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The structure of the network among firms participating in global value chains is an important factor in understanding the changes in China's carbon emissions. This paper focuses on the interdependence between firms and the interconnected networks to which they belong, utilizing an inter-country input–output model that distinguishes between domestic-owned enterprises and foreign-invested enterprises for measurement purposes. By distinguishing between domestic and cross-border global value chains, we illustrate the carbon emission effects of relational global value chains and their network structures, thereby contributing a Chinese perspective on relational global value chains and carbon emission reduction. This study reveals that (1) relational global value chain activities have emerged as a significant contributor to China's carbon emissions, constituting approximately 26.8%, with its growth mainly stemming from the expansion of domestic global value chain emissions. At the sectoral level, relational global value chain activities lead to higher carbon emissions from the service sector than from the manufacturing sector. (2) Domestic global value chain relationship activities are more likely to have favorable economic and environmental trade-offs, as evidenced by the lower carbon intensity of the domestic global value chain than the cross-border global value chain. The circle-structured relationship activities between domestic-owned enterprises and foreign-invested enterprises are associated with more sustainable carbon emission growth and greater potential for emission reduction than the chain structure. (3) Structural decomposition analysis indicates that the impact of cross-border global value chain emissions on China's carbon emission growth has been decreasing since 2012, while the influence of the domestic global value chain is on the rise and surpasses that of the cross-border global value chain by the end of the period. [ABSTRACT FROM AUTHOR]

At the second stage of China Spallation Neutron Source (CSNS-II), it is predicted that 2 PB raw experimental data will be produced annually from twenty instruments. Scientific computing puts forward higher requirements for data sharing, utilization, retrieval, analysis efficiency, and security. However, the existing data management system (DMS) based on ICAT has several limitations including poor scalability of metadata database, imperfect data-management lifecycle and inflexible API. To ensure the accuracy, usability, scalability and efficiency of CSNS-II experimental data, a new scientific data management system is therefore designed based on the DOMAS framework developed by the Computing Center of IHEP. The data acquisition, transmission, storage and service systems are re-designed and tailored specifically for CSNS-II. Upon its completion, the new DMS will overcome the existing challenges and offer functions such as online display, search functionality and rapid download capabilities for metadata, raw data and analyzed data; flexible and user-friendly authorization; and data lifecycle management. Ultimately, the implementation of the new Data Management System (DMS) is expected to enhance the efficiency of experimental data analysis, propelling CSNS-II to achieve international advanced standards. Furthermore, it aims to reinforce self-reliance and technological strength in the field of science and technology at a high level in China. The development and deployment of the new DMS begin at the end of 2023. [ABSTRACT FROM AUTHOR]

Peptide cyclization has dramatic effects on a variety of important properties, enhancing metabolic stability, limiting conformational flexibility, and altering cellular entry and intracellular localization. The hydrophilic, polyfunctional nature of peptides creates chemoselectivity challenges in macrocyclization, especially for natural sequences without biorthogonal handles. Herein, we describe a gaseous sulfonyl chloride derived reagent that achieves amine–amine, amine–phenol, and amine–aniline crosslinking through a minimalist linchpin strategy that affords macrocyclic urea or carbamate products. The cyclization reaction is metal‐mediated and involves a novel application of sulfine species that remains unexplored in aqueous or biological contexts. The aqueous method delivers unique cyclic or bicyclic topologies directly from a variety of natural bioactive peptides without the need for protecting‐group strategies. [ABSTRACT FROM AUTHOR]

Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AECs)) and DRF using eight independent BB emission inventories applied to the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) during the BB period (March 2019) in peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections; FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS + VIIRS fire detections; FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 TgM-1), with 1.09 ± 0.83 TgM-1 and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 MOSVIS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high-AOD (HAOD; AOD > 1) regions range from 15–22.5 ∘ N, 97–110 ∘ E. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed, using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AECs simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AECs, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of - 32.60 ± 24.50 Wm-2 at the surface, positive forcing (1.70 ± 1.40 Wm-2) in the atmosphere, and negative forcing (- 30.89 ± 23.6 Wm-2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region. [ABSTRACT FROM AUTHOR]

Nighttime ozone in the lower boundary layer regulates atmospheric chemistry and surface ozone air quality, but our understanding of its vertical structure and impact is largely limited by the extreme sparsity of direct measurements. Here we present 3-year (2017–2019) measurements of ozone in the lower boundary layer (up to 500 m) from the Canton Tower in Guangzhou, the core megacity in South China, and interpret the measurements with a 1-month high-resolution chemical simulation from the Community Multiscale Air Quality (CMAQ) model. Measurements are available at 10, 118, 168, and 488 m, with the highest (488 m) measurement platform higher than the typical height of the nighttime stable boundary layer that allows direct measurements of ozone in the nighttime residual layer (RL). We find that ozone increases with altitude in the lower boundary layer throughout the day, with a vertical ozone gradient between the 10 and 488 m heights (Δ O 3/Δ H 10–488 m) of 3.6–6.4 ppbv hm -1 in nighttime and 4.4–5.8 ppbv hm -1 in daytime. We identify a high ozone residual ratio, defined as the ratio of ozone concentration averaged over nighttime to that in the afternoon (14:00–17:00 LT), of 69 %–90 % in January, April, and October, remarkably higher than that in the other three layers (29 %–51 %). Ozone in the afternoon convective mixing layer provides the source of ozone in the RL, and strong temperature inversion facilitates the ability of RL to store ozone from the daytime convective mixing layer. The tower-based measurement also indicates that the nighttime surface O x (O x= O 3+ NO 2) level can be an effective indicator of RL ozone if direct measurement is not available. We further find significant influences of nocturnal RL ozone on both the nighttime and the following day's daytime surface ozone air quality. During the surface nighttime ozone enhancement (NOE) event, we observe a significant decrease in ozone and an increase in NO 2 and CO at the 488 m height, in contrast to their changes at the surface, a typical feature of enhanced vertical mixing. The enhanced vertical mixing leads to an NOE event by introducing ozone-rich and NO x -poor air into the RL to enter the nighttime stable boundary layer. The CMAQ model simulations also demonstrate an enhanced positive contribution of vertical diffusion (Δ VDIF) to ozone at the 10 and 118 m heights and a negative contribution at the 168 and 488 m heights during the NOE event. We also observe a strong correlation between nighttime RL ozone and the following day's surface maximum daily 8 h average (MDA8) ozone. This is tied to enhanced vertical mixing with the collapse of nighttime RL and the development of a convective mixing layer, which is supported by the CMAQ diagnosis of the ozone budget, suggesting that the mixing of ozone-rich air from nighttime RL downward to the surface via the entrainment is an important mechanism for aggravating ozone pollution the following day. We find that the bias in CMAQ-simulated surface MDA8 ozone the following day shows a strong correlation coefficient (r= 0.74) with the bias in nighttime ozone in the RL, highlighting the necessity to correct air quality model bias in the nighttime RL ozone for accurate prediction of daytime ozone. Our study thus highlights the value of long-term tower-based measurements for understanding the coupling between nighttime ozone in the RL, surface ozone air quality, and boundary layer dynamics. [ABSTRACT FROM AUTHOR]

Background: The incidence and mortality of hepatocellular carcinoma (HCC) had increased globally over the past decades. Previous studies found that transarterial chemoembolization (TACE) combined with lenvatinib had also shown efficacy in the unresectable HCC. We aimed to evaluate the safety and efficacy of TACE combined with lenvatinib and camrelizumab to treat unresectable multiple nodular and large HCC (>5 cm). Materials and methods: Between November 2018 and June 2021, we retrospectively recruited 82 patients with unresectable multiple nodular and large HCC (BCLC stage B or C with a single nodular diameter of >5 cm). Of the patients who had not previously been treated, 33 patients received TACE + lenvatinib + camrelizumab (group A, TLC), and 49 patients treated with TACE + lenvatinib (group B, TLB) as the initial treatment. Related efficacy and safety results were recorded and assessed. Results: The median follow-up periods of groups A and B were 14.5 ± 7.9 months (range, 3-36) and 12.5 ± 8.2 months (range, 3-32), respectively (P = 0.799). The progression-free survival (PFS) of groups A and B was 9.4 months and 5.9 months (P < 0.01), respectively, and overall survival (OS) was significantly longer in group A (16.4 months vs 11.0 months, P < 0.01). In group A, the local response rate (LRR) and disease control rate (DCR) were 51.5% and 81.8%, respectively, which was higher than the corresponding 46.9% and 77.6% observed in group B (P = 0.233; 0.429). Patients with BCLC B stage had better PFS and OS (P < 0.05). The BCLC stage was an independent factor that affected PFS and OS. There were no massive bleeding or treatment-related deaths. Conclusions: In patients with unresectable multiple nodular and large HCC (single nodular diameter of >5 cm), TACE combined with target therapy and immunotherapy is safe and effective. [ABSTRACT FROM AUTHOR]

Despite significant advancements in improving the dataset for biomass burning (BB) emissions over the past few decades, uncertainties persist in BB aerosol emissions, impeding the accurate assessment of simulated aerosol optical properties (AOPs) and direct radiative forcing (DRF) during wildfire events in global and regional models. This study assessed AOPs (including aerosol optical depth (AOD), aerosol absorption optical depth (AAOD), and aerosol extinction coefficients (AEC)) and DRF using eight independent BB emission inventories applied to the WRF-Chem model during the BB period (March 2019) in Peninsular Southeast Asia (PSEA), where the eight BB emission inventories were the Global Fire Emissions Database version 4.1s (GFED), Fire INventory from NCAR version 1.5 (FINN1.5), the Fire Inventory from NCAR version 2.5 MOS (MODIS fire detections, FINN2.5 MOS), the Fire Inventory from NCAR version 2.5 MOSVIS (MODIS+VIIRS fire detections, FINN2.5 MOSVIS), Global Fire Assimilation System version 1.2s (GFAS), Fire Energetics and Emissions Research version 1.0 (FEER), Quick Fire Emissions Dataset version 2.5 release 1 (QFED), and Integrated Monitoring and Modelling System for Wildland FIRES Project version 2.0 (IS4FIRES), respectively. The results show that in the PSEA region, organic carbon (OC) emissions in the eight BB emission inventories differ by a factor of about 9 (0.295–2.533 Tg/M), with 1.09 ± 0.83 Tg/M and a coefficient of variation (CV) of 76 %. High-concentration OC emissions occurred primarily in savanna and agricultural fires. The OC emissions from the GFED and GFAS are significantly lower than the other inventories. The OC emissions in FINN2.5 VISMOS are approximately twice as high as those in FINN1.5. Sensitivity analysis of AOD simulated by WRF-Chem to different BB emission datasets indicated that the FINN scenarios (v1.5 and 2.5) significantly overestimate AOD compared to observation (VIIRS), while the other inventories underestimate AOD in the high AOD (HAOD, AOD>1) regions range from 97–110° E, 15–22.5° N. Among the eight schemes, IS4FIRES and FINN1.5 performed better in terms of AOD simulation consistency and bias in the HAOD region when compared to AERONET sites. The AAOD in WRF-Chem during the PSEA wildfire period was assessed using satellite observations (TROPOMI) and AERONET data, and it was found that the AAOD simulated with different BB schemes did not perform as well as the AOD. The significant overestimation of AAOD by FINN (v1.5 and 2.5), FEER, and IS4FIRES schemes in the HAOD region, with the largest overestimation for FINN2.5 MOSVIS. FINN1.5 schemes performed better in representing AAOD at AERONET sites within the HAOD region. The simulated AOD and AAOD from FINN2.5 MOSVIS always show the best correlation with the observations. AEC simulated by WRF-Chem with all the eight BB schemes trends were consistent with CALIPSO in the vertical direction (0.5 km to 4 km), demonstrating the efficacy of the smoke plume rise model used in WRF-Chem to simulate smoke plume heights. However, the FINN (v1.5 and 2.5) schemes overestimated AEC, while the other schemes underestimated it. In the HAOD region, BB aerosols exhibited a daytime shortwave radiative forcing of -32.60±24.50 W/m2 at the surface, positive forcing (1.70±1.40 W/m2) in the atmosphere, and negative forcing (-30.89±23.6 W/m2) at the top of the atmosphere. Based on the analysis, FINN1.5 and IS4FIRES are recommended for accurately assessing the impact of BB on air quality and climate in the PSEA region. [ABSTRACT FROM AUTHOR]

The Modular Emission Inventory Allocation Tool for Community Multiscale Air Quality Model (MEIAT-CMAQ) v1.0 is a resource that enables the refinement of coarse emission inventories by delivering complete temporal, species, and vertical allocations. This tool generates model-ready emission files for CMAQ, and it effectively addresses the challenges concerning the pinpointing of grid information and the spatial allocation for spatial surrogates with specific shapes. These features significantly enhance the accuracy of the allocation of emissions from transportation sectors. Additionally, MEIAT-CMAQv1.0 features an efficient operational algorithm and a modular design, thus conferring greater flexibility and making it suitable for both gridded and tabulated emissions inventories. By inputting pre-assessment and post-assessment emissions separately into the CMAQ model, we observe that post-allocation inventory has a significant positive effect on both O3 and PM2.5 simulations. The development of MEIAT-CMAQv1.0 provides valuable insights into the automated operation of air quality models and the development of emission inventory allocation tools. [ABSTRACT FROM AUTHOR]