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The hypothesis underlying the abiogenic origin of life suggests that the nonenzymatic synthesis of long-chain fatty acids led to the construction of vesicles for compartmentalization in an early stage during the transition from geochemistry to biochemistry. However, evidence for this theory remains elusive as C5+ carboxylic acids cannot be synthesized using current laboratory simulations. Here, we report the synthesis of long-chain carboxylic acids (C3-C7) with a 42 mmol/gCo+Ni yield and 87.7% selectivity from formate (an intermediate of the acetyl-CoA pathway) over a cobalt-nickel alloy under alkaline hydrothermal conditions and the subsequent formation of microdroplets from organics. Density functional theory (DFT) calculations confirmed that the synergistic effect of the bimetal catalyst is key for catalyzing C-C coupling. Investigations by infrared spectroscopy, electron paramagnetic resonance, and isotope-labeled experiments revealed that HCO* serves as a reaction intermediate and is involved in the subsequent elementary steps for synthesizing long-chain carboxylic acids from formate. Taken together, these findings may help explain how the first protocells emerged geochemically and provide support for the hypothesis of the abiogenic origin of life. The hydrothermal system developed may also be applicable for the sustainable synthesis of long-chain carboxylates from one-carbon substrates using nonnoble metal catalysts.
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Promoting the Curie temperature (T C) and tunning the magnetocrystalline anisotropy energy (MAE) have been key issues with two-dimensional (2D) ferromagnetic (FM) materials. Here, the structural and magnetic properties of MnTe2/X (X = As, Sb and Bi) heterostructures are investigated through first-principles calculations. We reveal that monolayer MnTe2 weakly interacts with monolayer As or Sb through van der Waals (vdW) forces, but has strong covalent bonds with monolayer Bi, indicated by Bi-Te bond formation. The coupling of MnTe2 with these ß-phase group-VA semiconductor monolayers substantially modulates MAE, with MnTe2/As showing a shift to in-plane easy magnetization, and MnTe2/Sb exhibiting a large perpendicular MAE of 4.13 meV per cell. The formation of vdW heterostructures influence on Te spin-orbit coupling matrix elements markedly governs MAE. MnTe2/Bi also has an in-plane MAE, contributed by both Te and Bi atoms. Additionally, coupling MnTe2 with X significantly affects magnetic interactions. It is worth noting that the T C of MnTe2/Sb reaches 233.2 K, significantly larger than that of pure MnTe2. A large perpendicular MAE and a heightened T C makes MnTe2/Sb desired candidates for next-generation spintronic applications. Our work provides a way to modulate the magnetic properties of 2D FM materials.
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Combining terrestrial biomass as the reductant with submarine-type hydrothermal environments for CO2 reduction represents a possible approach for novel energy production systems that sustainably circulate carbon. However, increasing the reductive power of biomass is the main limitation of this potential method. Herein, we demonstrate that Co-doped with small amounts of Pd enhances the reduction of CO2 by selectively producing an active intermediate from carbohydrates. This catalytic reaction utilized glucose as a reductant to achieve high formate production efficiency (458.6 g kg-1) with nearly 100% selectivity with 7.5 wt% Pd1Co20/γ-Al2O3 at a moderate temperature of 225 °C. The regulation of the electronic structure of the catalytic Co surface by the dopant Pd plays a key role in promoting the C-C bond cleavage of glucose and hydrogen transfer for CO2 reduction. The findings presented here indicate that biomass can serve as the hydrogen source for CO2 reduction and provide insight into the potential utilization of CO2 in sustainable industrial applications.
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Efficient conversion of C1 molecules into multicarbon oxygenates is a promising avenue for energy storage. Herein, we synthesize adjustable alkanoic acids/alcohols from formate C1 molecules via a hydrothermal reaction without any metal catalyst participation. This is achieved via HCO* and HCOO- nonsymmetric C-C coupling by alkali catalysis in aqueous medium.
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A large-scale Cyber-Physical System (CPS) such as a smart grid usually provides service to a vast number of users as a public utility. Security is one of the most vital aspects in such critical infrastructures. The existing CPS security usually considers the attack from the information domain to the physical domain, such as injecting false data to damage sensing. Social Collective Attack on CPS (SCAC) is proposed as a new kind of attack that intrudes into the social domain and manipulates the collective behavior of social users to disrupt the physical subsystem. To provide a systematic description framework for such threats, we extend MITRE ATT&CK, the most used cyber adversary behavior modeling framework, to cover social, cyber, and physical domains. We discuss how the disinformation may be constructed and eventually leads to physical system malfunction through the social-cyber-physical interfaces, and we analyze how the adversaries launch disinformation attacks to better manipulate collective behavior. Finally, simulation analysis of SCAC in a smart grid is provided to demonstrate the possibility of such an attack.
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This paper presents a piezoelectric (PE) energy harvesting circuit, which integrates a Synchronized Switch Harvesting on Inductor (SSHI) circuit and a diode bridge rectifier. A typical SSHI circuit cannot transfer the power from a PE cantilever into the load when the rectified voltage is higher than a certain voltage. The proposed circuit addresses this problem. It uses the two resonant loops for flipping the capacitor voltage and energy transfer in each half cycle. One resonant loop is typically used for the parallel SSHI scheme, and the other for the series SSHI scheme. The hybrid SSHI circuit using the two resonant loops enables the proposed circuit's output voltage to no longer be limited. The circuit is self-powered and has the capability of starting without the help of an external battery. Eleven simple discrete components prototyped the circuit. The experimental results show that, compared with the full-bridge (FB) circuit, the amount of power harvested from a PE cantilever and the Voltage Range of Interest (VRI) of the proposed circuit is increased by 2.9 times and by 4.4 times, respectively. A power conversion efficiency of 83.2% is achieved.
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Weak reflected signal is one of the main problems in a recent developing remote sensing tool-passive GNSS-based radar (GNSS radar). To address this issue, an enhanced GNSS radar imaging scheme on the basis of coherently integrating multiple satellites is proposed. In the proposed scheme, to avoid direct signal interference at surveillance antenna, the satellites that used as transmission of opportunity are in backscattering geometry model. To coherently accumulate echo signal magnitudes of the scene center in the targeted sensing region illuminated by the selected satellites, after performing the paralleled range compressions, a coordinates alignment operator is performed to the respective range domains, in which, pseudorandom noise (PRN) code phases are aligned. Thereafter, the coordinates aligned range compressed signals of the selected satellites are coherently integrated along azimuth domain so that imaging gain is improved and azimuth processing can be accomplished in only one state operation. The theoretical analysis and field proof-of-concept experimental results indicate that compared to both conventional bistatic imaging scheme and the state-of-the-art multi-image fusion scheme, the proposed scheme can provide a higher imaging gain; compared to the state-of-the-art multi-image fusion scheme, the proposed scheme has a less computational complexity and faster algorithm speed.
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The constraints on directions of incoming and outgoing rays of Risley prisms, caused by total internal reflection and surface tilt, are investigated for the four typical configurations. After applying a nonparaxial ray-tracing method based on the vector form Snell's law, the incident angles at prisms' surfaces are calculated and compared with the critical angle. On this basis, the direction limitations of incoming and outgoing rays are investigated. The permissible incoming directions as well as the achievable outgoing directions depend on prisms' orientation. Their ranges over which the rays can pass through the system at any prism orientation are defined as the angular aperture and angular field of view (FOV). The effects of the prisms' refractive index, opening angle, and arrangement on angular aperture/FOV are discussed. It is shown that there exists a direct trade-off between the deviation power and the angular aperture/FOV for Risley prisms, that is, high refractive index and large opening angle yield a smaller angle aperture/FOV. Large angular aperture can be achieved by employing the 2121 configuration, while it is desirable to adopt a 1212 configuration to obtain large angular FOV. The research can afford guidance for prism material, geometry choices, and configuration setting in the design of a Risley prism system for wide-angle beam steering or imaging adjustment.
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Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes. Additionally, the power flow of the power grid can cause the load of a failed node to be allocated to its neighboring nodes and trigger a new round of load distribution when the load of these nodes exceeds their capacity. This means that the robustness of smart grids may be affected by four factors, i.e., load redistribution, local coupling, dual coupling link and coupling mode; however, the research on the influence of those factors on the network robustness is missing. In this paper, firstly, we construct the smart grid as a two-layer network with a dual coupling link and divide the power grid and communication network into many subnets based on the geographical location of their nodes. Secondly, we define node importance ( N I ) as an evaluation index to access the impact of nodes on the cyber or physical network and propose three types of coupling modes based on N I of nodes in the cyber and physical subnets, i.e., Assortative Coupling in Subnets (ACIS), Disassortative Coupling in Subnets (DCIS), and Random Coupling in Subnets (RCIS). Thirdly, a cascading failure model is proposed for studying the effect of local coupling of dual coupling link in combination with ACIS, DCIS, and RCIS on the robustness of the smart grid against a targeted attack, and the survival rate of functional nodes is used to assess the robustness of the smart grid. Finally, we use the IEEE 118-Bus System and the Italian High-Voltage Electrical Transmission Network to verify our model and obtain the same conclusions: (I) DCIS applied to the top-down coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or ACIS, (II) ACIS applied to a bottom-up coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or DCIS, and (III) the robustness of the smart grid can be improved by increasing the tolerance α . This paper provides some guidelines for slowing down the speed of the cascading failures in the design of architecture and optimization of interdependent networks, such as a top-down link with DCIS, a bottom-up link with ACIS, and an increased tolerance α .
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The near-repeat effect is a well-known phenomenon in crime analysis. The classic research methods focus on two aspects. One is the geographical factor, which indicates the influence of a certain crime risk on other similar crime incidents in nearby places. The other is the social network, which demonstrates the contacts of the offenders and explain "near" as degrees instead of geographic distances. In our work, these coarse-grained patterns discovering methods are summarized as bundled-clues techniques. In this paper, we propose a knotted-clues method. Adopting a data science perspective, we make use of a data interpretative technology and discover that the near-repeat effect is not always so near in geographic or network structure. With this approach, we analyze the near-repeat patterns in all districts of the dataset, as well as in different crime types. Using open source data from Crimes in Chicago provided by Chicago Police Department, we find interesting relationships and patterns with our mining method, which have a positive effect on police deployment and decision making.
Assuntos
Crime/estatística & dados numéricos , Mineração de Dados/métodos , Chicago , Análise por Conglomerados , Comportamento Criminoso , Interpretação Estatística de Dados , Conjuntos de Dados como Assunto , Humanos , RiscoRESUMO
A cyber-physical attack in the industrial Internet of Things can cause severe damage to physical system. In this paper, we focus on the command disaggregation attack, wherein attackers modify disaggregated commands by intruding command aggregators like programmable logic controllers, and then maliciously manipulate the physical process. It is necessary to investigate these attacks, analyze their impact on the physical process, and seek effective detection mechanisms. We depict two different types of command disaggregation attack modes: (1) the command sequence is disordered and (2) disaggregated sub-commands are allocated to wrong actuators. We describe three attack models to implement these modes with going undetected by existing detection methods. A novel and effective framework is provided to detect command disaggregation attacks. The framework utilizes the correlations among two-tier command sequences, including commands from the output of central controller and sub-commands from the input of actuators, to detect attacks before disruptions occur. We have designed components of the framework and explain how to mine and use these correlations to detect attacks. We present two case studies to validate different levels of impact from various attack models and the effectiveness of the detection framework. Finally, we discuss how to enhance the detection framework.