Individual sustainability competence development in engineering education: Community interaction open-source learning.

This empirical research creates and assesses a community interaction open-source learning framework. The framework established an efficient open-source learning environment for engineering courses to develop undergraduates' sustainability competencies. The teaching practice of the framework was designed into three stages: course preparation, theory lecture, and project practice. In the teaching practice, community interaction elements were embedded, including community/student two-way selection, systemic teaching and difficulty discussion, expert/student negotiation on teaching forms, teacher/expert coordination on teaching contents, and expert/student two-way feedback on schedules. The interaction elements between students, teachers, and experts enhanced the effectiveness of open-source learning in engineering courses. The experimental results showed that the students exhibited a positive attitude and high participation in the learning procedure and reported a sense of achievement in the project practice. The open-source learning framework significantly improved systemic thinking, conceptual understanding, interdisciplinary collaboration and professional skills. It enhanced students' key sustainability competencies and laid the foundation for them to become expertise-based innovators and open-source community contributors.

A New Strategy for Bearing Health Assessment with a Dynamic Interval Prediction Model.

Bearing is the critical basic component of rotating machinery and its remaining life prediction is very important for mechanical equipment's smooth and healthy operation. However, fast and accurate bearing life prediction has always been a difficult point in industry and academia. This paper proposes a new strategy for bearing health assessment based on a model-driven dynamic interval prediction model. Firstly, the mapping proportion algorithm is used to determine whether the measured data are in the degradation stage. After finding the starting point of prediction, the improved annealing algorithm is used to determine the shortest data interval that can be used for accurate prediction. Then, based on the bearing degradation curve and the information fusion inverse health index, the health index is obtained from 36 general indexes in the time domain and frequency domain through screening, fusion, and inversion. Finally, the state space equation is constructed based on the Paris-DSSM formula and the particle filter is used to iterate the state space equation parameters with the minimum interval data to construct the life prediction model. The proposed method is verified by XJTU-SY rolling bearing life data. The results show that the prediction accuracy of the proposed strategy for the remaining life of the bearing can reach more than 90%. It is verified that the improved simulated annealing algorithm selects limited interval data, reconstructs health indicators based on bearing degradation curve and information fusion, and updates the Paris-DSSM state space equation through the particle filter algorithm. The bearing life prediction model constructed on this basis is accurate and effective.

Approach to the Quantitative Diagnosis of Rolling Bearings Based on Optimized VMD and Lempel-Ziv Complexity under Varying Conditions.

The quantitative diagnosis of rolling bearings is essential to automating maintenance decisions. Over recent years, Lempel-Ziv complexity (LZC) has been widely used for the quantitative assessment of mechanical failures as one of the most valuable indicators for detecting dynamic changes in nonlinear signals. However, LZC focuses on the binary conversion of 0-1 code, which can easily lose some effective information about the time series and cannot fully mine the fault characteristics. Additionally, the immunity of LZC to noise cannot be insured, and it is difficult to quantitatively characterize the fault signal under strong background noise. To overcome these limitations, a quantitative bearing fault diagnosis method based on the optimized Variational Modal Decomposition Lempel-Ziv complexity (VMD-LZC) was developed to fully extract the vibration characteristics and to quantitatively characterize the bearing faults under variable operating conditions. First, to compensate for the deficiency that the main parameters of the variational modal decomposition (VMD) have to be selected by human experience, a genetic algorithm (GA) is used to optimize the parameters of the VMD and adaptively determine the optimal parameters [k, α] of the bearing fault signal. Furthermore, the IMF components that contain the maximum fault information are selected for signal reconstruction based on the Kurtosis theory. The Lempel-Ziv index of the reconstructed signal is calculated and then weighted and summed to obtain the Lempel-Ziv composite index. The experimental results show that the proposed method is of high application value for the quantitative assessment and classification of bearing faults in turbine rolling bearings under various operating conditions such as mild and severe crack faults and variable loads.

Variations in the morphological and chemical composition of the rhizomes of Polygonatum species based on a common garden experiment.

Polygonatum species have great potential in fighting chronic and hidden hunger. In this study, five Polygonatum species collected from different populations were cultivated in a common garden for 4 years. The species mainly differed in yield, saponin and polysaccharide contents, stem diameter, leaf width, inflorescence length, and floret inflorescence length. P. cyrtonema (PC) provides high-quality yield when planted in Zhejiang, with output as high as 7.5 tons per hectare and a promising breeding potential. Moreover, stem diameter can be used as an indicator of the harvest in the screening of varieties. In addition, the formation of plant genetic traits from different provenances is affected by the climatic factors of the origin. Furthermore, near-infrared spectroscopy combined with chemometrics for polysaccharide and saponin quantitation provides a rapid assessment of PC quality. Our findings provide a scientific basis for the development and sustainable utilization of PC as a high-yielding and high-quality forest crop.

[Relative molecular mass distribution and monosaccharide composition of polysaccharides in Polygonatum kingianum var.grandifolium].

Polygonatum kingianum var.grandifolium, different from most Polygonatum species in biological characteristics, sprouts and blooms in spring and autumn, respectively, and it is evergreen in winter.It is difficult to learn from the patterns of other Polygonatum plants because the chemical composition in P.kingianum var.grandifolium changes with phenology, which consequently restricts the production of high-quality medicinal and eatable substances.Samples of P.kingianum var.grandifolium in different months and ages collected from Xiushan, Chongqing were analyzed for polysaccharide content, polysaccharide relative molecular mass, and mono-saccharide composition by anthrone-sulfuric acid colorimetric assay, high-performance gel-permeation chromatography, and trimethylsilane(TMS) derivatization prior to GC-MS.The results showed that the polysaccharide content and composition in the rhizome of P.kingianum var.grandifolium were closely related to the growth period.New shoot sprouting promoted the accumulation of polysaccharides, and flowering and fruiting consumed polysaccharides.The highest polysaccharide content was found in April, reaching 134.04 mg·g~(-1).Polysaccharides in P.kingianum var.grandifolium were divided into five fractions according to the weight-average M_W, i.e., P1(2.02×10~7), P2(5.09×10~6), P3(1.37×10~6), P4(4.73×10~5), and P5(5.11×10~3), and P5 had the highest content.In terms of monosaccharide composition, polysaccharides were mainly composed of fructose, glucose, galactose, mannose, xylose, and arabinose with the average molar ratio of 1.31∶1.00∶0.90∶0.53∶0.22∶0.21.The results of the study provide a scientific basis for the precise harvesting and resource utilization of P.kingianum var.grandifolium.

[Polygonati Rhizoma: a crop with potential of being consumed as food and medicine].

As revealed by the investigation on the name change, biological characteristics, artificial cultivation, and edible history of Polygonatum kingianum var. grandifolium, it was described as a variation pattern of P. kingianum in the Chinese version of Flora of China(1978) and as a variant of P. kingianum in the revised English version of the Flora of China(2000). P. kingianum var. grandifolium, long been consumed as food by local folks, has been widely cultivated in its natural distribution area and circulated as Polygonati Rhizoma in the market. The important biological properties of P. kingianum var. grandifolium make it possess a great potential of being consumed as both medicine and food. The shoots of P. kingianum var. grandifolium sprout immediately out of the ground after seed germination and a new seedling will be formed at the same year, implying that its seedling cultivation period is at least two years shorter than that of P. cyrtonema. It can sprout more than twice a year, and the adult plants always remain evergreen, thereby obtaining higher biomass. Its rhizome biomass can be more than one time higher than that of P. cyrtonema. With reference to the diploid P. cyrtonema, flow cytometry revealed the polyploid and aneuploid forms in natural populations, which were tall and light-adapted with large underground rhizome. It can grow normally under the forest canopy and in the open field. Furthermore, P. kingianum var. grandifolium has important theoretical values for the study of ploidy variation, bud dormancy mechanism, etc.

Decentralized coordinated optimal guaranteed cost control for a roll-to-roll web machine.

This article investigates a coordinated optimal guaranteed cost control (DCOGCC) for a multi-motor roll-to-roll web machine with time-varying and uncertain parameters. The state-space oriented DCOGCC law is designed to ensure that each subsystem of the web machine is stable and the upper bound of performance index is minimum. Linear matrix inequality (LMI) conditions to guarantee the stability of the systems with DCOGCC are derived. A decentralized model is adopted by regarding the entire machine as a synthetic system, then the original decentralized model is transformed into an equivalent one. By choosing appropriate information of consecutive subsystems as coordination variables, the DCOGCC scheme may attenuate the interaction effects between subsystems. The results of some simulations and experiments are given to verify the feasibility and effectiveness of the DCOGCC.

[Epidemiological study on hyperuricemia and gout in Foshan areas, Guangdong province].

OBJECTIVE: To determine the prevalence rates and risk factors of hyperuricemia (HUA) and gout among residents aged over 20 years in Foshan areas. METHODS: A randomly stratified cluster sampling was conducted, and 7403 inhabitants were investigated on their prevalence rates of HUA and gout. RESULTS: (1) The prevalence of HUA was 15.09%, and the standardized rate was 15.27%, in which the prevalence in males was 19.90% and females was 10.54%. The prevalence of gout was 1.04% and the standardized rate was 1.08%, in which the prevalence in males was 1.73% and females was 0.39%. The prevalence of gout in patients with HUA was 6.89%. (2) Average serum uric acid was (336.4 ± 81.5) µmol/L, with (347.1 ± 88.6) µmol/L in males and (289.7 ± 78.6) µmol/L in females. The serum uric acid levels in male patients with HUA was higher than those in women. (3) Age, body mass index, systolic blood pressure, diastolic blood pressure, serum uric acid, blood sugar, triglyceride (TG), total cholesterol were significantly higher in patients with HUA and gout than in the normal group (P < 0.05 - 0.01). The incidence rates of patients with hyperuricemia and gout in the following indices as:overweight and obesity, high blood pressure, high blood sugar were significantly higher than those in the normal group (P < 0.05). Patients having gout in the following indices as age, TG, serum uric acid levels were significantly higher than the HUA group (P < 0.05). (4) Data from non-conditional logistic regression analysis showed that age, overweight, hypertension, diabetes, hyperlipidemia, use of diuretics, family history, alcohol uptake, eating seafood and drinking meat broth, post-menopausal women, and other factors were similar to those factors as patients with hyperuricemia. Tea, fresh vegetables, fruits seemed to be the protective factors. CONCLUSION: Both the prevalence rates of HUA and gout had significantly increased in Foshan areas in recent years. Restricting the intake of food with rich purine, alcohol intake as well as controlling obesity and blood pressure, improving the status of lipid metabolic disorder together with programs as hypertension control etc. were important measures in the strategies on prevention and treatment on hyperuricemia and gout.