**2. Background**

that is the number percentage of sugar solution and sedimentation time of "ball" on each of

**Figure 3** represents various concentrations of solutions. Practically, we used more details of sugar solutions by inserting 15, 25, 35, and 45% of sugar solution. Instructional design of mathematics based on the science using didactical phenomenology approaches was pre‐ sented to the students, so that the students have a sense of the relationship between two quan‐ tities. Students have the ability to represent it in a variety of mathematical representations. Furthermore, numbers obtained are processed and then packaged in various forms of math‐ ematical representations. Using this reflective thinking, students can think mathematically and scientifically to instill their awareness to be able to live in a healthy life and harmony.

The chapter presents the results of this study synergically involving scientific activities. Didactical phenomena of instructional design of mathematics were designed by the team in the laboratory activities, recorded using video camera, transferred to the power point presen‐ tation. The student tasks in the classroom were to make mathematical model or mathematical graph related to the data as the result of observation was recorded in video camera and power point presentation. These data were presented in the form of table. The pair numbers in the table as coordinates were then be plotted in the Cartesian coordinates. By graphing this phe‐

As a design proposed by Verschaffel, Greer, and De Corte (2002, cited by Turmudi et al. [2], **Figure 4**), the process of learning mathematics that involves the modeling process includes the observation of phenomena (reading), understand the situation, modeling, analyzing the

The teaching materials of mathematics in this study used the didactical phenomenon in the form of a natural situation or similar situations that conditioned the models created in the science laboratory. The students in the classroom are faced with these instructional materials

> Mathemacal Model

Generang from model Mathemacal Analysis

model, formulate the results, interpretation, and then make a communication:

and the materials were manipulated in the form of power point presentation.

Situaon Model

Evaluaon

Unde Modeling rstanding

Interpretaon

Interpretaon Communicaon

nomenon, the students were asked to interpret the phenomena.

Reports Results of

**Figure 4.** Diagram of mathematical modeling process.

these solutions.

10 Science Education - Research and New Technologies

Observed phenomena After doing some research in a clump of innovative teaching, research teams are interested in trying out the learning of mathematics with science‐based didactic phenomena within rea‐ sonable time. Research studies on realistic mathematics have been conducted with the result that is very promising and could attract the attention of students [3, 4]; encourage teachers in the Bandung city area to realize that they already know their innovative ideas but do not have the ability to present learning with innovative ideas because of the absence of exemplary prototypes [5, 6], the teachers realized that the training through lesson‐study has opened their insight to continue working and improving the learning for teaching of mathematics in the classroom [7] but the teachers still require exemplary prototype of mathematics learning using scientific approach that can be implemented in the classroom, so that openly they can watch in open‐lesson setting, and in turn the teachers be able to implement it in their respec‐ tive classes.

Results of research on mathematical modeling by [2, 8] show that the students involved in the study felt there was something new in mathematics instruction. For example in view of the variables that were not visible, but after attending the workshop the participants were able to see the variables in the phenomena, so they were able to make the association among vari‐ ables that exist to make a mathematical model. Consider the following figures:

**Figure 5** is the pattern model that originally taken from the floor of JICA‐FPMIPA building of UPI on the second floor (**Figure 6**, personal collection of photograph), the tile patterns can be seen in the image (**Figure 7**, personal collection of photograph).

At first time, the images were just as the pictures without meaning, the students are not too concerned with tile patterns like that, but with a small call "Let us see and we noticed a pat‐ tern (in **Figure 7**), as well as how to process it so we could have an interesting mathemati‐ cal concept." The invitation make a number of students feel surprised by the mathematical patterns that exist in the JICA Building, in Bandung. When the students were able to see the pattern of the picture and are able to associate with the image number and the area of the geometry shapes, then they obtained a mathematical model that previously did not figure

**Figure 5.** Patterns of floor in JICA‐FPMIPA building.

**Figure 6.** JICA‐FPMIPA building in UPI.

out. This association when we continued to the 4th, 5th , 6th terms and so on until the n‐th term, it will get the functional formula by following form of F(n) = n2 + 2n with n is the image num‐ ber (term) and F(n) is the area of geometrical shapes. By knowing how to build and determine the formula of model, the students can reach through the process of horizontal and vertical mathematization [9] and the process of progressive mathematization [10]). Teacher's capa‐ bilities to view such situations nowadays are needed urgently, so that they can try out these competences at the microlevel of the classroom. Such capabilities are seemed urgent, because the implementation of the 2013‐curriculum [11], which was characterized scientifically, in fact, was not absorbed completely by the teachers during the 2013‐curriculum upgrading. Therefore, the presence of such learning is a positive contribution toward building the current curriculum innovation in Indonesia.

Provisioning capabilities of mathematical concepts, and the pedagogical content knowledge (PCK) of mathematics for teachers would give effects to a teacher as an actor of mathematics learning in action in front of the class. The ability to see the phenomena should be the part of the teachers' as well as the students' competences, so that they always think continuously

**Figure 7.** Floor in JICA‐FPMIPA building.

over time and will always able to find connections between the existing phenomena by taking into account the specific quantities or the shapes in the flat geometry (2D) or space geom‐ etry (3D), therefore it can intertwined the functional relationship between the quantities that appeared in Ref. [54].


*3.5. Microbiological Assessment*

The ability of implants modified with TNT and TNT/AgNPs layers to inhibit microbial colonization and biofilm formation was tested in comparison to an unmodified Ti6Al4V surface (control biomaterial) with the use of Gram-positive (*S. aureus*, *S. gordonii*, *S. mutans*) and Gram-negative (*E. coli*) bacteria, as well as fungi (*C. albicans*, *C. glabrata*). The metabolic activity of the microorganisms attached to the surfaces after 24 h of exposure to the microbial suspensions was measured using Alamar Blue. The results are presented in Figures 7 and 8 (for bacteria and fungi, respectively) as a percentage of the metabolic active microbes recovered from the biofilms formed on the tested surfaces in comparison to the biofilms formed on unmodified control biomaterial (Ti6Al4V) being considered as 100%. All tested modified titanium alloy implant surfaces were able to inhibit microbial colonization and biofilm formation; however, in the case of bacteria, the observed effect strongly depended on the strain used. Generally, well-defined anti-biofilm activity on the tested TNT and TNT/AgNPs layers was demonstrated against *S. aureus* ATCC 29213 and *E. coli* ATCC 25922 (Figure 8). The average percentage

of biofilm inhibition, compared to the control biofilm developed on unmodified Ti6Al4V, achieved the range from 41.1 ± 3.0% (*p* = 0.034) to 49.7 ± 1.5% (*p* = 0.034) for *S. aureus* ATCC 29213 and from 33.2 ± 10.7% (*p* = 0.034) to 76.3 ± 1.5% (*p* = 0.034) for *E. coli* ATCC 25922. The weakest inhibitory effect was observed for *S. gordonii* ATCC 10558 (biofilm reduction of up to 9.0% on TNT5/AgNPs and TNT15/AgNPs, *p* = 0.028 and *p* = 0.0082, respectively). The surfaces expressed no significant or moderate activity against *S. aureus* ATCC 43300 and *S. mutans* ATCC 25175, with the exception of TNT5/AgNPs, which inhibited biofilm formation by these second bacteria of 80.9 ± 1.2% (*p* = 0.021). In the case of fungi, the inhibitory effect of the surfaces tested was similar for both strains (*C. albicans* and *C. glabrata*), achieving the level of 13.3 ± 1.6% to 33.7 ± 8.5% (Figure 8, all results were statistically significant). Interestingly, there was no great distinction in the reduction of the microbial biofilm caused by TNT surfaces and corresponding them to the TNT/AgNPs layers.

**Figure 7.** Bacterial biofilm on TNT- and TNT/AgNPs-modified Ti6Al4V surfaces assessed using Alamar Blue staining. The results are presented as the mean percentage ± standard deviation (SD) of the bacterial biofilm formed on the tested layers compared to a control biofilm formed on the reference biomaterial (Ti6Al4V) considered as 100%. Statistical analysis was estimated with nonparametric Kruskal–Wallis one-way ANOVA test (\* significant differences, *p* < 0.05).

**Figure 8.** Fungal biofilm on TNT- and TNT/AgNPs-modified Ti6Al4V surfaces assessed using FDA (fluorescein diacetate) staining. The results are presented as the mean percentage ± standard deviation (SD) of the fungal biofilm formed on the tested layers compared to a control biofilm formed on the reference biomaterial (Ti6Al4V) considered as 100%. Statistical analysis was estimated with nonparametric Kruskal–Wallis one-way ANOVA test (\* significant differences, *p* < 0.05).

Since biologically active (biostatic/biocidal) substances can be released from modified titanium surfaces when implants are in the host tissue, we also tested the antimicrobial effect of the supernatants obtained after short- (24 h) and long-term (2 and 4 weeks) biomaterial incubation in PBS to simulate such conditions. Four microbial strains were used for these studies (*S. aureus* ATCC 43300, *S. aureus* ATCC 29213, *E. coli* ATCC 25922, and *C. albicans* ATCC 10231) and the results are presented in Figure 9a–c as the mean density of microbial suspensions cultured for 24 h in the presence of biomaterial-derived supernatants (s). As expected, the type of titanium surfaces and the time of their incubation in PBS were the most important factors determining the release of biologically active substances from biomaterial samples and thus the antimicrobial activity of the supernatants tested. After a short (24 h) incubation, the supernatants showed almost no activity against bacterial strains (Figure 9a).

**Figure 9.** Antimicrobial effect of the supernatants obtained after 24 h (**a**), 2 weeks (**b**), and 4 weeks of (**c**) TNT- and TNT/AgNPs-modified Ti6Al4V surfaces' incubation in PBS, tested using the culture method and colony forming unit (CFU) counting. The results are presented as the mean microbial suspension density [CFU/mL] ± standard deviation (SD) after 24 h of culture in the presence of the tested supernatants.

The number of bacteria in the presence of the compounds released from AgNP-modified layers was reduced in the range 2.6%–27.9% for the TNT5/AgNPs supernatant and 0%–24.6% for the TNT15/AgNPs supernatant, in comparison to the number of the bacteria exposed on the control Ti6Al4V-derived supernatant. Whereas, *C. albicans* cells proved to be the most sensitive to the antimicrobial activity of the compounds released from the modified biomaterial samples. The reduction of the yeast cell number caused by the TNT15/AgNPs 24-h supernatant reached 99.9% (Figure 9a), which means it has strong biocidal activity against fungi. By extending the incubation time of the biomaterial samples, the bactericidal properties of the supernatants obtained from AgNP-containing layers increased significantly. However, the compounds released from TNT5/AgNPs demonstrated the strongest antibacterial activity after two weeks (Figure 9b) while those from TNT15/AgNPs after four weeks (Figure 9c). The two-week supernatant of TNT5/AgNPs significantly reduced the number of all tested microbial strains (both bacteria and fungi), with the reduction levels reaching 61.5%, 91.4%, 78.3%, and 99.9% for *S. aureus* ATCC 43300, *S. aureus* ATCC 29213, *E. coli*, and *C. albicans*, respectively (Figure 9b). The two-week TNT15/AgNPs-derived supernatant activity was similar only against *C. albicans* (99.8% reduction of fungal viability; Figure 9b). However, during 4 weeks of biomaterial incubation in PBS, the antimicrobial potential of the TNT15/AgNPs-derived supernatant increased significantly, causing complete elimination of most of the tested microorganisms. The reduction of the *S. aureus* ATCC 43300, *E. coli*, and *C. albicans* populations exceeded 99.9% after exposition of this supernatant (Figure 9c). The effect on *S. aureus* ATCC 29213 was a little bit weaker (71.3% of eradication) but still very strong (Figure 9c) while the supernatants derived from the TNT5 and TNT15 samples (both 2 and 4 weeks) did not exhibit killing activity against the microorganisms tested (Figure 9b,c).

#### *3.6. AFM Topography and Nanomechanical Properties Studies*

The topography images and the Sa parameter values of TNT5 and TNT5/AgNPs samples (systems whose surface shows the best biological properties) using atomic force microscopy (AFM) are presented in Figure 10. Analysis of these data showed that the implant surface has a much more extensive surface topography before the AgNP deposition process. The roughness parameters, Sa, decrease about 57% from 0.89 for TNT5 before silver deposition to 0.39 for implant TNT5/AgNPs with nanosilver on the surface. A significant decrease in the roughness value was probably caused by the deposition of silver nanoparticles in the surface cavities, which led to their smoothing.

**Figure 10.** The topography of TNT5 and TNT5/Ag implants with Sa (Average Roughness) parameter values, which was determined using atomic force microscope (AFM).

The nanomechanical and nanoindentation properties of the tested implants (TNT5 and TNT5/AgNPs) for the two tested areas of each surface are presented in Table 4. In the case of the TNT5, no such significant differences in the mechanical properties (nanohardness and Young's modulus) were observed between the tested area surfaces (I and II) as in the case of the tested areas (I and II) of the implant TNT5/AgNPs. The presence of silver nanoparticles resulted in an increase of the nanohardness and Young's modulus and as a consequence, as increase of parameter H/E (Hardness to

Young's Modulus ratio), which determines the resistance to wear of the tested specimens. The relation between parameter H/E and wear resistance were reported [35]. The significant standard deviation values confirm the credibility and diligence of the presented results and their value in studies on the nanoindentation on titanium dioxide nanotube layer were reported previously by Jemat et al. [41] and Rayon et al. [42]. Moreover, using small values of force (10 mN) on surfaces with a high surface roughness causes significant differences between individual measurements. The 3D distribution of nanomechanical properties, such as the nanohardness and Young's modulus, for TNT5/AgNPs (tested area II) are presented in Figure 11. The presented results confirm the value of the standard deviation presented in Table 4. The presented results show the heterogeneity of the distribution of the mechanical properties and the relationship between the hardness and Young's modulus because the distributions are similar to each other.

**Table 4.** Nanomechanical and nanoindentation properties of the tested implant samples.

**Figure 11.** The nanomechanical properties (nanohardness and Young's modulus) of TNT5/Ag implant in the studied area II.

The nanoscratch test results for TNT5 and TNT5/AgNPs are presented in Table 5. Nowadays, the nanoscratch test method is a dedicated method to assess the adhesion of thin coatings or layers, as in the case of the presented tests. In Table 5, two different types of force obtained during nanoscratch test measuring for the tested coatings are presented. The critical force is the maximum applied force between the coating and the indenter during full delamination of the coating from the metallic substrate (Ti6Al4V) and the critical friction force is the maximum friction force registered during full delamination of the coating. The presence of silver nanoparticles in the composite coating (TNT5/AgNPs) caused an increased critical force (from 79.70 to 173.40 mN) and critical friction force (from 130.77 to 212.34 mN). The results obtained from nanoindentation tests determined the wear resistance of the tested surfaces (H/E ratio) correlated with the nanoscratch test results. The H/E parameter for the TNT5/AgNPs surface was significantly higher than for the TNT5 surface. The same trend was reported in the nanoscratch tests results.

**Table 5.** Adhesion properties of the titanium dioxide nanocoatings to the titanium alloy surfaces.


*2.1. Materials*

An industrial, never-dried, bleached eucalyptus kraft pulp and an industrial, air-dried, bleached pinus kraft pulp were used in this work after disintegration according to ISO 5263-1. The additives used in this study were CBA and CMF. This commercial tissue additive, CBA, is a cationic polymeric solution specially designed as a replacement for cationic starch. CBA presents a viscosity of 500–900 cP, a pH of 2.1–4.0 and a density of 1.030 ± 0.040 g/cm3 at 20 ◦C (data supplied by a commercial enterprise). CMF was supplied by a research institute and obtained by mechanical (refining and homogenization) and enzymatic (cellulase) treatments using an industrial bleached eucalyptus kraft pulp. This sample was characterized in our previous work, which can be used for more detailed information [24]. CMF (Figure 1) presents an intrinsic viscosity of 1577 mL/g (ISO 5351), a carboxyl group content of 8.4 ± 0.2 mmol/100 g (TAPPI T 237 om-93), a suspension drainability degree superior to 80 ◦SR (Schopper–Riegler) and 56% of particles below 1000 nm, representing 10% of particles below 200 nm [24].

**Figure 1.** SEM image of the CMF additive, highlighting a high magnification image (3000×) where it is possible to verify the micro and nanofibrils of this sample.


**4. Relationship of muscle microstructure and meat quality**

Carcass is composed of meat, fat, adipose tissue, bone, cartilage, connective tissue and tendon. Muscle turns into flesh after cutting process because its physiological function stops. Muscle is the main component of meat constituents. All muscles have the same basic structure, consisting of muscle cells or fibers that are intertwined together in bundles and form larger groups. Collagen is the most important component related to meat texture. Collagen of old animals grow larger and they have more cross-linked connective tissues, causing the meat to become tough and less tender [12].

Muscle is composed of many bundles of muscle fibers commonly called fasciculi. Fasciculi consist of muscle fibers, whereas muscle fibers consist of many filaments called myofilaments. Connective tissue is composed of an epimysium located around the muscle, perimysium containing blood vessels, and relatively larger nerves located between fasciculi and endomysium containing amorphous component, non-fibrous tissue with fine woven binders surrounding muscle cells or muscle fibers [29].

(1) pH

pH range of 5.5–5.8.

72 Bovine Science - A Key to Sustainable Development

tenderness value.

beef.

process.

(2) Water holding capacity

of meat and its processed products [28].

to become tough and less tender [12].

The pH value of meat may indicate a deviation of the quality of the meat, since the pH value of the meat is related to the color, tenderness, taste, water holding capacity and the shelf life of the meat. The isoelectric pH points of the meat proteins are between 5.0 and 5.1 with a normal

If pH > 5.8, then there are two possibilities of normal or DFD (dark, firm, dry). The second pH test is done at 24 hours after cutting, if pH > 6.2 means the meat is DFD, whereas if the pH is about 5.5 means the meat is normal [25]. Ref. [26] reported that meat with high pHu has a low

Ref. [27] compares the physical characteristics of ongole crossbreed beef at different body weights. The results showed that body weight has a very low correlation with pH value of meat, that is, 0.192 in *Longissimus dorsi* (average pH value of 5.59) and 0.000 on *bicep femoris* (average pH value of 5.57). Ref. [18] reported that pH bali beef is no different from wagyu

The pH value of meat is generally more influenced by the factor at the time of the slaughter

Water is the most important part in meat composition. Meat contains about 75% water. Muscle protein (myofibrillar) plays an important role in water binding, which determines the quality

Water holding capacity is the ability of the meat (especially myofibrillary proteins) to bind water or water added during external influences (e.g. meat cutting, heating, grinding and pressing). Ref. [29] found that water holding capacity of buffalo meat is not affected by age, but it is affected by sex during the storage period of 0, 24, and 48 hours. Result of analysis show water holding capacity of buffalo meat is not influenced by age and sex [20]. There is no difference in water holding capacity of bali beef and wagyu beef [18]. Ref. [16] also reported that there was no difference in binding power of brahman cross beef, bali cattle, ongole cross-

Carcass is composed of meat, fat, adipose tissue, bone, cartilage, connective tissue and tendon. Muscle turns into flesh after cutting process because its physiological function stops. Muscle is the main component of meat constituents. All muscles have the same basic structure, consisting of muscle cells or fibers that are intertwined together in bundles and form larger groups. Collagen is the most important component related to meat texture. Collagen of old animals grow larger and they have more cross-linked connective tissues, causing the meat

breed cattle and simmental × ongole crossbreed cattle on *Semitendinosus* muscles.

**4. Relationship of muscle microstructure and meat quality**

Muscle fiber is composed of myofibrils containing many myofilaments. Myofibril is an organelle of cylindrical muscle fiber with a diameter of approximately 1–2 μm. A muscle fiber that has a diameter of 50 μm contains 1000–2000 myofibrils. Myofibril consists of segments called sarcomere. The length of sarcomere at rest is approximately 2.5 μm. Sarcomeres have two forms of myofilaments, namely thick filaments (myosin) with a diameter of 10–12 μm and thin filaments (actin) with a diameter of approximately 5–7 μm. The lighter portion of myofibril is called I band, while the thicker part is called A band. I band and A band are arranged in longitudinal parallel within muscle fibers, which causes the cross section of skeletal muscle fibers to appear transverse [12, 30]. Increasing number of muscle cells during prenatal growth can be indicated from the addition of the amount of muscle per fasciculus. Increased muscle size during postnatal growth can be indicated from the addition of muscle cross-sectional area.

Observations on histology of muscle not only result in obtaining images or descriptions of muscle tissues (existence of muscle fibers, connective tissues and intramuscular fat tissues), but also in discovering the size of the tissues (such as diameter of muscle fiber, diameter of fasciculus, and thickness of connective tissue). Nuraini et al. [20] state that the average diameter of muscle fibers of buffalo meat, which is 38.32 ± 1.9 μm, increases under 1 year of age (I.0 ) and reaches the highest point at the age of 3 years (I3 ) with 54.95 ± 8.6 μm (P < 0.05). This is in line with the decline of buffalo meat tenderness level, which is 6.53 ± 2.89 kg cm−2 (under 1 year of age) to 9.63 ± 1.45 kg cm−2 (3 years of age). Ref. [29] mentions that many factors affect the diameter of muscle fibers, such as the level of nutrition, the rate of postnatal body weight development, the level of muscle performance and the age of livestock.

Ref. [31] describe the histology and histomorphometry of bali beef and wagyu beef. It appears that the muscle cell diameter (75.00 ± 1.72 μm) and fat cell (195.20 ± 2.17 μm) of wagyu cattle were larger than the muscle cell diameter (45.00 ± 1.89 μm) and fat cell (90.10 ± 2.69 μm) of bali cattle. Foreign tourists in Bali prefer wagyu beef than bali beef. This is partly because wagyu beef is more tender. Histologic observation results in wagyu cattle muscle illustrates that the connective tissue of wagyu beef is very little so that the meat is more tender.

Samples of muscle histology can also be used to discover the thickness of connective tissue that can be an indicator of the level of meat tenderness. Thickness of connective tissue of female buffalo at I0 age (15.59 ± 2.00 μm) is smaller than at I2 age (16.29 ± 5.96 μm) and at I3 age (18.2 ± 5.81 μm) [20]. This condition illustrates that there is an increase in connective tissue as the livestock ages. It is related to the level of collagen in animal tissues. Collagen is the principal protein component of connective tissue and has a major influence on toughness of meat [30]. Collagen of old livestock is more stable against the influence of temperature change, which results in formation of thicker and larger connective tissue. An increase in livestock age is related to increased level of pyridinoline. The level of *pyridinoline* in younger livestock is lower, making collagen labile against heat.

Some of the circumstances causing the low quality of meat in Indonesia are most of the breeders employing cattle and buffalo, low quality of feeding, older slaughter age and handling before and at the time of slaughtering process that does not pay attention to aspects of animal welfare. The meat industry in Indonesia is only able to form two market segments namely the local market for middle to lower class consumers and special markets for hotel, restaurant, catering and franchise consumers. Efforts to improve livestock management, selection and crosses with *Bos taurus* breeds are expected to improve local livestock performance in

Meat Quality of Indonesian Local Cattle and Buffalo http://dx.doi.org/10.5772/intechopen.79904 75

The authors thank those who participated in the various projects that led to these results, all those who provided funding support for this research and also thanks to the Open Access

The authors declare that there is no conflict of interest regarding the publication of this paper.

1 Department of Animal Production and Technology, Faculty of Animal Science, Bogor Agricultural University, Jl. Agathis Bogor Agricultural University, Darmaga, Bogor,

3 Assessment Institute for Agricultural Technology, Ministry of Agricultural, Tidore

[1] Kusuma SB, Ngadiyono N, Sumadi S. The estimation of population dynamic and reproduction performance of Ongole crossbred cattle in Kebumen regency, central java province. Bulletin of Animal Science. 2017;**41**(3):230-242. DOI: 10.21059/buletinpeternak.

Henny Nuraini1,2\*, Edit Lesa Aditia1,2 and Bram Brahmantiyo3

2 Halal Science Center, Bogor Agricultural University, Indonesia

\*Address all correspondence to<EMAIL_ADDRESS>
Kepulauan City, North Malucas, Indonesia

Indonesia.

Publishing Fee.

**Acknowledgements**

**Conflict of interest**

**Author details**

West Java, Indonesia

**References**

v41i3.13618

Efforts to improve the quality of local livestock, in this case cattle and buffalo, have been conducted in various methods, both physical (e.g. aging, cold/frozen storage) and chemically (e.g. using protease enzymes). Refrigerator storage causes the split muscle fibers. Increase in period of freezer storage can result in separation of muscle fibers as well as structural damage to muscle shape caused by ice crystal formation. The fourth day of storing meat inside freezer (−10 ± 1°C) shows mild damage. It is the beginning of muscle fibers cracking. On the 60th day, the structural damage of muscle fibers becomes more severe with ice crystals pressing and tearing cells. On the 75th day, the damage of muscle fibers becomes greater than the 60th day with greater intercellular distance [32].

According to [33] the diameter of muscle fibers of buffalo meat is not influenced by sex difference, but influenced by age difference during different storage periods. The data of research results conducted by Rao et al. [33]. The decrease in muscle fiber diameter occurs gradually from 0 to 48 hours of storage period inside freezer (−15 ± 1°C), so as to increase the tenderness of meat during the period of aging. Freezing also affects the structure of muscle fiber diameter due to histological changes in muscle tissue during frozen storage. Muscle fibers of female buffalo that were stored inside freezer at a temperature of −12°C for 35 days had less structural damage when compared to muscles stored for 79 days. Increased storage time of meat inside freezer can increase the damage of muscle fibers, so that connective tissue and the distance between muscle fibers become more easily decomposed due to the process stretching. Such damage is most likely to result in myofibril alterations.

Another treatment to improve tenderness in meat is to use enzymes, such as papain or bromelain enzymes. Related to [34], the tissue structure of beef samples not treated with bromelain enzyme is seen to have intact-shaped structures of myofibril and sarcolemma. Meanwhile, the myofibrils structure of meat samples soaked with bromelin enzyme for 1 and 4 hours looks incomplete, or in other words, has endured degradation. Descriptively, the alterations that occur in the myofibril structure indicate that giving treatment of bromelin enzyme can improve the tenderness of meat.


*Article* **Development and Validation of a Machine Learning Model Predicting Arteriovenous Fistula Failure in a Large Network of Dialysis Clinics**

**Ricardo Peralta 1, Mario Garbelli 2, Francesco Bellocchio 2, Pedro Ponce 1, Stefano Stuard 3, Maddalena Lodigiani 2, João Fazendeiro Matos 1, Raquel Ribeiro 4, Milind Nikam 5, Max Botler 6, Erik Schumacher 6, Diego Brancaccio 3 and Luca Neri 2,\***

**Abstract: Background:** Vascular access surveillance of dialysis patients is a challenging task for clinicians. We derived and validated an arteriovenous fistula failure model (AVF-FM) based on machine learning. **Methods:** The AVF-FM is an XG-Boost algorithm aimed at predicting AVF failure within three months among in-centre dialysis patients. The model was trained in the derivation set (70% of initial cohort) by exploiting the information routinely collected in the Nephrocare European Clinical Database (EuCliD®). Model performance was tested by concordance statistic and calibration charts in the remaining 30% of records. Features importance was computed using the SHAP method. **Results:** We included 13,369 patients, overall. The Area Under the ROC Curve (AUC-ROC) of AVF-FM was 0.80 (95% CI 0.79–0.81). Model calibration showed excellent representation of observed failure risk. Variables associated with the greatest impact on risk estimates were previous history of AVF complications, followed by access recirculation and other functional parameters including metrics describing temporal pattern of dialysis dose, blood flow, dynamic venous and arterial pressures. **Conclusions:** The AVF-FM achieved good discrimination and calibration properties by combining routinely collected clinical and sensor data that require no additional effort by healthcare staff. Therefore, it can potentially enable risk-based personalization of AVF surveillance strategies.

**Keywords:** machine learning; artificial intelligence; vascular access surveillance; arteriovenous fistula; end stage kidney disease; dialysis; kidney failure


*3.3.2. Clustering in network layer*

**Protocol CH Election**

Maximum number of messages received from cluster relays is the CH.

230 Contemporary Issues in Wireless Communications

Vehicle nearer to middle of the cluster is the CH.

No reception of a message longer than a particular time units from a CH, then it elects itself as CH.

CH is based on waiting period of Hello messages to neighbors.

No CH

Lane weight, average distance, maximum number of neighbors, and average distance level.

Random after relaying one packet to ordinary node.

HCA [25]

Zaydoun [26]

Xi Zhang [27]

CBMAC [28]

> RCM [29]

TCMAC [30]

CFIVC [31]

**Cluster Formation**

Maximal distance between a CH and CM is two hops.

> RSS > threshold.

Undecided state to CM based on reception of one CH messages.

Geographical area. Vehicles are assigned to different channel pools.

According to speed.

**Table 3.** Comparison between various cluster based MAC protocols.

Not Specified TDMA City

TDMA in CMs-CHs, CSMA/C A CHs-CHs

**MAC Scenario Simulator Pros Cons**

End to End delay reduced.

Support both safety and nonsafety applications.

Reduces datacongestion and supports safety messages.

Minimizes the hidden terminal problem.

Reduced contention and throughput is increased.

Channel utilization, scalability, avoids hidden terminal problem, decreases collisions and packet drops.

> Avoids data collisions.

Overhead and packet loss is increased. Do not consider the direction of movement.

> Not suitable for high traffic. High overhead.

High overhead and complex algorithm. Require two transceivers

Does not select a stable CH during initial CH election.

Low bandwidth utilization in sparse scenarios.

Cannot be used for safety applications, it is delay intolerant.

It neglects any condition that might affect the maximum speed achievable by the vehicle nodes.

SUMO

C++ with graphical interface.

> Simone 2000

I-V Communic ation Based on Traffic Modeling.

TDMA City OMNeT++,

Highway

TDMA Highway A. law el al

Not simulated

Not simulated

TDMA City

Not specified TDMA Highway Ns-3

CDMA, MCSCD MA

In network layer clustering, a virtual network infrastructure must be created through the clustering of vehicles sharing similar characteristics in order to provide scalability. Routing protocols for VANETs mostly based on periodical broadcast messages to reveal their positions and traffic information to neighbors. Nevertheless, deterioration of routing performance is anticipated in urban areas due to high density of vehicles in the network. Basically, excessive broadcast messages as well as broadcast overhead may increase, resulting packet losses (due to collision) and significant routing performance deterioration. Information transfer or dissemination needs multi hop communications. When exchanging information between vehicles, there are network issues that must be addressed, including the hidden terminal problem, high density, high node mobility, and data rate limitations.

In multi-hop data forwarding method, the key problem is selecting the relay/CH for data routing. Most of the relay/CH selection method presented is more suitable for highway scenarios. In a city environment, the widely adopted method is the store-carry-forward scheme. Reactive protocols find routes on-demand. If a node wants to communicate with a node to which it has no route, the routing protocol will try to establish the shortest route between them. Here there is significant delay in determining the route. Proactive (table-driven) protocol, which is based on the exchange of control packets and it is continuously updating the reachability information in the routing table, so routes are immediately available when requested but there is high overhead in maintaining updated periodic routing tables and also maintains the routes that are not going to be used. Hybrid protocol is combination of proactive and reactive protocol. It is also known as cluster based routing. It is a convenient way for developing efficient routing scheme in VANETs. In Table 4 we compare between various cluster based routing protocols proposed in VANETs.

**Table 4.** Comparison between various cluster based routing protocols.


**Abstract**

It is omniscient that pharmacodynamics of a drug is understood as its effect on body by interacting with the structure of targets to either activate or inhibit their function/action. Based on the activity of the drug to the target binding site they have been classified into different types. Physiological, cellular, molecular, biochemical, and toxicological effects individually have a significant role in drug's effect and response. The mechanism of action, dosage and its response, therapeutic index are some of the noteworthy parameters to be considered in drug pharmacodynamics. This chapter comprehends the above-mentioned concepts, their importance in pharmacodynamics of drug, and the impact of recently developed methods like genome-wide or transcriptome-wide sequencing, chronopharmacodynamics, systems biology, pharmacometabolomics, etc., in different stages of drug discovery process, and how the digitization of therapeutics and healthcare direct the path to personalized medicine. The integration of bioinformatics, systems biology, and big data related approaches like ML & AI with the pharmacological (PK/PD) study highly benefits the patients' therapeutics.

**Keywords:** drug response, pharmacodynamic parameters, integrated approaches, pharmacology, digital therapeutics


**Acknowledgements**

**Figure 8.** Time histories of the control currents of the electromagnetic levitation system using Fe of Eq. (13), which are

**Figure 9.** Time histories of the Euclidean norm of Fe of Eq. (13), which are obtained by the experiment.

obtained by the experiment.

36 Bearing Technology

The author would like to thank the Satellite Technology Research Center at the Korea Advanced Institute of Science and Technology for its support to develop the electromagnetic levitation system.


**2.1. Definition**

Obesity is an important pediatric public health problem associated with risk of complications in childhood and increased morbidity and mortality throughout life. Overweight and obesity predispose people to noncommunicable diseases such as heart disease, diabetes mellitus, musculoskeletal and psychological disorders and certain types of cancer [1].

Without intervention, obese infants and young children will likely continue to be obese during childhood, adolescence and adulthood [1–3].

The methodological problem of inconsistency between criteria of childhood obesity classification is a major obstacle in studying global trends for younger age group. The body mass index [BMI: weight (kg)/height (m)2 ] is the parameter used for the screening of overweight and obesity in childhood because it is easy to determine, it tends to correlate well with body fat, and it has been widely used in adults to define obesity. It decreases until the period called "adiposity rebound" when body fat is at the lowest level (between 3 and 7 years) and after then BMI increases again until the adulthood [4, 5].

The child's BMI must be plotted on nationally recommended BMI—for age charts. The classification of overweight and obesity varies among guidelines, such as those from Centre for Disease Control (CDC), International Obesity Task Force (IOTF) and World Health Organization (WHO).

For example, in UK (IOTF BMI values) the cut off points for and are the BMI >91st and >98th percentile, respectively.

The definition of overweight and obesity using BMI percentiles in the USA: children aged 2 years and older with a BMI between the 85th and 95th percentile is overweight, and those with a BMI greater than the 95th percentile for a specific age and sex subgroup are obese [4–6].

According to WHO, for children aged between 5 and 19 years, overweight is >2 standard deviations and obesity is defined as a BMI-for-age >1 standard deviation, above the WHO growth reference median [1].

The IOTF BMI values represent standard international references that allow the screening of adiposity in children and adolescents worldwide under the same criterion, without variations depending on geographic, social and secular trends [5].

#### **2.2. Epidemiological data**

Currently, the prevalence of obesity among children and adolescents and related complications is considered one of the most important nutritional problem globally. The obesity epidemic among children is the result of excess energy intake and inadequate energy expenditure [2]. The prevalence of childhood overweight and obesity has increased worldwide in recent decades, and the numbers of those affected continue to rise at an alarming rate [6].

In recent years, the epidemiology of overweight and obesity is well described in many European countries and the data showed the increasing trends in the prevalence of childhood obesity. The current prevalence of childhood obesity is ten times higher than it was in the 1970s [5].

**2. Nosologic framework of obesity in children and adolescent**

musculoskeletal and psychological disorders and certain types of cancer [1].

ing childhood, adolescence and adulthood [1–3].

then BMI increases again until the adulthood [4, 5].

depending on geographic, social and secular trends [5].

index [BMI: weight (kg)/height (m)2

98 Adiposity - Epidemiology and Treatment Modalities

Organization (WHO).

percentile, respectively.

growth reference median [1].

**2.2. Epidemiological data**

obese [4–6].

Obesity is an important pediatric public health problem associated with risk of complications in childhood and increased morbidity and mortality throughout life. Overweight and obesity predispose people to noncommunicable diseases such as heart disease, diabetes mellitus,

Without intervention, obese infants and young children will likely continue to be obese dur-

The methodological problem of inconsistency between criteria of childhood obesity classification is a major obstacle in studying global trends for younger age group. The body mass

and obesity in childhood because it is easy to determine, it tends to correlate well with body fat, and it has been widely used in adults to define obesity. It decreases until the period called "adiposity rebound" when body fat is at the lowest level (between 3 and 7 years) and after

The child's BMI must be plotted on nationally recommended BMI—for age charts. The classification of overweight and obesity varies among guidelines, such as those from Centre for Disease Control (CDC), International Obesity Task Force (IOTF) and World Health

For example, in UK (IOTF BMI values) the cut off points for and are the BMI >91st and >98th

The definition of overweight and obesity using BMI percentiles in the USA: children aged 2 years and older with a BMI between the 85th and 95th percentile is overweight, and those with a BMI greater than the 95th percentile for a specific age and sex subgroup are

According to WHO, for children aged between 5 and 19 years, overweight is >2 standard deviations and obesity is defined as a BMI-for-age >1 standard deviation, above the WHO

The IOTF BMI values represent standard international references that allow the screening of adiposity in children and adolescents worldwide under the same criterion, without variations

Currently, the prevalence of obesity among children and adolescents and related complications is considered one of the most important nutritional problem globally. The obesity epidemic among children is the result of excess energy intake and inadequate energy expenditure [2]. The prevalence of childhood overweight and obesity has increased worldwide in recent decades, and the numbers of those affected continue to rise at an alarming rate [6].

] is the parameter used for the screening of overweight

**2.1. Definition**

The incidence of overweight and obesity increased progressively from infancy through adolescence [5, 6]. High prevalence of obesity in 0- to 6-year-old children is warning signs and risk for increased rates of obesity in adolescence and adulthood reported.

North America and some countries in Europe have shown consistent year-on-year increases in prevalence of overweight (20–30%) and obesity (5–15%), although recent surveys indicate that the rising trends are easing, with a plateau in prevalence levels shown since around 2005 [6].

Children's risk of obesity varies by age and sex groups, ethnic/racial groups, socioeconomic status, geographic and rural/urban regions. The key reason for the variations is due to the considerable socioeconomic and lifestyle differences and the differences in differing criteria for obesity and overweight definition [4, 7].

Several countries of Southern Europe appear to be showing high prevalence of childhood obesity (20–35%) in the Italy, Greece, Malta, Portugal and Spain. The highest levels of overweight and obesity were in Southern Italy (30.1 and 33.1% in preschool boys and, respectively, girls) and in various regions of Spain (29.4% in both sexes, increasing to 32.6% among children aged 7- to 10-year old), followed by Greece (19.1 and 23.6% in boys and, respectively, girls) [7–9]. Children and adolescents residing in countries surrounding the Mediterranean Sea show the highest rates ranging from 20 to 40%, too [7]. Studies concerning obesity with regard to its prevalence in Portugal reported a rate of overweight in children under the age of 6 years, 13.6% in boys and 20.4% in girls, and, obesity varied between 6.5% in boys and 6.9%, respectively, in girls [10]. The very high prevalence of childhood obesity in Mediterranean countries could be secondary to lifestyle changes (switching from a healthy Mediterranean diet to a fast food type of diet and lower physical activity levels) [7].

In children and adolescents residing the Scandinavian countries and Central Western European countries, the prevalence of overweight and obesity is far lower (10–20%). Scandinavian countries have the lowest prevalence of obesity in all age groups, except Finland which reported the prevalence of overweight and obesity in school children of 23.6 and 19.1% for boys and, respectively, girls [7, 11]. It is important to note that among preschool children, the highest prevalence rates of overweight and obesity were in Ireland (26 and 29% in boys and, respectively, girls), United Kingdom (24.1 and 21.4% in boys and, respectively, girls). In school children, the prevalence of overweight and obesity has increased to 32.7% and, respectively, 29.2% in 2007 the United Kingdom [7]. In developed countries, an increasing number of studies suggest that children of lower-income families are vulnerable to becoming obese, possibly due to poor dietary habits and limited opportunities for physical activity [7, 12]. In the UK, the prevalence of overweight and obesity in 11- to 12-year-old children was 25%, with higher rates in girls (29%) and students from lower socioeconomic backgrounds (31%), and the highest rates was observed in black girls (38%) [13].

Data from Eastern European countries indicate the prevalence rate is smaller (15%), but rising. In Lithuania, the Russian Federation, Slovakia and Poland, the overweight and obesity prevalence ranges from 8.46 to 15.8% in children aged 6–12 years. It is likely that the huge economic burden and the associated poverty following the political transition in the 1990s may have contributed to the relatively low obesity prevalence in Eastern Europe [7].


*Edited by Hossein Samadi-Boroujeni*

Hydroelectric energy is the most widely used form of renewable energy, accounting for 16 percent of global electricity consumption. This book is primarily based on theoretical and applied results obtained by the authors during a long time of practice devoted to problems in the design and operation of a significant number of hydroelectric power plants in different countries. It was preferred to edit this book with the intention that it may partly serve as a supplementary textbook for students on hydropower plants. The subjects being mentioned comprise all the main components of a hydro power plant, from the upstream end, with the basin for water intake, to the downstream end of the water flow outlet.

ISBN 978-953-51-0164-2

Hydropower - Practice and Application

Photo by cherrybeans / iStock

## Hydropower Practice and Application

*Edited by Hossein Samadi-Boroujeni*


**Author details**

Michael Meisenheimer1 \*, Yury Saenko2 and Elisabeth Eppard3 \*

1 Department of Nuclear Medicine, University Hospital Bonn, Germany

2 S.P. Kapitsa Research Institute of Technology, Ulyanovsk State University, Ulyanovsk, Russia

3 Positronpharma SA, Providencia, Chile

\*Address all correspondence to<EMAIL_ADDRESS>and<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**39**

*Gallium-68: Radiolabeling of Radiopharmaceuticals for PET Imaging - A Lot to Consider*

with advanced pancreatic (panNETs) and gastrointestinal (giNETs) grade 1/2 (G1/G2) neuroendocrine tumors: Results of the international phase II TALENT trial (GETNE 1509). Annals of

[8] Bodei L, Cremonesi M, Grana CM, Fazio N, Iodice S, Baio SM, et al. Peptide receptor radionuclide therapy with 177Lu-DOTATATE: The IEO phase I-II study. European Journal of Nuclear Medicine and Molecular Imaging.

[9] Sorbye H, Welin S, Langer SW, Vestermark LW, Holt N, Osterlund P, et al. Predictive and prognostic factors for treatment and survival in 305 patients with advanced gastrointestinal neuroendocrine carcinoma (WHO G3): The NORDIC NEC study. Annals of Oncology. 2013;**24**(1):152-160

[10] Gleason GI. A positron cow. The International Journal of Applied Radiation and Isotopes.

[11] Breeman WAP, Jong M,

[12] Velikyan I, Beyer GJ,

2004;**31**(8):1097-1104

Blois E, Bernard BF, Konijnenberg M, Krenning EP. Radiolabelling DOTApeptides with 68Ga. European Journal of Nuclear Medicine and Molecular Imaging. 2005;**32**(4):478-485

Langström B. Microwave-supported preparation of 68Ga bioconjugates with high specific radioactivity. Bioconjugate

[13] Meyer G-J, Mäcke H, Schuhmacher J, Knapp WH, Hofmann M. 68Ga-labelled DOTA-derivatised peptide ligands. European Journal of Nuclear Medicine and Molecular Imaging.

[14] Lenzo NP, Meyrick D, Turner JH. Review of Gallium-68 PSMA PET/CT

Chemistry. 2004;**15**(3):554-560

1960;**8**(2-3):90-94

Oncology. 2018;**29**(suppl\_8)

2011;**38**(12):2125-2135

*DOI: http://dx.doi.org/10.5772/intechopen.90615*

Herrmann K. 68Gallium- and 90Yttrium−/ 177Lutetium: "Theranostic twins" for diagnosis and treatment of NETs. Annals of Nuclear Medicine.

[2] Strosberg J, Wolin E, Chasen B, Kulke M, Bushnell D, Caplin M, et al. Health-related quality of life in patients with progressive Midgut neuroendocrine tumors treated with 177Lu-Dotatate in the phase III NETTER-1 trial. Journal of Clinical Oncology. 2018;**36**(25):2578-2584

[3] Strosberg J, El-Haddad G, Wolin E, Hendifar A, Yao J, Chasen B, et al. Phase 3 trial of 177Lu-Dotatate for Midgut neuroendocrine tumors. The New England Journal of Medicine.

Molecular Imaging. 2014;**41**(10):1845-1851

[5] Mahajan S, O'Donoghue J, Weber W, Bodei L. Integrating early rapid postpeptide receptor radionuclide therapy quality assurance scan into the outpatient setting. Journal of Nuclear Medicine and Radiation Therapy. 2019;**10**(1):395

Granberg D, Grozinsky-Glasberg S, Ahmadzadehfar H, Grana CM, et al. Peptide receptor radionuclide therapy in gastroenteropancreatic NEN G3: A multicenter cohort study. Endocrine-Related Cancer. 2019;**26**(2):227-239

[7] Capdevila J, Fazio N, Lopez C, Teule A, Valle JW, Tafuto S, et al. 1307OEfficacy of lenvatinib in patients

**References**

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2017;**376**(2):125-135

[4] Paganelli G, Sansovini M, Ambrosetti A, Severi S, Monti M, Scarpi E, et al. 177 Lu-Dota-octreotate radionuclide therapy of advanced gastrointestinal neuroendocrine tumors: Results from a phase II study. European Journal of Nuclear Medicine and

[6] Carlsen EA, Fazio N,

[1] Werner RA, Bluemel C, Allen-Auerbach MS, Higuchi T, *Gallium-68: Radiolabeling of Radiopharmaceuticals for PET Imaging - A Lot to Consider DOI: http://dx.doi.org/10.5772/intechopen.90615*


*4.8. Statistical Analysis*

Data are expressed as mean values ± SEM, indicating *n* as the number of single measurements, and N is the number of independent experiments, which means independent seeding of cells. Statistical analysis was performed using Student's *t*-test between the tricellulin KD clones and their corresponding control (KD 11 and KD 17 versus control 12). In case of angulin-1 KO clones, statistical significance of the difference between means was evaluated using one-way ANOVA and the Tukey and Dunnett adjustment for multiple testing.

MDCK C7 cells: \* *p* ≤ 0.05, \*\* *p* ≤ 0.01, \*\*\* *p* ≤ 0.001 with regard to control 14 and # *p* ≤ 0.05, ## *p* ≤ 0.01, ### *p* ≤ 0.001 with regard to control 18. HT-29/B6 cells: \* *p* ≤ 0.05, \*\* *p* ≤ 0.01, \*\*\* *p* ≤ 0.001 with regard to control 15 and # *p* ≤ 0.05, ## *p* ≤ 0.01, ### *p* ≤ 0.001 with regard to control 29. Statistical analysis was performed using GraphPad Prism 8 software (GraphPad; San Diego, CA, USA). A probability value of *p* ≤ 0.05 was considered statistically significant.


**3. Discussion**

As demonstrated by MIC and MBC test results reported in Table 1, ABR-C and ABR-E displayed distinct antibacterial activities against cariogenic *S. mutans* cells. Not surprisingly, the MIC values of ABR-C and ABR-E were higher than that of benchmark wide-spectrum bactericidal chlorhexidine, which is also highly leachable and does not offer sustained antibacterial activity once leached out. Also as expected, the 8 μg/mL MBC of ABR-C and ABR-E is higher than CHX's MBC of 4 μg/mL, whereas no bactericidal activities were observed at all for SDR Resin and TEGDMA. It has been shown that, for an organic QAS compound, 10~14 carbon atoms for the N-alkyl group are associated with higher antimicrobial activity [43,44]. Another study also showed that imidazolium's N-alkyl's chain length can play a critical role in antitumor activity and cytotoxicity; C-12 was found exhibiting high antitumor activity against ~60 tumor cell lines as well as low cytotoxicity in most cases. Longer chain length could improve antitumor potency but also increase imidazolium's cytotoxicity [45]. As demonstrated in their chemical structures in Schemes 3 and 4, respectively, both ABR-C and ABR-E have a 12-carbon atom chain length on their N-alkyl group, which helps in explaining their identical MIC and MBC values.

The dentin mass loss results (Figure 1) indicate that the ABR resins, even at low concentrations, are effective against matrix metalloproteinases (MMPs) for minimizing the collagen degradation. MMPs belong to a larger group of proteases known as the metzincin superfamily. These collagenases are capable of degrading triple-helical fibrillary collagens, such as those in dentin, into distinctive fragments. More specifically, certain MMPs are considered to contribute to the gradual degradation of collagen fibrils in hybrid layers established during dentin bonding. A wide range of MMPs, including MMP-2, MMP-8, MMP-9, and MMP-20, have been detected in the human dentin matrix [46]. It is well reported that CHX has broad anti-MMP activity in addition to antimicrobial capability. However, the long-term *in vivo* anti-MMP activity of CHX may not be as effective, which has been attributed to possible leaching out of the CHX [47,48]. It has also been reported that cationic quaternary ammonium methacrylates may exhibit dentin MMP inhibition comparable with that of CHX but that higher concentrations were required [49].

The synthetic strategy in this investigation focused on covalently linking antibacterial compounds that contain functional groups with strong antibacterial activities to a variety of backbones and polymerizable groups compatible with conventional dental resin systems. The antibacterial capability of the active compound could be either enhanced or reduced by polymerization. This depends on how the compound eradicates bacteria, either by disrupting bacterial membrane or via depleting the bacterial food supply. In order for an antibacterial resin to be a viable option for industrial-scale production and application, there are several essential requirements that need to be fulfilled: (1) synthesis of ABR should be straightforward and not cost-prohibitive; ideally, well-established synthetic routes are preferred; (2) ABR should have good storage stability (sufficient shelf life); (3) end products that contain ABR should be able to maintain their antibacterial activities through recurrent bacterial challenges; (4) ideally, the antibacterial effect can be achieved with relatively small dosing and minimum bacterial resistance in the target pathogenic microorganisms; (5) no drastic compromises to the other vital properties should be introduced by ABR. As shown in Table 2, even at up to 12 wt % loading level, there are no significant decreases in flexural strength or flexural modulus with the incorporation of the

imidazole-based polymerizable antibacterial monomer ABR-C, as compared to control. The flexural strength of the resin mixture with 16 wt % antibacterial monomer showed lower flexural strength, but flexural modulus still retained 84% value as compared to control.

During this investigation, it was found that a group of polymethacrylate resins containing at least one imidazole moiety could be readily prepared via appropriate hybrid methacrylate–acrylate resins or polyacrylate resins with proper control of the conversion of the imidazole addition. This is an e ffective approach to incorporating an imidazole moiety into a polymerizable resin as novel acid-free functional resins. Moreover, such imidazole-containing polymerizable resins may be further chemically modified by reacting with a variety of halogenated alkyls to form polymerizable resins with ionic moiety of imidazolium, which results in a unique class of polymerizable ionic liquid resins.

Su fficient mechanical properties of the orthodontic bonding cement are important as the bending force and torque during teeth straightening and aligning could be quite significant. There is a slight reduction of flexural strength with a higher loading amount of ABR-C; however, flexural modulus can be maintained with up to 3 wt % of ABR-C loading (Table 3). A similar trend was also observed for compressive strength. Ambient light sensitivity (ALS) is another important property for light curable orthodontic cement or adhesive, as adequate ALS is needed for the bracket to be carefully placed and aligned at the correct position and angle, before it is light cured. As also exhibited in Table 3, the ALS values of ABR-C-containing orthodontic cements are all at 2 min or higher, which compared well with commercially available orthodontic cements, as shown in Figure 3.

Orthodontic cement with the capability to prevent the development of WSLs without compromising enamel bond strength would be desirable. Orthodontic treatments last an average of two to three years, during which time orthodontic cement must be capable of bonding to the enamel with high bond strength in order to resist masticatory loads. As demonstrated in Table 3, for experimental orthodontic cements incorporating 1–4 wt % ABR-C, there is no drastic compromise to the SBS to enamel except for 3 wt % ABR-C. More importantly, their SBS values are all comparable to those of the commercially available orthodontic cements products (Figure 2), with mean SBS ranging from 20.1 MPa to 36.0 MPa. However, this bond strength to enamel should not be too high either, to prevent damages to the enamel while removing the bracket.

The strong e ffectiveness in eradicating bacteria for the imidazolium-based polymerizable resins was further demonstrated by the formulated experimental orthodontic cements. As exhibited in Table 4, even at a low-level loading (1 wt %) of such imidazolium-based polymerizable monomer, a reduction of over 2 logs of microorganisms can be achieved by ABR-C. When the loading level of ABR-C was increased from 2 wt % to 4 wt %, reductions of around 5 logs or higher were observed. Moreover, with optimized compositions, not only can a highly e ffective antibacterial capability be achieved, but balanced mechanical properties can also be maintained (Table 3). The potent antibacterial property of this novel polymerizable imidazolium resin o ffers another crucial benefit—no severe cytotoxicity was introduced [50]. Conventional QAS-based polymerizable resins, on the other hand, could be less effective and a high dose loading (up to 30 wt %) is needed, which frequently leads to significant drops in mechanical properties and elevated cytotoxicity [51,52].

E ffective antimicrobial agents are expected to regulate the oral biofilm at levels compatible with good oral health while not sacrificing the beneficial properties of the resident oral microflora. Compounds comprising imidazolium moieties have exhibited various antibacterial, antioxidant, and antifungal properties; imidazolium salts' overall mechanism of antibacterial function is similar to that of QAS—mainly by disturbing the planktonic cell membrane [52]. Nonetheless, comprehensive studies by Koo et al. have shown that ABR-MC (ABR-modified composite) impaired biofilm initiation by disrupting bacterial accumulation, cell colonization, and subsequent biofilm development, if left unintervened [50]. The anti-biofilm properties of ABR-MC were assessed using an EPS-matrix producing *S. mutans* in an experimental biofilm model. Using high-resolution confocal fluorescence imaging and biophysical methods, they observed severely reduced biomass, remarkable disruption of bacterial accumulation, and defective 3D matrix structure on the surface of ABR-MC. Mechanism-wise, it was speculated that the distinct difference in the basicity between N-substitute imidazole (pKaH of 7.20 for 1-methylimidazole) and aliphatic tertiary amine (pKaH of 10.7 for triethylamine) might be the major contributor to the increased polarity and higher potential in its charged conjugated moiety (imidazolium). However, the exact mechanism contributing to the much more pronounced bactericidal effects as compared to conventional QAS compounds will require further investigation. Other areas of relevant investigation include the further study of the hydrolytical stability of these antibacterial monomers.

#### **4. Materials and Methods**


**Author details**

Jonathan Glazzard University of Hull, UK

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Introductory Chapter: The Application of Cognitive Science in Supporting Learners with Dyslexia DOI: http://dx.doi.org/10.5772/intechopen.113927*


*2.2. Modeling Results*

Equations from (1) to (5) were solved numerically using an explicit difference scheme and a fixed grid method [22] implemented in Delphi 7.0.

The physical properties for an A356 alloy (Al-7% Si), listed in Table 1, were used in solving the problem.

**Table 1.** Physical quantities used in calculation.

The ranges of process parameters in the calculation were as follows:

The calculation showed that the temperature profile weakly depends on vibration within the given range of amplitude and frequency. Figure 2a shows the temperature in its center *T*(0,*t*) without and with vibration at a frequency of 50 and 80 Hz. The movement of the solidification front *rs*1 (that is, corresponding to the liquidus temperature *Tm*1) is nonlinear (Figure 2b).

**Figure 2.** (**a**) Time dependence of the temperature in the center of liquid metal volume for different conditions: 0—without vibration, 50—vibration of *f* = 50 Hz, 80–vibration of *f* = 80 Hz; *Ts* = 630 K, *T*0 = 900 K.; (**b**) Time dependence of the movement of the solidification front from the start point *tcol* for two thermal modes: 1—*Ts* = 630 K, *T*0 = 900 K, and 2—*Ts* = 430 K, *T*0 = 1050 K under *A* = 0.5 mm, *f* = 50 Hz.

First of all, the thermal solution allows one to define the kinetics of the process. Figure 2a shows the time-dependence of the temperature in the center of the melt volume *T*(0,*t*). Vibration accelerates the process of solidification: the "plateau" on the temperature profile corresponding to the solidification becomes shorter with the vibration.

The calculation shows that the duration of alloy solidification as well as the cooling time (combined cooling to the temperature of liquidus and then to the solidus), depends on the initial temperature difference between the melt and the chill mold, and is less dependent on frequency (Figure 3a). The solidification time slightly shortens with the increasing frequency (Figure 3b). As one can see, the solidification time is short in all cases, a few seconds. However, it is during this brief period of time that the vibration has an effect on the solidification and structure formation.

**Figure 3.** Dependencies of the cooling time (**a**) and the solidification time (**b**) on the vibration frequency: 1—*Ts* = 630 K, *T*0 = 900 K, and 2—*Ts* = 430 K, *T*0 = 1050 K; *A* = 0.5 mm.

Figure 4 shows the dependence of the cooling time *tcol* on the initial mold temperature, as well as the dependence of the solidification time on the initial melt temperature. The higher the initial temperature of the metal and that of the chill mold, the more time needed for cooling; which is the expected result.

**Figure 4.** Dependence of (**a**) the cooling time before solidification and (**b**) the solidification time on the initial temperature of the chill mold *Ts* for different starting melt temperatures *T*0.

When analyzing the stress amplitude imposed on the semi-solid alloys, one should note that the strength of semi-solid alloys can be significantly lower than that of the solid alloy, i.e., the tensile strength of an A356 alloy decreases from 157 MPa in the solid state [27] to 4.98 MPa at 860 K and to ~ 0.01 MPa at 880 K [24]. Nevertheless, a certain critical amplitude of mechanical stress *σmin* that is higher than the tensile strength of the semi-solid alloy, is required to effect the fracture of growing crystals, and as a consequence, the refinement of the crystalline grains in the casting. Not only the value of *σmin* is important but also the operating time of these stresses during the alloy solidification (number of oscillations during solidification). A combination of those can be characterized by the value *Zσ* (Equation (6)).

Figure 5a shows the dependence of the specific stress integral *Zσ* on the vibration frequency for the two following conditions: *T*s = 630 K, *T*0 = 900 K and *T*s = 430 K, *T*0 = 1050 K. The calculation demonstrates that the effectiveness of the vibration grows nonlinearly with increasing the vibration frequency and saturates at a certain frequency. This effect can be explained by the reduction of the solidification time during which the vibration affects the growing crystals (see Figure 3b). It can be assumed that the fracture of growing crystals is possible only under conditions when a relative value *Z* exceeds a certain critical value: Z = *Z*σ/*Zs* = *Z*σ/*c*1ρ1 > *Zcr*.

The dependence of this integral stress characteristic on amplitude is, however, linear and the values become substantial at the frequencies above 50 Hz (Figure 5b).

**Figure 5.** (**a**) The dependence of the specific stress integral on the vibration frequency for two thermal conditions: 1—*Ts* = 630 K, *T*0 = 900 K, and 2—*Ts* = 430 K, *T*0 = 1050 K; *A* = 0.5 mm. (**b**) The dependence of the specific stress integral on the vibration amplitude for the four values of frequency.

Thus, according to the proposed approach, the vibration of liquid and solidifying metal causes the following effects:

Considering that the vibration stresses operate on growing crystals in a particular short period of solidification, the time integral characteristic of mechanical stresses can be suggested as a measure of the effectiveness of vibration. The higher this value, the greater the effect of vibration stress on crystals. The integral characteristic of mechanical stresses increases linearly with rising amplitude but grows nonlinearly with rising vibration frequency. It is necessary to consider the time and mechanical conditions under vibration treatment of an alloy during solidification as: