*4.6. Evaluation*

To evaluate our proposed approach, three comparison experiments are designed in this section. First, it is necessary to confirm the efficiency of coarse-to-fine strategy. Second, the performance by using mean shape as initialization shape is evaluated. Furthermore, the third is to show the performances under different feature combination. In all experiments, distance error calculated as Euclidean distance between estimated landmarks location and corresponding ground truth were used to evaluate the performance. To evaluate and compare these methods, these three main experiments are carried out on the Bosphorus dataset. Among these 3632 data, 2800 data are randomly selected as training data, and the other 832 are regarded as testing data. The number of training data is increased to 2800 × 6 = 16,800 after augmentation. In this section, all models are trained and tested by using the same training and testing data.

To confirm the effective of global estimation, we compare our method with the method by taking mean shape as initialization shape. Different from taking the global estimation as initialization, mean shape is computed as the initialization shape for local refinement. Instead of global estimation, the local patches around mean shape are taken to extract local features. Then, we will update the

locations the same as the local refinement phase in our method. Figure 4a shows the average distance error after global estimation and mean shape calculation, and Figure 4b illustrates the average distance error via two different initialization ways after local refinement. As can be seen, the results of our proposed method outperforms after the local refinement.

**Figure 4.** The comparison results between mean shape and our proposed method. (**a**) denotes the results after global estimation and the (**b**) represents the results after refinement.

Furthermore, to verify the coarse-to-fine strategy, we compare the results after global estimation and local refinement. In Figure 5, the blue bars show the average distance error of 22 landmarks in the testing dataset after global estimation, while the other bars show the results after refinement. It can be easily observed that the results are enhanced effectively from coarse to fine. Note that the mean error has achieved 4.11 mm after global estimation, while 98.23% landmarks are located automatically with 20 mm and 93.31% landmarks are with 10 mm. After local refinement, the 100% landmarks are located automatically with 20 mm precision and 96.43% are with 10 mm. Furthermore, the average error of all landmarks in the testing data can also be improved to 3.37 mm, which has achieved the state-of-the-art.

**Figure 5.** The comparison results after global estimation and local refinement.

To show the performance under different feature combinations, the experiment is carried on the same training and testing data, and independent models are trained under different feature combinations. For this purpose, we selected maps from five facial attribute maps randomly and 30 = (25 − 2) kinds of feature combinations are generated to train and test models separately. In the case of each condition, the number of inputs would be modified to adjust the different network architecture, and other parameters in the networks are invariable. Figure 6 shows the global estimation results under different feature combinations. In this figure, the blue bars represent the mean error when different feature sets are fed into the network, while the red bar denotes our result. It can be observed that our global estimation result is the best, especially when we fuse all of these five facial attribute maps.

**Figure 6.** The global estimation results under different feature fusion.

#### *4.7. Comparison with Other Methods*

#### 4.7.1. Comparison with Handcrafted Features

To compare the performance of deep fusion feature with the results obtained by applying handcrafted features, their handcrafted features were tested. Instead of the deep fusion feature, three classical features including HOG (Histogram of Oriented Gradient), SIFT (Scale Invariant Feature Transform) and LBP (Local Binary Pattern), which have been proved to be efficient for image analysis, were employed to locate landmarks iteratively. For this purpose, these features around mean shape are firstly extracted and then respectively fused and fed into the designed networks to estimate landmarks coarse-to-fine with default parameters. Table 1 shows the average location error across all of the 22 landmarks on the Bosphporus database. We can easily draw the conclusion that the deep feature fusion marked with the bold fonts based on the pre-trained model is more accurate than the handcrafted features for all of these 22 landmarks. Furthermore, among these handcrafted features, the SIFT feature achieves the best performance, and outperforms HOG and LBP. These results also indicate that the location performance would obviously be affected by different features.

**Table 1.** Comparison with hand-crafted features on the Boshporus database.

#### 4.7.2. Comparison with Pre-Trained Models

This section compares the performance of deep fused features based on three different pre-trained models on the ImageNet dataset [43–45]. As aforementioned, different features extracted by using different pre-trained models were fed into the coarse-to-fine networks separately. In this paper, the same as the other handcrafted features, we use these pre-trained models to extract features from these facial attribute maps independently and fuse these features to train the designed model. Limited to numbers of the data, we keep all parameters fixed except the last fully connected layer. We only tested three classical deep models, including AlexNet [44], VGG-net [43] and Google Inception [45]. Table 2 shows the average location errors across all of the 22 landmarks on the Bosphorus database. The best performance is marked by bold fonts. From it, we can conclude that: (1) all of the deep features achieve better performance than the handcrafted features; (2) Deep fusion features all can achieve satisfied performance; and the (3) Google Inception network and AlexNet outperform the VGG-net for a few landmarks. However, comparing with VGG-net, Inception net takes too much time to extract features because of the complex architecture, and AlexNex is unsatisfactory among most of landmarks. Considering the computation accuracy and time complexity, the VGG-net has been chosen as the pre-trained deep model.

**Table 2.** Comparison with pre-trained deep models on BoshporusDB.

#### 4.7.3. Comparison on the Bosphorus Dataset

Furthermore, we compared our proposed approach with other existing methods on the Bosphorus dataset. Figure 7 depicts the mean distance error and standard deviation of 22 detected landmarks. From this figure, the mean distance error of all landmarks in the testing data is 3.37 mm, which has achieved the state-of-the-art, especially in some landmarks such as middle left/right eyebrow and so on. Compared with some other existing methods in these common landmarks, the comparison results are shown in Table 3. The best performance is marked by bold fonts. From it, we can see that our approach outperforms in outer eye corners, chin and mouth corners, which are difficult to locate. Figure 8 illustrates some examples of facial landmarking by the proposed approach on this dataset. In this figure, 3D facial geometry data are rotated through several directions, so that the performance of landmarking can be observed more clearly.

**Figure 7.** Mean distance error and standard deviation of 22 landmarks on the Bosphorus dataset.

**Table 3.** Comparison with other methods on BoshporusDB.

**Figure 8.** Samples of facial landmarking on 3D facial geometry data on the Bosphorus Dataset. To observe the performance more clearly, we rotate the facial data and estimated landmarks through several directions.

#### 4.7.4. Comparison on the BU-3DFE Dataset

The second experiment is carried out on the BU-3DFE dataset. Among the 2500 facial geometry data, 2000 facial scans from the 100 subjects were selected as the training data. The other 500 facial geometry data were used as testing data. After data argumentation, 12,000 facial scans can be obtained that contain neural expressions and six universal facial expressions. Figure 9 illustrates average distance error and standard deviation of 68 landmarks in the testing dataset of the 68 landmarks. Meanwhile, 98.88% of the landmarks are located with a 20 mm precision, and 93.20% are with the 10 mm precision. The mean distance error of all 68 landmarks has been improved to 4.03 mm. Compared with some other methods in the common landmarks on BU-3DFE dataset, Table 4 depicts the comparison results of 14

common landmarks. The best performance is marked by bold fonts. We can see that the average error of these points has been achieved 3.96 mm and the results in several points outperform, including the outer corner of the left eye, center of the upper lip, and center of the lower lip.

**Figure 9.** Mean distance error and standard deviation of 68 landmarks on the BU3DFE dataset.

**Table 4.** Comparison results with existing methods on BU3DFE.

## **5. Discussion**

With the development of deep learning, more and more data is needed to train a robust and accurate model. Unlike 2D images that can be easily obtained from the web, the 3D geometry data can't be constructed easily without professional equipment. Nowadays, the existing 3D geometry databases are all collected from labs and under the controlled conditions. Furthermore, the number of data is far from enough to train an appropriate deep model, so we need to fine-tune the pre-trained model. In this paper, using the pre-trained deep model to extract features from the different attribute maps is essential in the proposed approach. In most of the cases, fine-tuning these deep models means that most of the parameters in the pre-trained models remain unchanged and only a few are updated for specific tasks. For this purpose, we can update the parameters in the last layer or other layers based on the amount of training data. Thus, in our paper, limited to the number of 3D geometry data, we only updated the last layer and didn't test the other choices at all.

In addition, feature fusion is the key step in the proposed approach. Applying the fused feature extracted from deep model can take more useful information into account for locating landmarks. For 3D data, more useful information can be obtained including surface normal, curvature and other attribute maps. In this paper, we only select these five types of attribute maps to train the model. In fact, for each attribute map, the features can be extracted based on different pre-trained models. It is another way to improve the location performance, but it is too complex to be applied in the other testing data satisfied. On the other hand, a classical pre-trained model named ResNet was not considered because of the computational complexity and our computer performance. Although the model would achieve the best performance for our task perhaps, it still cost more than 3 min to extract the features without updating any parameters. For this reason, ResNet was not selected in our approach.

As other research about deep learning, the main weakness is also the computation complexity. Compared with other effective approaches, the computation complexity of our proposed method is higher than the others. In addition, this paper is the first time to utilize the deep-learning based approach to estimate 3D landmarks, while the other effective methods are all based on traditional ways such as hand-crafted features. Actually, to improve the accuracy, higher computation complexity is needed. Benefiting from more and more powerful computing power, the execution time is still satisfied. Of course, a lot of works will be done to reduce the computation complexity and to ensure the accuracy improvement synchronously in future works.

Although our algorithm has achieved state-of-the-art performance, there are a few other works to study. Firstly, we didn't take the profile face into account because there are only a few 3D profile data and fewer landmarks to train a unified location architecture. In addition, data missing caused by posing is the most challenging issue and the main weakness of our algorithm.


**9.1 Infective endocarditis (IE)**

It was in 1899, that the first report of infective endocarditis due to enterococci was published. The authors were MacCallum and Hastings who provided a detailed report of a case of acute endocarditis in a 37-year-old patient, caused by an organism they called Micrococcus zymogenes, probably the present *E. faecalis*. This bacterium was repeatedly isolated from the patient's blood until his death due to cardiac failure. The authors described that this bacterium was "very hardy and tenacious of life", which is true of enterococcus. They also showed that this particular isolate was haemolytic [8].

If we start with the risk factors for enterococcal infective endocarditis, only a few studies have addressed this. One study done in Denmark found that men were more prone, with prosthetic valve being a significant risk factor and most were community acquired and not related to hospital infection. They went on to say that for all cases of enterococcal bacteremia, it would be worthwhile to do echocardiography to rule out IE, especially in the presence of valve abnormality [16]. Another risk factor commonly encountered in cases of enterococcal IE in patients with valve abnormality is history of colorectal or urogenital disease or surgery [17]. A few case reports have been published describing enterococcal IE after colonoscopy and proctosigmoidoscopy [18]. In women, the ovaries may be a significant source. In a study done in our centre, we encountered a case of recurrent enterococcal endocarditis in a woman that could be resolved only after removal of an ovarian cyst. We also found that 12% of the valvular endocarditis was due to enterococci. Other than *E. faecalis*, *E. gallinarum* was also isolated from IE and was a challenge in treatment as it is intrinsically resistant to Vancomycin [19]. As described in the description of virulence factors, biofilm formation has been described to be a mode of pathogenesis in IE. IE requires a host factor, a thrombus, however enterococci can form micro-colonies on tissue surfaces without the host factor and this may lead to biofilm formation in a susceptible host with turbulent flow. In vitro models studied have not yet been correlated with in vivo studies in animals, and this is still a matter of hypothesis with no definite proof [20]. Treating IE due to enterococci involves getting an accurate identification up to species level, correct susceptibility data with minimum inhibitory concentrations for all antibiotics, including, Ampicillin, Vancomycin (if resistant to Ampicillin) and the aminoglycosides. Aminoglycosides have to be used as synergistic agents, only when they are not having high level antibiotic resistance (HLAR) [5]. The AHA/ IDSA guidelines recommend 6 weeks of treatment if symptoms have been present for more than 3 months [19]. However, there is a raging controversy on the duration of aminoglycoside therapy that may be detrimental to the kidney and the new mode of treatment called a double beta-lactam regimen that adds Ceftriaxone to Ampicillin in spite of the fact that enterococci are intrinsically resistant to all third generation cephalosporins. Readers may refer to recent guidelines issued from time to time by the American Heart Association (AHA). Streptomycin is suggested as an alternative to Gentamicin in cases of High level aminoglycoside resistance(HLAR) to Gentamicin [21].

#### **9.2 Urinary tract infections**

The close proximity of the gut flora to the urethra make *E. faecalis* and *E. faecium* causative organisms of urinary tract infections. Community acquired *E. faecalis* UTI is best treated with Ampicillin and there is no need for any combination. When catheter care is inadequate in a healthcare facility, *E. faecalis* colonises the catheter and this leads to CA-UTI when catheterisation is prolonged. Ascending infection generally causes only cystitis. This can be treated with Nitrofurantoin alone. If there is associated bacteremia, Ampicillin or Fosfomycin may be used for treatment. Fosfomycin can be reserved for Vancomycin resistant enterococci [22].

Enterococci cause a minority of community acquired UTI, 15–30% of catheter associated UTI and is the third common cause of hospital acquired UTI. Enterococci are seen to colonise the cells in the kidney and do not persist in the bladder. They have a tendency to persist inside macrophages in the kidney. Urothelial cells are also seen to have intracellular enterococci. All the above-mentioned constant cell bound virulence factors like Ace and Esp are important in the pathogenesis and persistence of enterococci in the urinary tract. In case of CA-UTI, enterococci can persist in the catheter forming a biofilm. However, CA-UTI due to gram positive bacteria including enterococci cause less inflammatory reaction as seen in a wet film of the urine. This may be the effect of immune evasion due to the biofilm formation.

Enterococci are also encountered in asymptomatic bacteriuria (ABU), like enterococci isolated during routine screening of urine in asymptomatic antenatals, at a healthcare facility. A review article on this subject found that such enterococci are actually protective against symptomatic bacteriuria in the future [23]. Treatment of ABU is recommended only in pregnancy and as part of pre-operative evaluation and decolonisation. ABU treatment is associated with higher incidence of multi drug resistant UTI [24].

Treatment: Ampicillin is the treatment of choice for strains that are sensitive. Ampicillin concentrates in the bladder and patients with strains that are resistant too can be treated with Ampicillin, as demonstrated in a study by Shah et al. Here they showed that Ampicillin can be used for treatment even if Vancomycin resistant strain is isolated. In their study 87.5% of patients on catheter with VRE responded to treatment with Ampicillin alone [25]. Another agent that holds hope in the face of VRE is Nitrofurantoin [26].

#### **9.3 Skin and soft tissue infections**

Enterococcus species are ubiquitous among the SSTIs due to trauma, surgical site infections (SSI), vascular ulcers and device associated infections. NHSN has released the SSI rates pathogen wise for the years 2015–2017 (**Figure 1**) [27].

Among SSTIs that are admitted in hospitals, a study from New Delhi, India, reports that out of 11,524 pus and tissue samples, 86 *Enterococcus* spp. were isolated. Of these, *E. faecium* (48/86, 56%) was the most common, followed by *E. faecalis* (34/86, 40%) and 4 (4%) of *Enterococcus casseliflavus*. Of these 8% were Vancomycin resistant. All VREs had history of prior hospitalisation and antibiotics use, however all were treated successfully with Linezolid or Quinupristin/Dalfopristin monotherapy [28].

In most studies, Vancomycin resistance is reported to be increasing and associated with hospitalisation, though one study reported community acquired Vancomycin resistant strains too [29, 30]. This increase has been variously

*Enterococcal Infections: Recent Nomenclature and Emerging Trends DOI: http://dx.doi.org/10.5772/intechopen.104792*

#### **Figure 1.**

*Enterococcus faecalis isolation rates in SSI in different surgical specialties as per CDC-NHSN 2015–2017 SSI data.*

attributed to prior antibiotic treatment and nosocomial spread due to poor hand hygiene and environmental cleaning practices.


**ELECTROMOTIVE FORCE AND MEASUREMENT IN SEVERAL SYSTEMS**

Edited by **Sadik Kara**

**INTECHOPEN.COM**

http://dx.doi.org/10.5772/2109 Edited by Sadik Kara

### **Contributors**

Mahammad Babanly, Yusif Yusibov, Nizameddin Babanly, Dong Wang, Kang Tianhe, Eduard Montgomery Meira Costa, Alexandr Vinogradov, Vladimir Vinogradov, Alexandr Agafonov, Anatoly Balmasov, Liana Inasaridze, Dominika Jendrzejczyk-Handzlik, Krzysztof Fitzner, Shigeji Fujita, Akira Suzuki, Irina Uspenskaya, Natalia Konstantinova, Elena Veryaeva, Mikhail Mamontov, Yuji Kurata

### **© The Editor(s) and the Author(s) 2011**

The moral rights of the and the author(s) have been asserted.

All rights to the book as a whole are reserved by INTECH. The book as a whole (compilation) cannot be reproduced, distributed or used for commercial or non-commercial purposes without INTECH's written permission. Enquiries concerning the use of the book should be directed to INTECH rights and permissions department (permissions@intechopen.com).

Violations are liable to prosecution under the governing Copyright Law.

Individual chapters of this publication are distributed under the terms of the Creative Commons Attribution 3.0 Unported License which permits commercial use, distribution and reproduction of the individual chapters, provided the original author(s) and source publication are appropriately acknowledged. If so indicated, certain images may not be included under the Creative Commons license. In such cases users will need to obtain permission from the license holder to reproduce the material. More details and guidelines concerning content reuse and adaptation can be foundat http://www.intechopen.com/copyright-policy.html.

### **Notice**

Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book.

First published in Croatia, 2011 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

Legal deposit, Croatia: National and University Library in Zagreb

Additional hard and PDF copies can be obtained from<EMAIL_ADDRESS>
Electromotive Force and Measurement in Several Systems Edited by Sadik Kara p. cm. ISBN 978-953-307-728-4 eBook (PDF) ISBN 978-953-51-6079-3


**4. Conclusions**

The effect of processing conditions in spray drying of blueberry juice and maltodextrin mixtures (BJ-MX) on content and retention of resveratrol was studied. Analysis of variance (ANOVA) showed that concentration (C) was the main variable influencing the content of resveratrol. Response surface plots (RSP) allowed observing that the content of resveratrol was also affected by the molecular weight distribution of MXs employed as carrying agents, where low molecular weight MX presented a higher content of resveratrol. With this study, it was possible to set the optimal processing conditions for spray drying of BJ-MX such as concentration of 23% of maltodextrin and temperature of 170 ◦C for CM, and 210 ◦C for M10. Additionally, the results reported herein were compared with those reported for content of quercetin 3-Q-galactoside, finding that quercetin 3-Q-galactoside was more readily to interact with MXs because of a higher availability of functional groups rather than by stearic hindrance effects.

**Author Contributions:** Conceptualization, C.L.-P. and M.Z.S.-L.; Data curation, E.C.-G.; Formal analysis, M.Z.S.-L. and P.A.-B.; Funding acquisition, M.Z.S.-L.; Investigation, C.L.-P., M.Z.S.-L. and P.A.-B.; Methodology, M.B.S.-C. and C.Á.-S.; Project administration, C.L.-P. and E.C.-G.; Software, E.C.-G.; Visualization, M.B.S.-C. and C.Á.-S.; Writing—original draft, C.L.-P. and M.Z.S.-L; Writing—review & editing, C.L.-P. and M.Z.S.-L.

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

**Acknowledgments:** The postdoctoral support managed by the Academic core "Chemistry and food technology, CA-259", through the Program for Teacher Professional Development (PRODEP) is gratefully acknowledge.

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


**3. Results**

In the following subsections the results obtained from the experimental tribotests and dimple dimensions nominal values assessment, the data pre-processing and the statistical analysis of textures dimensions are detailed.


2.8.7. Endogenous Hormones (IAA, SA, and ABA) Contents

Plant hormones are natural organic compounds that affect growth and metabolism, affecting all external manifestations and chemical reactions. These act as chemical signals to activate or inhibit plant growth. As mentioned in [47], the Indole acetic acid (IAA), Salicylic acid (SA), and Abscisic acid (ABA) contents were measured in the terminal buds of both treated and control plants.

### *2.9. Statistical Analysis*

Analyses were conducted using one-way variance (ANOVA). The statistically significant differences between treatments with a *p*-value of 0.05 or lower, the LSD test was used with CoStat (CoHort, Monterey, CA, USA) [48].


*Article* **Natural Radioactivity Measurements and Radiological Hazards Evaluation for Some Egyptian Granites and Ceramic Tiles**

**Essam Sidique 1,\*, Sedky H. A. Hassan 2,3 and Mohammad Mahmoud Dawoud 4,\***

**Abstract:** All over the world, people widely use granites and ceramic tiles in their residential establishments. Information concerning the radiological properties of such materials reveals how to ensure the sustainability of their safe use in terms of these properties. In the present work, the distribution of the terrestrial radioisotopes U-238 (Ra-226), Th-232, and K-40 for 23 different brands of Egyptian commercial granites and ceramic tiles samples (widely used domestically and exported) was determined using gamma radiation spectroscopy. This process pinpoints the possible radiological health risks related to gamma ray exposure and radon gas resulting from the use of these materials indoors. The concentration values of the aforementioned radioisotopes in the examined samples were compared to the corresponding global average values (GAVs) of the UNSCEAR and to those available in other countries. The overall average concentrations for U-238, Th-232, and K-40 in the total samples were observed to be 46.17 ± 2.81 (less than its GAV), 51.65 ± 2.35 (slightly above its GAV), and 701.62 ± 40.60 Bq/kg (1.4 times greater than the GAV), respectively. The related radiological parameters and indices were calculated and compared to the prescribed limits set by commissions and organizations concerned with radiation protection (the WHO, ICRP, UNSCEAR, and EC) to ensure the safe use of the investigated granites and ceramic tiles. The assessed indices and parameters fall within the recommended values and safety limits. In conclusion, there is no risk from using the granites and ceramic tiles under investigation in residential facilities.

**Keywords:** natural radioactivity; gamma rays; radon gas; radiation exposure; building materials; granites; ceramic

#### **1. Introduction**

For humans, exposure to natural ionizing radiation is unavoidable. Exposure arises primarily from both terrestrial and cosmogenic radioisotopes. Terrestrial radioisotopes (K-40, U-238, and Th-232) exist naturally in all different environmental media, including air, water, food, soil, rock, building materials, etc. [1–3]. The existence of the abovementioned radioisotopes in building materials is responsible for delivering about 85% of the radiation dosage to the world's population [3,4]. Accordingly, providing information on terrestrial radioisotope concentrations and distributions in building materials is essential and it is required to monitor contamination originating from their radioactivity in residential environments.

The natural radioactivity level in building materials is confined in the terrestrial radionuclide concentrations in the geological materials from which they are derived [4,5], i.e., it varies according to the geological origin and geochemical characteristics of the constituent materials. Additionally, the radiation dose received is controlled by several factors, including residences places ventilation, and kinds [1].

In fact, gamma rays and radon gas (Rn-222 and Rn-220) are the most significant products of the terrestrial radioisotopes' radioactivity in building materials, in light of the

**Citation:** Sidique, E.; Hassan, S.H.A.; Dawoud, M.M. Natural Radioactivity Measurements and Radiological Hazards Evaluation for Some Egyptian Granites and Ceramic Tiles. *Sustainability* **2022**, *14*, 14611. https://doi.org/10.3390/ su142114611

Academic Editor: Changhyun Roh

Received: 24 September 2022 Accepted: 30 October 2022 Published: 7 November 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 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 (https:// creativecommons.org/licenses/by/ 4.0/).

radiological hazards to the population [6]. Gamma rays are responsible for the external exposure of populations and their dose comes mainly from Tl-208 and Ac-228 of the Th-232 disintegration chain, from Pb-214 and Bi-214 derived from R-226 of the U-238 disintegration chain, and from K-40. On the other hand, radon gas (specifically Rn-222) which originates as a result of radium disintegration (Ra-226 of the U-238 chain), is responsible for the internal exposure [7]. According to the UNSCEAR [6], the average yearly external exposure indoors due to gamma rays was assessed as 0.41 mSv, while the internal exposure from Rn-222 inhalation was about 1.15 mSv. It is worth mentioning that several epidemiological investigations conducted in many countries have demonstrated substantial evidence linking raised levels of radon exposure in houses to an increased risk of lung cancer [8–10].

Construction materials that typically come from the soil and rocks of the earth may be categorized into three groups: structural materials, covering materials, and additive raw materials. Structural materials such as cement, concrete, mortar, and clay bricks, etc., are primarily used for building structures. The covering materials (granite, ceramic, marble, etc.) are employed for ornamentation and insulation purposes, whereas fly ash, bauxite, phosphogypsum, etc., are the additive raw materials used as optional components for modifying certain properties of building materials [1]. In light of global recommendations, determining the natural radioactivity levels of construction materials is crucial for assessing the radiological risks owing to radiation exposures as well as for developing national standards and guidelines for these materials. Recently, as a result of rising social concern, there has been a high worldwide interest in studying the natural radioactivity of construction materials as well as investigating their impact on the public (e.g., [4,5,11–20]). To the best of the authors' knowledge, important international studies on natural radioactivity measurements and radiological hazards evaluation for granites and ceramic tiles were published in the Refs. [1,2,9,18,19,21–39], just to name a few. Nevertheless, although granites and ceramic tiles of various brands are widely used in residences for interior and exterior ornamentation and decoration purposes in Egypt, no detailed studies have been conducted to determine the activity levels of terrestrial radioisotopes in these materials.

The present work investigates in depth the natural radioactivity of twenty-three wellknown Egyptian brands of commercial granites and ceramic tiles samples widely used in Egypt and abroad, as well as the potential health risks associated with their use indoors. Moreover, its overall goal is to complete a radiometric study on some sample Egyptian commercial granites and ceramic tiles which have not been previously covered. Hopefully, the findings of the present work and the accompanying assessments will establish baseline data for monitoring radioactive pollution in residential environments and will provide adequate public protection recommendations.

#### **2. Experimental Arrangements**

#### *2.1. Sample Preparation*

A total of 107 tile samples (42 granite samples plus 65 ceramic samples) from 23 different brands were purchased from Egyptian building materials markets and suppliers. The commercial ceramics and granites studied are among the best widely used decorative building materials brands in Egypt. Before transporting the samples to the lab, they were properly catalogued, labeled, and named according to their popular names known in both the global and domestic markets (Table 1). More detailed information, particularly for granite, is available at (www.stonecontact.com, accessed on 19 June 2022). The samples have been given identification numbers in brackets, which are (1 to 42) for granites, and (43 to 107) for ceramic tiles. Then, each sample was individually ground to a powder, to avoid contamination between samples, and sieved through a sieve (200 μm mesh). All the samples were oven-dried for 5 h at 105 ◦C to remove the moisture content. These prepared samples were subsequently weighed (between 600 g and 850 g) and sealed in plastic cylindrical beakers (48 mm radius, 82 mm height, and 0.5 mm thickness) for more than 4 weeks to guarantee access to the secular equilibrium between parent radioisotopes and daughters in the natural disintegration series (232Th and 238U).

**Table 1.** Granites and ceramic tiles of various brands used in Egypt.

#### *2.2. Gamma Spectrometric Analysis*

To measure the activity concentrations of the radioisotopes (γ-emitters) in the samples, a low-background γ-rays spectroscopy system consisting of a semiconductor HPGe (Hyper-Pure Germanium) detector (Model GR4020, Canberra, Meriden, CT, USA) with a 40% relative efficiency and energy resolution (FWHM) of 2 keV at the 1332 keV γ-line (Co-60) was used. In addition, the system contains a suitable lead shield (Model 747E, Canberra, USA) surrounding the detector to prevent more than 98% of the external background radiation from reaching the detector during the analysis. The gamma spectrums were acquired and analyzed utilizing the Genie-2000 software (Version 3.3, Canberra, USA) [40] coupled with a multichannel analyzer (Model DAS-1000, Canberra, USA). For calibrating the detector's energy and efficiency, the LabSOCS (Laboratory Sourceless Calibration Software) designed using the features of geometry composer and gamma analysis within the Genie-2000 software, was used. The Genie-2000 software also contains the detector's characterization files created based on the system manufacturer's fundamental calibration tests (Canberra). To authenticate the efficiency data provided by LabSOCS, measurements were completed in our laboratory with a set of gamma calibration sources (Co-60, Cs-137, Ba-133, Mn-54, Zn-65, and Na-22), which revealed a significant agreement (90%) between empirical and mathematical peak efficiency.

Each prepared sample was put on the detector for a time period no less than 12 h in order to obtain an accurate counting statistic for gamma lines (photo-peaks) of importance. Additionally, the background level in the laboratory was measured using an empty beaker in similar conditions. The K-40 radionuclide was determined directly by its own gamma line intensity (1460.8 keV). As for U-238 (Ra-226), it was specified through its progeny Bi-214 (1764.5, 1120.3, and 609.3 keV) and Pb-214 (351.9 and 295.2 keV). On the other hand, Th-232 was identified via its daughters Ac-228 (968.9, 911.2, and 338.3 keV), Tl-208 (2614.5 and 583.2 keV), and Pb-212 (238.6 keV). The activity concentration (AC) and the uncertainty in activity concentration (UAC) of the previously mentioned radionuclides in each sample were calculated from their corresponding gamma line intensities taking into account the sample mass, counting time, gamma decay transition probabilities, and detector efficiencies [41–43].

Activity Concentrations Estimation

The activity concentration (AC) in the granites and ceramic tiles samples under investigation was estimated as follows [41]:

$$\text{AC}[\text{Bq}/\text{kg}] = \frac{\text{N}\_{\text{c,E}}}{\text{P}\_{\text{y,E}} \cdot \text{\textdegree\:E} \cdot \text{M}\_{\text{s}}} \tag{1}$$

where Nc,E is the net count rate resulting from subtracting the count rate of the peak at energy E in the sample spectrum minus that of the background spectrum at the same energy E, Pγ,E denotes the probability of emitting gamma radiation with energy E for the radioisotope of interest, εE is the detector absolute efficiency at energy E, and Ms refers to the sample mass. Moreover, using the equation below, the uncertainty in activity concentration, UAC, was calculated based on uncertainties in Nc,E, Pγ,E, εE, and Ms [43]:

$$\mathbf{U\_{AC}} = \mathbf{AC}\sqrt{\left[\frac{\mathbf{U\_{N\_{cE}}}}{\mathbf{N\_{c,E}}}\right]^2 + \left[\frac{\mathbf{U\_{P\_{y,E}}}}{\mathbf{P\_{y,E}}}\right]^2 + \left[\frac{\mathbf{U\_{c\_E}}}{\varepsilon\_E}\right]^2 + \left[\frac{\mathbf{U\_{M\_b}}}{\mathbf{M\_s}}\right]^2} \tag{2}$$

#### **3. Estimation of Radiological Risks**

For understanding the effect of radiological hazards on human health when using the investigated granites and ceramic tiles as tiling materials in buildings, several radiation hazard indices were estimated. The radium equivalent activity (Raeq), gamma index (Iγ), indoor absorbed gamma dose rate (D*in*), yearly effective gamma dose rate (E*in*), and excess lifetime cancer risk (ELCR) were used to investigate gamma radiation risks, while the alpha index (Iα), radon exhalation rate (RX), radon concentration (CRn), and yearly effective dose due to radon (ERn) were evaluated in order to investigate the potential radon risks.

#### *3.1. Radium Equivalent Activity (Raeq)*

The Raeq is one of the most effective radiological indices for determining gamma radiation hazards due to the radioisotopes K-40, U-238 and Th-232 content in tiling materials, considering the non-uniform distribution of these radioisotopes in matter. As per Beretka et al. [44], Raeq is described by the following equation:

$$\text{Raq}\left[\text{Bq kg}^{-1}\right] = \left(\frac{\text{AC}\_{\text{U}}}{370} + \frac{\text{AC}\_{\text{Th}}}{259} + \frac{\text{AC}\_{\text{K}}}{4810}\right) \times 370 \tag{3}$$

where ACU, ACTh, and ACK are the specific activity concentrations of the radioisotopes U-238 (Ra-226), Th-232, and K-40, respectively. In fact, the Raeq reflects the weighted total of the abovementioned three radioisotopes' concentrations within materials under the premise that gamma dose rates from 4810 Bq/kg of K-40, 259 Bq/kg of Th-232, and 370 Bq/kg of U-238 (Ra-226) are almost equal.

From a radiation protection perspective, the ceramic and granite tiles studied herein are safe provided that their Raeq levels are not above 370 Bq/kg [44] (permissible limit) corresponding to a yearly effective dosage of 1.5 mSv [41,45].

#### *3.2. Gamma Index (I*γ*)*

The Iγ is taken into consideration as a monitoring tool specifying whether construction materials are safe to use or not. Considering that the external exposure due to gamma radiation from the tiling (superficial or covering) materials has a limit of 1 mSv/year, the Iγ is adopted by the European Commission [46] to be estimated via the following equation:

$$\mathrm{I}\_{\mathrm{Y}} = \frac{\mathrm{AC}\_{\mathrm{U}}}{\mathrm{300 \,\mathrm{Bq\,\,kg^{-1}}}} + \frac{\mathrm{AC}\_{\mathrm{Th}}}{\mathrm{200 \,\mathrm{Bq\,kg^{-1}}}} + \frac{\mathrm{AC}\_{\mathrm{K}}}{\mathrm{3000 \,\mathrm{Bq\,kg^{-1}}}} \tag{4}$$

According to the European Commission [46], for covering materials such as the ceramic and granite tiles under investigation, if they have a Iγ ≤ 2, this leads to an increase in the annual gamma dose rate with an amount ≤ 0.3 mSv/y resulting from these materials. In other words, these materials fall within the exemption level for building materials from all limitations about their radioactivity. Furthermore, if materials achieve criteria2<Iγ ≤ 6, they will contribute to the annual gamma dose rate with an amount ≤ 1 mSv/y and fall within the recommended action level. Eventually, materials with Iγ > 6 are not suitable for safe use in buildings [46].

#### *3.3. Indoor Absorbed Gamma Dose Rate (D*in*) and Yearly Effective Dose (E*in*)*

Estimation of the indoor absorbed gamma dose rate (D*in*) and its associated yearly effective dose (E*in*) are significant mechanisms for determining the external exposure caused by terrestrial radioisotopes (Th-232, U-238, and K-40). According to the European Commission [46], Equations (5) and (6) can be used to estimate the D*in* and E*in* in the air within rooms as a result of using the investigated granites and ceramic tiles as superficial construction materials:

$$\mathrm{D}\_{\mathrm{in}} \left[ \mathrm{nGy h}^{-1} \right] = \left( 12 \mathrm{AC}\_{\mathrm{Ra}} + 14 \mathrm{AC}\_{\mathrm{Th}} + 0.96 \mathrm{AC}\_{\mathrm{K}} \right) \times 10^{-2} \tag{5}$$

$$\mathrm{E}\_{\mathrm{in}}\left[\mathrm{mSvy}^{-1}\right] = \mathrm{D}\_{\mathrm{in}}\left[\mathrm{nGyh}^{-1}\right] \times \mathrm{F}\_1 \times \mathrm{F}\_2 \times \mathrm{F}\_3 \times 10^{-6} \tag{6}$$

where F1 (=0.7 Sv/Gy), F2 (=0.8), and F3 (=8766 h) represent the conversion factor from the absorbed dose to the effective dose in the air, indoor residency factor, and hours of the year, respectively.

#### *3.4. Excess Lifetime Cancer Risk (ELCR)*

The ELCR is an important quantity through which the incidence of cancer for an individual exposed to a low gamma radiation dose over their lifetime (66-years) can be figured out. Depending on the E*in* incurred by individuals from the studied ceramic and granite tiles (superficial building materials) when used in buildings, the ELCR can be estimated as follows [4,41]:

$$\text{ELCR} = \text{E}\_{in}[\text{Sv/y}] \times \text{C}\_1 \times \text{C}\_2 \tag{7}$$

where C1(=66 y [47]) and C2 (=0.05 Sv−1 for the general population) stand for life expectancy on average and fatal cancer risk, respectively [42,48].

#### *3.5. Alpha Index (I*α*)*

The Iα given by the equation below [41] is used for estimating the risk of exposure to internal alpha radiation owing to the inhalation of radon. The estimation of Iα is fundamentally dependent on the U-238 (Ra-226) activity concentration (ACRa) in construction materials, considering that materials with a concentration of 226Ra < 200 Bq kg−1 cannot emit an indoor radon concentration >200 Bq m−3, i.e., these materials come within the range of the recommended action level of indoor radon exposure for buildings, as previously agreed upon by the European Commission [46] and ICRP [49].

$$\mathcal{I}\_{\alpha} = \frac{\text{AC}\_{\text{Ra}}}{200 \text{Bq } \text{kg}^{-1}} \le 1 \tag{8}$$

#### *3.6. Radon Concentration (CRn) and Yearly Effective Dose Resulting Therefrom (ERn)*

In this study, the parallelepiped room model (4 × 5 × 2.8 m) is taken into account to assess the concentration of radon and the associated absorbed dose rate delivered to residents, assuming the floor is made of the investigated ceramic or granite tiles. Thus, Equation (9) is applied, according to the European Commission [46], to determine the

increase in indoor radon concentration (CRn) brought on by the radon exhalation rate (RX) from the investigated ceramic or granite tiles used in buildings:

$$\mathbf{C\_{Rn}} \left[ \mathbf{B\_{q}} \,\mathrm{m}^{-3} \right] = \frac{R \mathbf{X} \cdot \mathbf{S}}{(\lambda + \lambda\_{o}) \cdot V} \tag{9}$$

where *RX* [Bq m−2 h−1], *λ* (=0.0076 h−1), *λo* [h−1], *S* [m2], and *V* [m3] represent the radon exhalation rate per unit area, Ra-226 decay constant, ventilation rate, tiled floor surface, and volume of the room, respectively. Based on the determined Ra-226 concentration (ACRa), Equation (10) can be applied to estimate the RX for the investigated tiles with thickness *d* (=3 cm and 1 cm for granites and ceramic tiles, respectively), density *ρ* (=2600 kg/m3), and emanation coefficient *η* (=0.45), as reported in Refs. [20,41,50]:

$$RX = \text{AC}\_{\text{Ra}} \cdot \lambda \cdot \rho \cdot \eta \cdot d \cdot 0.5 \tag{10}$$

It is worth noting that the room ventilation rate (*λo*) was chosen with 0.5 h−1 for normal ventilation and 0.1 h−1 for poor ventilation. [9,41]. Furthermore, the (*S/V*) ratio of the room surface tiled with the investigated ceramic and granite tiles was chosen to be 2 m−1 [41].

As per the UNSCEAR [6] report, the yearly effective dose (ERn) that dwellers obtain from the indoor radon concentration (CRn) was estimated by the following formula:

$$\mathrm{E\_{Rn}}\left[\mathrm{mSv\,y^{-1}}\right] = \mathrm{C\_{Rn}}\left[\mathrm{Bq\,m}^{-3}\right] \times \mathrm{C\_1} \times 8766 \left[\mathrm{h\,y^{-1}}\right] \times \mathrm{C\_2} \times \mathrm{C\_3} \times 10^{-6} \tag{11}$$

where C1 (=9 nSv per Bq m−3 h), C2 (=0.8), and C3 (=0.4) stand for the factors of dose conversion, dwellers' indoor residency, and equilibrium equivalent radon concentration indoors, respectively [6,51].

#### **4. Results and Discussion**

#### *4.1. Radioisotope (238U, 232Th, and 40K) Concentrations*

Table 2 displays the ranges and averages, as well as standard errors, for the estimated concentrations values of U-238 (Ra-226), Th-232, and K-40 in the granites and ceramic tiles collected. Furthermore and by way of illustration, Figure 1 depicts the variations of the abovementioned radioisotopes concentrations in the samples under examination. Evidently, Figure 1 and Table 2 show that the concentrations of the considered radioisotopes fluctuate from 8.40 ± 2.09 in GBiH (sample No. 3) to 196.01 ± 37.84 Bq kg−1 in GRSS (sample No. 28), 11.62 ± 1.28 in GBiH (sample No. 3) to 140.32 ± 27.41 Bq kg−1 in GRSS (sample No. 28), and 141.01 ± 12.83 in CAR (sample No. 52) to 1785.78 ± 125.00 Bq kg−1 in GRN (sample No. 35) for 238U, 232Th, and 40K, respectively. Conceivably, the observed variations in radioisotopes' concentrations could be attributed to the samples' various origins and compositions. Evidently, most of the ceramic samples (samples No. 43 to 107) have lower concentrations of the three radioisotopes (U-238, Th-232, and K-40) than those of the granite samples (samples No. 1 to 42). This materializes the granite's naturally high level of terrestrial radioisotopes [3].

**Figure 1.** U-238, Th-232 and K-40 concentrations in the investigated granites and ceramic tiles samples.

Regarding the mean values of the radioisotope concentrations inserted in Table 2 and plotted in Figure 2, it is clear that CVE samples contain the lowest mean concentrations of both K-40 and Th-238, with levels of 269.36 ± 13.15 and 32.96 ± 1.94 Bq/kg, respectively, while GBiHa samples have the lowest mean concentration of U-238 with a level of 16.95 ± 4.90 Bq/kg. In contrast, GRSS samples appear to have the highest mean concentrations of both U-238 and Th-232, with levels of 174.55 ± 11.38 and 131.07 ± 5.20 Bq/kg, respectively, whereas, GBrHu samples have the highest mean concentration of K-40, with a level of 1695.38 ± 37.21 Bq/kg.

**Figure 2.** Comparison of the average values of U-238 (Ra-226), Th-232 and K-40 in the investigated ceramic and granites tiles to their corresponding GAVs in the building materials.

Figure 2 and Table 2 also display the mean values of the aforementioned radioisotope concentrations in the materials under investigation against their corresponding global average values (GAVs) in building materials as given by the UNSCEAR [52]. Notably, the GAVs for U-238, Th-232, and K-40 in building materials are 50, 50, and 500 Bq/kg, respectively, according to the UNSCEAR [52]. Apparently, the mean concentration of U-238 in all granites and ceramic tiles samples herein, except for GBrHu, GKG, GRHL, GRSS, and GRN samples, is lower than its GAV of 50 Bq/kg in building materials [52], (Figure 2 and Table 2). Similarly, the average concentration of Th-232 in the investigated samples, except for the GBrHu, GNA, GRAD, GRHL, GRAS, GRSS, GRA, GRN, GRF, and CAR samples, is lower than its GAV in building materials of 50 Bq/kg [52]. However, the average concentration of K-40 for all of the granite and ceramic brands, except for the CAL, CCL, CGL, CPH, CRO, and CVE samples, is greater than the GAV (500 Bq/kg) of building materials [52], (Figure 2 and Table 2).

The overall average concentrations for U-238, Th-232, and K-40 of the total samples were observed to be 46.17 ± 2.81 (less than its GAV), 51.65 ± 2.35 (slightly above its GAV), and 701.62 ± 40.60 Bq/kg (1.4 times greater than the GAV), respectively, as demonstrated in Table 2 and Figure 2. Moreover, in all of the investigated brands' samples (Figure 2), the K-40 concentration is the greatest among the concentrations of the three studied radionuclides, as the granites contain about 33% potash feldspar minerals [21]. Moreover, it was found that the K-40 concentration is the largest contributor to the total concentration for all samples (Figure 3). Both U-238 and Th-232 contribute roughly the same percentage (6%), to the overall concentration of samples, while K-40 contributes a larger percentage (88%), as shown in Figure 3.

**Figure 3.** Contributions of the three radioisotopes, 238U, 232Th, and 40K, to the studied samples' overall concentration.

A comparison between the radioactivity levels in the studied samples and those in other previous relevant studies on granites and ceramics used in Egypt and other countries is illustrated in Table 3. From Table 3, one can deduce that many of the data from the relevant literature are comparable to our findings. This can be confirmed using the dendrogram (Figure 4) derived from the hierarchical cluster analysis (HCA) based on the three variables (U-238, Th-232, and K-40 concentrations). In HCA, the cluster method between-groups linkage is used coupled with the square Euclidean distance. Accordingly, the countries in which the studies were accomplished have been divided into homogeneous groups based on the similarity in concentrations of the three radionuclides (U-238, Th-232, and K-40) (Figure 4). Figure 4a shows that the Egyptian granite tiles studied herein come close to the granites used in Bangladesh [22] and Nigeria [2] in terms of the content of the three aforementioned radionuclides, as they were grouped into a homogeneous group. However, they are far from those used in Pakistan [25], as illustrated in Figure 4a. Likewise, Figure 4b exhibits that the ceramic tiles examined herein are matched to the ceramics used in Italy [23] and Egypt [30] but are very different to those used in Poland [37], Serbia [9], and Nigeria [2] in terms of radionuclide content.

**Table 3.** The radioisotopes concentrations (present study) in comparison to other similar previous international research.

**Figure 4.** The dendrogram for comparing the Egyptian granites and ceramic tiles investigated herein with those used in Egypt and other countries in terms of the natural radioactivity.

Evidently, in many of the investigated granite and ceramic samples, the radioisotopes' displayed concentrations were more elevated than the GAVs (Figure 2). For instance, in granites of "Rosa Sardo Sinai" (GRSS) samples, concentrations of uranium, thorium, and potassium exceed their corresponding GAVs by about three times, confirming the previous study on the granite of the Sinai area by Fares [39]. Therefore, it was crucial to assess the likely radiological risks to peoples' health owing to the use of these materials in buildings.

#### *4.2. Gamma Radiation Impact Estimation*

Table 4 displays some of the evaluated radiological variables for the granite and ceramic samples under consideration. Through the estimated Req, Iγ, D*in*, E*in*, and ELCR (Table 4), the gamma ray hazards posed by the materials under investigation when used as tiling in buildings can be judged. It was found that all Raeq values in the samples of ceramic tiles fell within ranges below the threshold standard of 370 Bq/kg [44]. Similarly, the Raeq values for all the samples of the investigated granite tiles were in ranges lower than the criterion limitation of 370 Bq/kg, with the exception of three samples (No. 27 to 29) of GRSS and two samples (No. 33 and 35) from GRN samples. Furthermore, the mean Raeq values varied between 100.96 Bq/kg in the CVE samples and 463 Bq/kg in the GRSS samples, with an overall mean of 174.06 Bq/kg. Accordingly, the granites and ceramic tiles of the different brands herein don't constitute any considerable radiological risks for individuals when used as tiling materials, except for the GRSS samples which may be a cause for concern due to the mean value of Raeq going beyond 370 Bq/kg (recommended value) (Figure 5a).

**Table 4.** Ranges and mean values of the radiological parameters showing the gamma impact of the studied granite and ceramic brands.

a GAV given by the UNSCEAR [3]. b GAV reported by the European Commission [46]. c GAV indicated by Sidique et al. [41] and Qureshi et al. [53].

**Figure 5.** The radiological parameters showing the gamma impact from the ceramic and granite tiles of the brands under investigation.

According to the calculated values of Iγ (Table 4), none of the values in the samples under investigation go beyond the exemption limit of 2. This implies that the yearly effective gamma dose resulting from the investigated materials herein when used as covering or superficial building materials indoors is less than 0.3 mSv/y (exemption limit indicated by the European Commission [46]). Thus, the granites and ceramic tiles of the brands under investigation are suitable for use without any restrictions. Furthermore, and by way of illustration, Figure 5b displays the estimated mean values of Iγ for the granites and ceramic tiles where they do not go beyond their allowable limit, indicating that all of the investigated materials do not raise any cause for concern when used in buildings.

Considering the estimated D*in* and E*in* values for the samples under investigation (Table 4), neither the granites nor the ceramic samples of the various brands examined herein had D*in* and E*in* values going beyond their corresponding worldwide average values of 84 nGy/h and 0.41 mSv/y [3] and of 70 nGy/h and 1 mSv/y [46]. Notably, the mean values of D*in* and E*in* for the studied granites and ceramic tiles compared with the corresponding global average values (GAVs) are illustrated in Figs. 5c and 5d, where they are below the adopted limits, reflecting their safe use.

The indoor ELCR values based on E*in*, as well as their mean values in the granites and ceramics under investigation, are shown in Table 4 and plotted in Figure 5e. Evidently, all the ELCR values are within the range of 0.07 to 0.91, with an overall mean of 0.32. Namely, the mean ELCR values in all the brands of tiling materials are less than their corresponding GAV of 1.16 indicated by Sidique et al. [41] and Qureshi et al. [53], as shown in Figure 5e. Thus, in buildings where the materials under investigation are used, over a 66-year lifespan, their residents are at a very insignificant risk of developing cancer resulting from exposure to gamma rays emitted by these materials.

#### *4.3. Radon Impact Assessment*

The potential radon (Rn-222) risks posed by the studied materials when used as tiles in buildings can be investigated through the estimated Iα, RX, CRn, and ERn. For the samples of each brand, Table 5 displays ranges and averages of Iα, RX, CRn, and ERn values, while Figure 6 compares averages of these parameters with their corresponding allowable limits. Table 5 reveals that the Iα values oscillate between 0.04 and 0.98, with an overall mean value of 0.23. Furthermore, no mean value of Iα for any of the brands' samples under investigation goes beyond the unity, as shown in Figure 6a. Thus, arguably, the materials under consideration come under the range of the indoor radon safe exposure action level for buildings, as indicated by the European Commission [46] and ICRP [49].

**Figure 6.** The radiological parameters showing the Rn impact from the studied ceramic and granite tiles.

**Table 5.** Ranges and mean values of the radiological parameters showing the Rn impact of the studied granite and ceramic brands.

a GAV reported by the ICRP [49]. b GAV declared by the UNSCEAR [3]. c GAV recommended by the WHO (World Health Organization) [8].

Regarding the mean values of the radon exhalation rate (RX) for the samples under investigation (Table 5 and Figure 6b), they stretch between 1.44 Bq/m2 h in the CGL samples and 23.28 Bq/m2 h in the GRSS samples, with an overall mean value of 4.09 Bq/m2 h. Moreover, no mean value of RX for samples of any brand of ceramic or granite exceeds the global average value (GAV) of 57.6 Bq/m2 h (0.016 Bq/m2 s) as declared by the UNSCEAR [3], as shown in Figure 6b. It is therefore expected that the materials under investigation do not constitute any health risks to dwellers.

Based on the RX values, the indoor radon concentration (CRn) was assessed from the indirect mathematical model of a typical residence room tiled by the studied ceramics and granites in both poor and normal ventilation cases as per Equation (9). Accordingly, for the room model with normal ventilation, the mean values of CRn of granites and ceramics from the different brands under investigation fluctuate between 5.67 Bq/m3 in the CGL samples to 91.73 Bq/m3 in the GRSS samples, with an overall mean value of 16.13 Bq/m3 (Table 5 and Figure 6c). Consequently, for the normal ventilation case, none of the mean values of CRn in the studied brands of granites and ceramic tiles, as shown in Figure 6c, go beyond the acceptable range (100–300 Bq/m3) declared by the WHO (World Health Organization) [8]. On the other hand, for the room model with poor ventilation, the mean values of the CRn of granites and ceramics from the brands under examination oscillate between 26.75 Bq/m3 in the CGL samples and 432.75 Bq/m3 in the GRSS samples, with an overall mean value of 76.08 Bq/m3 (Table 5 and Figure 6c). Thus, for the poor ventilation case, none of the mean values of CRn in the studied brands of ceramics and granites, as shown in Figure 6c, exceed the acceptable range (100–300 Bq/m3) declared by the WHO [8], except for GRSS which as a result is not recommended for poorly ventilated buildings.

Regarding the yearly effective dose rate (ERn) due to radon concentration (Table 5 and Figure 6d), the mean values span a range from 0.14 mSv/y in the CGL samples to 2.32 mSv/y in the GRSS samples, with an overall mean value of 0.41 mSv/y in the case of normal ventilation. Moreover, all of these values fluctuated below the acceptable range of 3–10 mSv/y documented by ICRP [49], (Figure 6d). On the other hand, for the poor ventilation case, the mean values of ERn for the granites and ceramics from the different brands under investigation stretch between 0.68 mSv/y in the CGL samples to 10.93 mSv/y in the GRSS samples, with an overall mean value of 1.92 mSv/y. Furthermore, as shown in Figure 6d for poor ventilation, the granite from the brand GRSS is the only one that has a mean value of CRn going beyond the recommended range of 3–10 mSv/y [49]. Therefore, it is not recommended for poorly ventilated rooms.

The hierarchical cluster analysis (HCA) coupled with the Pearson correlation method was performed to effectively prove the relationship among all considered radiological variables. The dendrogram obtained from the HCA shows the relationship between the radionuclide concentrations and the relevant radiological parameters (Figure 7). Depending on the similarities in existence, all considered variables are gathered into two principal clusters. Cluster I comprised U-238 and Th-232 concentrations as well as all radiological parameters with a highly similar correlation (Figure 7). This reflects that the slight radioactivity level arising in both of the examined granites or ceramic tiles is ascribable to U-238 and Th-232 concentrations. On the other hand, cluster II is only comprised K-40, reflecting the weak relationship of K-40 with the radiological parameters, i.e., despite the high concentration of K-40 in the examined granites and ceramic tiles, K-40 contributes very little to the radioactivity level.

**Figure 7.** The dendrogram for exhibiting the relationship among the studied radiological variables of the granites and ceramic tiles under consideration.

#### **5. Conclusions**

A radiological evaluation for 23 well-known brands of Egyptian commercial granites and ceramic tile samples was performed for hazard and dose estimations. A total of 107 samples representative of the materials under investigation were analyzed using a HPGe detector. The terrestrial radionuclides (U-238 (Ra-226), Th-232, and K-40) concentrations in the investigated samples together with their radiological indices (Raeq, Iγ, D*in*, E*in*, ELCR, Iα, CRn, ERn) were determined. It was found that the concentrations of the aforementioned radioisotopes were higher in most of the granite samples than in the ceramic samples. Furthermore, the concentration values of the terrestrial radionuclides indicated significant differences in the granite and ceramic tile samples collected from the different brands. This is significant in differentiating between the considered brands. K-40 concentration was found to be the biggest contributor to the total concentration for all samples, followed by Th-232 and U-238. Generally, the terrestrial radioisotope concentrations in the materials under investigation are comparable to many of those from the relevant literature and come within the worldwide range. Although the average concentration values for K-40 and Th-232 were higher than their GAVs, the obtained results for the majority of the radiological parameters showed that the studied granites and ceramic tiles are safe to use indoors except "Rosa Sardo Sinai" granite (GRSS). The GRSS samples go beyond the recommended values in terms of their high radium equivalent (Raeq) mean values, and indoor radon concentration (CRn), as well as their associated yearly effective dose rate (ERn) in poorly ventilated buildings, which may be a cause for concern. Therefore, it is not recommended for poorly ventilated buildings. In line with the HCA conducted herein, it reflects the weak relationship of K-40 with all different radiological parameters without exception. In other words, the insignificant risk levels originating from the use of the concerned granites and ceramic tiles are principally due to Th-232 and U-238, with only a weak contribution of K-40.

Our data herein are important for two reasons: firstly, they may raise awareness among the general population of the natural radioactivity of the materials under investigation, and secondly, they are required for developing the standards, rules, and management of tiling materials used in Egypt and in any other country to which such materials are exported.

**Author Contributions:** All the authors contributed to the conception of the study, study design, methodology, data analysis, validation, writing of the original draft, revision of the manuscript, and final publication. All authors have read and agreed to the published version of the manuscript.

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

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors sincerely thank Mervat A. Elhaddad, Department of Geology, Faculty of Science, Assiut University, Egypt, for her support during the editing and revision of this research article.

**Conflicts of Interest:** The authors declare that they have no competing interest.

#### **References**


**1. Introduction**

Violence and conflicts across the Shia–Sunni divide have increased during the last decades. In fact, a disproportionate share of battle-related deaths falls upon armed conflicts that occur along the Shia–Sunni fault line (Finnbogason et al. 2019). Previous research has demonstrated how the increase of violent identity politics, by political elites and authoritarian leaders in the Middle East, but also in other parts of the wider Muslim world, has reactivated intra-Muslim tensions that had laid dormant (Abdo 2017; Byman 2014; Hinnebusch 2016; Larsson 2016). A well-established scholarly consensus recognizes that tensions between Shia and Sunni communities are not cases of primordial "ancient hatred" but rather that recently, these historical group identities have been instrumentalized by various political actors to maximize political gains and influence (Ahmed 2011; Behuria 2004; Hasheemi and Postel 2017; Nasr 2007; Wehrey 2017). The Shia and Sunni communities can be seen as what Benedict Anderson labeled "imagined communities," a concept that was originally developed to describe the socio-cultural construction of nationalism (Anderson 2006). In the Middle East, the regional rivalry between Saudi Arabia and Iran has been crucial in fomenting sectarian tensions, as their governments have utilized identity politics as measures to improve dominance and influence in a multi-sectarian region (Salloukh 2017). Moreover, the so-called Islamic State (IS) has carried out a brutal campaign against Shia Muslims across several countries outside the Middle East. Although the Shia–Sunni rift is only one divide in a region plagued by many multi-layered social conflicts (Phillips and Valbjørn 2018), it has risen to become the main identity cleavage in the Middle East: "Today, although there are myriad sects and forms of religious identity in the Middle East, the overarching intra-Islamic Shi'a-Sunni divide is the 'master cleavage' [ ... ]" (Sisk 2017, p. 266).

However, relatively little scholarly attention has been paid to contemporary institutional attempts to bridge this divide. We do not wish to add to the vast amount of research on the causes of conflict, but rather focus on their management. Our study builds upon what we identify as the puzzle of the Shia–Sunni interreligious dialogue deficit in contemporary politics. While the UN and other major international organizations have made dialogue, mediation, and peacebuilding e fforts in some of the most violent conflicts with a Shia–Sunni dimension, organizations specialized in interreligious dialogue and peacemaking have yet to play a role here. As we will show in this article, although there are some historical examples of dialogue between Sunni and Shia Muslims from the 20th century, these initiatives are no longer active. Thus, we do not know how, and to what extent, interreligious dialogue and peacemaking occur across the Shia–Sunni divide.

A note on the terminology and scope of this study is needed before we proceed. There is no consensus as to what exactly terms such as "interreligious peacemaking," "interreligious dialogue," or "interfaith cooperation" capture. For instance, Cheetham et al. (2013, p. 1) criticize that many authors use the terms "interreligious dialogue" and "interreligious relations" interchangeably, ignoring the fact that they capture different things. The authors view dialogue as one form of relational engagement within the field of interreligious relations. Cornille and Corigliano (2012, p. 1) define interreligious dialogue as a category that implies "the engagement between different religious traditions oriented toward mutual understanding and growth." Accordingly, Cornille (2013, p. xii) distinguishes interreligious dialogue from other forms of interreligious interaction, such as neutral religion studies, or traditional apologetics, as a form of "constructive engagement between religious traditions."

Here, we examine interreligious peacemaking attempts to bridge the Shia–Sunni divide, incorporating but not limiting our attention to interreligious dialogue. Instead, we look more specifically at the institutional perspective: interreligious peacemaking initiatives tailored to conflicts between Shias and Sunnis. Nonetheless, more research is needed to shed light upon existing local strategies to foster dialogue between Shias and Sunnis in violent conflicts.

By exploring intra-Muslim sectarian tensions, peacemaking across the Shia–Sunni divide, and challenges for religious identity politics, our study aims to set an agenda for a reinvigorated research endeavor into the contemporary challenges for interreligious peacemaking and dialogue. As sectarian tensions between Shias and Sunnis can be locally anchored but also transcend existing national boundaries, there is a regional perspective to Shia–Sunni tensions. Besides this dimension, future research should also consider the question of time, i.e., when do conflicts occur and under what conditions are Shia–Sunni divisions utilized, and when do they cease to have a rationale for spurring continued conflicts.

We seek to contribute to the development of a research agenda for how to address the puzzle of the Shia–Sunni peacemaking deficit. After situating the latter against a backdrop of increasing levels of violence that have included a sectarian dimension, this article proceeds by discussing what we consider to be the three most potent potential hypotheses for how this puzzle may be understood. First, we discuss the possibility that Shia–Sunni dialogue does not exist because Shia–Sunni tensions are epiphenomenal and there is, in essence, no Shia–Sunni divide to bridge in the first place. Second, we discuss whether the lack of Shia–Sunni dialogue is simply a reflection of interreligious dialogue,

as such, being a Western, Christian innovation that carries little weight in the Middle East and the wider Muslim world. Third, we discuss the possibility that the apparent lack of Shia–Sunni dialogue can be explained by arguing that dialogue and peacemaking occur through other institutional channels or informally through local actors, for example tribal leaders, village elders, or other local authorities. Of these three explanations, our analysis suggests that the third and last is most promising and warrants further attention. By examining these three hypotheses, we take the historical trajectory of Shia–Sunni "ecumenical" developments into account, as well as the track record of the intergovernmental approaches to conflicts across this divide and how the divide has been shaped by the inter-state rivalry between Iran and Saudi Arabia and their proxy wars in the Middle East. While this study aims to set a research agenda, by identifying and discussing what we argue to be an under-studied and little noted puzzle of a lack of institutional attempts to engage in interreligious dialogue in Shia–Sunni conflicts, we do not aspire to provide the full answer to solve this puzzle. Our discussion around the potential explanations should be seen as explorative, and the hypotheses are not necessarily mutually exclusive. The exploration of these potential explanations may hopefully enlighten further discussion and pave the way for a closer examination as to why there is so little institutional religious dialogue along the Shia–Sunni dimension, when the need for such dialogue is, as we suggest, evident.

### **2. Presenting the Puzzle: The Deficit of Shia–Sunni Dialogue**

### *2.1. The Increasing Levels of Violence with Shia–Sunni Dimensions*

Before discussing three hypotheses about what could help explain the apparent lack of Shia–Sunni dialogue, it is important to illustrate why we consider such dialogue to be necessary in the first place. Haddad (2014, 2017) has criticized what he describes as an indifferent and inflationary use of the term "sectarianism" in the regional context of the Middle East. In particular, he highlights the common failure to distinguish between the social, political, and religious dimensions that can create tensions between Shia and Sunni communities. Against this background, our study departs from the recognition that violence across the Shia–Sunni divided has increased substantially over time. Finnbogason et al. (2019) provide a conceptual framework of different sectarian dimensions of armed conflicts. Their empirical analysis, which builds upon the Religion and Armed Conflict (RELAC) dataset (Svensson and Nilsson 2018) on the religious dimensions of state-based conflict, as well as the Uppsala Conflict Data Program (UCDP) on one-sided violence (Eck and Hultman 2007) and non-state conflicts (Sundberg et al. 2012), demonstrates how levels of violence with different Shia–Sunni dimensions have increased over the last two decades. The authors distinguish between three dimensions of Shia–Sunni conflict: an identity-dimension, an alliance dimension, and an ideological (explicitly sectarian) dimension. Since 2014, an increasing number of fatalities has occurred in conflicts that share at least two such Shia–Sunni dimensions, and a notable share of these fatalities occurred in conflicts that shared all three Shia–Sunni dimensions (Finnbogason et al. 2019, p. 45). In other words, armed conflicts with multiple Shia–Sunni conflict dimensions have become increasingly violent in recent years.

In general, although armed conflicts with Shia–Sunni dimensions are relatively rare, if compared to the overall number of armed conflicts, their share of fatalities in organized violence has increased dramatically over the past decade: since 2011, the share of fatalities in organized violence with at least one Shia–Sunni identity dimension, of the total number of all fatalities in organized violence worldwide, lay at least above 40 percent (Finnbogason et al. 2019, p. 42). To a substantial extent, this high share can be explained by the Syrian Civil War, which includes multiple Shia–Sunni dimensions, as well as the growth of the so-called Islamic State and its violent campaign against Shia Muslims in several countries around the globe. Still, organized violence with Shia–Sunni dimensions also occurred elsewhere, for instance between tribal groups in Pakistan, and in the context of the ongoing civil war in Yemen (Finnbogason et al. 2019). Thus, although it should be noted that much of the organized violence with Shia–Sunni dimensions can be traced back to other contentious issues that may be partly overlapping with sectarian questions, the empirical trajectory of armed conflicts in the Middle East and parts of the wider Muslim world substantiates the claim that the Shia–Sunni divide constitutes a prominent cleavage in contemporary conflicts and that it has become increasingly militarized during the last decade.

Peacebuilding and dialogue are always a challenge in identity-based conflicts that have become militarized (Cox et al. 2017), but they might be even more so if they involve Shia–Sunni dimensions due to a number of complicating factors. The religious dimension to the conflicts transcends state borders, which creates a set of complex interactions between local political dynamics and transnational power relations. The local dynamics typically include the strategic instrumentalization of sectarian identities by authoritarian governments as well as the introduction of majority-based semi-democratic systems. The latter has, in these contexts, often led to ethnic and sectarian-based electoral mobilization, which further intensified ongoing cycles of violence (Sisk 2017, p. 260). In addition, high-level peacebuilding efforts are often undermined by regional powers that compete over strategic influence in the region, most importantly Iran and Saudi Arabia. However, despite the multifold challenges and the complexity of peacebuilding in conflicts with Shia–Sunni dimensions, the literature on identity-based conflicts has suggested several ways in which peacebuilding can work to effectively manage sectarian conflict and enhance social cohesion. Examples of successful peacebuilding efforts in sectarian conflicts include the cases of Northern Ireland, Bosnia, or Sri Lanka (Sisk 2017). As recognized by previous research, the building of peace and social cohesion "requires progress in extending the presence of an inclusive, resilient, and responsive state—especially at the local level" (Sisk 2017, p. 274; see also Cox et al. 2014). In other words, although these conflicts provide particular challenges, their complexity should not by itself explain the lack of peacebuilding initiatives and interreligious dialogue, which we empirically outline in the following section.

### *2.2. The Low Levels of Institutional Peacemaking Dialogue along the Shia–Sunni Fault Line*

If we explore existing databases on interreligious dialogue and peacemaking, we find that the prevalence of organized violence across the Shia–Sunni divide is not reflected in a similar prevalence of institutional attempts for dialogue and peacemaking. The most comprehensive list of international organizations engaged in interreligious dialogue and peacemaking is provided by the King Abdullah Bin Abdulaziz International Centre for Interreligious and Intercultural Dialogue (KAICIID) and is called the KAICIID Peace Map. It identifies 463 internationally operating organizations that are specialized in interreligious dialogue and peacemaking (KAICIID 2018). For this study, we have coded the religious communities targeted by the interreligious dialogue initiatives of these organizations, based on the information in the original dataset.1 Table 1 provides an overview of our coding, displaying the most common interreligious relations addressed by peacemaking organizations listed in the KAICIID Peace Map. As can be seen in Table 1, only eight of these organizations (or 1.7 percent) have Shia–Sunni dialogue as an explicit mandate and/or have had concrete programs aimed at creating dialogue across the Shia–Sunni divide. By far the largest number of organizations addresses relations between Christian and Muslim communities, although still one hundred organizations address Christian–Jewish and Jewish–Muslim relations, respectively. In fact, it is worthwhile to mention that there are many organizations that specialize in relations between all the three Abrahamic religions. This is the case for 70 organizations.

1 Our coding is based on the following variables provided in the original dataset, for every of the 463 organizations: "IRDActivities" (Column Q), "Activities" (S), "Aim" (AB), "IRDdefinition" (AC), "Events" (AD), and "Publications: (AE). We examined whether an organization worked to address a certain form of interreligious relations, for example, Christian–Muslim, Intra–Muslim, Intra-Christian, etc. The Peace Map with our additional coding can be accessed under the link that is listed under Supplementary Materials. The variables that we have coded ourselves can be found in columns AJ to BB.

**Table 1.** Type of interreligious dialogue promoted by organizations in King Abdullah Bin Abdulaziz International Centre for Interreligious and Intercultural Dialogue (KAICIID) Peace Map 1.

1 Organizations covered by the KAICIID Peace Map also focus on interreligious dialogue with other religions, including Animist, Buddhist, Druze, Hindu, or Sikh communities. Still, none of these religions are explicitly targeted by more than nine organizations. Finally, 206 (of a total of 463 organizations contained in the dataset) promote interreligious dialogue on a more general scale, without focusing on the relations between specific religious communities.

With regards to the eight organizations that have addressed Shia–Sunni relations, the degree to which these organizations focus on Shia–Sunni relations varies considerably. For instance, whereas the Royal Aal al-Bayt Institute for Islamic Thought, based in Jordan, defines its main goal as advancing dialogue between the seven Islamic schools of jurisprudence, the UNESCO Association for Interreligious Dialogue, and the International Council for Inter-Religious Cooperation adopt a much broader focus, although they have previously organized events and seminars addressing Shia–Sunni relations. The US-based Salam Institute for Peace and Justice primarily promotes dialogue between Muslim and non-Muslim communities, but has, for instance, also organized meetings with religious authorities in Iran to discuss Shia–Sunni relations. Another organization that partially addresses Shia–Sunni relations is the Malaysia-based International Institute of Advanced Islamic Studies. The Association for Conflict Transformation (ACT) of the Cordoba Foundation of Geneva (CFG) is particularly active in di fferent parts of the Muslim world and has thus also worked in contexts where it sought to foster dialogue in violent conflicts with a Shia–Sunni dimension. The Organization of Islamic Cooperation (OIC), despite promoting dialogue between the di fferent Islamic sects, su ffers from several problems, which are discussed to a greater extent in relation to our third hypothesis (Section 3.3). Finally, since the outbreak of the Syrian Civil War, the MENA Council of Religions for Peace (RFP), an international organization created in 1970, has sought to advance dialogue between religious authorities, including Sunni and Shia representatives. It is noteworthy that, apart from the Organization of Islamic Cooperation (OIC), none of the eight organizations that are listed in the KAICIID dataset has o ffices in a country that has both sizeable Shia and Sunni populations.

While we recognize limitations with regards to the comprehensiveness of the KAICIID Peace Map, as it may fail to include *all* such organizations, we see no reason to expect that this would introduce a systematic bias against the information gathered about Shia–Sunni dialogue. We therefore consider the fact that only 1.7 percent of the listed organizations focus specifically on Shia–Sunni relations to be indicative of a general interreligious peacemaking deficit when it comes to addressing Shia–Sunni tensions and violence. We have also consulted two other sources on interreligious peacemaking and dialogue, and both reveal a similar empirical picture. One such source is provided by the Directory of InterFaith and InterReligious Organizations (Guerrand-Hermès Foundation for Peace 2018). It lists a total of 42 additional organizations not covered by the KAICIID list, none of which seems to explicitly address the Shia–Sunni divide. Moreover, in their 2005 report, Bouta et al. (2005) report on a large number of Christian and Muslim faith-based peacebuilding organizations. While providing strong evidence that besides Christian organizations, there is also a substantial number of Muslim peacebuilding organizations (particularly in Africa), only a small share of these organizations specifically focuses on interreligious peacemaking and dialogue, and none seem to specifically address Shia–Sunni relations.

Since the US invasion of Iraq in 2003, there has been an increasing prevalence of organized violence and armed conflicts along the Shia–Sunni fault line, which has further escalated over the past decade (Finnbogason et al. 2019). However, this does not seem to have prompted the creation of new organizations and institutional attempts focusing on Shia–Sunni relations. In fact, only two of the eight organizations mentioned here were founded after 2003—in 2008 and 2009, respectively.

Taken together, the two empirical trajectories that we have identified above present us with a puzzle. In 2017, 44 percent all the world's fatalities in organized violence resulted from conflicts with Shia–Sunni dimensions (Finnbogason et al. 2019). Still, very few institutional mechanisms and organizations have been set up to explicitly address this fault line. This deficit of peacemaking and dialogue has neither been noted nor discussed in previous research, regardless of whether that research focusses on Shia–Sunni sectarianism (or sectarianization) (e.g., Byman 2014; Haddad 2017; Hasheemi and Postel 2017) or rather on interreligious dialogue and religious peacemaking (e.g., Cheetham et al. 2013; Haynes 2007; Smock 2002). In this study, we seek to explore why so few interreligious peacemaking initiatives seem to be targeted at conflicts between Shias and Sunnis, when the need for such dialogue is evident.


Waveform Design for Energy Efficient OFDM Transmission

*Homayoun Nikookar*

#### **Abstract**

In this chapter, a green radio transmission using the binary phase-shift keying (BPSK) modulated orthogonal frequency-division multiplexing (OFDM) signal is addressed. First, the OFDM transmission signal is clearly stated. For a specified performance of the system, the least transmit power occurs by the optimal OFDM shape, which is designed to minimize the average inter-carrier interference power taking into account the characteristic of the transmit antenna and the detection process at the receiver. The optimal waveform is obtained by applying the calculus of variations, which leads to a set of differential equations (known as Euler equations) with constraint and boundary conditions. Results show the transmission effectiveness of the proposed technique in the shaping of the signal, as well as its potential to be further applied to smart context-aware green wireless communications.

**Keywords:** green radio transmission, multicarrier, OFDM, signal design, optimization

#### **1. Introduction**

The advancements in the field of wireless communication have led to many exciting applications such as mobile internet access, health care and medical monitoring services, smart homes, combat radios, disaster management, automated highways, and factories. With each passing day, novel and advanced services are being launched even while existing ones continue to flourish. Wireless services have now found applicability in other sectors too including health care, transportation, security, logistics, education, and finance. Demand for wireless services is thus expected to grow in the foreseeable future. However, with the increasing popularity of wireless services (such as the 5G and the future 6G), the requirements on prime resources such as green transmission and radio spectrum are put to a great test. Recent studies have shown that the energy costs account for as much as half of a mobile service provider's annual operating expenses. Therefore, making the communication equipment more efficient in relation to its power consumption not only has implications with regard to environmental pollution and the level of CO2 emission, but also makes economic sense and can eventually reduce the cost of wireless services (for providers and users).

In this regard and given the 10% of the world's energy consumption due to the information and communication technology (ICT) industry [1], energy efficiency has become one of the key performance indicators (KPI) in the design and implementation of radio systems.

The theme of green radio communications is to design energy-efficient wireless communication techniques and protocols, which optimally utilizes available resources and minimize power consumption. Various strategies are employed for the design of energy-efficient wireless systems; among them are energy-efficient new radios [2, 3], minimization of interference [4], and optimal resource allocation [5]. In this chapter, we would like to design a signal for energy-efficient OFDM transmission. As can be seen from Section 4, we will reduce the power dissipation of the transmitter and consequently the level of CO2 emission of the radio system by optimal design of a waveform for transmission that minimizes inter-carrier interference of the OFDM system. In this way for reaching the same performance level of the provided communication services, a lower power level will be required for transmission, which leads to a green wireless radio system. As the reduction of the inter-carrier interference level is the basis for the optimization of OFDM signal, the approach explained in this chapter falls in the category of green radio by minimization of interference mentioned above.

The rest of the chapter is organized as follows. In Section 2, the basics of the OFDM transmission being provided. In Section 3, the data detection procedure in the receiver is mathematically explained. This procedure is further needed for the maximization of the detection performance of the system. Waveform design and the optimization procedure using calculus of variations and the Lagrange multiplier are detailed in Section 4, and the results are discussed. Conclusion remarks appear in Section 5.


**Prof. Carlos Hernández-Lahoz, MD**

Emeritus Assistant Professor of Neurology, University of Oviedo, Oviedo, Spain

Section 1 Introduction

**3**

**Chapter 1**

**1. Introduction**

ever since [2].

and DQ8(+) [4].

exposure to drugs [5, 6].

degrees of enteropathy [1].

and certain varieties of oats (avenins).

Introductory Chapter: Celiac

Celiac disease (CD) is a systemic disorder of an autoimmune nature that occurs in genetically susceptible individuals. It is caused by gluten and related prolamins and is characterised by the presence of a variable combination of gluten-dependent clinical manifestations, the presence of CD-specific antibodies, along with genetics compatible with HLA-DQ2 or HLA-DQ8 haplotypes and the presence of varying

It is triggered by the consumption of foods that contain or are made with gluten, mainly through wheat proteins (gliadins), and also rye (secalins), barley (hordeins)

It is a chronic disease with a genetic basis that affects, or may affect, various organs and systems in which inflammation of the small intestine may lead to various symptoms and eventually to malabsorption of nutrients. Treatment of CD consists of permanently following a gluten-free diet (GFD), which was developed in 1951 by the Dutch paediatrician Dr. Willem Karel Dicke, in the course of treating children suffering from chronic diarrhoea with malnutrition who had been admitted to the Children's Hospital of Utrecht after the Second World War. He found that they improved when foods containing wheat flour were removed from the diet. This was the starting point for the introduction of the GFD, which is the only treatment for CD that is effective throughout the world, and it has been applied

Genetics, immunology and aspects of the environment are important factors in the development of CD. Its principle determinants are the class II genes of the HLA system, which are largely related to the presence of HLA-DQ2 and HLA-DQ8 [3]. It is primarily an immune disorder, mediated by T cells, that affects the intestinal mucosa of genetically predisposed individuals. CD4+ T cells recognise gluten peptides, which are selectively present in the context of the molecules HLA-DQ2(+)

The enzyme transglutaminase 2 (TG2) deaminates positively charged gluten peptides. Gluten-specific CD4+ T cells, such as the cytotoxic intraepithelial CD8 T lymphocytes, play an important role in the development of intestinal lesions. Gluten is the most important environmental factor involved in its development, but other environmental factors have been implicated, such as infections, dysbiosis and

The Consensus Conference of Experts Meeting in 2012 and 2013, celebrated in Oslo and London respectively have accurately described the terms related to CD and also the sensitivity to non-celiac gluten sensitivity (NCGS) and wheat allergy, to unify criteria and accurately define the differences between such disorders [7, 8].

Disease - An Overview

*Luis Rodrigo and Carlos Hernandez-Lahoz*


*2.1. Cell Lines and Cell Treatments*

Normal human epidermal cells (HEKa-ATCC PCS 200-011) and dysplastic keratinocytes (DOK-ECACC) were cultivated in standard cell culture conditions (37◦C, 5% CO2) according to manufacturer instructions regarding cell culture media and supplements. The sea-buckthorn oil was a cold-pressed, commercially available product of Romanian origin and stored as 1/10 DMSO solution. Further dilutions were made with complete cell culture medium and appropriate controls containing a comparable dilution of DMSO. Cells were exposed to UVA with a UV-365 nm lamp (VL-340 BLB model—Vilber Lourmat, France) at a light intensity of 381 µW/cm2 , for 30 min, in a laminar flow hood, as previously described [17].


**1. Introduction**

Medical imaging techniques, such as computed tomography (CT) or X-ray among others, have been used in recent decades for the detection, diagnosis and treatment of different diseases [1].

A new and emerging field in dentistry is dental informatics, because of the possibility it offers to improve treatment and diagnosis [2], in addition to saving time and reducing stress and fatigue during daily practice [3]. Medical practice in general, and dentistry in particular, generates massive data from sources such as high-resolution medical imaging, biosensors with continuous output and electronic medical records [4]. The use of computer programs can help dental professionals in making decisions related to prevention, diagnosis or treatment planning, among others [5].

At present, one of the artificial intelligence methods employed in clinical fields is called deep learning [6].  The success of deep learning is mainly due to the progress in the computer capacity, the huge amount of data available and the development of algorithms [1]. This method has been proven and is used effectively in image-based diagnosis in several fields [8]. Convolutional neural networks (CNNs) are commonly used in applications relying on deep learning, which have been developed extremely quickly during the last decade [9], mainly as a choice for analyzing medical images. CNNs have been successfully employed in medicine, primarily in cancer, for the automated assessment of breast cancer in mammograms, skin cancer in clinical skin screenings, or diabetic retinopathy in eye examinations [10].

CNNs have been recently applied in dentistry to detect periodontal bone loss [11,12], caries on bitewing radiographs [13], apical lesions [14], or for medical image classification [12]. These kinds of neural networks can be used to detect structures, such as teeth or caries, to classify them and to segment them [15]. Neural networks need to be trained and optimized, and for that an image database is necessary.

There are several image techniques in the dentistry field depending on their use.  Bitewing images can only visualize the crowns of posterior teeth with simple layouts and considerably less overlaps [17]. Panoramic radiographies are very common in dentistry, because they allow for the screening of a broad anatomical region and at the same time, require a relatively low radiation dose [18].

The objective of this review of the literature was to visualize the state of the art of artificial intelligence in various dental applications, such as the detection of teeth, caries, filled teeth, or endodontic treatment, among others.


**Author details**

 *=*

through magnetic (inductive) coupling in the disconnected circuits of 220 kV power lines with double circuit from the Banat area – Romania. The results are presented in Table 5, in com‐

This case brings about an important observation. Considering phase shift φ, between voltages and currents, through which the charging with power of the inductor circuit is indirectly expressed, the mathematical model has required the representation of the currents through momentary values instead of effective ones. But this leads to an additional unknown, which is time, *t*, namely the measuring moment of the voltages induced for each phase. It means that this case also requires the digitization of period *T = 0.02* seconds in 100 time intervals, *Δtk*

*0.0002* seconds and the search of the moment in which the measurement of the voltage induced through magnetic coupling for each of the phases of the disconnected circuit was performed.

Comparing the measured values of the voltages induced through magnetic (inductive) coupling with the calculated ones there has been observed a very good concordance, which demonstrates an appropriate mathematical approach of the physical phenomena which lead to the magnetic (inductive) coupling between the conductors of the high voltage overhead

**a.** In all of the cases, the middle phase of the disconnected circuit of the high voltage overhead power lines with double circuit has got the lowest value for the voltage induced. It has been proved by both the measurements on the ground and the mathematical modeling. The explanation for the electric coupling lies in the longest distance between the phases of the active circuit and the middle phase of the disconnected circuit. As to the magnetic (inductive) coupling, the effect is due to the vector summation of the intensities of the

**b.** In the case of the power lines where the transposition of the phases has not been per‐ formed, the voltage induced through magnetic (inductive) coupling is the highest on the upper phase. This phenomenon is explained by the fact that the respective conductor – earth loop has the largest surface. This means that if all the protection conductors of each of the pillars were grounded there would be realized a large number of conductor – earth loops (equal with the number of openings) which would capture a part of the inductor magnetic flux, particularly that of the upper phase, thereby reducing the voltages induced

**c.** All the voltages induced through electric (capacitive) coupling have got very high values, which are dangerous for the operating staff. By being grounded, the power lines are discharged of this high potential, but there appear voltages induced through magnetic (inductive) coupling, they being high enough to be dangerous, too. Therefore, we consider that, in the case of circuits separated from the ground in a galvanic way, the operating

staff have to obey the protection rules regarding working under high voltage.

parison with the values of the voltages measured on the ground..

power lines.

**4. Conclusions**

364 Computational and Numerical Simulations

inductor magnetic fields..

through magnetic (inductive) coupling.

Flavius Dan Surianu

Politechnica University of Timisoara, Romania