*4.2. Mathematical Experiment Modeling*

#### 4.2.1. Physical Model and Meshing

According to the orthogonal tests, it is necessary to establish three physical models with different roadway lengths. The spatial relationship model and grid meshing of the ventilation system are shown in Figure 4. The parameters of each test model are shown in Table 2.

**Figure 4.** Physical model and its meshing.

## 4.2.2. Mathematical Model

There are three basic equations of the fluid numerical simulation, which includes the mass conservation equation, the momentum conservation equation, and the energy conservation equation. After the gas outburst accident in the excavation roadway, the airflow should also be satisfied by gas migration. Furthermore, a chemical component exchange exists in this numerical simulation, i.e., CH4, O2, and N2, so the component transport equation should be introduced.

A turbulent flow is a common flow phenomenon in nature, and the fluid is always in the state of turbulence in most engineering problems. The realizable *k-ε* model is adopted because its good performance for solving the adverse pressure gradient and vortex problems.

## 4.2.3. Boundary Conditions

The boundary conditions of the model are shown in Table 3.

From Table 3, the physical model area is the Fluid Type, and the pressure of operation condition is 101.325 kPa. The inlet boundary condition includes Inlet 1 of the intake airway, Inlet 2 of the return airway, outburst position, and auxiliary fan. The inlet boundary type of auxiliary fan inlet is the Velocity-inlet, and the other is the Pressure-inlet. The species of the outburst position is 100% CH4, and the other is 20% oxygen and 80% nitrogen.

The outlet boundary includes Outlet 1 of the intake airway and Outlet 2 of the return airway, the outlet boundary type is also the Pressure-outlet. Furthermore, the species are 20% oxygen and 80% nitrogen either.

The gauge pressure of each boundary condition is calculated as follows: Assuming that both the sectional area of the return airway and excavation roadway is 25 m2, the friction resistance coefficient is 100 × 10−4, the inlet air quantity of the intake airway and return airway *Q*10 = *Q*20 is 75 m3/s, and the air quantity of the auxiliary fan *Qfan* is 4 m3/s, 10 m3/s, and 20 m3/s, respectively. The outlet of the return airway is *Q*21 = *Q*20 + *Qfan*, *Q*12 = *Q*10 − *Qfan*.

**Table 3.** Boundary conditions of each test.

The relationship between the air resistance and the friction resistance coefficient of the roadway is

$$R = \frac{LIL\alpha}{S^3} \tag{1}$$

where *R* represents the air resistance, kg/m7; *L* represents the length of the roadway, m; *U* represents the perimeter of the roadway section, m; *α* represents coefficient of frictional resistance, kg/m3; *S* represents the sectional area of the roadway, m2.

From Equation (1), the air resistance value of the return airway is *R*10 = *R*12 = *R*20 = *R*21 = 0.0032 kg/m7, the excavation roadway from the air duct outlet to the return airway is *R*31 = 0.0256 kg/m7. The air pressure *H*10 = 16.13 Pa, *H*12 = *H*20 = 18 Pa, *H*21 = 19.97 Pa and the air pressure of the excavation roadway are calculated by the air quantity of the auxiliary fan and the length of the excavation roadway.

Furthermore, the initial gauge total pressure at Inlet 1 is the sum of the pressure difference of the air door and the air pressure of the upper wind side of the intake airway *H*10, and the initial pressure of Outlet 1 is the sum of the pressure difference of air door and *H*12. Suppose the operation pressure is the standard atmospheric pressure (101.325 kPa), the gauge total pressure at Outlet 2 of the return airway is 0 Pa. Then, the air pressure of each inlet and outlet are calculated as shown in Table 3.

#### 4.2.4. Controlling Parameters of Fluid Dynamics

(1) Solver

In the Pressure-based type, the absolute velocity formulation and Pressure-velocity coupling algorithm are usually adopted to solve the problem. Furthermore, using the SIMPLE scheme to calculate the mathematical model, it computes the mass conservation and obtains the pressure field by the mutual correction of pressure and velocity.

(2) Convergence accuracy

A reasonable accuracy is an important parameter to ensure the convergence of the model. The convergence residuals are 10−6 in this model, and the number of iterations is 500, so the calculation will be finished when the residuals of each variable are less than 10−6 or the iterations reach to 500 steps. Furthermore, the convergence of the calculation results can be dynamically monitored by checking the iterative residual of each variable.

#### *4.3. Results of Numerical Simulation*

Using Fluent numerical simulation software, the flow field distributions of the outburst gas of the above nine tests are simulated. Figure 5 illustrates the path-line near the air door of each test on the horizontal plane 1 m away from the floor, which is colored by the velocity magnitude.

**Figure 5.** Color map of velocity path-line near the air door.

From Figure 5, the air velocity of L3 is the highest near the air door after the gas burst accident, followed by L2 and L1, and L7 is the smallest. The excavation roadway length of L1, L2, and L3 is 200 m, which has the greatest air velocity magnitude. The larger air velocity has a greater impact on the ventilation system, especially in the air inlet part. Figures 6 and 7 show the air velocity distributions of the two inlet boundaries.

**Figure 6.** Air velocity of Inlet 2 of the return airway.

**Figure 7.** Air velocity of Inlet 1 of the intake airway.

As can be seen from the contour map in Figures 6 and 7, all inlet boundaries are reversed in each test, and the air velocity of Inlet 2 is larger than Inlet 1. Therefore, the influence of the gas outburst accident on the return air system is greater than that on the inlet air system. Extracting the maximum air velocity of the section, the airflow reversal degree is calculated, as shown in Table 4. Meanwhile, the variation curve of air velocity and airflow reversal degree is shown in Figure 8.

**Table 4.** Air velocity and airflow reversal degree of the inlet boundary.

**Figure 8.** Variation of air velocity and airflow reversal degree.

From Table 4 and Figure 8, the airflow reversal degree of Inlet 2 is larger than Inlet 1, that is, because the air pressure distribution of the ventilation system can restrain the outburst gas, and the air pressure variation of the intake airway is smaller than the return airway.

The numerical simulation results show that the airflow reversal degree of 200 m roadway is greater than that of 1000 m roadway and 2000 m roadway. Therefore, the airflow reversal degree decreases with the increase of the roadway length. Furthermore, the outburst air flow pressure of L3, L6, and L9 is 0.3 MPa, and the absolute value of their airflow reversal degree is greater than the outburst pressure of 0.1 MPa and 0.2 MPa in the same length of the excavation roadway. Therefore, the airflow reversal degree increases with the increase of the outburst pressure and the outburst energy.

#### **5. Comprehensive Evaluation of Airflow Disorder**

#### *5.1. Fuzzy Comprehensive Optimization Theory*

According to the main factors that affect the safety and stability of the ventilation system as well as the basic data of orthogonal experiments, the air quantity of the auxiliary fan, the air pressure difference of the air door, and the air flow reversal degree of Inlet 1 and Inlet 2 are used to establish the evaluation model of the airflow disorder on the basis of variable fuzzy theory.

Assuming F = {*Fij*}, *i* = 1,. ... , *m*, *j* = 1,. ... , *n* indicates that the parameter of the *m* test model corresponds to the set of evaluation factors of *n.* Here, *m* = 4. The method of relative membership is adopted to deal with the initial data. There are three situations,

(a) The larger the better

$$Fr\_{ij} = \frac{F\_{ij} - \min\_{1 \le i \le m} \{ F\_{ij} \}}{\max\_{1 \le i \le m} \{ F\_{ij} \} - \min\_{1 \le i \le m} \{ F\_{ij} \}} \tag{2}$$

where *Frij* is the relative membership of the set *Fij* and its range is [0, 1]; max {} indicates the maximum value of the set; min {} indicates the minimum value of the set.

(b) The smaller the better

$$Fr\_{ij} = \frac{\max\_{1 \le i \le m} \{ F\_{ij} \} - F\_{ij}}{\max\_{1 \le i \le m} \{ F\_{ij} \} - \min\_{1 \le i \le m} \{ F\_{ij} \}} \tag{3}$$

(c) The value is equal to 1

$$Fr\_{i\rangle} = 1, \left(F\_{1\rangle} = F\_{2\rangle} = \dots \dots = F\_{mj}\right) \tag{4}$$

The fuzzy partition matrix is defined as follows,

$$\mathcal{U} = \begin{bmatrix} \mu\_{11} & \mu\_{12} & \dots & \mu\_{1m} \\ \mu\_{21} & \mu\_{22} & \dots & \mu\_{2m} \end{bmatrix} = \begin{bmatrix} \mu\_{1i} \\ \mu\_{2i} \end{bmatrix} \tag{5}$$

where *u*1*i* is subordinate to the superior index and *u*2*i* is the inferior index, 2 ∑ *k*=1 *uki* = 1, *uki* ∈ [0, 1].

The objective function is the minimal sum of the weight difference squared of the *m* models.

$$\min f(u\_{1i}) = \sum\_{i=1}^{m} \left( \left( u\_{1i} \sqrt{\sum\_{j=1}^{4} \left[ \omega\_j (gr\_j - Fr\_{ij}) \right]^2} \right)^2 + \left( u\_{2i} \sqrt{\sum\_{j=1}^{4} \left[ \omega\_j \left( Fr\_{ij} - br\_j \right) \right]^2} \right)^2 \right) \tag{6}$$

where *ωj* is the weight of each factor; *grj* represents the standard superior membership, which is the optimal value of evaluation factor *j*; *brj* represents the standard inferior subordinate, which is the worst value of evaluation factor *j*.

Supposing *d f*(*u*1*i*) *du*1*i* = 0, the optimal fuzzy partition matrix is calculated. Then, the influence of different factors is evaluated by *u*1*i*.

#### *5.2. Quantification and Weight Analysis of the Factors*

#### 5.2.1. Factors

The pressure difference of the air door has a strong inhibition of the outburst energy, which belongs to situation (a). The greater the pressure difference of the air door, the greater the pressure energy of the air inlet roadway. The air quantity of the auxiliary fan belongs to situation (a). Because it is opposite to the direction of the outburst gas, the resistance to the migration of the outburst gas increases with the larger air quantity of the auxiliary fan. The airflow reversal degree of Inlet 1 and Inlet 2 also belongs to situation (a), the larger the better.

The above factors consist of the *F* matrix.

#### 5.2.2. Weight

Since the airflow reversal degree is more important than the pressure difference of air door and the air quantity of the auxiliary fan, the weight of the airflow reversal degree is 0.4 and 0.4, respectively, at Inlet 1 and Inlet 2. The weight of the pressure difference of the air door is equal to the air quantity of the auxiliary fan, their value is 0.1, respectively. Then the weight vector *ωj* = (0.1, 0.1, 0.4, 0.4)T.

#### *5.3. Results and Discussion*

The fuzzy comprehensive optimization theory is used to evaluate the airflow disorder degree of the mine ventilation network after a gas outburst accident. From Tables 1 and 4, the max {*Fij*} = (1500, 1200, −19.50, −7.22)T, min {*Fij*} = (500, 240, −85.23, −46.77)T. The membership vector of nine groups is calculated by Equations (2)–(6), *u*1*i* = (0.4928, 2.2160, 23.5568, 0.1586, 0.0394, 0.3398, 0, 0.0746, 0.1209). The values of each factor and evaluation results are shown in Figure 9.

**Figure 9.** The evaluation results of each test.

From Figure 9, the evaluation result of L3 is the largest, illustrating that this parameter condition has the strongest influence on the ventilation system, and L7 is the smallest. In L3, the length of excavation roadway is 200 m, the outburst pressure is 0.3 MPa, the pressure difference of air door is 1500 Pa, and the air quantity of the auxiliary fan is 600 m3/min. In L7, the length of the excavation roadway is 2000 m, the outburst pressure is 0.1 MPa, the pressure difference of air door is 1500 Pa, and the air quantity of the auxiliary fan is 1200 m3/min.

According to the extreme difference of the range analysis method, the results of the orthogonal experiment are determined. The extreme difference is the difference between the maximum and minimum value of the airflow disorder of each factor. With the increase of the influence range, the disturbance degree of the factor increases. The result is shown in Table 5 and Figure 10. *Ki* represents the sum of levels of factor *i*; *ki* represents the average value of the levels of factor; *R* represents the polar difference.

**Table 5.** Range analysis of the orthogonal experiment.

**Figure 10.** Range analysis of the orthogonal experiment.

From Figure 10, A > B > D > C, the length of the excavation roadway and the outburst pressure are relatively important factors affecting the ventilation system. The airflow reversal degree of the ventilation system increases with the increase of the outburst pressure or the decrease of the length of the excavation roadway.

The energy is continuously attenuated while the outburst gas migrates in the roadway. Adopting the method of reducing the air resistance of the airway or changing the air pressure distribution of the main fans, the initial air pressure in both the roadway and its parallel roadway is easily affected and will be increased in a gas outburst accident. Meanwhile, it will contribute to increase the total air quantity and improve the kinetic energy of the airflow under the condition of the constant capacity of the main fans, so it is harder to reverse the airflow.

#### **6. Conclusions**

This paper analyzes the reversal principle of airflow induced by a coal and gas outburst in the excavation roadway and proposes the indexes of the airflow disorder. Through an orthogonal experiment, it is found that all the inlet boundaries are reversed in each test, and the air velocity of Inlet 2 is larger than Inlet 1, indicating that the influence of the gas outburst accident on the return air system is greater than that on the inlet air system. Moreover, the larger air velocity has a greater impact on the ventilation system, especially the air inlet part.

On the basis of the fuzzy comprehensive optimization theory, the evaluation model of the airflow disorder is established. The results show that the order of effect factors for the stability of the mine ventilation system are the length of excavation roadway > outburst pressure > pressure difference of air door > air quantity of auxiliary fan. The most influential result is that the length of the excavation roadway is 200 m, the outburst pressure is 0.3 MPa, the pressure difference of the air door is 1500 Pa, and the air quantity of the auxiliary fan is 600 m3/min. The airflow reversal degree of the ventilation system increases with the increase of the outburst pressure or decreases with the length of the excavation roadway.

**Author Contributions:** Methodology, J.S.; software, Y.W.; formal analysis, J.C.; investigation, L.L.; resources, J.S., W.H., L.L. and T.L.; data curation, J.S.; writing—original draft preparation, L.L.; writing—review and editing, J.S., J.C. and Z.L.; supervision, J.C. and Y.W.; project administration, J.S.; funding acquisition, J.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by "the Fundamental Research Funds for the National Natural Science Foundation of China" (51804120, 52074122), "the National Key Research Project of China" (2018YFC08080306), "the Fundamental Research Funds for the Central Universities"<PHONE_NUMBER>) and Science and Technology Research Project of Higher Education in Hebei Province (Z2018004).

**Acknowledgments:** The authors would like to thank the anonymous referees for their thoughtful comments and suggested edits that have improved the rigor and presentation of this work.

**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

#### **References**


3.5.3. Sensitivity Analysis

After excluding one study in the sensitivity analysis, (1) BEEV showed a tendency to be most effective in all 16 analyses; (2) in three sensitivity analyses (when excluding [40,44,47]), the ranking between MANU and ELEC was changed, with ELEC showing a better effect; and (3) CONV tended to have the smallest effect size throughout the analysis (Supplementary Materials Digital Content 6).


*5.4. Marine/Saline Environments*

Covering more than roughly 78% of the earth's surface, water is the most prevalent natural substance, of which approximately 97.5% is salt water in the world's oceans [96]. The salt tolerance of myxobacteria is low in general. It was assumed for a long time that myxobacteria exclusively live in terrestrial habitats. Indeed, even in 1963, Brockman observed fruiting myxobacteria in sand samples from an ocean beach in South Carolina [97]. Species of the already known terrestrial genera *Archangium*, *Chondrococcus* (*Corallococcus*), *Chondromyces*, *Myxococcus*, and *Polyangium*, could be cultivated. As late as 2002 with *Haliangium ochraceum* and *H. tepidum*, the first myxobacterial genus was isolated and described from coastal salt marshes. The strains differ from known terrestrial myxobacteria with regard to salt requirements (2–3% NaCl) and the presence of anteiso-branched fatty acids [4]. Other genera, exclusively detected in marine habitats like *Plesiocystis* [5], *Enhygromyxa* [6], and *Pseudenhygromyxa* [7] (all Nannocystineae-suborder) followed (Figure 9).

**Figure 9.** Marine myxobacterial type strains on agar plates. (**a**) *Haliangium tepidum* (DSM 14436T) on VY/2SWS, (**b**) *Enhygromyxa salina* (DSM 15217T) on VY/4SWS, (**c**) *Pseudenhygromyxa salsuginis* (DSM 21377T) on 1102, (**d**) *Plesiocystis pacifica* (DSM 14875T) on VY/2SWS.

In 2010, Jiang et al. investigated the diversity of marine myxobacteria in comparison to terrestrial soil myxobacteria [82]. Therefore, they established myxobacteria enriched libraries of 16S rRNA gene sequences from four deep-sea sediments and a hydrothermal vent and identified 68 different myxobacteria related sequences from randomly sequenced clones of these libraries. The authors concluded that the myxobacterial sequences were diverse but phylogenetically similar at different locations and depths. However, they separate from terrestrial myxobacteria at high levels of classification.

In 2012, the study of Brinkhoff and co-workers gave an impressive insight to the marine myxobacterial community [83]. They detected a cluster of exclusively marine myxobacteria (marine myxobacteria cluster, MMC) in sediments of the North Sea, but not in the limnetic section of the Weser estuary and other freshwater habitats. In a quantitative real-time PCR approach, the authors found out that the MMC constituted up to 13% of total bacterial 16S rRNA genes in surface sediments of the North Sea. In addition, in a global survey including sediments from the Mediterranean Sea, the Atlantic, Pacific, and Indian Oceans, and various climatic regions, the MMC appears in most samples and to a water depth of 4300 m, but there was no synteny to other myxobacterial genomes. The study of Brinkhoff et al. showed that the MMC is an important and widely distributed but largely unknown component of marine sediment-associated bacterial communities. Figure 10 shows some representative clones from different marine habitats mentioned in the Brinkhoff study. The 17 clones show 95.1–100% similarity to each other and 88–91% to the next type strain *Sandaracinus amylolyticus.* This implies that members of the MMC cluster do at least belong to new genera if not even families, but presumably belong to the Sorangiineae suborder. However, the genus *Sandaracinus* was published shortly after the Brinkhoff study, so this relative was not mentioned there.

In 2013, Zhang et al. isolated fifty-eight terrestrial and salt-tolerant myxobacteria from the saline-alkaline soils collected from Xinjiang, China [95]. Based on morphology and 16S rRNA gene sequences, the authors identified species of *Myxococcus*, *Cystobacter*, *Corallococcus*, *Sorangium*, *Nannocystis*, and *Polyangium*. They reported that all the strains grew better with 1% NaCl than without salt; some *Myxococcus* strains even grow with 2% NaCl.

Li et al. (2014) chose a cultivation-independent approach to analyze the diversity of myxobacteria from saline-alkaline soils of Xinjiang, China, too. A semi-nested PCR-denaturing gradient gel electrophoresis (DGGE) based on the taxon-specific gene mglA (a key gene involved in gliding motility) was used [98]. In accordance to previous studies, Li et al. also suggested that there are still many viable, but under standard laboratory conditions uncultured myxobacterial strains in the investigated saline-alkaline habitat. Natural product classes discovered from marine Myxococcales strains include polyketides, hybrid polyketide-nonribosomal peptides, degraded sterols, diterpenes, cyclic depsipeptides, and alkylidenebutenolides [99]. Four genera of marine/saline origin are known so far (Figure 10) and from two, *Haliangium* and *Enhygromyxa*, numerous (bioactive) secondary metabolites could be isolated [100]: Haliangicin [101], salimabromide [102], salimyxins, enhygrolides [103], and haliamide [104]. The above-mentioned data reveal that marine/saline environments as oceans harbor

an enormous potential of new myxobacteria. These organisms are an unexplored resource of novel antibiotics of novel chemical scaffolds, as mentioned by Albataineh and Stevens, who highlighted the need for continued discovery and exploration of marine myxobacteria as producers of novel natural products [104].

**Figure 10.** Neighbour joining tree of myxobacterial type strains (16S rRNA-genes), some representative clones from the MMC-cluster (blue) and the next cultivated relative *Sandaracinus amylolyticus*. Genera isolated from marine environment are in green blue. Suborders of the order Myxococcales, origin of clones, and accession numbers are shown. Bar, 0.1 substitutions per nucleotide position.

#### *5.5. Facultative or Strictly Anaerobic Myxobacteria*

All known myxobacteria live aerobically, with one exception: The facultative-anaerobic genus *Anaeromyxobacter* comprises one species, *A. dehalogenans.* The type strain was isolated from stream sediment and grows with acetate as electron donor and 2-chlorophenol (2-CPh) as electron acceptor [11]. Since 2002, several strains of *Anaeromyxobacter* were isolated from various habitats. Flooded rice field soil [105], uranium contaminated surface environment [106], corrosion material of drinking water pipelines [107], arsenic-contaminated soils [108], or chemically and electro-chemically enriched sodic-saline soil (unpublished) served as sources for the cultivation of *Anaeromyxobacter*-strains. A total of 23 sequences designated as *Anaeromyxobacter* (sequence lengths > 1000 bp) are available from the NCBI database (FJ90053–FJ90062, FJ90048, FJ90049, FJ90051, EF067314, AJ504438, KF952446, AF382397, AF382399, AF382400, FJ939131, KF952441, KF952438, KC921178) and were added to a phylogenetic tree of myxobacterial type strains. A similarity matrix calculated with arb (www.arb-home.de) revealed 98.4–100% similarity (on basis of 16S rRNA gene) for 20 of these strains to the type strain of *A. dehalogenans*. Assuming that the standard value for the definition of a new species is 98.65% [109] and 94% for a new genus, respectively, the above-mentioned 20 cultures probably do belong to *A. dehalogenans*. However, strains OnlyC-B2 (KF952441) and SSS-B8 (KF952438) show only 96.3% and 96.0% similarity to the corresponding type strain (but 99.4% to each other) and putatively represent a new species. One culture, isolated from ginger foundation soil, and also designated as *A. dehalogenans* (KC921178), shows only 86% similarity to the next cultivated (myxobacterial) type strain *Vulgatibacter incomptus*. This culture definitely represents at least a new family if not even a new suborder of myxobacteria (unpublished).

In summary, there are currently two cultivated species of *Anaeromyxobacter,* but only one is validly described. But what about further facultative or even strictly anaerobic myxobacteria?

The NCBI search for 16S rRNA gene sequences of "uncultured *Anaeromyxobacter*" revealed more than 1200 hits. Nevertheless, not all sequences designated as "Uncultured *Anaeromyxobacter*" are close relatives of *Anaeromyxobacter*, as a revision of randomly selected sequences revealed. For example: the

sequence GU271851, mentioned as "Uncultured *Anaeromyxobacter*", shows 91% similarity to the next type strain *Haliangium tepidum,* but only 87% to the type strain of *A. dehalogenans* [110]. Clone GU271788, also mentioned as *A. dehalogenans*, shows 92% to the next type strain, *Sorangium cellulosum*, but only 86% to *Anaeromyxobacter* [111]. On the other hand, there are probably numerous sequences deposited at NCBI which are close relatives of *Anaeromyxobacter*. However, these sequences are just mentioned as "uncultivated Myxococcales", "uncultivated (delta) proteobacteria" or "uncultured bacterium clone" such as clone EUB\_19 (FJ189540), which shows 98.7% [112] or clone A\_Ac-2\_16 (EU307085), which shows 97.8% similarity to the next type strain: *A. dehalogenans* [113]. In 2009, Thomas et al. analysed the diversity and distribution of *Anaeromyxobacter* strains in a uranium-contaminated environment by mainly cultivation-independent methods. Phylogenetic analyses of the clone and culture sequences revealed that there are at least three distinct *Anaeromyxobacter* clusters at the IFC (Integrated Field-Scale Subsurface Research Challenge) site near Oak Ridge, whereby two sides are exclusively represented by clones. As mentioned above, quantitative PCR assay and pyrosequencing analysis of 16S rRNA genes also revealed *A. dehalogenans* as a part of the microbial community in the sediment of Poyang Lake, the largest freshwater lake in China [95].

To get an impression about the diversity of uncultured *Anaeromyxobacter*, I added about 80 clone sequences from NCBI with corresponding designation to a phylogenetic tree of myxobacterial type strains (data not shown). The clones revealed 90.0–100% similarity on the basis of 16S rRNA gene to the type strain of *A. dehalogenans* (AF382396). Figure 11 shows the affiliation of some representative clones. These clones represent at least several new genera, if not even families of myxobacteria, which are probably also facultative or strictly anaerobic and which could not be cultivated so far.

Although the 16S affiliation of clones does not give any information about metabolism of the corresponding organism, high similarities to aerobic or anaerobic cultures indicate similar metabolic capabilities. However, no bioactive secondary metabolites have been described so far from *Anaeromyxobacter* strains, which is certainly because anaerobic isolation, cultivation, and large scale fermentation requires special efforts regarding equipment and microbiological skills and experience.


**2. Background on Bitcoin**

Bitcoin is a unique digital currency with the potential to change the nature of the transactions that people conduct in digital space. Bitcoin enables consumers for the first time to make electronic transactions from person to person without the need for an intermediary between them, like cash (Brito 2014). Transactions conducted in the digital space with BTC allow individuals to push payments directly to the merchants without having to share personally identifiable information, which could be intercepted by cybercriminals for fraud. One of the greatest concerns for BTC as a commonly accepted currency is the security, as there is no intermediary to ensure the coverage on stolen BTC, should theft occur (Brito 2014). As the value of the asset appreciated 63% YTD in 2016, and 87% YTD in 2020, identifying historical patterns of behavior could help in understanding how the BTC security (and the security of similar cryptocurrencies) is likely to behave from inception.


**2. Endovascular treatment**

The first report of embolization of an AVM was published by Luessenhop and Spence et al. in 1960 [18] who used methyl methacrylate pellets after a direct carotid puncture. Selective catheterization of the intracranial circulation with microcatheters was first described by Serbinenko et al. [19] and Kerber. Further evolution has occurred with the use of new liquid embolic agents like cyanoacrylate by Drake et al. [20] and Debrun et al. [21]. After years of embolization with N-butyl cyanoacrylate, introduction of a new agent composed of ethylene vinyl alcohol polymer (Onyx, Medtronic, Irvine, CA, USA) has changed the practice of AVMs once more.

Endovascular treatment of cerebral AVMs can be used before open surgery, before radiosurgery, for cure as a stand-alone treatment, to target the weak angioarchitectural points, or for palliative purposes. The advantages of endovascular treatment include minimally invasiveness, immediate angiographic evaluation during and after the treatment, and immediate occlusive effect. Angiography is the gold standard for the diagnosis and treatment planning for AVMs. Angiograms show the location, size, and number of arterial feeders and draining veins and locate weak points such as intranidal aneurysms, flow-related aneurysms, venous drainage stenosis, ectasia, or aneurysm of the draining veins. These angioarchitectural characteristics lead to decision on the treatment strategy for a specific AVM including surgical, endovascular, or radiosurgical techniques.


*4.1. Plant Materials and Growth Conditions*

Japonica type rice cultivar Nipponbare (*Oryza sativa* L.) was grown in commercial nursery soil (Bonsol Number 2; Sumitomo Chemical Corp., Tokyo, Japan) in a greenhouse at 28 ◦C (day)/23 ◦ C (night) with ca. 50% relative humidity.


*5.4. FtsHi4*

In addition to its suborganellar location in the chloroplast envelope [19,58,59], FtsHi4 was also identified as a thylakoid membrane-associated protein [73]. If FtsHi4 indeed is dual-targeted to the envelope and the thylakoid membrane or if this result is due to antibody cross-reaction (as shown for FtsH11 [40]) or impurity of the preparation (in the study, no envelope marker protein was used to examine the purity of the thylakoid fraction [73]) remains to be shown. Ubiquitous transcript levels of *FTSHi4* were detected in all organs of 40-day-old wild-type plants. The lowest *FTSHi4* transcripts were present in roots; transcripts were most abundant in young leaves [73]. *A. thaliana* mutants depleted of FtsHi4 display embryo lethality and disrupted thylakoid formation. Heterozygous *ftshi4/FTSHi4* plants exhibit abnormal division pattern within the same silique, with 80% wild-type embryos reaching maturity and 20% arresting at the heart-shaped stage. Then, albino and green seeds are distributed in developing siliques [73]. These results imply that even FtsHi4 can be substituted in the FtsH12/FtsHi complex. Gene expression of *FTSHi2* and *FTSHi3* was enhanced in homozygous *ftshi4-2* mutants compared to WT [26], while on the protein level, the amount of FtsH12 was slightly diminished in the mutant [65].

Significantly lower numbers of seeds per siliques were observed in *ftshi4/FTSHi4- 1* mutants grown under semi-natural conditions. These heterozygous *ftshi4/FTSHi4-1* plants [26] and RNAi-FtsHi4 mutant plants [69] are smaller than WT; their cotyledons have white and yellowish leaves. Six-week-old *ftshi4-2* mutant plants exhibited pale phenotypes compared to WT when exposed to cold stress under short-day conditions [26].


**5.3 Surface condition**

408 Microelectromechanical Systems and Devices

because the electric power was removed suddenly thus the display area did not 100% return to its original state. A study done with a periodical electric power supply which continuously switched between two polarities and thus the charges could be removed and the upper layer could return back to the original state. The electrodes with accumulated charges were further supported with more and more charges under the cumulative stress test, thus the display area expanded larger and larger. Some solutions for this reliability

In order to obtain high and solid insulating material in a roll-to-roll process system, a sputter process is necessary and the sputter still matches the mass production requirement as the metal sputter process does. To continuously include the isolation layer sputter in the same apparatus of metal target can further reduce the process time (vacuum pumping) and

Since the highest working temperature of plastic material is normally lower than 200°C, the over 350°C curing temperature for SiO2 curing is not acceptable. This issue can be solved by replacing the plastic substrate by glass. Even though the glass substrate is fragile for shear stress, it can be made thin and thus flexible. Section 3.1 gave one example of how thin, how

Either the sputtered SiO2 or the completely cured SiO2 ink will not solve the profound impact of electrostatic adhesion between upper electrode layer and the isolation layer. As a result, the sputtered SiO2 or the completely cured SiO2 ink will still degrade owing to the detachment of electrode material from the upper substrate. To prevent the electrode material from detaching from its substrate, a good solution is to cover the electrode with the isolation material. When this device is ON, the combinational thickness matches the color design value in the second section and the output color is expected to be the same. However, as summarized in Table 8, the OFF state non interfered color needs to be specially designed. The thickness in this table was easily divided the isolation layers into equivalent two parts from its originally designed value. Compared to the data for single layer, the data for double layer will form a larger triangle which is a drawback explained

Red=160 (0.30, 0.24)

Blue=245 (0.22, 0.26)

CIE coordinate when OFF

Green=325 (0.25, 0.26) ---

Red=80×2 (0.32, 0.24) acceptable Green=162×2 (0.29, 0.21) acceptable Blue=122×2 (0.23, 0.44) large

Difference

issue are thus proposed in three ways:

**B. Complete drying and curing process**

large, and how flexible can the thin glass be.

Structure Isolation layer

thickness (nm)

Table 8. OFF color difference from single and double layer designs.

the equipment space (add one target instead of add a machine).

**A. Solid isolation material**

**C. Doubled isolation layers**

in section 4.1.

Single layer

Double layer

Previously study concluded that the surface unevenness was the root cause for the poor color purity. The reference also concluded that the same issue caused the isolation breakdown. Furthermore, the surface unevenness structures distributed on the substrate surface mentioned in the reference were dense and uniformly spread on the substrate, the color interference of the defects then should not be as uniform as the data disclosed in the same reference. But even though the hypothesis was not correct, this surface defect should be eliminated. Figure 40 is the surface profile analyzed by atomic force microscope (AFM, SII NanoTechnology Inc., Nanopics). Here *Rq* is the root mean square value of measured data. The surface condition was monitored (a) before metal electrode sputtering, (b) after metal electrode sputtering, (c) after pattern lift-off, and (d) after isolation layer printing. There was no significant difference for the first three steps which suggested the substrate's profile was always inherited and followed from layer to layer until the SiO2 was capped. Compared to the sputter and lift-off process, the gravure SiO2 printing and the following drying and curing processes covered all these surface defects. The SiO2 droplets transferred out from the gravure cylinder reflowed, spread, and finally merged before drying process provided a more uniform surface than the original substrate did. Thus the printing rheology is a key point for study.

Fig. 40. Surface profile after different processes.