4.2.1. General Properties and Multi-Wavelength Observations

The extremely bright prompt emission of this event, which is the seventh in brightness among the GRBs detected by the Fermi-GBM until then, lasted for *T*90 = 48.9 ± 0.4 s and released an isotropic-equivalent energy *Eγ*,*iso* = 6.0 ± 0.1 × 1053 erg in the 50–300 keV range.

Multi-wavelength afterglow observations covered the entire electromagnetic spectrum (see Figure 11). A significant signal was detected by Fermi-LAT from the trigger time up to 700 s, with the highest photon energy of 5 GeV detected 137 s after the burst trigger [160]. The Swift-XRT telescope observed and identified a bright afterglow starting from 90 s. This was still visible almost 30 days after the trigger time. The late-time light curve (from 2 × 103 s to 4 × 106 s) can be modeled with an initial power-law decay with an index −1.19+0.01 −0.02 followed by a break at *tbreak* = 8 × 104 s to an index of −1.55+0.04 −0.05 5 . Several optical observations [161–170] revealed the presence of a counterpart and allowed us to estimate the redshift value of *z* = 0.654. The optical afterglow was observed to be slowly fading at an almost constant rate from around 10–11 h after the trigger time [171,172] as discussed in [173]. Radio observations (not shown in the figure) were also performed starting from ∼1.7 days after the burst showing a steep power-law decaying emission [173].


Contents

Preface

*Heat Illness and Critical Care* describes the management of acute and critically ill patients due to exposure to the heat. It discusses important topics in acute care and diagnosis of heat-related illnesses. Chapters address professionalism and teamwork in the management of heat-related illnesses. This book is a useful resource for emergency and acute care physicians, EMS staff, and acute and critical care nurses. We are thankful to Ms. Kristina Kardum Cvitan for her continuous help at all stages of the publication process. I am indebted and thankful to Dr. Firdos for her support and encouragement during the editing process. I am grateful for the patience and cooperation of my daughters Dr. Amara and Dr. Jaza.


**FRONTIERS IN BIOENERGY AND BIOFUELS**

Edited by **Eduardo Jacob-Lopes**  and **Leila Queiroz Zepka**

#### **Frontiers in Bioenergy and Biofuels**

http://dx.doi.org/10.5772/63185 Edited by Eduardo Jacob-Lopes and Leila Queiroz Zepka

#### **Contributors**

Ewa Pecka-Kiełb, Andrzej Zachwieja, Dorota Miśta, Wojciech Zawadzki, Anna Zielak-Steciwko, Patrick Mukumba, Masahide Yasuda, A. K. M. Aminul Islam, Md. Moniruzzaman, Muhammad Farooq, Gisela Montero, Conrado García, Margarita Stoytcheva, Marcos Coronado, Lydia Toscano-Palomar, Ricardo Torres, Ana MarÃa Vázquez, Daniela Montes Nuñez, Vinicyus Rodolfo Wiggers, Laércio Ender, Edésio Simionatto, Henry Meier, Ramon Beims, Venko Beschkov, Elina Bastos Caramao, Javed Iqbal Qazi, Fouzia Tabssum, Valentin Antonovič, Jadvyga Kerienė, Rimvydas Stonys, Renata Boris, Jacek Szczerba, Eduardo Montero, Fernando Aguilar, Natalia Muñoz-Rujas, Fatima E. M. Alaoui, Henry Quesada Pineda, Jeremy Withers, Robert Smith, Valentin Missiakô Kindomihou, Roland Ahouélété Yaovi Holou, Claudia Santibanez, Edson Luiz Silva, Paula Rúbia Ferreira Rosa, Romana Krištof, Jose Castanheiro, Salete Alves, Saima Mirza, Habib Ur Rehman, João Cajaiba Da Silva, Alex Queiroz, Alline Oliveira, Vinicius Kartnaller, Amornvadee Veawab, Hanifa Taher, Sulaiman Al-Zuhair, Elisabeth Jamet, Maria Juliana Calderan-Rodrigues, Juliana Fonseca, Carlos Alberto Labate, Eduardo Jacob-Lopes

#### **© The Editor(s) and the Author(s) 2017**

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First published in Croatia, 2017 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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**5. Measure of crop diversification and its characterization**

Different measurements of crop diversification and their characterization are depicted in the **Table 2** [24].

#### **Table 2.**

*Measure of crop diversification and its characterization.*

*Crop Diversification an Effective Strategy for Sustainable Agriculture Development DOI: http://dx.doi.org/10.5772/intechopen.102635*

#### **Table 3.**

*Extent of diversification and sources of diversification in South Asian countries.*


*4.2. Flood Extent and Frequency for Winter 2019/2020 in Estonian Floodplains*

In Figure 5, open water and water under vegetation mapped from S1 data for winter 2019/2020 at our test sites are presented. The winter of 2019/2020 was extremely warm in Estonia. The monthly average temperatures from November 2019 to March 2020 were above zero (Figure 6). Climatological averages for December, January, February, and March have been negative in Estonia in the past (Figure 6). Due to positive air temperatures in the 2019/2020 winter, the soils did not freeze, there was no permanent ice cover on inland waters, and the precipitation was mostly rain. Due to the environmental conditions of winter 2019/2020, open water could be mapped throughout the winter. The flooded area (in hectares—ha) was estimated as the extent of water-covered area outside the official shoreline within the region of interest shown in Figure 1.

**Figure 5.** *Cont*.

(**e**) (**f**)

**Figure 5.** Floods mapped at test sites; (**a**) Open water frequency (%) at Alam-Pedja, (**b**) Frequency of water under vegetation (%) at Alam-Pedja, (**c**) Extent of open-water flood (ha) and water level (cm) at Alam-Pedja, (**d**) Extent of flood under vegetation (ha) and water level (cm) at Alam-Pedja, (**e**) Open water frequency (%) at Soomaa, (**f**) Frequency of water under vegetation (%) at Soomaa, (**g**) Extent of open-water flood (ha) and water level (cm) at Soomaa, (**h**) Extent of flood under vegetation (ha) and water level (cm) at Soomaa, (**i**) Open water frequency (%) at Matsalu, (**j**) Frequency of water under vegetation (%) at Matsalu, (**k**) Extent of open-water flood (ha) and water level (cm) at Matsalu, (**l**) Extent of flood under vegetation (ha) and water level (cm) at Matsalu.

**Figure 6.** Meteorological data: monthly average air temperature (black) and corresponding climatological average (blue).

At the Alam-Pedja test site, open-water floods occurred near the Emajõgi river. The frequency of flood in pixel varied mainly between 5 and 25%; however, in some areas it reached over 50% (Figure 5a). Figure 5c also shows the water level measured at the Tartu hydrological station on the Emajõgi river and the estimated open-water flood extent. From mid-February, the water covered area repeatedly exceeds the shoreline, and the maximum open-water flood extent (>1000 ha) lasted from February 29 until 15 March 2020 (Figure 5c). In Figure 5, the flood frequency (Figure 5b) and extent (Figure 5d) under the vegetation at the Alam-Pedja test site are also shown. The extent of the flooded area under the vegetation was about three times larger than that of the open-water flood, reaching up to 3500 ha on 13 March 2020 (Figure 5d). However, the frequency of FUV was lower than that of the open-water flood, between 5 and 25%.

At the Soomaa floodplain, the largest flood extent was detected at the beginning of the study period on 7 November 2019, when the open-water flood reached up to 230 ha and the flooded area under the vegetation was 4400 ha (Figure 5g,h). Starting from mid-November, the open-water flood decreased, and the following flood events occurred in mid-December and mid-January. The last flood event lasted from mid-February until mid-March (Figure 5g). The maximal water level measured at the Riisa hydrological station corresponds well to the maximal open-water flood events (Figure 5g). The frequency of open-water flooding remained below 50% in Soomaa. The flood extent analysis revealed that floods detected under the vegetated area lasted through the winter. In the forested area at the Soomaa test site, the floods were absent only during the second half of November (Figure 5h). The flood frequency map presented in Figure 5f indicates the forested areas (dark blue denotes flood frequency >75%) where floods occurred throughout almost the whole duration of the winter.

At the Matsalu test site, large open-water floods outside the official shoreline (ETD) could be detected throughout almost the whole duration of the winter (Figure 5k). The maximum open-water flood extent was detected in March, reaching up to 3000 ha (Figure 5k). In Figure 5i, there is a highlighted area (red rectangle) where open-water floods were observed most frequently (on more than 70% of images). The Matsalu test site has fewer forested areas than the Alam-Pedja and Soomaa test sites. However, there are large areas covered with coastal reed at this test site. The largest floods under the vegetation at this test site are related to an area with coastal reeds (Figure 5j, red rectangle). At the Matsalu test site, the floods under the vegetated area were smaller at 1300 ha (Figure 5k), compared to the open area floods at 3000 ha (Figure 5l).

#### *4.3. Causation Analysis between Flood Extent and Water Level Measured at Hydrological Stations*

An analysis was performed with the aim of defining the critical water level at the closest hydrological station that indicates the start of a flooding event (shoreline excess), and to find site specific relationships between the measured water level and flood extent. At the Alam-Pedja test site, a polynomial relationship between the flooded area extent and water level measured at the Tartu hydrological station (HS) was observed (Figure 7). The correlation (r2) with water level was most significant (0.94) for the open-water flood extent estimated from IW VH data; the correlation (r2) for EW HV was 0.85 (Figure 7). The r2 between the flooded area extent under vegetation and the water level measured at the Tartu HS was 0.51 (Figure 7). Our analysis indicated that open-water floodings at the Alam-Pedja floodplain occur when the water level at the Tartu HS increases above 120 cm (Figure 7, red line). Additionally, there was a significant correlation (0.51) between the extent of the flooded area under vegetation and the water level measured at the Tartu HS. It was not possible to define the precise critical water level for the Tartu HS at which flooding under vegetation starts (Figure 7).

**Figure 7.** Correlation between flooded area and water level at the closest hydrological station. FA: flooded area extent; WL: water level. Red line denotes the critical water level at which coastline excess occurs and flooding starts.

The relationship between the water level at the Riisa HS and the flooded area extent at Soomaa was polynomial (Figure 7). The correlation coefficient (r2) between the Soomaa open-water flood extent and the water level measured at the Riisa hydrological station was 0.62 for EW HV data and 0.57 for IW VH data (Figure 7). The correlation (r2) between the water level measured at the Riisa hydrological station and the flooded area extent under vegetation was 0.29 (Figure 7). Our analysis showed that open-water floodings occur when the water level at the Riisa HS increases above 160 cm (Figure 7, red line).

While the relationship between the water level and the extent of the flooded area was polynomial at the Alam-Pedja and Soomaa test sites, the relationship was linear at the Matsalu test site. The r2 between the open-water flood extent at the Matsalu site and the water level measured at the Kasari hydrological station was 0.34 for IW VH data and 0.38 for EW HV data (Figure 7). There was no correlation between the water under vegetation and the water level measured at the Kasari HS (Figure 7). At the Matsalu test site, floods occurred throughout the winter, and it was not possible to define a precise critical water level at the Kasari HS that could be related to the beginning of flooding.

#### **5. Discussion**

Previous studies have shown the advantages of incidence angle dependent thresholding in the case of TerraSAR-X and Envisat ASAR datasets [18,54]. Our operational setup for flood mapping from S1 data for Estonian floodplains integrates incident angle dependent water thresholding and post-processing using auxiliary information from the Estonian Topographic Database. Post-processing using information from the ETD enables the elimination of water lookalikes. We evaluated the open water mapping accuracy for IW mode VH polarization at our test sites. There was good agreement between the water mapped from IW VH data and the S2 MNDWI index, with an accuracy as high as 96.70% and a kappa hat of 0.86 (Table 6). The accuracy of flood mapping using S1 VH polarization has also been evaluated by Twele et al. [23], who obtained a kappa hat coefficient of 0.88 and an accuracy of 94%. While their operational methodology applied for flood mapping differs from that used in our study, the overall accuracy of the flood mapping is comparable. In the study conducted by Twele et al. [23], the split based thresholding for water mapping was used together with the HAND index in the post-processing step.

During the winter season, the default imaging mode of S1 over the Baltic Sea region is the EW regime. To delineate the information about flooded areas in Estonia, an algorithm for open water mapping for the EW regime was established and applied. The open water mapping accuracy from EW HV polarization data was 97.8%. By including the information from EW data, we could delineate the flood maps approximately using 55 images from each test site. Combining the information from IW and EW regimes, we analyzed 83 images from the Alam-Pedja test site, 93 from the Soomaa test site, and 64 from the Matsalu test site for open water mapping for the period of 1 November 2019–31 March 2020 (Figure 5). Thus, the proposed flood mapping method was tested on a large and diverse dataset. The method developed and proposed in the current study has potential for operational mapping of floods in Estonia and neighboring countries (e.g., Latvia).

The winter of 2019/2020 was extremely mild in Estonia, and there was no permanent ice on the rivers, nor was there snow cover. The monthly averaged air temperature was above 0 ◦C at all meteorological stations. Our analysis of flood duration and extent showed that in the winter of 2019/2020, floods were observed almost through the whole period of winter. However, the dynamics of the floods differed between the test sites. The maximum flooding observed at Alam-Pedja occurred in March, while at Soomaa and Matsalu several flood events were detected during the winter of 2019/2020. Analysis of the open-water flood extent and water level measured at the closest hydrological station confirmed the correlation between these variables. The correlation was more significant (r2 < 0.6) for the inland riverside floodplains of Alam-Pedja and Soomaa. For the coastal floodplain at Matsalu, the correlation was 0.34, indicating that the river gauge data cannot be used as proxy for flood extent as the coastal flood was significantly influenced by marine processes (not only by riverine hydrology and precipitation). The analysis also revealed that at Alam-Pedja, floods occur when the water level rises above 120 cm at the Tartu HS. At the Soomaa test site, floods occur when the water level rises above 170 cm at the Riisa HS. At the Matsalu test site, open water outside the official coastline could be observed throughout the winter, and we could not define the precise water level at the Kasari HS that results in a flooding at the floodplain. The Matsalu floodplain is located at the outflow to the Baltic Sea; therefore, it is also influenced by the water level in the sea.

Defining the water level at the closest hydrological station from which the floods start (shoreline excess occurs) can provide information for risk mitigation. Hydraulic modelling is a common tool used in flood risk estimation [57]. However, for hydraulic and hydrological modelling, detailed information about riverbed topography, a digital elevation model of the landscape, and a flow rate are needed. These datasets are not always available; therefore, analysis of remote sensing information in combination with standard gauge data can give valuable information from a single source. S1 time series analysis with local gauge data has been used to determine the positional accuracy of riverside embankments [58]. A study conducted by Wood et al. [58] also pointed out the possibility of determining the positional accuracy of embankments using only a sequence of S1 imagery and gauge data without using topographic data.

In the winter of 2019/2020, several floods in forested areas that harmed economic activities were also reported in the Estonian press [41]. However, the economic loss caused by wintertime flooding in Estonia is unknown. The current study indicated that at the inland riverside floodplains of Soomaa and Alam-Pedja, the flooded areas under vegetation reached up to 4500 ha and were about three times larger than open-water floods at these test sites. Voormasik et al. [30] analyzed the flood extent at Alam-Pedja from TerraSAR-X imagery and estimated the area of flooded forest to be about three times larger than the extent of the open-water flood. Studies indicate that an evaluation of the extent of flooded forest near inland riverbank floodplains is necessary for the estimation of the total flood extent and its economic consequences. Our analysis also revealed that in the case of the inland water floodplains of Alam-Pedja and Soomaa, flood under vegetation could be correlated with the water levels measured at the closest hydrological station.

#### **6. Conclusions**

The current paper presents an automatic water mapping method for S1 EW and IW modes by compiling local incident angle thresholding and the application of ancillary information from the Estonian Topographic Database in a post-processing scheme. The proposed method was used to analyze the flood duration and extent in Estonian floodplains during the extremely mild winter of 2019/2020. Our analysis revealed the areas that are most frequently inundated in Estonian floodplains. The observed flood maps allowed us to evaluate the connections between the extent of the flooded area and the water level measured at the closest hydrological station. The study enabled us to determine the water level at which floods occur at the floodplains and to provide valuable information for risk mitigation purposes (standard water level readings from automatic stations are available with a ten-minute interval). The analysis of the extent and frequency of wintertime floods can form the basis for various economic analyses, evaluations of revenue foregone in the forest industry due to mild winters, and evaluations of stress to northern boreal alluvial meadows. The analysis also contributes to the implementation of flood risk assessment and management directive in Estonia [59]. Moreover, the proposed method can be implemented for operational flood mapping in Estonia and neighboring countries.

**Author Contributions:** Conceptualization, L.S.; methodology, L.S. and A.A.; software, L.S. and A.A.; formal analysis, L.S. and A.A.; writing—original draft preparation, L.S.; writing—review and editing, L.S., A.A. and R.U.; visualization, L.S. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the European Regional Development Fund within the National Programme for Addressing Socio-Economic Challenges through R&D (RITA1/02-52-04) and by Estonian Environment Agency project "Development and implementation of flood monitoring service from satellite remote sensing data" (LLMAE21069).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not Applicable.

**Data Availability Statement:** The data supporting the conclusions of this article will be made available by the authors, without undue reservation.

**Acknowledgments:** We would like to thank the Estonian Environment Agency for its cooperation.

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

#### **References**


*4.1.3. Cycles and chaos in distributed market economy*

162 Nonlinearity, Bifurcation and Chaos – Theory and Applications

replacement

where parameter

function *f*(,, ) *u v*

 *arctg u u* ( ) .

equations

where the derivative undertakes on a variable

consider the system of Eqs. (48)- (49) with nonlinearities

and function *g*(,, ) *u v*

perturbations distribution along an axis *x* . For *c* 1 ( 1) / (1 )

values of parameters. Besides that, for 1 /

singular points \* \* *Ou u* ( ,0, / )

\* \*

*4.1.2. Running waves, impulses and diffusion chaos in excitable mediums*

Nagumo equations can be written down in the following general form

*u y y cy f u v D v g u v c* , ( ( , , )) / , ( , , ) / ,

Special case of reaction-diffusion systems is the case of systems of the FitzHugh-Nagumo equations describing nonlinear processes occurring in so-called excitable mediums. Examples of such processes are distribution of impulse on a nervous fiber and a cardiac muscle and also various kinds of autocatalytic chemical reactions. The basic property describing a class of excitable mediums is slow diffusion of one variable in comparison with other variable in system of reaction-diffusion (46). Therefore the system of the FitzHugh-

> ( , , ), ( , , ). *t xx t u Du f u v v g u v*

It is well-known, that in system of Eqs. (48) in one-dimensional spatial case there can be switching waves, running waves and running impulses, dissipative spatially nongomogeneous stationary structures, and also diffusion chaos - irregular nonperiodic

The analysis of solutions of system of Eqs. (48) on a straight line can be carried out by

(48) is described by separatrix of the system (49) going from its one singular point into another singular point, running wave and running impulse of system of Eqs. (48) are

Let's show, that diffusion chaos in the system of FitzHugh-Nagumo equations (48) is described by singular attractors of the system of ordinary differential equations (49) in accordance with the Feigenbaum-Sharkovskii-Magnitskii (FSM) theory. For this purpose

*u* , describes some kinds of autocatalytic chemical reactions (Zimmermann et al., 1997). It is easy to see that system of Eqs. (49)-(50) has singular point *O*(0,0,0) for any

A case of greatest interest is, naturally, a case when bifurcation parameter is the parameter *c* , not entering obviously in system of the Eqs. (48) and being the value of velocity of

*x ct* and transition to three-dimensional system of ordinary differential

is a small parameter. Note, that system of Eqs. (48) with polynomial

, where value \* *u* is a positive solution of the equation

(50)

nonstationary structures named sometimes as biological (or chemical) turbulence.

described by limit cycle and separatrix loop of a singular point of the system (49).

*f*( , , ) ( 1)( ) / , ( , , ) ( ) , *u v u u v g u v arctg u v*

having at everyone *v* final limiting values at

system of Eqs. (49)-(50) has two more

  the limit stable

. Thus the switching wave in system of Eqs.

(48)

(49)

Another, essentially different example of formation of spatio-temporal chaos in the nonlinear mediums is the distributed model of a market self-developing economy offered by the author and developed then in (Magnitskii & Sidorov, 2006). The model is a system of three nonlinear differential equations, two of which describe the change and intensity of motion (diffusion) of capital and consumer demand in a technology space under the influence of change of profit rate. The last is described by the third ordinary differential equation.

Self-development of market economy is characterized by spontaneous growth of capital and its movement in the technology space in response to differences in profitability. The model describes formation of social wealth, including production, distribution, exchange, and consumption. A distinctive feature of the model is that distribution of profitability (profit rates) determines the direction and the intensity of motion (diffusion) of capital and its spontaneous growth through generation of added value. Three economic agents having their own interests take part in economic processes that are employers, workers and government. In the model, being based on rigorous rules of Karl Marx's theory of added value, self-development of a market economy involves movement and spontaneous growth of capital of employers, which is the result of creation of added value by workers in the circulation process of capital under government control.

Universality of Transition to Chaos in All Kinds of Nonlinear Differential Equations 165

Consider now the second boundary-value problem for the system of Eqs. (51) on an interval

Linearize the considered problem in the neighborhood of the thermodynamic branch, one can obtain that it is stable only when 1 2 *d dd* / (Magnitskii & Sidorov, 2006). Thus, we can draw the second important conclusion: high inertia of the capital, slowing down its response to changes in profit rates and consumer demand, also makes the economic system unstable

It is well-known that any solution of the reaction-diffusion system (46) in a neighborhood

1 2 (1 ) (1 ) , *W W ic W ic W W*

oscillations with frequency 2*c* and this solution is stable in some area of parameters 1*c* and

In other area of parameters 1*c* and 2*c* the Kuramoto-Tsuzuki (Ginzburg-Landau) equation

oscillations of the next elements occur with a constant phase lag, that corresponds to movement on space of a phase wave. In a two-dimensional case the equation (53) has also solutions in a kind of leading centers - sequences of running up concentric phase waves, and spiral waves. But equation (53) has also nonperiodic nonhomogeneous solutions in some

From an opinion of most of researchers analysis of such solutions can be successfully fulfilled by using the Galerkin small-mode approximations for reducing the equation (53) to a nonlinear three-dimensional chaotic system of ordinary differential equations. As it was shown in (Magnitskii & Sidorov, 2005b; Magnitskii & Sidorov, 2006), all irregular attractors of reductive three-dimensional system are also singular attractors, and transition to chaos in this system occurs also in accordance with the Feigenbaum-Sharkovskii-Magnitskii (FSM) theory.

*4.2.1. Transition to chaos in Kuramoto-Tsuzuki (Ginzburg-Landau) equation*

(53) has a stable automodel solution *Wr Fr i ar* ( , ) ( )exp( ( ( )))

of the thermodynamic branch can be approximated by some complex-valued

of the Kuramoto-Tsuzuki (or Time Dependent Ginzburg-

,0 , , 1 2 *с* ,*c* - some real constants. It is evident that for

. Hence, each element of the medium (53) makes harmonious

the equation (53) has a space homogeneous solution

*rr* (53)

. If *a r kr* ( ) then

 \*\*\* 1 11 (,,) , , 1 1 1 *xyz d*

and the thermodynamic branch of this problem

**4.2. Spatio-temporal chaos in autooscillating mediums**

2

2*c* . Such mediums refer to as **autooscillating mediums**.

areas of parameters - spatio-temporal or diffusion chaos.

and lead to its destruction.

solution *W r u r iv r* (,) (,) (,)

Landau) equation (Kuramoto & Tsuzuki, 1975):

0 *r x t rR*

0

where 2

arbitrary phase

 ,

2 *W ic* ( ) exp( ( ))

We show that the market economy system can exist in periodic or chaotic regimes only. Periodic regime can have any period in accordance with the theory FSM and any chaotic regime (economic crisis) can be described by some complex cycle or singular attractor.

 The model assumes an unstructured closed economic system that is developing in a finitedimensional Euclidean space *n R* , called the technology space. Each point *n c R* corresponds to a certain production technology of some commodity and its coordinate , 1,..., *i ci n* is the consumption of resource *i* per unit output.

System of market self-developing economy has the form (Magnitskii & Sidorov, 2005; Magnitskii & Sidorov, 2006):

$$\begin{aligned} \frac{\partial \mathbf{x}(t,c)}{\partial t} &= -\text{div}(d\_1(c,\mathbf{x},z)\text{grad}\,z) + b\mathbf{x}((1-\sigma)z-\delta y),\\ \frac{\partial \mathbf{y}(t,c)}{\partial t} &= -\text{div}(d\_2(c,y,z)\text{grad}\,z) + \mathbf{x}(1-(1-\delta)y+\sigma z),\\ \frac{\partial \mathbf{z}(t,c)}{\partial t} &= a(y-d\mathbf{x}).\end{aligned} \tag{51}$$

where *xtc* (,) is a normalized distribution of capital density, *y*(,) *t c* is a normalized distribution of total consumer demand density and *ztc* (,) is a distribution of profit rate at time *t* in the technology space; is government portion of added value (taxis, custom duties, etc.), is employers personal consumption portion of added value and *abd* , , are structural economic parameters. Note that the system of Eqs. (51) is a particular case of systems with multicomponent diffusion, where the activator (the variable providing positive feedback) is the capital and the inhibitor (the variable suppressing capital growth) is the consumer demand.

System of equations describing the variation of macroeconomic variables can be similarly reduced to the form

$$\dot{\mathbf{x}}(t) = b\mathbf{x}((1-\sigma)\mathbf{z} - \delta\mathbf{y}),\\\dot{\mathbf{y}}(t) = \mathbf{x}(1 - (1-\delta)\mathbf{y} + \sigma\mathbf{z}),\\\dot{\mathbf{z}}(t) = \mathbf{a}(\mathbf{y} - d\mathbf{x}).\tag{52}$$

Parameters and are bifurcation parameters in system of Eqs. (52). Increase in values of parameter as well as reduction of values of parameter generate the Feigenbaum cascade of period-doubling bifurcations and then the Sharkovskii subharmonic cascade and chaotic dynamics in system of Eqs. (52) (cycle of period three is presented in Fig.10d). These results gave us possibility to draw the first important conclusion: uncontrolled growth of personal consumption of the employers as well as low government demand for consumer goods (government orders, government support to business, etc.) lead to various crisis phenomena and destroy the economic system.

Consider now the second boundary-value problem for the system of Eqs. (51) on an interval and the thermodynamic branch of this problem

$$\left( \left( \mathbf{x}^\*, y^\*, z^\* \right) \right) = \left( \frac{1 - \sigma}{d \left( 1 - \delta - \sigma \right)}, \quad \frac{1 - \sigma}{1 - \delta - \sigma}, \quad \frac{1 - \delta}{1 - \delta - \sigma} \right)$$

Linearize the considered problem in the neighborhood of the thermodynamic branch, one can obtain that it is stable only when 1 2 *d dd* / (Magnitskii & Sidorov, 2006). Thus, we can draw the second important conclusion: high inertia of the capital, slowing down its response to changes in profit rates and consumer demand, also makes the economic system unstable and lead to its destruction.

## **4.2. Spatio-temporal chaos in autooscillating mediums**

164 Nonlinearity, Bifurcation and Chaos – Theory and Applications

circulation process of capital under government control.

, 1,..., *i ci n* is the consumption of resource *i* per unit output.

(,) ( ).

*ztc a y dx t*

phenomena and destroy the economic system.

1

2

Magnitskii & Sidorov, 2006):

technology space;

reduced to the form

 and

Parameters

parameter

their own interests take part in economic processes that are employers, workers and government. In the model, being based on rigorous rules of Karl Marx's theory of added value, self-development of a market economy involves movement and spontaneous growth of capital of employers, which is the result of creation of added value by workers in the

We show that the market economy system can exist in periodic or chaotic regimes only. Periodic regime can have any period in accordance with the theory FSM and any chaotic regime (economic crisis) can be described by some complex cycle or singular attractor.

 The model assumes an unstructured closed economic system that is developing in a finitedimensional Euclidean space *n R* , called the technology space. Each point *n c R* corresponds to a certain production technology of some commodity and its coordinate

System of market self-developing economy has the form (Magnitskii & Sidorov, 2005;

(,) ( ( , , ) ) ((1 ) ),

*xtc div d c x z grad z bx z y t*

(,) ( ( , , ) ) (1 (1 ) ),

where *xtc* (,) is a normalized distribution of capital density, *y*(,) *t c* is a normalized distribution of total consumer demand density and *ztc* (,) is a distribution of profit rate at time *t* in the

employers personal consumption portion of added value and *abd* , , are structural economic parameters. Note that the system of Eqs. (51) is a particular case of systems with multicomponent diffusion, where the activator (the variable providing positive feedback) is the capital and the inhibitor (the variable suppressing capital growth) is the consumer demand.

System of equations describing the variation of macroeconomic variables can be similarly

cascade of period-doubling bifurcations and then the Sharkovskii subharmonic cascade and chaotic dynamics in system of Eqs. (52) (cycle of period three is presented in Fig.10d). These results gave us possibility to draw the first important conclusion: uncontrolled growth of personal consumption of the employers as well as low government demand for consumer goods (government orders, government support to business, etc.) lead to various crisis

*x t bx z y y t x y z z t a y dx* ( ) ((1 ) ), ( ) (1 (1 ) ), ( ) ( ).

as well as reduction of values of parameter

is government portion of added value (taxis, custom duties, etc.),

are bifurcation parameters in system of Eqs. (52). Increase in values of

>

(51)

is

(52)

generate the Feigenbaum

*ytc div d c y z grad z x y z t*

It is well-known that any solution of the reaction-diffusion system (46) in a neighborhood 0 of the thermodynamic branch can be approximated by some complex-valued solution *W r u r iv r* (,) (,) (,) of the Kuramoto-Tsuzuki (or Time Dependent Ginzburg-Landau) equation (Kuramoto & Tsuzuki, 1975):

$$\mathcal{W}\_{\tau} = \mathcal{W} + (1 + \mathrm{i}\varepsilon\_1)\mathcal{W}\_{rr} - (1 + \mathrm{i}\varepsilon\_2) \left| \mathcal{W} \right|^2 \mathcal{W}\_{\prime} \tag{53}$$

where 2 0 *r x t rR* , ,0 , , 1 2 *с* ,*c* - some real constants. It is evident that for arbitrary phase the equation (53) has a space homogeneous solution 2 *W ic* ( ) exp( ( )) . Hence, each element of the medium (53) makes harmonious oscillations with frequency 2*c* and this solution is stable in some area of parameters 1*c* and 2*c* . Such mediums refer to as **autooscillating mediums**.


**2. Basic wavelet theory**

Wavelet theory is a natural continuation of Fourier transformation and its modified shortterm Fourier transformation. Over the years, wavelets have been being developed independently in different areas, for example, mathematics, quantum physics, electrical engineering and many other areas and the results can be seen in the increasing application in signal and image processing, turbulence modelling, fluid dynamics, earthquake predictions, etc. Over the last few years, WT has received significant attention in electric power sector since it is more suitable for analysis of different types of transient wavelets when compared to other transformations.

#### **2.1 Development of wavelet theory**

From a historical point of view, wavelet theory development has many origins. In 1822, Fourier (Jean-Baptiste Joseph) developed a theory known as Fourier analysis. The essence of this theory is that a complicated event can be comprehended through its simple constituents. More precisely, the idea is that a certain function can be represented as a sum of sine and cosine waves of different frequencies and amplitudes. It has been proved that every 2π periodic integrible function is a sum of Fourier series 0 *k k* cos sin *k a a kx b kx* , for corresponding coefficients *k a* i *k b* . Today, Fourier analysis is a compulsory course at every technical faculty. Although the contemporary meaning of the term 'wavelet' has been in use only since the 80s', the beginnings of the wavelet theory development go back to the year 1909 and Alfred Haar's dissertation in which he analysed the development of integrable functions in another orthonormal function system. Many papers were published during the 30s'; however, none provided a clear and coherent theory (Daubechies, 1996; Polikar, 1999).

First papers on wavelet theory are the result of research by French geophysicist and engineer, Jean Morlet, whose research focused on different layers of earth, and reflection of acoustic waves from the surface. Without much success, Morlet attempted to resolve the problem using localization technique put forward by Gabor in 1946. This forced him to 'make up' a wavelet. In 1984, Morlet and physicist Alex Grossmann proved stable decomposition and function reconstruction using wavelets coefficients. This is considered to be the first paper in wavelet theory (Teofanov, 2001; Jaffard, 2001).

Grosman made a hypothesis that Morlet's wavelets form a frame for Hilbert's space, and in 1986 this hypothesis was proved accurate by Belgian mathematician Ingrid Daubechies. In 1986, mathematician Ives Meyer construed continuously differentiable wavelet whose only disadvantage was that it did not have a compact support. At the same time, Stephane Mallat, who was dealing with signal processing and who introduced auxiliary function which in a certain way generates wavelet function system, defined the term 'multiresolution analysis' (MRA). Finally, the first stage in the wavelet theory development was concluded with Ingrid Daubechies' spectacular results in 1988 (Graps, 1995).

She created orthonormal wavelet bases of the space of square integrable functions which consists of compactly supported functions with prescribed degree of smoothness. Compact support means that the function is identically equal to zero outside a limited interval, and therefore, for example, corresponding inappropriate integrals come down to certain integrals. Daubechies wavelets reserved their place in special functions family. The most important consequence of wavelet theory development until 1990 was the establishment of a common mathematical language between different disciplines of applied and theoretical mathematics.


**4. Discussions**

Based on the description of PSTP, this study estimates the PSTP effects on student performance in the three subjects: Chinese, mathematics, and chemistry. First, the results of the empirical study show that PSTP in Chinese could be classified into content knowledge preparation and pedagogical content knowledge preparation. The results can verify Hypothesis I. According to the connotation covered by the common factors, content knowledge preparation includes teachers' knowledge and understanding of the subjects they teach, teaching competencies, general pedagogy, and teaching methods. The pedagogical content knowledge preparation involves teachers' preparation to differentiate instruction for various types of students, interdisciplinary skill teaching, and classroom management skills. The PSTP classification is consistent with Shulman's (1986) content knowledge in teaching [19].

Second, there are differences in PSTP between subjects. The empirical findings can verify Hypothesis II. Based on the results of the descriptive statistical analysis, the content knowledge and pedagogical content knowledge of Chinese teachers are lower than the overall level, while those of the mathematics teachers are higher than the overall average. The chemistry teachers' content knowledge and pedagogical content knowledge are lower than the overall level but higher than those of the Chinese teachers. It may be due to differences in subject knowledge. There also exist differences in the teachers' competencies by subject. The findings of this study are consistent with those of existing studies [26,27,29,33].

Finally, the effect of PSTP on student performance varies across subjects. The results of the empirical study show partial validation for Hypothesis III. In the Chinese subject, PSTP directly affects student performance in which content knowledge significantly negatively influences student performance, and pedagogical content knowledge significantly positively impacts student performance. In mathematics, PSTP does not have a significant effect on student performance. In chemistry, pedagogical content knowledge in PSTP has a significantly negative effect on student performance. According to existing literature, teacher preparation serves as a significant predictor of student performance. The negative relationship between students' performance and teachers' content knowledge may be contrary to the findings of some existing studies. For example, Monk (1994) suggested that teachers' knowledge positively affects student performance [20]. Meanwhile, the significantly positive effect of pedagogical content knowledge on student performance agrees with the findings of relevant research, which confirms the correlation between teacher expertise as well as high-quality teaching and student learning [25]. Given that there may be more teacher discretion in teaching Chinese than in teaching math or chemistry, pedagogical variations in the teaching of Chinese may be more influential on students compared with other subjects. In this way, the findings suggest that Chinese teachers should be more equipped with strong pedagogy than content expertise. Furthermore, it should be noted that the requirements of different subjects for high school students are nationalized, though with minor variations across the provinces, which may be comparable to the US curriculum variation (Daun-Barnett and St. John, 2012; St. John, 2006; St. John and Musoba, 2010) [23–25]. Therefore, the results based on the survey analysis of the Haidian District, Beijing, can be generalized to the nationwide population to a certain extent.


Concluding, we hope that synthetic inorganic chemists active in the transition-metal SIM and SMM areas or scientists who just enter into this field will find this review useful. We shall be happy if the readers enjoy the review as much we enjoyed writing it.

**Author Contributions:** P.S.P., D.M. and E.P. studied the literature and proposed some of the cited examples. P.S.P. and E.K. proposed some ligand systems. D.M. prepared the figures and typed the manuscript. S.P.P. developed the concept of the review and wrote the manuscript jointly with E.K. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the research program THALES, grand number 377365, D. 533.

**Acknowledgments:** This work has been supported by the European Union (European Social Fund-ESF) and Greek National funds through the Operational Program "Educational and Lifelong Learning" of the National Strategic Reference Framework (NSRF)—Research Funding Programs: THALES: "Investigating in knowledge society through the European Social Fund (to S.P.P. and E.K.).

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

#### **References**

© 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/).


**Acknowledgement**

This study was supported by the Subprogram of the Presidium of the Russian Academy of Sciences "Gene Pools and Gene Diversity," State Contract no. 14.740.11.0164 in the framework of the Federal Target Program "Science and Education Professionals of Innovative Russia," and the Russian Foundation for Basic Research (grant no. 12-04-92214 Mong\_a).

#### **5. References**

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**Chapter 4**

© 2013 Méndez et al., licensee InTech. This is an open access chapter 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.

© 2013 The Author(s). Licensee InTech. 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,

**Prolactin in the Immune System**

Lorenza Díaz, Mauricio Díaz-Muñoz, Leticia González, Saúl Lira-Albarrán, Fernando Larrea and Isabel Méndez

Prolactin (PRL) is a protein hormone, as well as a cytokine, which is synthesized and secreted from specialized cells of the anterior pituitary gland, named lactotrophs. More than 300 functions exerted by PRL in vertebrates have been recognized; and they reflect the ubiquitous distribution of its receptors, as well as the fact that PRL is synthesized in many extrapituitary tissues. Among these sites of PRL synthesis are cells of the immune system, such as macrophages, natural killer cells, and T- and B-lymphocytes. Regulation of PRL synthesis is organ specific, which confers additional complexity to the spectrum of PRL actions. In the physiology of the immune system, PRL acts by stimulating the secretion of other cytokines and the expression of cytokine receptors, and also as a growth and survival factor. In pathological conditions, increased levels of PRL could cause deterioration of the subject's condition. In this review, we integrate the information on regulation of PRL synthesis with that concerning its physiological and pathological actions in extrapituitary

**2. Regulation of prolactin expression and secretion in the pituitary and at**

PRL was originally identified as a neuroendocrine hormone of pituitary origin; however, its synthesis is not limited to the hypophysis since numerous extrapituitary tissues also express this protein, including the placenta, ovary, testis, mammary gland, skin, adipose tissue, endothelial cells, and immune cells [1]. This wide-spread PRL expression might explain its involvement in very different processes such as reproduction, metabolism, immunology,

PRL expression and secretion are regulated by different stimuli provided by the environment and the internal milieu. Although pituitary PRL secretion is under a tonic and

and reproduction in any medium, provided the original work is properly cited.

Additional information is available at the end of the chapter

tissues, highlighting those in the immune system.

http://dx.doi.org/10.5772/53538

**1. Introduction**

**extrapituitary sites**

and behavior.


**3. Discussion**

Seaweed cell-wall is made of different components namely cellulose, xylan, mannan, among others [19], although important constituents are alginates and fucans for brown algae, ulvans and other sulphated glycans for green algae, and agar and carrageenan for red algae [20]. The latter complex group of components are also sulphated polysaccharides which are recognised by their pharmacological and industrial uses [21]. In Rhodophyta, agar and carrageenan account for 40–50% of the dry weight, but can be as much as 70–80% [20]. Focusing on carrageenans, the backbone structure comprises linear chains of repeating D-galactose sugars and 3,6-anhydro-galactose units, with a different number and location of the sulphate groups attached. Sulphation degree and molecular conformation allow classifying carrageenans in three main types with commercial importance, namely κ-, ι- and λ-carrageenan, all containing 15–40% ester sulphate; although seaweeds can also contain hybrids carrageenans [22]. Sulphation takes place in the cell wall by the action of carbohydrate sulfotransferase whilst desulphation by galactose-6 sulfurylase also occurs in the cell wall, although its role is not fully clarified. Galactose-6 sulfurylase catalyses the conversion of μ-carrageenan into κ-carrageenan, but λ-carrageenan seems to not be susceptible to its action [16,23,24]. The number of sulphate groups is, in turn, one of the features that affects the properties of carrageenan types as carrageenans are gel-forming and viscosifying polysaccharides [25]. In addition, variations in carrageenan composition, i.e., sulphation degree, have been associated to life cycles stages of algae, alga species and environment conditions.

With the goal of revealing changes in sulphation degree of galactan of carrageenan during carposporogenesis in *G. imbricata*, expression levels of two genes involved in the biosynthesis of carrageenan has been reported. One of main achievements of this work lies on the fact that changes in transcript levels of these genes, i.e., *carbohydrate sulfotransferase* and *galactose-6-sulfurylase*, are associated at different stages of thalli development and the well-recognised stages of cystocarp maturation. Thus, expressions of *sulfotransferase* were reported in all stages of thalli development (Figure 4A). Results indicated that (1) the *ST1* and *ST2* could encode proteins responsible for similar mechanisms

and metabolic pathways during thalli development, and (2) *sulfotransferase* could be involved in housekeeping activity as sulphated galactan is component of cell wall of red seaweeds. Hence, transcript expression suggests that the addition of sulphate groups occurs during all stages of thalli development.

It is also worth drawing attention to the behaviour of both *sulfurylase* sequences (Figure 4B). The expression behaviour of *sulfurylase* (*SY1* and *SY2*) indicated that they may play several roles and that they are time-regulated. It was also evident that *SY1* was induced to a larger extent when the thalli were fertilised (Figure 4B). Noticeably, overexpression was higher in *sulfurylase SY1* than *sulfurylase SY2* for fertilised thalli, suggesting a concrete development-specific expression role for the *sulfurylase SY1* gene during thalli maturation. Apart from that, *sulfurylase SY2* expressions may also depend on the stage of the thalli, as differential transcript expression was also reported, albeit with different expression levels that were significantly lower than those for *sulfurylase SY1* (Figure 4B). The exhibition of these expression patterns for *SY1* and *SY2* in the red seaweed *G. imbricata* opens up an interesting pathway for determining whether the differential expressions of *SY1* and *SY2* could be a consequence of specific transcription factors of each gene copy. Interestingly, it could infer the presence of specific transcription factors, which would only function efficiently at specific stages of thalli maturation. Hence, the different stages of seaweed thalli development could contribute to the expression of different regulatory proteins. In higher plants, different proteins can participate as elements of regulatory mechanisms and co-ordinate cell activity [26]. Furthermore, if the transcription factors were activated and regulatory proteins were synthesised, this would reinforce the theory of a time-gene regulation of two sulfurylase as thalli development proceeds. All in all, genes that encode proteins responsible for the desulphation of the galactan skeleton of the cell wall will allow *G. imbricata* thalli to soften and enable the development of reproductive structures (cystocarps) in thalli.

Cystocarp disclosure is elicited by complex multiple factors, encompassing the period from when cystocarps first become visible (well-developed cystocarps), through to the adequate development of cystocarps (fully-developed cystocarps). Thus, cystocarps could achieve optimal maturity when elicitation factors and the mechanisms that weaken and soften the cell wall act in co-ordination [8]. In line with this, the behaviour of the genes that encode the adding and elimination of the sulphate group during maturation of reproductive structures must be appraised, along with the genes that encode oxidative-stress-related proteins, which also potentially contribute to softening the thallus.

Little has been reported to date about genes that control sulphate addition. This is one of the few studies aimed at characterising *sulfotransferase* expression levels at different stages of maturity in red seaweed cystocarps. Although monitoring the expressions of two types of *sulfotransferase* (*ST1* and *ST2*) showed similar behaviour and transcript expression levels, significant transcript expression was shown in fully-developed cystocarps of *G. imbricata* (Figure 5A,B). Our results seem to suggest that genes encoding proteins that add the sulphate group are working to reconstitute the cell wall after disclosure and maturity of cystocarps and even early release of spores, as this is an unsynchronised process. Thus, it would not be misconceived to think that once fertilisation has occurred in *G. imbricata*, the re-arrangement of carrageenan constituents proceeds to improve and recover the organisation of the cell wall.

Remarkably, what occurs with *sulfurylase* differs from the expected. Following the line of argument, the thalli would soften prior to the appearance of cystocarps. Hence, one would expect transcript overexpression of *sulfurylase* to be reported when cystocarps are first developing (well-developed cystocarps) and always prior to their complete maturity (fully-developed cystocarps). However, *SY2* showed transcript expression is significantly higher in the presence of fully-developed cystocarps than in thalli with well-developed cystocarps (Figure 6B). Thus, different functionality of *SY1* and *SY2* can be assumed. To gain greater insight into what could be occurring, it is worth considering that fertilisation in *G. imbricata* takes place when a spermatium fertilises a carpogonium on the female gametophyte. The fertilised carpogonium develops into a structure called a cystocarp that will contain spores [27]. This cystocarp develops in the auxiliary ampulla after the auxiliary cell receives the diploid

nuclei from the fertilised carpogonial cell [28]. Thus, carrying the argument of *SY* di fferent functionality a step further, *SY1* may be responsible for weakening the cell wall to embrace the development of auxiliary ampulla cells, and *SY2* allows the cystocarps to grow in size and develop their spores within. These di fferentiated functions should show a co-ordination of the di fferent kinds of *sulfurylase* over time and cell type during the cystocarp maturation. In short, this time–transcript expression could orchestrate specific adaptation and protective responses during cystocarps development. This would mean that *sulfurylase* genes are closely related to reproductive development and that maturity stages of cystocarps require genes expressed in di fferent ways from early stages.

Beyond the sulphation and de-sulphation of galactan backbone as a consequence of thalli development and cystocarp maturation, the gene encoding *WD40* has also been reported to potentially play a role in cystocarp maturing, as the gene transcripts were significantly overexpressed in fully-developed cystocarps, compared with expression in developing cystocarps (Figure 7). To some extent, these results are to be expected as earlier studies on gene expression during carposporogenesis of *G. imbricata* showed *WD40* and *cytochrome P450* transcript expressions are limited to di fferent signals related to both cystocarp disclosure and development of the red seaweed *G. imbricata* [9,10]. Specifically, *WD40* plays an active role in the processes of regulation and response to damage [29], so *WD40* gene expression in *G. imbricata* could suggest cross talk between cystocarp maturation and a reduction of oxidative damage.

In summary, gene expressions involved in the sulphation and desulphation of galactan backbone are associated with alterations in thalli development and cystocarp maturation in the red seaweed *G. imbricata*. This opens an interesting framework to gain insight into gene mechanisms involved in carrageenan synthesis.


2.6.1. Urinary Tract Infection

Estimates of the treatment effectiveness on the occurrence of UTIs were informed by 10 studies [7–9,11–16,23,24]. The RE model revealed that OnabotulinumtoxinA was associated with a higher incidence of UTIs compared with the placebo, SNM, and PTNS (Table 3). The ranking results for the post-management risk of UTIs was as follows: PTNS ranked best, SNM ranked second, placebo ranked third, and OnabotulinumtoxinA ranked worst (Figure 3C).

#### 2.6.2. Urine Retention Needing Clean Intermittent Catheterization

Estimates on the effect of treatments on post-management urine retention were reported in 11 studies [7–16,23,24]. The RE model demonstrated that OnabotulinumtoxinA was associated with a higher occurrence of post-treatment urine retention needing catherization compared with the placebo, SNM, and PTNS (Table 3). The ranking results for post-management risk of post-treatment urine retention was as follows: SNM ranked best, placebo ranked second, PTNS ranked third, and OnabotulinumtoxinA ranked worst (Figure 3D).


**Appendix A**

**Table A1.** Detailed development of the *ACR* with *p*-values of the two-sided *t*-test from January 1998–December 2015. *ACR* denotes the average cumulative returns.

**Table A2.** Annualized risk-return measures for BHS, FTS, GVS, RVS, and JDS for sub-periods of 3 years from January 1998–December 2015.


**NANOMATERIALS**

**INTECHOPEN.COM**

Edited by **Mohammed Muzibur Rahman**

http://dx.doi.org/10.5772/1371 Edited by Mohammed Muzibur Rahman

#### **Contributors**

Ana Arenillas, J. Angel Menéndez Díaz, Esther G.Calvo, Enrico Marsili, Sujoy K Das, Tifeng Jiao, Jingxin Zhou, Sufeng Wang, Kevin Deplanche, Lynne Macaskie, Angela Murray, Scott Taylor, Claire Mennan, Krzysztof Lukaszkowicz, Joaquim Esteves da Silva, Alexander Rud, Natalja Kuskova, Lyubov Ivaschuk, Leonid Boguslavskii, Anatolii Perekos, Morteza Sasani Ghamsari, Hamed Mehranpour, Masoud Askari, Jeong Hyun Yeum, Lavinia Balan, Raphael Schneider, Mohammed Muzibur Rahman, Aslam Jamal, Sher Khan, M Faisal, Nicoleta S. Petrea, Rodica Mihaela Lungu, Ciprian Sau, Petrisor Zamora Iordache, Razvan Petre, Ioan Safta, Andrada Pretorian

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Veikko Uahengo Department of Physics, Chemistry and Material Science, University of Namibia, Windhoek, Namibia

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*The ESIPT-Steered Molecular Chameleon for Cations and Anions Based on Alizarin… DOI: http://dx.doi.org/10.5772/intechopen.103829*


**14. Patterns of recurrence**

As we gain more experience using anti-angiogenic agents in high grade gliomas, we also learn more about what occurs after treatment failure. Mancuso et al. conducted a pre-clinical study using a mouse xengraft model to address the reversibility of VEGF inhibition after cessation of anti-VEGF therapy. It was noted that even after a 50–60% reduction of tumour vascularity, ''empty sleeves of basement membrane were left behind.'' By day 7 after drug cessation, tumours were fully re-vascularized, suggesting that these remaining empty sleeves of basement membrane and pericytes are responsible for this tumor revascularization. These basement membranes also serve as storage sites for angiogenic growth factors as well as ''tracks'' for tumor vascular regrowth. This "rebound" phenomenon has also been observed in clinical studies (figure 9) [46]. This phenomenon appears to be associated with rapid clinical demise and dismal prognosis.

**Figure 9.** Rebound progression after discontinuation of bevacizumab: Original tumor area seen on post-Gd T1 weighted (a) and FLAIR MRI (e) sequences prior to initiating therapy with bevacizumab in a patient with recurrent high-grade glioma. Post-Gd T1 weighted (b) and FLAIR MRI (f) sequences that demonstrate partial response after 1 six-week cycle of treatment with bevacizumab. Post-Gd T1 weighted (c) and FLAIR MRI (g) sequences at the time of bevacizumab failure and subsequent cessation of bevacizumab therapy. Post-Gd T1 weighted (d) and FLAIR MRI (h) sequences at the time of "rebound" progression demonstrating a dramatic increase in area of enhancement and ab‐ normal FLAIR signal 6 weeks after cessation of therapy with bevacizumab. [44]

## **15. MicroRNA – Potential target**

**13. Bevacizumab as first line therapy**

22 Tumors of the Central Nervous System – Primary and Secondary

maker for overall survival.

bevacizumab group.

**14. Patterns of recurrence**

Two large phase III double-blinded randomized studies published in NEJM in February, 2014 evaluated the use of bevacizumab in the first line setting in patients with glioblastoma. Gilbert et al, led a study that randomized 637 patients with newly diagnosed glioblastoma to standard six weeks of chemo-radiotherapy (adjuvant temozolomide and concurrent radiotherapy) followed by up to twelve months or until disease progression of maintenance temozolomide, with or without bevacizumab starting at week four of chemo-radiotherapy [46]. The results were disappointing in that no survival benefit was determined between the two groups. The bevacizumab group reported a median overall survival (OS) of 15.7 months and the placebo group had an OS of 16.1 months. Progression-free survival favored the bevacizumab group at 10.7 months vs. 7.3 months in the placebo group. Interestingly, over time the patients who received bevacizumab did not benefit from a quality of life standpoint despite better response rates. These points further reinforce the question as to whether PFS is an appropriate surrogate

A second published in the same issue of NEJM performed by Chinot et al, studied the use of bevacizumab in the front line setting as well [49]. Similar conclusions were reported in this study compared to the performed by Gilbert et al. The treatment regimen used in the study differed in that after 6 months of maintenance temozolomide with or without bevacizumab were continued with bevacizumab alone or placebo until disease progres‐ sion or until suffering from intolerable side effects. The results were again disappointing in that the addition of bevacizumab to standard chemo-radiation and maintenance therapy with this anti-angiogenic agent did not provide a survival benefit (72% and 33.9% one and two year survival rate respectively in the bevacizumab group versus 66.3% and 30.1%) despite a significantly better PFS (10.6 months in bevacizumab group vs. 6.2 months in placebo group). Baseline quality of life was maintained for a longer period of time in the

These results, in particular the study by Gilbert et al, appears to possibly support the use of maintenance temozolomide for twelve months instead of traditional standard therapy with six months as conducted in the landmark study by Stupp et al now considered standard of care. This is a question that every neuro-oncologist has to address when treating patients with newly diagnosed glioblastoma. Although difficult to extrapolate data from two separate studies, no large scale study has been performed making a direct comparison of twelve months versus six months of maintenance temozolomide. However, this data suggests that twelve months of maintenance temozolomide leads to an improvement in OS reporting 16.1 months

As we gain more experience using anti-angiogenic agents in high grade gliomas, we also learn more about what occurs after treatment failure. Mancuso et al. conducted a pre-clinical study

versus14.6 months reported in the EORTC trial led by Stupp et al.

MicroRNAs (miRNAs) are molecules of RNA numbering 20-23 nucleotides that function to interfere with messenger RNA (mRNA) translation into protein, the final step in gene expression. Through a complex and elegantly-characterized molecular sequence of steps, miRNAs function to "flag" mRNAs for decay, translational inhibition, or cleavage prior to the process of translation. This, in turn, results in a decreased level of encoded proteins, which in turn affects a myriad of essential cell functions, i.e. growth, proliferation, metabolism, apoptosis, etc. [43] Interestingly, though miRNA constitutes roughly 1-3% of

the human genome, it is postulated that these molecules have influence on as much as ~30% of all gene expression [44]. The expression of one mRNA may be affected by numerous miRNAs; on the same token, one miRNA may affect the expression of multiple mRNAs [44]. The deregulation of miRNA has been pivotally implicated in tumorigenesis; a positive association has been found between those sites in the human genome associated with cancer and areas of miRNA expression [44].  Of recent, the same has also been found in GBM wherein a multitude of miRNAs have been reported to have roles in tumor suppression or oncogenesis. Therapeutic strategies with respect to miRNA aim to augment tumor suppression or antagonize oncogenesis, respectively. In the former case, it is postulated that viral vectors may be utilized to deliver gene therapy to increase the *in situ* expression of tumor suppressive miRNAs. In the latter case, studies pursuing anti-miRNA therapies, e.g. the use of anti-miRNA oligonucleoti‐ des, are underway for downregulation of oncogenic miRNAs [44].