**1. Introduction**

Currently, water deficiency is increasing and becoming a challenge for human society. It is increasingly becoming the most important environmental limitation, which is limiting plant growth. According to the statistics, over 30 arid and semi-arid countries are expected to experience water deficiency in 2025 [1]. This will limit agricultural development, threaten food supplies, and inflame rural poverty. Evaporation estimations are essential for controlling and modelling the integrated hydrological resources connected to hydrology, agricultural business, arboriculture, irrigation, flooding, and lake ecosystems. Evaporation is described as the reduction of deposited water due to the conversion of liquid phase to steam phase, which is influenced by the climate situation, such as weather, wind velocities, relative humidity, and sunshine. According to the World Meteorological Organization (WMO), more than half of the total inflow (rainfall or any other sources) to Lake Victoria in the U.S. is lost due to evaporation, which results in relatively humid conditions [1].

The evaluation of evaporation from reservoirs in arid and semi-arid areas is also important. For example, Libya has built one of the largest civil engineering groundwater pumping and transferring systems to overcome water limitations and climate hindrance (high temperature and low rainfall). This project is known as the Manmade River Project (MRP) [1]. The purpose of this project was to supply the water demand of Libya by pumping underground water underneath the Sahara Desert and transfer it using a network

**Citation:** Jasmine, M.;

Mohammadian, A.; Bonakdari, H. On the Prediction of Evaporation in Arid Climate Using Machine Learning Model. *Math. Comput. Appl.* **2022**, *27*, 32. https://doi.org/10.3390/ mca27020032

Academic Editor: Nicholas Fantuzzi

Received: 27 March 2022 Accepted: 31 March 2022 Published: 5 April 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/).

of huge underground pipes, especially for irrigation. The high cost of water pumping and lack of appropriate planning are the main concerns. In Egypt's Lake Nasser (located in an arid area), where the Nile's water is stored, downstream water loss, due to evaporation, is estimated to be 3 m in depth, or double that of Lake Victoria [1]. In Australia, it is calculated that around 95% of the precipitation evaporates and has no contribution to runoff [1].

Artificial intelligence models are becoming increasingly popular for forecasting data, instead of traditional models [2]. ANFIS model is one of them, which is also called a data-driven model [3,4], and can be used for different measurements, such as rainfall, streamflow, evaporation, water quality, and many others. A comparison has been made by Moghaddamnia et al. [5] on evaporation evaluation using an artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). The ANFIS model was compared with the regression-based method by Dogana et al. [2], and ANFIS was declared to be the finest. A group of researchers [6] has published their work on ANN, LS-SVR, fuzzy logic, and ANFIS on daily pan evaporation, with the conclusion of fuzzy logic as being the best performer.

More recent research on evaporation is also conducted by AI methods. A new artificial technique, support vector regression (SVR), and a few nature-inspired algorithms (whale optimization algorithm, particle swarm optimization, and salp swarm algorithm) were investigated by a bunch of researchers in 2021 [7]. A unique contribution to evaporation estimation, based on maximum air temperature, was published earlier this year by scientists [8]. They became successful in the application of deep learning-based model to predict evaporation. However, a group of scholars found effective results of the application of the multiple learning artificial intelligence model in 2020 [9]. They analyzed multiple model-artificial neural networks (MM-ANN), multivariate adaptive regression spline (MARS), support vector machine (SVM), multi-gene genetic programming (MGGP), and 'M5Tree' to simulate the evaporation on a monthly scale basis (EPm) at two stations in India. Artificial neural network (MM-ANN) and multi-gene genetic programming (MGGP) posed the best results.

Some analysis was performed based on four climate variables, whereas some depended only on maximum temperature. Additionally, different researchers worked on different models for different locations. This is the first time ANFIS model, and few optimizers were adopted for this data set of Arizona, United States, along with six weather variables inputs. In this study, adaptive neuro-fuzzy inference system (ANFIS), ANFIS with firefly algorithm [10,11], ANFIS with genetic algorithm [5], and PSO [12] were analyzed and compared, for the first time, in order to investigate the best modeling approach for evaporation. The main objectives of this study are:

#### **2. Methodology**

#### *2.1. Adaptive Neuro Fuzzy Inference System (ANFIS)*

The ANFIS model is a mixture of fuzzy inference system (FIS) and artificial neural network (ANN). The fuzzy inference system (FIS) is a very successful and popular model, based on fuzzy logic, which was first proposed by Chang in his study [13]. For the modeling of reservoir performance and problems regarding data uncertainty, fuzzy logic is a highly recommended system [13]. This model is adopted mainly due to its good capacity of extraction of data from input to fuzzy values, in a range of 0 to 1. The ANN model was combined to overcome the limitation of the FIS model. ANN is adopted due to its ability to arrange input and output in pairs and make the structure ready to calibrate. ANN also has the following characteristics:

**Figure 1.** Flow chart of the ANFIS model.


**1. Introduction**

34 Will-be-set-by-IN-TECH

[70] Fossorier M. P. C., Mihaljevic M., et al. (1999) Reduced complexity iterative decoding of low-density parity check codes based on belief propagation. Communications, IEEE

Transactions on, vol. 47, pp. 673-680, 1999.

The use of ultra wide band (UWB) signals can offer many advantages for communications. It can provide a very robust performance even under harsh multipath and interference conditions, the capability of precision ranging and a reduced power consumption. Since the power spectral density is very low, it is possible to overlay UWB networks with already existing non-UWB emissions.

Early UWB concepts for communications have almost exclusively relied on impulse radio, where the whole available bandwidth, i.e., up to 7.5 GHz, is covered at once by means of very short pulses which are generated with a low duty cycle. Meanwhile, a bandwidth of 7.5 GHz is only available in the US [1, 3]. In Europe, the spectrum which is available with the same transmit power spectral density of -41.3 dBm/MHz ranges only from 6.0 to 8.5 GHz [4], if no detect and avoid techniques are applied1. A potential UWB system has therefore to be able to 'live' with a mean transmit power of less than -7.3 dBm.

This is a small value, but fortunately UWB systems may exploit the signal energy very efficiently because firstly, even at data rates in the Gbps range, it is not required to use bandwidth efficient (but energy inefficient) modulation schemes like a 1024-QAM. Secondly, UWB transmission benefits from a good fading resistance.

For a measured indoor channel [7], Fig. 1 shows that even a bandwidth of 'only' 500 MHz ensures a very good fading resistance: If the receiver is moved over all *x*-*y*-positions in the non-LOS case, the smallest power value at the receive antenna lies less than 3 dB below the mean power, averaged over all positions. Thus the fading margin could be chosen in the order of 3-4 dB — even for indoor channels which exhibit the largest coherence bandwidth.

The second energy efficiency argument claimed above is underpinned in Fig. 2. It shows the channel capacity depending on the bandwidth, where additive white Gaussian noise (AWGN) is assumed. A value of 83 MHz just corresponds to the total bandwidth available in the 2.4 GHz ISM band, which is chosen for comparison. At 1 Gbps, a 2.5 GHz bandwidth promises an advantage of 25 dB with respect to the required receive-power. Furthermore, even binary modulation (on the inphase and quadrature components) promises high data rates.

1 With detect and avoid techniques, -41.3 dBm/MHz is also permitted between 4.2 and 4.8 GHz.

©2013 Song et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ©2013 Song et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### 2 Will-be-set-by-IN-TECH 110 Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications Non-Coherent UWB Communications 3

Unfortunately, a very large signal bandwidth is also associated with some serious problems. These problems are related to the transceiver components itself (availability of broadband antennas, amplifiers etc.), and to the technical effort which is required for synchronization, channel estimation and interference rejection. Since UWB networks operate in frequency bands already assigned to other RF-systems, the probability that narrowband interference occurs at all increases with the bandwidth, too.

Furthermore, by increasing the bandwidth, more and more multipath arrivals with different path gains and delays are resolvable at the receiver, which makes it more difficult to collect the multipath energy coherently — although the power at the receive antenna does not suffer from the fading effect. Fig. 1 shows an example that one may lose 10 dB and more, if an UWB-receiver uses only the strongest signal echo. Thus, especially in non-LOS scenarios, a coherent RAKE receiver requires a very large number of RAKE fingers and a precise channel knowledge to efficiently capture the multipath energy. Such a coherent RAKE receiver will be very complex and costly, such that the hardware itself may consume a lot of power. This fact is the major motivation for systems using non-coherent detection, which are discussed in this chapter.

−100 −95 −90 −85 −80 −75 −70 −65 −60

non-coherent receiver is clearly the dramatically reduced effort which is required for channel estimation, synchronization, and multipath diversity combining. This advantage is, however, bought by a serious drawback: non-coherent detectors are more susceptible to narrowband

Non-coherent detection can either rely on envelope detection or on differential detection. In the simplest case, path-diversity combining is carried out via an analog integration device. However, the change from analog to digital combining stimulates new perspectives. Since a digital code matched filter can be applied prior to the non-coherent part of the receiver, the capability to distinguish users (or networks) by means of code division multiple access is improved. We show that digital receiver implementations with user specific filtering have also an enhanced interference rejection capability and energy efficiency. Moreover, we present well suited solutions for the analog-to-digital conversion, the spread-spectrum code sequences,

Although non-coherent detection is not restricted to low data rates — even orthogonal frequency division multiplex (OFDM) can be combined with non-coherent modulation and

Non-coherent detection can either be based on envelope detection or on differential detection. In the simplest case, path-diversity combining can be achieved by means of a single, analog integrate and dump filter, see Fig. 3 and Fig. 4. The integration effectively provides a binary weighting of the multipath arrivals: all components inside the integration window of size *T*int are weighted with "1", while all the others are weighted with "0". Regardless of whether envelope or differential detection is chosen, we assume that the receiver uses a quadrature

detection [19] — we focus our attention on low data rate single carrier transmission.

**Figure 2.** Capacity of an AWGN channel as a function of the receive-power for different signal

interference (NBI), multi-user interference (MUI), and inter-symbol interference (ISI).

bandwidths. The 2.4 GHz ISM band offers a bandwidth of 83 MHz.

**2. Non-coherent detection in multipath AWGN**

Rx−power in dBm

B=83 MHz B=500 MHz B=1000 MHz B=2500 MHz binary modulation

Non-Coherent UWB Communications 111

SISO AWGN channel, Nyquist rate

101

and the modulation format.

102

channel capacity in Mbps

103

104

**Figure 1.** Received energy *E*rx normalized by the transmitted symbol's energy *E*tx in dB, versus different signal bandwidths. The thickness of the curves indicates LOS or non-LOS regimes. The curves without markers show *E*rx/*E*tx averaged across all *x*-*y*-positions within an rectangular area of 30 cm × 40 cm (1 cm grid, data from [7]), if an ideal full RAKE-receiver is used. The curves marked with triangles show the minimum value of *E*rx/*E*tx which occurs within these positions, again assuming a full RAKE. Thus the small-scale fading effect becomes visible. The curves with circles depict the normalized receive energy for a receiver which exploits only the strongest propagation path, i.e., a single correlator is applied. Transmitters-receiver separation is about 3 m, the carrier frequency is always set to 6.85 GHz.

Non-coherent UWB transmission is an attractive approach especially if simple and robust implementations with a small power consumption are required. Main application fields are low data rate sensor or personal area networks, which require low cost devices and a long battery life time. It should be noted that the current IEEE802.15.4a UWB-PHY for low data rate communications enables non-coherent detection, too [18]. The main advantage of a

**Figure 2.** Capacity of an AWGN channel as a function of the receive-power for different signal bandwidths. The 2.4 GHz ISM band offers a bandwidth of 83 MHz.

non-coherent receiver is clearly the dramatically reduced effort which is required for channel estimation, synchronization, and multipath diversity combining. This advantage is, however, bought by a serious drawback: non-coherent detectors are more susceptible to narrowband interference (NBI), multi-user interference (MUI), and inter-symbol interference (ISI).

Non-coherent detection can either rely on envelope detection or on differential detection. In the simplest case, path-diversity combining is carried out via an analog integration device. However, the change from analog to digital combining stimulates new perspectives. Since a digital code matched filter can be applied prior to the non-coherent part of the receiver, the capability to distinguish users (or networks) by means of code division multiple access is improved. We show that digital receiver implementations with user specific filtering have also an enhanced interference rejection capability and energy efficiency. Moreover, we present well suited solutions for the analog-to-digital conversion, the spread-spectrum code sequences, and the modulation format.


**4. Conclusions**

In this study, the flavonoid contents of PUL were investigated, and the PUL were discovered to be rich in flavonoids, such as rutin, hyperoside, and isoquercitrin. Extraction using different DESs based on CC and dicarboxylic acids was found to effectively improve the extraction efficiency of the three flavonoids from the PUL. Among the different DESs tested, the DES based on CC and GA exhibited the highest extraction efficiency. The extraction conditions were optimized using the BBD analysis. According to these conditions, the highest extraction efficiency (217.515 μg/mL) could be achieved by performing the extraction of PUL for 1 h at a temperature of 30 ◦C and stirring speed of 1113.1 rpm, using the DES based on CC and GA at a concentration of 30.85 wt.%. The extraction efficiency

achieved using the DES was more than twice as high as that of aqueous extraction. In addition, the PUL extract obtained using the DES synthesized from CC and GA exhibited appreciable antioxidant activity, which was approximately 1/6 that of L-ascorbic acid. The potential utility of the PUL extracts as antioxidants was, thus, demonstrated. The PUL extract obtained using the DES synthesized from CC and GA significantly inhibited NO generation (up to 26.1%) at a concentration of 0.1%. These results indicated the antiinflammatory properties of the active components of the PUL extracted using the DES.

**Supplementary Materials:** The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/molecules27092798/s1: Figure S1: liquid chromatogram of PUL extract and mass spectra of flavonoid peaks; Figure S2: effect of extraction conditions on extraction efficiency of DES.

**Author Contributions:** Conceptualization, H.Y.P. and J.P.; methodology, J.W.L.; validation, J.W.L.; resources, H.Y.P.; writing—original draft preparation, J.P.; writing—review and editing, J.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Institute of Biological Resources (NIBR), funded by the Ministry of Environment (MOE) of the Republic of Korea, grant number NIBR202219101, and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT), grant number 2019R1F1A1058645.

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** This work was supported by a grant from the National Institute of Biological Resources (NIBR), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIBR202219101) and a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (2019R1F1A1058645).

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

**Sample Availability:** Not applicable.


**4. Results**

## *4.1. Frequency Analysis*

In response to the question about participation in a mass-casualty incident or disaster as a healthcare worker, the majority of respondents (74.6%) declared that they had not participated in such an event. More than a quarter of the respondents (25.4%) answered in the affirmative to the analyzed question.

The respondents were asked whether the facility where they currently worked has a plan for dealing with mass-casualty incidents and disasters. Most of the respondents (71.6%) answered "yes" to this question. Only 3% of the respondents answered "no" to this question. More than a quarter of the respondents (25.4%) felt they did not know the answer to this question (Table 3).

The respondents most frequently (77.6%) reported that they were familiar with the procedure for dealing with mass-casualty incidents and disasters. Only 22.4% of the research group was not acquainted with the procedure for handling such situations.

Most of the respondents (79.1%) knew who was responsible for managing mass-casualty incidents and disasters in the facility of their current workplace. On the other hand, 20.9% answered in negatively to this question.

In response to the question concerning the knowledge of the procedures to be followed in the event of evacuation during a mass-casualty incident at their workplace, the majority of respondents (87.3%) answered a ffirmatively. Only 12.7% of respondents did not know the procedures to be followed in this situation.

The respondents were asked whether their workplace had adequate logistical infrastructure for mass-casualty incidents. Most often (41.8%) respondents did not know whether their workplace had such a logistical infrastructure. On the other hand, 39.6% of the respondents believed their workplace to be prepared logistically for mass-casualty incidents. On the other hand, 18.7% of respondents answered negatively to this question.

More than half of the respondents (54.5%) reported a lack of organization with drills regarding disaster management at their workplace. In turn, 45.5% of the respondents stated that such activities had been organized at their workplace.

As far as the frequency of organizing drills is concerned, respondents most frequently reported that such drills were organized less frequently than once every 3 years (91.8%). Individual respondents provided the following answers: once every 3 years (3%), once every 2 years (3%) and annually (2.2%). More than half of the respondents (53.7%) had not received training related to disaster preparedness at theircurrentworkplace.However,46.3%ofrespondentsreportedthattheyhadreceivedsuchtraining.

In response to the question concerning knowledge of triage, almost all respondents (99.3%) answered yes. Only one person answered negatively to this question.

#### *4.2. Relationship between Sociodemographic Variables and Evaluation of Preparedness for Mass-Casualty Incidents and Disasters*

The statistical analyses carried out checked the relationship between sociodemographic variables and the evaluation of preparedness for mass-casualty incidents and disasters. To this end, a correlation analysis using Spearman's rho coe fficient and a one-way analysis of variance were performed.

Initially, the relationship between the seniority of the respondents and the evaluation of preparedness for mass-casualty incidents and disasters was tested. For this purpose, correlation analyses using Spearman's rho coe fficient were performed. The results of this analysis are presented in Table 1.

**Table 1.** Results of the analysis of correlation between the length of service of the respondents and the evaluation of preparedness for mass-casualty incidents and disasters.

According to the analyses carried out, seniority is positively linked to the evaluation of the preparedness of the current workplace for a mass-casualty incident or disaster (weak link). This shows that the longer the respondents have been working, the better do they evaluate the preparedness of the institution where they work for a mass-casualty incident or disaster.

A one-way analysis of variance was then carried out to see if occupation di fferentiates the evaluation of preparedness for mass-casualty incidents or disasters. The results of this analysis are presented in Figure 1.

The results indicate a statistically significant e ffect for assessing the preparedness of the current workplace for a mass-casualty incident or disaster. In order to investigate the exact di fferences, Sidak post hoc tests were performed. The test results show no statistically significant di fference.

**Figure 1.** Average with a confidence interval of 95% for the evaluation of preparedness for mass-casualty incidents and disasters by occupation.

*4.3. Di*ff*erences between the Evaluation of Preparedness for a Mass-Casualty Incident or Disaster in the Current Place of Work and the Evaluation of One's Own Preparedness*

In the next stage of the analyses, it was assessed whether there are differences between the evaluation of one's own preparedness and the evaluation of the current workplace's preparedness for a mass-casualty incident and disaster. For this purpose, Student's t-test was performed for dependent samples. The results of this test are presented in Table 2 and in Figure 2.

**Table 2.** Differences between the evaluation of preparedness for a mass-casualty incident or disaster in the current place of work, and the evaluation of one's own preparedness.

*M*—mean; *Me*—median; *SD*—standard deviation; *Bias.*—bias*; Kurt.—*kurtosis; *Min & Max*.—the lowest and highest value of distribution; *D—*Kolmogorov–Smirnov test result; *p*—significance.

**Figure 2.** Average with a 95% confidence interval for the evaluation of preparedness for a mass-casualty incident or disaster for the current place of work, and one's own preparedness.

The test results indicate statistically significant di fferences. It turned out that the test subjects evaluate their own preparedness for mass-casualty incidents and disasters better than the preparedness of the current place of work. The strength of this e ffect is high.

#### *4.4. Di*ff*erences in the Evaluation of Preparedness for a Mass-Casualty Incident or Disaster Depending on Previous Participation in a Mass-Casualty Incident or Disaster as a Healthcare Professional*

It was assessed whether the subjects who had previously been involved in a mass-casualty incident or disaster as a healthcare worker di ffer in their evaluation of preparedness for such situations from those who had not been involved in such an event. A Mann Whitney test was conducted due to the large numerical di fferences between the analyzed groups. The results are presented in Table 3.

**Table 3.** Di fferences between persons who have been involved in a mass-casualty incident or disaster as a healthcare worker, and persons who have not been involved in such an event in terms of their evaluation of preparedness for a mass-casualty incident or disaster.

*M*—mean; *Me*—median; *SD*—standard deviation; *Bias.*—bias*; Kurt.—*kurtosis; *Min & Max*.—the lowest and highest value of distribution; *D—*Kolmogorov–Smirnov test result; *p*—significance.

The results of the tests indicate a statistically significant e ffect of moderate strength for the evaluation of one's own preparedness for mass-casualty incidents or disasters. As it turns out, respondents who took part in a mass-casualty incident or disaster as a healthcare worker evaluate their own preparedness much better than respondents who had not been involved in such an event.

#### *4.5. Di*ff*erences in the Evaluation of Preparedness for a Mass-Casualty Incident or Disaster Depending on the Organisation of Drills by the Institution and Whether They Were Attended by the Respondents*

In order to check the di fferences in the evaluation of preparedness for mass-casualty incidents or disasters between respondents with di fferent opinions concerning the organization of drills by the institution and depending on whether they took place, Student's t-tests for independent samples and Mann Whitney tests were performed. Initially, a Student's t-test for independent samples was conducted. It was decided to assess whether the respondents whose institution had organized drills regarding disaster management di ffered from those whose institution had not conducted such drills in relation to the evaluation of preparedness for such situations. The test results are presented in Table 2.

It was then assessed whether the evaluation of preparedness for such situations is impacted by the frequency of training on what to do in the event of a mass-casualty incident or disaster. Due to significant di fferences in the number of groups compared, Mann Whitney tests were performed.

The results of this test indicate a statistically significant and moderate e ffect for the evaluation of the preparedness of the current workplace for a mass-casualty incident or disaster. This results from the fact that the respondents, whose institution organized drills for such situations once every 3 years or more often, better evaluate the preparedness of the institution than the respondents whose institution organized trainings less frequently than once every 3 years. The results of the tests are presented in Table 4.

*M*—mean; *Me*—median; *SD*—standard deviation; *Bias.*—bias*; Kurt.—*kurtosis; *Min & Max*.—the lowest and highest value of distribution; *D—*Kolmogorov–Smirnov test result; *p*—significance.

It was then assessed whether training in preparation for disasters impacts upon the evaluation of preparedness for mass-casualty incidents or disasters. Student's t-tests for independent tests were performed for this purpose.

The results of this test indicate significant differences for the evaluation of both one's own preparedness and also that of the institution. Both of these effects are of moderate strength. The analysis showed that after training, the respondents evaluate their own and the institution's preparedness for a mass-casualty incident or disaster better than the respondents without such training. Test results are presented in Figure 3.

**Figure 3.** Average with a 95% confidence interval for evaluations of preparedness for mass-casualty incidents and disasters, categorized by participation in training related to preparation for such situations.


*Edited by Zühre Akarslan and Farid Bourzgui*

This book provides information on nomenclature, tooth numbering systems, tooth morphology, and anatomy and stages of tooth formation. It continues with root canal morphology and anatomy of incisors, canines, premolars, and molars. External and internal anatomies of mandibular permanent incisors and maxillary permanent first molars are presented according to a literature review. Orofacial structures affecting tooth morphology are discussed in detail. The book ends with the evolution of dental implant shapes and today's custom root analog implants.

ISBN 978-1-78923-839-6

ISSN 2631-6218

Human Teeth - Key Skills and Clinical Illustrations

Published in London, UK © 2020 IntechOpen © undefined / iStock

IntechOpen Book Series Dentistry, Volume 5


**Author details**

Kavitha Palaniappan Centre of Regulatory Excellence, Duke-NUS Medical School, Singapore

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


**6. Conclusions**

Radioactive materials are extensively used in industrial and research activities into medical, agricultural and environmental applications, and in various other areas. During the produc‐ tion and use of these materials, radioactive waste will inevitably arise; this must be managed with particular care owing to its inherent radiological, biological, chemical and physical hazards.

Producers and users of radioactive materials must be sure that a waste management strategy exists prior to the start of waste generation. A well-developed waste management strategy should consider the entire sequence of waste management operations, from the waste's production until its final disposal, including the various regulatory, sociopolitical and economic issues. The identified goal of radioactive waste management can be met with reasonable cost and resource use by implementing a carefully planned waste management strategy using appropriate technologies.

Waste containing long lived radionuclides must be treated, conditioned, stored and disposed of at a repository specifically designed for this purpose. Sample storage capacity is needed for the decay of short lived radionuclides and for storing long lived waste prior to, and after, the treatment and conditioning steps. Decay is the only natural way of reducing radioactivity (the process of transmutation of some long lived radionuclides is not considered viable at this time).

Since radionuclides have decay rates ranging from days to thousands of years, proper segregation of wastes depending on their half-lives, and separate treatment and conditioning of these wastes, is an important factor in the overall scheme of radioactive waste management. Treatment of waste involves operations intended to benefit safety and/or economy by changing the characteristics of the waste. There are different procedures to the treatment of radioactive waste, like:

In the case of electroremediation treatment of radioactive wastes offers many advantages such as the capacity to remove organic and inorganic pollutants by applying direct electric current into the soil, even in clays, it is easy to operate and involves the installation of electrodes into the soil or waste and the application of a low voltage gradient or direct current through them. In consequence, the EKR is a very good technological alternative to remove radioactive species as 22Na, 137Cs, 134Cs, 85Sr, 90Sr, 60Co and 238Ur from both saturated and unsaturated radioactive soils, sludges, ash and sediments, with less time and high efficiencies of removal in comparison of the other alternatives to remove radioactive wastes.


*Article* **Characteristic Volatile Composition of Seven Seaweeds from the Yellow Sea of China**

**Pengrui Wang 1, Jiapeng Chen 1, Lujing Chen 1, Li Shi 1 and Hongbing Liu 1,2,\***

**Abstract:** Plant volatile organic compounds (VOCs) represent a relatively wide class of secondary metabolites. The VOC profiles of seven seaweeds (*Grateloupia filicina*, *Polysiphonia senticulosa*, *Callithamnion corymbosum*, *Sargassum thunbergii*, *Dictyota dichotoma*, *Enteromorpha prolifera* and *Ulva lactuca*) from the Yellow Sea of China were investigated using multifiber headspace solid phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS), among them, the VOCs of three red algae Grateloupia filicina, Polysiphonia senticulosa, and Callithamnion corymbosum were first reported. Principal component analysis (PCA) was used to disclose characteristic categories and molecules of VOCs and network pharmacology was performed to predict potential biomedical utilization of candidate seaweeds. Aldehyde was found to be the most abundant VOC category in the present study and (*E*)-*β*-ionone was the only compound found to exist in all seven seaweeds. The chemical diversity of aldehydes in *E. prolifera* suggest its potential application in chemotaxonomy and hinted that divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber is more suitable for aldehyde extraction. VOCs in *D. dichotoma* were characterized as sesquiterpenes and diterpenes and the most relevant pharmacological pathway was the neuroactive ligand–receptor interaction pathway, which suggests that *D. dichotoma* may have certain preventive and therapeutic values in cancer, especially in lung cancer, in addition to neuropsychiatric diseases.

**Keywords:** volatile organic compounds; seaweeds; characteristic VOCs; chemotaxonomy; biomedical utilization; headspace solid phase microextraction

#### **1. Introduction**

Plant volatile organic compounds (VOCs) are produced by a range of physiological processes in many different plant tissues and typically occur as a complex mixture of lipophilic compounds with extremely diverse structures [1]. Their low molecular weight and high vapor pressure under ambient conditions allow them to freely exit through cellular membranes and reach the surrounding environment [2].

Plant VOCs have been reported in different geographical conditions ranging from Mediterranean environments [3] and tropical rainforests [4] to various extreme environments [5]. In aquatic ecosystems, algae are the main emitter of VOCs and the extraction of VOCs using headspace solid phase microextraction (HS-SPME) technology has been reported from brown algae [6], red algae [7] and green algae [8]. Algae release an abundance of VOCs to increase their tolerance to abiotic stresses, transfer stress information to homogeneous algae to induce defense, play allelopathic roles on heterogeneous algae and aquatic macrophytes for competing nutrients, or protect against predators [9]. In addition, the volatile contaminant in algae caught the interest of environmentalists [10]. Most of the studies on marine algae VOCs have focused on their allelopathy effects, whereas their

**Citation:** Wang, P.; Chen, J.; Chen, L.; Shi, L.; Liu, H. Characteristic Volatile Composition of Seven Seaweeds from the Yellow Sea of China. *Mar. Drugs* **2021**, *19*, 192. https://doi.org/ 10.3390/md19040192

Academic Editors: RuAngelie Edrada-Ebel, Chang-Yun Wang and Bin-Gui Wang

Received: 28 February 2021 Accepted: 25 March 2021 Published: 29 March 2021

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

**Copyright:** © 2021 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/).

contributions in other areas have been seldom investigated. VOCs are released under biotic or abiotic stresses and have great significance for plant survival and reproduction. In many cases, evolution has resulted in some plant VOCs acting as metabolic safety valves, protective or defense compounds, or communication cues [1]. VOCs can be divided chemically as aldehydes, alcohols, terpenoids, ketones, halogenated compounds, sulfur compounds and hydrocarbons and exhibit multitudinous functions, such as in being feeding attractants [11], pheromones [12] involved in chemical defenses [13–15] and acting as antimicrobial agents [16].

In the present study, VOC profiles of seven seaweeds blooming in the littoral area of Qingdao (the Yellow Sea of China) were investigated, including the first report of VOCs for three red algae species—*Grateloupia filicina*, *Polysiphonia senticulosa* and *Callithamnion corymbosum*. Characteristic categories and molecules of VOCs are discussed from the point of view of their chemotaxonomic significance and bioactivities are discussed in order to further expand these seaweeds' potential utilities in pharmaceutical areas. Our study provides new insights for the chemotaxonomy of algae and for the biomedical application of *D. dichotoma.*

#### **2. Results and Discussion**

#### *2.1. Headspace VOC Composition of Seaweeds*

VOC compositions were investigated in seven algae using headspace solid phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC– MS) and are reported according to their phylum. The number of VOC categories identified in each alga are given in Figure 1.

#### 2.1.1. Headspace VOC Composition of Rhodophyta

There were 34, 19 and 18 compounds identified from *Grateloupia filicina*, *Polysiphonia senticulosa* and *Callithamnion corymbosum*, respectively (Table 1), and, among them, four compounds were common to all three species, including two norisoprenoids (*β*-cyclocitral and (*E*)-*β*-ionone), one alkene (3,5,5-trimethyl-1-hexene) and one alkane (heptadecane). This is the first report on the headspace VOC composition for these three red algae species.

The VOCs of *G. filicina* exhibited the most chemical diversity, with the most abundant being pentadecanal (20.11% in polydimethylsiloxane (PDMS) fiber), tridecanal (19.20% in PDMS fiber), 1-hexen-3-ol (19.58% in divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber) and 1-octen-3-ol (18.72% in DVB/CAR/PDMS fiber). Wang Xiu-juan et al. [17] analyzed the semi-volatile organic compounds (SVOCs) of *G. filicina* using ethyl acetate as an extraction solvent and found that the main SVOCs were aldehydes, fatty acids and alcohols, with pentadecanal having the highest concentration. Our VOC

analysis results are consistent with the results for SVOCs in the literature, suggesting that aldehydes play an important role in the metabolism of *G. filicina.*

**Table 1.** VOC composition in Rhodophyta, determined by headspace solid phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS).

T tentatively identified. S identified by mass spectra (MS) and retention index (RI) compared with authentic standard. a RI: retention index relative to C7-C30 alkanes. b GF—*Grateloupia filicina*; PS—*Polysiphonia senticulosa*; CC—*Callithamnion corymbosum*. \* data from fiber DVB/CAR/PDMS. # data from fiber PDMS.

> Both *P. senticulosa* and *C. corymbosum* are from the same taxonomical order, Ceramiales Oltmanns and were found to contain two common compounds, 5-methyl-1-undecene and 1-undecyne, which were not found in *G. filicina*. Moreover, ectocarpene (21.83% in DVB/CAR/PDMS fiber; 14.71% in PDMS fiber) was a uniquely abundant compound in *P. senticulosa.*

#### 2.1.2. Headspace VOC Composition of Phaeophyta

The VOC compositions of brown algae *Sargassum thunbergia* and *Dictyota dichotoma* are reported in Table 2. Four compounds were commonly found, including one norisoprenoid ((*E*)-*β*-Ionone), one alkane (pentadecane) and two aldehydes (tridecanal and pentadecanal).

**Table 2.** VOC composition in brown algae, determined by headspace solid phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME/GC–MS).

T tentatively identified. S identified by mass spectra (MS) and retention index (RI) compared with authentic standard. a RI: retention index relative to C7–C30 alkanes. b ST—Sargassum thunbergii; DD—Dictyota dichotoma. \* data from fiber DVB/CAR/PDMS. # data from fiber PDMS.

> The most abundant VOCs in *S. thunbergia* are 8-heptadecene (5.97% in DVB/CAR/PDMS fiber; 14.82% in PDMS fiber), pentadecane (9.24% in DVB/CAR/PDMS fiber; 13.87% in PDMS fiber), pentadecanal (11.33% in PDMS fiber) and tridecanal (11.46% in DVB/CAR/PDMS fiber; 11.02% in PDMS fiber). A low relative content of 8-heptadecene (1.70%) has been reported in *S. thunbergia*, also using the SPME method though the fiber type was not mentioned [18]. Our data suggest that the choice of fiber type in the HS-SPME method has a decisive influence on the study's conclusion. In addition, two types of volatile polyenes were reported to have been found in an essential oil prepared by a simultaneous distillation extraction method from *S. thunbergia* [19], although no polyenes were found in our study.

Fifteen sesquiterpenes were found in *D. dichotoma*, with the predominant one being germacrene D (34.83% in DVB/CAR/PDMS fiber; 62% in PDMS fiber) together with minor ones such as cadinene, muurolene and bourbonene. Compared with the VOC results (PDMS/DVB fiber) from *D. dichotoma* collected from the Adriatic Sea [20], we identified a lower number of sesquiterpenes. The reason for this difference may be that the profile of plant secondary metabolites may vary in different environments, or that different extract fibers have differing abilities to capture sesquiterpenes.

It has been reported that a total of 233 diterpenes were isolated from *Dictyota* species, most of which were from *D. dichotoma* [21]. The present study firstly reports three volatile diterpenes—1,5,9-trimethyl-12-(1-methylethyl)-4,8,13-cyclotetradecatriene-1,3-diol, thunbergol and geranyl-*α*-terpinene in *Dictyota*. 1,5,9-Trimethyl-12-(1-methylethyl)-4,8,13 cyclotetradecatriene-1,3-diol is a macrocyclic diterpene and is used as a representative flavor compound in tobacco [22]. Geranyl-*α*-terpinene is distributed in some Compositae plants, as well as existing in the volatiles of beech buds, which act as semiochemical attractants for the beech leaf-mining weevil, *Orchestes fagi* [23].

2.1.3. Headspace VOC Composition of Chlorophyta

The results for two green algae, *Enteromorpha prolifera and Ulva lactuca*, are presented in Table 3. In total, 40 VOCs were identified and, among these, 21 were aldehydes.

**Table 3.** *Cont.*

T tentatively identified. S identified by mass spectra (MS) and retention index (RI) compared with authentic standard. a RI: retention index relative to C7–C30 alkanes. b EP—Enteromorpha prolifera; UL—Ulva lactuca. \* data from fiber DVB/CAR/PDMS. # data from fiber PDMS.

> The top three compounds with the highest content in *E. prolifera* were aldehydes, consisting of pentadecanal (8.49% in DVB/CAR/PDMS fiber; 24.4% in PDMS fiber), (*E*)-2 heptenal (9.64% in DVB/CAR/PDMS fiber) and tetradecanal (3.34% in DVB/CAR/PDMS fiber; 6.32% in PDMS fiber). It has been reported that significant differences were observed in the composition and types of VOCs in different harvest seasons for *E. prolifera* [24]. Differently from *E. prolifera*, the top three compounds with the highest content found in *U. lactuca* were not aldehydes, but alkenes and a ketone, including 8-heptadecene (5.32% in DVB/CAR/PDMS fiber; 19.70% in PDMS fiber), (*E*)-*β*-ionone (8.69% in DVB/CAR/PDMS fiber; 18.13% in PDMS fiber) and 3-ethyl-1,4-hexadiene (10.17% in DVB/CAR/PDMS fiber).

> For *U. lactuca*, 30 VOCs were identified. Among them, 25 compounds also existed in *E. prolifera*, including 11 aldehydes ((*E*)-2-heptenal, 2,4-nonadienal, decanal, (*E*,*E*)-2,4 decadienal, undecanal, (*E*)-4,5-epoxydec-2-enal, tridecanal, tetradecanal, *Z*-11-pentadecenal, pentadecanal, (Z,Z,Z)-7,10,13-hexadecatrienal); four norisoprenoids (*β*-cyclocitral, *α*-ionone, (*E*)-geranylacetone, (*E*)-*β*-ionone); four alkenes (3,5-dimethyl-1-hexene, 3-ethyl-1,4-hexadiene, 1,2-dimethyl-cycloheptene, 8-heptadecene); two alkanes (1-butenylidene-cyclohexane, heptadecane); three alcohols ((*E*)-2-undecen-1-ol, 2,4-dimethyl-cyclohexanol, (*Z,Z*)-6,9 pentadecadien-1-ol); one ketone (6,10-dimethyl-2-undecanone) and one furan derivative (2-propyl-furan). The above common constituents in the two green algae covered almost all the VOC categories, differently from the red and brown algae.

> (E)-β-Ionone was the only compound found to existing in all seven algae characterized in this study and it is widely distributed in the plant kingdom. As a C13 norisoprenoid, (E)-β-ionone can be produced by secondary metabolism of β-carotene and can also be produced by thermal degradation and photooxidation of carotenoids [25,26]. It has been reported that (E)-β-ionone has a wide range of biological activities, including having a strong anticancer effect [27].

#### *2.2. Characteristic VOC Molecules and Potential Application in Chemotaxonomy* 2.2.1. PCA on Total VOCs Variables

Principal component analysis (PCA) on data from fiber DVB/CAR/PDMS exhibited that, except for *D. dichotoma* and *E. prolifera*, the other five seaweeds were clustered together (Figure 2a). The PCA results for fiber PDMS show that *D. dichotoma* was distinct from the other six seaweeds (Figure 2b).

**Figure 2.** Principal component analysis (PCA) of VOC compositions in seven seaweeds determined by HS-SPME/GC–MS; score plot for (**a**) divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber; (**b**) polydimethylsiloxane (PDMS) fiber.

*D. dichotoma* is an outlier in PCA, being very different from the other six seaweeds. The molecules that contributed most to this difference were revealed in the loading plot and are reported in the Supplementary Materials (Figure S1 and Table S1). As expected, the main differences were regarding sesquiterpenes and diterpenes.

Based on the revised biogenetic scheme that is widely cited, *Dictyota* diterpenes can be divided into three groups (I–III), resulting from the first formal cyclization of the geranylgeraniol precursor, which makes them potentially useful as chemotaxonomic and phylogenetic markers [28]. Unfortunately, the number of diterpenes available in *Dictyota* VOCs is very limited, making it difficult for them to be used in chemotaxonomy.

On the other hand, *Dictyota* contains large numbers of sesquiterpenes, distinguishing them from other seaweeds in this study. It is still not clear whether volatile sesquiterpenes can be used as chemotaxonomic markers for species identification of genus *Dictyota*, but it is worth exploring this through the VOC approach.

#### 2.2.2. PCA on Aldehyde Variables

Using all the VOC data as PCA variables, *E. prolifera* was found to be an outlier, as shown in Figure 2a (DVB/CAR/PDMS fiber), but not in Figure 2b (PDMS fiber). Considering that aldehydes are the most abundant VOC categories (Figure 1), aldehydes were used as variables in PCA to reveal chemical differences between species. The results show that *E. prolifera* was separated well from other seaweeds (Figure 3). The aldehydes that contribute the most to species differences are shown in Table 4. There are six aldehydes characteristically distributed in *E. prolifera*.

**Figure 3.** Bi-plot of PCA using aldehydes: (**a**) DVB/CAR/PDMS fiber; (**b**) PDMS fiber.

**Table 4.** Various aldehydes in PCA loading plot, as shown in Figure 3.

Δ with the highest content.

Aldehydes are substances released by algae under biotic or abiotic stress and some aldehydes may induce the synthesis of a series of oxylipins in algae and therefore act as inducers of metabolic responses [29]. In view of the limited species and numbers of seaweeds in the present study, our data can only suggest that aldehydes may be of important value for the chemotaxonomic significance of *E. prolifera* and that the DVB/CAR/PDMS fiber is more suitable for headspace solid phase microextraction for aldehydes.

The volatile components of red algae *Bangia fuscopurpurea*, *Gelidium latifolium*, *Callithamnion granulatum*, *Ceramium elegans*, *Laurencia papillosa* and *Laurencia coronopus* from Black sea was detected and found that hydrocarbons can be used as chemotaxonomic markers of the two classes Bangiophyceae and Florideophyceae [30]. The chemotaxonomic significance was also discussed according to VOCs detection in two brown algae: *Taonia atomaria* and *Padina pavonica* [6]. The VOCs were used in evolutionary relationship discussion between the algae and liverwort *Fossombronia angulosa* due to the similarity [31].

#### *2.3. Network Pharmacology and Potential Biomedical Application of D. Dichotoma*

VOCs in *D. dichotoma* are characterized by sesquiterpenes and diterpenes. It has been reported that a total of 78 structurally diverse diterpenes have been isolated from *D. dichotoma* and exhibit multi-biological properties, such as cytotoxic, antitumor, antiviral, antifouling, antioxidant, antibacterial and antifungal activities [21]. In the present study, a network pharmacology method was performed to verify and discover new bioactivities of *D. dichotoma*.

First, the VOCs of *D. dichotoma* were entered into the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) in the "chemical name" search box to obtain relevant targets. The "compound–target" relationships are shown in Figure 4, with 31 nodes (1 alga, 10 compounds and 20 targes). Comparing with the average degree score, 6.07, from network topology analysis, six key compounds were disclosed as cedrene, α-selinene, cubenol, *α*-muurolene, 2,4-decadienal and *γ*-muurolene, of which most are sesquiterpenes. The first three compounds are cedrene, α-selinene and cubenol, each of which can act on 10 targets.

**Figure 4.** Compound–target interaction network of Dictyota dichotoma.

Next, the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to obtain the potential pathway in which VOCs might play a role.

According to the literature, the neuroactive ligand–receptor interaction pathway plays an important role in lung cancer etiology [32].  The non-polar fractions of *D. dichotoma* exhibit anticancer activity in vitro, including the lung adenocarcinoma cell line (A-549) [33].

**Figure 5.** Bubble chart of pathway enrichment information.

In addition, it should be noted that the neuroactive ligand–receptor interaction pathway is the most relevant pathway for VOCs in *D. dichotoma*, with nine target genes involved—CHRM1, CHRM2, CHRM3, CHRNA2, GABRA1, GABRA2, GABRA3, GABRA5 and ADRA1B. The neuroactive ligand–receptor interaction pathway is involved in environmental information processing as well as signaling molecules and interactions and an association has been found with certain neuropsychiatric disorders [34]. Therefore, *D. dichotoma* may have some potential use in the study of some neuropsychiatric diseases.

#### **3. Materials and Methods**

#### *3.1. Sample Collection*

The samples of seven algae were single-point collected from the coast of Qingdao city (120◦20- 30" E, 36◦3- 43" N, the Yellow Sea), Shandong Province, China, in July 2019. All of the studied algae are local common species, including *Grateloupia filicina* (Wulfen) C. Agardh, 1822 (Halymeniaceae Bory, Gigartinales Schmitz, Rhodophyceae), *Polysiphonia senticulosa* Harvey,1862 (Rhodomelaceae Areschoug, Ceramiales Oltmanns, Rhodophyceae), *Callithamnion corymbosum* (Smith) Lyngbye, 1819 (Ceramiaccae Dumoritier, Ceramiales Oltmanns, Rhodophyceae), *Sargassum thunbergii* (Mertens ex Roth) O'Kuntze, 1893 (Sargassaceae Kuetzing, Fucales Kylin, Phaeophyta), *Dictyota dichotoma* (Hudson) J. V. Lamouroux, 1809a (Dictyotaceae Lamourous ex Dumortier, Dictyotales Kjellman in Engler et Prantl, Phaeophyta), *Enteromorpha prolifera* (O.F.Müller) J. Agardh, 1883 (Ulvales Blackman et Tansley, Ulvaceae Lamourous ex Dumortier, Chlorophyta), *Ulva lactuca* Linneaeus, 1753 (Ulvales Blackman et Tansley, Ulvaceae Lamourous ex Dumortier, Chlorophyta). The voucher specimens have been deposited in the Key Laboratory of Marine Drugs, Chinese Ministry of Education, School of Medicine and Pharmacy, Ocean University of China.

The samples were separately collected and placed in an air-tight plastic bag containing surrounding seawater and were immediately transported to the laboratory. Before extraction, each sample were cut into small pieces and excess water was removed using filter paper.

#### *3.2. Headspace Solid Phase Microextraction (HS-SPME)*

HS-SPME was performed with a manual SPME holder. Four types of fibers obtained from Supelco Co. (Bellefonte, PA, USA) were compared for their adsorption properties in pilot experiments and two fibers, divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS, 50/30 μm) and polydimethylsiloxane (PDMS, 100 μm) were finally, chosen. Fibers polyacrylate (PA, 85 μm) and 7 μm PDMS were not used in the present study. The fibers were activated in advance, according to the instructions.

A 1 g amount of prepared sample was placed into 4 mL glass vials and sealed using a cover with a Teflon gasket to provide a closed environment. The vials were placed at 60 ◦C for 15 min to equilibrate and the fiber was then pushed into the vial and maintained there for 20 min to adsorb the VOCs of the sample. After absorption, the fiber was removed from the vial and inserted into the injector (250 ◦C) of the GC–MS and kept for 6 min (DVB/CAR/PDMS fiber) or 4 min (PDMS fiber) to realize desorption. HS-SPME was performed in triplicate for each sample.

#### *3.3. Gas Chromatography–Mass Spectrometry (GC–MS) Analyses*

GC–MS analyses was performed on a Thermo Trace 1300 ISQ gas chromatographymass spectrometer (Thermo Fisher Scientific Inc., San Jose, CA, USA) equipped with a TG-5MS capillary column (5% phenyl-methylpolysiloxane, 30 m × 0.25 mm, 0.25 μm, Thermo Fisher Scientific Inc.). For DVB/CAR/PDMS fiber, the oven temperature was initially set at 70 ◦C and maintained for 1 min, increased at a rate of 3 ◦C/min to 100 ◦C and continually increased at a rate of 5 ◦C/min to 200 ◦C, followed by a final hold at this temperature for 2 min. For PDMS fiber, the oven temperature was initially maintained at 70 ◦C for 2 min, increased from 70 to 200 ◦C at 3 ◦C/min and then held at 200 ◦C for 6 min. Helium (99.9% purity) was used as the carrier gas at a flow rate of 1 mL/min. The temperature of the injector, detector transfer line and ion source were 250, 270 and 230 ◦C, respectively. The MS detector was operated in the full scan mode and the electron energy was 70 eV and the scan range was from *m/z* 30 to 350 amu. All analyses were performed in triplicate.

Visualization, calibration and normalization of the GC–MS data were performed using Xcalibur 2.1 (Thermo Fisher Scientific Inc.). The VOC peaks were identified by comparison of their retention index (RI) and MS data with data in the NIST Chemistry WebBook [35] and NIST 11 MS Data Library, respectively. The RI values of the VOCs were calculated by analyzing the C7–C30 *n*-alkanes (Sigma-Aldrich, St. Louis, MO, USA) under the same GC–MS conditions as samples. Authentic standards included trans-2-nonenal (Shanghai Macklin Biochemical Co., Ltd., Shanghai, China), tridecanal (Shanghai Macklin Biochemical Co., Ltd.), 1-octen-3-ol (Shanghai Macklin Biochemical Co., Ltd.), tetradecanal (Shanghai Aladdin Biochemical Technology Co., Ltd., Shanghai, China), germacrene D (Toronto Research Chemicals, Toronto, ON, Canada) and (*E*)-*β*-ionone (Xiya Chemical Technology Co., Ltd., Chengdu, China), which were used for confirming VOC identity. All VOC peaks were quantified by area normalization with consistent peak parameters (baseline, area noise and peak noise) prior to data analysis and statistics.

#### *3.4. Chemometrics and Network Pharmacology Analysis*

The principal components analysis (PCA) of all VOCs was conducted using SIMCA 14.1. The targets of identified volatile components were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, https: //tcmspw.com/tcmsp.php, accessed on 21 December 2020) [36], the gene information of the related targets was taken from the Uniport database (https://www.Unitprot.org/, accessed on 21 December 2020) and the String database (https://string-db.org/, accessed on 21 December 2020) [37,38] and KEGG pathway enrichment analysis were accessed through DAVID software (https://david.ncifcrf.gon/, accessed on 21 December 2020) [39] with the corresponding bubble chart realized using the R program. The interactive component– target relationships in algae were visualized using Cytoscape 3.7.2 software.

#### **4. Conclusions**

The volatile composition of seven algae from Yellow Sea of China was detected by HS-SPME/GC-MS, the VOCs of three red algae *Grateloupia filicina*, *Polysiphonia senticulosa* and *Callithamnion corymbosum* among them are first reported. The PCA analysis of VOCs reveals the chemotaxonomy significance of aldehydes in green algae *Enteromorpha prolifera* and sesquiterpenes in brown algae *Dictyota dichotoma*, as well as the applicability of DVB/CAR/PDMS fiber in volatile aldehydes. The network pharmacology analysis of *Dictyota dichotoma* indicate the potential biomedical application in fields of lung cancer and neuropsychiatric diseases. Our study exploits the new research value of VOCs in algae from the perspective of chemotaxonomy and network pharmacology.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/md19040192/s1, Figure S1: PCA of VOC compositions in seven seaweeds determined by HS-SPME/GC–MS, loading plot with: (a) DVB/CAR/PDMS fiber; (b) PDMS fiber. Table S1: The compounds corresponding to dots with coordinates in the loading plot.

**Author Contributions:** Conceptualization, H.L. and P.W.; methodology, P.W.; software, P.W., J.C. and L.C.; validation, L.C. and L.S.; formal analysis, P.W.; investigation, P.W.; data curation, P.W.; writing—original draft preparation, P.W.; writing—review and editing, H.L.; project administration, H.L.; funding acquisition, H.L. and P.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the National Natural Science Foundation of China, grant number 81973433 (H.-B. Liu), Independent Research Projects for Graduate Students of Ocean University of China (P.-R. Wang).

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

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available in the manuscript.

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

#### **References**


*2.7. Dealing with Missing Data*

The authors contacted the corresponding author via email regarding any unclear information in the concerned study. If the data were still insufficient after contacting the corresponding author or if contact was not possible, it was analyzed using the available data.

#### **3. Results 3. Results**

data.

#### *3.1. Study Selection 3.1. Study Selection*

*2.7. Dealing with Missing Data*

*Healthcare* **2021**, *9*, x 5 of 18

Through database searching, a total of 2623 articles were searched, and no studies were identified through other sources. After removing 843 duplicates, the titles and abstracts of 1780 articles were screened for first inclusion, and 1714 studies were excluded. After assessing full-text of the remaining 66 articles, 36 studies including eight only abstract available with no details, one case series, four quasi-RCTs, two review articles, 10 not meeting intervention criteria, five without outcomes of interest, four using duplicated data, and two unavailable full-text were excluded (Supplement S2). Finally, total 30 RCTs [18–47] were included in qualitative synthesis, and 21 RCTs [19,20,22–24,27–31,33,35,36,38,41–47] were included in meta-analysis (Figure 1). Through database searching, a total of 2623 articles were searched, and no studies were identified through other sources. After removing 843 duplicates, the titles and abstracts of 1780 articles were screened for first inclusion, and 1714 studies were excluded. After assessing full-text of the remaining 66 articles, 36 studies including eight only abstract available with no details, one case series, four quasi-RCTs, two review articles, 10 not meeting intervention criteria, five without outcomes of interest, four using duplicated data, and two unavailable full-text were excluded (Supplement S2). Finally, total 30 RCTs [18–47] were included in qualitative synthesis, and 21 RCTs [19,20,22–24,27– 31,33,35,36,38,41–47] were included in meta-analysis (Figure 1).

The authors contacted the corresponding author via email regarding any unclear information in the concerned study. If the data were still insufficient after contacting the corresponding author or if contact was not possible, it was analyzed using the available

**Figure 1.** A PRISMA flow diagram of the literature screening and selection process. AMED—Allied and Complementary Medicine Database; CENTRAL—Cochrane Central Register of Controlled Trials; CNKI—China National Knowledge Infrastructure; KCI—Korea Citation Index; KISS—Korean Studies Information Service System; RCT—randomized controlled trial. **Figure 1.** A PRISMA flow diagram of the literature screening and selection process. AMED—Allied and Complementary Medicine Database; CENTRAL—Cochrane Central Register of Controlled Trials; CNKI—China National Knowledge Infrastructure; KCI—Korea Citation Index; KISS—Korean Studies Information Service System; RCT—randomized controlled trial.


**Author details**

Mark Schifter1,2, Suran L. Fernando3,4 and Jamma Li4

1 Department of Oral Medicine, Oral Pathology and Special Care Dentistry, Westmead Hos‐ pital, Western Sydney, Australia

2 Faculty of Dentistry, University of Sydney, Sydney, NSW, Australia

3 Department of Clinical Immunology and Allergy, Royal North Shore Hospital, Sydney, Australia

4 Sydney Medical School – Northern, Sydney University, Sydney, Australia

Department of Clinical Immunology and Allergy, Royal North Shore Hospital, Sydney, Australia


**1. Introduction**

Due to the global increase in processed food production, the market for fresh food is predicted to grow more in coming years. Modern consumers have become more nutrition and health conscious and have a growing interest in *(i)* where their food comes from and *(ii)* in food additives [1]. Food labeling has increased interest in understanding the physiological needs of the body. Consumers tend to shy away from chemical compounds such as food additives, viz., antioxidants, preservatives and colors. They search for natural additives in natural foods that are safe and good for them. On the other hand, consumers have a growing awareness of natural products where toxicants may also be present [2].

Historically, throughout the world, natural pigments have been used for many purposes. The advent of synthetic dyes reduced the use of natural pigments to a greater extent. Recently, dyes derived from natural sources are gaining importance, since some synthetic dyes have been reported to have carcinogenic effects [3,4]. Natural pigments gained interest due to worldwide concern over the use of eco-friendly and biodegradable materials. Demand for natural colorants, especially yellow and red pigments, israpidly increasing worldwide. Production of safe and natural pigments from natural resources are mainly being focused on in food, textile and pharmaceutical industries, due to the serious environmental and safety problems caused by many artificial synthetic pigments [5].

Many natural pigments are from plant or microorganism-based origins. There are a number of major drawbacks to plant pigments, viz., non-availability throughout the year, pigment stability and solubility. Exploitation of plants on a large scale may lead to a loss of valuable species. For these reasons, the pigments from plant sources are not considered viable. Microorganisms, viz., fungi, bacteria, algae and actinomycetes, are a reliable and readily available alternative source of natural pigments [6,7]. Microorganisms are advanta-

**Citation:** Poorniammal, R.; Prabhu, S.; Dufossé, L.; Kannan, J. Safety Evaluation of Fungal Pigments for Food Applications. *J. Fungi* **2021**, *7*, 692. https://doi.org/10.3390/ jof7090692

Academic Editor: David S. Perlin

Received: 16 June 2021 Accepted: 23 August 2021 Published: 26 August 2021

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

**Copyright:** © 2021 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/).

geous over plant for pigments production because of easy and rapid multiplication in a low cost medium, easy processing and growth independent from weather conditions [8].


3.1.2. Thermogravimetric Analyses (TGA)

Figure 9 shows the thermogravimetric curves of the ECC, ECC-R-120, and ECC-R-160 samples in air and nitrogen flow.

**Figure 9.** Thermogravimetric curves of ECC sample and the rubber functionalized mixtures ECC-R-120 and ECC-R-160 in air and nitrogen flow.

Comparing the TGA curves of the ECC-R-120 and ECC-R-160 samples with that of sample ECC, it is evident that the thermal stability of the functionalized samples is higher than that of the unfunctionalized resin ECC. Table 2 shows data from TGA analyses performed in air and nitrogen flow for the ECC, ECC-R-120, and ECC-R-160 samples. The initial degradation temperature (Td5%), expressed as temperature corresponding to a weight loss of 5 wt%, presents an increase of about 20 ◦C and 30 ◦C for the samples ECC-R-120 and ECC-R-160, respectively. The behaviour in nitrogen flow is the same as observed in air; in this last case, the initial degradation temperature (Td5%) of the samples ECC-R-120 and ECC-R-160 manifests an increase of 13 ◦C and 7 ◦C, respectively, with respect to the ECC sample.

**Table 2.** Data of TGA analyses performed in air and nitrogen flow for ECC, ECC-R-120, and ECC-R-160 samples.

\*Td5%: temperature corresponding to a weight loss of 5 wt%.

Considering the more reactive environment, the tests performed in air, the functionalized precursor presents a higher thermal stability than the raw precursor.

The functionalization reaction obtained at 160 ◦C allows for obtaining a modified precursor with greater thermal stability achieving a Td5% value up to 220 ◦C.


**Replacement**

**References**

60 Advances in Shoulder Surgery

[1] Smith J. Pathological appearances of seven cases of injury of the shoulder joint, with

[2] Codman E. Complete rupture of the supraspinatus tendon: Operative treatment with

[3] Hauser E. Avulsion of the tendon of the subscapularis muscle. The Journal of Bone and

[4] Kato SFH, Kan I, Yoshida M, Kasama K, Marumo K. Incomplete joint side tear of the sub

[5] Bhalla A, Higashigawa K, McAllister D. Subscapularis tendon rupture in an 8-year-old boy: a case report. American Journal of Orthopedics (Belle Mead, N.J.). 2011;**40**:471-474

[6] Lo IK, Burkhart SS. The comma sign: An arthroscopic guide to the torn subscapularis

[7] Denard P, Lädermann A, Burkhart S. Arthroscopic management of subscapularis tears.

[8] Foad A, Wijdicks C. The accuracy of magnetic resonance imaging and magnetic reso

[9] Barth J, Audebert S, Toussaint B, Charousset C, Godeneche A, Graveleau N, Joudet T, Lefebvre Y, Nove-Josserand L, Petroff E, Solignac N, Scymanski C, Pitermann M, Thelu C. Society FA Diagnosis of subscapularis tendon tears: are available diagnostic tests per

[10] Gerber C, Hersche O, Farron A. Isolated rupture of the subscapularis tendon. The Journal

[11] Barth J, Burkhart S, De Beer J. The bear-hug test: a new and sensitive test for diagnosing

[12] Lafosse L, Lanz U, Saintmard B, Campens C. Arthroscopic repair of subscapularis tear: Surgical technique and results. Orthopaedics & Traumatology, Surgery & Research.

[13] Osti L, Rizzello G, Panascì M, Denaro V, Maffulli N. Full thickness tears: Retaining the

of Bone and Joint Surgery. American Volume. 1996;**78**:1015-1023

a subscapularis tear. Arthroscopy. 2006;**22**:1076-1084

cuff. Sports Medicine and Arthroscopy. 2011;**19**:409-419

nance arthrogram versus arthroscopy in the diagnosis of subscapularis tendon injury.

tinent for a positive diagnosis? Orthopaedics & Traumatology, Surgery & Research.

Sports Medicine Arthroscopy Rehabilitation Therapy and Technology. 2012;

scapularis tendon with a small fragment in an adolescent tennis player: A case report.

**4**:24

report of two successful cases. Boston Medical Surgery. **20**:708-710

remarks. London Medical Gazette. 1834;**14**:280

Joint Surgery. American Volume. 1954;**36**:139-141

Sports Medicine and Arthroscopy. 2011;**19**:333-341

tendon. Arthroscopy. 2003;**19**:334-337

Arthroscopy. 2012;**28**:636-641

2012;**98**:S178-S185

2010;**96**:S99-108

**Chapter 4**

**Provisional chapter**

**Surgical Approaches in Shoulder Arthroplasty**

**Surgical Approaches in Shoulder Arthroplasty**

DOI: 10.5772/intechopen.70363

Shoulder arthroplasty is a complex procedure that is becoming increasingly more utilized throughout the world. Due to the numerous static and dynamic stabilizers of the glenohumeral joint, along with the relative proximity to vital neurovascular structures, great care must be taken to access the joint in a safe and effective manner. To date, there are two well-described approaches utilized in shoulder arthroplasty: the deltopectoral approach and the anterosuperior approach. Both of these approaches are effective in accessing the glenohumeral joint; however, due to their anatomic location, they both have distinct advantages and disadvantages. The aim of this book chapter is to describe the methodology for approaching the glenohumeral joint through each of these approaches, as well as to discuss the advantages and disadvantages of utilizing each. In addition, we aim to discuss the various methodologies for closing these wounds and, briefly, to discuss the

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

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

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

Shoulder arthroplasty is becoming an increasingly popular procedure performed for a variety of problems. It has been utilized with great success for advanced degenerative and traumatic conditions of the shoulder [1–5]. Because the shoulder joint is surrounded by vital structures including muscles, nerves, and blood vessels, great care must be taken to ensure safe but adequate exposure to the glenohumeral joint when performing shoulder arthroplasty. To date, the deltopectoral approach [6] and the anterosuperior lateral approach [7] are the two main approaches that have been well described in the literature for access to the glenohumeral joint for shoulder arthroplasty. Each approach offers distinct advantages and disadvantages with

Brian W. Sager and Michael Khazzam

Brian W. Sager and Michael Khazzam

http://dx.doi.org/10.5772/intechopen.70363

**Abstract**

**1. Introduction**

Additional information is available at the end of the chapter

other approaches described in the orthopedic literature.

**Keywords:** shoulder, arthroplasty, approaches, deltopectoral, anterosuperior

Additional information is available at the end of the chapter

**Provisional chapter**