse micro-emulsions system formed from octylphenyl polyoxyethylene ether (TX-100)/n-hexanol/cyclohexane/ammonia. The influence of different reaction conditions on the morphology, particle size, and dispersion of nano-silica particles was investigated via single-factor analysis. When the concentration of chlorosilane residue liquid (0.08 mol/L), hydrophile-lipophilic-balance (HLB) values (10.50), and the concentration of ammonia (0.58 mol/L) were under suitable conditions, the nano-silica particles had a more uniform morphology, smaller particle size, and better dispersion, while the size of the nano-silica particles gradually increased with the increase in the molar ratio of water to surfactant (ω). The prepared nano-silica was characterized through XRD, FT-IR, N2 adsorption/desorption experiments, and TG-DSC analysis. The results showed that the prepared nano-silica was amorphous mesoporous silica, and that the BET specific surface area was 850.5 m2/g. It also had good thermal stability. When the temperature exceeded 1140 °C, the nano-silica underwent a phase transition from an amorphous form to crystalline. This method not only promoted the sustainable development of the polysilicon industry, it also provided new ideas for the protection of the ecological environment, the preparation of environmental functional materials, and the recycling of resources and energy.

Cholangiocarcinoma (CCA) is one of the most common tumors with high malignancy. Its incidence is increasing year by year, and it is insidious and easily metastasized, and most patients are already in advanced stages when they are diagnosed. Surgery is an essential treatment for CCA, but the 5-year survival rate is still unsatisfactory due to the low early diagnosis rate and high malignancy of CCA. Therefore, exploring the molecular mechanisms of CCA to find reliable biomarkers and effective therapeutic targets is essential to improve the early diagnosis and survival rate of CCA. Non-coding RNA (ncRNA) is a class of RNA without protein-coding ability, mainly including microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA). In recent years, numerous pieces of evidence have shown that aberrantly expressed ncRNAs can regulate the occurrence and development of CCA through various mechanisms such as mediating epigenetic, sponge miRNAs regulating the expression of target genes and participating in regulating cancer-related signaling pathways, which provides new approaches and ideas for early diagnosis, prognosis assessment and therapeutic targeting of CCA. In this paper, we review the molecular mechanisms of lncRNAs and circRNAs regulating the progression of CCA in recent years and discuss their potential clinical value in CCA.

Power converter design evaluation by means of real-time simulation techniques is prevalent, although it is mostly restricted to simple power semiconductor switch models that exclude device-level physical details. In this work, the nonlinear high-order electrothermal model of the IGBT is developed and then deployed onto the heterogeneous digital hardware for real-time implementation. As the complexity of the NBM of the IGBT poses a significant computational burden on real-time hardware emulation, ML methodology is utilized so that the trained model can reproduce the characteristics of its original counterpart as much as possible and then it is implemented on the ACAP, which composes of the PS, PL, and AIE. The vector multiplication feature of the AIE caters to mathematical operations of the ML-based model particularly well and consequently enables it to be executed in real-time with remarkable speedup over the original model with which matrix inversion is otherwise mandatory. Finally, the validation for real-time device-level results and system-level results of a multiconverter system is provided by SaberRD and MATLAB/Simulink.

Modern power systems have been expanding significantly including the integration of high voltage direct current (HVDC) systems, bringing a tremendous computational challenge to transient stability simulation for dynamic security assessment (DSA). In this work, a practical method for energy control center with the machine learning (ML) based synchronous generator model (SGM) and dynamic equivalent model (DEM) is proposed to reduce the computational burden of the traditional transient stability (TS) simulation. The proposed ML-based models are deployed on the field programmable gate arrays (FPGAs) for faster-than-real-time (FTRT) digital twin hardware emulation of the real power system. The Gated Recurrent Unit (GRU) algorithm is adopted to train the SGM and DEM, where the training and testing datasets are obtained from the off-line simulation tool DSAToolsTM/TSAT®. A test system containing 15 ACTIVSg 500-bus systems interconnected by a 15-terminal DC grid is established for validating the accuracy of the proposed FTRT digital twin emulation platform. Due to the complexity of emulating large-scale AC-DC grid, multiple FPGA boards are applied, and a proper interface strategy is also proposed for data synchronization. As a result, the efficacy of the hardware emulation is demonstrated by two case studies, where an FTRT ratio of more than 684 is achieved by applying the GRU-SGM, while it reaches over 208 times for hybrid computational-ML based digital twin of AC-DC grid.

Abstract The electromagnetic transient (EMT) simulation of multi‐terminal DC (MTDC) grids requires a detailed device‐level modular multilevel converter (MMC) model, which can have thousands of state variables and complex internal structures. The fast device‐level insulated gate bipolar transistor (IGBT) transient requires a very small time‐step, making the computational overhead prohibitive. Based on the analysis of the parallel‐in‐time (PiT) implementation of detailed modelled MMCs, this paper proposes a task‐based hybrid PiT algorithm to achieve high parallel efficiency and speed‐up of MMC with device‐level modelling. Moreover, a transmission line model(TLM)‐based parallel‐in‐time‐and‐space (PiT+PiS) method is proposed to connect PiT grids to conventional or other PiT grids and exploit the maximum parallelism. Simulation results show greater than 30× speed‐up and 60% parallel efficiency on a 48 cores computer for the hybrid PiT method in a 201‐level three‐phase MMC test case, and 20× speed‐up in the transient simulation of CIGRÉ B4 DC grid test system for the PiT+PiS method.

Abstract Accurate delineation of compound flood hazard requires joint simulation of rainfall‐runoff and storm surges within high‐resolution flood models, which may be computationally expensive. There is a need for supplementing physical models with efficient, probabilistic methodologies for compound flood hazard assessment that can be applied under a range of climate and environment conditions. Here we propose an extension to the joint probability optimal sampling method (JPM‐OS), which has been widely used for storm surge assessment, and apply it for rainfall‐surge compound hazard assessment under climate change at the catchment‐scale. We utilize thousands of synthetic tropical cyclones (TCs) and physics‐based models to characterize storm surge and rainfall hazards at the coast. Then we implement a Bayesian quadrature optimization approach (JPM‐OS‐BQ) to select a small number (∼100) of storms, which are simulated within a high‐resolution flood model to characterize the compound flood hazard. We show that the limited JPM‐OS‐BQ simulations can capture historical flood return levels within 0.25 m compared to a high‐fidelity Monte Carlo approach. We find that the combined impact of 2100 sea‐level rise (SLR) and TC climatology changes on flood hazard change in the Cape Fear Estuary, NC will increase the 100‐year flood extent by 27% and increase inundation volume by 62%. Moreover, we show that probabilistic incorporation of SLR in the JPM‐OS‐BQ framework leads to different 100‐year flood maps compared to using a single mean SLR projection. Our framework can be applied to catchments across the United States Atlantic and Gulf coasts under a variety of climate and environment scenarios.

Background and aimsThe progressive and generalized loss of skeletal muscle mass, strength and physical function is defined as sarcopenia. Sarcopenia is closely related to the prognosis of patients. Accurate diagnosis and adequate management of sarcopenia are crucial. The psoas muscle mass index taken at the third lumbar vertebra (L3-PMI, cm2/m2) is one of the established methods for evaluating skeletal muscle mass. However, the cutoff values of L3-PMI for diagnosis of sarcopenia are not yet to be clarified in Asian populations. We attempted to establish reference values for low L3-PMI that would be suitable for defining sarcopenia in the Northern Chinese population.MethodsThis was a retrospective, multicenter cross-sectional study. A search of abdominal CT imaging reports was conducted in four representative cities in northern China. Transverse CT images were measured using the analysis software Slice-O-Matic. Low psoas muscle index was defined as the 5th percentile or mean-2SD of the study group.Results1,787 healthy individuals in the study were grouped by age. The sex and number of people in each group were similar. L3-PMI had a negative linear correlation with age, and a strong correlation with the skeletal muscle index taken at the third lumbar vertebrae (L3-SMI, cm2/m2). The L3-PMI reference values in males were 5.41 cm2/m2 for 20–29 years, 4.71 cm2/m2 for 30–39 years, 4.65 cm2/m2 for 40–49 years, 4.10 cm2/m2 for 50–59 years and 3.68 cm2/m2 for over 60 years by using 5th percentile threshold. Similarly, the reference values in females were 3.32, 3.40, 3.18, 2.91, and 2.62 cm2/m2. When using mean-2SD as the reference, the values for each age group were 4.57, 4.16, 4.03, 3.37, and 2.87 cm2/m2 for males and 2.79, 2.70, 2.50, 2.30, and 2.26 cm2/m2 for females, respectively.ConclusionWe defined the reference values of age-specific low skeletal muscle mass when simply evaluated by L3-PMI. Further studies about the association of sarcopenia using these reference values with certain clinical outcomes or diseases are needed.

We analyze a public dataset of rescue requests for the Houston Metropolitan Area during Hurricane Harvey (2017) from the Red Cross. This dataset contains information including the location, gender, and emergency description in each requester's report. We reveal the spatial distribution of the rescue requests and its relationship with indicators of the social, physical, and built environment. We show that the rescue request rates are significantly higher in regions with higher percentages of children, male population, population in poverty, or people with limited English, in addition to regions with higher inundation rate or worse traffic condition during Hurricane Harvey. The rescue request rate is found to be statistically uncorrelated with the percentage of flood hazard zone designated by the Federal Emergency Management Agency (FEMA).

It is widely accepted that climate change will cause sea level rise and increase the coastal flood hazard in many places. However, climate change also has significant implications for hurricane climatology. While the effect of climate change on hurricane frequency is inconclusive, there is a general consensus among climate scientists that hurricane intensity will increase over the coming decades. A number of studies indicate that hurricane size and translation speed may intensify with climate change as well. Each of these properties influences storm surge generation and propagation, and thus has significant implications for the coastal flood hazard, particularly in the densely populated northeast region of the U.S. As coastal populations grow, increasing the resilience of the built environment will become an increasingly necessary priority. Local, detailed, and comprehensive flood hazard assessment is a central aspect of such efforts. In this work, we integrate global climate data, statistical-deterministic hurricane modeling, physics-based numerical storm surge modeling, and extreme value analysis methods to comprehensively assess the present day and end of century flood hazard due to hurricanes for several coastal communities along the U.S. North Atlantic coastline. We find that by the end of the century, annual exceedance probabilities of the 100-year flood may increase by factors as great as 7 due to sea level rise, and on average projected changes to tropical cyclone climatology cause these probabilities to double. For truly effective long-term resilience efforts, coastal engineers, planners, and other stakeholders must account for climate change impacts to both sea level and tropical storm climatology.

Abstract Background Neck circumference, a proxy for upper-body subcutaneous fat, is a unique and pathogenic fat depot that confers additional metabolic risk. The purpose of present study was to determine whether neck circumference associates with nonalcoholic fatty liver disease (NAFLD) in postmenopausal women with normal body mass index. Methods A cross-sectional survey (n = 2492) and a 3.1-year follow-up investigation (n = 1354) were conducted among Chinese postmenopausal women with normal BMI (18.5 to

Large-scale photovoltaic (PV) power plant has witnessed a dramatic increase in the integration into transmission and distribution network, manifesting subsynchronous control interaction (SSCI) when the host grid is weak. In this work, the oscillation modes of a typical PV network are analyzed, and a faster-than-real-time (FTRT) emulation is proposed for predicting the SSCI and consequently mitigating its impacts on AC grid by taking the effective active/reactive power control action. The electromagnetic transient (EMT) simulation is utilized to model the PV panels and converter stations to reflect the actual dynamic process. Meanwhile, the AC grid undergoes transient stability (TS) simulation to obtain a high speed up over real-time, and consequently, a power-voltage interface is adopted for the coexistence of different simulation methods. The reconfigurability and parallelism of the field-programmable gate arrays (FPGAs) enable the EMT-TS co-emulation strategy to run concurrently. With a remarkable 122 FTRT ratio, the proposed hardware emulation can provide an effective solution before the SSCI causes serious disruption following its detection. The hardware emulation results are validated by the off-line simulation tool Matlab/Simulink® and TSAT® in the DSATools™ suite.

Abstract Background Proprotein convertase subtilisin/kexin type 9 (PCSK9) regulates cholesterol metabolism by targeting the low-density lipoprotein receptor. Recent studies have shown that circulating PCSK9 is associated with glucose homeostasis and insulin resistance. The aim of this study was to examine the association of circulating PCSK9 levels and risk for the development of type 2 diabetes in individuals with prediabetes. Methods A population-based prospective study was conducted among 4205 Chinese subjects with prediabetes (average age 56.1 ± 7.5 years). Incident type 2 diabetes was diagnosed according to 2010 American Diabetes Association criteria. Circulating PCSK9 levels were measured using a commercially available enzyme-linked immunosorbent assay (ELISA). The association of circulating PCSK9 levels with the risk of incident type 2 diabetes was assessed by Cox regression analysis. Results During a median follow-up period of 3.1 years, 568 subjects developed type 2 diabetes. Baseline circulating PCSK9 levels were significantly higher in female subjects developing incident type 2 diabetes than in those not developing incident type 2 diabetes (p