Simplified Aeroelastic Model for Fluid Structure Interaction between Microcantilever Sensors and Fluid Surroundings

Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments.     

Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 1: weighting method

Purpose

Life cycle sustainability assessment is meaningful for the decision-makers/stakeholders to select the most sustainable option among multiple alternatives; however, there are usually various severe uncertainty problems in sustainability-oriented decision-making, i.e., the vagueness and ambiguity that existed in human judgments and the lack of information. This study aims at developing a novel life cycle multi-criteria sustainability assessment method for helping the decision-makers/stakeholders to determine the sustainability level of the industrial and energy systems. In part 1, an improved interval analytic hierarchy process (AHP) which allows multiple decision-makers/stakeholders to participate in the decision-making was developed to determine the weights of the criteria which were used in life cycle sustainability assessment.

Methods

It is usually difficult for the decision-makers/stakeholders to use the numbers from 1 to 9 and their reciprocals for determining the comparison matrix when using the traditional AHP method for weight calculation, because human judgments usually involve various uncertainties. In order to the overcome this weak point of the traditional AHP, an improved AHP, so-called interval AHP, in which, multiple decision-makers/stakeholders are allowed to participate in the decision-making and allowed to use interval numbers instead of crisp numbers to establish the comparison matrix for determining the weights of the criteria for life cycle sustainability assessment, has been developed.

Results and discussion

The proposed method was used to determine the weights of the four aspects for life cycle sustainability assessment including economic, safety, social, and environmental aspects. Five representative stakeholders were invited to participate in the decision-making. After Monte Carlo simulation, the final weights of the four aspects have been determined with the proposed interval AHP.

Conclusions and perspectives

An interval AHP method was developed for determining the weights of the criteria for life cycle sustainability assessment; the decision-makers are allowed to use interval numbers to establish the comparison matrix for weight calculation. The weighting coefficients determined by Monte Carlo method can accurately reflect the preferences and willingness of multi-actor comparing with the traditional AHP method. This paper merely presents a novel method to calculate the weights of the criteria for life cycle sustainability assessment, but the method for determining the sustainability performance has been presented in part 2.

     

Bayesian nonparametric inference for panel count data with an informative observation process

In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is proposed to jointly model the observation process and the recurrent event process. Bayesian nonparametric inference is proposed for simultaneously estimating regression parameters, bivariate frailty effects, and baseline intensity functions. Inference is done through Markov chain Monte Carlo, with fully developed computational techniques. Predictive inference is also discussed under the Bayesian setting. The proposed method is shown to be efficient via simulation studies. A clinical trial dataset on skin cancer patients is analyzed to illustrate the proposed approach.     

The oxalyl‐CoA synthetase‐regulated oxalate and its distinct effects on resistance to bacterial blight and aluminium toxicity in rice

• Oxalic acid is widely distributed in biological systems and known to play functional roles in plants. The gene AAE3 was recently identified to encode an oxalyl‐CoA synthetase (OCS) in Arabidopsis that catalyses the conversion of oxalate and CoA into oxalyl‐CoA. It will be particularly important to characterise the homologous gene in rice since rice is not only a monocotyledonous model plant, but also a staple food crop.
• Various enzymatic and biological methods have been used to characterise the homologous gene.
• We first defined that AAE3 in the rice genome (OsAAE3) also encodes an OCS enzyme. Its K_m for oxalate is 1.73 ± 0.12 mm , and V_m is 6824.9 ± 410.29 U·min^?1·mg protein^?1. Chemical modification and site‐directed mutagenesis analyses identified thiols as the active site residues for rice OCS catalysis, suggesting that the enzyme might be regulated by redox state. Subcellular localisation assay showed that the enzyme is located in the cytosol and predominantly distributed in leaf epidermal cells. As expected, oxalate levels increased when OCS was suppressed in RNAi transgenic plants. More interestingly, OCS‐suppressed plants were more susceptible to bacterial blight but more resistant to Al toxicity.
• The results demonstrate that the OsAAE3‐encoded protein also acts as an OCS in rice, and may play different roles in coping with stresses. These molecular, enzymatic and functional data provide first‐hand information to further clarify the function and mechanism of OCS in rice plants.

     

MoS2‐Based All‐Purpose Fibrous Electrode and Self‐Powering Energy Fiber for Efficient Energy Harvesting and Storage

Here an all‐purpose fibrous electrode based on MoS₂ is demonstrated, which can be employed for versatile energy harvesting and storage applications. In this coaxial electrode, ultrathin MoS₂ nanofilms are grown on TiO₂ nanoparticles coated carbon fiber. The high electrochemical activity of MoS₂ and good conductivity of carbon fiber synergistically lead to the remarkable performances of this novel composite electrode in fibrous dye‐sensitized solar cells (showing a record‐breaking conversion efficiency of 9.5%) and high‐capacity fibrous supercapacitors. Furthermore, a self‐powering energy fiber is fabricated by combining a fibrous dye‐sensitized solar cell and a fibrous supercapacitor into a single device, showing very fast charging capability (charging in 7 s under AM1.5G solar illumination) and an overall photochemical‐electricity energy conversion efficiency as high as 1.8%. In addition, this wire‐shaped electrode can also be used for fibrous Li‐ion batteries and electrocatalytic hydrogen evolution reactions. These applications indicate that the MoS₂‐based all‐purpose fibrous electrode has great potential for the construction of high‐performance flexible and wearable energy devices.     

Promoting acid resistance and nisin yield of <Emphasis Type="Italic">Lactococcus lactis</Emphasis> F44 by genetically increasing D-Asp amidation level inside cell wall

Nisin fermentation by Lactococcus lactis requires a low pH to maintain a relatively higher nisin activity. However, the acidic environment will result in cell arrest, and eventually decrease the relative nisin production. Hence, constructing an acid-resistant L. lactis is crucial for nisin harvest in acidic nisin fermentation. In this paper, the first discovery of the relationship between D-Asp amidation-associated gene (asnH) and acid resistance was reported. Overexpression of asnH in L. lactis F44 (F44A) resulted in a sevenfold increase in survival capacity during acid shift (pH 3) and enhanced nisin desorption capacity compared to F44 (wild type), which subsequently contributed to higher nisin production, reaching 5346 IU/mL, 57.0% more than that of F44 in the fed-batch fermentation. Furthermore, the engineered F44A showed a moderate increase in D-Asp amidation level (from 82 to 92%) compared to F44. The concomitant decrease of the negative charge inside the cell wall was detected by a newly developed method based on the nisin adsorption amount onto cell surface. Meanwhile, peptidoglycan cross-linkage increased from 36.8% (F44) to 41.9% (F44A), and intracellular pH can be better maintained by blocking extracellular H⁺ due to the maintenance of peptidoglycan integrity, which probably resulted from the action of inhibiting hydrolases activity. The inference was further supported by the acmC-overexpression strain F44C, which was characterized by uncontrolled peptidoglycan hydrolase activity. Our results provided a novel strategy for enhancing nisin yield through cell wall remodeling, which contributed to both continuous nisin synthesis and less nisin adsorption in acidic fermentation (dual enhancement).