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China’s Green Finance (GF) policy has been making significant strides toward the transition from a resource-oriented society to one that is resource-conserving and environmentally sustainable. Policymakers are currently focused on increasing green output to facilitate the next stage of green financial growth. In this study, we use panel data from 30 Chinese provinces between 2011 and 2020 to empirically analyze GF’s effect on Green Total Factor Productivity (GTFP). Evidence reveals that GF has a significant positive effect on provincial GTFP by promoting investment in innovation and optimizing industrial structure. However, the positive impact of GF on GTFP can be mitigated by green technology innovation output, highlighting the need for collaborative strategies for GF policy implementation and technology advancement. Furthermore, with the expansion of fintech innovation, the reduction of carbon emissions, and the intensification of environmental regulation, the effect of GF on GTFP is even more pronounced. [ABSTRACT FROM AUTHOR]

CaO and phosphates showed synergistic effects in the regulation of pyrolysis products in the pyrolysis of when they were directly mixed with camphor wood. The alkyl phenol yield increased during the pyrolysis process of corn straw fermentation residue directly mixed with KH2PO4 supported by γ-Al2O3. Rice stalks from agricultural crops are often disposed as waste. However, the potassium phosphate impregnated raw straw pyrolysis with CaO and Al2O3 has not been reported. This paper studied the synergistic effects of CaO or Al2O3 and three potassium phosphates (i.e., KH2PO4, K2HPO4·3H2O, and K3PO4·3H2O) in the rice straw pyrolysis through pyrolysis–gas chromatography-mass spectrometer (Py-GC/MS) experiments. The results showed that CaO/Al2O3 and potassium phosphates showed synergistic effects in the regulation of the types or contents of phenols, ketones, aldehydes, etc. and increased the contents of phenols, aldehydes, acids, and levoglucosan (LG) from most samples and increased those of ketones compared with those catalyzed by potassium phosphates alone. They were suitable for the production of ketone-rich and acid-low bio-oil, which is an important precursor for the preparation of power or jet fuel. The highest contents of ketones (HCK) reached 56.65% and 56.02% in the pyrolysis of K3PO4·3H2O impregnated rice straw with CaO or Al2O3, respectively. The lowest contents of acids and acetic acid (LCA) were nearly or equal to 0, respectively. HCK and LCA were respectively significantly higher and lower than the values reported in the literatures for biomass catalytic pyrolysis using CaO/Al2O3 and potassium phosphates alone or in combination. Dehydration reactions, etc. were further promoted under the co-catalysis of the two catalysts, and some phenols could be converted to benzene products, etc. For 50% K3PO4·3H2O impregnated sample, the yields of furans reduced sharply after CaO addition. For most impregnated samples except 50% K2HPO4·3H2O and 30% and 50% K3PO4·3H2O samples, the contents of total furans and furfural increased after Al2O3 addition. Highlights: CaO/Al2O3 and potassium phosphates showed synergistic effects in the regulation of the types or contents of phenols, ketones, aldehydes, etc. They were suitable for the production of ketone-rich and acid-low bio-oil, which was an important precursor for the preparation of power or jet fuel. Dehydration reactions, etc. were further promoted under the co-catalysis of the two catalysts, and some phenols could be converted to benzene products, etc. The lowest contents of acids and acetic acid were nearly or equal to 0, respectively. [ABSTRACT FROM AUTHOR]

• Consumption, international trade, and carbon emissions were examined in Japan. • Carbon emission transfers among sectors/countries were identified from 2000 to 2014. • Japan was found to be an emissions net import country (58% of emissions from China). • Household consumption accounted for ∼60% of consumption-based emissions. • These findings can help Japan customise sectoral carbon reduction priorities. International trade accelerates the separation between consumption and production on a global scale, thus leading to carbon transfer. Consequently, carbon flow embodied in international trade reallocates global carbon emission responsibilities, consisting of domestic demand and imports but excluding exports. To tackle the geographic flow of emissions embodied in products and services, carbon emissions must be quantified according to the global value chains. Using Japan as a case study, this study tracked the evolution of consumption patterns, international trade, and related carbon emissions based on multi-regional input-output tables, and carbon emissions inventories. Carbon emission transfers among sectors and countries were identified from 2000 to 2014. As a result, imports from the industrial sector led to a gap between production- and consumption-based carbon emissions. Japan was found to be an emissions net import country over the study period, with about 58% of the total carbon emissions inflow coming from China. Moreover, household consumption accounted for nearly 60% of consumption-based emissions, with industrial sector products and services being the primary source of carbon inflow, and the service, transport, and industry sectors are responsible for the majority of domestically released emissions. These conclusions provide valuable information for Japan to customize sectoral carbon reduction priorities, an essential component of setting decarbonization goals from the consumer perspective. [ABSTRACT FROM AUTHOR]

While the US electric power sector transitioning towards a low-carbon system, the escalated adoption of renewable energy has paradoxically increased water consumption. Consequently, it is imperative to engineer a power generation matrix that mitigates CO 2 emissions and minimizes water utilization. The primary endeavor should be to meticulously identify the variables affecting water consumption changes, especially highlighting and addressing the inherent tension between water conservation and carbon reduction. Employing temporal and spatial Logarithmic Mean Divisia Index methodologies, this study meticulously investigated the factors driving water consumption changes across state-level electricity production sectors in the US from 2010 to 2018. The analysis revealed that the generation mix structure was a predominant factor in escalating water consumption, exerting a more substantial influence than total power generation. Moreover, while the water consumption coefficient initially mitigates the impact of other factors, its effectiveness diminishes over time. Utilizing spatial Logarithmic Mean Divisia Index techniques, this paper further delineated state-level disparities, illuminating the heterogeneous nature of water consumption across regions. Projections up to 2050 suggest that water consumption reductions could be realized even amidst a highly intense scenario. The study's robustness and reliability were further augmented by employing an adaptive Logarithmic Mean Divisia Index. • Temporal-spatial LMDI reveals significant shifts in the US power sector water consumption. • Water consumption coefficient, fuel structure, and generation identified as key drivers. • Scenario analysis forecasts significant water savings potential by 2050. • Findings highlight the necessity for integrated water-energy transition policies. • Study proposes targeted strategies for a sustainable energy-water nexus. [ABSTRACT FROM AUTHOR]

Agricultural mechanization ties to fostering agricultural yield growth; however, it is still unknown how much methane from rice cultivation will be released after the universal electrification of the farm in the era of widespread agricultural mechanization. The main battlefield of greenhouse gas reduction is in industry, energy, and transportation sectors, and the emission reduction problem in agriculture and rural areas has not received enough attention. This study utilizes provincial data in China from 2010 to 2019 to investigate the farming facility electrification's effect on methane emissions from rice production at the provincial level. In this way, methane emission mitigation potentials and regional heterogeneity can be identified. As a result, a negative association between the expansion of green agricultural machinery electrification in rice production and methane emissions is solved by the proposed econometric models, indicating the necessity of expanding green and motorized agricultural machinery across provinces in China. Besides, this finding is reinforced through the robustness check. This research further finds that a region that has stronger resources and environment-carrying capacity, obtains more R&D investment, and is located in carbon-constrained pilot areas, as well as being in South China, would abate a higher number of methane emissions as renewable energy generation penetrating agricultural machinery. This study's findings support province-level expansion objectives for electrification of farming facilities and methane emission mitigation strategies. • Path-independent effect of methane emission is proven by Dynamic GMM models. • Reverse green energy consumption-methane association is significant. • The carbon pilot policy is beneficial for methane emission reduction. • Methane reduction attributes to renewable energy penetration in south China. • Build a novel framework identifying co-benefits of environmental regulations. [ABSTRACT FROM AUTHOR]

• A Stackelberg-Nash-Cournot equilibrium model is proposed for agricultural irrigation. • Water rights transaction is proved to lead to sustainable usage and development. • Scenario analysis is used to explore future uncertainty and its impacts on results. • The superiority of the proposed model is proved by comparison analysis. This paper focuses on water allocation in an irrigation district considering water rights transaction. The relationship between the reservoir authority and the sub-area managers is explored based on a novel Stackelberg-Nash-Cournot equilibrium model. In this framework, the reservoir authority has higher priority in allocating initial water rights to Sancha town, Danjing and Xinmin villages; after get the decisions from the reservoir authority, the sub-area managers decide water distribution to multi-crops planting areas and water rights transaction with the promise of Nash-Cournot equilibrium, then the reservoir authority can modify his decision by Stackelberg strategic interaction. To obtain the optimal irrigation strategy, fuzzy goal programming and genetic algorithm methods are applied. In this context, a Stackelberg-Nash-Cournot equilibrium solution can be obtained. The proposed model is applied to Sancha irrigation area, and the results show that more available water can be distributed in Sancha town while guaranteeing the equity among the sub-areas in this irrigation district; more water was utilized for wheat and oilseed rape than paddy and bean, which matched the fact that wheat and oilseed rape grow in quarters with relatively less rainfall inflows. A changeable and uncertain environment, regarding inflow levels, planting areas, and irrigation coefficient, take potential challenges to agricultural irrigation process. Hence, to cope with the challenges, cope with the future uncertainty and offer more information on the adjustment of agricultural irrigation patterns, scenario technique is applied by changing the three parameters – inflow levels, planting areas, and irrigation coefficient respectively. Finally, to highlight the superiority of the proposed model, a comparative analysis is conducted in a situation without considering the water market, which verifies the importance and effectiveness of water rights transaction. [ABSTRACT FROM AUTHOR]

• Stackelberg-Nash and Cournot-Nash games are applied to gain optimum strategies. • Uneven precipitation and stream inflow are characterized as fuzzy random variables. • An interactive-dynamic-programming-based genetic algorithm (IDP-GA) is designed. • An emergency response mechanism based on different climatic scenarios is developed. Increasing water demand aggravates water scarcity in water-scarce regions (e.g., India, Pakistan, and China), where uneven precipitation increases the risk of maintaining sustainable eco-economic development. Ignoring precipitation's effects leads to misguided policy recommendations that either deplete or underuse basin water resources. Therefore, this paper highlights the concept of uneven precipitation and uncertain stream inflow based on scenario analysis. Within a river basin, the regional authority and subarea managers both have water allocation and reallocation privileges. Motivated by sustainable development of water resource management systems, we argue that regional authorities should focus on alleviating the contradiction between supply and demand, and then seeking an optimum allocation strategy to ensure societal and economic benefits for its subareas, from which the subareas can provide reasonable reaction strategies. Authorities dominate water transactions between subareas involved in water rights distribution. This paper proposes a multi-objective multi-stage Stackelberg-Nash-Cournot (m2SNC) game model to cope with conflicts between regional authorities and subarea managers concerning multiple activities. An interactive-dynamic-programming-based genetic algorithm (IDP-GA) is designed to simulate the policies needed for the optimum allocation of water resources under various climate scenarios. The significant stress caused by unsustainable water resource allocation has been a perplexing problem for Sancha Lake, an important area in the southeast basin of the Dujiangyan Irrigation System in China. To identify the tradeoffs among stakeholders, we apply the proposed model to this basin. To gain further insight into climate change and water usage sustainability, we simulate the varying spatial and seasonal distribution of stream inflow based on historical climate data and propose different water management strategies for normal, slight drought, moderate drought, and serious drought conditions. This creates an emergency response cooperative mechanism based on different climate scenarios for developing countries that need to cope with water deficiency and uncertain situations. [ABSTRACT FROM AUTHOR]

In this work, we introduce Video Question Answering in the temporal domain to infer the past, describe the present and predict the future. We present an encoder-decoder approach using Recurrent Neural Networks to learn the temporal structures of videos and introduce a dual-channel ranking loss to answer multiple-choice questions. We explore approaches for finer understanding of video content using the question form of 'fill-in-the-blank', and collect our Video Context QA dataset consisting of 109,895 video clips with a total duration of more than 1000 h from existing TACoS, MPII-MD and MEDTest 14 datasets. In addition, 390,744 corresponding questions are generated from annotations. Extensive experiments demonstrate that our approach significantly outperforms the compared baselines. [ABSTRACT FROM AUTHOR]

China pushed for the unification of markets for natural resources and emissions, wherein initial allocation mechanisms have a significant impact on how well the market functions. To identify how the market works well, this paper builds an integrated framework, comprised of permits initialization and reallocation processes. Additionally, we simulate variables by 2030 through scenario analysis and machine learning methods. At the unified energy-carbon market, GDP could increase by more than 49%, while the total energy consumption and the total carbon emission increase by around 410 million tons and 711 million tons, respectively, in China. This illustrates how joint trading markets favor economic growth and emission reduction simultaneously. Besides, most of China's provinces obtain improved energy consumption and carbon emission intensities, which proves the effectiveness and importance of the unified market. However, two rebound effects are found, one is that the increased investment is not always promoting positive effects, and the other is that provinces with higher GDPs have less incentive to cut their energy use. Further, the accumulated per capita initialization type favors energy conservation, while per GDP initialization benefits economic growth and carbon reduction. It's needed that simultaneously constructing an economic and efficient incentive mechanism while effectively playing up the government's role. [Display omitted] • Energy and carbon joint markets have economic and environmental co-benefits. • A novel framework is designed enabling the exchange of energy and carbon permits. • The influence of socio-economic and climate change scenarios in the future is considered. • The influence of initial permits allocation modes on market performance is identified. • Promotion measures are needed especially for provinces with higher economic outputs. [ABSTRACT FROM AUTHOR]

Carbon emission trading, a market-incentive environmental regulation, plays a critical role in leading China towards the carbon peaking and carbon neutrality. To improve the national carbon emission trading in China, we analyze the effects of the policy in pilot provinces and pilot A-share listed firms from 2008 to 2016. Particularly, to explore the pilot policy's environmental and financial impacts, this paper applies a difference-in-difference method. After the robustness check, the results confirm the carbon emission trading pilot's significantly positive impact at both firm- and province-level regarding carbon emission reduction. Meanwhile, corporate innovation seems to partially mediate the relationship between the policy and corporate carbon emission reduction. Plus, the policy promotes firms' market-based financial performance but such impact on accounting-based financial performance is insignificant. Ultimately, the operational mechanism of the policy is proved to be effective. In this paper, industry- and firm-level carbon emissions databases are established via environmental extended input-output table, which fill the research gap of China's firm-level carbon emissions. To ensure the reliability of results, the list of covered firms is sorted out manually in accordance with the disclosed data of seven carbon trading markets. Our results are meaningful for avoid productivity reduction and mechanism re-design in the context of the national carbon emission trading launched in 2021. Specifically, encouraging firms to further improve their productivity and competitiveness by innovation could eventually achieve a win-win situation between economic performance and environmental merits in the long run. [ABSTRACT FROM AUTHOR]

Abstract: The successful applications of manifold learning in computer vision and multimedia research show that the geodesic distance along the manifold is more meaningful than Euclidean distance in the linear space. Therefore, in order to get better performance of image classification, it is preferable to have classifier defined on the low-dimensional manifold. However, most of the manifold learning algorithms do not provide explicit mapping of the unseen data. In this paper, we propose a framework of image classification with manifold learning for out-of-sample data. The method of local and global regressive mapping for manifold learning simultaneously learns the low-dimensional embedding of the input data and a mapping function for out-of-sample data extrapolation. The low-dimensional manifold embedding of large-scale images can be obtained by the mapping functions. Utilizing the supervised classifier, we predict class labels for test images in the learned low-dimensional manifold. Experiments on two large-scale image datasets demonstrate that the proposed framework has better performance of image classification than the kernelized dimension reduction methods. [Copyright &y& Elsevier]

Due to the unequal distribution of water resources, challenges remain in the water resource allocation. How to upgrade water use efficiency has become an urgent issue worldwide, especially in arid and semiarid areas. Therefore, water allocation management that balancing the trade-off between economic development and environmental protection has become a hot topic in recent years but lacks applicational analysis. To narrow this knowledge gap, this study introduces a food-water nexus to the case study by introducing virtual water trade into the proposed model. Given climate change's impacts on seasonal water supply, this study divides a planning year by season. Under this framework, a bi-objective dynamic model for water allocation is formulated and applied to a typical water-arid area, Lanzhou, China in 2017. The study aims to produce an optimal water resource allocation strategy among industrial, domestic, agricultural and ecological sectors and reveal the effects of variable precipitation on the water allocation strategy. Finally, this model is found to reach an economic-environmental balance based on the Pareto frontier depicted by the solved solutions. The results show that the gap between supply and demand will be supplemented by virtual water, and virtual water trade has simultaneously increased economic benefit, saved water and improved integrated water-use efficiency. In addition, distinct strategies about water allocation and virtual water trade are identified in spring, summer, autumn and winter. The study also finds that virtual water trade contributes to equity improvement of water resource allocation, which can provide vital information on common prosperity for future water resource management at the regional level. • A bi-objective dynamic model to optimize seasonal water allocation and VWT pattern. • 1.51∗107 m3 of irrigation water is saved via incorporating VWT in the planning year. • Water allocation inequity is redressed by optimizing water allocation and VWT together. • Considering economic-environment sustainability for optimizing water-food nexus pattern. [ABSTRACT FROM AUTHOR]

Suitable cropland use is not only beneficial for satisfying human daily demand, but also for controlling non-point source pollution leaks into adjacent rivers. Optimal industrial production levels are economical, and they also avoid water deterioration. With the promise of being lower than the total allowed emission cap, water use participants have to balance trade-offs between optimal production levels and emission amounts. Effluent trading seems to be a cost-effective method to reduce effluent emission as it allows effluent reallocation among different sectors. Because of changing hydrological information and continuous development of treatment technology, the effluent production ratio is regarded as uncertain and is characterized as polygonal budget sets. This study tries to control the total emission quantity by optimizing cropland use and non-agricultural production levels using effluent trading under uncertain future environments. To illustrate the feasibility of the proposed model, an application is conducted in Indonisian Citarum River. The application finds that the proposed model is able to (1) identify an optimal effluent trading scheme that balances various production plans from multiple water users; (2) balance the trade-off between total emission reduction and total benefit maximization by changing budget levels; and (3) ease the decision makers burden, avoid information losses or distortions, and guide them in adjusting farmland planning, production levels, and effluent trading results under uncertainty. Based on the results, managerial implications are analyzed in terms of (1) the optimal crop area planning in the agricultural sector and the optimal production level in non-agricultural sectors; and (2) the optimal effluent trading pattern that expands economic development without deteriorating water environments. Finally, the comparison analysis with a traditional deterministic model, verify that with the incorporation of robust parameters, flexible solutions are offered to decision makers that have different attitudes toward constraints-violation risks. • Point and non-point source pollution within a watershed are considered together. • Polyhedral uncertainty sets are used to characterize pollutant production ratios. • Effluent trading is allowed while optimizing sectoral production levels. • Able to guide crops area planning, industrial production and effluent trading. [ABSTRACT FROM AUTHOR]

• We develop a decision-making framework to evaluate wastewater treatment technology. • Opinions of experts and local residents are integrated in the framework. • Different wastewater treatment technologies are suitable for different contexts. • The decision-making framework eases the burden of decision makers. • Interval Type-2 fuzzy sets are used to manage the complexity of the process. Water pollution is a problem globally, where untreated human and industrial waste is directly discharged into water bodies. Choosing a suitable wastewater treatment technology (WTT) is vital. We develop a novel multi-criteria group decision-making framework to evaluate four WTTs (Anaerobic Anoxic Oxic, Triple Oxidation Ditch, Anaerobic Single Oxidation Ditch, Sequencing Batch Reactor Activated Sludge). It consists of four phases: (1) collecting incomplete linguistic pairwise comparisons; (2) characterizing this matrix by incomplete interval type-2 fuzzy sets; (3) repairing incomplete information to reach predefined consistency/consensus levels; and (4) calculating the arithmetic ranking values. We demonstrate the feasibility and superiority of the model, inviting experts to evaluate the WTTs against eight criteria. Finally, we conduct a series of comparative analyses and a sensitivity analysis. The model gives a thorough measure of WTTs across multiple criteria. The suitable WTT is different for small or medium towns, and big cities in developing or developed countries. [ABSTRACT FROM AUTHOR]

Industrial production and environmental management systems should be simultaneously considered for sustainable development. This paper evaluated the performance of an integrated two-stage system using a proposed type-2 fuzzy bi-objective two-stage slacks-based measurement Data Envelopment Analysis model with super efficiency. A Step Method was applied to solve for the Pareto optimal solution to ensure no implicit priority was given to one stage over the other, and a CV-based reduction method and generalized credibility based chance constrained programming were used to cope with the type-2 fuzzy variables. A case study in China was then developed from a time-perspective and a region-perspective, the results from which indicated that the overall performance of China's integrated system improved from 2005 to 2014, and the efficiency gap between the industrial production system and the environmental management system reduced, however, there was significant disparity shown across the different economic regions. Three comparative analyses were then conducted to highlight the superiority of the proposed model. The developed model was able to: measure efficiency scores and find proportionate ratios and disproportionate slacks for each DMU to decrease inputs for performance improvement, distinguish the DMU from DMUs with same efficiency value and indicate the maximum change scope for the inputs and outputs to maintain the DMU efficiency. In addition, type-2 fuzzy sets were incorporated to describe the fuzziness with greater flexibility, which can assist decision makers and produce more accurate, robust results. [ABSTRACT FROM AUTHOR]

The Omei wood frog (Rana omeimontis), endemic to central China, belongs to the family Ranidae. In this study, we achieved detail knowledge about the mitogenome of the species. The length of the genome is 20,120 bp, including 13 protein‐coding genes (PCGs), 22 tRNA genes, two rRNA genes, and a noncoding control region. Similar to other amphibians, we found that only nine genes (ND6 and eight tRNA genes) are encoded on the light strand (L) and other genes on the heavy strand (H). Totally, The base composition of the mitochondrial genome included 27.29% A, 28.85% T, 28.87% C, and 15.00% G, respectively. The control regions among the Rana species were found to exhibit rich genetic variability and A + T content. R. omeimontis was clustered together with R. chaochiaoensis in phylogenetic tree. Compared to R. amurensis and R. kunyuensi, it was more closely related to R. chaochiaoensis, and a new way of gene rearrangement (ND6‐trnE‐Cytb‐D‐loop‐trnL2 (CUN)‐ND5‐D‐loop) was also found in the mitogenome of R. amurensis and R. kunyuensi. Our results about the mitochondrial genome of R. omeimontis will contribute to the future studies on phylogenetic relationship and the taxonomic status of Rana and related Ranidae species. [ABSTRACT FROM AUTHOR]

In this paper, we consider the wave propagation with Debye polarization in nonlinear dielectric materials. The Rothe's method is employed to derive the well-posedness of the electric fields and the polarized fields by monotonicity theorem as well as the boundedness of the two fields are established. Then, the decoupled full-discrete scheme is established with the first order approximation in time and Raviart-Thomas-Nédélec element k ≥ 2 in spatial. Based on the truncated error, we present the convergent analysis with the order O (Δ t + h s) under an a-prior L ∞ assumption of numerical solutions. For k = 1 , we employ the superconvergence technique to ensure the a-prior L ∞ assumption. In the end, we give some numerical examples to demonstrate our theories. [ABSTRACT FROM AUTHOR]

Pyrolysis-gas chromatography-mass spectrometer (Py-GC/MS) was used to investigate the catalytic pyrolysis of camphor wood with the mixture of CaO and four types of calcined phosphates (K 3 PO 4 ·3H 2 O, K 2 HPO 4 ·3H 2 O, KH 2 PO 4 , and Zn 3 (PO 4) 2 ·4H 2 O). The results show that after CaO and calcined K 3 PO 4 ·3H 2 O addition, the relative yields of 3-methoxy-1,2-benzenediol, 3-methoxy-2,5,6-trimethylphenol decrease significantly, while those of isoeugenol, trans -isoeugenol, and furfural are obviously enhanced. CaO and calcined K 3 PO 4 ·3H 2 O exhibit strong synergistic effects and can regulate the composition distributions of products such as phenols. The relative yields of cyclopentanones and phenols are enhanced after the mixture of CaO and calcined K 2 HPO 4 ·3H 2 O addition compared with those with single CaO or calcined K 2 HPO 4 ·3H 2 O addition. The relative yields of acetic acid fluctuate in the range of 8.90–9.56% after calcined KH 2 PO 4 addition. After adding the mixture of CaO and calcined KH 2 PO 4 , the relative yields of acetic acid decrease from 9.11% to 4.65% and those of propionaldehyde and 2, 6-dimethoxy-phenylpropionic acid compounds are improved compared with those after single catalyst addition. CaO and calcined Zn 3 (PO 4) 2 ·4H 2 O have strong synergistic effects on the formation of chain alkanes. They also enhance the relative contents of phenol and further decrease those of resorcinol, 3-methoxy-1,2-benzenediol, 4-methyl-1,2-benzenediol, indicating they exhibit strong synergistic effects and can further catalyze the cleavage of hydroxyl, methyl and methoxy groups. [ABSTRACT FROM AUTHOR]