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Terrestrial heat flow plays a vital role in determining the present thermal regimes of sedimentary basins, offering a robust foundation for understanding hydrocarbon maturation processes and the geothermal resource potential. The Junggar basin is one of the largest and most petroliferous superimposed petroleum basins in China. However, research on heat flow is scarce. In this study, 94 new high-quality heat flow values are derived from through borehole temperature analysis and thermal conductivity measurements of rocks. The results indicate that (1) the geothermal gradient in the basin varies from 11.4 to 28.3 °C km−1, with a mean value of 20.9 ± 3.4 °C km−1, and the heat flow varies from 23.4 to 64.5 mW m−2, with a mean value of 45.1 ± 8.4 mW m−2. The overall low geothermal gradient and heat flow are attributed to the continuous cooling during the Meso-Cenozoic. (2) At basin scale, the high heat flow values are primarily concentrated in areas characterized by basement uplift, whereas the low heat flow values are mainly located in the depressions. This suggests that thermal refraction is the primary factor influencing the heat flow variations. (3) Although large-scale development and utilization of geothermal resources face challenges, certain local areas in the basin show promise for geothermal resource utilization. [ABSTRACT FROM AUTHOR]

Aflatoxin B1 (AFB1), a mycotoxin commonly found in foodstuffs, poses significant health risks when ingested through contaminated food sources. Therefore, it is imperative to devise a safe and efficient method for AFB1 degradation. Graphitic carbon nitride (g-C3N4) stands out as an exceptionally stable, non-toxic, and economical photocatalyst, which is widely used in photocatalysis. In this study, we explored the photocatalytic performance of four g-C3N4 catalysts derived from different precursors (dicyandiamide (D-CN), melamine (M-CN), thiourea (T-CN), and urea (U-CN)) in AFB1 degradation under visible light. Notably, the U-CN catalyst displayed an impressive degradation rate of 93.5% for AFB1 within 30 min, outperforming M-CN (82.5%), T-CN (78.5%), and D-CN (46.2%). This superior performance is attributed to its inherent porous structure, enlarged specific surface area, and reduced electron–hole pairs' recombination rate. Additionally, our investigation identified ˙O2− as the primary active species in AFB1 degradation. Furthermore, we explored the degradation pathway of AFB1 and its associated inactivation mechanism mediated by the U-CN catalyst. This work provides a theoretical foundation for developing highly efficient photocatalysts in AFB1 degradation. [ABSTRACT FROM AUTHOR]

Based on the large-scale parallel computing platform, the numerical reactor uses advanced physical models, numerical simulation algorithms and fined modeling, so as to accurately simulate various physical phenomena of the reactor under normal operation and accident conditions. In order to solve the problems of low calculation resolution, low calculation accuracy and small application range caused by a series of theoretical approximations in the traditional reactor simulation technology, advanced simulation methods for numerical reactor were studied. In terms of neutronics resonance calculation, a resonance calculation method based on the globallocal coupling was proposed. The effects in resonance were divided into global effects and local effects. The Dancoff correction factor was used to deal with the global effects, and the pseudoresonantnuclide subgroup method was used to deal with the local effects. Based on the 2D/1D coupling method, an improved leakage splitting method was proposed to obtain the angular flux of each flat source region through the anisotropic angular reconstruction in the fuel rod, and a threelevel CMFD method was proposed to improve the computational efficiency of the traditional CMFD method. For the depletion calculations, a prediction/correction method based on reaction rate prediction was proposed to predict the change of nuclear reaction rate according to the first few burnup points and reduce the calculation time of subsequent burnup points. The Picard iterative method was used to calculate the full coupling of neutronics, thermalhydraulics and fuel performance. Based on the above methods, a numerical reactor code named NECPX was developed and verified by a set of internationally famous benchmark problems. It is proved that the code is of high calculation accuracy and efficiency. The code is then applied to the simulations of large commercial PWRs, research reactors and experimental reactors such as the second generation improved PWR M310, the third generation PWR AP1000, Xi’an Pulse Reactor, JRR-3M plate fuel reactor and Watts Bar reactor. For M310 core simulation, the critical boron concentration error of the code is within 30 ppm, and the maximum fuel effective temperature occurs at the beginning of the cycle and decreases with the burnup increasing. The change of the coolant temperature distribution is consistent with that of the fuel temperature distribution. Taking the solution from the MonteCarlo code as the reference, for the AP1000 simulation, the difference between NECPX and the reference in keff is 59 pcm. The difference in power for most assemblies is within 15%. For Xi’an Pulsed Reactor, the max difference in keff is 84 pcm, the max power difference is 52%. For JRR3M plate reactor, the max difference in keff is 97 pcm, the max power difference is 18%. For the multiphysics coupled simulation of Watts Bar reactor, the max fuel temperature calculated by the code is 1 709 K, the Mises stress of cladding changes little with time and space, the gap width is large at both ends of the fuel rod and small in the middle. The numerical results show that it can accurately predict key safety parameters of the reactor core, such as effective multiplication factors, power distributions, temperatures, stress, gap width, etc., and it is a reliable tool for the design and safety analysis of commercial largescale pressurized water reactors, research reactors and research reactors.

Accurate prediction of agricultural product prices is instrumental in providing rational guidance for agricultural production planning and the development of the agricultural industry. By constructing an end-to-end agricultural product price prediction model, incorporating a segmented Bézier curve fitting algorithm and Long Short-Term Memory (LSTM) network, this study selects corn futures prices listed on the Dalian Commodity Exchange as the research subject to predict and validate their price trends. Firstly, corn futures prices are fitted using segmented Bézier curves. Subsequently, the fitted price sequence is employed as a feature and input into an LSTM network for training to obtain a price prediction model. Finally, the prediction results of the Bézier curve-based LSTM model are compared and analyzed with traditional LSTM, ARIMA (Autoregressive Integrated Moving Average Model), VMD-LSTM, and SVR (Support Vector Regression) models. The research findings indicate that the proposed Bézier curve-based LSTM model demonstrates significant predictive advantages in corn futures price prediction. Through comparison with traditional models, the effectiveness of this model is affirmed. Consequently, the Bézier curve-based LSTM model proposed in this paper can serve as a crucial reference for agricultural product price prediction, providing effective guidance for agricultural production planning and industry development. [ABSTRACT FROM AUTHOR]

Ti3C2Tx MXene/CuxO composites were prepared by acid etching combined with electrochemical technique. The abundant active sites on the surface of MXene greatly increase the loading of CuxO nanoparticles, and the synergistic effect between the different components of the composite can accelerate the oxidation reaction of glucose. The results indicate that at the working potential of 0.55 V (vs. Ag/AgCl), the glucose sensor based on Ti3C2Tx MXene/CuxO composite presents large linear concentration ranges from 1 µM to 4.655 mM (sensitivity of 361 µA mM−1 cm−2) and from 5.155 mM to 16.155 mM (sensitivity of 133 µA mM−1 cm−2). The limit of detection is 0.065 µM. In addition, the sensor effectively avoids the oxidative interference of common interfering species such as ascorbic acid, dopamine and uric acid. The sensor has good reproducibility, stability and acceptable recoveries for the detection of glucose in human sweat sample (97.5-103.3%) with RSD values less than 4%. Based on these excellent properties it has great potential for the detection of glucose in real samples. [ABSTRACT FROM AUTHOR]

Network security is one of the key concerns with wireless sensor networks. Because sensor nodes employ radio channel frequencies, which are riskier than traditional networks, the attacker may be able to force the node to compromise, disrupt data integrity, eavesdrop, or insert false data into the network, wasting network resources. Creating dependable sensor networks that offer the highest level of security while using the fewest resources is thus one of the problems. The designers of wireless sensor networks can take into account providing an efficient key management system that can enhance any efficiency features such as communication overhead, calculation rate, memory demand, and energy consumption rate. The energy level of nodes is determined in this article using a novel approach based on fuzzy systems and simple to implement in both hardware and software. In this study, the memory needed to carry out the plan was decreased, and the search performance was raised by integrating elliptic curve cryptography with an AVL search tree and a LEACH model. Also, the frequency range of radio channels in this study is 2.4 GHz. Based on the theoretical analysis as well as the outcomes of the experiments, the suggested key management strategy for wireless sensor networks improves security while also reducing computational overhead by 23%, energy consumption by 14%, and memory consumption parameters by 14%. 18% of people have used the network. Additionally, it was demonstrated that the suggested approach is scalable and extendable. Because of this, the suggested technique has a wide range of applications in massive wireless sensor networks. [ABSTRACT FROM AUTHOR]

Ti3C2Tx MXene has a high specific surface area and high conductivity, and can be used in the field of humidity sensing. By controlling the surface termination and microstructure of the material, it is expected to improve the humidity sensing performance of Ti3C2Tx MXene. In this paper, we report a method of electrolytic intercalation treatment of Ti3C2Tx MXene in NaOH solution. Theoretical and experimental results show that this method can remove the original F terminations from the surface of Ti3C2Tx MXene and form a large number of OH and O terminations. The partial oxidation of the surface and the replacement of terminations and the insertion of Na+ lead to the change of the Ti3C2Tx MXene layer morphology from flat to curly and significantly improve the hydrophilicity and resistance. The curly flake structure constructs a fast channel for the entry and exit of water molecules which improves the hydration/dehydration efficiency of the material; the enhanced hydrophilicity of the material sharply reduces the resistance of the material after moisture absorption, which significantly improves the responsiveness of Ti3C2Tx MXene to humidity. The curly flake Ti3C2Tx MXene humidity sensor has an ultra-high sensitivity of S = 1.2 × 105 (two orders of magnitude higher than that of the reported humidity sensor based on MXene), with a fast response rate (2 s), good repeatability and stability (4 weeks), and it can be used for the analysis of human respiration rate, and also for non-contact sensing detection of the human body and environmental humidity detection. [ABSTRACT FROM AUTHOR]

Research has been conducted on the major pathways on the mRNA turnover in eukaryotes which initiate with the poly(A) tail shortening. Results indicate that CCR4 and CAF1 encode the major cytoplasmic deadenylase components in yeast and that there may be a link between mRNA synthesis and turnover.