Comparative transcriptome analysis of Saposhnikovia divaricata to reveal drought and rehydration adaption strategies.

BACKGROUND: Water scarcity has become one of the most prevalent environmental factors adversely affecting plant growth and development. Different species have developed multiple ways of drought resistance. Saposhnikovia divaricata is a commonly used traditional herb in East Asia. However, limited information is available on the drought response of this herb and further clarification of underlying molecular mechanism remains a challenge. METHODS AND RESULTS: In this study, a comparative transcriptome analysis was firstly conducted to identify the major pathways and candidate genes involved in the drought adaptive response of S. divaricata. The seedlings of S. divaricata were subjected to progressive drought by withholding water for 16 days followed by 8 days of rehydration. Transcriptome analysis identified a total of 89,784 annotated unigenes. The number of differentially expressed genes (DEGs) gradually increased with the deepening of drought and decreased after rehydration. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested genes related to oxidoreductase activity, carbohydrate metabolism, plant hormone signaling pathway and secondary metabolism were important in drought response of S. divaricata. Specific genes involved in reactive oxygen species scavenging system (POD, Cu/Zn-SOD, APX), abscisic acid and jasmonic acid signaling pathway (PYL4, PP2Cs, JAR1, JAZ) and phenylpropanoid biosynthesis (4CL, CCR, CAD) underwent dynamic alterations under drought and rehydration. Finally, the expression pattern of 12 selected DEGs from the transcriptomic profiling was validated by real-time quantitative PCR. CONCLUSION: Our study laid a foundation for understanding the stress response of S. divaricata and other Apiaceae family plant at molecular level.

Factors affecting household solid waste generation and management in Sri Lanka: an empirical study.

This study examines the effect of "waste management" factors (Knowledge, Motivation, Time, Awareness, Contribution, Attitudes) on household waste generation (HWG), more precisely the measured weight of waste generated at households for a week (MWWGHW) while controlling for the socioeconomic factors such as family size, monthly family income, education level, and occupation. It also examines the moderating effects of the geographic location (urban versus rural areas) on the relationships between waste management factors and MWWGHW while controlling for the aforementioned socioeconomic factors. The overall results show that socioeconomic factors such as Family Size ([Formula: see text] = 0.134; p < 0.001) and Monthly Family Income ([Formula: see text] = 0.301; p < 0.001) significantly and positively influence MWWGHW, whereas the Occupation factor ([Formula: see text] = - 0.106, p < 0.05) significantly and negatively influences MWWGHW. Furthermore, the results show that the Knowledge ([Formula: see text] = - 0.129, p < 0.05), Motivation ([Formula: see text] = - 0.161, p < 0.001), Contribution ([Formula: see text] = - 0.111, p < 0.05), and Awareness ([Formula: see text]= - 0.189, p < 0.001) factors significantly and negatively influence MWWGHW. While the results show that the geographic location Urban Area moderates significantly the relationship between the Motivation factor and MWWGHW ([Formula: see text] = - 0.129, p < 0.05), the same results show, however, that the geographic location Rural Area moderates significantly but negatively the relationships between Knowledge factor and MWWGHW ([Formula: see text] = - 0.187, p < 0.01); Motivation factor and MWWGHW ([Formula: see text] = - 0.390, p < 0.001); Contribution factor and MWWGHW ([Formula: see text] = - 0.154, p < 0.10); and Awareness factor and MWWGHW ([Formula: see text] = - 0.285, p < 0.001). Based on these results, implications for policy orientations and future research are provided.

Cell-Penetrating Peptide Enhanced Antigen Presentation for Cancer Immunotherapy.

The development of effective cancer vaccines is an important direction in the area of cancer immunotherapy. Although certain types of preventive cancer vaccines have already been used in the clinic, therapeutic cancer vaccines for treatment of already established tumors are still in high demand. In this study, we develop a new type of cancer vaccine by mixing cell-penetrating peptide (CPP) conjugated antigen as the enhanced antigen, together with CpG as the immune adjuvant. A special CPP, cytosol-localizing internalization peptide 6 (CLIP6), which has the ability to enter cells exclusively via a nonendosomal mechanism, i.e., direct translocation across the cell membrane, is conjugated with model antigen ovalbumin (OVA). Compared to naked OVA, the obtained CLIP6-OVA conjugates show greatly increased uptake by dendritic cells (DCs) and, more importantly, remarkably enhanced antigen cross-presentation, eliciting stronger cytotoxic T lymphocyte (CTL) mediated immune responses with the help of CpG. This CLIP6-OVA/CpG formulation offers effective protection for mice against challenged B16-OVA tumors, and is able to further function as a therapeutic vaccine, which, in combination with immune checkpoint blockade therapy, can significantly suppress the already-established tumors. Such a CLIP6-based cancer vaccine developing strategy shows promising potential toward clinical practice owing to its features of easy preparation, low cost, and remarkable biocompatibility.

Secreted peroxidases VmPODs play critical roles in the conidiation, H2O2 sensitivity and pathogenicity of Valsa mali.

Apple Valsa canker, caused by the necrotrophic pathogen Valsa mali, is a devastating disease of apples and causes great financial loss in East Asia. Improving the understanding of apple - V. mali interactions will contribute to disease management. In this study, three predicted secreted peroxidases (VmPOD1, VmPOD2 and VmPOD3) were uncovered based on the secretome and genome information of V. mali. Phylogenetic analysis showed that VmPOD1 is a catalase peroxidase, VmPOD2 is a chloroperoxidase, and VmPOD3 is a plant peroxidase-like peroxidase. The secretion function of the corresponding genes was confirmed using the yeast invertase secretion system. The deletion of VmPODs did not affect the vegetative growth when the mutants (ΔVmPOD1, ΔVmPOD2 and ΔVmPOD3) and the wild-type strain 03-8 were grown on PDA medium at 25 °C in the dark. However, the respective mutants showed impaired conidiation ability with fewer pycnidia, and all gene deletion mutants grew more slowly than 03-8 on PDA supplemented with H2O2 (Final concentration: 0.06 mol/L H2O2). In addition, VmPOD1 and VmPOD2 were found to be significantly up-regulated at an early infection stage, and VmPOD3 showed sustained high expression during the whole infection progress of V. mali. In addition, the virulence of ΔVmPOD3 was significantly reduced, implying that VmPOD3 plays a critical role during the interaction between V. mali and apple. All of the defective phenotypes could be nearly restored by re-introducing the wild-type VmPOD1, VmPOD2 or VmPOD3 allele. The results enhanced our understanding of the secreted peroxidase, which could also act as a type of virulence factor from the necrotrophic pathogen V. mali and provided new insight into the role of the pathogen-secreted peroxidase.

Prognostic impact of pretreatment lymphocyte-to-monocyte ratio in advanced epithelial cancers: a meta-analysis.

BACKGROUND: There is increasing evidence that inflammation-based biomarkers are associated with tumor microenvironment which plays important roles in cancer progression. A high lymphocyte-to-monocyte ratio (LMR), has been suggested to indicate favorable prognoses in various epithelial cancers. We performed a meta-analysis to quantify the prognostic value of LMR in advanced-stage epithelial cancers undergoing various treatment. METHODS: We searched PubMed, EMBASE, Web of science and Cochrane Library up to July 2018 for relevant studies. We included studies assessing the prognostic impact of pretreatment LMR on clinical outcomes in patients with advanced-stage epithelial cancers. The primary outcome was overall survival (OS) and the secondary outcome was progression free survival (PFS). The summary hazard ratio (HR) and 95% confidence interval (CI) were calculated. RESULTS: A total of 8984 patients from 35 studies were included. A high pretreatment LMR was associated with favorable OS (HR = 0.578, 95% CI 0.522-0.641, P < 0.001) and PFS (HR = 0.598, 95% CI 0.465-0.768, P < 0.001). The effect of LMR on OS was observed among various tumor types. A higher pretreatment LMR was associated with improved OS in chemotherapy (n = 10, HR = 0.592, 95% CI 0.518-0.676, P < 0.001), surgery (n = 10, HR = 0.683, 95% CI 0.579-0.807, P < 0.001) and combined therapy (n = 11, HR = 0.507, 95% CI 0.442-0.582, P < 0.001) in the subgroup analysis by different therapeutic strategies. The cut-off value for LMR was 3.0 (range = 2.35-5.46). Subgroup analysis according to the cut-off value showed a significant prognostic value of LMR on OS and PFS in both subgroups. CONCLUSIONS: A high pretreatment LMR is associated with favorable clinical outcomes in advanced-stage epithelial cancers undergoing different therapeutic strategies. LMR could be used to improve clinical decision-making regarding treatment in advanced epithelial cancers.

Adaptive Ship Detection for Single-Look Complex SAR Images Based on SVWIE-Noncircularity Decomposition.

In this paper, we present an adaptive ship detection method for single-look complex synthetic aperture radar (SAR) images. First, noncircularity is analyzed and adopted in ship detection task; besides, similarity variance weighted information entropy (SVWIE) is proposed for clutter reduction and target enhancement. According to the analysis of scattering of SVWIE and noncircularity, SVWIE-noncircularity (SN) decomposition is developed. Based on the decomposition, two components, the high-noncircularity SVWIE amplitude (h) and the low-noncircularity SVWIE amplitude (l), are obtained. We demonstrate that ships and clutter in SAR images are different for h detector and h detector can be effectively used for ship detection. Finally, to extract ships from the background, the generalized Gamma distribution (G Γ D) is used to fit h statistics of clutter and the constant false alarm rate (CFAR) is utilized to choose an adaptive threshold. The performance of the proposed method is demonstrated on HH polarization of Alos-2 images. Experimental results show that the proposed method can accurately detect ships in complex background, i.e., ships are close to small islands or with strong noise.

A Suitable Option for Gustilo and Anderson Grade III Injury.

BACKGROUND The management of Gustilo and Anderson grade III injury remains difficult, particularly due to the incidence of wound infections, delayed fracture union, and traumatic extremity amputation. However, little data is available on delayed skin graft or flap reconstructions of Gustilo grade III injury, especially using new technologies of wound coverage, such as vacuum sealing drainage (VSD) combined with limited internal and/or external fixation. MATERIAL AND METHODS Between June 2008 and May 2013, we performed the VSD technique combined with limited internal and/or external fixation on 38 patients (22 males and 16 females, with a mean age of 36.5 years) with Gustilo and Anderson grade III injury. VSD was regularly changed and delayed skin grafts or flaps were used to cover the defect. Two patients were lost to follow-up, and the remaining 36 were available for evaluation. The complications, wound healing, infections, and bony union were assessed for a mean duration of 2.5 years (range, 1-4 years). RESULTS Complications were seen in 5 of the 36 cases: 2 cases had infection alone, 1 case had delayed union or nonunion, 1 case had infection and delayed union, and 1 case had wound necrosis, infection, and nonunion. VSD was regularly changed 2-6 times. Morphological appearance and functional recovery were satisfactory in all cases. CONCLUSIONS Using VSD before skin grafts or flaps coverage, combined with limited internal and/or external fixation, is a suitable option for Gustilo and Anderson grade III injury.

Assessing the influence of the digital economy on carbon emissions: Evidence at the global level.

This paper discusses the influence of the digital economy (DE) on carbon emissions based on evidence at the global level. Specifically, based on the panel data from 80 countries from 2010 to 2020, this paper creates a DE measurement index and uses the System-GMM model to assess the influence of DE on carbon emissions. The results show that: (1) The development of DE significantly promotes carbon emissions reduction. (2) The development of DE significantly promotes carbon emissions reduction through technological advancement, structural optimization, and educational enhancement; (3) Regulatory quality and financial development play a positively moderating role in DE's promoting effect on carbon emissions reduction; (4) DE of European and North American nations have stronger promoting effect on carbon emissions reduction than DE of other countries. Compared to DE of developing countries, DE of developed countries has a stronger promoting effect on carbon emissions reduction. Additionally, this paper also finds that institutional differences can impact the carbon emission reduction effects of DE. Based on the results, this paper suggests that governments globally should promote the development of DE and foster international cooperation to enhance DE's driving role in promoting carbon emissions reduction.

Novel ß-Hairpin Antimicrobial Peptide Containing the ß-Turn Sequence of -NG- and the Tryptophan Zippers Facilitate Self-Assembly into Nanofibers, Exhibiting Excellent Antimicrobial Performance.

Antimicrobial peptides (AMPs) have emerged as promising agents to combat the antibiotic resistance crisis due to their rapid bactericidal activity and low propensity for drug resistance. However, AMPs face challenges in terms of balancing enhanced antimicrobial efficacy with increased toxicity during modification processes. In this study, de novo d-type ß-hairpin AMPs are designed. The conformational transformation of self-assembling peptide W-4 in the environment of the bacterial membrane and the erythrocyte membrane affected its antibacterial activity and hemolytic activity and finally showed a high antibacterial effect and low toxicity. Furthermore, W-4 displays remarkable stability, minimal occurrence of drug resistance, and synergistic effects when combined with antibiotics. The in vivo studies confirm its high safety and potent wound-healing properties at the sites infected by bacteria. This study substantiates that nanostructured AMPs possess enhanced biocompatibility. These advances reveal the superiority of self-assembled AMPs and contribute to the development of nanoantibacterial materials.

Arginine and tryptophan-rich dendritic antimicrobial peptides that disrupt membranes for bacterial infection in vivo.

The potent antibacterial activity and low resistance of antimicrobial peptides (AMPs) render them potential candidates for treating multidrug-resistant bacterial infections. Herein, a minimalist design strategy was proposed employing the "golden partner" combination of arginine (R) and tryptophan (W), along with a dendritic structure to design AMPs. By extension, the α/ε-amino group and the carboxyl group of lysine (K) were utilized to link R and W, forming dendritic peptide templates αRn(εRn)KWm-NH2 and αWn(εWn)KRm-NH2, respectively. The corresponding linear peptide templates R2nKWm-NH2 and W2nKRm-NH2 were used as controls. Their physicochemical properties, activity, toxicity, and stability were compared. Among these new peptides, the dendritic peptide R2(R2)KW4 was screened as a prospective candidate owing to its preferable antibacterial properties, biocompatibility, and stability. Additionally, R2(R2)KW4 not only effectively restrained the progression of antibiotic resistance, but also demonstrated synergistic utility when combined with conventional antibiotics due to its unique membrane-disruptive mechanism. Furthermore, R2(R2)KW4 possessed low toxicity (LD50 = 109.31 mg/kg) in vivo, while efficiently clearing E. coli in pulmonary-infected mice. In conclusion, R2(R2)KW4 has the potential to become an antimicrobial regent or adjuvant, and the minimalist design strategy of dendritic peptides provides innovative and encouraging thoughts in designing AMPs.

How does air pollution affect the stock market performance? Evidence from China.

Given its broad impact on human society, air pollution could become a non-economic factor affecting the stock market. But the impact of air pollution on the stock market performance has not received enough attention. This study examines the influence and potential mechanism of air pollution on stock market performance based on the panel data of 1344 A-share listed firms in China covering the period 2013-2019. The result shows that air pollution can negatively affect stock market performance. Second, heterogeneity analysis creatively points out that firms with less analysts, smaller size, stated-owned ownership, polluting related industry are more vulnerable to the negative effects of air pollution. Finally, the result also reveals a mechanism that air pollution could worsen the stock market by depressing investors' sentiments. The above findings enrich current research related to the impact of air pollution on stock market performance and also provide a new perspective for investors to make stock investment decisions.

Catalpol Alleviates Depression by Inhibiting NLRP3 Inflammasome via TLR4/MAPK/NF-Kb Pathway.

Background: We aimed to explore catalpol and NF-k. The role of antidepressant and anti-inflammatory effects of b inhibitor in depression induced by chronic unpredictable mild stress (CUMS). Methods: Under the guidance of Qiqihar Medical University, from January 2020 to January 2021, the weight, sucrose consumption and rest time of mice during swimming were monitored, the neurobehavioral changes of rats under CUMS were used to determine the experimental model; ELISA detection of iNOS, ROS, caspase-1, IL-1 ß And IL-18 expression level; Western blotting detection of TLR4, MAPK and NF-κB expression level; LPS-induced cell model. INOS, NLRP3, caspase-1, IL-1 in RT-qPCR and ELISA detection models ß And IL-18 expression level; the TLR4, MAPK and NF-κB level were detected by Western blotting. Results: CUMS can make rats lose weight, reduce sucrose consumption rate and prolong rest time. Catapol can enhance this effect; In the depression model, ROS, NLRP3, NF-κ B and iNOS were up-regulated Catalpol group MAPK, NF-κ Reduced expression of B and TLR4; ROS, caspase-1, IL-1ß, IL-18 and iNOS protein increased. Cell model group TLR4, MAPK and NF-κ. The high protein content of B decreased in catalpol group. Conclusion: Catalpol acts as anti-depressant and anti-inflammatory molecule indepression induced by CUMS. Combination of catalpol with NF-κB inhibitor might play a role in the treatment of depression through regulating the neuroinflammation.

What drives the export-related carbon intensity changes in China? Empirical analyses from temporal-spatial-industrial perspectives.

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002-2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002-2014; the effects of the value-added coefficient, input-output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested.

Global value chains participation and carbon emissions embodied in exports of China: Perspective of firm heterogeneity.

This paper studies the impact of global value chains (GVCs) participation on carbon emissions embodied in exports (EEE) of China during 2005-2016, and analyses firm heterogeneity from the perspective of firm ownership and trade patterns; Then, industries are classified based on factor intensity and technology level, and the industrial heterogeneity of different firms is analyzed; Finally, through counterfactual analysis, this paper evaluates EEE under four anti-globalization scenarios. The empirical study shows that with the increase of GVCs position, EEE first increases and then decreases, showing an inverted U-shaped distribution. From the perspective of firm ownership, the relationship between GVCs position of domestic firms and EEE is inverted U-shaped distribution, while GVCs position of multinational enterprises (MNEs) is positively correlated with EEE. The relationship of capital-intensive and technology-intensive domestic firms, high-tech and medium-tech manufacturing domestic firms are also inverted U-shaped distribution. The positive correlation of MNEs is reflected in the low-tech manufacturing industries. From the perspective of trade patterns, with the increase of GVCs position, EEE of processing trade firms presents an inverted U-shaped distribution, while it is not significant for general trade firms. The inverted U-shaped relationship between GVCs position in capital-intensive industries and EEE are confirmed in all firms. Under anti-globalization scenarios of 50% backflow, EEE would increase. Under scenarios of 100% backflow, EEE would reduce. The results above provide useful references to achieve carbon emission reduction targets.

Structural and technological determinants of carbon intensity reduction of China's electricity generation.

Electricity generation is the largest sector with decarbonization potential for China and the world. Based on the new emission factors, this paper aims to identify the structural and technological determinants of provincial carbon intensity in the electricity generation sector (CIE) using the multiplicative LMDI-II method. Results demonstrate that (1) China's overall CIE decreases by 7.3% in 2001-2015, and the research period can be divided into four stages according to CIE changes (i.e., rapid growth, rapid decline, slow growth, and transition). The CIE in the 12th FYP estimated in this paper, 24.9% lower than that using the emission factors from IPCC, is closer to China's actual situation. (2) There exists huge heterogeneity in the determinants of provincial CIE changes in four stages. CIE growth in the Northwest and Northeast is caused by the coal-dominated energy structure. CIE growth in the Southwest is attributed to the electricity structure effect, while that of the Coast region is caused by the geographic distribution effect. The electricity efficiency effect is attributed to the CIE growth for these regions and the Southwest should also place focus on the electricity trade effect. The impact of electricity trade-related factors depends on the region being a net exporter or importer of electricity. (3) To achieve carbon intensity reduction targets, 30 provinces are categorized into four types based on various combinations of structural and technological determinants. The findings provide insights into capturing future emission-mitigating focus as well as defining the emission-mitigating responsibilities between electricity exporters and importers in China.

Dynamic characteristics and drivers of the regional household energy-carbon-water nexus in China.

Being a node of the energy-water consumer and carbon dioxide (CO2) emitter, the household is one key sector to pilot integrated energy-carbon-water (ECW) management. This study developed an integrated framework to explore China's provincial household ECW nexus as well as their drivers from the years 2000 through 2016. The absolute amount and growth rate of household energy use (HEU), household CO2 emissions (HCE), and household water use (HWU) were abstracted to reveal the dynamic characteristics of the household ECW nexus. Efficiency advance, income growth, urbanization, family size, and household number were defined to explain the changes in the household ECW nexus. This study revealed that there is a huge regional heterogeneity in China's household ECW nexus. Developed regions such as Zhejiang, Jiangsu, Guangdong, and Shanghai are the most important household ECW nexus nodes with larger amounts and growth rates of household ECW. Income growth overwhelmingly increases ECW, while efficiency advance effectively curbs its growth. Comparatively, household number, family size, and urbanization have small effects. Therefore, implementing differentiated management and focusing on the synergy of socioeconomic factors are the keys to achieving integrated household ECW management. And the analytical framework can be used to analyze ECW nexus from a sector, city, or country perspective.

Critical transmission paths and nodes of carbon emissions in electricity supply chain.

As the largest contributor to production-based emissions, electricity generation sector has led to huge carbon emission transmissions. This is the first attempt to explore the latest features of carbon emission transmissions from electricity sector to the final domestic consumption of China in 2002-2015, combining MRIO-based Structural Path Analysis and transmission-based emission method. Results show that: (1) Although inter-provincial transmissions are increasing significantly, emission transmissions within intra-provincial trading are dominated. (2) 30 provinces are classified into two types, i.e., consumption centers and production centers. Both the inter-provincial transmission paths in consumption centers and production centers show the grid-level agglomeration and provincial heterogeneity. The inflow paths in consumption centers are mainly sourced from the production of Eastern China and South China, while the outflow paths for production centers are caused by the consumption in Central China, Guangdong and Jiangsu. Inter-provincial linkages are intensified and perform the feature of territorial propinquity. (3) Both intra-grid and inter-grid transmission nodes show an agglomeration trend of "electricity sector < intermediate sectors < electricity sector < consumption". These intermediate sectors include manufacture sectors, energy-intensive sectors and service sector. This paper provides policy implications on promoting low-carbon electricity cooperation across provinces and managing intermediate transmissions along supply chain.

Permafrost Dynamics Observatory-Part I: Postprocessing and Calibration Methods of UAVSAR L-Band InSAR Data for Seasonal Subsidence Estimation.

Interferometric synthetic aperture radar (InSAR) has been used to quantify a range of surface and near surface physical properties in permafrost landscapes. Most previous InSAR studies have utilized spaceborne InSAR platforms, but InSAR datasets over permafrost landscapes collected from airborne platforms have been steadily growing in recent years. Most existing algorithms dedicated toward retrieval of permafrost physical properties were originally developed for spaceborne InSAR platforms. In this study, which is the first in a two part series, we introduce a series of calibration techniques developed to apply a novel joint retrieval algorithm for permafrost active layer thickness retrieval to an airborne InSAR dataset acquired in 2017 by NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar over Alaska and Western Canada. We demonstrate how InSAR measurement uncertainties are mitigated by these calibration methods and quantify remaining measurement uncertainties with a novel method of modeling interferometric phase uncertainty using a Gaussian mixture model. Finally, we discuss the impact of native SAR resolution on InSAR measurements, the limitation of using few interferograms per retrieval, and the implications of our findings for cross-comparison of airborne and spaceborne InSAR datasets acquired over Arctic regions underlain by permafrost.

Rabi splitting induced by a metamaterial plasmon cavity.

We studied the surface plasmon resonance properties of transverse electric (TE) wave in a µ-negative (MNG) material/dielectric/µ-negative (MNG) material waveguide with a finite length which works as a subwavelength cavity. The wavelength of the surface plasmon becomes shorter when decrease the thickness of the dielectric core and decrease the plasma frequency of MNG material. The resonance in this cavity can be understood as a Fabry-Perot resonance caused by the reflection of the TE guided mode at the entrance and the exit surfaces. The electromagnetic fields and power flow are concentrated around the dielectric core at the resonant frequency, the magnetic field is maximized at the dielectric core entrance and exit. When a subwavelength magnetic resonator is put at the core entrance and the resonance frequency is tuned to the plasmon cavity mode, Rabi splitting and Rabi oscillation can appear because of the strong coupling between this resonator and the cavity mode.

How China's electricity generation sector can achieve its carbon intensity reduction targets?

As the largest sector with decarbonization potential, electricity generation is critical for achieving carbon intensity reduction targets of China by 2020 and 2030. This study combines temporal decomposition and scenario analysis to identify the key drivers and provinces with increasing carbon intensity of electricity generation (CIE) and designs four scenarios by integrating efficiency improvement and structural adjustment in 30 provinces of China, and estimates the possible reduction of CIE by 2020 and 2030. Results show that 1) CIE in China decreases by 7.25% during 2001-2015. The estimated CIE during 12th FYP in this study is 25% lower than the estimation using IPCC emission factors, which is closer to China's reality. 2) Driving forces of CIE changes in 30 provinces vary greatly across provinces. The increasing CIE in four worse-performance regions (i.e. Northeast, South Coast, Southwest, Northwest) is mainly caused by energy mix effect and geographic distribution effect. The CIE growth in South Coast is also related to thermal power share effect. 3) Both 2020/2030 targets can be achieved by regulating the drivers for CIE growth in 30 provinces (i.e., RAK scenario). CIE decline is concentrated in three types of provinces, namely provinces with large economic size, strong policy support and clean energy implementation. The findings and recommendations provide insights into achieving 2020/2030 targets for CIE reduction.