Abstract With the widespread application of genetically modified (GM) technology, the safety and traceability of derived edible oils from GM oilseed crops and their oil products have raised significant public concerns. However, the advancement of GM identification methods for oil products remains constrained by the absence of convenient and reliable extraction methods. This review first categorizes components that are commonly selected for GM identification into DNA, proteins, and fatty acids, and then critically evaluates the principles, advantages, and limitations of core methodologies, including classical and silica/magnetic bead-based nucleic acid extraction, protein precipitation strategies, and fatty acid separation techniques. Furthermore, emerging alternative solutions, including functionalized nanoparticles and ionic liquid-based aqueous biphasic systems, are highlighted as potential strategies to address the challenges associated with low yield and analyte degradation. We also propose cross-disciplinary insights from forensic and archeometric trace analysis, as well as the application of microfluidic devices, which could further enhance the performance of existing GM identification methods. This review not only synthesizes current technological landscapes but also presents a pathway for next-generation pre-treatment protocols, aiming to support accurate, sensitive, and practical GM oil authentication in both regulatory and commercial settings.

The pursuit of alloys that integrate high strength and substantial plasticity persists across various industries. Nevertheless, alloys engineered for elevated strength commonly manifest unsustainable work hardening, ultimately leading to a decline in plasticity. Dual-or even multi-phase systems offer vast potential for novel microstructural engineering aimed at harmonizing these inversely related property requirements. Here, heterogeneous lamellar structure consisting of alternating austenite and ferrite lamellae is explored to decouple and leverage the distinct roles of individual phases in a dual-phase system. This phase-specific tailoring strategy meticulously manipulates intra-phase microstructure, and tunes the lamella thickness to promote both high initial strength and prolonged work hardening. The significantly enhanced strength benefits from pre-existing defects, interfaces strengthening and quasi isostrain deformation mode while high plasticity originates from relatively uniform strain partitioning between phases across a wide strain range achieved through exploiting various hardening components. For austenite, prolonged work hardening is achieved by sequential utilization of dislocation hardening followed by martensitic transformation hardening. Moreover, the martensite laths in favorable configuration along with the retained austenite contribute to retarding cracking. For ferrite, wide-range work hardening is ensured by expanding the potential for dislocation activities which lowers initial density and raises peak density through reducing the space in the thickness dimension. Such innovation elevates the traditionally inferior work-hardening capability of high-strength BCC structure to an exceptional level. The resultant alloy, while boosting nearly twice the yield strength of its conventional counterpart, exhibits a total elongation of 45 %. This strategy holds potential for broad application across dual-and multi-phase systems and proposes a new avenue for enhancing plasticity in high-strength lamellar-structured alloys.

Amorphous solids exhibit scale-free avalanches, even under small external loading, and thus can work as suitable systems to study critical behavior and universality classes. The abundance of scale-free avalanches in the entire elastic tension regime of bulk metallic glass (BMG) samples has been experimentally observed using acoustic emission (AE) measurements. In this work, we compare the statistics of avalanches with those of earthquakes, and find that they both follow the Gutenberg-Richter law in the statistics of energies and Omori's law of aftershock rates, and share the same characteristics in the distribution of recurrence times. These resemblances encourage us to propose the term "glass-quake" to describe avalanches in elastically loaded BMGs. Furthermore, our work echoes the potential universality of critical behavior in disordered physical systems from atomic to planetary scales, and motivates the use of elastic loaded BMGs as valuable laboratory simulators of seismic dynamics.

Geometrically necessary dislocations (GNDs) play a pivotal role in polycrystalline plastic deformation, with their characteristics notably affected by strain rate and other factors, but the underlying mechanisms are not well understood yet. We investigate GND characteristics in pure copper polycrystals subjected to tensile deformation at varying strain rates (0.001 s−1, 800 s−1, 1500 s−1, 2500 s−1). EBSD analysis reveals a non-linear increase in global GND density with the strain rate rising, and a similar trend is also observed for local GND densities near the grain boundaries and that in the grain interiors. Furthermore, GND density decreases from the grain boundaries towards the grain interiors and this decline slows down at high strain rates. The origin of these trends is revealed by the connections between the GND characteristics and the behaviors of relevant microstructural components. The increase in grain boundary misorientations at higher strain rates promotes the increase of GND density near the grain boundaries. The denser distribution of dislocation cells, observed previously at high strain rates, is presumed to increase the GND density in the grain interiors and may also contribute to the slower decline in GND density near the grain boundaries. Additionally, grain refinement by higher strain rates also promotes the increase in total GND density. Further, the non-linear variation with respect to the strain rate, as well as the saturation at high strain rates, for grain boundary misorientations and grain sizes align well with the non-linear trend of GND density, consolidating the intimate connections between the characteristics of GNDs and the behaviors of these microstructure components.

Restrained by the strength-ductility tradeoff, it is still challenging to develop advanced high-strength low carbon low alloy (LCLA) steels with superior strength-ductility combinations and cost-effectiveness to satisfy industry demands. In this study, an innovative 2-cyclic quenching and partitioning (Q&P) heat treatment was developed to produce a novel LCLA steel with the optimized microstructure, in which a bimodal grain size distribution across various constituent phases was achieved. Tensile test results show that the 2-cyclic Q&P LCLA steel exhibits excellent mechanical properties with a uniform elongation, close to 18%, nearly triple that of conventional Q&P LCLA steel while maintaining a tensile strength above 1 GPa. To reveal the underlying mechanisms of such exceptional strength-elongation synergy, the detailed deformation behaviors of the developed LCLA steel were characterized while the evolution of hetero-deformation-induced (HDI) stress and effective stress was investigated from the perspective of the dislocation model. It is indicated that, with increasing strain, the heterogeneous structures promote strong strain partitioning which leads to extensive geometrically necessary dislocations (GNDs) pile-ups at hetero-interface and persistently strong HDI strengthening effect, and produce the coordinated deformation among constituent phases to realize dislocation forest strengthening, collectively contributing to the enhanced work hardening capacity and hence overcoming the strength-ductility tradeoff. This study provides a new processing strategy for developing strong and ductile LCLA steels.

In this study, the refinement of two microstructures was controlled in medium carbon 25Cr2Ni3MoV steel via multi-step tempering and partition (MTP) to achieve high cryogenic strength–ductility combinations. Microstructure evolution, the distribution of stress concentration, and microcrack formation and propagation during cryogenic Charpy impact testing were investigated. Compared with their performance in the quenching and tempering states (QT), the MTP steels showed a significant improvement in yield strength (1300 MPa), total elongation (25%), and impact toughness (>25 J) at liquid nitrogen temperature (LNT). The strengthening contributions mainly originated from the high dislocation density and refinement cementite (size: 70 nm) in the martensite lath (width: 1.5 μm) introduced by refined reversed austenite and its latter decomposition. The instrumented Charpy impact results indicated that cracks nucleated in the primary austenite grain (PAG) boundary for two steels due to the strain concentration band preferring to appear near PAGs, while cracks in the QT and MTP samples propagated along the PAGs and high-angle grain boundary (HAGB), respectively. The crystallized plasticity finite element simulation revealed that the PAG boundary with cementite precipitates of large size (>200 nm) was less able to dissipate crack propagation energy than the HAGBs by continuously forming a high strain concentration area, thus leading to the low-impact toughness of the QT steel.

Strain gradient plasticity theory addresses the plastic strain gradient induced hardening by considering the internal stress and Taylor hardening associated with the geometrically necessary dislocations (GNDs). However, the continuum description of internal stress associated with GNDs is inaccurate due to the coarsening of discrete dislocations. Corrections are thus derived as the difference between the stresses produced by the continuous configuration and the discrete configuration. We further demonstrate the capability of this correction in effectively capturing the internal stress induced strengthening effect associated with GNDs, and elucidate that its role in strengthening is to homogenize the deformation and extend the influence of grain boundaries into the interior of grains within polycrystals. This capability to capture intragranular slip distribution is validated through the simulation of a polycrystalline tensile experiment. This work explains the limitations of classical crystal plasticity theory under high strain gradients and offers a straightforward yet robust slip discreteness correction to crystal plasticity with transparent input from dislocation theory, opening a new perspective for the connections between continuum crystal plasticity theory and dislocation theory.

With the rapid development of the electricity market, businesses such as market regulation and market dispute resolution are facing significant challenges. The reliable storage of business data is the key foundation for solving these problems, blockchain technology provides us with new idea. In this paper, we comprehensively considered the characteristics of both electricity market and blockchain technology, then designed the Electricity Market Alliance Chain and implemented a blockchain-based data storage system for electricity market. The system achieved more than 1.3 million market data on-chain storage, and realized the full life cycle traceability mechanism of transaction and settlement business. Based on the data on the blockchain, Green Electricity Usage Certificates are generated and issued for market members by smart contracts, which provide an important reference for carbon emission verification in a transparent way. At last, we designed a set of experiments to test the performance of the system, and the results prove that it can fully meet performance requirements.

Benefiting from the popularization of 6G and loT, blockchain-based collaborative sensing of power trading has received extensive attention from academia and industry. However, the low scalability seriously hinders the further widespread application of blockchain technology. Therefore, this paper proposes a blockchain-based hierarchical-domain sharding system BCShard, which adopts the client-edge-cloud three-layer architecture and adopts an improved privacy protection clustering algorithm based on historical transactions to securely implement blockchain sharding and efficiently process cross-shard transactions. In addition, we implement a blockchain sharding system prototype system based on open-source codes. Detailed theoretical analysis and experimental results show that our system is compared with other state-of-the-art solutions in different metrics, demonstrating the scalability, efficiency and security of our system in the PloT scenario.

Leakage and explosion of hazardous chemicals during road transportation can cause serious building damage and casualties, and adoption of highly-efficient emergency rescue measures plays a critical role in reducing accidental hazards. Considering a liquefied petroleum gas (LPG) transport tanker explosion accident that occurred in Wenling, Zhejiang Province, China on June 13, 2020 as example, this study proposes a risk assessment framework. This framework recreates the leakage and explosion of the accident process using FLACS v10.9, suggests plans for evacuation, describes the rescue areas of different levels, and explores the influence of environmental factors on the evacuation and rescue areas. The results show that simulated and predicted distributions of fuel vapour cloud concentration and explosion overpressure can provide a reference basis for rapid rescue activities; the characterization of the dynamic effects of wind speed, wind direction, and temperature with respect to the evacuation and rescue areas can be used as theoretical support for on-site adjustment of rescue forces. The role of obstacles can prevent the expansion of the evacuation areas under low wind-speed conditions, and the presence of highly congested obstacles determines the level of the rescue area. The results obtained are important for the risk analysis and the development of emergency rescue measures in case of explosion accidents associated with transportation of hazardous chemicals on high-hazard and high-sensitive road sections.

The installed capacity of renewable energy generation in the new power system is increasing, and the demand for frequency regulation in the power system is increasing. In recent years, the potential of controllable loads represented by electric vehicles and electric heating loads to participate in grid frequency regulation has received wide attention, but how to organize a large number of dispersed and small capacity users to participate in the ancillary service market is still in the exploration stage. To this end, this study proposes a scheme for controllable load clusters to participate in the market through aggregators, and establishes a joint clearing model for the electric energy and ancillary service market based on the Stackelberg game, which enables controllable load clusters to participate in the electricity market in a distributed manner. In this example, the participation of flexible loads significantly reduces the AGC capacity provided by the generator set and reduces the total power generation cost.

In this work, multi-spectroscopic and molecular docking methods have been conducted in the investigation of enantioselective interactions between diclazuril enantiomers and human/bovine serum albumins (HSA/BSA). The binding constants between serum albumins (SAs) and diclazuril enantiomers revealed that SAs exhibited stronger binding affinity for (R)-diclazuril than (S)-enantiomer. In addition, the fluorescence quenching of SAs induced by diclazuril enantiomers was ascribed to static quenching mechanism, in which hydrogen bonds and Van der Waals forces were the main interactions. According to the thermodynamic study, binding of diclazuril enantiomers and SAs was an exothermic process driven by enthalpy change. Then, circular dichroism spectroscopy of SAs with diclazuril enantiomers revealed that the SAs conformation had changed in the presence of diclazuril. Moreover, molecular docking technology was applied in exploration of interactions between SAs and diclazuril enantiomers. The docking energy between SAs and (R)-diclazuril was larger than (S)-diclazuril, which indicated that the affinity of SAs with (R)-diclazuril was stronger than (S)-enantiomer. This work may provide valuable information for explaining differences in pharmacokinetics and residue elimination of diclazuril enantiomers in living organisms.

Heterogeneous non-noble bimetallic CuCo nanoparticle catalysts for selective N -monomethylation and N , N -dimethylation reactions under base-free conditions, offering >50 examples from aromatic/aliphatic amines, nitrocompounds and different alcohols.

The application of collaborative filtering algorithm based on time behavior in the electricity market electricity sales package recommendation system is to recommend electricity sales packages suitable for users. This method has been implemented in MATLAB and c++ programming languages. It is a multi-objective optimization problem consisting of two objectives: profit maximization and cost minimization. The objective function maximizes profits by selecting the most appropriate combination of power supply, demand forecasting and price forecasting, and minimizes costs by calculating the total revenue generated by each customer and the total cost generated in the forecasting process. As an important power commodity, power sales packaging is the carrier. In order to gain an advantage in the market competition, the power selling company improves the quality service level to customers from all aspects and improves customer satisfaction. One of their methods is to recommend power supply sales packaging. Aiming at the problems of data scarcity and cold start in collaborative filtering algorithm, a collaborative filtering algorithm based on time behavior is proposed. The algorithm first solves the historical data of the super user, analyzes the secret behavior preference information of the super user, and connects the activation of the super user to the sales kit. The results show that the improved algorithm effectively solves the data shortage and cold start problems of the synergy algorithm.

In order to support large-scale and complex blockchain application scenarios such as distributed power trading platforms, we propose a cloud-based blockchain management service middle platform Baas platform based on cross-chain communication to improve the resource utilization of the underlying blockchain platform through a standardized and reusable blockchain service system. By supporting the construction of "one master, many sides" consortium blockchain architecture, it meets the demand for cross-chain business data interaction, reduces the technical threshold for business applications to access the blockchain platform, improves the development efficiency and enhances the intelligence and automation of operation and maintenance.

With the continuous development and improvement of smart grid systems, related services such as the power market transaction management system power system will also increase in the future, resulting in a large amount of data analysis, processing, and management, and high storage costs. Database solutions, the decentralization and transparency of blockchain technology, and the concept of the energy Internet express their demands. This paper proposes a new blockchain-based power transaction storage system to improve service capabilities in a large-scale system.

手性药物与血清蛋白的结合通常表现出立体选择性.采用UV-Vis吸收光谱、荧光光谱和分子对接技术研究了R-烯唑醇和S-烯唑醇与人血清蛋白(HSA)/牛血清蛋白(BSA)的结合差异.结果表明:血清蛋白与R-烯唑醇的结合能力强于S-烯唑醇;烯唑醇对血清蛋白的荧光猝灭机制为静态猝灭;R-烯唑醇和S-烯唑醇与HSA相互作用的总能量分别为-26.4 kJ/mol和-23.6 kJ/mol,与BSA的对接能量分别为-27.6 kJ/mol和-23.3 kJ/mol,说明R-烯唑醇与血清蛋白形成的复合物更稳定.研究结果可为后续开展烯唑醇的立体选择性作用机制研究提供依据.

The key state-owned forest areas in the Greater Khingan Mountains of Inner Mongolia are areas with a high incidence of forest fires. Accurate prediction of forest fire is necessary for forest fire prevention and effective control. This paper uses satellite fire and meteorological data in the Greater Khingan Mountains of Inner Mongolia as the experimental data set, and uses geographic information system software for data preprocessing. Temperature, air pressure, wind speed, elevation, etc. are selected as explanatory variables. The Extreme Gradient Boosting (XGBoost) is proposed to predicts the area of forest fire in the study area. Bayesian parameter adjustment method is used in the modeling process. The results show that the model is superior to traditional regression algorithms in terms of error parameters, training speed, and prediction accuracy.

Herein, we reported a facile and novel Ag nanoparticle (NP) catalyst fabricated on renewable biomass derived biochar through a facile in-situ reduction-pyrolysis process. In the absence of reductants or stabilizing agents, the oxygen-containing groups in original lignocellulosic biomass offer the requisite sites (–OH, –COOH, C-O-C) for in-situ reduction of Ag + and anchor the metal center, which is conducive to synthesize uniformly dispersed Ag nanoparticle. The Ag@C catalyst was further applied to the conversion of 1-alkynes and N-halosuccinimide (-Cl, -Br and -I) to 1-haloalkynes of diverse structures with good to excellent yields up to 98% at room temperature. The catalyst showed broad substrate applicability and good recyclability. Extensive studies indicated that homogeneously dispersed Ag(0) particles were key to the high efficiency. Experimental and theoretical calculations also revealed that the addition of base could significantly activated the inert C-Cl bond in N-chlorosuccinimide, promoting its conversion at room temperature. The current finding offers a facile and economic method for the fabrication of nano metal catalysts on biomass derived carbon, further demonstrating the feasibility of utilizing the rigid structure and functionalities of biomass to prepare the carbonaceous material for catalysis applications.

The results of extracellular polymeric substances (EPS) extraction, physiological and biochemical determination and gene expression revealed the adsorption mechanism of Synechocystis sp. PCC6803 under cadmium stress.