How to Keep Brand Fan Page Followers? The Lens of Person Environment Fit Theory

Companies create brand fan pages (BFPs) on social media platforms to broadcast product information, increase brand awareness, and engage customers. A common issue facing BFPs is how to attract and retain followers. When examining this issue, previous research has mostly explored the antecedents of individual’s initial follow or acceptance behavior towards BFPs, without considering the post “follow” stage of BFPs fans. To address this research gap, we develop and validate a theoretical model to explain the antecedents of fans’ continued intention to follow BFPs. Our model is grounded in the theory of person-environment fit (TPEF) to understand how multidimensional fit perceptions play an important role in fans’ continued intention to follow. Data will be collected from active followers of BFPs on Facebook, the most prevalent social media platform in the world, to test the proposed model. Partial least squares method will be employed to assess the relationships in the model

Relationship between serum phosphate and mortality in critically ill children receiving continuous renal replacement therapy

PurposeWe aimed to explore the relationship between serum phosphate concentration and 90-day mortality in critically ill children receiving continuous renal replacement therapy (CRRT).MethodsData from the medical records of children aged <13 years who received CRRT at the Pediatric Intensive Care Unit of Hunan Children's Hospital, China from January 2015 to June 2020 were retrospectively collected. Children were grouped into four categories according to the baseline phosphate concentration before CRRT and mean serum phosphate concentration during CRRT: <0.81 mmol/L (hypophosphatemia), 0.81–1.19 mmol/L, 1.2–2.4 mmol/L (normal phosphate concentration), and >2.4 mmol/L (hyperphosphatemia), with the normal phosphate group serving as the comparator group. The correlation of the serum phosphate concentration before and during CRRT with the 90-day mortality after CRRT initiation was analyzed using logistic regression.ResultsA total of 177 children were included in our study. The mean serum phosphate concentration before CRRT was 1.46 mmol/L (quartiles: 1.04, 2.20). The 90-day mortality rate was increased in children with a serum phosphate concentration >2.4 mmol/L before CRRT (adjusted odds ratio [aOR] 3.74, 95% confidence interval [CI] 1.42–9.86, P = 0.008). The mean serum phosphate concentration during CRRT was 1.2 mmol/L (quartiles: 0.91, 1.49). The 90-day mortality rate was increased in children with a mean serum phosphate concentration >2.4 mmol/L during CRRT (aOR 7.34, 95% CI 1.59–33.88, P = 0.011).ConclusionHyperphosphatemia before and during CRRT predicts a higher 90-day mortality rate

Enhanced bioconversion of hydrogen and carbon dioxide to methane using a micro-nano sparger system: mass balance and energy consumption

Simultaneous CO2 removal with renewable biofuel production can be achieved by methanogens through conversion of CO2 and H2 into CH4. However, the low gas–liquid mass transfer (kLa) of H2 limits the commercial application of this bioconversion. This study tested and compared the gas–liquid mass transfer of H2 by using two stirred tank reactors (STRs) equipped with a micro-nano sparger (MNS) and common micro sparger (CMS), respectively. MNS was found to display superiority to CMS in methane production with the maximum methane evolution rate (MER) of 171.40 mmol/LR/d and 136.10 mmol/LR/d, along with a specific biomass growth rate of 0.15 d−1 and 0.09 d−1, respectively. Energy analysis indicated that the energy-productivity ratio for MNS was higher than that for CMS. This work suggests that MNS can be used as an applicable resolution to the limited kLa of H2 and thus enhance the bioconversion of H2 and CO2 to CH4

RESEARCH ON THE DESIGN METHOD OF THE AEROSPACE STANDARD THIN-WALLED SPECIMEN TO MEASURE THE PRECISION OF MACHINE TOOL

The design and optimization of standard parts to the machine tool is always being the focus of domestic and foreign countries,which is helping for the machine tool inspection and assessment of the performance. In this study,according to the advantages and disadvantages of standard specimen of the universal five-axis NC machine tools,comparing the structural characteristics and machine features for the testing performance of ISO international standard specimen, NASA979 series specimen,"S"shape of the specimen and other specimens. The most characteristics of modern aviation parts are combined to design the "X"form of new aircraft thin-wall standard specimen. By analyzing the "X"shaped aviation thin-walled specimen with the finite element method,the open,close angles and curvature continuity curves are calculated and discussed. Based on the results of finite element analysis,it’s the first time to put forward the processing complexity coefficient concept,compares the cutting force and thermal load,the cutting force dominates in the residual stress generated,this paper only consider the effect of cutting force,to evaluate the characteristics of the"X"shape aviation thin-wall specimen in the geometric model and mechanical structure design in-depth. It proved that "X"shaped aviation thin-wall specimen is better than the other standard specimens in comprehensively reflecting the multi-axis linkage and dynamic stiffness characteristics of the CNC machine possess,showing more comprehensive and superiority in the aspect of detection. All above conclusions provide the scientific basis and effective approach for integrated precision detection characteristic of five-axis CNC machine based on the "X "shaped new aircraft thin-walled standard specimen

A Novel Intelligent Fault Diagnosis Method for Self-Priming Centrifugal Pumps

The real-time diagnostic monitoring of self-priming centrifugal pumps is essential to ensure their safe operation. Nevertheless, owing to the intricate structure and complex operational conditions inherent in such pumps, existing fault diagnosis methods encounter challenges in effectively extracting crucial fault feature information and accurately identifying fault types. Consequently, this paper introduces an intelligent fault diagnosis method tailored for self-priming centrifugal pumps. The approach amalgamates refined time-shift multiscale fluctuation dispersion entropy, cosine pairwise-constrained supervised manifold mapping, and adaptive chaotic Aquila optimization support vector machine techniques. To begin with, refined time-shift multiscale fluctuation dispersion entropy is employed to extract fault-related features, adeptly mitigating concerns related to entropy domain deviations and instability. Subsequently, the application of cosine pairwise-constrained supervised manifold mapping serves to reduce the dimensionality of the extracted fault features, thereby bolstering the efficiency and precision of the ensuing identification process. Ultimately, the utilization of an adaptive chaotic Aquila optimization support vector machine facilitates intelligent fault classification, leading to enhanced accuracy in fault identification. The experimental findings unequivocally affirm the efficacy of the proposed method in accurately discerning among various fault types in self-priming centrifugal pumps, achieving an exceptional recognition rate of 100%. Moreover, it is noteworthy that the average correct recognition rate achieved by the proposed method surpasses that of five existing intelligent fault diagnosis techniques by a significant margin, registering a notable increase of 15.97%

Mathematical Modeling and Machining of the Internal Double-Arc Spiral Bevel Gear by Finger Milling Cutters for the Nutation Drive Mechanism

A method of machining the internal double-arc spiral bevel gear with a finger milling cutter was presented. The mathematical model of the internal spiral bevel gear tooth profile was established considering the principle of machining a spiral bevel gear by the generating method, and a three-dimensional (3D) tooth profile graph was developed. Subsequently, by applying the gear meshing theory, the 3D model of the tooth alignment curve for the finger milling cutter was established. Based on the tooth surface equation of crown gear, the cutter intercept equation was derived. The cutter was divided into four finger milling cutters considering the design difficulty of the cutter, which is used to manufacture different arc segments of the double-arc tooth profile, respectively. The special machining tool model of the internal spiral bevel gear was further developed by using SolidCam, and the simulation experiment was carried out. The simulated gear model was compared with the theoretical gear model and the error of the simulation experiment was estimated. Actual machining on the machine tool and the internal spiral bevel gear were inspected. The maximum error is 0.035 mm, and the minimum error is 0.005 mm. The machining accuracy meets the requirements. The feasibility of machining the internal double-arc spiral bevel gear with a finger milling cutter was verified

Refined Composite Multiscale Fluctuation Dispersion Entropy and Supervised Manifold Mapping for Planetary Gearbox Fault Diagnosis

A novel fault diagnosis scheme was developed to address the difficulty of feature extraction for planetary gearboxes using refined composite multiscale fluctuation dispersion entropy (RCMFDE) and supervised manifold mapping. The RCMFDE was first utilized in this scheme to fully mine fault features from planetary gearbox signals under multiple scales. Subsequently, as a supervised manifold mapping method, supervised isometric mapping (S-Iso) was applied to decrease the dimensions of the original features and remove redundant information. Lastly, the marine predator algorithm-based support vector machine (MPA-SVM) classifier was employed to achieve intelligent fault diagnosis of planetary gearboxes. The suggested RCMFDE combines the composite coarse-grained construction and refined computing technology, overcoming unstable and invalid entropy in the traditional multiscale fluctuation dispersion entropy. Simulation experiments and fault diagnosis experiments from a real planetary gearbox drive system show that the complexity measure capability and feature extraction effectiveness of the proposed RCMFDE outperform the multiscale fluctuation dispersion entropy (MFDE) and multi-scale permutation entropy (MPE). The S-Iso’s visualization results and dimensionality reduction performance are better than principal components analysis (PCA), linear discriminant analysis (LDA), and isometric mapping (Isomap). Moreover, the suggested fault diagnosis scheme has an accuracy rate of 100% in identifying bearing and gear defects in planetary gearboxes

Spatio-Temporal Variations of the Stable H-O Isotopes and Characterization of Mixing Processes between the Mainstream and Tributary of the Three Gorges Reservoir

Understanding the runoff characteristics and interaction processes between the mainstream and its tributaries are an essential issue in watershed and water management. In this paper, hydrogen (δD) and oxygen (δ18O) isotope techniques were used in the mainstream and Zhuyi Bay (ZYB) of the Three Gorges Reservoir (TGR) during the wet and dry seasons in 2015. It revealed that (1) Precipitation was the main source of stream flow compared to the TGR water line with meteoric water line of the Yangtse River basin; (2) The δD and δ18O values exhibited a ‘toward lighter-heavier’ trend along mainstream due to the continuous evaporation effect in the runoff direction, and the fluctuations reflected incoming water from the nearest tributaries. The general trend of d-excess increased with increasing distance from the Three Gorges Dam, which indicated that kinetic fractionation was an important process affecting the isotopic composition. The enrichment effect of isotopes was found in the downstream of TGR; (3) Water mass from the TGR mainstream flowed backward to the confluence zone of ZYB via the middle and bottom layers in the dry season, whereas in the wet season, water reversed through the upper-middle layers due to thermal density flows. This study described and demonstrated that the water cycle of TGR was driven by natural environmental variability and operational system, which will provide valuable information for the water resource management and for controlling the algal blooms in the future