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Developing microbial consortiums is necessary for microbial enhanced oil recovery (MEOR) in heavy crude oil production. The aqueous phase of produced fluid has long been considered an ideal source of microorganisms for MEOR. However, it is recently found that rich microorganisms (including hydrocarbon-degrading bacteria) are present in the crude oil phase, which is completely different from the aqueous phase of produced fluid. So, in this study, the microbial consortia from the crude oil phase of produced fluids derived from four wells were enriched, respectively. The microbial community structure during passage was dynamically tracked, and the response of enriched consortia to successive disturbance of environmental factors was investigated. The results showed the crude oil phase had high microbial diversity, and the original microbial community structure from four wells was significantly different. After ten generations of consecutive enrichment, different genera were observed in the four enriched microbial consortia, namely, Geobacillus, Bacillus, Brevibacillus, Chelativorans, Ureibacillus, and Ornithinicoccus. In addition, two enriched consortia (eG1614 and eP30) exhibited robustness to temperature and oxygen perturbations. These results further suggested that the crude oil phase of produced fluids can serve as a potential microbial source for MEOR.

Catalytic enantiodifferentiating photoisomerization of cyclooctene (1Z) included and sensitized by regioisomeric 6-O-(o-, m-, and p-methoxybenzoyl)-β-cyclodextrins (CDs) was performed under a variety of solvent conditions for higher enantioselectivities. The enantiomeric excess (ee) of chiral (E)-isomer (1E) produced was a critical function of all the internal and external factors examined, in particular, the sensitizer structure and the solvent conditions, to afford (R)-1Ein record-high ee’s of up to 67% upon sensitization with the meta-substituted β-CD host in water and salt solutions but neither in 50% aqueous ethanol nor with the ortho- and para-substituted hosts. The mechanistic origin of the sudden ee enhancement achieved under the specific conditions is discussed on the basis of the circular dichroism spectral behaviors upon substrate inclusion and the compensatory enthalpy–entropy relationship of the activation parameters for the enantiodifferentiating photoisomerization.

Healing skin wounds with anatomic and functional integrity, especially under chronic pathological conditions, remain an enormous challenge. Due to their outstanding regenerative potential, mesenchymal stem cells (MSCs) have been explored in many studies to determine the healing ability for difficult-to-treat diseases. In this article, we review current animal studies and clinical trials of MSC-based therapy for chronic wounds, and discuss major challenges that confront future clinical applications. We found that a wealth of animal studies have revealed the versatile roles and the benefits of MSCs for chronic wound healing. MSC treatment results in enhanced angiogenesis, facilitated reepithelialization, improved granulation, and accelerated wound closure. There are some evidences of the transdifferentiation of MSCs into skin cells. However, the healing effect of MSCs depends primarily on their paracrine actions, which alleviate the harsh microenvironment of chronic wounds and regulate local cellular responses. Consistent with the findings of preclinical studies, some clinical trials have shown improved wound healing after transplantation of MSCs in chronic wounds, mainly lower extremity ulcers, pressure sores, and radiation burns. However, there are some limitations in these clinical trials, especially a small number of patients and imperfect methodology. Therefore, to better define the safety and efficiency of MSC-based wound therapy, large-scale controlled multicenter trials are needed in the future. In addition, to build a robust pool of clinical evidence, standardized protocols, especially the cultivation and quality control of MSCs, are recommended. Altogether, based on current data, MSC-based therapy represents a promising treatment option for chronic wounds.Impact statementChronic wounds persist as a significant health care problem, particularly with increasing number of patients and the lack of efficient treatments. The main goal of this article is to provide an overview of current status of mesenchymal stem cell (MSC)-based therapy for chronic wounds. The roles of MSCs in skin wound healing, as revealed in a large number of animal studies, are detailed. A critical view is made on the clinical application of MSCs for lower extremity ulcers, pressure sores, and radiation burns. Main challenges that confront future clinical applications are discussed, which hopefully contribute to innovations in MSC-based wound treatment.

Isovalerate is an important intermediate in anaerobic degradation of proteins/amino acids. Little is known about how this compound is degraded due to challenges in cultivation and characterization of isovalerate-degrading bacteria, which are thought to symbiotically depend on methanogenic archaea. In this study, we successfully enriched novel syntrophic isovalerate degraders (uncultivated Clostridiales and Syntrophaceae members) through operation of mesophilic and thermophilic isovalerate-fed anaerobic reactors. Metagenomics- and metatranscriptomics-based metabolic reconstruction of novel putative syntrophic isovalerate metabolizers uncovered the catabolic pathway and byproducts (i.e., acetate, H2, and formate) of isovalerate degradation, mechanisms for electron transduction from isovalerate degradation to H2and formate generation (via electron transfer flavoprotein; ETF), and biosynthetic metabolism. The identified organisms tended to prefer formate-based interspecies electron transfer with methanogenic partners. The byproduct acetate was further converted to CH4and CO2by either Methanothrix(mesophilic) and Methanosarcina(thermophilic), which employed different approaches for acetate degradation. This study presents insights into novel mesophilic and thermophilic isovalerate degraders and their interactions with methanogens.

Collagen membranes are widely used in guided bone regeneration (GBR) because of their good biocompatibility and low immunogenicity. As a bioderived collagen membrane, small intestinal submucosa (SIS) has good regenerative potential for soft tissue repair, but it lacks sufficient mechanical properties for GBR application unless properly modifided. Epigallocatechin-3-gallate (EGCG) is a natural cross-linking agent featuring osteoinductive activity. In this study, we modified SIS by EGCG cross-linking, and such modified materials were characterized both in vitroand in vivo. The results showed that EGCG cross-linking significantly improved the mechanical properties and hydrophilicity of SIS while maintaing good cytocompatibility. Compared to SIS, EGCG-cross-linked SIS (E-SIS) enhanced the adhesion of fibroblasts and preosteoblasts and promoted the osteogenic differentiation of MC3T3-E1 cells cultured on the materials. In a rat cranial defect model, E-SIS material showed better occlusion effect than SIS material. Most importantly, E-SIS material accelerated bone regeneration more than SIS material and even a commercially available GBR membrane. Taken together, we conclude that E-SIS is a promising material as a GBR membrane.

The microbial community structures of two mesophilic anaerobic chemostats, one fed with glucose, the other with starch as sole carbon sources, were studied at various dilution rates (0.05–0.25 d–1for glucose and 0.025–0.1 d–1for starch) during two years continuous operation. In the glucose-fed chemostat, the aceticlastic methanogen Methanosaetaspp. and hydrogenotrophic methanogen Methanoculleusspp. predominated at low dilution rates, whereas Methanosaetaspp. and the hydrogenotrophic Methanobacteriumspp. predominated together when dilution rates were greater than 0.1 d–1. Bacteria affiliated with the phyla Bacteroidetes, Spirochaetes, and Actinobacteria predominated at dilution rates of 0.05, 0.1, and 0.15 d–1, respectively, while Firmicutes predominated at higher dilution rates (0.2 and 0.25 d–1). In the starch-fed chemostat, the aceticlastic and hydrogenotrophic methanogens coexisted at all dilution rates. Although bacteria belonging to only two phyla were mainly responsible for starch degradation (Spirochaetes at the dilution rate of 0.08 d–1and Firmicutes at other dilution rates), different bacterial genera were identified at different dilution rates. With the exception of Archaea in the glucose-fed chemostat, the band patterns revealed by denaturing gradient gel electrophoresis (DGGE) of the microbial communities in the two chemostats displayed marked changes during long-term operation at a constant dilution rate. The bacterial community changed with changes in the dilution rate, and was erratic during longterm operation in both glucose-fed and starch-fed chemostats.

The tradition elevator risk assessment model depends on the expert experience, which causes that the assessment process takes a long time. To deal with this problem, this paper proposes a new risk assessment model which is based on fuzzy analytic hierarchy process (F-AHP) and artificial neural network (ANN). This model is applied to the risk-assessment of elevators. The results show that the assessment time is shorter and the accuracy is not lower, in comparison with the traditional model.

The time-domain energy message conveyed by vibration signals of different gear fault are different, so a method based on local mean decomposition (LMD) and variable predictive model-based class discriminate (VPMCD) is proposed to diagnose gear fault model. The vibration signal of gear which is the research object in this paper is decomposed into a series of product functions (PF) by LMD method. Then a further analysis is to select the PF components which contain main fault information of gear, the energy feature parameters of the selected PF components are used to form a fault feature vector. The variable predictive model-based class discriminate is a new multivariate classification approach for pattern recognition, through taking fully advantages of the fault feature vector. Finally, gear fault diagnosis is distinguished into normal state, inner race fault and outer race fault. The results show that LMD method can decompose a complex non-stationary signal into a number of PF components whose frequency is from high to low. And the method based on LMD and VPMCD has a high fault recognition function by analyzing the fault feature vector of PF.

Empirical mode decomposition (EMD) can extract real time-frequency characteristics from the non-stationary and nonlinear signal. Variable prediction model based class discriminate (VPMCD) is introduced into roller bearing fault diagnosis in this paper. Therefore, a fault diagnosis method based on EMD and VPMCD is put forward in the paper. Firstly, the different feature vectors in the signal are extracted by EMD. Then, different fault models of roller bearing are distinguished by using VPMCD. Finally, an simulation example based on EMD and VPMCD is shown in this paper. The results show that this method can gain very stable classification performance and good computational efficiency.

In order to discover the fault with roller bearing in time, a new fault diagnosis method based on Empirical mode decomposition (EMD) and BP neural network is put forward in the paper. First, we get the fault signal through experiments. Then we use EMD to decompose the vibration signal into a series of single signals. We can extract main fault information from the single signals. The kurtosis coefficient of the single signals forms a feature vector which is used as the input data of the BP neural network. The trained BP neural network can be used for fault identification. Through analyzing, BP neural network can distinguish the fault into normal state, inner race fault, outer race fault. The results show that this method can gain very stable classification performance and good computational efficiency.

As a new nonlinear and non-stationary signal analysis method,local mean decomposition (LMD) has a good adaptability. We decompose the original non-stationary acceleration vibration signals into several stationary production function (PF).But performing LMD will produce end effects which make results distorted. A hidden Markov model (HMM)-based speech recognition system for Chinese spell.After analyzing reasons for end effects of LMD in detail,a new method based on weighted matching similar waveform was proposed.Experiments in speech recognition to the production function as the training model, the more traditional identification method to identify higher rates. LMD is an effective method. It is feasible to extract the feature from speech signals with LMD.

This paper is aimed at the security problems of elevator system.Fuzzy fault tree analytic method is applied to study the reliability of the elevator system.First of all, the elevator system is divided into four subsystems, and then the paper take elevator fall accident as the top event as a example, applying the ascending method for qualitative analysis to find out 7 minimum cut sets in the fault tree and 15 bottom event structure importance sorting. Finally, the fuzzy fault interval probability come out through introducing the concept of fuzzy number in fuzzy set theory, using the triangular fuzzy number to describe the probability of basic event occurrence in the fault tree, making an quantitative interval probability calculation in middle events and top events in the fault tree..The results show that the fuzzy fault tree is an effective and practical method for reliability analysis when we are difficult or unable to obtain the accurate probability of bottom events in terms of the elevator system. Compared with the traditional method of fault tree, the calculated result is more scientific and reasonable, closer to the engineering practice.

This paper constructed the technological innovation ability index system of logistics enterprise, propose causation model to evaluate technology innovation ability of modern logistics enterprise, model and solve the causal relationship among the evaluation indexes by structural equation model, The empirical results show that: this model can correctly describe the causal relationship between the indexes, define key indicators of logistics enterprise technology innovation ability accurately, and determine the main influencing factors, provide scientific basis for evaluating and improving the modern logistics enterprise technology innovation ability.

This paper proposes the index set of safety management of shield metro construction, then realizes the PCA dimension of the 24 indexes in the set. By integrating and restructuring the 9 principal component which we got as the SPSS operate result, the Index System of safety management of shield metro construction is built up. Combined with FUZZY theory, the safety management model of shield metro construction is established. Finally, combined the practical engineering, this paper analyzes the result of safety management, and gives the improvement suggestion against the shield metro construction.

The random amplified polymorphic DNA marker (RAPD) was applied to detect the genetic relationships and diversity among 21 germplasm materials of Kudingcha species in Oleaceae, which involved 8 species, i.e., Ligustrum robustum(Roxb.) Blume, L. henryiHemsl., L. japonicumThunb, L. japonicumThunb. var. pubscensKoidz, L. lucidumAit., L. pedunculareRehd, Osmanthus masumuranusHayata, and L. delavayanmHariot. 20 RAPD primers selected were applied for the amplification on the 21 germplasm materials mentioned above. 427 bands were obtained, and the percentage of polymorphic bands (PPB) was 97.7%. The genetic similarity coefficients (GS) ranged from 0.1522 to 0.8322 with an average of 0.5466. There was a significant genetic difference among germplasm materials of Kudingcha species in Oleaceae, and UPGMA cluster based on the GS of RAPD could distinguish all test germplasm materials clearly and indicated the relationship of the 8 species mentioned above, all of which indicated that RAPD markers could be used for the studies of genetic diversity and relationship and classification of germplasm resources of Kudingcha species in Oleaceae. Analysis results of RAPD showed that L. japonicumThunb. var. pubscensKoidz has closer genetic relationship with L. pedunculareRehd and further genetic relationship with L. japonicumThunb. among all tested species. The authors suggest that further research is needed to study whether L. japonicumThunb. var. pubscensKoidz should be classified into a variata of L. japonicumThunb, or should be considered as an independent species. The analysis results supported that L. pururascensY. C. Yang should be combined into L. robustum(Roxb.) Blume.