Double Target Research Articles

Research on Government Regulations, Cognition and Farmers’ Willingness of Straw-to-Field

Contemporarily, the promotion and application of straw-to-field technology plays an important role in developing high-quality green agriculture, alleviating agricultural non-point source pollution and realizing the double carbon target. As the main subject of straw-to-field, a farmers’ willingness directly determines their straw-to-field behavior. To explore the influencing factors of farmers’ straw-to-field willingness and to improve the comprehensive utilization level of straw, this paper researches the relationship between government regulation, farmers’ subject cognition and straw-to-field willingness based on the survey data of 733 farmers in Heilongjiang province, and it examines the mediating role of farmers’ cognition in the process of government regulation affecting farmers’ willingness of straw-to-field. The results evidence that policy incentives and administrative constraints affect farmers’ willingness of straw-to-field by influencing ecological and technical cognition. However, farmers’ cognition of the cost and benefit of straw-to-field is biased; thus, this factor cannot effectively transform the willingness of straw-to-field into action.

A Monitoring Method for Corporate Environmental Performance Based on Data Fusion in China under the Double Carbon Target

The production and operation of corporates have a significant impact on the environment, and it is crucial for corporates to operate in an environmentally friendly manner, especially in the context of the China double carbon target. Corporate environmental performance refers to the degree of impact on the environment and the degree of contribution to environmental protection by corporates in their business activities. Our study conducted an assessment and early warning system for corporate environmental performance by monitoring seven typical corporate environmental performance variables, including the green asset ratio (Gra), the proportion of environmentally friendly products (Pefp), and cash flow for environmental protection to total assets ratio (ECF), of 2718 non-financial listed corporates in China’s A-share market. The dataset comprised empirical data from the CSMAR database and multi-scale measurements collected by us. Among data-driven monitoring methods, deep learning is widely applied due to its powerful automatic feature extraction abilities. However, multi-time scale data is often encountered in industrial ecology-related data, as the different underlying physical quantities of various data result in inconsistent sampling rates. Multi-time scale data are incomplete and asymmetrical, making it difficult for traditional models to use directly for corporate ecological monitoring. In this article, an improved CNN-LSTM monitoring model based on data fusion is proposed to address this issue. This method employs unified vectorization processing to transform incomplete multi-time scale data into uniform complete data. An end-to-end diagnostic model is constructed to simultaneously optimize feature extraction and monitoring. In a multi-time scale corporate monitoring model, CNN can mine hidden features of data, while LSTM can further capture the time dependence of underlying time series. Compared to manual feature extraction that relies on prior knowledge, the proposed model can learn more effective data features. The effectiveness of the method has been demonstrated through empirical data experiments, which is beneficial for corporates in the context of double carbon emissions, providing a method for regulating corporate ecological indicators.

Challenges and responses of China’s energy legal system under the double carbon target

The deep-seated problem of carbon neutrality is the energy problem, and the change in energy consumption structure determines the degree of achieving China’s double carbon target. The basic path to achieve the dual carbon goal is to realize the rule of law in energy governance, and the premise of the rule of law in energy governance is to establish a perfect energy legal system. In this paper, we use literary analysis to understand the current research status of this topic, normative and empirical analysis to understand the current legal norms and their implementation status of the implementation of the dual carbon goal in China, and comparative analysis to understand the construction status of the energy legal system of each country in achieving the dual carbon goal. In China, there are also problems such as the dilemma of energy law structure, the lack of dual-carbon legislative goals, the lack of basic framework laws, and the disconnection between energy laws and energy policies, etc. To remedy these dilemmas and shortcomings, the path of constructing a perfect energy law and regulation system is to: establish a Chinese energy development plan with dual-carbon goals; to formulate a basic energy law to lay the framework of China’s energy legal system; to establish the concepts and principles of energy legislation as the basis for maintaining a coordinated and unified energy legal system and so on.

Study of linear shaped charge (LSC) jet penetrating layered targets

This paper presents the results of an experimental and numerical study conducted to investigate the mechanism of penetration of linear shaped charges (LSCs) into double layered targets. A type of LSC causing less collateral damage in terms of jet residues was studied. The LSC consisted of a linear liner and case with the depth to diameter aspect ratio of 2.0. Anti-theft doors and spaced steel plates were used to represent double layered targets. The anti-theft door and the equivalent targets were penetrated with little jet residues behind the exit crater. The experiments were simulated using the commercially available software AutoDYN as a 2-D planer symmetry FEM model of the LSC penetrating a double layered target. An Eulerian mesh was used to model the LSCs whilst the double layered target was modelled using a Lagrangian mesh. A fully coupled algorithm was used for two different meshes. The data from the experiments (the shape of the breach and jet residues) were used to validate the numerical model. The validated numerical model was used to gain insights into the penetrating mechanisms of the LSC. The numerical results indicated that the penetration mechanisms of the two layers target were different. The first layer was penetrated by a continuous jet typical of a high-speed jet whereas the second layer was perforated by both a jet tip and slug characterized by a low-impact velocity projectile (slug).

How to Improve Industrial Green Total Factor Productivity under Dual Carbon Goals? Evidence from China

This paper focuses on the relationship between green credit and industrial green total factor productivity under the dual carbon target. In recent years, weather extremes that break historical extremes have occurred frequently around the world, and the resulting loss of life and property has deepened people’s concern about climate change. As a responsible developing country, China has set the goal of reaching peak carbon emissions and reducing carbon intensity by 60–65% by 2030. In this context, based on China’s provincial-level data from 2006 to 2019, this paper first measures the growth rate of industrial green total factor productivity using the SBM-ML model, and then analyzes the impact of green credit on industrial green total factor productivity under the double carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We then analyze the impact of green credit on industrial green total factor productivity under the dual carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We find that green credit can improve the energy consumption structure and thus increase industrial green total factor productivity. In addition, the study finds that the interaction effect of green credit and environmental regulation suppresses the positive impact of green credit on industrial green TFP. This paper provides empirical evidence and policy implications for the orderly promotion of carbon peaking and carbon neutral efforts to effectively improve industrial green total factor productivity and promote high-quality economic development.

Scalable neural quantum states architecture for quantum chemistry

Variational optimization of neural-network representations of quantum states has been successfully applied to solve interacting fermionic problems. Despite rapid developments, significant scalability challenges arise when considering molecules of large scale, which correspond to non-locally interacting quantum spin Hamiltonians consisting of sums of thousands or even millions of Pauli operators. In this work, we introduce scalable parallelization strategies to improve neural-network-based variational quantum Monte Carlo calculations for ab-initio quantum chemistry applications. We establish GPU-supported local energy parallelism to compute the optimization objective for Hamiltonians of potentially complex molecules. Using autoregressive sampling techniques, we demonstrate systematic improvement in wall-clock timings required to achieve coupled cluster with up to double excitations baseline target energies. The performance is further enhanced by accommodating the structure of resultant spin Hamiltonians into the autoregressive sampling ordering. The algorithm achieves promising performance in comparison with the classical approximate methods and exhibits both running time and scalability advantages over existing neural-network based methods.

High-speed impact performance of a high-performance concrete with functionally gradient structure designs

Ultra-high performance concrete is characterized by its high strength and high toughness, and ceramsite concrete can absorb energy and function as a buffer. Based on the mechanical properties of both, the two kinds of concrete materials are combined in the spatial structure, and three structural models, namely, gradient structure group target, double stacked structure group target, and single material structure group target, are designed and prepared. Then, the dynamic characteristics and protection performance of the three targets are compared and analyzed via experiments and numerical simulations under different projectile penetration velocities. The results show that because the two transition layers and the fiber layer between the interfaces are set in the gradient structure group target, which largely improves the resistance in the process of projectile penetration, the cratering area, cratering depth, and penetration depth of the gradient structure group target are the smallest under the same projectile penetration velocity. The larger the projectile penetration velocity is, the more outstanding the penetration resistance of the gradient structure group target is.

Adeno-Associated Virus-Mediated Immunotherapy Based on Bispecific Tandem scFv for Alzheimer's Disease.

Patients with Alzheimer's disease (AD) have considerably increased globally as a result of population aging, placing a significant burden on the global economy and the medical system. The outcome of clinical trials for AD immunotherapy that solely targeted amyloid-β (Aβ) or phosphorylated tau protein (p-Tau) was unsatisfactory. Therefore, blocking both Aβ and p-Tau's pathological processes simultaneously while also preventing their interaction may be the key to developing an effective AD therapy. To develop a novel immunotherapy based on bispecific tandem scFv (TaFv) against AD. Bispecific single-chain antibody that targets both Aβ and p-Tau were obtained using E. coli expression system. Biological ability of TaFvs were determined by ELISA, SDS-PAGE, and immunohistochemical assay. Recombinant adeno-associated virus 9 (rAAV9) were packaged to create TaFv. The in vivo activity of rAAV9 were detected in mouse, using biophotonic imaging and frozen section methods. The outcomes demonstrated that both Aβ and p-Tau had a high affinity for the bispecific TaFv. Additionally, it can bind to the amyloid plaques and neuronal tangles in the brain slices of an AD mouse model. Moreover, the rAAV9 could infect neuronal cells, transverse the blood-brain barrier, and express TaFv in the mouse brain. This novel immunotherapy offers a fresh concept for the immunotherapy of AD and successfully delivers the double target antibody into the brain, acting on both pathogenic substances Aβ and p-Tau.

FORECAST OF RENEWABLE ENERGY GENERATION TREND IN CHINA

Developing and utilizing renewable energy have become a common choice for all countries to ensure energy security, cope with climate change, and achieve sustainable development. Based on the data released in the Statistical Yearbook of China 2021, this paper predicts the data trends of two indicators, installed renewable energy capacity and total electricity consumption, from 2021 to 2030 by using the grey prediction model. According to the forecast results, by 2030, China's renewable energy installed capacity will reach 19,4674 GW, and power generation will be 42,261 billion kW, while the total electricity consumption in China will rise up to 12,738.3 billion kWh. This shows that China will still be unable to achieve its nationwide carbon neutrality goal by 2030. There is still a long way to go to accomplish the whole society's electricity consumption by relying entirely on renewable energy generation, but it has a substantial reference value for China's double carbon target. The recommendations of the research include: continuous increase in the renewable energy installed capacity in the whole society; accelerating energy transformation; strengthening research on renewable energy technology and the environment; establishing a renewable energy data platform; enrichment of the research methods and models for renewable energy development.

Study on the initial carbon quota allocation and spatial balance compensation strategy at the provincial level in China

With the official national unified carbon market launch on July 16, 2021, the allocation and trading of initial carbon quotas between regions will become the focus of research in the future. Based on a reasonable regional initial carbon quota allocation, introducing the concept of carbon ecological compensation and formulating differentiated emission reduction strategies according to the characteristics of different provinces can better guarantee the realization of China's carbon emission reduction goals. Based on this, this paper first analyzes the distribution effects under different distribution principles from the perspective of fairness and efficiency. Secondly, the Pareto optimal multi-objective particle swarm optimization (Pareto-MOPSO) algorithm is used to build the initial carbon quota allocation optimization configuration model to optimize the allocation results. The optimal initial carbon quota allocation scheme is determined through the comparative analysis of the allocation results. Finally, we explore the combination of carbon quota allocation and the concept of carbon ecological compensation and formulate the corresponding carbon compensation scheme. This study not only reduces the relative sense of exploitation of carbon quota allocation in different provinces but also contributes to the realization of a carbon peak in 2030 and carbon neutrality in 2060 (the "30.60" double carbon target).

Closing the compliance gap in marine protected areas with human behavioural sciences

AbstractAdvocates, practitioners and policy‐makers continue to use and advocate for marine protected areas (MPAs) to meet global ocean protection targets. Yet many of the worlds MPAs, and especially no‐take MPAs, are plagued by poaching and ineffective governance. Using a global dataset on coral reefs as an example, we quantify the potential ecological gains of governing MPAs to increase compliance, which we call the ‘compliance gap’. Using ecological simulations based on model posteriors of joint Bayesian hierarchical models, we demonstrate how increased compliance in no‐take MPAs could nearly double target fish biomass (91% increases in median fish biomass), and result in a 292% higher likelihood of encountering top predators. Achieving these gains and closing the compliance gap necessitates a substantial shift in approach and practice to go beyond optimizing enforcement, and towards governing for compliance. This will require engaging and integrating a broad suite of actors, principles, and practices across three key domains: (i)) harnessing social influence, (ii) integrating equity principles, and (iii) aligning incentives through market‐based instruments. Empowering and shaping communication between actor groups (e.g., between fishers, practitioners, and policy‐makers) using theoretically underpinned approaches from the behavioural sciences is one of the most essential, but often underserved aspects of governing MPAs. We therefore close by highlighting how this cross‐cutting tool could be further integrated in governance to bolster high levels of compliance in MPAs.

Fluorescent deactivation behaviors based on ESIPT and TICT of novel double target fluorescent probe and its sensing mechanism for Al3+/Mg2+: A TD-DFT study

Based on density functional theory (DFT) and time-dependent DFT (TD-DFT) methods with integral equation formula polarized continuum model (IEFPCM), the fluorescent behavior and recognizing mechanism of probe N'-((1-hydroxynaphthalen-2-yl)methylene)isoquinoline-3-carbohydrazide (NHMI) for Al3+/Mg2+ ion were investigated in more detail. Excited state intramolecular proton transfer (ESIPT) process in probe NHMI occurs in the stepwise pattern. The proton H5 of enol structure (E1) firstly moves from O4 to N6 to form single proton-transfer (SPT2) structure, and then the proton H2 of SPT2 transfers from N1 to N3 to form the stable double proton-transfer (DPT) structure. Subsequently, the transformation from DPT to its isomer (DPT1) induces the twisted intramolecular charge transfer (TICT) process. Two non-emissive TICT states (TICT1 and TICT2) were obtained, and TICT2 state quenches the fluorescence observed in the experiment. With the addition of aluminum (Al3+) or magnesium (Mg2+) ion, TICT process is prohibited by the coordination interaction between NHMI and Al3+/Mg2+, and the strong fluorescent signal is turned on. For probe NHMI, the twisted C-N single bond of acylhydrazone part leads to the TICT state. This sensing mechanism may inspire researchers to develop new probes from a different direction.

Tracking analysis of viral nucleic acid Ct value in patients with re-positive SARS-CoV-2 infection

To track analysis of viral nucleic acid test results in patients with re-positive SARS-CoV-2 infection, and provide clinical reference for nucleic acid test of re-positive cases. A retrospective study was conducted. The multiple nucleic acid results of 96 cases with SARS-CoV-2 infection tested by medical laboratory of Shenzhen Luohu Hospital Group from January to September in 2022 were analyzed. The test dates and cycle threshold (Ct) values of detectable positive virus nucleic acid in the 96 cases were summarized and analyzed. A total of 96 patients with SARS-CoV-2 infection were retested re-sampled for nucleic acid testing at least 12 days after the initial positive screening. Among them, 54 cases (56.25%) had Ct value of < 35 for nucleocapsid protein gene (N) and/or open reading frame 1ab gene (ORF 1ab), 42 cases (43.75%) had Ct value ≥ 35. In the re-sampling of infected patients, N gene titers were 25.08 to 39.98 Ct cycles, and ORF 1ab gene titers were 23.16 to 39.56 Ct cycles. Compared with the positive results of the initial screening, the Ct values of N gene and/or ORF 1ab gene positive were increased in 90 cases (93.75%). Among them, the patients with the longest duration of nucleic acid positive could still be positive for double targets (the Ct value of N gene was 38.60, and the Ct value of ORF 1ab gene was 38.11) at an interval of 178 days after the initial positive screening. Patients infected with SARS-CoV-2 can be sustained or repeatedly tested positive for nucleic acid for a long period of time, and most of them had Ct values < 35. But whether it is infectious needs to be comprehensively evaluated by combining epidemiology, variant type, samples with the alive virus, and clinical symptoms and signs.

Microseismic Monitoring Technology Developments and Prospects in CCUS Injection Engineering

CO2 geological storage projects are an essential tool for China to achieve the double carbon target of energy savings and emission reductions. In order to safely and effectively control the implementation of injection projects and monitor the dynamics of CO2 injection, multi-dimensional and multi-disciplinary monitoring tools are required. Among them, microseismic monitoring is a key technology for predicting reservoir dynamics and reflecting reservoir geomechanical behavior. Such monitoring has been carried out previously for reservoirs in other countries, but experimental projects are also gradually being developed in China. In this paper, we focus on the research and analysis results of microseismic monitoring of carbon storage projects in various work areas. For different reservoir conditions, we explore combinations of the monitoring implementation methods in China, comparing the differences in each work area. We propose a joint well and ground microseismic monitoring method and a multi-spatial and multi-physical field coupling research system for use in the implementation of domestic demo projects for the future research and development of microseismic monitoring of carbon storage projects. The monitoring program can meet the requirements for certain periodic repeated or continuous observations and can intelligently assess the risk and handle the alert behavior. The foundation is laid for the development of the future microseismic monitoring technology to achieve the goal of developing cost-controllable, permanent, and real-time monitoring equipment. The application of the monitoring system in China has been effective, and this experience can contribute to the development of injection engineering in the future.

Evaluation and Promotion Mechanism of Urban Energy Internet Development under Double Carbon Target

Under the "double carbon" strategy, as the main source of carbon dioxide emissions, the energy industry is the main force in carbon reduction, and cities which are the main energy consumers are the main battleground. Thoroughly implementing the new development concept, building a clean, low-carbon, safe and reliable, intelligent and open energy network, and building a modern intelligent energy system are the key to realizing the low-carbon transformation of the national energy industry. This paper analyzes the requirements of energy Internet development and the shortcomings of energy Internet development based on the necessity of energy Internet development in China, constructs a development evaluation index system, and proposes the development mechanism and policy recommendations of urban energy Internet under the background of "double carbon".

Characteristics of Multi-Stage Auxiliary Equipment Linkage in Pumped Storage Power Station Under Double Carbon Target

The auxiliary control linkage system of the pumped storage power station has become a necessary technical means for the safe operation and production of the station. However, due to the scattered linkage control function and low control level of each subsystem of the pumped storage power station, the security system cannot play a full role, affecting the safety portion and other effects. This paper studies a multistage auxiliary equipment linkage method based on a linkage body for the pumped storage power station. In the framework of the system dividing safety intervals, five linkage bodies are constructed for multi-layer hierarchical linkage, including real-time monitoring, fire fighting, five-prevention locking, online monitoring, and video monitoring. Completing the development of the linkage method of auxiliary equipment comprehensive control based on a multi-level linkage strategy and implementing multi-stage auxiliary equipment linkage in the station can reduce the loss of auxiliary equipment in pumped storage stations and improve the carbon neutrality and carbon compliance benefit of the pumped storage stations.

Nonlinear evolution of the Weibel instability with relativistic laser pulses

The Weibel instability is investigated using relativistic intense short laser pulses. A relativistic short laser pulse can generate a sub-relativistic high-density collisionless plasma. By irradiating double parallel planar targets with two relativistic laser pulses, sub-relativistic collisionless counterstreaming plasmas are created. Since the growth rate of the Weibel instability is proportional to the plasma density and velocity, the spatial and temporal scales of the Weibel instability can be much smaller than that from nanosecond large laser facilities. Recent theoretical and numerical studies have revealed that astrophysical collisionless shocks in sub-relativistic regimes in the absence and presence of an ambient magnetic field play essential roles in cosmic ray acceleration. With experimental verification in mind, we discuss the possible experimental models on the Weibel instability with intense short laser pulses. In order to show the experimental feasibility, we perform 2D particle-in-cell simulations in the absence of an external magnetic field as the first step and discuss the optimum conditions to realize the nonlinear evolutions of the Weibel instability in laboratories.

Coordinated carbon reduction mechanism and policy design to achieve carbon peak and neutrality goals in the Yangtze River Delta

Carbon emissions reduction has become a major issue in global development. China has adopted various carbon reduction policies since committing to the double carbon target and now requires an effective and systematic collaborative carbon reduction mechanism. The Yangtze River Delta, a developed region in China, is a suitable pilot city for developing such a mechanism. In this study, carbon emissions from the Yangtze River Delta region were analyzed and the pressures to and potential of carbon emissions reduction were summarized. By dialectically analyzing the characteristics of each emissions reduction policy, we proposed the implementation of carbon tax policies. We designed a set of emissions reduction policies suitable for the current Yangtze River Delta region with other mechanisms that promote energy transformation and industrial upgrades and provided ideas for implementing carbon emissions reduction policies nationwide. The design of the carbon tax policy emphasizes collaboration with the carbon trading policy and promotes energy structure transformation and process upgrades to the entire industry. The carbon tax also emphasizes that tax revenue control should have a guiding role. The government should encourage enterprises to actively improve green technology and adjust the energy structure through the rational use of carbon tax revenues.

Exploring the impact of “double carbon target” on environmental efficiency of coal cities in China

Chinese government proposed the “Double Carbon Target” (DCT) in 2020 to deal with the increasing global warming crisis. In this regard, the study identifies temporal and spatial evolution characteristics of environmental efficiency through the DEA-SBM model and further explores the impact of DCT on the environmental efficiency of coal cities using scenario analysis method. Empirical results show that: 1) Both economic efficiency and environmental efficiency of China’s coal cities are first rising and then falling during the period 2003–2022, and the gap between coal cities and non-coal cities was very small before 2011, but it begins to be enlarged after 2011. The main reason is environmental regulation has exerted a significant impact on coal cities; 2) the difference in environmental efficiency among coal cities is huge due to their policies for supporting renewable energy. Some cities have broken carbon lock-in by the favorite policy for renewable energy, while others have been trapped into path dependence on the coal-related industry; 3) generally, the more amount of emission reduction required, the lower the environmental efficiency of coal cities in the carbon neutralization scenario. Furthermore, some cities rich of renewable energy resources, such as Erdos, and Xuzhou, still have better environmental performance under different carbon neutralization scenarios, while others will encounter many transformation barriers and even may cause a social crisis. Therefore, it is suggested that some coal cities in northwest China can vigorously develop solar energy to improve environmental efficiency.

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with “G4” Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.