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Abstract Background Postoperative progressive cerebral edema and hemorrhage (PPCEH) are major complications after meningioma resection, yet their preoperative predictive studies are limited. The aim is to develop and validate a multiparametric MRI machine learning model to predict PPCEH after meningioma resection. Methods This retrospective study included 148 patients with meningioma. A stratified three-fold cross-validation was used to split the dataset into training and validation sets. Radiomics features from the tumor enhancement (TE) and peritumoral brain edema (PTBE) regions were extracted from T1WI, T2WI, and ADC maps. Support vector machine constructed different radiomics models, and logistic regression explored clinical risk factors. Prediction models, integrating clinical and radiomics features, were evaluated using the area under the curve (AUC), visualized in a nomogram. Results The radiomics model based on TE and PTBE regions (training set mean AUC: 0.85 (95% CI: 0.78–0.93), validation set mean AUC: 0.77 (95%CI: 0.63–0.90)) outperformed the model with TE region solely (training set mean AUC: 0.83 (95% CI: 0.76–0.91), validation set mean AUC: 0.73 (95% CI: 0.58–0.87)). Furthermore, the combined model incorporating radiomics features, and clinical features of preoperative peritumoral edema and tumor boundary adhesion, had the best predictive performance, with AUC values of 0.87 (95% CI: 0.80–0.94) and 0.84 (95% CI: 0.72–0.95) for the training and validation set. Conclusions We developed a novel model based on clinical characteristics and multiparametric radiomics features derived from TE and PTBE regions, which can accurately and non-invasively predict PPCEH after meningioma resection. Additionally, our findings suggest the crucial role of PTBE radiomics features in understanding the potential mechanisms of PPCEH.

This is an article in the field of mineral processing engineering. The gasification slag is a by-product produced in the process of coal gasification, which is difficult to be industrialized. In order to realize the rational and effective utilization of gasification slags, the gasification coarse slags produced by the typical coal water slurry process in Ordos area of China are simply separated into high, medium and low carbon slags by screening. The physicochemical properties, heavy metal content, carbon content, micro morphology, mineral phase composition and pore structure of the three types of carbon slags were characterized and analyzed by XRF, element analyzer, XRD, SEM, BET specific surface area analyzer, thermogravimetric analyzer and ICP-MS. The high, medium and low carbon slags have significant differences in characteristics. The screening can better realize the preliminary quality separation of gasified slags, which lays a foundation for the classified utilization of gasified slags.

Abstract Introduction Previous studies have explored the connections between various ocular biological parameters with myopia. Our previous study also found that pupil data can predict the myopic progression during the interventions for myopia. However, studies exploring the association between pupil diameter and myopia in preschoolers with myopia were lacking. Hence this study was aimed to investigate the association between pupil diameter and myopia in preschoolers with myopia based on a real-world, large-scale dataset. Methods Data containing 650,671 preschoolers were collected from a total of 1943 kindergartens in Shenzhen, China. Refraction and pupil parameters were collected. After data filtering, the occurrence of myopia and its association with age, gender, pupil diameter, and other variables, were analyzed. Random forest (RF) and eXtreme gradient boosting (XGBoost) were selected from seven machine learning algorithms to build the model. The mean decrease accuracy (MDA), mean decrease Gini (MDG), and gain feature importance (GFI) techniques were employed to quantify the importance of pupil diameter and other features. Results After the assessments, 51,325 valid records with complete pupil data were included, and 3468 (6.76%) were identified as myopia based on the calculated cycloplegic refraction. Preschoolers with myopia presented reduced pupil diameter and greater variation (5.00 ± 0.99 mm) compared to non-myopic preschoolers (6.22 ± 0.67 mm). A nonlinear relationship was found according to the scatterplots between pupil diameter and refraction (R 2 = 0.14). Especially preschoolers with myopia had reduced pupil diameter compared to emmetropic preschoolers, but hyperope did not experience additional pupil enlargement. After adjusting for other covariates, this relationship is still consistent (P

Employee turnover has a negative impact on business profitability. To tackle this issue, we can utilize computational advancements to forecast attrition and minimize expenses. We employed an HR Analytics dataset to investigate the feasibility of using these predictive models in decision support systems. We developed an ensemble of gradient-based decision trees that accurately predicted employee turnover and performed better than other sophisticated techniques. This approach demonstrates exceptional performance in handling structured and imbalanced data, effectively capturing intricate patterns. Gradient-based decision trees provide scalable solutions that effectively balance predictive accuracy and computational efficiency, making them well-suited for strategic business analysis. The importance of our findings lies in their ability to offer dependable insights for making well-informed decisions in business settings.

To effectively recognize the incipient potential faults caused by degradation of multiple components in DC-DC converters, a fault diagnosis method that involves multi-dimensional feature fusion and sensitive feature extraction is proposed. Firstly, the time-domain statistical characteristics of fault and normal samples are extracted. The KL divergence and normalized kurtosis of intrinsic mode functions (IMFs) between them are calculated by empirical mode decomposition (EMD). In order to further improve the feature discrimination, a sensitive feature extraction method based on Mahalanobis distance (SFMD) is designed to screen out the key features. Finally, the sensitive features are used to construct the SA-LSSVM (Simulated annealing-Least squares support vector machine) model to realize the fault diagnosis. The accuracy of fault diagnosis in simulation and hardware experiment are 99.61% and 97.93% respectively. Compared with other fault diagnosis and feature selection methods, the proposed method still has higher accuracy and better engineering practicability.

DC-DC converter is the vital part of the power system, and its fault can cause the failure of complex electronic equipment. Therefore, the timely and accurate fault diagnosis of DC-DC converter is particularly important. This paper proposes a DC-DC converter fault diagnosis method based on improved SE-ResNet algorithm. First, in order to extract all information about the signals, we transform the one-dimensional signal into Gramian angular differential field (GADF) images. Then, the Squeeze-and-Excitation (SE) network is added to ResNet-50, combined with h-swish function and label smoothing cross entropy loss function (LSCE) to improve the model performance. In addition, simplify the redundancy layer of the network and achieve lightweight to improve the training efficiency. In the end, the logsoftmax is used for evaluating the effectiveness of the proposed method. The simulation experimental accuracy is up to 99.3220%,which is higher than other five classical deep learning algorithms. The hardware experiment also denotes the engineering practicability of the proposed method.

Recently, magnetic bearings have been widely used in inertial actuators of spacecraft. Aiming at the problem of unbalanced vibration in magnetically suspended system, the research status of active vibration control method is described in detail. Firstly, the structure and working principle of magnetically suspended system are introduced, and the causes of unbalanced vibration are expounded. Then, the research status of active vibration control methods at home and abroad is introduced from two aspects of synchronous vibration and harmonic vibration, and the advantages and disadvantages of each control method are summarized. Finally, the future development trend of active vibration control technology for magnetically suspended system is prospected.

Membrane separation technology has been taken up for use in diverse applications such as water treatment, pharmaceutical, petroleum, and energy-related industries. Compared with the design of membrane materials, the innovation of membrane preparation technique is more urgent for the development of membrane separation technology, because it not only affects physicochemical properties and separation performance of the fabricated membranes, but also determines their potential in industrialized application. Among the various membrane preparation methods, spray technique has recently gained increasing attention because of its low cost, rapidity, scalability, minimum of environmental burden, and viability for nearly unlimited range of materials. In this Review article, we summarized and discussed the recent developments in separation membranes using the spray technique, including the fundamentals, important features and applications. The present challenges and future considerations have been touched to provide inspired insights for developing the sprayed separation membranes.

Abstract Radix Bupleuri (Chaihu in Chinese) is a traditional Chinese medicine commonly used to treat colds and fevers. The root metabolome and transcriptome of two cultivars of B. chinense (BCYC and BCZC) and one of B. scorzonerifolium (BSHC) were determined and analyzed. Compared with BSHC, 135 and 194 differential metabolites were identified in BCYC and BCZC, respectively, which were mainly fatty acyls, organooxygen metabolites. A total of 163 differential metabolites were obtained between BCYC and BCZC, including phenolic acids and lipids. Compared with BSHC, 6557 and 5621 differential expression genes (DEGs) were found in BCYC and BSHC, respectively, which were annotated into biosynthesis of unsaturated fatty acid and fatty acid metabolism. A total of 4,880 DEGs existed between the two cultivars of B. chinense. The abundance of flavonoids in B. scorzonerifolium was higher than that of B. chinense, with the latter having higher saikosaponin A and saikosaponin D than the former. Pinobanksin was the most major flavonoid which differ between the two cultivars of B. chinense. The expression of chalcone synthase gene was dramatically differential, which had a positive correlation with the biosynthesis of pinobanksin. The present study laid a foundation for further research on biosynthesis of flavonoids and terpenoids of Bupleurum L.

Aiming at the influence of the magnetic flux density uniformity error (MFDUE) of the Lorentz force magnetic bearing (LFMB) on the sensitivity accuracy of magnetically suspended control and sensing gyroscopes (MSCSGs) on the angular rate of a spacecraft, a high precision measurement method of the angular rate of a spacecraft based on the MFDUE compensation of LFMB is proposed. Firstly, the structure of MSCSG and the sensitivity principle of MSCSG to the spacecraft angular rate are introduced. The mechanism influencing the accuracy of MSCSG to spacecraft angular rate sensitivity is deduced based on the definition of magnetic flux density uniformity. Secondly, the 3D magnetic flux distribution of LFMB is analyzed using ANSYS. The relationship between the rotor tilt angle, tilt angular rate, and magnetic flux density is established. The induced current calculation model due to MFDUE is proposed, and the LFMB magnetic flux density error compensation is realized. Finally, the simulation results show that the estimation accuracy of the induced current by the proposed method can reach 96%, and the simulation and the experiment show that the error compensation method can improve the accuracy of MSCSG in measuring the spacecraft angular rate by 12.5%.

Chaihu, the dried roots of some species of Bupleurum L., is a famous Chinese herbal medicine for treatment of liver‐ and cold‐related diseases, in which saikosaponins (SSs) are the major active compounds. Many of the genetic components upstream of SS biosynthetic pathways have been characterized; however, the regulatory mechanisms remain elusive. In this study we identified the APETALA2/Ethylene Responsive Factor family transcription factor gene BcERF3 from B. chinense. The expression of BcERF3 was induced in methyl‐jasmonate‐treated adventitious root of B. chinense; it was also expressed at higher levels in roots than in other tissues (stem, leaf, flower, and tender fruit of early fruiting plants). Transient expression of BcERF3 in the leaves of Nicotiana benthamiana resulted in intracellular localization of the protein in the nucleus. It was also demonstrated that the number of SSs was greater in BcERF3‐overexpressing hairy roots of B. chinense than in plants treated with empty vector controls. This coincided with upregulation of β‐AS, which encodes a key enzyme involved with triterpenoid biosynthesis. In conclusion, BcERF3 plays a positive regulatory role in the biosynthesis of SSs.

Participation in the farmland transfer market provides farmers with diversified opportunities which would generate a range of social and economic benefits to improve their overall well-being. However, the previous studies have disproportionately focused on the income increase of farmers’ participation while ignoring its impact on other dimensions significantly contributing to the well-being gap of farmers with different social and economic characteristics. Based on the capability approach, this study constructed a multi-dimensional well-being assessment framework and employed the fuzzy method to evaluate the well-being level of rural households. By employing the national rural survey data from China, this paper examined the impact of farmland transfer participation on the well-being of farmers with different livelihoods. Further, it explored the influence of farmland transfer participation on the well-being gap of farmers by using the quantile regression method. Our results suggest that farmland transfer participation played a positive role in increasing farmers’ well-being, while farmland transfer participation has no significant impact on farmers’ well-being inequality. Meanwhile, the heterogeneity of farmers’ livelihoods is the key factor for the differentiation of farmers’ well-being.

Job satisfaction, resilience, and teacher well-being, as the three major psychological variables emotioncy- based education, have received special attention among English as a foreign language (EFL) researchers. To pursue the line of this inquiry, this particular study aimed to investigate the relationship between Chinese EFL teachers’ job satisfaction, resilience, and their well-being. To conduct the study, 343 Chinese EFL teachers with different academic qualifications, various academic degrees, and different majors voluntarily participated in this study. The results of the study showed that job satisfaction and resilience could jointly predict 56.4 of the variance in psychological well-being. Both variables were the significant predictors of well-being, while job satisfaction was a better predictor, uniquely explaining 29.6 of well-being’s variance. Based on the findings, some pedagogical implication for administrators, educational institutions, and EFL teachers were discussed in the article.

The importance of project governance in curbing opportunistic behavior (OB) has been clearly established in the project literature. Although contract governance and trust are considered critical factors that explain project governance, there is a lack of understanding regarding their interplay at various stages of project development. The current study takes a dynamic perspective and breaks down contract governance into contract completeness (CC) and contract enforcement (CE), while differentiating ex-ante trust from ex-post trust. As such, the current study takes a dynamic perspective and the Grossman-Hart-Moore (GHM) model, which aims to investigate how each of the two facets of contract governance and trust intertwine during the management of construction projects as well as their effects on OB. We undertook a questionnaire survey of individuals involved in 342 construction projects in China, and our research results show that, first of all, governance mechanisms at different stages have different inhibitory effects on OB. Taking contract-signing as the boundary, the governance effect of a contract is gradually enhanced, while the governance effect of trust is gradually reduced. Second, ex-ante trust is more important than ex-post trust: the former moderates not only the relationship between CE and OB, but also the influence of CC on OB. Finally, a contract that is overly complete is not conducive to precluding OB, as such completeness can give the contract parties a sense of security that is guaranteed. The current study not only garners insights into project governance research but also provides implications for architectural practitioners in deploying resources that relate to governance mechanisms.

AbstractMicroRNAs (miRNAs), a class of 22 nucleotide (nt) noncoding RNAs, negatively regulate mRNA posttranscriptional modification in various biological processes. Morphogenesis of skin hair follicles in cashmere goats is a dynamic process involving many key signaling molecules, but the associated cellular biological mechanisms induced by these key signaling molecules have not been reported. In this study, differential expression, bioinformatics, and Gene Ontology/Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on miRNA expression profiles of Inner Mongolian cashmere goats at 45, 55, and 65 days during the fetal period, and chi-miR-370-3p was identified and investigated further. Real-time fluorescence quantification (qRT-PCR), dual luciferase reporting, and Western blotting results showed that transforming growth factor beta receptor 2TGF-βR2fibroblast growth factor receptor 2FGFR2TGF-βR2FGFR2TGF-βR2FGFR2

Metabolic engineering usually focuses on manipulating enzyme(s) within a single pathway. Here, the authors show that a promiscuous enzymatic activity-based multiple-pathway design can minimize cell metabolic burden and allow carbon flow rearrangement, leading to efficient hydroxytyrosol biosynthesis.

Objective This study investigated the expression of genes in cashmere goats at different periods of their fetal development. Methods Bioinformatics analysis was used to evaluate data obtained by transcriptome sequencing of fetus skin samples collected from Inner Mongolia cashmere goats on days 45, 55, and 65 of fetal age. Results We found that FoxN1, FoxE1, and FoxI3 genes of the Fox gene family were probably involved in the growth and development of the follicle and the formation of hair, which is consistent with previous findings. Real-time quantitative polymerase chain reaction detecting system and Western blot analysis were employed to study the relative differentially expressed genes FoxN1, FoxE1, and FoxI3 in the body skin of cashmere goat fetuses and adult individuals. Conclusion This study provided new fundamental information for further investigation of the genes related to follicle development and exploration of their roles in hair follicle initiation, growth, and development.

The rural land rental market is playing an increasingly important role in the agricultural transformation period for developing countries, including China, where rural farmland rental is highly context-specific with the implementation of the collective-owned rural land system; thus, in turn, the access to farmland rental markets for rural households has profoundly influenced their livelihood strategies and income earnings. This paper investigates the income impact differences caused by rural households’ farmland rental participation activities and explores such impact mechanisms by further evaluating the income impacts caused by rental area and household agricultural productivity. Data from the Chinese national household survey were used for estimating the empirical models. Our results show that farmland renting has positively affected households’ on-farm and total income, but there is no significant effect upon off-farm income. According to income differences across quantiles, we find households with high on-farm income are more sensitive about enlarging their farm size by renting farmland, and households with middle and upper-middle off-income may benefit more from renting out their farmland. Furthermore, the joint effects of renting area and household agricultural productivity on lessee households’ farm income is significantly positive. For lessor households, our results indicate that renting out farmland did not improve their off-farm and total income as it may have a limited effect on farm household labor distribution. Our findings suggest that engaging in farmland rental activity can enhance farming productivity efficiency and poverty alleviation among rural households. Under the collective-owned rural land system, it is urgent and necessary to initiate and design incentive policies to encourage highly efficient large farms to expand the farm size and provide smallholders with equal opportunities to engage in farmland rental activities.

This study is to discuss the application of functionalized ionic liquid in fine organic synthesis. Functionalized ionic liquid oligomer is selected as the research object, and its application effect in styrene epoxy reaction is studied. It is found that the size of nanogold particles is in the range of 10nm, and temperature and oxidant dosage will affect the action of functionalized ionic liquid. The styrene conversion rate can reach 100% when the catalyst is under the most reactive conditions. The conclusion has been drawn that the thioether functionalized ionic liquid has the research and application value in the styrene oxidation reaction.

Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that do not generalize well. In this paper, we make an efficient combination of confidence-based Active Learning and Self-Training with the aim of minimizing the need for human annotation for sound classification model training. The proposed method pre-processes the instances that are ready for labeling by calculating their classifier confidence scores, and then delivers the candidates with lower scores to human annotators, and those with high scores are automatically labeled by the machine. We demonstrate the feasibility and efficacy of this method in two practical scenarios: pool-based and stream-based processing. Extensive experimental results indicate that our approach requires significantly less labeled instances to reach the same performance in both scenarios compared to Passive Learning, Active Learning and Self-Training. A reduction of 52.2% in human labeled instances is achieved in both of the pool-based and stream-based scenarios on a sound classification task considering 16,930 sound instances.