**3. Applications of porous graphene materials**

Unique porous structure of graphene along with its superior properties makes graphene a potential candidate for energy storage and conversion applications. The following sections review several key applications of porous graphene in LIBs, Li-S batteries, supercapacitors, and the dye-sensitized solar cells.

#### **3.1. Lithium-ion batteries**

Lithium-ion battery has a widespread increasing demand because of its high energy density, flexibility, low maintenance, and longer lifespan compared with other battery technologies [62]. To further increase the energy density, charging efficiency, and cycle life of lithium-ion batteries, it is essential to look at new electrode materials that have good lithium storage capability. Porous graphene with exceptional properties holds a great potential as an electrode material for the lithium-ion battery. The high surface area of graphene can significantly increase the diffusion of lithium ions and electrons. Furthermore, the superior electrical conductivity provides a good conductive network within the electrodes. Graphene can construct a 3D framework with a strong tolerance to the volume change of electrochemically active materials during charge-discharge cycles [63].

An anode material for Li-ion battery was made by hierarchical mesoporous and macroporous carbon using the spinodal decomposition of a mesophase pitch (MP) carbon precursor and polystyrene as a soft template [64]. Scanning Electron Microscope (SEM) images of this structure revealed a 3D bicontinuous network of macropores and according to Hg porosimetry the average macropore size was recorded as 100 µm. The first reversible capacity of 470 mAh/ g was recorded at a discharge-charge rate of C/5. When discharge-charge rates were increased to 1 and 5 C, reversible capacities of 320 and 200 mAh/g were obtained. Yang et al. [30] managed to synthesize a graphene-based mesoporous carbon anode which performed better than previous graphitic anode. Two-dimensional sandwich like graphene structure increases the surface area while each nanosheet acts as a mini-current collector. They facilitate the rapid transportation of electrons during charge-discharge cycles. At the rate of C/5, its reversible capacity stabilized at 770 mAh/g. When the discharge-charge rates were increased to 1 and 5 C, the reversible capacities recorded 540 and 370 mAh/g, respectively.

Graphene materials loaded with macroporous structures have shown positive results as anode materials for the Li-ion batteries. Mn3O4-graphene [65], Co3O4-graphene [66], and Fe3O4 graphene [67–69] have been studied extensively as potential anode materials for Li-ion materials. Chen et al. [69] reported a 3D graphene-Fe3O4 hybrid prepared by chemical reduction of the GO in the presence of Fe3O4 nanoparticles. The as-prepared hybrid was tested as an anode material for LiBs and exhibited capacities of 990 and 730 mAh/g at current densities of 800 and 1600 mA/g, respectively.

#### **3.2. Li-sulfur batteries**

For more than 20 years, the Li-ion battery has dominated the rechargeable battery market for portable devices and it is still the best choice for electric vehicles. But, when it comes to the electrical performance, a significant improvement is less likely as the performance of the Liion battery has almost reached its theoretical limits [70, 71]. Therefore, Li-S battery is consid‐ ered as one of the potential candidates to replace the Li-ion battery as the next generation rechargeable battery. Sulfur is considered as the 10th most abundant element in the Earth. When employed as a cathode, it has a high specific capacity of 1675 mAh/g and it can deliver a specific energy of 2600 Wh/kg. However, several key issues have prevented the practical applications of Li-S batteries so far. The issues which need to be addressed are (i) poor electrical conductivity of sulfur and its final discharge products (Li2S/Li2S2); (ii) large volume change of sulfur electrode during electrochemical cycling; and (iii) dissolution of polysulfides, inter‐ mediate reactant products in the organic electrolyte leading to deposition of Li2S2/Li2S at the electrode interface. To overcome these drawbacks, extensive researches have been carried out to use graphene materials as scaffolds for cathodes in Li-S batteries [72–76].

**3.1. Lithium-ion batteries**

2006 Recent Advances in Graphene Research

active materials during charge-discharge cycles [63].

of 800 and 1600 mA/g, respectively.

**3.2. Li-sulfur batteries**

C, the reversible capacities recorded 540 and 370 mAh/g, respectively.

Lithium-ion battery has a widespread increasing demand because of its high energy density, flexibility, low maintenance, and longer lifespan compared with other battery technologies [62]. To further increase the energy density, charging efficiency, and cycle life of lithium-ion batteries, it is essential to look at new electrode materials that have good lithium storage capability. Porous graphene with exceptional properties holds a great potential as an electrode material for the lithium-ion battery. The high surface area of graphene can significantly increase the diffusion of lithium ions and electrons. Furthermore, the superior electrical conductivity provides a good conductive network within the electrodes. Graphene can construct a 3D framework with a strong tolerance to the volume change of electrochemically

An anode material for Li-ion battery was made by hierarchical mesoporous and macroporous carbon using the spinodal decomposition of a mesophase pitch (MP) carbon precursor and polystyrene as a soft template [64]. Scanning Electron Microscope (SEM) images of this structure revealed a 3D bicontinuous network of macropores and according to Hg porosimetry the average macropore size was recorded as 100 µm. The first reversible capacity of 470 mAh/ g was recorded at a discharge-charge rate of C/5. When discharge-charge rates were increased to 1 and 5 C, reversible capacities of 320 and 200 mAh/g were obtained. Yang et al. [30] managed to synthesize a graphene-based mesoporous carbon anode which performed better than previous graphitic anode. Two-dimensional sandwich like graphene structure increases the surface area while each nanosheet acts as a mini-current collector. They facilitate the rapid transportation of electrons during charge-discharge cycles. At the rate of C/5, its reversible capacity stabilized at 770 mAh/g. When the discharge-charge rates were increased to 1 and 5

Graphene materials loaded with macroporous structures have shown positive results as anode materials for the Li-ion batteries. Mn3O4-graphene [65], Co3O4-graphene [66], and Fe3O4 graphene [67–69] have been studied extensively as potential anode materials for Li-ion materials. Chen et al. [69] reported a 3D graphene-Fe3O4 hybrid prepared by chemical reduction of the GO in the presence of Fe3O4 nanoparticles. The as-prepared hybrid was tested as an anode material for LiBs and exhibited capacities of 990 and 730 mAh/g at current densities

For more than 20 years, the Li-ion battery has dominated the rechargeable battery market for portable devices and it is still the best choice for electric vehicles. But, when it comes to the electrical performance, a significant improvement is less likely as the performance of the Liion battery has almost reached its theoretical limits [70, 71]. Therefore, Li-S battery is consid‐ ered as one of the potential candidates to replace the Li-ion battery as the next generation rechargeable battery. Sulfur is considered as the 10th most abundant element in the Earth. When employed as a cathode, it has a high specific capacity of 1675 mAh/g and it can deliver a specific energy of 2600 Wh/kg. However, several key issues have prevented the practical applications of Li-S batteries so far. The issues which need to be addressed are (i) poor electrical

For the first time, Wang et al. [77] synthesized a sulfur-graphene (S-GNS) composite by heating a mixture of graphene nanosheets and elemental sulfur. The electrochemical performance of the battery was unsatisfactory as S-GNS electrode contained only 17.6 wt% sulfur. Wang et al. [78] improved the performance of this cathode by increasing the sulfur content up to 44.5 wt % using the same synthesis method. The reversible capacities of the electrode were recorded as 662 mAh/g at 1 C and 391 mAh/g at 2 C after 100 cycles.

Kim et al. [79] produced mesoporous graphene-silica composite (m-GS) as a cathode structure to host sulfur for Li-S batteries. With the help of the ternary cooperative assembly of triblock copolymer (P123), silica precursor and graphene, porous silica structure was made parallel to graphene sheets. Sulfur was infiltrated into the mesoporus structure by melt diffusion at 155°C for 12 h. S intercalated graphite oxide cathode was made by in situ sulfur reduction and intercalation of graphite oxide [80]. By heating a mixture of S8 and graphite oxide at 600°C under vacuum, would break large molecules of S8 into S2 and in the meantime reduce graphite oxide to graphene. Interplanar distance of the carbon matrix allows S2 to intercalate into GO. To minimize the capacity decay, surface S8 could be removed by CS2. This specified cathode was able to maintain a reversible capacity of 880 mAh/g after 200 cycles.

To obtain better electrochemical performance, Zhang et al. [81] created dense nanopores on the surface of graphene nanosheets by chemically activating hydrothermally reduced gra‐ phene oxide (rGO). Sulfur was infiltrated into the KOH-activated graphene hydrogels by the melt diffusion method (**Figure 3**). The rGO hydrogel served as a trap for soluble polysulfides.

**Figure 3.** (a) Schematic representation of the preparation route of activated graphene nanosheets through self-assem‐ bly of GO, ion diffusion and chemical activation strategy. (b) Proposed scheme for the constrained electrochemical re‐ action process of the graphene/sulfur composite. (c) Cycling performances of graphene/sulfur composite electrode at 0.5 C and 1 C [81]. Reprinted with the permission of the Royal Society of Chemistry.

According to results from nitrogen sorption measurements, the surface area of the mesoporous system was 2313 m2 /g and the mean value of nanopores was 3.8 nm. At 0.5 C and 1 C, the graphene/sulfur composite electrode delivered high reversible capacities of 1143 and 927 mAh/ g, respectively.

Evers and Nazar [82] prepared a graphene-sulfur cathode material with a sulfur loading of 87 wt% by a simple one pot method. A mixture of GO and soluble polysulfide was oxidized *in situ* as a one pot reaction. Because of the formation of insulating Li2S layer, the initial discharge capacity of 705 mAh/g at 0.2 C decreased drastically after 50 cycles. S/rGO composite material for Li-S battery cathode was made by concurrently oxidizing sulfide and reducing GO [83]. In this method, Na2S and Na2SO3 were mixed with the GO solution. The composite material is obtained by the reduction of GO by Na2S. The composite with a sulfur loading of 63.6 wt% delivered a reversible capacity of 804 mAh/g after 80 cycles at 0.186 C and 440 mAh/g after 500 cycles at 0.75 C. Gao et al. [84] prepared a sulfur cathode composed of sulfur nanoparticles wrapped in graphene by using Na2S2O3 as a precursor of sulfur. In acidic medium, Na2S2O3 can also serve as a reducing agent of GO. Polyvinylpyrrolidone (PVP) was used to prevent the S particles from aggregation and to keep the sulfur particles at submicrometer range. By using (NH4)2S2O3 as a sulfur precursor, Xu et al. made a graphene-encapsulated sulfur composite. In this synthesis method, a mild reducing agent, urea, was used to reduce GO.

#### **3.3. Supercapacitors**

Supercapacitor is another major alternative solution for the energy storage applications. Supercapacitors have higher power densities than batteries and also higher energy densities than dielectric capacitors [46, 85–88]. The first attempt to use graphene as a supercapacitor was done by Rouff et al. [89] in 2008. In that method, GO was reduced by using hydrazine hydrate and the surface area as measured by BET method was 705 m2 /g. Specific capacitances of 135 and 99 F/g were obtained in aqueous and organic electrolytes, respectively. However, strong π-π stacking and van der Waals attractions among inter layers cause irreversible agglomera‐ tion to form graphite, resulting a decrease in surface area which may hinder the diffusion of the electrolyte. Therefore, making graphene in to a highly open porous structure is an effective way to increase the accessible surface area and the specific capacitance.

Zhu et al. [46] were able to make a carbon based supercapacitor by chemically activating the microwave exfoliated GO (MEGO) and thermally exfoliated GO (TEGO) using the KOH to obtain surface area values up to 3100 m2 /g and a high electrical conductivity of 500 S/m with a C/O atomic ratio of 35 . The specific capacitance values calculated from the charge-discharge curves were 165, 166, and 166 F/g at current densities of 1.4, 2.8, and 5.7 A/g, respectively.

Chen et al. [90] discovered a route to convert noncovalent functionalized graphene to a graphene-activated carbon composite by chemically activating with the KOH, which consisted of a specific surface area of 798 m2 /g. Stable graphene colloids absorbed by oligomers of pphenylene diamne (PPD) were converted to a graphene-activated carbon composite by the KOH activation annealing method. The KOH activation created micro/mesopores in the activated carbon covered on graphene whereas pores in activated carbon also contributed the high surface area of the composite. The as-prepared graphene composite exhibited a specific capacitance of 122 F/g and energy density of 6.1 Wh/kg in aqueous electrolyte. Maximum energy density values of 52.2 and 99.2 Wh/kg were obtained in 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIMBF4) electrolyte at room temperature and 80°C, respectively.

According to results from nitrogen sorption measurements, the surface area of the mesoporous

graphene/sulfur composite electrode delivered high reversible capacities of 1143 and 927 mAh/

Evers and Nazar [82] prepared a graphene-sulfur cathode material with a sulfur loading of 87 wt% by a simple one pot method. A mixture of GO and soluble polysulfide was oxidized *in situ* as a one pot reaction. Because of the formation of insulating Li2S layer, the initial discharge capacity of 705 mAh/g at 0.2 C decreased drastically after 50 cycles. S/rGO composite material for Li-S battery cathode was made by concurrently oxidizing sulfide and reducing GO [83]. In this method, Na2S and Na2SO3 were mixed with the GO solution. The composite material is obtained by the reduction of GO by Na2S. The composite with a sulfur loading of 63.6 wt% delivered a reversible capacity of 804 mAh/g after 80 cycles at 0.186 C and 440 mAh/g after 500 cycles at 0.75 C. Gao et al. [84] prepared a sulfur cathode composed of sulfur nanoparticles wrapped in graphene by using Na2S2O3 as a precursor of sulfur. In acidic medium, Na2S2O3 can also serve as a reducing agent of GO. Polyvinylpyrrolidone (PVP) was used to prevent the S particles from aggregation and to keep the sulfur particles at submicrometer range. By using (NH4)2S2O3 as a sulfur precursor, Xu et al. made a graphene-encapsulated sulfur composite. In

Supercapacitor is another major alternative solution for the energy storage applications. Supercapacitors have higher power densities than batteries and also higher energy densities than dielectric capacitors [46, 85–88]. The first attempt to use graphene as a supercapacitor was done by Rouff et al. [89] in 2008. In that method, GO was reduced by using hydrazine hydrate

and 99 F/g were obtained in aqueous and organic electrolytes, respectively. However, strong π-π stacking and van der Waals attractions among inter layers cause irreversible agglomera‐ tion to form graphite, resulting a decrease in surface area which may hinder the diffusion of the electrolyte. Therefore, making graphene in to a highly open porous structure is an effective

Zhu et al. [46] were able to make a carbon based supercapacitor by chemically activating the microwave exfoliated GO (MEGO) and thermally exfoliated GO (TEGO) using the KOH to

a C/O atomic ratio of 35 . The specific capacitance values calculated from the charge-discharge curves were 165, 166, and 166 F/g at current densities of 1.4, 2.8, and 5.7 A/g, respectively.

Chen et al. [90] discovered a route to convert noncovalent functionalized graphene to a graphene-activated carbon composite by chemically activating with the KOH, which consisted

phenylene diamne (PPD) were converted to a graphene-activated carbon composite by the KOH activation annealing method. The KOH activation created micro/mesopores in the

/g. Specific capacitances of 135

/g and a high electrical conductivity of 500 S/m with

/g. Stable graphene colloids absorbed by oligomers of p-

this synthesis method, a mild reducing agent, urea, was used to reduce GO.

and the surface area as measured by BET method was 705 m2

obtain surface area values up to 3100 m2

of a specific surface area of 798 m2

way to increase the accessible surface area and the specific capacitance.

/g and the mean value of nanopores was 3.8 nm. At 0.5 C and 1 C, the

system was 2313 m2

2028 Recent Advances in Graphene Research

**3.3. Supercapacitors**

g, respectively.

Zhang et al. [91] introduced a method to produce porous 3D graphene-based bulk materials with ultrahigh specific area of 3523 m2 /g and excellent bulk conductivity (up to 303 S/m) by *in-situ* hydrothermal polymerization/carbonization of a mixture of industry carbon sources and the GO followed by KOH activation (**Figure 4**). The carbon sources used in this method were biomass, phenol-formaldehyde (PF), polyvinyl alcohol (PVA), sucrose, cellulose, and lignin. Graphene-PF composite material gave the highest specific capacitance values of 202 F/ g in 1 M TEABF4/AN and 231 F/g in neat EMIMBF4 electrolyte systems, respectively.

**Figure 4.** (a) Schematic representation of the synthesis procedure of the porous three-dimensional graphene-based ma‐ terials. Galvanostatic charge/discharge test results of supercapacitors based on the optimized porous 3D graphenebased materials in (b) 1 M TEABF4/AN and (c) neat EMIMBF4 electrolytes under different current densities. CV curves of PF16G-HA based supercapacitor under different scan rates in (d) 1 MTEABF4/AN and (e) neat EMIMBF4 electrolyte. Reproduced with permission [91], Copyright 2013 NPG.

The electrochemical performance of carbon based materials can be enhanced by doping carbon network with nitrogen and boron [92–95]. Nitrogen and boron co-doped 3D graphene aerogel (BN-GA) was fabricated by using the GO and ammonia boron trifluoride (NH3BF3) [96]. The interconnected framework of graphene nanosheets had a surface area of 249 m2 /g with a macroporous structure. BN-GAs were directly processed into thin electrodes without destroy‐ ing the 3D continuous frameworks and used in all-solid-state supercapacitors (ASSSs). Because of the unique structure and strong synergetic effects of nitrogen and boron co-doping, a specific capacitance of 62 F/g and energy density of 8.65 Wh/kg were obtained. 3D graphene aerogels with mesoporous silica frameworks (GA-SiO2) were fabricated by the hydrolysis of TEOS with graphene aerogel and CTAB as the soft template [97]. Graphene aerogel-mesoporous carbon (GA-MC) with a surface area of 295 m2 /g was generated by infiltrating a sucrose solution into the GA-SiO2 followed by carbonization at 700°C for 3 h in argon. The as-prepared GA-MC exhibited a specific capacitance of 226 F/g when it was used as a supercapacitor.

#### **3.4. Dye-sensitized solar cells**

The dye-sensitized solar cells are among third generation photovoltaic devices that are costeffective and highly efficient. It consists of a mesoporous TiO2 photoanode with a dye to increase light absorption, a counter electrode (CE), and electrolyte. The CE should reduce redox species, which are used to regenerate the sensitizer after electron ejection. To increase the efficiency of DSSC, it is essential to select a CE material with low sheet resistance, high catalytic activity for the reduction of redox species, excellent chemical stability, and low cost. Recently, graphene-based CEs have been studied extensively as a potential cost-effective replacement for platinum based CEs.

Compared with other graphene-based materials, functionalized or doped graphene exhibits exceptional electocatalytic activity. In 2012, Xu et al. prepared Hemin, an iron-containing porphyrin functionalized rGO by microwave irradiation [98]. The Hemin-rGO hybrid exhibited a power conversion efficiency (PCE) value of 2.45 %. Yen et al. [99] reported a nitrogen-doped graphene prepared using a hydrothermal method. The nitrogen-doped domains on the graphene surface act as electroactive sites, which have selectivity for redox species in the reduction reaction. The as-prepared nitrogen-doped graphene CE exhibited the PCE value of 4.75%. Xue et al. [100] managed to prepare 3D nitrogen-doped graphene foams with a nitrogen content of 7.6% freeze drying the GO foams followed by annealing at 800°C in ammonia/argon mixture for 1 h. Because of the high content of nitrogen, the PCE value of 7.07% was obtained.

#### **4. Conclusion**

In conclusion, owing to its high surface area, unique pore structure, and remarkable electro‐ chemical performances, porous graphene has attracted great attention in the fields of energy storage and conversion. However, there are several key issues, which need to be addressed. The precise control of pore size, pore morphology, and wall thickness is necessary for the assembly of hierarchically structured porous graphene materials. Introduction of different sizes of pores into graphene matrix is essential to produce porous graphene materials to obtain synergic effects of different pores. With increasing research efforts in the field, we believe that there would be significant advances in the synthesis and application of porous graphene in the near future, benefiting development of high performance energy conversion and storage devices. This research was partially supported under the Australian Research Council Discovery Project (DP150101717). Kimal Chandula Wasalathilake acknowledges the QUTPRA scholarship from the Queensland University of Technology.


**4. Results**

As can be seen in Table 2, most of the variables in every factor resulted in sufficient loadings. This also indicates a sufficient extent of relevance of variables in explaining the construct of each of the proposed factors. However, there were six variables that resulted in factor loadings of less than 0.500. They are depicted in the table with a strikethrough line. We decided to exclude them from the regression analysis and their involvement as independent variables in the impact that they have on the dependent variable, namely, the organic search engine visit percent. Regarding the percent of variance explained in each factor, most of them expressed considerable variability, reaching up to 55%.

**Table 2.** Descriptives and internal validity and consistency of the examined factors and their variables.

**Table 2.** *Cont*.

The underlines depict the factor and its items, the italics depict the sub-factors, and the strikethrough lines depict each dropped variable.

Linear regression analysis returned significant indications (Table 3). Prior preprocessing and analysis was conducted in order to exclude outliers that would possibly influence the outcomes of the prediction. We also note that no changes were observed when we used a hierarchical technique. From the results of the test, all the produced models have clear statistical significance with *p* values less than 0.05. Nevertheless, there is a marginal exception in the factor of Website Loading Speed with a *p* value of 0.061, greater than 0.05. In terms of R2 values, the results depict alignment with prior studies stating that ranking algorithms involve a massive number of secret variables in the SEO context [20,48]. In fact, Size of Websites explained up to 30.06% of the variability of the response data around its mean; SEO Crawling, up to 17.7%; Website Loading Speed, up to 10.01%; Website Security Condition, up to 17.9%; and User Behavior, up to 29.5%.

**Table 3.** Regression analysis output.

*N* = 171. \* and \*\* indicate statistical significance at the 95% and 99% levels, respectively.

Indeed, the more numerous the variables, the higher the model fit and, consequently, the R2 values [59]. In other words, we defined some variables in each factor; however, all of them require further research to investigate even more variables that play a crucial role in the increase of the organic search engine traffic percent.

In terms of the first hypothesis, a significant regression equation was found with *p* = 0.012 and R2 of 0.306. This means that the mean value of the organic search traffic percent is increased by 1.06% for every percentage point increase in each variable of the Size of Websites factor. For the second hypothesis, a significant regression equation was observed with *p* = 0.021 and R2 of 0.177. This means that the mean value of the organic search traffic percent is increased by 2.14% for every percentage point increase in the percent of the SEO Crawling factor.

For the third hypothesis, a slightly nonsignificant regression equation was found with a marginal value of *p* = 0.061 and R2 of 0.101. Even by bootstrapping of 1000 additional re-samples, there was no significant change in the *p* value, R2, or coefficients. Therefore, the mean value of the organic search traffic percent is increased by 1.11% for every percentage point increase in the Website Loading Speed factor. For the fourth hypothesis, Website Security Condition provided a significant regression equation with *p* = 0.019 and R2 of 0.189. As a result, the mean value of the organic search traffic percentage is increased by 1.36% for every unit increase in the Website Security Condition factor.

For the last hypothesis, User Behavior in the examined cultural websites seems to have the highest impact on the increase in organic search engine traffic percent. More specifically, a significant regression equation was observed with *p* = 0.000 and R2 of 0.295. Thus, the mean value of the organic search traffic percent is increased by 3.14% for every percentage point increase in each variable of the User Behavior factor. This constitutes an important research result. Prior research implied that search engines encapsulate user behavior in order to rank websites in their search engine result pages [20,48]. And indeed, the higher the ranking position of a website, the higher the organic search engine traffic percentage that they receive [18,19,60].

#### *Agent-Based Model Development*

The extracted outcomes of the regression statistics resulted in significant implications that could be incorporated into a predictive data-driven agent-based model. The purpose of ABM is to compute and represent each case individually at a micro-level view while taking into consideration temporal changes [53–55]. This is not possible through the aggregated macro-level approach of Fuzzy Cognitive Mapping.

For instance, in ABM, decision-makers are able to estimate the impact of each change in SEO performance and user behavior individually for each website. This advantage provides precise results regarding the impact that each SEO factor has for every website and also about the percentage variance of organic search traffic that the website receives. As all cultural websites differ in their content and how compatible they are with the SEO factors, it is possible to generate different data analytics, both technical and behavioral. This means that managerial staff need more or less time to rectify SEO issues and, therefore, to improve user behavior and enhance organic search traffic. In this case, ABM as a predictive modeling and simulation method gives risk-free flexibility to decision-makers. They are able to themselves define the time needed to keep up with the SEO compatibility framework and, thereafter, to improve their organic search traffic. This approach combines both managers' domain knowledge, as each cultural organization differs in its operations, and the practical insights of the data analytics results.

The first main goal of the proposed computational model is verification that the proposed methods and results can be used to optimize the organic search engine traffic percentage. The second goal is decrease of the bounce rate level as a negative indicator of the overall user behavior in the examined cultural heritage websites. In the next figure (Figure 8), we present the developed ABM, its entities, and its conditions. For model development, AnyLogic ver. 8.5.2 software was used in JAVA source code in order to compute agent behavior. We defined a specific time range of 90 days in order to predict and simulate the percentage increase of organic search engine traffic. No additional days were included as there was no other crucial percentage variance in the organic search engine and bounce rates.

The model starts in its initial stage with the possibility of entrance and visit inside the cultural heritage institution websites, an initial point that depicts fundamental aspects of the agent-based development process [54–56]. This is indicated in the first statechart, entitled "Potential Search Engine Users". The transition of users (as agents) among statecharts is computed based on the prior descriptive statistics of the study, such as min, max, mean, and mode, and the outcomes of the regression analysis. The impact level that users receive from the Size of Websites, the Website Loading Speed, and the Website Security is defined by the conditions of the Size of Websites Impact, Website Loading Speed Impact, and Website Security Impact. These three major factors and their defined conditions impact drastically on user behavior inside cultural heritage websites. However, as the regression results indicated, the Website Loading Speed factor does not impact the organic traffic percentage, so there is no kind of transition between the two statecharts. At the same time, the Size of Websites, Website

Security, and SEO Crawling factors are depicted as statecharts that impact both User Behavior and the final goal, which is positive influence of the Organic Search Engine Traffic Percentage.

**Figure 8.** A predictive agent-based model for optimization of the organic search engine visit percentage and decrease of the bounce rate.

This kind of impact is computed through Poisson distributions, while setting up the results of the regression as lambda values (λ). The Poisson distribution was selected because our sample

Moreover, we define the consequence of low interaction rate and dissatisfied user behavior resulting in immediate abandonments via the bounce rate metric, which is illustrated through the Bounce Rate statechart and computed through the Percent of Bounce Rate condition. That is, users enter the websites, but they find insufficient content (Size of Websites), low speed of navigation (Website Loading Speed), and insufficient security in their exploration, so they leave the websites almost immediately upon their visit. In Figure 9 we present the outcomes of the predictive agent-based model.

The graph in Figure 9 represents the potential scenario of improving each of the examined factors based on the outcomes of the regression and their impact on the organic search engine traffic percentage and bounce rate level. Indeed, the model, after the initial days of the run, shows an improvement in organic search engine traffic. At the same time, a decrease and steadiness is observed in the bounce rate level without any significant sign of increase. Furthermore, it is noted that the Organic Search Engine Visit Percent does not show any further optimization after Day 50, following a straight line without any kind of fluctuation or change. This happens for two reasons. First the examined cultural websites are able to receive the rest of their visitors from paid advertising, social networks, direct traffic, email marketing campaigns, and other external websites. Secondly, it is possible for the managerial staff to cover and rectify all the SEO technical compatibility factors that are able to optimize the organic search traffic up to ~75%, as depicted in Figure 9. Therefore, new data analytics and regression results are needed in order to provide feedback, update the predictive model, and determine the potential extent of the percentage increase in organic search engine traffic.

**Figure 9.** Optimization of the organic search engine traffic percentage in a time range of 90 sequential days. The horizontal axis demonstrates the specific time range from 0 up to 90 days of the simulation run. The vertical axis depicts the percentage of organic search engine traffic.

#### **5. Discussion and Future Implications**

The optimization of visibility in cultural heritage websites improves the knowledge that stakeholders receive from them. More specifically, in an open and democratized way, CHI websites increase people's interest in the past and allow them to recognize how their surrounding societal context has changed over time. In this respect, the SEO strategy must be set within the prism of the overall mission of cultural heritage institutions, rather than assigning these functionalities unilaterally to technical staff. This will enhance the overall importance of SEO strategies from the support personnel to the upper management levels.

In this paper, we proposed a novel methodology that quantifies in a manageable way the impact of several factors on the organic search engine traffic percentage in CHI websites with the purpose of increasing visibility and findability. One step further, this methodology offers to the administrators of CHI websites an opportunity to convert data analytics about SEO performance into useful insights and actions for potential optimization of their visibility on the Web. Otherwise, a big data analytics framework without evaluation, analysis, interpretation, and suggestion for further improvement is completely useless [61]. Based on that, we believe that this research establishes a new SEO context of communication, as more and more big data analytics can be retrieved and interpreted, while focusing on critical factors and omitting less relevant ones in organic traffic optimization. In this respect, this methodology provides new opportunities both for managers in cultural institutions and for research on this topic.

#### *5.1. Managerial Implications for Cultural Heritage Institutions*

#### 5.1.1. Implications for Optimized Website Performance and Visibility

The proposed model shows validity, reliability, and cohesion as regards the variables and factors that it contains for evaluation and, hence, optimization of organic search engine traffic. This works as a solid stepping stone for managers to adopt this methodology, evaluating the importance of each factor and focusing precisely on each one for further improvement. However, although the results of the obtained behavioral data analytics demonstrated that CHI websites receive on average up to 62.76% of their total traffic solely from search engines (Table 2), the bounce rate level was observed to reach up to 55%. This means that more than one in two visitors immediately abandon the websites after their visit.

Based on that, we suggest to marketing managers and administrators of cultural websites to focus first on usability improvement with the purpose to improve user interaction and behavior. The factor of SEO Crawling includes variables that might have crucial impacts for enhanced usability and user experience in CHI websites. The avoidance of thin or duplicated content, removal of broken links that confuse users, and proper mobile friendliness are some of these user-centered variables. Moreover, this factor includes variables that have a systemic impact on increasing search engine friendliness to crawlers. The appropriate curation of headings, titles, meta-descriptions, robots.txt, and sitemap files are some of the points that managers should focus on with the purpose to develop favorable conditions for the indexing process by search engines.

In this research, regression results show that user behavior has the highest impact among the factors that affect the percentage increase of organic search engine traffic (Table 3). Indeed, User Behavior can increase by up to 3.14% the total percentage of organic search traffic in the examined websites. Nevertheless, if the administrators do not pay greater attention to aligning their efforts firstly with the optimization of website usability, then the behavior of users and their experience will negatively affect the percentage of search engine traffic. Therefore, the managerial staff of cultural institutions must not focus only on SEO strategies that aim for ranking optimization; it is more important to improve usability for better engagement between users and content [60,62]. This will positively increase behavior and, thereafter, provide higher organic traffic percentages.

#### 5.1.2. Utility of the Methodology

The proposed methodology not only supports managerial staff to seek an aggregated evaluation of a CHI website, it is also a flexible approach to focus on the individual performance of specific collections contained in unique webpages which unfortunately suffer from low visibility and findability on the Web. For instance, administrators could evaluate the SEO performance of specific webpages of cultural content while manipulating in a more efficient way the process of optimization in specific *parts* rather than the *whole*. This approach covers a rigorous and challenging task for cultural heritage institutions, as they have to deal with the large size of their content. Indeed, the larger the size of a web-based system, the more complex its manipulations and rectifications [12,19,45,54].

In addition, the outcomes of this methodology provide practical and educational implications for cultural institutions to avoid big data frameworks that rely more on data storage and not enough on their analysis. As the reliability of the gathered data constitutes a core value for the quality of a well-informed decision-making process [61], website analysts of cultural heritage websites should focus more on big data metrics systems that fit the following:

Therefore, the proposed methodology offers the flexibility to tackle other problematic issues in the online presence of cultural heritage institutions, such as the proper utilization of analytics for social media optimization or cost-effective online paid advertising campaigns. That is, we proceed to the careful delimitation of KPIs; gather, validate, and examine the data analytics that align with the KPIs; and then develop data-driven predictive models for optimization.

#### 5.1.3. Optimized Financing Resource Management

In the EU context, the Eurostat report of 2018 [64] depicted a low percentage of expenditures in cultural services ranging from 0.4% up to 0.8% of the GDP. Bearing in mind the reduced financial flexibility of cultural institutions and their limited available resources for the management of the cultural material that they contain, the process of search engine optimization could be a cost-effective marketing strategy.

In contrast with other digital marketing strategies that increase website visitor numbers but provide poor content curation and usability, SEO constitutes a sustainable digital marketing strategy that focuses on one of the most fundamental aspects of digital marketing: the effectiveness of the landing page. If users *land* in webpages that express usability and proper curation of content, then their experience will be better, making any kind of marketing communication strategy more effective. This constitutes a promising approach to reduce paid advertising strategies that do not eventually return the investment, due to the minimal interaction of users after visiting websites.

#### *5.2. Research Implications*

The dimension reduction results through principal component analysis indicated that most of these variables are suitable for providing reliable evaluations of website performance and the impact that they have on user behavior and organic search engine traffic. Notwithstanding, even if we include more than 50 variables that impact the organic search engine traffic optimization, the regression R-square values indicate the depth of search engine ranking algorithms and the multidimensionality of the variables they involve. Following the above findings, we have started further research efforts in order to explore and include more variables or factors that probably influence rankings and, hence, percentage variance in organic search engine visits. Based on this assumption, as big data mining and analytics techniques are getting more and more sophisticated and impact organizations' decision-making process in terms of marketing and promotion strategies [62], the research topic of SEO reliance in big data analytics will be discussed in a detailed manner in the future.

Regarding the predictive agent-based model development, from the initial research approaches as a computational method to describe the complexity of a system and its entities, to recent characterizations, it is referred to more as an art than as a science [56,58,65]. However, as big data analytics expand the opportunities for integrating more and more data into simulation models, the *art* is sidelined. Therefore, new research approaches are developed to overcome a lack of data and combine prior domain knowledge and analytics for logical well-informed and data-driven predictive models.

In this paper, we developed the ABM as a supportive tool that provides feedback to the managers of cultural heritage institutions regarding the impact of several factors on user behavior and organic search engine traffic percent. An abstraction level that describes the impact of each factor was developed. Nevertheless, predictive models are mostly stable in abstraction levels but unstable with larger perturbations when more conditions and entities are included. Therefore, further research is needed to evaluate predictive model efficiency through ABM when expanding the level of abstraction or integrating system dynamics approaches [66].

Furthermore, the results of the study emphasize the necessity to redefine the SEO topic. Apparently, the higher the compatibility of the SEO factors, the higher the rankings and search engine visit percentage. However, the main aim of search engines is confirmation that they provide the most qualitative content, in the highest volume, in the fastest time to their users, according to their search terms [67]. In this respect, Web developers and content creators should have practical quantified indicators in order to evaluate and optimize their website performance and content. Thus, we redefine SEO as it is not solely the process of rectification for higher search rankings. It is rather much more a *user-centric* strategy that improves the findability and visibility of information in search results and aims for integrated user experience inside websites.

**Author Contributions:** All the authors have contributed equally in this research effort in terms of the conceptualization, methodology, software, validation, formal analysis, investigation, resources, data curation, writing the original draft and writing review-editing. D.K.-M., G.A.G. and D.P.S. contributed to the supervision and project administration of this study. All authors have read and agreed to the published version of the manuscript

**Funding:** This research received no external funding.

**Acknowledgments:** Dedicated to those who fought against the covid-19, but did not make it. We heartily thank the guest editors of *Big Data Analytics in Cultural Heritage* for giving us this opportunity. We are also grateful to the Reviewers for their vital remarks. To conclude, we acknowledge the valuable technical contribution of Nikolaos Lazaridis for the provision of cutting-edge hardware helping us to work faster for this project.

**Conflicts of Interest:** The authors declare no conflict of interest.

## **References**

*Big Data Cogn. Comput.* **2020**, *4*, 5

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


*Article* **The Risk of Obstetrical Hemorrhage in Placenta Praevia Associated with Coronavirus Infection Antepartum or Intrapartum**

**Irina Pacu 1,2, Nikolaos Zygouropoulos 2, Alina Elena Cristea 2, Cristina Zaharia 2, George-Alexandru Rosu 1,2, Alexandra Matei 1,2, Liana-Tina Bodei 1,3, Adrian Neacsu 1,3,\* and Cringu Antoniu Ionescu 1,2**

**Abstract:** *Background and Objectives*: The aim was to evaluate the severity of obstetrical bleeding in the third trimester associated with COVID infection in placenta previa and accreta. *Materials and Methods*: A retrospective study was conducted to compare the risk of obstetrical bleeding in the case of placenta previa with or without associated SARS-CoV-2 infection. Patients presenting with placenta previa before labor were classified into three groups: group A (control) as no infection throughout their pregnancy, group B as confirmed infection during the 1st trimester, and group C as confirmed infection at the time of delivery. Infected patients were stratified according to the severity of signs and symptoms. The severity of obstetrical hemorrhage at birth was assessed quantitatively and qualitatively. All placentas were analyzed histologically to identify similarities. *Results*: Prematurity and pregnancy-induced hypertension appear significantly related to SARS-CoV-2 infection during the 3rd trimester. Placenta accreta risk increases significantly with infection during the 1st trimester. No statistically significant differences in the severity of hemorrhage associated with childbirth in cases with placenta previa between groups A and C but increased obstetrical bleeding mainly due to emergency hemostatic hysterectomy in group B driven by placenta accrete were detected. Obstetrical hemorrhage at birth in the case of coexistence of the infection was found not to correlate with the severity of the viral disease. Meanwhile, the number of days of hospitalization after birth is related to the specific treatment of COVID infection and not related to complications related to birth. *Conclusions*: The study finds an increased incidence of placenta accreta associated with placenta previa in cases where the viral infection occurred in the first trimester of pregnancy, associated with an increased incidence of hemostasis hysterectomies in these patients. Placental histological changes related to viral infection are multiple and more important in patients who had COVID infection in the first trimester.

**Keywords:** obstetrical bleeding; SARS-CoV-2; placenta previa; placenta accreta

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).


**Chao-Feng Liu , Xin-Gui Tang \* , Lun-Quan Wang, Hui Tang , Yan-Ping Jiang, Qiu-Xiang Liu, Wen-Hua Li and Zhen-Hua Tang**

School of Physics & Optoelectric Engineering, Guangdong University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China

**\*** Correspondence<EMAIL_ADDRESS>Tel.: +86-20-3932-2265

Received: 15 July 2019; Accepted: 2 August 2019; Published: 4 August 2019

**Abstract:** The resistive switching (RS) characteristics of flexible films deposited on mica substrates have rarely been reported upon, especially flexible HfO2 films. A novel flexible Au/HfO2/Pt/mica resistive random access memory device was prepared by a sol-gel process, and a Au/HfO2/Pt/Ti/SiO2/Si (100) device was also prepared for comparison. The HfO2 thin films were grown into the monoclinic phase by the proper annealing process at 700 ◦C, demonstrated by grazing-incidence X-ray diffraction patterns. The ratio of high/low resistance (off/on) reached 1000 and 50 for the two devices, respectively, being relatively stable for the former but not for the latter. The great difference in ratios for the two devices may have been caused by different concentrations of the oxygen defect obtained by the X-ray photoelectron spectroscopy spectra indicating composition and chemical state of the HfO2 thin films. The conduction mechanism was dominated by Ohm's law in the low resistance state, while in high resistance state, Ohmic conduction, space charge limited conduction (SCLC), and trap-filled SCLC conducted together.

**Keywords:** resistance switching; high/low resistance; oxygen defect; conduction mechanism


**Abstract**

Heavy metals accumulated the earth crust and causes extreme pollution. Accumulation of rich concentrations of heavy metals in environments can cause various human diseases which risks health and high ecological issues. Mercury, arsenic, lead, silver, cadmium, chromium, etc. are some heavy metals harmful to organisms at even very low concentration. Heavy metal pollution is increasing day by day due to industrialization, urbanization, mining, volcanic eruptions, weathering of rocks, etc. Different microbial strains have developed very efficient and unique mechanisms for tolerating heavy metals in polluted sites with ecofriendly techniques. Heavy metals are group of metals with density more than 5 g/ cm3 . Microorganisms are generally present in contaminated sites of heavy metals and they develop new strategies which are metabolism dependent or independent to tackle with the adverse effects of heavy metals. Bacteria, Algae, Fungi, Cyanobacteria uses in bioremediation technique and acts a biosorbent. Removal of heavy metal from contaminated sites using microbial strains is cheaper alternative. Mostly species involved in bioremediation include Enterobacter and *Pseudomonas* species and some of bacillus species too in bacteria. *Aspergillus* and *Penicillin* species used in heavy metal resistance in fungi. Various species of the brown algae and Cyanobacteria shows resistance in algae.

**Keywords:** heavy metal resistance, bioremediation, biosorption, bioleaching, plasmid


*3.4.4. Chillers*

There are several ways to regulate system cooling capacity. (1) On–off control: This is the simplest way to control the capacity, but can cause frequent short cycling of compressors, which is detrimental to compressor performance. (2) Unloading control: This is often used for reciprocating compressors with multiple cylinders. (3) Slide valve control: This is often used for a screw compressor, which can adjust the compressor capacity with a wide range. (4) Hot gas bypass: This is not an efficient way as a mixture of hot and cold refrigerant is used. (5) Digital compressor: This is developed by Emerson for scroll compressors. The cooling capacity can be varied from 10% to 100%. (6) Variable speed compressor: This provides a smooth system capacity modulation with a wide range and is more energy efficient. Some chiller manufac‐ turers already produced chillers with variable speed scroll compressors or variable speed screw compressors.

For a VFD-equipped compressor, the compressor speed is often modulated to maintain the supply water or supply air temperature set point.