*Article* **Optimization of a Calcium-Based Treatment Method for Jellyfish to Design Food for the Future**

**Francesca Anna Ramires 1,†, Stefania De Domenico 1,2,†, Danilo Migoni 2, Francesco Paolo Fanizzi 2, Dror L. Angel 3, Rasa Slizyte 4, Katja Klun 5, Gianluca Bleve 1,\* and Antonella Leone 1,6**

**Abstract:** Edible jellyfish are a traditional Southeast Asian food, usually prepared as a rehydrated product using a salt and alum mixture, whereas they are uncommon in Western Countries and considered as a novel food in Europe. Here, a recently developed, new approach for jellyfish processing and stabilization with calcium salt brining was upgraded by modifying the pre-treatment step of freshly caught jellyfish and successfully applied to several edible species. Treated jellyfish obtained by the application of the optimized version of this method respected both quality and safety parameters set by EU law, including no pathogenic microorganisms, absence or negligible levels of histamine and of total volatile basic nitrogen, no heavy metals; and the total bacterial, yeast, and mold counts were either negligible or undetectable. Jellyfish treated by the presented method exhibited unique protein content, amino acid and fatty acid profiles, antioxidant activity, and texture. The optimized method, initially set up on *Rhiszostoma pulmo*, was also successfully applied to other edible jellyfish species (such as *Cotylorhiza tuberculata*, *Phyllorhiza punctata*, and *Rhopilema nomadica*) present in the Mediterranean Sea. This study discloses an innovative process for the preparation of jellyfish-based food products for potential future distribution in Europe.

**Keywords:** jellyfish; novel food; safety; quality; nutritional traits; organic calcium salts


**1. Introduction**

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Waves. Phys. Plasmas 2006; 13, 052303/1-7

94, 175003/1-4

282 Computational and Numerical Simulations

Rev. Lett. 2009; 102, 185003/1-4

042304

Mean field dynamics have been extensively applied for organizing neural networks in the field of computational neuroscience, since Hopfield pioneered collective decisions of interconnected processing elements for combinatorial optimization [1–6] and memory association [7, 8]. Both nonlinear transfer functions and synapses in a Hopfield neural network are a subsequence of mean field dynamics that characterize the mean configuration of a large scaled physical system at thermal equilibrium in the field of statistical mechanism. In the past decades, the mean field dynamics has been extensively applied for deriving interactive neural dynamics of solving complex tasks, such as combinatorial optimization [4, 6, 9], self-organization [10], clustering analysis [11][12], independent component analysis [13], and regression [14][15].

Mean field equations characterize feasible configurations for problem solving. Let *si* ∈ {−1, 1} denote a binary random variable for modeling a stochastic two-alternative processing element and **s** = {*si*}*i* represent a configuration for problem solving. The feasibility of **s** to the attacked problem is inversely quantified by an energy function *E*(**s**). Minimizing *E*(**s**) with respect to **s** means to seek the optimal solution. Under the Boltzmann assumption, the joint probability of all *si* is proportional to *exp*(−*βE*(**s**)), where *β* denotes the inverse of a temperature-like parameter. As in previous works [4][5][6], the Kullback-Leibler divergence between the product of marginal probabilities and the joint probability of all *si* induces a tractable free energy function *ψ* that depends on the expectation of *si*, denoted by �*si*�, for all *i*.

The following mean field dynamics exactly characterize the saddle point of a typical tractable free energy function,

$$\mu\_{l} = -\frac{\partial E(\langle \mathbf{s} \rangle)}{\partial \,\langle s\_{l} \rangle} \tag{1}$$

$$
\langle s\_i \rangle = f(u\_i) \equiv \tanh(\beta u\_i) \tag{2}
$$

©2012 Wu, Ban and Wu, licensee InTech. This is an open access chapter distributed under the terms of the

where *ui* denotes an external field, *f* ≡ tanh is a sigmoid-like transfer function and �*si*� denotes the mean activation. In previous works [4][6], *E* is quadratic and *ui* measures a weight sum of activations other than �*si*�, such as

$$\mu\_{i} = \sum\_{j \neq i} w\_{ij} \left< s\_{j} \right> + c\_{i} \tag{3}$$

10.5772/57217

285

http://dx.doi.org/10.5772/57217

Equations (4)-(6) describe synchronous data transmissions and parallel signal processes, by

Tracking Mean Field Dynamics by Synchronous Computations of Recurrent Multilayer Perceptrons

A recurrent network of multilayer perceptrons is further equipped with circular connections from the output to input layers. By feedback circular connections, the current output becomes the network input at the upcoming time step. Let *R* be an identity matrix. Setting **x** to **y***n* and **y** to **y***n*+1 leads to the following recursive function realized by recurrent multilayer

Since perceptrons and adalines perform post-nonlinear projection, the organized multilayer neural network realizes a high dimensional nonlinear mapping from the input domain to the output range, which has been shown significant for solving complex tasks against traditional linear systems. Recurrent multilayer perceptrons perform parallel and synchronous computations for realizing the behavior of MIMO (multiple input multiple output) recurrent relation or characterizing nonlinear autoregression of time series. Recurrent multilayer perceptrons have been applied for nonlinear autoregressive modeling of chaotic time series

This work applies recurrent multilayer perceptrons for tracking mean field dynamics by synchronous and parallel computations. A systematic approach is proposed for translating mean field dynamics (1) and (2) to the nonlinear recursive function (7) such that recurrent multilayer perceptrons can track the saddle point of *ψ* by parallel and synchronous computations. The strategy is to introduce time delays and auxiliary variables for expanding local memories of storing individual states, and translate loosely coupled or densely coupled first order mean field equations to a system of post-nonlinear recursive functions, which can be evaluated directly by iterative synchronous computations of recurrent multilayer

Section 2 applies parallel and synchronous computations of recurrent multilayer perceptrons for tracking mean field dynamics. Asynchronous updating of tracking linear dynamics and mean field dynamics is translated to equivalent synchronous updating. Section 3 applies the transformation to derive synchronous updating of tracking mean field dynamics for solving graph bisection problem and verifies the proposed approach by numerical simulations. Section 4 further presents a hybrid of asynchronous and synchronous processes for tracking

By asynchronous updating at each time step numerical simulations select one processing element and refine its mean activation under fixed mean activations of the others. Let *ψi*(�*si*�)

2 log 1 + �*si*�

2 +

1 − �*si*�

2 log 1 − �*si*�

2

, (8)

sparse large scaled mean field dynamics of sparse connectivity for problem solving.

**2. Synchronous computation of tracking mean field dynamics**

1 + �*si*�

**y***n*+1 = *F*(*A***y***n*) (7)

which it only takes three time clocks to translate **x** to **y**.

prediction [19] and financial time series [20].

perceptrons

perceptrons.

denote *ψ* with fixed

*sj*

*ψi*(�*si*�) = *hi* �*si*� + *ci* −

, *j* �= *i*,

where *wij* denotes the synapse that connects neural processing elements *i* and *j*. For fixed *β*, equation (2) defines the transfer function of interconnected processing elements and equation (3) sketches synapses. The realized information processes are distributed and with computational features of fault tolerance and collective decision. All interconnected processing elements in a Hopfield neural network asynchronously operate to seek a stable configuration under an annealing process [6] that carefully scheduling *β* from sufficiently small to large values.

At each intermediate *β*, a stable configuration means a result of minimizing the mean energy function against maximizing the entropy for emulating thermal equilibrium of statistical mechanism. At the end of the annealing process, by equation (2), �*si*� ∈ {−1, 1} and the mean configuration �**s**� is a vector of *N* binary values, well representing a feasible solution for problem solving. Empirical results in previous works [4][6] have extensively shown that the physical-like annealing process guarantees effectiveness and reliability of seeking the global or near global minimum of *E*(**s**) for problem solving. In previous works [15–18], mean field dynamics have been extended for multi-state Potts modeling and applied for unsupervised learning and supervised learning of neural networks toward solving self organization, independent component analysis, function approximation and discriminate analysis.

However from the perspective of numerical simulations, asynchronous operation of interconnected processing elements means one-by-one sequential updating of neural variables. It is more efficient to simulate synchronous and parallel updating of neural variables by vector codes. Multilayer perceptrons or Adalines have been organized for parallel and synchronous processes. Significant computational features include synchronous data transmission and parallel signal processes through multilayer perceptrons. A network of multilayer perceptrons is typically composed of input, hidden, output layers as well as inter-connections among consecutive layers. The input **x** ∈ *Rd* transmits through interconnections to form external fields,

$$h = A\mathbf{x} + \mathbf{c},\tag{4}$$

and the nonlinear transfer function translates *h* to activations of hidden units,

$$\mathbf{v} = F(h) = [f(h\_1), \dots, f(h\_M)]^T,\tag{5}$$

which is multiplied by a matrix of posterior weights, denoted by *R*, to form the network output

$$\mathbf{y} = R\mathbf{v} \tag{6}$$

Equations (4)-(6) describe synchronous data transmissions and parallel signal processes, by which it only takes three time clocks to translate **x** to **y**.

2 Computational and Numerical Simulations

small to large values.

analysis.

output

interconnections to form external fields,

weight sum of activations other than �*si*�, such as

where *ui* denotes an external field, *f* ≡ tanh is a sigmoid-like transfer function and �*si*� denotes the mean activation. In previous works [4][6], *E* is quadratic and *ui* measures a

where *wij* denotes the synapse that connects neural processing elements *i* and *j*. For fixed *β*, equation (2) defines the transfer function of interconnected processing elements and equation (3) sketches synapses. The realized information processes are distributed and with computational features of fault tolerance and collective decision. All interconnected processing elements in a Hopfield neural network asynchronously operate to seek a stable configuration under an annealing process [6] that carefully scheduling *β* from sufficiently

At each intermediate *β*, a stable configuration means a result of minimizing the mean energy function against maximizing the entropy for emulating thermal equilibrium of statistical mechanism. At the end of the annealing process, by equation (2), �*si*� ∈ {−1, 1} and the mean configuration �**s**� is a vector of *N* binary values, well representing a feasible solution for problem solving. Empirical results in previous works [4][6] have extensively shown that the physical-like annealing process guarantees effectiveness and reliability of seeking the global or near global minimum of *E*(**s**) for problem solving. In previous works [15–18], mean field dynamics have been extended for multi-state Potts modeling and applied for unsupervised learning and supervised learning of neural networks toward solving self organization, independent component analysis, function approximation and discriminate

However from the perspective of numerical simulations, asynchronous operation of interconnected processing elements means one-by-one sequential updating of neural variables. It is more efficient to simulate synchronous and parallel updating of neural variables by vector codes. Multilayer perceptrons or Adalines have been organized for parallel and synchronous processes. Significant computational features include synchronous data transmission and parallel signal processes through multilayer perceptrons. A network of multilayer perceptrons is typically composed of input, hidden, output layers as well as inter-connections among consecutive layers. The input **x** ∈ *Rd* transmits through

which is multiplied by a matrix of posterior weights, denoted by *R*, to form the network

and the nonlinear transfer function translates *h* to activations of hidden units,

+ *ci* (3)

*h* = *A***x** + **c**, (4)

**y** = *R***v** (6)

**v** = *F*(*h*)=[ *f*(*h*1), ..., *f*(*hM*)]*T*, (5)

*ui* = ∑ *j*�=*i wij sj*  A recurrent network of multilayer perceptrons is further equipped with circular connections from the output to input layers. By feedback circular connections, the current output becomes the network input at the upcoming time step. Let *R* be an identity matrix. Setting **x** to **y***n* and **y** to **y***n*+1 leads to the following recursive function realized by recurrent multilayer perceptrons

$$\mathbf{y}\_{n+1} = F(A\mathbf{y}\_n) \tag{7}$$

Since perceptrons and adalines perform post-nonlinear projection, the organized multilayer neural network realizes a high dimensional nonlinear mapping from the input domain to the output range, which has been shown significant for solving complex tasks against traditional linear systems. Recurrent multilayer perceptrons perform parallel and synchronous computations for realizing the behavior of MIMO (multiple input multiple output) recurrent relation or characterizing nonlinear autoregression of time series. Recurrent multilayer perceptrons have been applied for nonlinear autoregressive modeling of chaotic time series prediction [19] and financial time series [20].

This work applies recurrent multilayer perceptrons for tracking mean field dynamics by synchronous and parallel computations. A systematic approach is proposed for translating mean field dynamics (1) and (2) to the nonlinear recursive function (7) such that recurrent multilayer perceptrons can track the saddle point of *ψ* by parallel and synchronous computations. The strategy is to introduce time delays and auxiliary variables for expanding local memories of storing individual states, and translate loosely coupled or densely coupled first order mean field equations to a system of post-nonlinear recursive functions, which can be evaluated directly by iterative synchronous computations of recurrent multilayer perceptrons.

Section 2 applies parallel and synchronous computations of recurrent multilayer perceptrons for tracking mean field dynamics. Asynchronous updating of tracking linear dynamics and mean field dynamics is translated to equivalent synchronous updating. Section 3 applies the transformation to derive synchronous updating of tracking mean field dynamics for solving graph bisection problem and verifies the proposed approach by numerical simulations. Section 4 further presents a hybrid of asynchronous and synchronous processes for tracking sparse large scaled mean field dynamics of sparse connectivity for problem solving.


**4. Retrofitting toward a nearly zero energy future**

In retrofitting a building, one of the critical aspects to consider is the material properties of the existing building and the carbon content typically residing therein.

#### *Energy-Efficient Retrofit Measures to Achieve Nearly Zero Energy Buildings DOI: http://dx.doi.org/10.5772/intechopen.101845*

The London Energy Transformation Initiative (LETI) proposed an embodied carbon budget of 600kgCO2e/m2 for us to attain our carbon reduction goals [22]. To understand the feasibility of achieving this low figure, one must comprehend the total embodied energy typically present in an old building. Aecom, in a web article titled "The carbon and business case for choosing refurbishment over new build," breaks down the embodied carbon within various components of typical residential buildings: Frame 24%; substructure 19.6%; upper floors (14.9%); building services (13.4%); internal finishes (12.4%); external walls; windows and doors (8.8%); roof (5%); fitting and furnishings (1.2%); internal walls and doors (0.6%). The elements typically associated with the highest embodied carbon (substructure, frame, upper floor, and roof) are candidates that qualify for retrofitting to save on emissions produced during the breaking down of an old building and re-constructing these buildings elements while building anew.

To holistically retrofit existing buildings for enabling the transition toward a nearly zero energy building, three main scopes encompassing passive and active strategies should thus be considered:

To explain these three strategies, the chapter, apart from providing theoretical advice, also elaborates upon the results of a simulated case study—an educational building in Iran. An initial comfort analysis in terms of visual and thermal condition and energy use of this existing building provides insights on the required improvements and thus informs retrofitting strategies. The elaborated project deploys the three-stage retrofit process on an educational building in Tehran (35.6892° N, 51.3890° E), Iran, in a cold semiarid climatic condition (Köppen climate classification: BSk). The process adopted by the authors incorporated radiance and energy plus simulation engines. According to the weather data for a typical year in this area, January is the coldest month, and August represents the hottest time of the year, each with an average monthly temperature of 3.89°C and 30.07°C. The site also enjoys a high level of solar exposure and experiences cloudy sky conditions only 15% of the time.

Situating a to-be retrofitted building within its environmental context is an ideal strategy for understanding the reasons behind its current energy performance. To strive toward an energy-efficient status for an existing building, both interior and exterior aspects are equally crucial to be considered. Visual and thermal comfort components can be primarily linked with the urban positioning of the building itself and imply conducting on-site solar radiation analysis for extracting the degree of solar exposure received by the building's external facades. In addition to this, mapping the demand for lighting and thermal energy of the interior programs of the building is vital. This step aids in making informed decisions to re-position or augment a building's program to take the best advantage of the building's solar exposure while naturally reducing the amount of energy required to heat or cool the building's interiors.

For instance, in our educational Building case study, solar radiation analysis (**Figure 2**) revealed that the Southern zones witnessing the highest solar radiation

**Figure 2.** *Solar radiation analysis on building envelope.*

constituted of primary programs and were induced to a high level of daylight and solar heat gain. On the contrary, northern zones were the coldest spaces with a pleasant daylight quality without experiencing visual discomfort caused by glare. The Eastern and Western zones were typically dedicated to circulation and service areas. Daylighting and thermal requirement-based zoning and categorization of the building's program are also conducted to determine the ideal spatial distribution of the program within the building (**Figure 3**).

The other important aspect of understanding visual comfort is calculating daylight quality to evaluate illuminance levels and glare probability and subsequently calculate thermal conditions to evaluate the total amount of discomfort hours within the primary programs of a building. It is vital to educate and to understand the importance of using the sun for solar tempering. Working with rather than against natural solar movement and exposure also aids in achieving energy savings otherwise required for heating purposes, and appropriately shading also aids in reducing cooling requirements. A strategic manner of avoiding added costs and energy expenditure for added thermal mass required for maximizing passive solar heating can thus be achieved. Such concerns are primarily best addressed during the design phase of the proposed retrofit.

In the case of the studied institution building, the south-facing spaces tend to receive excessive sunlight and suffer excessive visual discomfort (ASE > 10%, LEED 0 point). Therefore, the use of optimum shadings is suggested in the retrofit process. Despite this, the northern zone achieves all 3 points of the LEED rating system, which indicates that both sufficient daylight level (sDA > 75%) and visual comfort

**Figure 3.** *Spatial zoning based on the solar geometry.*

*Energy-Efficient Retrofit Measures to Achieve Nearly Zero Energy Buildings DOI: http://dx.doi.org/10.5772/intechopen.101845*

**Figure 4.** *Visual comfort (daylight distribution and glare) assessment.*

(ASE < 10%) is achieved in these zones. Therefore, it is highly suggested to consider solar geometry in the renovation process to establish the feasibility of removing or adding the interior partitions. An overall analysis of daylight distribution on each floor (**Figure 4**) can elaborate on the optimal positioning of the interior program of a building in relation to solar radiation. Such strategic thinking and informed decision-making pertaining to program positioning before beginning the retrofitting process can thus ensure reducing the total energy consumption of a building considerably.

Thermal comfort analysis by assessing the average monthly temperature within an existing building's interior spaces can further help designers to understand overcooling or overheating scenarios throughout the year. Similarly, an annual analysis of discomfort hours also provides information on thermal conditions on a dynamic scale and can show critical thermal condition levels of interior space. Thermal imaging using an infrared camera can also be deployed for measuring on-site thermal conditions in individual rooms. Typically, such analysis can also be categorized under an energy audit of an existing building. For the case of the educational building understudy, the annual discomfort hours were calculated as 988.73 hours (**Figure 5**) and were associated with the average monthly temperature and the percentage of occupancy time that the hours corresponded with. The design phase of the retrofit being a calculated experimental phase also renders itself for making design decisions pertaining to elements such as atriums, window opening sizes, etc., while keeping in mind the window to wall ratio. Such additions, typically aimed at improving natural ventilation, can dramatically improve inside temperature conditions, thus impacting the total energy required for heating, cooling, and artificial ventilation. In the case of the educational building, the insertion of a central atrium combined with interior windows with a window to wall ratio of 20% was experimented with as a designed addition. A computational fluid dynamics (CFD) simulation analysis on a typical spring day (without an HVAC system operational) was able to provide a good overview of well-ventilated zones vs. zones which needed further improvement strategies such as supply vents etc., (**Figure 6**). Such initial analyses of the indoor environmental condition thus offer a basis for taking calculated decisions of the required retrofit strategies on a case-by-case basis.

#### **Figure 6.**

*Ventilation (velocity and temperature) assessment in the central atrium.*

Tangible aspects connected with thermal comfort can be further categorized into lighting, sealing, insulation, and window replacement components. Lighting inside a building is equally crucial. Older buildings typically make use of fluorescent lighting and light bulbs. These tend to consume much more energy than contemporary energy-efficient CFL or LED light bulbs that last longer and are mercury-free. Retrofitting should thus ideally involve replacing existing fluorescent lighting systems with LEDs equipped with linear controllers. This simple change can almost halve the energy used for lighting purposes. Using motion sensors in areas where lights are left on often also allows energy to be saved. For the case of the educational building, this small change in lighting coupled with a daylight sensor for controlling the intensity of lighting in real time can halve the total energy consumed (**Figure 7**).

Sealing the building envelope is another step that is a highly efficient and costeffective measure that can be deployed during the retrofitting phase for any building. Saving valuable energy required for heating and cooling and improving comfort,

*Energy-Efficient Retrofit Measures to Achieve Nearly Zero Energy Buildings DOI: http://dx.doi.org/10.5772/intechopen.101845*

**Figure 7.**

*The energy use of reference (fluorescent) VS. optimized lighting system (LED with linear control).*

reducing noise, and improving air quality are all direct impacts of sealing the building envelope, resulting in nearly zero energy targets. Often a blower door test can be conducted to evaluate the air leakage during air change per hour. Air change here implies the volume of air that equals the house volume exchanged with the outside air [23]. A blower door can establish a negative 50-pascal house pressure. Existing homes in need of retrofitting can often leak air at the rate of 15 air changes per hour (15 ACH50). Sealing the external and internal surfaces of a building can aid in bringing this level of leakage down between a range of 2ACH50 (airtightness standard for a cost-effective zero energy home)—0.7 ACH50 (airtightness standard for a passive house). Setting an airtightness goal for retrofitting projects can thus prove to be a wise decision for cutting down on energy consumption by optimizing the building envelope.

Building insulation should be considered as a fundamental component of any retrofit project. Different surfaces, such as walls, floors, and ceilings, require different types and thicknesses of insulating materials that are contextually derived based on climatic conditions and solar exposure. The R-value, or in other words, the ability of a material to resist the flow of heat, is important while choosing adequate insulation and is highly dependent on the kind of material used for insulation rather than the thickness of the material used. The climatic context of the region within which the retrofitting needs to be undertaken thus plays a significant role in determining the requisite R-value of the chosen insulation type and thickness. The Zero Energy Project report [24] outlines practical ways in which high-performance walls (exterior rigid insulation; single plate, double stud walls; double plate walls), highinsulated ceilings (blow insulation onto flat ceilings; insulating cathedral ceilings; exterior rigid insulation), and high insulated-floors (insulated slabs; insulated basements; crawl space), can aid in reducing energy loads by means of the application of appropriate insulation.

Similarly, window replacement and door replacements can play an essential role in transitioning to a nearly zero energy building. Organizations such as the National Fenestration Rating Council have contributed heavily toward establishing rating systems of window and door performance measurements in the form of labels affixed to off-the-shelf window and door units [25]. This process aids in the simplification of retrofitting wherein the everyday citizen can make informed decisions pertaining to the efficiency of these quintessential components of a building. Like the R-value of insulation, a U factor is of prime importance as it indicates the efficiency of a window

**Figure 8.** *Construction material optimization.*

as regards heat escaping from the interior of a building. For visual comfort purposes, the visible transmittance value is also associated with window ratings. It is responsible for measuring the effectiveness of a window to light the interiors of space with daylight. For doors, the solar heat gain coefficient value that demarcates the door's resistance toward unwanted heat gain and the air leakage value that indicates the entry of external air through the door are vital measures specified by such councils.

For the case of the studied educational building, to establish a lower heat transfer threshold, the application of interior insulation (0.10 m air gap +0.15 m wood wool), replacement of windows with highly sealed windows with a low U value and coated with efficiency-enhancing coatings (Dbl LOE Elec Abs Bleached 6 mm/13 mm Arg), provision of interior window shading (shade roll-medium opaque) and exterior localized shading elements (2 meters overhang), were explicitly deployed for enhancing the efficiency of south facing spaces (**Figure 8**).

The energy consumption component for a building retrofit process involves active strategies. HVAC systems are omnipresent in the majority of homes globally and how to reduce the energy required for heating or cooling purposes is of particular importance here. The strategies—visual and thermal comfort enhancements, already contribute to reducing conventional HVAC systems' load. However, apart from these passive measures, selecting appropriate HVAC systems conducive to the climatic context and the proportion of spaces to be conditioned are essential criteria to consider. For instance, for residential properties, air-source heat pumps are highly efficient and can take up the form of mini-split heat pumps for individual rooms or multi-zone installations. Variable speed operation by means of sensing temperature conditions inside a building and accordingly increasing or decreasing heating or cooling speeds results in air-source heat pumps in achieving energy savings.

Other strategies such as working with combinations of different heating and cooling systems per the degree of solar exposure and desired comfort levels could also be experimented with. For the case of the educational building, four different systems of radiator + evaporative cooling (the most common system used in the location), VAV, fan coil, and heat pump were simulated and optimized to establish the most efficient option. Accordingly, the optimum system of unitary heat pump can reduce heating, cooling, and the total energy use intensity (EUI) by 69.03%, 38.21%, and 28.81%, respectively. The final results indicated that the proposed method could reduce the annual energy consumption (EUI) by almost half while doubling the comfortable

*Energy-Efficient Retrofit Measures to Achieve Nearly Zero Energy Buildings DOI: http://dx.doi.org/10.5772/intechopen.101845*

**Figure 9.**

*Energy use and physical features (construction material, HVAC, and lighting systems) of the retrofitted case study.*

hours indoors. **Figure 9** represents the energy consumed by different energyconsuming components of the retrofitted case study and the suggested replacement of physical features of the building. Such informed and analytically validated suggestions can inform property owners and make them aware of the retrofitting process's impact in transitioning to a nearly zero energy future.

Another active mode of energy generation is the renewable energy sector. Harnessing the sun's power by means of solar photovoltaic (PV) panels is one of the most cost-effective modes of harvesting renewable energy. The efficiency of solar panels is typically dependent on the amount of unobstructed solar radiation captured by the panels over a period throughout the day. After calculating the amount of energy conserved by applying the aforementioned passive and active strategies, a well-thought-out plan for solar energy capture must be developed. This is also due to the limitations of existing homes regarding the amount of open and exposed roof surface square meters available for the installation of PVs. A well-developed plan can aid in calculating the exact number of panels needed to manage and balance out the amount of energy required to reach a near-zero energy target. The inclusion of microinverters rather than centralized inverters should become the norm to encourage capturing optimal performance per panel while future-proofing the ability to add more panels in the future. Governments globally are now encouraging the installation of panels by providing subsidies and encouraging schemes that make solar leasing affordable and easily accessible.

For instance, in the case of the educational building understudy, PVs were suggested to make the most from renewable energy sources, such as solar radiation, to transfuse an annual amount of 10.7 mWh of electricity to the grid supply a part of the projects' total energy consumption. Hence, 24 panels are suggested to be placed on the roof to bring it closer to an nZEB design. Accordingly, the final design incurs less than 55 kWh/m2 energy consumption, from which 9.32% is supplied by harvesting solar energy. The associated carbon emission (operational) was also reduced by 17.96% (**Figure 10**).

As a proof of concept for the propositions made in this chapter, jointly—both passive and active strategies proposed for the retrofitting of the educational building exhibited the potential to reduce the energy consumed for heating, cooling, and lighting purposes up to 85.19%, 58.57%, and 23.68%, respectively, compared to the base case (**Figure 11**).

Furthermore, the annual EUI could effectively be reduced by 52.98%, while the associated carbon emissions (t CO2) and annual comfort hours also exhibit

#### **Figure 10.**

*Energy savings and CO2 emissions reduction by PV installation.*

#### **Figure 11.**

*The impact of the proposed retrofit strategies on the annual discomfort hours and CO2 emissions.*

#### **Figure 12.**

*The impact of retrofit strategies on annual energy use.*

improvement by 46.48% and 49.28%. Replacing existing windows with highly efficient windows proved to have the highest impact (22.58%) on the comfort experienced indoors, followed by using an optimum HVAC system and applying interior insulations, each with an effective percentage of 21.90% and 19.18%. The inclusion of an efficient HVAC system also aided in reducing operational carbon emission to a great extent (24.05%). Installing PV panels also exhibited a substantial reduction in carbon emissions (19.18%) (**Figure 12**).


**1.1 Epidemic disease**

The term epidemic is derived from Greek word "epi" meaning "upon" and "demos" meaning "people". It refers to a communicable disease which spreads rapidly in a given population within a very short period of time. Any infectious disease existing in a region does not make it epidemic unless it causes faster mortality. A death rate of around 1.6 folds higher than usual death rate (baseline) caused by a

disease in a population within a fixed period could be considered as an epidemic disease. A disease lower than this fold increase, observed in a population could be designated as an outbreak of a disease [1].

Diseases like tuberculosis, hepatitis, yellow fever, chikungunya, ebola virus disease, marburg virus disease, Crimean-Congo haemorrhagic fever, rift valley fever, typhoid fever, Shigellosis, plague, lassa fever, West Nile fever, zika virus disease, meningitis, MERS-CoV, plague, monkeypox, nodding syndrome, nipah virus infection are considered as epidemic diseases as per World Health Organization [2]. Epidemic diseases like plague, small pox and cholera caused unsurpassed deaths in human population till the end of eighteenth century [3].


**Systemic Approach to the Genome Integration Process of Human Lentivirus**

Felipe García-Vallejo and Martha Cecilia Domínguez

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/52885


*Article* **Magnetic and Structural Properties of Barium Hexaferrite Nanoparticles Doped with Titanium**

#### **Abdul Raouf Al Dairy 1, Lina A. Al-Hmoud 2,\* and Heba A. Khatatbeh 1**

Received: 6 May 2019; Accepted: 24 May 2019; Published: 28 May 2019

**Abstract:** Samples of Barium Hexaferrite doped with Titanium BaFe12−*x*Ti*x*O19 with (*x* = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0) were synthesized by the sol–gel auto-combustion technique. The powdered samples were divided into two parts, one sintered at 850 ◦C and another sintered 1000 ◦C for 1 h and samples were characterized by different experimental techniques. The XRD patterns confirmed the presence of M-type hexaferrite phase. The sizes of the crystallites were calculated by the Scherer equation, and the sizes were in the range of 27–42 nm. Using the hysteresis loops, the saturation magnetization Ms, remanence (Mr), the relative ratio (Mr/Ms), and the coercivity (Hc) were calculated. The study showed that the saturation magnetization (Ms) and remanence (Mr) decreased with increasing titanium concentration and were in the range from 44.65–17.17 emu/g and 23.1–7.7 emu/g, respectively. The coercivity (Hc) ranged between 0.583 and 4.51 (kOe). The magnetic properties of these Barium Hexaferrite doped with Titanium indicated that they could be used in the recording equipment and permanent magnets.

**Keywords:** Barium hexaferrite; titanium; hysteresis; X-ray diffraction; permanent magnet applications

#### **1. Introduction**

There are vast numbers of applications based on magnetic materials and as a result of that; our lives have improved. They are used in the fabrication of many types of equipment and have a major role in the advancement of technological and industrial products. The types of magnetic materials, according to their magnetic behavior, are one of five types; Diamagnetic, Paramagnetic, Ferromagnetic, Antiferromagnetic, and Ferrimagnetic materials [1–3]. Magnetic ferrites, first discovered in the 1950s, are ceramics made from iron oxides with one or more additional metals chemically added [4,5]. These ferrites had been considered very highly valuable electronic materials for many decades. The ferrite compounds have a cubic structure, but there is also a group of ferrites with a hexagonal crystal structure, known as hexaferrites [6]. There was an increasing degree of interest in hexaferrites, and it is still growing today. They have been massively produced and became important materials; commercially and technologically used in many electrical systems, such as permanent magnets, magnetic recording and data storage devices [6,7].

 They can be classified on the basis of their chemical composition and the A–M combination and the crystal structure into six fundamental, structural types: M, W, Y, X, U, and Z [8–13].

The ferromagnetic and ferromagnetic types show nonlinear relation between the magnetization *M* of the compound and the applied H. The hysteresis loop depicts the behavior of the magnetization M of the sample with the variation of the applied field H. As H increases, the magnetization increases up to its highest value; this defines an important characteristic parameter of the material called the saturation magnetization Ms at high enough applied fields. The value of the field needed to reach the saturation magnetization depends on the nature of the material, method of preparation, and other intrinsic and extrinsic parameters. The magnetization retains a value even at zero applied fields called the remnant magnetization or the remanence Mr. This parameter has particular importance in the case of permanent magnets production because it defines the magnetization of a magnet in the absence of an applied external field. The size of the opposite field needed to reduce M to zero is called the coercivity Hc. The value of the coercive field, the coercivity, defines the so-called magnetic hardness of the magnetic material [14].

Many research groups prepared these ferrites and investigated the effect of the dopants on the magnetic properties of such M-type magnetic hexaferrites [15–33]. The hexaferrites are of great interest for applications in the microwave technology and others. S.V. Trukhanov et al. studied the effect of gallium doping on the properties of barium hexaferrite, BaFe12-*x*Ga*x*O19 (*x* ≤ 1.2), prepared by the ceramic technology method [34,35]. They showed that the unit cell monotonically decreases with increasing *x* and these Ga doped hexaferrites can effectively absorb high-frequency electromagnetic radiation. The maximum of the real part of permeability depends on the level of substitution by titanium cations and it is located in the region of 5–6 GHz. For gallium-substituted hexaferrites, the real part of permittivity decreases more slowly at low frequencies and almost monotonically with concentration. In last case, the real and imaginary parts of the permeability have a peak in the region of 49–51 GHz, which is determined by the level of diamagnetic substitution. Researchers have prepared (BaFe11.9Al0.1O19)1−*x*(BaTiO3)*x* with *x* = 0. 0.25, 0.5, 0.75, and 1 bicomponent compounds using the ceramic technique [36]. The researchers reported that these hexaferrites exhibited ferroelectricity at room temperature and the coercive field was lower due to the contribution of the microstructure-dependent shape anisotropy to the magnetic anisotropy energy and the behavior of these samples was discussed based on the grain size, density, and porosity. The magnetic and dipole moments in BaFe12-*x*In*x*O19 hexaferrites were studied by S. V. Trukhanov group [37]. These indium doped samples were prepared by solid reaction method as published by coworkers of the same group before [38]. The samples were studied by high resolution neutron powder diffraction and vibrating sample magnetometry in the temperature range of 4–730 K. They showed that spontaneous polarization was established due to the displacement of Fe3+(In3+) cations and the appearance of nonzero electric dipole moment, which causes the formation of the z-component of the spontaneous polarization. The crystal structure and magnetic properties of BaFe12-*x*Me*x*O19 (Me = In3+ or Ga3+ and *x* = 0.1–1.2) solid solutions were studied using the time–of–flight neutron diffraction method [39]. The workers reported that the electric field–induced polarization was observed in these barium hexaferrite solid solutions at room temperature. Using the Gorter's model, the researchers found that the magnetic moments of iron ions were oriented along the hexagonal axis which is the easy axis of magnetization. The previously mentioned works of S.V. Trukhanov and co-workers proved that the magnetoelectric characteristics of M-type hexaferrites fabricated by a modified ceramic technique can be more advanced than those for the well-known room temperature BiFeO3 orthoferrite multiferroic.

The main goal of this project was to study the effect of Titanium substitution on the magnetic and structural properties of the barium hexaferrites prepared according to the formula BaFe11.9Ti*x*O19 with *x* = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0.

#### **2. Experimental Techniques**

A number of ferrite samples BaFe12-*x*Ti*x*O19 with (*x* = 0.0, 0.2, 0.4, 0.6, 0.8, 1.0) were prepared by using the sol-gel auto combustion technique. The chemicals used for the preparation of the samples were Fe(NO3)3, Ba(NO3)2, and TiCl3 and were dissolved in 100 ml of de-ionized water. Citric acid was added to the solution, and the molar ratio for the metallic mixture to acid was kept at 3:1 [33]. Using a hot plate and continuous stirring, the solution was heated up to a temperature of 80 ◦C. A solution of ammonia was added to the mixture to reach a pH value of 8.0. The solution was then heated slowly to 450 ◦C for several hours until a viscous brown gel mixture is formed. The gel was heated further to a

temperature of 550 ◦C and the gel ignited and was burned out completely and formed a fluffy brown colored powder. This powder was divided into two samples, using a furnace one sample was sintered at 850 ◦C and the second sample was sintered at 1000 ◦C each for a period of one hour.

The structure of the samples was studied using X-ray powder diffraction (with Cu*-K*α radiation λ = 1.5405 Å). Infrared spectroscopy was used to ensure the formation of M-type hexaferrite phase. The scanning electron microscope was used to study the microstructure of samples. Finally, the magnetic properties were studied at room temperature using a Vibrating Sample Magnetometer.

#### **3. Results and Discussion**

Figure 1 shows the XRD pattern for BaFe12O19 and the XRD patterns for doped BaFe12-*x*Ti*x*O19 samples sintered at 850 ◦C, while Figure 2 shows the XRD pattern for BaFe12O19 and those patterns for doped BaFe12-*x*Ti*x*O19 samples sintered at 1000 ◦C. It is clear that the XRD pattern for the BaFe12O19 (i. e., *x* = 0) as the prepared sample is consistent with the standard pattern (JPCDS #: 00-043-0002) for BaM compound but with a higher percentage of that phase at the higher sintering temperature. This leads to the conclusion that the samples must be sintered at temperatures even higher than 1000 ◦C. As seen from Figure 2, the patterns indicated the presence of α-Fe2O3 in samples sintered at 1000 ◦C as seen from the peak at 33.1 degree and other lower peaks at 24.2, 49.4, and 54 degree and the content of α-Fe2O3 changes with *x* and was the highest for *x* = 0.6. It is also clear from peaks at 53.2 and 61.8 degree that there are traces of FeTiO3 oxide and the peak at 28.8 degree indicated a presence of a small trace of BaTiO3.

The Scherrer formula was then used to calculate the average crystallite sizes for the samples:

$$D = \frac{k\lambda}{\beta \cos \theta}.\tag{1}$$

Here, *D* is the average crystallite size, *K* is called the Scherrer's constant and is taken equal to 0.89 for the hexaferrite, λis the x-ray wavelength and equals1.5405 Å, βis the width of the peak at half maximum and is measured in radians, and θis the position of the peak. Using several peaks, the average crystallite size for all samples was calculated; the results and calculations are summarized in Tables 1 and 2.

**Figure 1.** XRD patterns for BaFe12-*x*Ti*x*O19 samples with (*x* = 0.0–1.0) sintered at 850 ◦C for 1 h and shown the standard pattern of BaFe12O19 (file no.: 043-0002).

**Figure 2.** XRD patterns BaFe12-xTi*x*O19 samples with (*x* = 0.0–1.0) sintered at 1000 ◦C for 1 h and shown the standard XRD pattern of BaFe12O19 (file no.: 043-0002).

The average crystallite sizes were found to be in the range of (27–36) nm for samples sintered at 850 ◦C, and the average crystallite sizes for samples sintered at 1000 ◦C were found to be in the range of (35–41.5) nm. This may lead us to conclude that Ti substitution improved the BaM phase crystallinity especially at the sintering temperature of 1000 ◦C.

**Table 1.** The calculated average crystallite sizes for the system BaFe12-*x*Ti*x*O19 with (*x* = 0.0–1.0) sintered at T = 850 ◦C.

**Table 2.** The calculated average crystallite sizes for the system BaFe12-*x*Ti*x*O19 with (*x* = 0.0–1.0) sintered at T = 1000 ◦C.

To prove the presence of M-type hexaferrite phase, Infra-Red (IR) analysis was used because the IR- spectra can point to its presence. The samples were mixed with 0.05% KBr in order to get an acceptable resolution of the compound bands. IR spectra of the as-prepared samples were obtained with a wave number varying between 300 cm−1 to 1000 cm−1 and the results are summarized in Figures 3 and 4 for the two sintering temperatures, respectively.

**Figure 3.** Infra-Red (IR) spectra of BaFe12-*x*Ti*x*O19 sintered at T = 850 ◦C.

**Figure 4.** IR spectra of BaFe12-*x*Ti*x*O19 sintered at T = 1000 ◦C.

As seen from Figures 3 and 4, the IR spectra of the sintered samples have absorption bands at wave numbers in the range 430−590 cm−1, which are characteristic to the formation of ferrites. The peaks were clearer for those samples sintered at 1000 ◦C. The peak at about 430 cm−1 is due to bending of the absorption bands of the metal-oxygen and that at about 590 cm−1 is due stretching of these bands.

Figure 5 shows an SEM image for one of the samples, namely BaFe12-*x*Ti*x*O19 (with *x* = 0.2), which was sintered at T = 1000 ◦C. It shows that grains are ultrafine and almost have homogeneous distribution. The image also shows that the platelets have sizes in the range of 200 nm to 500 nm.

**Figure 5.** SEM image for BaFe12-xTi*x*O19 (*x* = 0.2) sample sintered at T = 1000 ◦C.

Based on X-ray results and IR data, we believe that samples are improved if heat-treated at 1000 ◦C.

We studied only magnetic properties for samples sintered at 1000 ◦C. Magnetic measurements were carried out at room temperature by a VSM with applied field between 0 and 10 kOe. The group of hysteresis loops (HL) for all samples is shown in Figure 6. The loops do indicate that all the samples are indeed hard magnetic materials. The values of remanence magnetization and coercive field for each sample were read directly from graphs of loops. Since it is expected that samples have high magnetic anisotropy, we used the law of approach to saturation (LAS) to calculate the saturation magnetization. This is simply found by plotting M versus 1/H2 for values taken from high field region and all samples gave perfect straight linear graphs. The intercept of that line is equal to the saturation magnetization.

**Figure 6.** Hysteresis loops for the samples BaFe12-*x*Ti*x*O19 (*x* = 0.0 − 1.0) sintered at 1000 ◦C.

Table 3 shows summary of the calculated values for the saturation magnetization, the remanence magnetization, the reduced magnetization, and the coercivity.

**Table 3.** The saturation magnetization, remanence magnetization, reduced remnant magnetization and coercive field for the system BaFe12-*x*Ti*x*O19 (*x* = 0.0–1.0).

The saturation magnetization shows inverse relation titanium concentration. The partial substitution of Fe by titanium ions in these hexaferrites has affected the values of MS, which depends on the amount of Ti ions diffusing into the BaM crystal in which Ti+3 ions partially replace Fe+3. However, the higher the Ti concentration results in lower Ms because other phases are then formed as was concluded from XRD data.

Hard ferrites typically have a high value of Mr, which is about 50% of the saturation magnetization (Ms), therefore the reduced remnant magnetization (Mrs = Mr/Ms) must be nearly 0.5, and this is true for samples consisting of single-domains and random orientations of grains [32]. Table 3 shows that the values of Mrs are very close to 50%. The coercive field, Hc, for the samples varied with Ti concentration and it ranged between 0.6 and 4.5 kOe as can be seen in Table 3. A plot of Ms and Hc versus the concentration of titanium is shown in Figure 7.

**Figure 7.** Saturation magnetization and coercive field versus Ti concentration.

We calculated the average paramagnetic behavior for each sample by approximating the loop by a straight line as shown in Figure 8. Of course, this behavior is correct only for shallow applied fields, but we found that there is a general trend in these samples that can be depicted by the slopes of these lines. Slopes of these lines are listed in Table 4. The slopes are related to the magnetic susceptibility and increased slowly by increasing the concentration up to *x* = 0.6 and then decreases to half its value after that.

**Figure 8.** The hysteresis loop for the system BaFe12-*x*Ti*x*O19 (*x* = 0.2) approximated by a straight line.

**Table 4.** The slope and hysteresis losses (in W) for the system BaFe12-*x*Ti*x*O19 (*x* = 0.0–1.0).

We also calculated hysteresis losses for each sample and the calculated values are listed in Table 4. It is clear from the values of losses that Ti concentration could be a scaling factor for magnetic energy stored when these materials are used in components of electromagnetic devices. This behavior is displaced in Figure 9. Losses are significant and almost linear for *x* < 0.6.

**Figure 9.** Hysteresis losses (in W) BaFe12-*x*Ti*x*O19 (*x* = 0.0–1.0) sintered at 1000 ◦C.

#### **4. Conclusions**

A group of BaFe12-*x*Ti*x*O19 samples with (*x* = 0.0–1.0) were prepared by sol-gel-auto combustion method and were sintered at 850 ◦C and 1000 ◦C for 1 h in air. The XRD data and IR data analysis confirmed the presence of M type phase of the hexaferrite in these samples, and the higher sintering temperature showed an improvement of crystallinity. The average crystallite size for all samples was in the range of 27–42 nm. We believe that these are suitable to obtain the reasonable signal to noise ratio when used in a high-density recording medium. The values of saturation magnetization (Ms) and retentivity (Mr) calculated values decreased with increasing the Ti concentration, and this may result from particle size effects. The addition of titanium reduced the saturation magnetization from about 45 emu/g down to 17.2 emu/g. The rest of the magnetic properties that include coercivity, remanence magnetization, reduced remnant magnetization, and hysteresis losses suggest that these materials are beneficial in the components of electromagnetic devices that are used in recording technology and permanent magnets. We suggest that further work is needed to study the effect of sintering temperatures and very low controlled Ti concentrations. In addition, structural and magnetic studies at temperatures above and below room temperature using other techniques could be of great importance.

**Author Contributions:** Formal analysis, L.A.A.-H.; Methodology, H.A.K.; Supervision, A.R.A.D. All authors contribute equally to this manuscript.

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

**Acknowledgments:** This research work was supported by the Deanship of Graduate Studies and Research, Yarmouk University, Irbid, Jordan; project 7/2017. We acknowledge the help of Prof. A. Hammoudeh in preparation of samples and IR data.

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

#### **References**

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


**Author details**

Igor Cretescu1 \*, Dorina Nicolina Isopescu2 , Doina Lutic3 \* and Gabriela Soreanu1

1 Department of Environmental Engineering and Management, Faculty of Chemical Engineering and Environmental Protection, "Gheorghe Asachi" Technical University of Iasi, Iasi, Romania

2 Faculty of Civil Engineering and Building Services, "Gheorghe Asachi" Technical University of Iasi, Iasi, Romania

3 Department of Material Chemistry, Faculty of Chemistry, "Alexandru Ioan Cuza" University, Iasi, Romania

\*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.


**4. Management of deformities**

#### **4.1. Varus deformity**

During the arthritic course, there are expected modifications in native alignment and ligament function. Loss of cartilage can create an asymmetrical compartment balance, leading to contracture of soft tissues on the concave side and contralateral loosening on the convex side. As the deformity progresses, these modifications tend to establish into fixed deformities. In varus knees, contraction of medial side involves medial collateral ligament and the whole medial periosteal sleeve, including hamstrings, posteromedial capsule, and PCL. As the deformity progresses, the lateral compartment becomes insufficient, causing abnormal lateral opening and instability.

**4.2. Valgus deformity**

augmentation and more constrained implants.

In the valgus knee, the lateral structures contract, while the medial soft tissues stretch. Differing from varus knees, where the bone erosion occurs more in the tibial bone, in valgus knees most of the bone deformity comes from the femoral side (**Figure 13**). As the deformity

**Figure 12.** In advanced deformities, when there is great medial bone loss, the surgeon must consider using metal

Planning Primary Total Knee Arthroplasties http://dx.doi.org/10.5772/intechopen.72775 15

Lateral soft tissue structures, including the lateral collateral ligament (LCL), iliotibial band (ITB), and the lateral capsule, contract, while the medial soft tissues stretch. When this

**Figure 13.** Most part of the bone wear occurs on lateral femoral condyle, although it could involve tibial bone as well.

progresses it tends to involve the tibial bone and cartilage as well.

Instability of the arthritic knee may be viewed as symmetrical or asymmetrical. Symmetrical instability is seen during early arthritis, when there is erosion of cartilage or bone without associated adaptive soft tissue changes. During physical examination, the deformity can be corrected under active reciprocal stress on physical examination. This kind of instability is easily corrected during surgery without needing extensive ligament releasing.

As the deformity progresses it tends to turn into an asymmetrical instability, which is not corrected by active reciprocal stress during physical examination. This kind of fixed deformity occurs when cartilage and bone loss lead to adaptive ligamentous changes. In order to correct this kind of deformity, ligamentous release is mandatory, turning a trapezoidal gap into a rectangular gap. In asymmetrical instabilities, the bone cuts alone are not sufficient to accomplish articular balance.

Instead of only releasing ligaments from the contracted concave side someone could advocate to advance ligament complexes on the convex side, especially when the opposing ligaments are stretched to the point of being incompetent. These authors do not favor ligament advances or reconstructions on the convex side since the functional outcomes have not been acceptable in most series. In such cases, the authors advise considering a more constrained knee design (**Figure 12**).

**Figure 12.** In advanced deformities, when there is great medial bone loss, the surgeon must consider using metal augmentation and more constrained implants.


**2.2. Investigating the intellectual structure in scientometrics**

Scientometrics depicts the intellectual landscapes of a science with a variety of bibliographic units such as authors, keywords, texts, and citations and networks of those entities. The present chapter systematically mapped historical footprint and emerging technologies from published research in scientometrics. In particular, we investigated citation paths at a disciplinary level, co-occurrence of WoS categories and keywords, and networks of co-cited references. Network clustering and topic modeling were also used to find homogeneous sets of literature and coherent streams of research. In so doing, we captured emerging trends, recent developments, and current challenges in the domain. Especially, we employed a top-down approach in analyzing data going from macro-level to micro-level. It had us add richer interpretations as we gradually moved on to lower-level units of analysis such as journal-level citation paths, subject categories, keywords, titles and abstracts to cited references. To this end, this chapter is mainly guided by

two suites of software, namely CiteSpace [4–6] and VOSviewer [7]. The input is a collection of bibliographic records relevant to a topic of interest. Given the records, the toolkits detect and render thematic patterns and emerging trends in science as networked in a variety of bibliographic units. As argued by preceding papers [8, 9], this chapter's approaches have several methodological merits over a conventional domain analysis. First, a much more inclusive range of topically relevant literature can be examined. Second, an inquiring individual does not need prior expertise to analyze a domain of interest. Finally, this kind of survey can be conducted as frequently as in need given the fast growth of a science. The underlying techniques and findings of the present chapter could be more clearly delivered as we introduce followings:

**Table 2.** Querying terms (the wildcard character "\*" captures any relevant variations of a term).

**Term Duration Total Articles Procs. Reviews** bibliometric\* 1990–2017 6352 5449 313 590 scientometric\* 1990–2017 1779 1577 93 109 informetric\* 1990–2017 382 334 28 20 webometric\* 1997–2017 288 254 25 9 altmetric\* 2012–2017 261 237 7 17 cybermetric\* 1999–2015 28 27 1 entitymetric\* 2013–2015 3 3 — —

Scientometrics of Scientometrics: Mapping Historical Footprint and Emerging Technologies…

http://dx.doi.org/10.5772/intechopen.77951

13

• Network reduction: In network analysis, investigating the entire nodes and edges between them is computationally challenging. It may not intuitively communicate the topological structure to the audience as well for it is visually overwhelming with many links. To handle this, we select up to 100 frequently occurring entities such as keywords and cited references

• Clustering: Clustering is unsupervised learning which uncover latent groups of entities sharing homogeneous characteristics. We employ a network clustering technique called smart local moving [10] to capture thematically similar clusters on a document co-citation network. • Burst detection: Proposed by [11], burst detection models the burstiness of features which rise sharply in frequency. An entity has bursting activities when it intensively appears during a specific span of time. We can overcome the limitation coming from considering

• Cluster labeling: CiteSpace labels clusters with extracted terms from titles and abstracts of citing articles. There are three algorithms to serve cluster labeling: (1) latent semantic analysis (LSA), (2) log-likelihood ratio (LLR), and (3) mutual information (MI). LSA captures unknown semantic relationships over all the documents while LLR and MI reflect a

• Topic modeling: Topic modeling is unsupervised machine learning which aims to discover latent semantic structure occurring in a text body. We employ dynamic topic modeling

within a one-year time slice.

unique aspect of a cluster [5].

cumulative, snapshot metrics as impact measures.

**Table 1.** Data statistics.

**Figure 3.** The distribution of records over time.

Scientometrics of Scientometrics: Mapping Historical Footprint and Emerging Technologies… http://dx.doi.org/10.5772/intechopen.77951 13

**Table 2.** Querying terms (the wildcard character "\*" captures any relevant variations of a term).

two suites of software, namely CiteSpace [4–6] and VOSviewer [7]. The input is a collection of bibliographic records relevant to a topic of interest. Given the records, the toolkits detect and render thematic patterns and emerging trends in science as networked in a variety of bibliographic units. As argued by preceding papers [8, 9], this chapter's approaches have several methodological merits over a conventional domain analysis. First, a much more inclusive range of topically relevant literature can be examined. Second, an inquiring individual does not need prior expertise to analyze a domain of interest. Finally, this kind of survey can be conducted as frequently as in need given the fast growth of a science. The underlying techniques and findings of the present chapter could be more clearly delivered as we introduce followings:

**Figure 3.** The distribution of records over time.

**Table 1.** Data statistics.

cases text fields were omitted. Thus, we excluded data before 1990. The brief statistics of the

**Figure 3** renders the record distribution over time in our data collection. As illustrated, there

**Table 2** describes the contributing terms to the data retrieval and corresponding number of records to each term. As shown, the literature has used "bibliometric\*" the most frequently.

Scientometrics depicts the intellectual landscapes of a science with a variety of bibliographic units such as authors, keywords, texts, and citations and networks of those entities. The present chapter systematically mapped historical footprint and emerging technologies from published research in scientometrics. In particular, we investigated citation paths at a disciplinary level, co-occurrence of WoS categories and keywords, and networks of co-cited references. Network clustering and topic modeling were also used to find homogeneous sets of literature and coherent streams of research. In so doing, we captured emerging trends, recent developments, and current challenges in the domain. Especially, we employed a top-down approach in analyzing data going from macro-level to micro-level. It had us add richer interpretations as we gradually moved on to lower-level units of analysis such as journal-level citation paths, subject categories, keywords, titles and abstracts to cited references. To this end, this chapter is mainly guided by

**Duration Total Articles Procs. Reviews Authors Keywords Refs.** 1990–2017 8098 7013 413 672 23,791 98,493 328,096

has been exponentially increasing interest in scientometrics from the community.

**2.2. Investigating the intellectual structure in scientometrics**

retrieved data set is described in **Table 1**.

12 Scientometrics

(DTM) which is a generative technique extended from Latent Dirichlet Allocation (LDA). DTM captures the evolution of latent topics in a collection of documents whereas it was oblivious to the preceding model [12].


*3.12. Western Blotting Analysis*

The Western blotting analysis was performed as previously described [31]. Briefly, the samples with cell lysates were boiled for 10 min at 100 ◦C. The concentrations of proteins in the cell lysates were quantified using the bicinchoninic acid method. Equal amounts of protein were subjected to 8%–10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred to polyvinylidene fluoride membranes (Millipore, Bedford, MA, USA) activated with 100% methanol. The membranes were blocked using 5% BSA in a mixture of Tris-buffered saline and Tween 20 (1×), and subsequently probed with the following antibodies: anti-iNOS, COX-2, and GAPDH (Cell Signaling Technology, Beverly, MA, USA). The blots were visualized using an enhanced chemiluminescence detection kit (Intron Biotechnology, Sungnam, Korea) and an ImageQuant LAS-4000 Imager (Fujifilm Corp., Tokyo, Japan).


*3.2. q-RT-PCR Analyses*

The influence of quercetin on some transcription factors and target genes of the IIS pathway was also explored by quantification of the expression of *daf-16, hsf-1, skn-1, daf-18*, and *hsf-16.2* by RT-qPCR in wild type worms, both submitted and not submitted to thermal stress (5 h, 35 ◦C) after growing 4 days in the presence of the flavonol. As it can be seen in Figure 5, the treatment with Q did not modify the expression of *daf-18* either after subjecting or not subjecting the worms to thermal stress. However, the results previously obtained with the mutants (Figure 4) indicated that *daf-18* could be involved in the protective effects of quercetin against stress. A possible explanation to this apparent contradiction could be that the result obtained in the *daf-18* mutant is rather reflecting the involvement of the protein kinase AGE-1, as the DAF-18/phosphatase and tensin homolog (PTEN)protein is responsible for dephosphorylating and inhibiting AGE-1/PI3K, counteracting its activity [21]. Another possibility is that DAF-18 was regulated by quercetin at the post-transcriptional or activity level.

**Figure 5.** Effect of Q on the expression of *daf-16*, *hsf-1*, *skn-1, daf-18*, and *hsp-16.2* genes in N2 *C. elegans* cultivated in the absence (controls) and presence of Q (200 μM) (**A**) under non-stressed conditions or (**B**) after subjecting them to thermal stress. The expression level was determined by RT-qPCR. *act-1* was used as housekeeping control. Nine independent experiments were performed. The results are presented as the mean values ± Standard Error of the Mean (SEM). Statistical significance was calculated using by one-way analysis of variance (ANOVA). The asterisk (\*) indicates significant differences at *p* < 0.05.

Similarly, the expression of *hsf-1* was not modified by the treatment with Q, neither in normal growing conditions nor after application of thermal stress (35 ◦C, 5 h) (Figure 5). This result would confirm that the heat transcription factor *hsf-1* is not involved in the effects of Q on stress resistance, supporting the above-described observations on *hsf-1* mutants (Figure 4). In a previous study on *hsf-1* loss of function mutants, Fitzenberger et al. [28] also found that this gene was not required to explain the ability of Q to prevent the glucose-induced reduction of survival in *C. elegans.*

The treatment with Q did not produce changes in the expression of *daf-16* (Figure 5). Together with the findings obtained in the assays with mutants, these results seem to confirm that the effect of Q on worm stress resistance is independent of *daf-16*. Other authors had already studied the involvement of *daf-16* in the effects of Q using knockout worms [10,11,13], finding that Q continued improving longevity and resistance to thermal and hydrogen peroxide-induced oxidative stress in *daf-16* mutants, which suggest that this gene was not essential for the effects of quercetin, observations that are consistent with the results obtained herein, either in worms subjected or not subjected to stress.

SKN-1 is the homologue of Nrf-2 transcription factor, which regulates oxidative stress response and lifespan, mobilizing the conserved phase 2 detoxification response [29]. No differences were found in the expression of *skn-1* between worms treated or not treated with Q and not subjected to stress (Figure 5A), which seems in agreement with the observations of Pietsch et al. [11], who reported that quercetin induced an increase in the lifespan of *skn-1* mutants under normal growth conditions, indicating that the effects of this flavonoid in the absence of stress are independent of that gene. However, the results obtained with the *skn-1* mutants (Figure 4) indicated that this gene is a mediator in the protective effects of Q against stress. Tullet et al. [29,30] suggested that SKN-1 is a transcriptional co-regulator of DAF-16 regarding resistance to oxidative stress and the expression of detoxification genes in response to a reduced IIS signal, but it extends worm half-life independently of DAF-16. This dual function of *skn-1* might be coherent with the results observed herein, where Q did not change the *skn-1* expression in absence of stress, although this gene seems to be necessary in the improvement of resistance to thermal stress mediated by Q.

The influence of Q on thermal shock proteins HSP-16.2, whose expression is influenced by the IIS, was also studied. As shown in Figure 5, the treatment with Q induced an increase in the expression of *hsp-16.2*, either without or with stress. However, the differences were more noticeable in the absence of stress, which could possibly be explained by the already strong induction of HSP-16.2 caused by the thermal stress, which would make the effect induced by Q treatment less relevant. Together with the results in the *hsp-16.2* mutants, where a decrease in the resistance to thermal stress was observed in quercetin-treated worms (Figure 4), it appears that thermal shock proteins can be involved in the protective effects of the flavonol against stress.

All in all, the obtained results showed that, at least in part, the IIS pathway would be involved in the improvement to thermotolerance induced by Q, entailing the genes *age-1, akt-1, akt-2, sgk-1, daf-2, daf-18, skn-1*, and *hsp-16.2*, but independent of *daf-16* and *hsf-1*. In addition, the involvement of these genes was not modified by the age of the worm. Previous studies by our group with epicatechin also showed that the enhanced stress resistance induced by this flavan-3-ol in *C. elegans* was also mediated by the IIS pathway, although it did not necessarily involve the same genes, as in that case the expression levels of the main transcription factors of the pathway (*daf-16, skn-1*, and *hsf-1*) were modified by the compound [31]. Actually, even compounds belonging to the same flavonoid class seem to act through different mechanisms. Thus, the lifespan extension produced by quercetin-3-*O*-diglucoside in *C. elegans* was explained by upregulation of the genes *daf-2, old-1, osr-1*, and *sek-1*, whereas no modification was produced in the expression of *daf-16, age-1*, and *sir-2.1* [12]. However, assays with a flavonol-rich extract obtained from *Baccharis trimera* concluded that the improvement in the stress resistance was independent of several stress-related signaling pathways (p38, JNK, and ERK) and transcription factors SKN-1 and DAF-16 [32].


Meet the editor

Basim A. Almayahi, PhD, is a full professor in the Department of Environment, Faculty of Science, University of Kufa. His main areas of interest are applied nuclear physics, radon, alpha, and gamma spectrometry, environmental radioactivity and protection, radionuclides, biomarkers, renewable energy, and synthesis and applications of nanoparticles on bacterial pathogens. For many years he has been working on the development of radon,

alpha, and gamma detection dosimeters. He took up the role of Head of the Department of Environment and Director of Scientific Affairs and Cultural Relations. He was the mentor of two masters theses. He is the editor and author of two books and a reviewer in 100 journals. He is editorial board member of 17 boards, international Scientific Program Committee of 44 members, and has membership of different institutions. He has published 75 scientific papers in domestic and international journals and participated in a large number of scientific congresses and conferences.

Contents

**Section 1**

*by Lubna A. Al-Asadi*

*by Hasna Albandar*

Arctic Regions *by Bertil R.R. Persson*

Subterranean Detectors

*by Hassane Erramli and Jaouad El Asri*

**Section 2**

**Section 3**

Basic Modes of Radioactive Decay

*by Hai Lin, ChengPu Liu and Chen Wang*

**Preface III**

Natural Radioactivity **1**

**Chapter 1 3**

**Chapter 2 23**

**Chapter 3 37**

**Chapter 4 49**

Radiation Detection and Measurement **65**

**Chapter 5 67**

**Chapter 6 85**

Gamma Rays Applications **107**

**Chapter 7 109**

Gamma Background Radiations and Measurements with Applications

Gamma-Ray Emitting Radionuclides in People Living in Northern Sub

High Purity Germanium: From Gamma-Ray Detection to Dark Matter

*by Monia Kazemeini, John Vargas, Alexander Barzilov and Woosoon Yim*

Gamma Rays: Applications in Environmental Gamma Dosimetry and Determination Samples Gamma-Activities Induced by Neutrons

*by Nicolas Fourches, Magdalena Zielińska and Gabriel Charles*

Gamma Ray Measurements Using Unmanned Aerial Systems

Electron Oscillation-Based Mono-Color Gamma-Ray Source


Bovine Embryonic Development to Implantation

*Loide Valadão, Helena Moreira da Silva and Fernando Moreira da Silva*

### **Abstract**

Throughout this chapter, we will express the embryonic development from fertilization, commonly called conception, to the implantation. It is well documented that preimplantation is considered a critical period for embryo development in ruminants, in which high pregnancy loss occurs; in fact, several authors point out that 50–75% of blastocysts fail to implant. The high rate of implantation failure is one reason why pregnancy typically requires on average two ovulation cycles to achieve. Events involved in the embryo growth and survival are directly or indirectly related to cytokines, steroids, metabolites, and growth factors. When one of these compounds fails, it normally leads to the death of the embryo or fetus. As known, the period required for full development of a fetus in utero is referred to as gestation, and it is commonly subdivided into two distinct periods. The first 2 weeks of prenatal development are referred to as the pre-embryonic stage. By the end of the embryonic period, all of the organ systems are structured in rudimentary form, and the embryo shifts to the fetus from the ninth week of gestation until birth.

**Keywords:** bovine, oocyte, fertilization, embryonic development implantation