3. Definition and classification

AFL is defined as abnormal atrial activity inside a reentrant circuit with a diameter more than 2 cm2 at a high rate of 240–320 bpm which makes a continuous oscillation without an isoelectric baseline [2]. In contrast, focal atrial tachycardia (AT) is a rapid abnormal atrial rhythm originating from a "point source" with a baseline between P waves on ECG. The most practical classification is based on isthmus versus non-isthmus dependency (Diagram 1). According to the new classification, typical AFL is a macroreentrant atrial tachycardia that usually proceeds up the atrial septum (counterclockwise or CCW), down the lateral atrial wall, and through the CTI between the tricuspid valve annulus and inferior vena cava (IVC). It is also known as "common AFL" or "CTI-dependent AFL." When the circuit rotates in the opposite direction, it is referred to as clockwise (CW) typical AFL or reverse typical AFL (Figure 1). Clockwise AFL is observed in only 10% of clinical cases. However, the flutter wave morphology might change in the presence of underlying atrial disease, prior surgery, or previous ablation which makes the flutter wave morphology not a reliable indicator of AFL type [2, 3].

group, different circuits have been described, including "perimitral flutter" reentry, LA roof dependent flutter and reentry around scars from previous surgery or ablation in atria. Obviously, these flutters are not amenable to ablation of the CTI, but common AFL often coexists

Figure 1. Counterclockwise typical flutter (a), clockwise typical flutter (b), atypical flutter (c), atrial fibrillation (d), atrial flutter 1:1 in a patient on flecainide (e). In tracing d, the atrial waves amplitude in V1 is changing with irregular irregular

Atrial Flutter: Diagnosis and Management Strategies http://dx.doi.org/10.5772/intechopen.74850 25

The CTI is bounded anteriorly by the tricuspid annulus and posteriorly by the ostium of the IVC and the eustachian ridge. The width and muscle thickness of CTI are variable, from several millimeters to around 3 cm in width and depth of 1 cm roughly. The CTI is wider in the lateral portion and thinner in the central portion. The central isthmus is concave and pouch-like in 47 and 45% of patients, respectively. The subeustachian isthmus is the area between the tricuspid annulus and the eustachian ridge which ends in IVC junction. The pectinates, spare the myocardium just in atrial part of the tricuspid valve and makes the smooth portion of the CTI which is referred to as the vestibular portion. Of note, the septal part of the CTI is adjacent to the posterior extensions of the AV node as well as the middle cardiac vein [5, 6]. This anatomic proximity explains the higher risk of AV block if ablation is done in the septal aspect. Also, the smooth vestibular portion around the tricuspid valve lies

The patients with flutter sometimes are asymptomatic or may present with a variety of symptoms including palpitations, dyspnea, fatigue, dizziness or reduced functional class. However, it might be the first presentation of more serious conditions like acute pulmonary embolism, acute coronary syndrome or acute pulmonary edema. The severity of symptoms

with these atypical reentry circuits [4].

very close to the right coronary artery.

4. Clinical manifestation

3.1. Anatomy of the CTI

RR interval.

Atypical flutter, or "non-CTI-dependent macroreentrant atrial tachycardia," is attributed to those flutters that do not use the CTI originating in the right (RA) or left atrium (LA) [3]. In this

Diagram 1. Classification of atrial flutter (see the text for discussion).

Figure 1. Counterclockwise typical flutter (a), clockwise typical flutter (b), atypical flutter (c), atrial fibrillation (d), atrial flutter 1:1 in a patient on flecainide (e). In tracing d, the atrial waves amplitude in V1 is changing with irregular irregular RR interval.

group, different circuits have been described, including "perimitral flutter" reentry, LA roof dependent flutter and reentry around scars from previous surgery or ablation in atria. Obviously, these flutters are not amenable to ablation of the CTI, but common AFL often coexists with these atypical reentry circuits [4].

#### 3.1. Anatomy of the CTI

2. Epidemiology

24 Cardiac Arrhythmias

Overall, the incidence of AFL in the United States is 88 per 100,000 person-years. 15% of supraventricular arrhythmias are AFL and usually coexists with AF. More than 80% of patients who undergo RFA of typical AFL will have AF within the following 5 years. The incidence of AFL in men is more than twice that of women. Paroxysmal AFL can be seen in patients with no structural heart disease (SHD), whereas chronic AFL is frequently associated with underlying SHD, such as valvular disease or heart failure. Acute AFL may happen secondary to acute disease process, such as pericarditis, pulmonary embolism, exacerbation of lung disease,

AFL is defined as abnormal atrial activity inside a reentrant circuit with a diameter more than 2 cm2 at a high rate of 240–320 bpm which makes a continuous oscillation without an isoelectric baseline [2]. In contrast, focal atrial tachycardia (AT) is a rapid abnormal atrial rhythm originating from a "point source" with a baseline between P waves on ECG. The most practical classification is based on isthmus versus non-isthmus dependency (Diagram 1). According to the new classification, typical AFL is a macroreentrant atrial tachycardia that usually proceeds up the atrial septum (counterclockwise or CCW), down the lateral atrial wall, and through the CTI between the tricuspid valve annulus and inferior vena cava (IVC). It is also known as "common AFL" or "CTI-dependent AFL." When the circuit rotates in the opposite direction, it is referred to as clockwise (CW) typical AFL or reverse typical AFL (Figure 1). Clockwise AFL is observed in only 10% of clinical cases. However, the flutter wave morphology might change in the presence of underlying atrial disease, prior surgery, or previous ablation which makes

Atypical flutter, or "non-CTI-dependent macroreentrant atrial tachycardia," is attributed to those flutters that do not use the CTI originating in the right (RA) or left atrium (LA) [3]. In this

following heart or lung surgery, or myocardial infarction. [1]

the flutter wave morphology not a reliable indicator of AFL type [2, 3].

Diagram 1. Classification of atrial flutter (see the text for discussion).

3. Definition and classification

The CTI is bounded anteriorly by the tricuspid annulus and posteriorly by the ostium of the IVC and the eustachian ridge. The width and muscle thickness of CTI are variable, from several millimeters to around 3 cm in width and depth of 1 cm roughly. The CTI is wider in the lateral portion and thinner in the central portion. The central isthmus is concave and pouch-like in 47 and 45% of patients, respectively. The subeustachian isthmus is the area between the tricuspid annulus and the eustachian ridge which ends in IVC junction. The pectinates, spare the myocardium just in atrial part of the tricuspid valve and makes the smooth portion of the CTI which is referred to as the vestibular portion. Of note, the septal part of the CTI is adjacent to the posterior extensions of the AV node as well as the middle cardiac vein [5, 6]. This anatomic proximity explains the higher risk of AV block if ablation is done in the septal aspect. Also, the smooth vestibular portion around the tricuspid valve lies very close to the right coronary artery.

#### 4. Clinical manifestation

The patients with flutter sometimes are asymptomatic or may present with a variety of symptoms including palpitations, dyspnea, fatigue, dizziness or reduced functional class. However, it might be the first presentation of more serious conditions like acute pulmonary embolism, acute coronary syndrome or acute pulmonary edema. The severity of symptoms closely depends on the baseline left ventricular ejection fraction (LVEF), ventricular rate during the flutter and underlying SHD. As a common scenario, the patients present with a stroke or with decompensated heart failure secondary to tachycardia-induced cardiomyopathy. AFL occurs in nearly 25% of patients with AF.

6. Typical flutter

6.1. Electrocardiographic characteristics

Figure 2. The typical CCW flutter ECG characteristic (see the text).

sequence in focal AT with silent periods causing flat isoelectric line.

In "typical" counterclockwise AFL, the wave of depolarization propagates through the lateral right atrium, then travels through the CTI in a lateral-to-medial direction. The wave of depolarization arrives at the inferior part of the interatrial septum, splits and propagates caudocephalically up the septum, finally traveling across the roof to arrive lateral RA to complete the circuit. At the same time, the depolarization wave propagates from inferior septum to the lateral wall of the left atrium. Flutter waves have constant morphology and polarity with same CL. In typical AFL, they are most visible in lead V1 and the inferior leads (II, III, aVF) with a sawtooth appearance. The propagation of depolarization wave is through interatrial septum which makes it positive or negative in inferior leads in clockwise (high to low) or counterclockwise (low to high) AFL, respectively. The wave includes a slow downsloping portion, with a sharp negative deflection, followed by a rapid positive deflection, merging to the next downsloping deflection (Figure 2). Because of constant activation inside the circuit, there is no electrically silent period and consequently no isoelectric period. This is as opposed to focal AT with silent periods between focal discharges (Figure 3). However, focal

Atrial Flutter: Diagnosis and Management Strategies http://dx.doi.org/10.5772/intechopen.74850 27

Figure 3. The top diagram demonstrates the atrial activation sequence correlated with typical CCW atrial flutter. The slow conduction through CTI causes the flatter portion of flutter wave. The bottom diagram shows atrial activation


*Article* **Antimicrobial Activity of Chamomile Essential Oil: E**ff**ect of Di**ff**erent Formulations**

**Sourav Das 1,4,**†**, Barbara Horváth 2,**†**, Silvija Šafranko 3, Stela Joki´c 3, Aleksandar Széchenyi 2 and Tamás K˝oszegi 1,4,\***

#### Academic Editor: Igor Jerkovi´c

Received: 31 October 2019; Accepted: 21 November 2019; Published: 26 November 2019

**Abstract:** Essential oils (EOs) are highly lipophilic, which makes the measurement of their biological action difficult in an aqueous environment. We formulated a Pickering nanoemulsion of chamomile EO (CPe). Surface-modified Stöber silica nanoparticles (20 nm) were prepared and used as a stabilizing agent of CPe. The antimicrobial activity of CPe was compared with that of emulsion stabilized with Tween 80 (CT80) and ethanolic solution (CEt). The antimicrobial effects were assessed by their minimum inhibitory concentration (MIC90) and minimum effective (MEC10) concentrations. Besides growth inhibition (CFU/mL), the metabolic activity and viability of Gram-positive and Gram-negative bacteria as well as *Candida* species, in addition to the generation of oxygen free radical species (ROS), were studied. We followed the killing activity of CPe and analyzed the efficiency of the EO delivery for examined formulations by using unilamellar liposomes as a cellular model. CPe showed significantly higher antibacterial and antifungal activities than CT80 and CEt. Chamomile EOs generated superoxide anion and peroxide related oxidative stress which might be the major mode of action of Ch essential oil. We could also demonstrate that CPe was the most effective in donation of the active EO components when compared with CT80 and CEt. Our data suggest that CPe formulation is useful in the fight against microbial infections.

**Keywords:** chamomile essential oil; Pickering emulsion; antimicrobial activity; free radical generation


**4. The current difficulties of using multisensor VR**

Even though VR provides many unique advantages over traditional or new rehabilitation approaches, there are limitations to its widespread practical use as a routine rehabilitation method.

First, there is currently no sufficient evidence base for clinical studies that would demonstrate the unambiguous effectiveness of using VR in sensorimotor rehabilitation in various clinical groups in comparison with various traditional methods of motor rehabilitation. In addition, there is still quite a bit of information regarding the possibility of replacing physical exercises only with classes in virtual reality, namely, how interchangeable, and acceptable it is for short-term and long-term results of motor rehabilitation. That is why it is still impossible to say unambiguously how high the advantages of sensorimotor rehabilitation in VR are relative to those in the real physical world. Thus, all these questions justify the need to continue research in the field of studying the possibility of expanding the use of VR, as well as studying the short-term and long-term effectiveness of using VR in sensorimotor or cognitive rehabilitation, by accumulating a clinical base and obtaining the possibility of conducting a meta-analysis of research data to achieve the maximum high level of evidence. And although nowadays there are several studies in which attempts have been made to solve these problems, rehabilitation using VR technology continues to be considered only as an adjuvant method of sensorimotor and cognitive rehabilitation [5, 52].

The second important reason for the difficulty in the routine use of rehabilitation in VR is the relative high cost of equipment for using these systems as a method of rehabilitation within the framework of the telemedicine concept. A few years ago, the equipment needed to simulate VR, making it difficult to use for more than 40 minutes due to the heavy weight of the VR helmet, has become much more convenient today, because there has been an abrupt growth in the number of manufacturers of these technical devices offering more and more comfortable products for use.

**139**

*Proprioception in Immersive Virtual Reality DOI: http://dx.doi.org/10.5772/intechopen.96316*

According to data obtained on biological models that allow studying the processes of neuroplasticity, the lack of stimulation of the motor cortex during the "critical period", which usually corresponds to an acute state after damage of any genesis, leads to the loss of corticospinal synaptic connections [53], while stimulation motor cortical networks in the same "critical period" may contribute to the partial restoration of some of these lost connections [54]. Long-term lack of stimulation of the motor cortex in the acute period after injury ultimately leads to the consolidation of existing changes that will prevent further restoration of function. The key component of the theory of neuroplasticity activation is the dynamic nature of changes in neural connections during motor rehabilitation using VR technology, which can be adapted to the individual needs of the person being rehabilitated, providing a personalized approach to sensorimotor and cognitive

Some studies demonstrate rich intrahemispheric cortical–cortical connections that link the occipital, parietal and frontal cortex [32, 33, 55]. Moreover, individual studies demonstrate that a significant number of motor neurons in the premotor and motor cortical areas are modulated by visual information [35, 37–39], suggesting that visual information can be a powerful signal for functional reorganization

The main parameters through which the processes of neuroplasticity can be activated, and which can be influenced when the immersive environment is formed, are visualized movement, biofeedback, motivation and learning through observation. Rehabilitation measures in VR can also contribute to the process of functional

The possibility of obtaining a significant rehabilitation result is achievable only with a long training process, because the formation of new skills, which is due to the activation of the processes of synaptogenesis or Hebb learning, as well as other mechanisms of neuroplasticity, does not give an immediate stable result, since stabilization requires subsequent reinforcement in order to stimulate the transition of interneuronal interaction from functional to morphologically fixed changes [56, 57]. Thus, in an immersive environment, it is quite easy to set the proper volume of tasks to be performed and combine them with secondary cognitive tasks, making the performance of a motor task interesting due to diversity, increasing the motiva-

Studies on biological models have demonstrated that the intensity and duration of physical exercise is one of the determining factors that have a significant impact on neuroplastic changes during rehabilitation [59]. For example, changes at the synaptic level in a biological experiment occurred after the animal was exposed to thousands of repetitions of a given task over a short period of time, i.e. 12,000

Also, it was noted that patients with CNS disease receiving rehabilitation on this occasion require more and more intensity of physical exercises in order to achieve positive results in restoring physical function, in comparison with the process of developing new motor skills in healthy people [62]. The duration of rehabilitation sessions to achieve positive effects in the restoration of function, for example, the upper limb, after a stroke also depends on the stage of stroke: from 1–2 hours in the acute stage [63] and up to 10–20 repetitions per training in the chronic stage of stroke [64]. At the same time, it is implied that during the entire time of the training, it is required to maintain a high level of motivation to achieve a positive result

reorganization in the CNS due to the activation of neuroplasticity processes.

tion of the person being rehabilitated for a long rehabilitation process [58].

and maintain it throughout the entire course of rehabilitation.

**5. Neuropasticity and VR**

rehabilitation.

of sensorimotor connections.

repetitions over 2–3 days [60, 61].


**1. Introduction**

Field programmable gate array (FPGA) is prefabricated integrated circuit (IC), which contains programmable gate matrix to implement logic functions and interconnect resources to connect the logic functions and I/O blocks. These interconnect resources can be electrically programmed by the user to implement any digital circuits and systems. Due to faster time to market, lower cost, and flexibility, FPGA prefers over ASIC (application‐specific IC) design although it has disadvantages like larger size, slower speed, and larger power consumption. Due to the flex‐ ibility of FPGA, it is possible to partially program any portion of the FPGA depending on the requirement even when the rest of an FPGA is still running. Computer‐aided design (CAD) tools and architecture are the two important technologies, which differentiate FPGAs. First memory‐based programming FPGAs were introduced in 1986 by Xilinx Inc., San Jose, CA [1].

© 2017 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, and reproduction in any medium, provided the original work is properly cited.

The programmable term in FPGA only reflects that any new function can be implemented on the chip even after its fabrication. Programmability/reconfigurability of an FPGA is based on an underlying programming technology, which can cause a change in behavior of a prefab‐ ricated chip. The main programming technologies used in FPGAs are static random memory (SRAM), flash memory, and antifuse [2–5].

The SRAM‐based FPGAs provide ideal prototyping medium and are widely used to inte‐ grate FPGAs in an embedded system [6–8] due to the use of standard CMOS technologies, higher performance, and reprogrammability. However, the larger static power consumption in SRAM cell limits the use of SRAM‐based FPGAs in portable embedded system compared to flash‐based FPGAs [9, 10]. The other concern related to SRAM‐based FPGA is its volatile nature. Although the dynamic power management and duty‐cycling techniques [11, 12] have been used to save static power during idle mode of FPGA, these techniques are not very effec‐ tive due to the energy consumption associated with the resulting reconfiguration process. Due to large load capacitance and high access rate, SRAM cells are responsible for consuming sig‐ nificant portion of the total power of the design. Thus, SRAM power consumption is an impor‐ tant consideration for designers to find the balance between the performance and the overall power consumption. The speed of the SRAM cell in FPGA is not a critical factor because it does not affect the operating speed of the circuit implemented in FPGA as mentioned in ref. [13].

In this chapter, we investigate the various factors responsible for power consumption in SRAM‐based FPGAs and review the different techniques proposed in the literature to save the power. We will also consider the static and dynamic power in the conventional 6T SRAM cell and its architecture. Various design techniques, presented in the literature, to reduce power consumption in SRAM cell will be reviewed in detail with their merits and demerits. A data‐ aware power‐efficient SRAM cell will be discussed to save power and to optimize the stability.


**Ingrid Lu**ff**man \* and Arpita Nandi**

Department of Geosciences, East Tennessee State University, Johnson City, TN 37614, USA<EMAIL_ADDRESS>**\*** Correspondence<EMAIL_ADDRESS>
Received: 11 February 2020; Accepted: 20 March 2020; Published: 25 March 2020

**Abstract:** This study examines the relationship between gully erosion in channels, sidewalls, and interfluves, and precipitation parameters (duration, total accumulation, average intensity, and maximum intensity) annually and seasonally to determine seasonal drivers for precipitation-related erosion. Ordinary Least Square regression models of erosion using precipitation and antecedent precipitation at weekly lags of up to twelve weeks were developed for three erosion variables for each of three geomorphic areas: channels, interfluves, and sidewalls (nine models in total). Erosion was most pronounced in winter months, followed by spring, indicating the influence of high-intensity precipitation from frontal systems and repeated freeze-thaw cycles in winter; erosion in summer was driven by high-intensity precipitation from convectional storms. Annually, duration was the most important driver for erosion, however, during winter and summer months, precipitation intensity was dominant. Seasonal models retained average and maximum precipitation as drivers for erosion in winter months (dominated by frontal systems), and retained maximum precipitation intensity as a driver for erosion in summer months (dominated by convectional storms). In channels, precipitation duration was the dominant driver for erosion due to runoff-related erosion, while in sidewalls and interfluves intensity parameters were equally important as duration, likely related to rain splash erosion. These results show that the character of precipitation, which varies seasonally, is an important driver for gully erosion and that studies of precipitation-driven erosion should consider partitioning data by season to identify these drivers.

**Keywords:** gully erosion; seasonality; precipitation; statistical modeling; precipitation intensity


**1. Introduction**

Oxidative stress is strongly involved in the pathogenesis of different neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis [1]. Particularly, an excess of reactive oxygen species (ROS) released by cells promotes oxidative stress, which is a cause of tissue injury and results in dysfunction in the nervous system. So far, no drugs have been discovered to prevent or halt the progression of these widely spread neurological disorders, and the treatments available only manage the symptoms. Therefore, there is an urgent need for new treatments for these diseases, since the World Health Organization (WHO) predicts that by 2040, neurodegenerative diseases will become the second-most prevalent cause of death [2]. New therapeutic approaches can derive from phytochemicals, a huge source of compounds that have been widely investigated in the last years [3]. Sulforaphane (SF) (Figure 1a) is an isothiocyanate derived from *Brassicae* vegetables and has consistent support in the literature for its preventive role against oxidative stress [4], in addition to its well-known role in chemoprevention [5]. Epigallocatechin gallate (EGCG) (Figure 1b), the major catechin found in green tea [6] with diverse medical potential [7] has been demonstrated to promote neuroprotection in numerous studies [8]. Plumbagin (PB) (Figure 1c), a naphthoquinone isolated

from the *Plumbaginacae* family, has mainly been studied in respect to its anti-inflammatory [9–11] and antimicrobial activities [12], even though it was also shown to modulate oxidative stress response [13] and precisely target NADPH oxidase 4 (NOX4) [14]. Importantly, the treatment of undifferentiated SH-SY5Y cells with a specific concentration of SF [15], EGCG [16], and PB [17] has been reported to decrease oxidative stress at different levels. On this basis, we hypothesized that a proper combination of such bioactive compounds could possess a higher effect in counteracting oxidative stress-induced neurodegeneration. Within organs, there are various concentration gradients for oxygen as well as for effector molecules, i.e., internal metabolites or exogenous compounds/drugs. Since the human brain cannot be modelled adequately in animals [18], reductionist humanized cellular systems are used and increasingly requested according to the 3Rs (Replacement, Reduction and Refinement) rule.

**Figure 1.** Chemical structures of the natural compounds used in this study. (**a**) Sulforaphane (SF), (**b**) epigallocatechin gallate (EGCG), (**c**) plumbagin (PB).

Currently, the majority of cell-based studies on neurodegeneration have been carried out on cultured cells propagated in two dimensions on plastic surfaces. However, cells cultured in these non-physiological conditions do not represent the cells residing in the complex microenvironment of the brain. With respect to this, recent evidence has suggested that three-dimensional (3D) in vitro microenvironments may better model key features of brain tissues in order to study the molecular mechanisms at the base of neurodegeneration and neurorepair [19,20]. Numerous in vitro approaches have been carried out to mimic human neuronal features, based on neuronal-like cells such as the neuroblastoma line SH-SY5Y. SH-SY5Y is a human cell line that divides quickly and has the ability to differentiate in post-mitotic neurons, thus it is considered a convenient model to study Parkinson's [21] and Alzheimer's diseases [22]. Unlike traditional two-dimensional (2D) cultures, the different availability of oxygen and growth factors in a 3D cell culture should expectantly favor a more in vivo-like morphology and growth of these cells. Indeed, several 3D culture models have been developed with SH-SY5Y cells, in terms of cell aggregates [23], spheroids [24,25], or including different scaffolds [26–28]. To support 3D cultures of SH-SY5Y or neuronal cell lines, collagen has also been used, like collagen hydrogel [29] or porous collagen-based scaffolds [26,30]. To the best of our knowledge, none of the previous models has been used to investigate the ability of natural bioactive molecules to confer resistance to oxidative stress. The aim of this study was to evaluate the neuroprotective effect of a combination of SF, EGCG, and PB in preventing cell damage derived from oxidative stress in a 3D cell culture based on a collagen porous scaffold.


**6. Conclusions**

This article analyzed the foundations of the future methodology for synthesizing the risk of functional smart expansive systems, taking into account the need to consider the balance between its constituent subsystems: production, development potential and regulation. We propose considering risks as "development anti-potentials" that slow down the reproduction speeds of the entire system. The concept of the geometric integral "antirisk" is introduced, resulting from the concept of "difficulties in achieving the goal". Thus, the conceptual definition of risk as the influence of uncertainties on the achievement of the goal of smart expansive systems is formalized.

To assess private risk factors included in the integral risk, we propose a method of vector compression. The idea to build compatible reference solutions, which form the basis for the developed method, represents an alternative to pairwise comparison in the method of analysis of hierarchies and the method of analytical networks.

Further to this, we propose an approach to processing partial matrices of pairwise comparisons, which makes it possible to minimize the disadvantages of the existing methods for working with similar matrices, especially for matrices of large dimensions. The principles of handling pairwise comparison matrices by describing their upper and lower boundaries have been investigated. The developed vector compression algorithm allows us to obtain the weights of compared objects on the basis of matrices of pairwise comparisons containing omissions, without fully restoring the matrix of pairwise comparisons, and also allows us to obtain the weights of given upper and lower boundaries through comparative assessment of pairs of objects.

This paper is not a standalone work capable of covering all issues and presenting the variety of smart expansive systems. These will undoubtedly be the topics of further

research. To give an example of where future studies may take us, the smart expansive system in this paper was considered in a linear approximation and stationary case. Beyond the scope of the article, a question must also be raised about the behavior of an intelligent expansive system in a "non-stationary state", where oscillatory processes (and maybe chaos) may occur. Moreover, the uniqueness of the approximation we chose has not been proven, and the option of using the vector compression method for upper and lower bounds in cases of restrictions imposed on the coefficient (greater than/less than zero) for fuzzy definition of the original matrices has not been considered. We plan to investigate all these and many other avenues in the future.

The proposed method could become an important element in the algorithmic provision of expert advising systems to support decision-making on the management of smart expansive systems, provided there is an appropriately organized procedure for selecting experts to be involved in the assessment of solutions.

**Author Contributions:** Conceptualization, A.B. and N.Z.; methodology, A.B.; software, A.R.; validation, A.B., N.Z. and N.K.; formal analysis, N.K.; investigation, N.Z.; data curation, N.Z.; writing— original draft preparation, A.B.; writing—review and editing, A.B.; visualization, A.R.; supervision, N.Z.; project administration, A.B. All authors have read and agreed to the published version of the manuscript.

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

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


**6.1 Streaming instability**

This type of instability occurs, when either a current or a beam of energetic particles is driven through plasma so that the different species of particles have drifts relative to one another. This drift energy attempt to excite waves and oscillation. This energy is acquired at the loss of the drift energy, which is in the unperturbed state.

### **6.2 Rayleigh–Taylor instabilities**

In this kind of instability, the plasma has a sharp boundary or a density gradient, so that it does not remain uniform. In addition to this, an external, nonelectromagnetic force is applied into the plasma. This force is responsible for driving the instability in plasma. This analogy can be realized in an inverted glass of water. Though the plane interface between the air and the water is in the state of equilibrium, where the air pressure support the weight of the water. Any ripple arising in the surface of water tend to grow at the loss of potential energy in the influence of gravitational field. Whenever a light fluid supports a heavy fluid this things happen, which is quite known in the field of hydrodynamics [1].

## **6.3 Universal instabilities**

A plasma is hardly present in perfect thermodynamic equilibrium, when it is confined by gravitational field or an electric field (driving forces). The plasma is expanded by plasma pressure and an instability is driven by the expansion energy. Any finite plasma always contains this type of free energy and the waves, which comes out as a result are called universal instabilities.


**3.1 Tensile properties**

The survivability plot is an indication of the lower and upper limits of any variable which gives the reliability and reproducibility of the data. In **Figures 2**–**4**, the tensile property changes of Sc, Er, Y, and V added A357 in as-cast conditions are given. For the yield strength (**Figure 2**), 0.05 and 0.1 wt% Sc reveal the highest reproducible results where the strength value changes between 116 and 120 MPa. In terms of design parameters, the survivability plot gives information about the possible lowest and highest potential values that this parameter can provide. For

**Figure 2.** *Survivability plot of yield strength.*

*Characterization of Casting Properties of Rare-Earth Modified A356 DOI: http://dx.doi.org/10.5772/intechopen.101722*

**Figure 3.** *Survivability plot of ultimate tensile strength.*

**Figure 4.** *Survivability plot of elongation at fracture.*

example, 0.05 wt% Er castings reveal that they can exhibit a minimum of 109 MPa below which the material will always be in an elastic region. This particular test result also provides the information that this alloy can provide a yield strength of 140 MPa as well. Thus, it shows the potential of the alloy. However, since the scatter is too high (yield strength ranging between 109 and 140 MPa), the reliability of this parameter becomes very low. On the other hand, looking at 0.05 wt% Sc addition, it is very steep at values between 116 and 120 MPa which is quite narrow and thus

the reliability of this casting is too high. This states that the yield strength value will undoubtedly be between these values.

The highest scatter is observed with 0.05 wt% Er and 0.1 wt% Y additions. The values are in the range of 90–133 MPa for Y, and 107–140 MPa for Er. Although, Er shows high scatter, yet it had the potential that this addition has the highest yield strength value of 140 MPa. On the other hand, the lowest yield strength value was obtained when Y was used as a modifier to A357.

The ultimate tensile strength values for all additions were very close to each other (**Figure 3**). The highest reliable and most reproducible results were obtained with 0.05 wt% Sc samples which were 197 MPa with a standard deviation of ±3. Pramod [22] had found that Sc additions to A356 had increased the UTS 45% when Sc was added up to 0.4 wt%.

The highest scatter was observed 0.05 wt% Er castings. The lowest UTS values were found to be in Y modified alloy whereas the highest possible UTS values were obtained with 0.05 and 0.1 wt% Er added A357 with a potential of having 265 MPa. Colombo [14] reported that 0.3 wt% Er addition was the optimum ratio in their study to exhibit the highest tensile properties.

As can be seen in **Figure 4**, 0.1 wt% Y added A357 had the potential of having 9% elongation at fracture, however, this alloy has the highest scatter and thereby revealing the least reliable casting. The 0.05 wt% Y added A357 has the lowest elongation while 0.05 and 0.1 wt% Er show the highest reproducible results.

The change in the tensile properties after the samples were subjected to heat treatment is given in **Figures 4**–**9**. There is almost twice the change in yield strength after heat treatment with Sc showing the highest value of 260 MPa and Y showing the lowest of 216 MPa (**Figure 5**). The ultimate tensile strength increases approximately 25% where Sc and Er have the highest value of 300 MPa whereas Y additions show the lowest UTS of 240 MPa (**Figure 6**). There is an almost 70% decrease in elongation values for all additions, except Er additions. Therefore, the toughness change of Er with and with heat treatment is nearly too small and Er additions exhibit the highest toughness amongst the alloys studied in this work (**Figure 7**).

**Figure 5.** *Yield strength change with heat treatment.*

*Characterization of Casting Properties of Rare-Earth Modified A356 DOI: http://dx.doi.org/10.5772/intechopen.101722*

**Figure 6.**

*Ultimate tensile strength change with heat treatment.*

**Figure 7.**

*Elongation at fracture change with heat treatment.*

Hu [29] used the HPDC method to check the mechanical properties change of Al12Si alloy where Er content was changed between 0, 0.3, 0.06, and 0.9 wt%. It was reported that as Er content was increased, UTS was increased with decreased grain size, however, elongation at fracture values was decreased. This was attributed to the presence of Al3Er phases found on the SEM images of fracture surface analysis. Therefore, it was concluded that these precipitates acted as reinforcements to the matrix, thus increasing UTS but decreasing elongation. Gao [16] reported

**Figure 8.** *Toughness change with heat treatment.*

**Figure 9.**

*Quality index change with heat treatment.*

similar results claiming that nano-sized Al3Er, Al3Zr, and Al3(Zr,Er) precipitates show resistance to dislocations and increase the strength of pure aluminum significantly. Shi [15] proposed that Al3(RE) intermetallic phases do not have the grain refinement effect but rather act as barriers to dislocation movement and thereby increase the tensile properties of Al-Si alloys. Shi [15] also reported that Er has more physicochemical activity than that of other modifiers which have the potential to eliminate bifilms [27, 30–36] and increase the melt quality, therefore exhibiting

*Characterization of Casting Properties of Rare-Earth Modified A356 DOI: http://dx.doi.org/10.5772/intechopen.101722*

higher mechanical properties. In the trials reported by Pramod [22], 0.4 wt% Sc addition to A356 had resulted in achieving 300 MPa levels with the lowest SDAS (10 μm) and refined Si morphology. In this work, 30 μm SDAS was good enough to achieve 300 MPa.

Pourbahari [21] studied the effect of La addition and they reported that the presence of intermetallic like Al4La was more spherical and distributed in the microstructure (at low levels of La addition), and therefore they did not act as stress rising locations that would decrease the ductility of the alloy. However, when La content was higher than 0.1 wt%, new intermetallic phases such as AlSiLa were formed which were flakey and needle-like, thereby reducing the toughness of the matrix. The fracture surfaces were quasi-cleavage facets and not dimple like as in low La levels.

Drouzy's quality index [37] assessment was also used in this study and the results are given in **Figure 9**. It can be seen that Er and Sc both have the highest index values. Additionally, those elements are the only ones that show an increase in the quality index after heat treatment.

### **3.2 Microstructure**

Although, the mechanical properties of each different grain refiner addition show a wide range of values and there is a quite difference between the samples, yet the microstructural analysis had revealed that the DAS and SDAS of all castings were very close to each other (**Figures 10** and **11**). Only 0.05 wt% Y addition shows the highest DAS value compare to the others, but all SDAS measurements of castings were recorded to be between 30 and 40 μm as seen in **Figure 12**. It is interesting to note that only in Y additions Si morphology was altered to fibrous type (**Figures 10b** and **11b**). Colombo [14] added 0.2 and 0.4 wt% Er and found that Er acted as a modifier for Si

**Figure 10.** *Microstructures of 0.05 wt% (a) V, (b) Sc, (c) Er and (d) Y added A356.*

### *Aluminium Alloys - Design and Development of Innovative Alloys, Manufacturing Processes...*

**Figure 11.** *Microstructures of 0.1 wt% (a) V, (b) Sc, (c) Er and (d) Y added A356.*

*Characterization of Casting Properties of Rare-Earth Modified A356 DOI: http://dx.doi.org/10.5772/intechopen.101722*

**Figure 13.** *Fluidity change of different grain refiner (a) 0.05 wt%, (b) 0.1 wt% additions.*

together with a 30% reduction in SDAS. However, in this work, 0.05 and 0.1 wt% Er were added and no modification of Si was observed (**Figures 10c** and **11c**).

Pramod [22] reported that 0.4 wt% Sc had a reduction capability of SDAS by 50%. Compare to 0.2 wt% Sc addition, the silicon size was also significantly decreased which resulted in having the highest UTS values of 300 MPa. Pandee [38] added three different levels of Sc to A356; namely 0.24, 0.40, and 0.65 wt%. Two different cooling rates were studied. At both cooling rate levels (0.1 and 3°C/s), as Sc content was increased, Si morphology was modified to a fibrous structure. At 3°C/s, the modification of Si was found to be the optimum for 0.4 wt% Sc modified A356. In a similar kind of work, W. Zhang [4] also reported similar findings that higher than 0.15 wt %Sc addition to A356, Si morphology was completely modified.

On the other hand, Xu [25] found almost a linear decrease in grain size with increased Sc content varying from 0.2 towards 0.8 wt% Sc additions to F357 where the modification of Si was started at 0.2 wt% additions. With UTS values as high as 350 MPa.

### **3.3 Fluidity**

The fluidity test results were analyzed under the wt% additions as seen in **Figure 13**. When 0.05 wt% addition levels are compared, it can be seen that Er and Y appear to have higher fluidity lengths compared to the other additions. On the other hand, when 0.1 wt% additions are analyzed, Sc has significantly higher fluidity compared to the other additions. In each of the cases, V reveals the lowest fluidity results. Prukkanon [39] reported that up to 0.2 wt% Sc addition, the fluidity of A356 was increased, but a higher amount of Sc addition had not affected the fluidity and remained unchanged at 660, 690, and 720°C.