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Understanding canopy nitrogen (N) and phosphorus (P) differences is crucial for optimizing plant nutrient distribution and management. This study evaluated leaf N and P content in citrus trees across three cultivation modes: traditional mode (TM), wide-row and narrow-plant mode (WRNPM), and fenced mode (FM). We used hyperspectral data for non-destructive quantification and compared 1080 leaf samples from upper, middle, and lower canopy layers. Four models—Random Forest (RF), Backpropagation Neural Network (BPNN), Partial Least Squares (PLS), and Support Vector Machine (SVM)—were employed for leaf N and P estimation. Results showed that the TM had significantly lower N content compared to the WRNPM and FM, while the WRNPM exhibited higher P content. The canopy layer had minimal impact on N and P in the FM, and leaves in the upper layer had higher nutrient content in the WRNPM and TM. RF provided the best estimation accuracy, with R2 values of 0.66 for N and 0.72 for P. The cultivation mode and canopy layer significantly influenced the estimation accuracy, with the TM yielding the highest R2, followed by the WRNPM and FM obtaining the lowest accuracy. The labor-saving cultivation mode had different nutrient utilization efficiency compared to the TM. The cultivation mode and canopy layer should be considered when hyperspectral data were used for estimating the leaf N and P content. The study can offer new insights for precise fertilization strategies in fruit trees. [ABSTRACT FROM AUTHOR]

To address the demands of precision agriculture and the measurement of plant photosynthetic response and nitrogen status, it is necessary to employ advanced methods for estimating chlorophyll content quickly and non-destructively at a large scale. Therefore, we explored the utilization of both linear regression and machine learning methodology to improve the prediction of leaf chlorophyll content (LCC) in citrus trees through the analysis of hyperspectral reflectance data in a field experiment. And the relationship between phenology and LCC estimation was also tested in this study. The LCC of citrus tree leaves at five growth seasons (May, June, August, October, and December) were measured alongside measurements of leaf hyperspectral reflectance. The measured LCC data and spectral parameters were used for evaluating LCC using univariate linear regression (ULR), multivariate linear regression (MLR), random forest regression (RFR), K-nearest neighbor regression (KNNR), and support vector regression (SVR). The results revealed the following: the MLR and machine learning models (RFR, KNNR, SVR), in both October and December, performed well in LCC estimation with a coefficient of determination (R2) greater than 0.70. In August, the ULR model performed the best, achieving an R2 of 0.69 and root mean square error (RMSE) of 8.92. However, the RFR model demonstrated the highest predictive power for estimating LCC in May, June, October, and December. Furthermore, the prediction accuracy was the best with the RFR model with parameters VOG2 and Carte4 in October, achieving an R2 of 0.83 and RMSE of 6.67. Our findings revealed that using just a few spectral parameters can efficiently estimate LCC in citrus trees, showing substantial promise for implementation in large-scale orchards. [ABSTRACT FROM AUTHOR]

This study aimed to explore the applicability of DNA barcoding for assessing the authenticity of caviar on the Chinese market. A set of universal COI primers and two sets of designed primers based on COI and D-loop genes were used to identify maternal species of samples from 21 batches of caviar. The results showed that the PCR products from three sets of primers had more than 98% similarity to the sequences in database. The COI gene could not distinguish sturgeons with closed genetic relationships, while D-loop gene could effectively improve the accuracy of DNA barcoding and was more suitable to the identification of interspecific sturgeon than the COI gene. The neighbor-joining dendrogram further confirmed the applicability and accuracy of COI and D-loop genes in identifying maternal relatives of caviar (Acipenser baerii/Acipenser gueldenstaedtii/Acipenser schrenckii/Huso dauricus/Huso huso). Despite the limitations of mitochondrial DNA in identifying hybrid sturgeon species, the presence of counterfeit caviar of non-sturgeon ingredients could be excluded. All the caviar samples were identified successfully as sturgeon species, but the mislabeling rate of species was 33.4%, indicating that there were illegal phenomena such as disorderly labeling, mislabeling, and adulteration on the market. [ABSTRACT FROM AUTHOR]

Ensuring training safety is paramount to flight schools. In response to the inadequacy of traditional flight training assessment for comprehensive quantitative evaluation of cadet competency, an initial flight training competency assessment standard based on behavioral indicators was developed and optimized using the VENN model. Firstly, the Assessor Score Measurement Form (ASMF) was constructed according to the requirements of the Training Evaluation Worksheet specification, such as typical subjects, observations, and completion criteria. Secondly, based on the basic principles of the experience of the flight expert and the Competency-Based Training and Assessment (CBTA), a matrix of correlations between the observations and each competency-based behavioral indicator was created to construct a competency assessment matrix. In addition, a two-dimensional model for representing competency items characterized by behavioral indicators was established and an optimization model for competency assessment criteria was constructed. Finally, through combining actual flight training data, the proposed method was validated in the flight screening check phase. The results show that the optimized flight training competency assessment scheme can be well quantified and matched to real instructor ratings with an accuracy of 84%. The assessment worksheet, the assessment matrix, and the VENN competency rating model can be adapted to the different teaching requirements of each flight phase, achieving a perfect match between the behavioral indicators and the competency items, which is highly versatile. The proposed model can more accurately reflect the core competencies of flight trainees, enable quantitative assessment of behavioral indicators and competency items, and provide support for subsequent training of trainees. [ABSTRACT FROM AUTHOR]

Three-way fuzzy inference is the theoretical basis of three-way fuzzy control. The proposed TCRI method is based on a Mamdani three-way fuzzy implication operator and uses one inference and simple composition operation. In order to effectively improve the TCRI method, this paper proposes a full implication triple I algorithm for three-way fuzzy inference and gives the triple I solution to the TFMP problem. The emphasis of our research is R 0 and G o ¨ del triple I solution, which is related to three-way residual implication, as well as Zadeh's and Mamdani's triple I solution, which is based on three-way fuzzy implication operator. Then the three-way fuzzy controller is constructed by the proposed Zadeh's and R 0 triple I algorithm. Finally, the proposed triple I algorithm is applied to the three-way fuzzy control system, and its advantage is illustrated by the three-dimensional surface diagram of the control variable. [ABSTRACT FROM AUTHOR]

Recently, the notion of a three-way fuzzy set is presented, inspired by the basic ideas of three-way decision and various generalized fuzzy sets, including lattice-valued fuzzy sets, partial fuzzy sets, intuitionistic fuzzy sets, etc. As the new theory of uncertainty, it has been used in attribute reduction and as a new control method for the water level. However, as an extension of a three-way decision, this new theory has not been used in multi-criteria decision making (MCDM for short). Based on the previous work, in this paper, we present rough set models based on three-way fuzzy sets, which extend the existing fuzzy rough set models in both complete and incomplete information systems. Furthermore, the new models are used to solve the issue of MCDM. Firstly, three-way fuzzy relation rough set and three-way fuzzy covering rough set models are presented for complete and incomplete information systems. Because almost all existing fuzzy rough set models are proposed under complete information, the new proposed models can be seen as a supplement to these existing models. Then, a relationship between the three-way fuzzy relation rough set and the three-way fuzzy covering rough set is presented. Finally, a novel method for the issue of MCDM is presented under the novel three-way fuzzy rough set models, which is used in paper defect diagnosis. [ABSTRACT FROM AUTHOR]

Injecting low-cost semi-coke is critical to reducing blast furnace production costs. The combustion behavior of the co-injection of semi-coke and undersized coke powder is still rarely studied. In this work, a three-dimensional CFD mathematical model was established to simulate the gas velocity, temperature, composition distribution and burnout of semi-coke during the combustion of pulverized semi-coke. The influence of mass fraction of semi-coke on the composition and burnout in the combustion zone of blast furnace was also studied. The results show that the maximum concentrations of CO and H2 in the combustion zone are 36% and 8%, respectively. With the decrease of the semi-coke ratio in the blended coal, the fixed carbon content and the calorific value of the blended coal increase, but the burnout of the blended coal reduces. When bituminous coal is single injected, the burnout reaches 70%, which is higher than that of semi-coke. In actual production, for the semi-coke and coke powder injecting into the blast furnace, a proportion of bituminous coal can be appropriately added to improve the burnout rate of the coal blends and increase the H2 content in reducing gas. [ABSTRACT FROM AUTHOR]

Myogenesis is a central step in prenatal myofiber formation, postnatal myofiber hypertrophy, and muscle damage repair in adulthood. RNA-Seq technology has greatly helped reveal the molecular mechanism of myogenesis, but batch effects in different experiments inevitably lead to misinterpretation of differentially expressed genes (DEGs). We previously applied the robust rank aggregation (RRA) method to effectively circumvent batch effects across multiple RNA-Seq datasets from 3T3-L1 cells. Here, we also used the RRA method to integrate nine RNA-Seq datasets from C2C12 cells and obtained 3140 robust DEGs between myoblasts and myotubes, which were then validated with array expression profiles and H3K27ac signals. The upregulated robust DEGs were highly enriched in gene ontology (GO) terms related to muscle cell differentiation and development. Considering that the cooperative binding of transcription factors (TFs) to enhancers to regulate downstream gene expression is a classical epigenetic mechanism, differentially expressed TFs (DETFs) were screened, and potential novel myogenic factors (MAF, BCL6, and ESR1) with high connection degree in protein–protein interaction (PPI) network were presented. Moreover, KLF5 cooperatively binds with the three key myogenic factors (MYOD, MYOG, and MEF2D) in C2C12 cells. Motif analysis speculates that the binding of MYOD and MYOG is KLF5-independent, while MEF2D is KLF5-dependent. It was revealed that KLF5-binding sites could be exploited to filter redundant MYOD-, MYOG-, and MEF2D-binding sites to focus on key enhancers for myogenesis. Further functional annotation of KLF5-binding sites suggested that KLF5 may regulate myogenesis through the PI3K-AKt signaling pathway, Rap1 signaling pathway, and the Hippo signaling pathway. In general, our study provides a wealth of untapped candidate targets for myogenesis and contributes new insights into the core regulatory mechanisms of myogenesis relying on KLF5-binding signal. [ABSTRACT FROM AUTHOR]

Manganese dioxide is typically reduced to a bivalent state before being extracted; here, sulfur is considered an efficient reductant and sulfur–based reduction has been industrialized in China. In this study, the reaction mechanism between MnO2 and gaseous sulfur was investigated. Thermodynamically, the reduction of MnO2 by gaseous sulfur is feasible. The predominant phase diagram as functions of temperature and input S2(g) fraction in the S2–MnO2 system was calculated. Experimental validation showed that MnO2 was reduced stepwise to low-valence manganese oxides and manganese sulfate. The phase composition of the roasted products was complex, and MnS was inevitably formed. The valence state as well as microstructure of manganese dioxide during reduction roasting were also investigated by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy–energy-dispersive spectroscopy (SEM–EDS). The reaction process could be described by an unreacted nuclear model. Manganese was extracted by sulfuric acid solution after reduction by sulfur waste. In sulfuric acid, 95.2 wt% Mn extraction was achieved, using a roasting temperature of 450 °C, roasting time of 30 min, and S2/MnO2 molar ratio of 0.40. With the same conditions, low Fe extraction was achieved. On the other hand, in deionized water, 24.3 wt% Mn extraction was achieved, confirming the formation of MnSO4. [ABSTRACT FROM AUTHOR]

High-performance anti-corrosion coatings featuring easy processability and thin thickness are highly desired in industry. Yet, solution process coating often faces a sedimentation problem with particles which are used as reinforcement in coatings. In this contribution, boron nitride (BN) was modified by an acrylate silane coupling agent (KH-570) to obtain acrylated BN flakes. Afterwards, the acrylated BN flakes were in situ copolymerized with 2-(perfluorohexyl)ethyl methacrylate to synthesize BN-fluorinated poly methacrylate (PFBP) composites. The as-obtained PFBP composites can form stable coating solutions, in which sedimentation of BN flakes seldom happens. The coating solution can easily form uniform coatings on various substrates with nanoscale thickness, confirmed by scanning electron microscope (SEM). The corrosion resistance of the samples coated PFBP coatings in 3.5 wt.% sodium chloride solution was evaluated by electrochemical impedance spectroscopy (EIS). It is indicated that the incorporation of BN flakes greatly reduce the corrosion rate. Adhesion measurements and abrasion resistance test indicate the PFBP coating performs good adhesion to substrate and robustness. Through the in situ polymerization, acrylated BN flakes are connected with the polymer chain, which inhibits the sedimentation of BN in the coating solution. Additionally, the BN flakes dispersed in the fluorinated polymer act as barriers, improving the corrosion resistance of the coated samples. [ABSTRACT FROM AUTHOR]

The commercial and financial attributes of oil have significantly changed the evolution characteristics of prices and returns of the international crude oil market. Using monthly data from April 2003 to October 2020, this paper identifies dynamic characteristics of oil's commercial and financial attributes based on the structural vector autoregressive model (SVAR) and further analyzes their market effects with different attributes. The result shows that there are situations of commercial and financial attributes dominating, and dual attributes co-dominating for oil. Furthermore, their durations account for 51%, 23%, and 26% respectively, of the full sample. Besides, the reactions of crude oil price or return to the different properties of oil are heterogeneous. Specifically, the dual attributes of oil play the most important role in the price evolution of the international crude oil market, which is 80.851. There are significant differences among the impact of different attributes of oil on the evolution of international crude oil market returns, which are 0.009, −0.008, and −0.004, respectively. Then, some relevant recommendations for policy-makers and investors based on the above research conclusions are also put forward. [ABSTRACT FROM AUTHOR]

Aquaporins are integral membrane proteins that facilitate the diffusion of water and other small, uncharged solutes across the cellular membrane and are widely distributed in organisms from humans to bacteria. However, the characteristics of prokaryotic aquaporins remain largely unknown. We investigated the distribution and sequence characterization of aquaporins in prokaryotic organisms and summarized the transport characteristics, physiological functions, and regulatory mechanisms of prokaryotic aquaporins. Aquaporin homologues were identified in 3315 prokaryotic genomes retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, but the protein clustering pattern is not completely congruent with the phylogeny of the species that carry them. Moreover, prokaryotic aquaporins display diversified aromatic/arginine constriction region (ar/R) amino acid compositions, implying multiple functions. The typical water and glycerol transport characterization, physiological functions, and regulations have been extensively studied in Escherichia coli AqpZ and GlpF. A Streptococcus aquaporin has recently been verified to facilitate the efflux of endogenous H2O2, which not only contributes to detoxification but also to species competitiveness, improving our understanding of prokaryotic aquaporins. Furthermore, recent studies revealed novel regulatory mechanisms of prokaryotic aquaporins at post-translational level. Thus, we propose that intensive investigation on prokaryotic aquaporins would extend the functional categories and working mechanisms of these ubiquitous, intrinsic membrane proteins. [ABSTRACT FROM AUTHOR]

Neutrosophic triangular norms (t-norms) and their residuated lattices are not only the main research object of neutrosophic set theory, but also the core content of neutrosophic logic. Neutrosophic implications are important operators of neutrosophic logic. Neutrosophic residual implications based on neutrosophic t-norms can be applied to the fields of neutrosophic inference and neutrosophic control. In this paper, neutrosophic t-norms, neutrosophic residual implications, and the residuated lattices derived from neutrosophic t-norms are investigated deeply. First of all, the lattice and its corresponding system are proved to be a complete lattice and a De Morgan algebra, respectively. Second, the notions of neutrosophic t-norms are introduced on the complete lattice discussed earlier. The basic concepts and typical examples of representable and non-representable neutrosophic t-norms are obtained. Naturally, De Morgan neutrosophic triples are defined for the duality of neutrosophic t-norms and neutrosophic t-conorms with respect to neutrosophic negators. Third, neutrosophic residual implications generated from neutrosophic t-norms and their basic properties are investigated. Furthermore, residual neutrosophic t-norms are proved to be infinitely ∨-distributive, and then some important properties possessed by neutrosophic residual implications are given. Finally, a method for producing neutrosophic t-norms from neutrosophic implications is presented, and the residuated lattices are constructed on the basis of neutrosophic t-norms and neutrosophic residual implications. [ABSTRACT FROM AUTHOR]

Cut sets, decomposition theorem and representation theorem have a great influence on the realization of the transformation of fuzzy sets and classical sets, and the single-valued neutrosophic multisets (SVNMSs) as the generalization of fuzzy sets, which cut sets, decomposition theorem and representation theorem have the similar effects, so they need to be studied in depth. In this paper, the decomposition theorem, representation theorem and the application of a new similarity measures of SVNMSs are studied by using theoretical analysis and calculations. The following are the main results: (1) The notions, operation and operational properties of the cut sets and strong cut sets of SVNMSs are introduced and discussed; (2) The decomposition theorem and representation theorem of SVNMSs are established and rigorously proved. The decomposition theorem and the representation theorem of SVNMSs are the theoretical basis for the development of SVNMSs. The decomposition theorem provides a new idea for solving the problem of SVNMSs, and points out the direction for the principle of expansion of SVNMSs. (3) Based on the decomposition theorem and representation theorem of SVNMSs, a new notion of similarity measure of SVNMSs is proposed by applying triple integral. And this new similarity is applied to the practical problem of multicriteria decision-making, which explains the efficacy and practicability of this decision-making method. The new similarity is not only a way to solve the problem of multi-attribute decision-making, but also contains an important mathematical idea, that is, the idea of transformation. [ABSTRACT FROM AUTHOR]

As a new generalization of the notion of the standard group, the notion of the neutrosophic triplet group (NTG) is derived from the basic idea of the neutrosophic set and can be regarded as a mathematical structure describing generalized symmetry. In this paper, the properties and structural features of NTG are studied in depth by using theoretical analysis and software calculations (in fact, some important examples in the paper are calculated and verified by mathematics software, but the related programs are omitted). The main results are obtained as follows: (1) by constructing counterexamples, some mistakes in the some literatures are pointed out; (2) some new properties of NTGs are obtained, and it is proved that every element has unique neutral element in any neutrosophic triplet group; (3) the notions of NT-subgroups, strong NT-subgroups, and weak commutative neutrosophic triplet groups (WCNTGs) are introduced, the quotient structures are constructed by strong NT-subgroups, and a homomorphism theorem is proved in weak commutative neutrosophic triplet groups. [ABSTRACT FROM AUTHOR]