*3.2. Pharmacokinetic Modeling*

The one-compartment model was successfully applied to describe each group in terms of the plasma concentration-time profile after a single oral administration of 2 mg/kg tadalafil. Among the various compartment models, the one-compartment model, which is the simplest and best suited to the observed pharmacokinetic profile of tadalafil, was used to compare the observed pharmacokinetic profile with the fitted pharmacokinetic profile. The one-compartment modeling supports the results of the non-compartment analysis that changed by the co-administration of ticagrelor. The modeling-based comparison allows for greater confidence in the metabolic inhibition effect by comparing the observed pharmacokinetic profile with the fitted pharmacokinetic profile, as well as by matching with the parameters of the non-compartment analysis. Additionally, the model-based approach was used to evaluate a more specific and quantified absorption, elimination, and distribution of tadalafil in vivo.

As shown in Figure 1, the dashed lines and dotted marks mean the predicted plasma concentration and observed plasma concentration, respectively. The dashed lines showed similar patterns to the dotted marks. Figure 3 indicates the residual plot of the fold error versus time or observed plasma concentration. It shows the acceptable residual values (fold error <2) at most of the analyzed points, which indicates that the one-compartment model is suitable for the explanation of the plasma concentration profile of tadalafil [35,40].

**Figure 3.** Residual plots written with the pharmacokinetic modeling values of non-pretreated rats (Group N) and ticagrelor-pretreated rats (Group T). (**A**) Fold error vs. time; (**B**) fold error vs. plasma concentration.

Table 2 lists the parameters of the one-compartment model. In the one-compartment model, Ke and V/F were decreased significantly in Group T compared to Group N. The Ke of Group T (0.13 ± 0.03 h−1) were decreased compared with that of Group N (0.17 ± 0.05 h−1) (*p* < 0.05). Moreover, the V/F of Group T (3.36 ± 0.95 L/kg) was significantly decreased compared with that of Group N (4.39 ± 0.78 L/kg) (*p* < 0.05). These reductions led to a decrease in the clearance of tadalafil. In addition, the Ka of Group T was also decreased, but there was no statistical significance (*p* = 0.1933) (Figure 4). However, this slight reduction was due to the delay in absorption, and it is clear that the absorption increased because of the high Cmax. These results were consistent with those from the non-compartment analysis, indicating that the more absorption and the low clearance caused the increased exposure of tadalafil.

**Table 2.** The one-compartment model parameters of tadalafil in non-pretreated rats (Group N) and ticagrelor-pretreated rats (Group T). Values are represented as mean ± SD (n = 10).

a Ratio = *Value o f Group T Value o f Group N* ; Absorption rate constant from the gut compartment to the central compartment (Ka); elimination rate constant from the central compartment to the gut compartment (Ke); the central volume of distribution (V/F).

**Figure 4.** Comparisons of the one-compartment model parameters of tadalafil in non-pretreated rats (Group N) and ticagrelor-pretreated rats (Group T). Boxes mean 25th and 75th percentiles of data and whiskers mean 5th and 95th percentiles of data. The median and mean values are displayed as a solid line (–) and a plus mark (+) in boxes, respectively. (**A**) Ka; (**B**) Ke; (**C**) V/F. Absorption rate constant from the gut compartment to the central compartment (Ka); elimination rate constant from the central compartment to the gut compartment (Ke); the central volume of distribution (V/F).

In addition, the results from the modeling indicate that ticagrelor is a weak CYP3A inhibitor. The weak inhibitor is defined as a substance that increases the AUC value of the CYP substrate by 1.25-fold to 2-fold, or that it reduces the clearance of the CYP substrate by 20–50%, and ticagrelor is also classified as this inhibitor [22,41]. Changes in the AUC (1.61-fold) and clearance (37%) of tadalafil by co-administration with ticagrelor were within the range, supporting the above classification. Therefore, we inferred that ticagrelor acts as a weak CYP3A inhibitor, a ffecting the pharmacokinetic profiles of tadalafil, a CYP3A substrate. Furthermore, co-administration of tadalafil with ticagrelor or other CYP3A inhibitors, such as ketoconazole and diltiazem, would also be expected to increase tadalafil exposure [42].

In a clinical aspect, tadalafil shows robust safety and tolerability [12]. However, the co-administration of tadalafil with ticagrelor to elderly men may cause unexpected side e ffects. The half-life of tadalafil in normal healthy men is reported to be approximately 17.5 h after administration, whereas that of elderly men is about 21.6 h [43]. This half-life in elderly men is likely to increase further due to co-administration with ticagrelor, which may increase the incidence of side e ffects, such as headaches and dyspepsia. In addition, patients receiving nitrate medication for treatment of angina are recommended to postpone the nitrate treatment for at least 48 h after administration of tadalafil, but this may need to be longer to prevent serious hypotension [44]. Therefore, most patients receiving these drugs are older, so co-administration of tadalafil should be carefully considered.


**3.7 Testing for soluble protein expression in** *E. coli*

The following protocol is written for proteins expressed under the control of the lac, tac, or T7 promoters. The method as described is a generic protocol that can be expanded to test expression in different strains of *E. coli*, induction temperatures, concentrations of IPTG, or even in the presence of ligands or cofactors.

## *3.7.1 Protein expression*

**47**

*Growing and Handling of Bacterial Cultures within a Shared Core Facility for Integrated…*

5.Transfer the equivalent of 1 mL of cells at OD600 = 0.8 in a 1.5-mL microcentri-

6.Collect cells by centrifugation at 16,000× g on a tabletop centrifuge for at least 1 min. Carefully remove all of the supernatant. This is the uninduced sample.

8.Measure the OD600. Collect cells by centrifugation in two tubes containing the equivalent of 1 mL of cells at OD600 = 0.8 and remove the supernatant. These are the induced samples; one tube will be used to test for expression and the second for solubility. Store the cells at −20°C until ready to test for expression.

1.Take the tube of uninduced and one tube of induced cells and resuspend each in 100 μL of 1X SDS polyacrylamide gel electrophoresis (SDS-PAGE) sample

4.Take 10 μL of each sample from the top of tube taking care not to disturb the

5.Analyze the results using SDS-PAGE following Section 3.9 (**Figure 2**), with

1.Resuspend the remaining induced cell pellet in 50 μL of lysis buffer containing

4.Carefully transfer all of the supernatant into a new microcentrifuge tube. Add

5.Resuspend the pellet in 100 μL of 1X SDS-PAGE buffer. This is the insoluble

6 In order to have equal loading on an SDS-PAGE gel, the same amount of cells need to be harvested for gel analysis. To harvest the same number of cells each time, calculate the volume in mL needed of your culture

3.Spin down in a microcentrifuge at maximum speed for 10 min at 4°C.

2.Boil the samples for 10 min, then cool down to room temperature.

3.Centrifuge for 5 min at 16,000× g on a tabletop centrifuge at room

7.Add IPTG to a final concentration of 1.0 mM to the remaining culture.

Continue shaking at 250 rpm for 12–16 h at 18°C.

*DOI: http://dx.doi.org/10.5772/intechopen.81932*

Store the cells at −20°C.

*3.7.2 Testing for expression*

buffer.

pellet.

temperature.

*3.7.3 Testing for solubility*

fraction.

western blotting if necessary.

protease inhibitors and 1 mg/mL of lysozyme.

2.Follow Section 3.8.1 for freeze-thawing to lyse the cells.

50 μL of 2X SDS-PAGE buffer. This is the soluble fraction.

6.Boil the samples for 10 min, then cool down to room temperature.

that would be the equivalent of 1 mL of OD600 = 0.8. E.g. X mL = 0.8/OD600 of your culture.

fuge tube.6

*Growing and Handling of Bacterial Cultures within a Shared Core Facility for Integrated… DOI: http://dx.doi.org/10.5772/intechopen.81932*


**1. Introduction**

446 Dyslipidemia - From Prevention to Treatment

Stankov, M., & Behrens, G. (2010) Contribution of Inflammation to Fat Redistribution and

Tall, A. (1990) Plasma high density lipoproteins. Metabolism and relationship to

Ter Hofstede, H., Burger, D., & Koopmans, P. (2003). Antiretroviral therapy in HIV patients:

Thiébaut, R., Daucourt, V., Mercié, P., Ekouévi, D. K., Malvy, D., Morlat, P., Dupon, M.,

Tien, P., Cole, S., Williams, C., Li, R., Justman, J., Cohen, M., Young, M., Rubin, N.,

Van Griensven, J., De Naeyer, L., Mushi, T., Ubarijoro, S., Gashumba, D., Gazielle, C., &

World Health Organization (CH), United Nations Programme on HIV/Aids - UNAIDS

 <http://data.unaids.org/pub/Report/2009/jc1700\_epi\_update\_2009\_en.pdf>. World Health Organization. (1995). Physical Status: The Use and Interpretation of

Available from: <http://whqlibdoc.who.int/trs/WHO\_TRS\_854.pdf>. Yarasheski KE, Tebas P, Stanerson B, et al (2001). Resistance exercise training reduces

*in-Publication Data,* Date of access: Jun 2011, Available from:

*Cardiologia*, Vol. 85, No. 5, (Oct 2005), pp. (58-61).

Vol. 16, No. 30, (Out 2010), pp. (3361-3371), ISSN 1381-6128.

<http://www.hiv.gov.gy/edocs/glossary.pdf>.

(Fev 2007), pp. (3-4), ISSN 0004-2730.

(379-384), ISSN 00219738.

ISSN 1058-4838.

798), ISSN 0035-9203**.**

Metabolic Disturbances in HIV-1 Infected Patients. *Current Pharmaceutical Design*,

atherogenesis. *The Journal of Clinical Investigation*, Vol. 86, No. 2, (Aug 1990), pp.

aspects of metabolic complications and mitochondrial toxicity. *The Netherlands Journal of Medicine*, Vol. 61, No. 12, (Dec 2003), pp. (393-403), ISSN 0300-2977. The HIV/Aids Treatment Information Service (ATIS). (Sep 2002). *Glossary of HIV/AIDS-*

*Related Terms*, The HIV/Aids Treatment Information Service (ATIS), Retirado de

Neau, D., Farbos, S., Marimoutou, C., & Dabis, F. (2000). Lipodystrophy, metabolic disorders, and human immunodeficiency virus infection: Aquitaine cohort, France, 1999. Groupe d'Epidémiologie Clinique du Syndrome d'Immunodéficience Acquise en Aquitaine. *Clinical Infectious Diseases*. Vol. 31, No. 6 (Dec 2000), pp. (1482-7),

Augenbraun, M., & Grunfeld, C. (2003). Incidence of lipoatrophy and lipohypertrophy in the women's interagency HIV study. *Journal of Acquired Immune Deficiency Syndromes*, Vol. 34, No. 5, (Dec 2003), pp. (461-466), ISSN 1077-9450. Tovar, J., & Schering, D. (2006) Management of Dyslipidemia in Special Populations. *Journal of Pharmacy Practice*, Vol. 19, No. 2, (Apr 2006), pp. (63-78), ISSN 0897-1900. Valente, A., & Valente, O. (2007). Síndrome Lipodistrófica do HIV: Um Novo Desafio para o

Endocrinologista**.** *Arquivos Brasileiros de Endocrinologia e Metabologia*, Vol. 51, No. 1,

Zachariah, R. (2007). High prevalence of lipoatrophy among patients on stavudinecontaining first-line antiretroviral therapy regimens in Rwanda. *Transactions of the Royal Society of Tropical Medicine and Hygiene*, Vol. 101, No. 8, (Ago 2007), pp. (793-

(CH). (2009). Aids epidemic update: November 2009, In: *WHO Library Cataloguing-*

Antropometry. In: *WHO Technical Report Series 854*, Date of Access: May 2011,

hypertriglyceridemia in HIV-infected men treated with antiviral therapy. *Journal of Applied Physiology*; Vol. 90, No. 1 (april 2001**)**,. pp. (133–138), ISSN 8750-7587. Yu, P., Calderaro, D., Lima, E. & Caramelli, B. (2005). Terapia hipolipemiante em situações

especiais – Síndrome de Imunodeficiência Adquirida. *Arquivos Brasileiros de*

Fenofibrate, a selective peroxisome proliferator-activated receptors alpha (PPAR-α) activator, has been primarily developed to treat human dyslipidemia. PPAR modulate the expression of genes involved in lipid metabolism through peroxisome proliferator response elements (Willson et al., 2000). Although fenofibrate became commercially available in 1974 (Fournier, Inc., France), its lipid-lowering action mechanism has not been clarified until the late 1990's, contributing to open new research doors. With respect to the mechanisms of action, the drug with pleiotropic activity may be regarded as a "21st-century agent" (Staels et al., 1995).

Fenofibrate as a ligand of PPAR-α exhibits lipid-lowering effects by activating PPAR-α.

PPAR-α activators stimulate the β-oxidation of fatty acids in the liver resulting in a decreased availability of fatty acids for triglyceride (TG) synthesis (Schoonjans et al., 1995, 1996a, 1996b). In addition, fenofibrate enhances the production of apo-AI and apo-AII: the major component of HDL by activating PPAR-αand increases plasma level of HDL-C directly (Vu-Dac, 1994, 1995). Thus, the lipid-lowering action mechanism of fenofibrate involves potent TG-reducing and HDL-C-increasing actions. Statins, another type of lipidlowering agent do not show such actions, though statins can inhibit hydroxymethylglutaryl (HMG)-CoA reductase (Endo A, 1992).

Furthermore, fenofibrate decreased the level of low-density lipoprotein cholesterol (LDL-C), especially "small dense LDL", which may be a powerful metabolic contributor to arteriosclerosis (Superko, 2000).

PPAR-α regulates the transcription of lipid-associated genes and various genes involved in homeostasis, suggesting the PPAR-α-mediated pleiotropic activities of fenofibrate. The reports on the pleiotropic activities of fenofibrate has been accumulated in a variety of largescale, randomized, controlled trials (RCTs).

The studies presumably associated with the anti-aging actions of fenofibrate are reviewed in this article.


5. Empirical analysis of FDI in Chongqing and Beijing

From discussions above, it is found that GMM has higher prediction accuracy and better fitting effects than those of TSM of Chinese FDI level. To further verify the credibility of this result, we construct GMM and TSM based on the FDI level of Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend… DOI: http://dx.doi.org/10.5772/intechopen.83801

Beijing (1990–2016) and Chongqing (1990–2015). The divided states involved in the GMM are shown in Table 7, and the transition matrixes of GMM associated with Beijing and Chongqing are denoted as P2 and P3. For simplification, we only list the form of transition matrix P2. The comparison of GM(1,1) and GMM can be seen in Tables 8 and 9. The average relative errors of GM(1,1) and GMM of Beijing (Chongqing) are 0.0312 (0.5285) and 0.0029 (0.1051), respectively. The Gray

Table 7.

Residual states of FDI in Beijing and Chongqing.

Annotations: In Table 8, the unit of original value is 1 million dollars. GM, GMM, and TSM represent the predicted value of Gray model, Gray-Markov model, and time series model, and their unit is 106 million dollars. GR and MR represent the residuals of Gray model and Gray-Markov model. Data source: Beijing Statistical Yearbook (1990–2017), Beijing Municipal Bureau of Statistics.

#### Table 8.

Comparison of predicted errors of GMM and GM(1,1) of Beijing FDI level.

4.3.2 Comparing predicted values with actual values

Figure 3.

Figure 4.

110

Original value and that in TSM.

Original value and that in GMM.

Time Series Analysis - Data, Methods, and Applications

As shown in Table 6, the prediction accuracy of GMM has been improved manifestly compared with that in GM(1,1) model. Therefore, the forecasting value in GMM is closer to the actual level of China's FDI. Then, from Figures 3 and 4, we

From discussions above, it is found that GMM has higher prediction accuracy and better fitting effects than those of TSM of Chinese FDI level. To further verify the credibility of this result, we construct GMM and TSM based on the FDI level of

can clearly see that GMM model has a better fitting effect than that in TSM.

5. Empirical analysis of FDI in Chongqing and Beijing

relational degrees of GM(1,1) and GMM of Beijing (Chongqing) are 64.62% (75.26%) and 79.39% (86.82%), respectively. Therefore, the errors of GM(1,1) and GMM are barely qualified or qualified, and hence GMM is superior to GM(1,1):

Similar to Section 4.2, TSM of Beijing FDI can be modeled as MA (1):

Year Original value GM(1,1) GMM TSM To state GR MR 2009 401,643 4.1914 3.6046 0.6941 E1 0.0417 �0.1143 2010 304,264 4.8388 2.8307 0.6809 E2 0.3712 �0.0749 2011 582,575 5.5862 3.2679 0.2878 E2 �0.0429 �0.7827 2012 352,418 6.4490 3.7727 1.2269 E2 0.4535 0.0659 2013 414,353 7.4452 4.3554 0.2769 E2 0.4435 0.0487 2014 423,348 8.5952 1.8909 0.5837 E4 0.5075 �1.2388 2015 377,183 9.9228 2.1830 0.5124 E4 0.6199 �0.7278 332 0.0033 0.0029 0.0003 E1 0 �0.1628 Annotations: In Table 9, the unit of original value is 1 million dollars. GM, GMM, and TSM represent the predicted value of Gray model, Gray-Markov model, and time series model, and their unit is 105 million dollars. GR and MR represent the residuals of Gray Model and Gray-Markov model. Data source: Chongqing Statistical Yearbook

Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend…

TSM of Chongqing FDI can be modeled as ARMA(1,2,1):

Original value and that in GMM of BJ. Annotations: BJ denotes the city of Beijing.

Comparison of predicted errors of GMM and GM(1,1) of Chongqing FDI level.

where X ¼ num � 0:27264 and t ¼ year.

(1990–2016), Beijing Municipal Bureau of Statistics.

DOI: http://dx.doi.org/10.5772/intechopen.83801

Table 9.

Figure 5.

where X ¼ num � 2:178452 and t ¼ year.

ð Þ 1 þ 0:82673B 1 � B2 Xt ¼ εt

ð Þ 1 � 0:82442B ð Þ 1 þ B 1 � B2 Xt ¼ εt

Figure 5 (Figure 6) shows the difference between the original value and the predicting value in Gray-Markov model (time series model) of foreign direct investment in Beijing. It is apparent that the fitting effect of GMM is better than

Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend… DOI: http://dx.doi.org/10.5772/intechopen.83801

Annotations: In Table 9, the unit of original value is 1 million dollars. GM, GMM, and TSM represent the predicted value of Gray model, Gray-Markov model, and time series model, and their unit is 105 million dollars. GR and MR represent the residuals of Gray Model and Gray-Markov model. Data source: Chongqing Statistical Yearbook (1990–2016), Beijing Municipal Bureau of Statistics.

#### Table 9.

relational degrees of GM(1,1) and GMM of Beijing (Chongqing) are 64.62% (75.26%) and 79.39% (86.82%), respectively. Therefore, the errors of GM(1,1) and GMM are barely qualified or qualified, and hence GMM is superior to GM(1,1):

>

 0 0

BBBBBBBBBBBBBB@

 0 0

CCCCCCCCCCCCCCA , Pð Þ5 ¼

Year Original value GM(1,1) GMM TSM To state GR MR 332 0.0033 0.0029 0.0003 E1 0 �0.1628 977 0.3159 0.0347 0.0010 E5 0.9691 0.7188 1992 10,247 0.3647 0.1276 0.0029 E3 0.7190 0.1972 1993 25,915 0.4210 0.2463 0.0846 E2 0.3844 �0.0523 1994 44,953 0.4860 0.4180 0.0686 E1 0.0751 �0.0755 1995 37,926 0.5611 0.3282 0.0842 E2 0.3241 �0.1554 1996 21,878 0.6478 0.2267 0.0406 E3 0.6623 0.0350 1997 38,466 0.7478 0.4375 0.0165 E2 0.4856 0.1207 1998 43,107 0.8633 0.5050 0.0755 E2 0.5007 0.1465 1999 23,893 0.9967 0.2193 0.0563 E4 0.7603 �0.0897 2000 24,436 1.1506 0.2531 0.0181 E4 0.7876 0.0347 2001 25,649 1.3284 0.2922 0.0296 E4 0.8069 0.1223 2002 28,089 1.5335 0.1687 0.0329 E5 0.8168 �0.6651 2003 31,112 1.7704 0.1947 0.0360 E5 0.8243 �0.5976 2004 40,508 2.0439 0.4497 0.0417 E4 0.8018 0.0991 2005 51,575 2.3596 0.5191 0.0599 E4 0.7814 0.0065 2006 69,595 2.7241 0.9534 0.0776 E3 0.7445 0.2700 2007 108,534 3.1448 1.1007 0.1059 E3 0.6549 0.0139 2008 272,913 3.6306 3.1223 0.1930 E1 0.2483 0.1259

 0

  CCCCCCCCCCCCCCA , Pð Þ3 ¼

 0

BBBBBBBBBBBBBB@

 3

 0 0

000

 0 1

>

0 0

0 0

CCCCCCCCCCCCCCA

 0

0 0

  CCCCCCCCCCCCCCA ,

 0

BBBBBBBBBBBBBB@

Pð Þ1 ¼

BBBBBBBBBBBBBB@

 0

2

Pð Þ 4 ¼

  CCCCCCCCCCCCCCA , Pð Þ2 ¼

Time Series Analysis - Data, Methods, and Applications

 0

BBBBBBBBBBBBBB@

0 0

 3

 0 0

   0

000

Comparison of predicted errors of GMM and GM(1,1) of Chongqing FDI level.

Similar to Section 4.2, TSM of Beijing FDI can be modeled as MA (1):

$$(\mathbf{1} + \mathbf{0}.\mathbf{82673B}) \left(\mathbf{1} - \mathbf{B}^2\right) \mathbf{X}\_\mathbf{t} = \mathbf{e}\_\mathbf{t}$$

where X ¼ num � 0:27264 and t ¼ year. TSM of Chongqing FDI can be modeled as ARMA(1,2,1):

$$(\mathbf{1} - \mathbf{0}.\mathbf{82}\mathbf{44}\mathbf{2B})(\mathbf{1} + \mathbf{B})(\mathbf{1} - \mathbf{B}^2)\mathbf{X}\_\mathbf{t} = \mathbf{e}\_\mathbf{t}$$

where X ¼ num � 2:178452 and t ¼ year.

Figure 5 (Figure 6) shows the difference between the original value and the predicting value in Gray-Markov model (time series model) of foreign direct investment in Beijing. It is apparent that the fitting effect of GMM is better than

Figure 5. Original value and that in GMM of BJ. Annotations: BJ denotes the city of Beijing.

Figure 6. Original value and that in TSM of BJ. Annotations: BJ denotes the city of Beijing.

that of TSM. The similar conclusion can be drawn from Figures 7 and 8. Tables 9 and 10 show the predicting effect of GMM is better than that of TSM from the point of predicting errors and accuracy. There is no doubt that it is a good thing to predict accurately the foreign direct investment of the forthcoming 5 or 10 years for the domain specialists. Because if the predicting results is lower or higher than they expected, they could pay attention to seeking the critical factors and policy which have impacts on FDI and adjust them in advance.

6. Conclusions and future work

Comparison of predicting accuracy of two models.

Area Index MSE ¼ 1

DOI: http://dx.doi.org/10.5772/intechopen.83801

Figure 8.

error.

115

Table 10.

international investment.

Our contributions are threefold. Firstly, comparing the predicting results of the Gray-Markov model and the time series model and the original value, respectively, we can find that the fitting effect of the former (GMM) is better than the latter (TSM) and so does its scientific and practical importance. Secondly, the predicting results of GMM show that the level of foreign investment in China has been increasing by years. Thirdly, in order to further enhance Chinese international status and attract more foreign investment, the government should play a role at a macro level to reduce excessive market administrative intervention, establish a service-oriented government, and reduce the relevant approval procedures for

Original value and that in TSM of CQ. Annotations: CQ denotes the city of Chongqing.

n ∑n

i¼1 xi � bxi ð Þ2 MAE ¼ 1

Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend…

GMM 4.3599e+09 3.9369e+04 0.1032 TSM 5.4378e+09 4.6731e+04 0.1335

GMM 5.8230e+09 3.4080e+04 0.2663 TSM 4.4524e+10 1.0126e+05 0.6018 Annotations: MSE, MAE, and MAPE denote mean squared error, mean absolute error, and mean absolute percentage

Beijing GM(1,1) 3.3244e+09 4.7473e+04 0.2587

Chongqing GM(1,1) 3.9173e+10 1.3478e+05 2.9584

n ∑n

i¼1 xi � xbi j j MAPE ¼ 1

n ∑n i¼1 xi�bxi xi � � � � � �

Figure 7. Original value and that in GMM of CQ. Annotations: CQ denotes the city of Chongqing.

Using Gray-Markov Model and Time Series Model to Predict Foreign Direct Investment Trend… DOI: http://dx.doi.org/10.5772/intechopen.83801

Figure 8. Original value and that in TSM of CQ. Annotations: CQ denotes the city of Chongqing.

Annotations: MSE, MAE, and MAPE denote mean squared error, mean absolute error, and mean absolute percentage error.

#### Table 10.

that of TSM. The similar conclusion can be drawn from Figures 7 and 8. Tables 9 and 10 show the predicting effect of GMM is better than that of TSM from the point of predicting errors and accuracy. There is no doubt that it is a good thing to predict accurately the foreign direct investment of the forthcoming 5 or 10 years for the domain specialists. Because if the predicting results is lower or higher than they expected, they could pay attention to seeking the critical factors

Original value and that in TSM of BJ. Annotations: BJ denotes the city of Beijing.

Time Series Analysis - Data, Methods, and Applications

Figure 6.

Figure 7.

114

and policy which have impacts on FDI and adjust them in advance.

Original value and that in GMM of CQ. Annotations: CQ denotes the city of Chongqing.

Comparison of predicting accuracy of two models.


**About the Editors**

#### **Chengfang Li**

Chengfang Li, Doctor, associate professor, College of Plant Science and Technology of Huazhong Agricultural University; major in Conservation tillage management and agricultural ecology, including conservation tillage, plant fertilization, water-saving irrigation, global warming potential, soil nutrient cycles, soil carbon sequestration, crop yield; soil microbial community, greenhouse gas emission, etc.

#### **Lijin Guo**

Lijin Guo, Doctor, Lecturer, College of Resources and Environment, Fujian Agriculture and Forestry University; major in conservation tillage management and soil organic carbon, including conservation tillage, soil organic carbon, carbon sequestration, soil microbial community, mycorrhizal fungi, abiotic stress, greenhouse gas emission, climate change impact and adaptation, etc.


**Research and Development of New Drugs Against Tuberculosis**

Juan D. Guzman, Ximena Montes-Rincón and Wellman Ribón

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/54278


**Abstract**

SYNTHESIS is a platform of platforms (PoP) for the management, curation, and creation of digital cultural experiences related to cultural heritage material (artifacts), and their visualization through mobile applications and virtual and augmented reality (VR/AR) technologies. The digital cultural experiences may relate to specific cultural heritage monuments or exhibits of museum collections and may reside either on site or remotely. The platform provides a comprehensive supervisory tool that allows curators to select digital artifacts from different databases around the topic of interest, associate them through narratives that translate them into a sequence of semantic correlations that can be visualized using VR/AR technologies. The SYNTHESIS of platforms contributes to the creation of a new condition for the promotion of cultural heritage sites, museums, and exhibits, and facilitates the management and interaction of the user-visitor with them. The platform contributes to the creation of an innovative system for the management and curation of large volume of digital material related to an exhibit and consequently its promotion by unifying the stages of: (a) production of digital content; (b) connection of additional digital multimedia material related to the digital content; (c) curation of the digital content and transformation to a digital experience in accordance to a desired narrative; and (d) visualization of the digital experience in-situ or remotely with the use of mobile apps and VR/AR technologies.

**Keywords:** Narration, digital experience, curation, digital cultural artifacts, visualization, virtual reality, augmented reality, mobile apps, VR/AR technologies, digital tourism


**Author details**

Yuriy Zhulay1 and Olexiy Nikolayev2 \*

1 Institute of Transport Systems and Technologies of National Academy of Sciences of Ukraine, Dnepr, Ukraine

2 Institute of Technical Mechanics of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine, Dnepr, Ukraine

\*Address all correspondence to<EMAIL_ADDRESS>
© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


*5.2. Inference from Historical Storms in the North Atlantic*

Given their geographic location, archipelagos located north of Cabo Verde off the northwest coast of Africa are likely to be impacted by high-energy storms [25]. The Azores Archipelago is struck by high-energy storms with a frequency every seven years [26], causing several shipwrecks in the harbor of Ponta Delgada on São Miguel (Figure 7a). More recently, the passage of Hurricane Lorenzo in October 2019 caused the destruction

of several piers among the islands, as well as the near disappearance of Lajes das Flores harbor (Figure 7b). The Canary Islands are no exception. The high-energy events that affect the islands have caused considerable damage [12] and even fatalities (Figure 7c,d).

**Figure 7.** Evidence of destruction caused by storms in the Azorean and Canary islands; (**a**) Shipwrecks in Ponta Delgada harbor (São Miguel, Azores) after the December 1996 storm (photo by João Brum); (**b**) Destruction of the pier of Lajes das Flores (Flores Island, Azores) after the passage of Hurricane Lorenzo in October 2019 (Flores Island, Azores) after the passage of Hurricane Lorenzo in October 2019 (*Journal Açores* 9, 2019); (**c**) Shipwreck beached in Gran Canaria after the November 1968 storm (*Efemérides Meteorlógicas de Canárias*, 2018); (**d**) destruction caused by the April 1970 storm that hit Gran Canari (*Efemérides Meteorlógicas de Canárias*, 2018).

Historical records (Table 3) are scarce in terms of available wave-height information. However, in some cases inferences can be made: the events of 21 February 1966 (10 to 12 m), 23 November 1968 (10 m), and 21 April 1970 (8 m). These inferences suggest that storm waves can reach considerable values in the Canary Islands. Empirical models for wave modulation about the island of Gran Canaria indicate average wave height values between 5.22 and 5.58 m [27,28]. Such wave heights are compatible with the maximum average values estimated for boulders summarized for location 6 (Table 2) with averages based on Equation (1) [17] of 5.5 m and Equation (2) [19] of 5.6 m. The location of El Confital beach within the bay also is pertinent. The development of the volcanic edifice of La Isleta (Figure 1c) played an important role in protecting the area. Although consideration of the effect and action of waves before the Last Interglacial Epoch is possible, the formation of a large sandy isthmus since that time connected the La Isleta to the larger island of Gran Canaria, making the area even more sheltered from storm events. No direct evidence is observable at El Confital, but it is necessary to remember that the Canary Islands are subject to tsunami waves resulting from earthquakes like the wider regional event of 1755 that destroyed Lisbon, as well as volcanic flank collapse on the home islands.

**Table 3.** Coastal disturbances between 1755 and 2009 that affected Gran Canaria and islands elsewhere in the Canary Archipelago.

#### *5.3. Comparison with Coastal Boulder Deposits Elsewhere*

Pleistocene and Holocene deposits formed by cobbles and boulders are widely distributed all around the world [3], but studies in coastal geomorphology seldom consider density as related to parent rock types when investigating the range of wave heights necessary for their development as eroded boulders. Application of mathematical formulae such as Equation (1) from Nott [17] to estimate storm wave height has been applied previously to coastal boulder deposits throughout Mexico's Gulf of California, including those formed by limestone, rhyolite, and andesite clasts [4–6]. Extension of this work to include Equation (2) as derived from Pepe et al. [19] also has been applied to coastal basalt deposits in the Azores [1]. The variation in mass among these rock types ranges from 1.86 gm/cm3 for limestone, 2.16 gm/cm3 for the rhyolite, 2.55 gm/cm3 for andesite, and 3.0 gm/cm3 for basalt.

Among the largest Holocene boulders treated in these studies are those derived from rhyolite shores on the Gulf of California yielding mega-boulders with a calculated weight of 4.3 metric tons requiring an estimated wave height of 16.8 m to shift from the parent rocky shore [5]. In this particular case, the estimated wave height from storms in the Gulf of California is commensurate with the wave height formulated for the largest basalt boulder recorded anywhere on El Confital beach at study site 6 (Table 2). The recent history of hurricanes in the Gulf of California filmed under direct observation, confirms wave heights at least half that size against contemporary rhyolite sea cliffs [5].

The island of Santa Maria in the Azores has yielded a study comparing present-day and Upper Pleistocene basalt boulders [1] most applicable to the present study at El Confital beach in Gran Canaria. The largest Pleistocene boulder recorded in that study is smaller than many of the typical basalt boulders from El Confital, but still exemplified an estimated wave height of 8 m necessary for its emplacement. The largest boulder from a modern deposit on Santa Marine Island was calculated to require a wave height of 6.4 m for its emplacement [1].

Technically, hurricanes have a tropical to subtropical source dependent on high oceansurface water temperatures and excessive air moisture [29]. However, major storms of hurricane intensity also occur in Arctic latitudes, where contemporary and Holocene boulder deposits occur along the coast of Norway. Small boulders formed by low-grade chromite ore with a density of 3.32 g/cm3 are described from Holocene deposits on Norway's Leka Island that imply wave heights as much a 7 m for their emplacement [30].

#### *5.4. Notes on the Geoheritage of El Confital Beach*

El Confital beach takes its name from the former abundance of "confites" (candies in English) on the beach, a popular name given to rhodoliths throughout the Canary Islands for their white color and ball-like shape. Notably, the study area at El Conital beach is richly fossiliferous as known since the visit by Charles Lyell in 1854 to Gran Canaria island [31]. Historically, deposits with fossil rhodoliths, as well as other carbonates were exploited massively to manufacture lime, due to the lack of this resource in the Canary Islands. This industry has led to the loss of essential paleontological paleoecologial, and taphonomical information. The outcrop at El Confital was chosen as a Geosite (site of geological interest, acronym LIG in Spanish) [32,33] and is included in the Inventory of Geosites of the Canary Islands, carried out by project LIGCANARIAS [11,34], due to its high scientific value that represents an area where different types of geological heritage are combined. Stratigraphic sequence is the central feature around which others are related including paleontology, sedimentology, and geomorphology [34–37]. The volcano-sedimentary sequence at El Confital reaches a maximum level of 200 m above sea level in which characteristics of the geological evolution of Gran Canaria island are represented.

As shown in this study, the significance of El Confital is magnified as an example of an accumulation zone of basaltic boulders of different sizes that denote high-energy events essential to understanding the impact of storms and hurricanes in the island groups of the North Atlantic. Apart from the materials belonging to the last interglacial maximum (MIS5e) described in this paper, El Confital includes a range of other features represented by submarine and subaerial basaltic deposits and hyaloclastites (peperites) together with marine sands and conglomerates, aeolian sand dunes, and colluvial deposits [35].

For all its value as a Geosite with high scientific, educational, and touristic value [32,33,35,36], El Confital beach is extremely fragile and vulnerable to human impact and climate change. Therefore, it remains necessary to adopt a management plan that ensures its regulatory protection in the short- and intermediate-term [37]. Although adjacent to the Bahia del Confital Special Conservation Area, Community Interest Area, as well as La Isleta Marine Area, and the Protected Landscape of La Isleta, it is urgent that the Geosite attain an effective geoconservation plan sanctioned by the regional government of the Canary Islands.


**2.15** *Strix virgata*

*S. v. virgata:* Stomach contents of three museum specimens (ANSP 181031, MECN 6991, 8350) contained remains of Coleoptera, other insects, and one reptile [23]. No information from the Amazonian population, whose subspecific identity remains unsolved [33].


**6. SEM fractography**

SEM micrographs are generally used to give information about the type of fracture. Here, since tensile tests have not been done, SEM has been used to identify Sn whiskers. There have been some studies showing Sn whiskers in the SEM micrographs of SnCu alloys.

The abovementioned SEM micrographs are of two samples of slightly varying chemical composition. **Figures 18** and **19** show the absence of tin whiskers in both

**Figure 18.** *Sample 1.*

**Figure 19.** *Sample 2.*

the alloys. The presence of tin whiskers results in deterioration of electrical properties. Chuang and Lin [24] showed that 0.5% Zn addition into SnAgCu solder refined the microstructure and suppressed whisker growth.

Sn**▬**Zn alloys have been used as a substitute for Pb**▬**Sn alloys. However, Sn**▬**Zn alloys are susceptible to oxidation and ZnO forms easily (**Figures 20** and **21**) [25–27].

SEM micrographs are for two different compositions of Sn**▬**Zn**▬**La leadfree solders (composition as mentioned in the Hardness **Tables 4** and **5**). Some

**Figure 20.** *SEM micrographs of Sn▬Zn▬La alloys.*

**21**

*Role of Intermetallics in Lead-Free Alloys DOI: http://dx.doi.org/10.5772/intechopen.85515*

precipitates are seen, which may have an effect on the hardness and tensile strength of the solders. However, in this case, it was found that hardness for both alloys is around 18 HV. Hence, the effect of precipitates seems to be marginal for this leadfree alloy. These SEM micrographs have been taken from unpublished work done by

There is not much difference between the EDAX of the two samples. There do not seem to be intermetallics present in this alloy. Hardness values also corroborate

This chapter starts with the importance of intermetallic systems in lead-free solders. The effect of some rare earths like lanthanum and indium on intermetallic formation in lead-free alloys has been explained. Tin-zinc-lanthanum and tin-zincaluminium-indium have been chosen for detailed analysis. Microhardness surveys have been done along two perpendicular diagonals of a square-shaped specimen, and the results of the microhardness surveys have been analysed. Microstructures in both these systems have been discussed with respect to the phases present and their distribution. Based upon both the microhardness and microstructure of the two alloys chosen, the presence of intermetallics and the types of intermetallics has been discussed. Growth kinetics of intermetallics has been briefly analysed. SEM fractographs have been taken to show the type of fracture. EDAX has been employed to

the author as part of undergraduate project work.

*EDAX of Sn▬Zn▬La of slightly different composition.*

EDAX Studies of two samples (**Figures 22** and **23**).

EDAX Studies.

this statement.

**Figure 22.**

**Figure 23.**

*EDAX of Sn▬Zn▬La sample.*

**7. Conclusion**

show the distribution of phases.

**Figure 21.** *SEM micrographs of Sn▬Zn▬La alloys.*

**Figure 22.** *EDAX of Sn▬Zn▬La sample.*

#### **Figure 23.**

*Lead Free Solders*

[25–27].

**Figure 19.** *Sample 2.*

**Figure 20.**

*SEM micrographs of Sn▬Zn▬La alloys.*

*SEM micrographs of Sn▬Zn▬La alloys.*

the alloys. The presence of tin whiskers results in deterioration of electrical properties. Chuang and Lin [24] showed that 0.5% Zn addition into SnAgCu solder refined

Sn**▬**Zn alloys have been used as a substitute for Pb**▬**Sn alloys. However, Sn**▬**Zn

alloys are susceptible to oxidation and ZnO forms easily (**Figures 20** and **21**)

SEM micrographs are for two different compositions of Sn**▬**Zn**▬**La leadfree solders (composition as mentioned in the Hardness **Tables 4** and **5**). Some

the microstructure and suppressed whisker growth.

**20**

**Figure 21.**

*EDAX of Sn▬Zn▬La of slightly different composition.*

precipitates are seen, which may have an effect on the hardness and tensile strength of the solders. However, in this case, it was found that hardness for both alloys is around 18 HV. Hence, the effect of precipitates seems to be marginal for this leadfree alloy. These SEM micrographs have been taken from unpublished work done by the author as part of undergraduate project work.

EDAX Studies.

EDAX Studies of two samples (**Figures 22** and **23**).

There is not much difference between the EDAX of the two samples. There do not seem to be intermetallics present in this alloy. Hardness values also corroborate this statement.