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Cobalt has excellent electrochemical, magnetic, and heat properties. As a strategic resource, it has been applied in many high-tech products. However, the recent rapid growth of the battery industry has substantially depleted cobalt resources, leading to a crisis of cobalt resource supply. The paper examines cobalt ore reserves and distribution, and the recent development and consumption of cobalt resources are summarized as well. In addition, the principles, advantages and disadvantages, and research status of various methods are discussed comprehensively. It can be concluded that the use of diverse sources (Cu-Co ores, Ni-Co ores, zinc plant residues, and waste cobalt products) for cobalt production should be enhanced to meet developmental requirements. Furthermore, in recovery technology, the pyro-hydrometallurgical process employs pyrometallurgy as the pretreatment to modify the phase structure of cobalt minerals, enhancing its recovery in the hydrometallurgical stage and facilitating high-purity cobalt production. Consequently, it represents a promising technology for future cobalt recovery. Lastly, based on the above conclusions, the prospects for cobalt are assessed regarding cobalt ore processing and sustainable cobalt recycling, for which further study should be conducted.

•The entransy dissipation ratio (EDR) was introduced.•The performance of the system and components was analyzed.•The irreversibility rates for each component was studied. With the continuous progress of urbanization, building energy consumption is increasing dramatically. At present, energy consumption caused by air conditioning accounts for a half in typical building energy consumption in China. Using exergy and entransy analysis, this paper experimentally studies the thermal performance of an air source heat pump water heater and its components under different meteorological conditions. This paper, for the first time, introduces the dimensionless number of entransy dissipation ratio (EDR), namely the percentage of a component's entransy dissipation into the entire system. The findings indicate that with the increase in air temperature, the heat production, the EDR of condenser and evaporator, and the exergy efficiency of condenser and compressor increase while the exergic efficiency of evaporator and throttle valve decrease. In the case of increased air flow rate, the heat production and exergy destruction of water heater as well as the EDR of evaporator are enhanced, while the exergy efficiency of evaporator, compressor and throttle and the EDR of condenser decrease, with the exergy efficiency of the throttle remaining the highest. The irreversibility rates of components are affected by change in the relative humidity of air, which is specified as follows: The percentage range of irreversibility rates for compressor, condenser, throttle and evaporator is 11.5–16 %, 37–45 %, 6.8–11.5 % and 32–41 %, respectively. [Display omitted]

Secoatractylohexone A (1), an unprecedented secoguaiane lactone glycoside featuring 6/7 cores and dihydroxy-9-guaine-3-one 11-O-β-d-glucopyranoside (2), a 9,10-unsaturated guaiene-type glycoside possessing an uncommon scaffold, were isolated from the water-soluble portion of the ethanolic extract of Atractylodes lancea rhizomes together with five known compounds (3–7). The structures of 1 and 2 were elucidated on the basis of extensive spectroscopic data and application of the CD technique. The potential biological activities of secoatractylohexone A were predicted by network pharmacology in silico, the result of which indicated that secoatractylohexone A may be used to treat type II diabetes.

The clustered regularly interspaced short palindromic repeats (CRISPR) systems have been demonstrated to be the foremost compelling genetic tools for manipulating prokaryotic and eukaryotic genomes. Despite the robustness and versatility of Cas9 and Cas12a/b nucleases in mammalian cells and plants, their large protein sizes may hinder downstream applications. Therefore, investigating compact CRISPR nucleases will unlock numerous genome editing and delivery challenges that constrain genetic engineering and crop development. In this study, we assessed the archaeal miniature Un1Cas12f1 type‐V CRISPR nuclease for genome editing in rice and tomato protoplasts. By adopting the reengineered guide RNA modifications ge4.1 and comparing polymerase II (Pol II) and polymerase III (Pol III) promoters, we demonstrated uncultured archaeon Cas12f1 (Un1Cas12f1) genome editing efficacy in rice and tomato protoplasts. We characterized the protospacer adjacent motif (PAM) requirements and mutation profiles of Un1Cas12f1 in both plant species. Interestingly, we found that Pol III promoters, not Pol II promoters, led to higher genome editing efficiency when they were used to drive guide RNA expression. Unlike in mammalian cells, the engineered Un1Cas12f1‐RRA variant did not perform better than the wild‐type Un1Cas12f1 nuclease, suggesting continued protein engineering and other innovative approaches are needed to further improve Un1Cas12f1 genome editing in plants. Core Ideas Exploration of a novel compact clustered regularly interspaced short palindromic repeats‐Cas system in plants. Testing of uncultured archaeon Cas12f1 in both monocot and dicot plants. Improved genome editing with polymerase III promoters for guide RNA expression. Plain Language Summary Plant genome editing is a promising breeding technology. Many clustered regularly interspaced short palindromic repeats (CRISPR)‐Cas systems have been discovered and engineered as tools for genome editing. Most of the existing CRISPR‐Cas nucleases and genome editing systems are based on Cas9 and Cas12a, which are large proteins. The Hypercompact CRISPR‐Cas system could enable more innovative delivery approaches. Here, we explored uncultured archaeon Cas12f1 (Un1Cas12f1), a type V‐F miniature CRISPR system, for genome editing in plants. We developed an efficient CRISPR‐Un1Cas12f1 expression system that is based on an optimized guide RNA scaffold and polymerase III small RNA promoters. We further characterized Un1Cas12f1's sequence preference and editing outcomes in rice and tomato protoplasts by next‐generation sequencing. This is a comprehensive study of the Un1Cas12f1 system in plants. Further improvement of Un1Cas12f1 is warranted before it becomes a powerful tool for genome editing in plants.

In this paper, we investigate covert communications for an unmanned aerial vehicle (UAV)-aided rate-splitting multiple access (RSMA) system in which the UAV transmits to the covert and public users separately while shielding covert transmissions from a warden. Under the RSMA principles, the messages of the covert and public users are converted to common and private streams for air-to-ground transmissions. Subject to the quality of service (QoS) requirements of the public user and covertness constraint of the UAV-aid RSMA (UAV-RSMA) system, the aim of covert communication design is to maximize the covert rate by jointly optimizing the transmit power allocation, common rate allocation, and UAV hovering height, which each contribute to the uncertainty of the warden’s binary decision and attempts to enhance communication performance. To address the non-convex covert rate maximization problem in addition to the highly coupled system parameters, we decouple the original problem into three subproblems of transmit power allocation, common rate allocation, and UAV hovering height. We derive the optimal solutions for each of the subproblems of the transmit power and rate allocations and formulate a signomial programming problem to tackle UAV hovering height optimization. The simulation results indicate the superior covert rate performance achieved by the proposed AO algorithm and demonstrate that the proposed UAV-RSMA scheme achieves a higher covert rate than the benchmark schemes.

Aim Considering the direct or indirect influence of crops on greenhouse soil, we improved the traditional greenhouse prediction of soil temperature, and established an accurate greenhouse soil temperature prediction model for the research gap of crop-soil thermal relationship in the climate of subtropical region. Multiple sets of replicated experiments were conducted to verify the hypothesis of crop-root-soil thermal relationship and compared with the model predictions. Methods The direct or indirect effects of crops on soil temperature are considered in the analysis of soil energies, in particular the effects of the results of the study of the crop-root-soil heat relationship. A new soil heat balance equation was re-established to correct the original greenhouse soil prediction model based on the soil heat balance equation. After experimental validation and model comparison verification, the model performance was evaluated by calculating two indicators, root mean square error (rRMSE) and mean bias error (MBE). Results The experimental results show that there is a relatively stable temperature difference between the crop root system-soil. At ambient temperatures below sub-high temperatures, a stable temperature difference existed at all soil depths; at sub-high temperatures, this temperature difference became so small as to be almost negligible. Conclusion Comparison of the simulated data with the experimental data showed that the changes in soil temperature were consistent with the crop activities and the model simulated with higher accuracy than the original model. This provides an accurate method of predicting soil boundary conditions for studying the greenhouse thermal environment in the subtropics.

In recent years, the learning method based on depth convolution neural network has achieved unprecedented results in image denoising, and it has become a research hotspot to obtain better image denoising effect by adjusting network structure and parameters. Noise reduction convolution neural network adopts residual learning method in depth neural network, which not only improves the effect of noise reduction, but also solves the problem of blind noise reduction to a certain extent. Its disadvantage is that the algorithm has a long convergence time. In this paper, the structure of noise reduction convolution neural network is further improved, and an image denoising algorithm based on deconvolution neural network is proposed. The main features of this paper are as follows: 1) in the original network structure, deconvolution neural network is introduced to optimize the residual learning method; 2) A new loss function calculation method is proposed. BSD68 and SET12 test data sets are used to verify the proposed method. The experimental results show that the noise reduction performance of this algorithm is compared with the noise reduction convolution neural network algorithm. Under the same noise reduction effect, the convergence time of this algorithm is shortened by 120%. 138%. At the same time, compared with the traditional deep learning image denoising algorithm, the denoising effect and running efficiency of this method are also improved.

In order to improve the accuracy and efficiency of piezoelectric structure design, the static mechanic-electric coupling of two-dimensional piezoelectric material problems are investigated by a cell-based smoothed isogeometric analysis (CS-IGA) in this work. The CS-IGA was developed on the basis of the isogeometric analysis by using strain smoothing technology. Based on the generalized Galerkin weak form and the constitutive equation of piezoelectric structures, the equilibrium equation of piezoelectric material in the problem of mechanic-electric coupling is obtained. For further improving the calculation precision of the algorithm, average strain is defined in the element domains. It completely avoids the gradient calculation of rational NURBS basis function in the stiffness matrix formula and further improves the computational efficiency. Besides, numerical example results can verify the precision, correctness and reliability of the proposed method in comparison with the finite element method in the analysis of piezoelectric material problems. Overall, this work can provide a help for analyzing the problems of piezoelectric structures.

Rate-splitting multiple access (RSMA) has recently received attention due to its benefits in both spectral and energy efficiencies. In this paper, we propose a hybrid RSMA-time-division multiple access (TDMA) scheme for a mobile edge computing (MEC) system, where two edge users need to offload their task data to a MEC server. In the proposed scheme, the offloading time is divided into two time phases. Specifically, we design a cognitive radio (CR)-inspired RSMA scheme, in which two users, namely the primary user and secondary user, offload their task data to the MEC server in the first time phase, while only a single user can offload task data in the second time phase. With the aim of minimizing the overall offloading delay, we formulate the offloading delay minimization problem subject to the transmit power and total energy constraints. We transform the original fractional programming non-convex problem to a convex one by using the Dinkelbach transform and propose Dinkelbach and Newton iterative algorithms to determine the optimal transmit power allocation. Specifically, we establish the optimization criteria for the three offloading schemes and derive the corresponding closed-form expressions for the optimal power allocation. Compared to the existing offloading schemes, the numerical results show that the proposed hybrid RSMA-TDMA scheme in scenarios where having a limited energy budget is superior in offloading delay compared to other offloading schemes and the sum offloading delay tends to a constant with the increase in the energy budget.

Secoatractylohexone A (1), an unprecedented secoguaiane lactone glycoside featuring 6/7 cores and dihydroxy-9-guaine-3-one 11-O-β-d-glucopyranoside (2), a 9,10-unsaturated guaiene-type glycoside possessing an uncommon scaffold, were isolated from the water-soluble portion of the ethanolic extract of Atractylodes lancea rhizomes together with five known compounds (3–7). The structures of 1 and 2 were elucidated on the basis of extensive spectroscopic data and application of the CD technique. The potential biological activities of secoatractylohexone A were predicted by network pharmacology in silico, the result of which indicated that secoatractylohexone A may be used to treat type II diabetes.