*3.1. C3N4 Characterization*

Figure 1A,B shows the morphology of the synthesized C3N4. The FTIR spectra demonstrate characteristic peaks at 810 cm−1 and 1600–1200 cm−1 (Figure 1C), corresponding to the breathing mode of triazine units and the stretching mode of CN heterocycles, respectively [55]. All of this indicates successful C3N4 synthesis. The zeta potential value indicates that C3N4 was negatively charged (−18 to −24 mV in both deionized water and nutrient solutions); half-strength Hoagland's solution further decreased the zeta potential as compared with deionized water. The hydrodynamic diameters of C3N4 in half-strength Hoagland's solution and deionized water were similar at 50 mg/L. However, at 250 mg/L, the hydrodynamic diameters of C3N4 in half-strength Hoagland's solution and deionized water were decreased to approximately 600 and 250 nm, respectively (Figure 1D). The possible explanation could be that a high concentration of C3N4 simply formed large aggregates, which could settle faster in the solution.

**Figure 1.** Characterization of C3N4 nanosheets. (**A**,**B**) represent TEM images of C3N4; (**C**) shows FTIR scheme 3, N4; (**D**) shows the hydrodynamic diameter and zeta potential of C3N4 in deionized water (DI) water and half-strength Hoagland's solution. Values of zeta potential followed by different uppercase letters are significantly different at *p* < 0.05; values of hydrodynamic diameter followed by different lowercase letters are significantly different at *p* < 0.05.


**4. Conclusions**

In conclusion, the GaN-based DFB LDs that integrated with the surface and sidewall gratings were investigated by the FDTD method. The surface and sidewall gratings alongside the p-contact metal stripe on the ridge waveguide were fabricated by EBL and ICP etching on the same epitaxial

wafer. The DFB LD with the 20th order, 80% duty-cycle surface gratings showed a single wavelength emission at 398.86 nm with an FWHM of 0.32 nm under the electrical pulsed driving, and the DFB LD with the 20th order, 80% duty-cycle sidewall gratings obtained a peak emission at 399.95 nm with an FWHM of 0.23 nm. Additionally, both of the DFB LDs showed a narrower linewidth compared to that of the F–P LDs. Moreover, the FWHM of the DFB LDs with the ridge width of 2.5 μm was obviously lower than that of the DFB LDs using the same type of gratings with ridge widths of 5 or 10 μm, which indicates that the narrow ridge width was favorable for the narrowing of the linewidth. Furthermore, the sidewall grating DFB LDs possessed a slightly higher slope e fficiency than that of the surface grating DFB LDs with the same ridge width and period of gratings. Given that, the DFB LD with sidewall grating required a lower fabrication cost and achieved better device performance compared to the surface grating DFB LDs, which makes it a better choice for these applications. In addition, in order to further improve the performance of the DFB LDs, the optimization of the structure of the gratings and the conduction of the cavity surface coating process are required to reduce threshold current and improve slope e fficiency. Additionally, the side-mode suppression ratio and the high resolution spectral measurement are also required in future work.

**Author Contributions:** Conceptualization—Z.D. and J.L.; data curation—Z.D. and M.L.; methodology—Z.D. and M.L.; project administration—J.L.; supervision—J.L.; validation—W.X. and S.L.; writing original draft—Z.D.

**Funding:** This work was funded by Science Challenge Project (No. TZ2016003-2), National Natural Science Foundation of China (No. 61804140), and National Key R&D Program of China (No. 2017YFB0403103).

**Acknowledgments:** The authors would like to thank the Nanofabrication facility in Suzhou Institute of Nano-tech and Nano-bionics (CAS) for equipment access.

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


KEHATI Index from 2012 to 2016 fluctuated but did not soar so far that it can be said that PBV is stable, ranging from 4.61 to 5.57, which is indicated in the graph in **Figure 5**.

Based on the description above, it can be seen how the relationship between CSR and PBV can be analyzed, as follows:

PT Timah (Pesero) Tbk implements CSR almost near perfect which is an average of 89.62%, but its PBV value does not show a good development of an average of 1.55. This means that investors still think that investing in the mining sector has a high risk. But, on the contrary, PT Unilever Indonesia Tbk has a low CSR that is 41.77%, but its PBV value is 49.09, meaning investors prefer stocks with low risk because PT Unilever Indonesia products are already known by the public. Whereas, for other companies, it can be said to be balanced between the value of CSR and PBV.

Hypothesis examiner:

Based on the draft hypothesis stated above whether corporate social responsibility affects the value of companies listed on the SRI KEHATI Index from 2012 to 2016 by using the SPSS obtained as follows (**Tables 6**–**8**):

Simple linear regression analysis:

*Implementation of Corporate Social Responsibility to Increase the Value of Companies Listed… DOI: http://dx.doi.org/10.5772/intechopen.93482*

#### **Figure 4.**

*Graph of issuers' CSR that was registered at SRI KEHATI Index in 2012–2016.*

**Figure 5.** *PBV chart of companies listed on the SRI Kehati Index.*

From the research model, the regression equation is obtained as follows:

$$\mathbf{Y} = \mathbf{41}, \mathbf{512} - \mathbf{0}.\\ \mathbf{014X} + \mathbf{e} \tag{4}$$

or

$$\text{Company's value} = 41,512 - 0.014 \,\text{CSR} + \text{e} \tag{5}$$

Based on the above output, a significance value of 0.918 is known to be greater than 0.005, so it can be concluded that H0 is accepted and Ha is rejected, which means CSR (X) has no effect on PBV (Y).

#### **Table 5.**

*Statistic description of price-to-book value listed on Sri Kehati Index, year 2012–2016.*

#### **Table 6.**

*Model summary.*

*Dependent variable: CSR.*

*b Predictors: (constant) PBV.*

*CSR has no influences on PBV, and it can be shown the significance value 0.918.*

**Table 7.** *ANOVA.a* *Implementation of Corporate Social Responsibility to Increase the Value of Companies Listed… DOI: http://dx.doi.org/10.5772/intechopen.93482*


4.3 Active indirect concept for TES with single tank

Active indirect design with a single storage tank is also possible which is quite efficient than the two-tank storage system. In this design, TES material in cold and hot

Figure 2. Active direct concept for TES [13].

Figure 3. Active indirect concept for TES using two tanks [13].

state is stored in the same tank as illustrated in Figure 4. The materials get separated by itself due to different material properties at different temperature. Thermal stratification causes the hot material to be stored in the upper part of the tank, while cold material is stored in the bottom. This system is also known as thermocline system, which is approximately 35% cheaper than the two-tank storage system.

In thermocline storage systems, a filler material like rocks, concrete, or sand is used so that less quantity of TES materials is required to enhance the thermocline effect. In this system, handling accuracy during charging and discharging of the TES is required using controlled methods and devices to avoid mixing of materials. Among differently investigated structures during discharging of thermocline, packed-bed configuration is reported to be the best performing [13].

## 4.4 Passive concept for TES

This is another concept of thermal energy storage in which TES materials are fixed and do not move during entire processes. The concept is demonstrated in Figure 5. The TES material is kept in a tank through which HTF is circulated. During charging phase, hot HTF is passed through TES and it transfers its heat to the TES. During discharging, cold HTF is passed from TES which is already at very

#### Figure 4.

Active indirect concept for TES integration, single tank [13].

Figure 5. Passive concept for TES [13].

high temperature. In such systems, thermal conductivity of the storage material and surface contact area defines the rate of heat transfer from and to the HTF during charging and discharging, respectively. In this type of design, rocks and concrete are used as TES materials.


**3. Methodology**

#### *3.1. Measurement Instrument*

The questionnaire had three parts, namely, (1): socio-demographic characteristics of consumers (e.g., gender, age, education level, personal income, and place of living); (2) general questions about consumers' sustainable consumption behaviour; (3) factors influencing consumers' sustainable consumption behaviour. All measurement scales for the constructs have been included in prior publications. The SCB scale is a multi-dimensional second-order construct, which incorporates three dimensions, i.e., "Quality of Life (QL)", "Care for the Future Generation (CEW), and "Care for the Environ-mental Well-being (CFG)". Twenty-four items were used to measure QL, CEW, and CFG on the scale developed by Quoquab et al. (2019). The measurement of the constructs of environmental knowledge and sustainable consumption behaviour intention was based on the research conducted by Saari et al. (2021). Both constructs included three items each. The environmental influences construct included three items based on the operationalisation applied and validated by Figueroa-García et al. (2018). Nine items for measuring materialism were adopted from the scale of Lindblom et al. (2018) and Ponchio and Aranha (2008). Sustainable consumption promotion involves information about environmental issues, green product promotion, the promotion of recycling, and other external initiatives. To measure PSC, four items from the scale provided by Piligrimiene et al. ˙ (2020) were used. All items were measured on a seven-point Likert scale [where 7 specifies a positive opinion (Strongly Agree/Always) and 1 denotes a negative opinion (Strongly Disagree/Never)]. The measurement items have been listed in Appendix B (Table A2).

The questionnaire was professionally translated into Bulgarian by two bilingual experts from the Department of Language and Specialised Training of Foreign Students at one of the largest Bulgarian universities, and then a standard back translation procedure was used to ensure that the translated content conformed with the original English meaning.

## *3.2. Sample and Data Collection*

The survey design followed a sequence of steps, including a pilot test with 50 respondents aimed to identify problematic items and further improve the survey (Fink 2016). The data were collected with the help of a certified sociological agency operating in Bulgaria. A quota sample was formed for the study of three defined characteristics (gender, age groups, and place of living in administrative-territorial regions in the country). It reproduced the structure of the population in Bulgaria as of 31 December 2021 (in conformity with the data published by the National Statistical Institute in the Republic of Bulgaria). A total of 522 respondents were approached for the questionnaire-based online survey. Observations with missing values and straight lining were deleted, leaving a total sample size of 489. This sample size highly exceeded the recommended minimum sample sizes of 160 and 146 as indicated by the inverse square root and gamma-exponential methods, respectively (Kock and Hadaya 2018).

The respondents' age ranged between 16 and 64 years, with an average age of 40. The age group (based on the age groups formulated by the National Statistical Institute in the Republic of Bulgaria) and the other sample characteristics have been presented in Table 1.

**Table 1.** Socio-demographic profile of the sample.

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

This study employed partial least squares structural equation modelling (PLS-SEM) and the latest software version of SmartPLS–SmartPLS 4 (Ringle et al. 2022) to test the hypothesized relationships. SmartPLS software is widely used in many social science disciplines because of its variety of capabilities and user-friendly features. It can estimate very complex and higher-order models, with a considerably smaller sample size at the same time (Sarstedt et al. 2021).

The analysis pursued the guidelines, procedures, and cut-off values as suggested by Hair et al. (2021). The skewness and kurtosis tests were assessed. The findings indicated that the assumption of normality was violated for some items since the threshold of the absolute skewness value and the absolute kurtosis value exceeded 1.

A two-step process was followed, where the measurement model (outer model) was analysed first, followed by the structural model (inner model). To assess the significance of the path coefficients and the loadings, a bootstrapping method with 5000 resamples was used.

Harman's single-factor test was performed to detect common method bias (CMB) before proceeding to measuring the structural model and the measurement model. The result based on the unrotated principal axis factoring revealed that the first factor explained 34.7% of the total variance, which was less than the critical value of 50% (Fuller et al. 2016). Henceforth, CMB was not at all a concern in the present study.

The model in the present study contained eight first-order reflective constructs and a second-order reflective-reflective construct. The PLS-SEM literature outlines several approaches to the estimation of models containing higher-order constructs, such as the repeated indicators approach and the two-stage approach (embedded and disjoint) (Sarstedt et al. 2019). Since these approaches provide highly similar results when sample sizes are sufficiently large, the disjoint two-stage approach was chosen for the current research. In the first stage of the approach, the model was estimated for reliability and validity with only first-order constructs. After the evaluation of the model, the construct scores for the SCB subconstructs QL, CEW, and CFG were obtained and named QL\_LV, CEW\_LV, and CFG\_LV, respectively. In the second stage, variables QL\_LV, CEW\_LV, and CFG\_LV were used as SCB indicators for the purpose of assessing the hierarchal model. The structural model assessment was created on the grounds of the stage two results.


**A Comparison of Beach Nourishment Methodology and Performance at Two Fringing Reef Beaches in Waikiki (Hawaii, USA) and Cadiz (SW Spain)**

**Juan J. Muñoz-Perez 1,\* ,**† **, Shari L. Gallop 2,**† **and Luis J. Moreno 3,**†

Received: 14 March 2020; Accepted: 4 April 2020; Published: 9 April 2020

**Abstract:** Fringing reefs have significant impacts on beach dynamics, yet there is little research on how they should be considered in beach nourishment design, monitoring, and conservation works. Thus, the behavior and characteristics of nourishment projects at two reef protected beaches, Royal Hawaiian Beach (RHB) in Hawaii, USA, and Victoria Beach (VB) in Cadiz, Spain, are compared to provide transferable information for future nourishment projects and monitoring in fringing reef environments. The nourishment cost at RHB was nine times higher than VB. This is partly due to lower total volume and a more complex placement and spreading method at RHB, despite the much closer borrow site at RHB. There was a significant difference in post-nourishment monitoring frequency and assessment of accuracy. RHB elevation was monitored quarterly for 2.7 years at 30 m-spaced profiles, compared to 5 years of biannual surveys of 50 m-spacing at VB. An additional problem related to the presence of reefs at both RHB and VB was estimating the beach volume increase after nourishment, due to variable definitions of the 'beach' area and high alongshore variability in reef topography. At sites where non-native sediment is used, it is imperative to understand how wave and current energy changes due to reefs will influence nourishment longevity. Thus, differences in erosion and accretion mechanisms at both beaches have been detected, though are still little understood. Moreover, discrepancies in sediment porosity between the two sites (which should be surveyed in future nourishments) have been found, probably due to differences in the nourishment sand transportation and distribution methods. In summary, more dialogue is needed to explicitly consider the influence of fringing reefs on coastal processes and beach nourishment projects.

**Keywords:** beach nourishment; perched beaches; monitoring; cost; volume density; geologically controlled beach

#### **1. Introduction**

Beach nourishment is a key 'soft engineering' approach used worldwide to remediate coastal erosion, in contrast to 'hard coastal engineering' which involves construction of defenses such as breakwaters. Beach nourishment is used on beaches with a variety of sedimentary characteristics, from sand to gravel [1]. Such beach fills are generally designed using simplified mathematical models that assume the geologic setting has no influence on the beach morphology [2]. One such commonly used model is the equilibrium beach profile, which is meant to reflect the beach profile that would occur if the forces (dominantly waves and water levels) were held constant for a sufficiently long

time [2,3]. However, there is increasing research showing that the geologic setting plays a dominant role in contemporary beach morphodynamics [4–7]. In fact, some studies have taken into account the former geologic setting to design multifunctional artificial reefs that serve several purposes [8].

One common type of geologically-controlled beach is situated landward of areas of hard bottom, such as rock or coral reefs. Reefs have large impacts on coastal hydrodynamics, sediment transport, and morphology, such as by influencing water level fluctuations [9], wave set-up and cross-reef currents [10], wave breaking, wave-induced flows, and wave attenuation over reef platforms [11–15], which affect the beach morphodynamics tidal range at multiple scales [16–19], even under hurricane conditions [20,21].

Despite clear evidence that beaches with reefs behave differently to their non-reef counterparts, there has been scant attention given to how reefs should be considered in beach nourishment projects. A recent study by Habel et al. [22] focused on the methodology of a beach nourishment at Royal Hawaiian Beach (RHB), Waikiki, which is fronted by a fringing coral reef. They also analyzed the subsequent monitoring. We share their interest in beaches that are fronted by reefs and find this a welcome opportunity to start a discussion of how reefs should be considered in beach nourishment projects. Therefore, the goal of this paper is to compare the method and performance of beach nourishments in fringing reef environments, performed at RHB and Victoria Beach (VB) in SW Spain, in order to provide transferable information for future projects with similar fringing reef environments. We compare nourishment costs and methods for nourishment performing, total nourishment volume, fine sediment fraction, and post-nourishment monitoring techniques between the two beaches.

#### **2. Location Descriptions**

RHB in Hawaii and VB in Cadiz, SW Spain, are both supported by calcareous reef platforms (Figures 1 and 2, respectively). Beaches on both of these coasts have experienced significant long-term erosion, which is problematic for the nationally important tourism industries that they support. Erosional trends are expected to accelerate with sea level rise [23], which is currently about 6 mm/year in Hawaii [24], and 2–3 mm/year in Cadiz. The costs of adaptation strategies (including beach nourishment) are already being considered [25].

RHB extends 520 m alongshore in a crescent shape between the Royal Hawaiian groin at the western end of the beach and the Kuhio Beach Ewa groin at the eastern end. This beach has been losing volume at a rate of 760 ± 450 m3 /year, consistent with the design rate of 1,070 m3 /year, that is, the value used for the nourishment project [22]. Victoria Beach is 3 km long and is divided into two zones due to the existence of a transversal fault to the shoreline. The northern zone (~1.2 km long) has a quasi-horizontal rocky platform, the surface of which aligns with spring low tide level. The dominant swell comes from the west, which generates dominant littoral drift towards the southeast, with an average loss value (i.e., the sand volume lost every year) of approximately 30,000 m3 /year [26].

Southerly swell at RHB generates, over the summer months, an average significant wave height and period of 0.8 m and 13.1 s, respectively. Erosion is usually experienced under shorter period winter waves at this beach [22]. On the other side, the western swell in VB generates a significant wave height of about 0.7 m (similar to HRB wave), but the average period is less, approximately 7 s [27]).

A summary of noteworthy morphological and sedimentological characteristics for the two beaches is shown in Table 1, and a visualization of these morphological concepts is shown in Figure 3. RHB is microtidal, whereas VB is mesotidal, with spring tidal ranges of up to 0.9 and 3.8 m, respectively. All elevations are relative to the lowest low-water level (LLWL) (+ 0.00 m). Elevation of the reef flat coincides approximately with this datum, and therefore the reef platform is emerged at the low tide level for VB and almost emerged for RHB. Another difference is related to the nature of sediment, which is calcareous in RHB, and almost completely silicic in VB (where the sand is 90–95% quartz and 5–10% bioclastic material). Both beaches have fine/medium sand, although the median grain size (D50) is slightly larger, at 0.34 mm for RHB, and 0.25 mm at VB.

A final key difference is that while both beaches have their toes supported by a reef platform, VB also has a fault scarp along its entire front and lacks the offshore channel which characterizes RHB. At RHB, this offshore channel is thought to be an important conduit for cross-shore sediment transport [22], a topic also mentioned by other researchers [28].

**Figure 1.** Location of Royal Hawaiian Beach (RHB) in Waikiki, Hawaii, USA (**a**); and an aerial view where the fringing reef can be observed and the sand extraction site is located (**b**) (image source: Google Earth 2018).

(**a**)

**Figure 2.** Location of Victoria Beach (VB) and indication of the borrow site (named Placer de Meca) in Cadiz, SW Spain, (**a**); and a ground view of the reef platform (**b**) (source: Muñoz-Perez, 2009).

**Table 1.** Comparison between Royal Hawaiian Beach (RHB) and Victoria Beach (VB) characteristics.

**Figure 3.** Sketch clarifying different morphological terms used in the text. LLWL refers to the lowest low water level.

#### **3. Nourishment Methodology and Monitoring**

Here, we compare and contrast the nourishment techniques and post-nourishment monitoring at RHB and VB.

#### *3.1. Nourishment Method*

There was a big difference in the method of placing, conveying and spreading the sand between RHB and VB. At RHB, 18,350 m3 of sand was extracted from a source located approximately 0.6 km offshore of the nourishment site (Figure 1), using a pump that was suspended from a crawler crane stationed on a barge [22]. Sand was first pumped to an onshore dewatering basin adjacent to the placement location, before being distributed onto the beach using the truck haul method. This intermediate step was likely an important driver of the higher nourishment cost at RHB, discussed further in the next section.

In contrast, sand was pumped directly onto the dry beach at VB (i.e., the zone from high tide level to the landward edge). A volume of 260,000 m3 was extracted from a borrow site called Placer de Meca, located 42 km (23 nm) from VB, close to the Cape of Trafalgar (Figure 2), using a trailing suction hopper dredger (TSHD). The dredger extracted the sand from a depth of ~20 m, and the complete process (mining, going to the beach, delivery, and returning to the borrow site) took about 8 h. Some pictures showing different aspects of the sediment pouring are shown in Figure 4.

#### *3.2. Determination of Nourishment Volume*

Methods used to quantify beach nourishment volumes to determine payment vary and can have significant implications for total nourishment costs. Although there was no specific indication in Habel et al. [22] of the measurement and payment guidelines used at RHB, they state that the initial post-nourishment survey, accomplished 10 days following the completion of sand placement, was used to determine the total nourished volume. During the first beach nourishments performed in Spain in the 1980s, payments to dredging companies were based on volume calculated by comparing pre- and post-nourishment beach profiles. A prominent dredging company at the time adduced that they were not to be held responsible for any possible erosion that may happen to nourished beaches caused by wave or tidal activity. The basis for this discrepancy was later discussed by Rullens et al. [29]. The final court decision was to their advantage, and since then payment has been made on hopper measurements taken before the sand sediment is pumped onto the beach. However, pre- and post-volume calculations are still undertaken, but only for monitoring purposes.

Concerns about the accuracy of the volumes measured aboard the ship are common. Readers interested in a detailed description of the methodology, and about an independent and portable meter system for dry weight control in hopper dredgers in order to distinguish between the dry sand weight and the sea water weight can consult [30].

**Figure 4.** Different aspects of the sediment pouring on Victoria Beach, showing (**a**) pipe assembly; (**b**) transport of the pipe to the sea; (**c**) aerial view of the pipe while pouring; and (**d**) pipe outlet onto the beach.

#### *3.3. Post-Nourishment Monitoring*

Post-nourishment monitoring is important to confirm the design life of the project and to assist in future planning. At RHB, beach elevation data were collected quarterly along cross-shore profiles for 2.7 years after nourishment. At VB elevation campaigns were performed biannually for 5 years post-nourishment. According to US Army Corps of Engineers (USACE) recommendation [31], monitoring beach nourishment requires large numbers of topo-bathymetric surveys (quarterly during the year following nourishment works, and biannually for at least one additional post-nourishment year).

At RHB, the shore-normal profiles were established at ~30 m intervals along the 520 m-long site, and extended either beyond the seaward toe of the fringing reef, or where fringing reef was absent to depths of 2–3 m. Profiles were surveyed by tracking a swimmer moving a rod-mounted prism across the beach, into nearshore waters, and over the fringing reef. Surveying was carried out randomly with respect to wave state and tidal cycle. The main sources of elevation error were identified and analyzed, including survey measurement error (by using established control points) and surface interpolation error (by conducting a comparison between random real and interpolated elevations). This is particularly noteworthy because only a handful of investigations have described errors related to typical beach bathymetric data sets and their influence on quantitative and qualitative interpretations of nearshore processes [32]. Grosskopf and Kraus [33] recommend a mean error of less than 11.5 m3 /m of beach volume to estimate sand volume with an accuracy comparable to the 10% to 20% contingencies associated with project designs. Following this line of reasoning, instrument

error was not monitored at RHB, as the measurement device (Leica TC407 total station) had millimeter accuracy, although accuracy can diminish when this topographic procedure is applied to seaward zones, due to the inclination of the rod where the prism is mounted. A method to take into account and reduce this error was developed and described by [34].

On the other hand, at VB the sand was extended with a berm width of 100 m, and the berm elevation was about 1 m above the spring tidal level (+ 3.80 m over the datum). High resolution topographic levellings were carried out biannually during the following five years to account for sea-swell seasonality. Another important aspect of the post-monitoring survey method relates to the accuracy of the surveys. Surveying at RHB was undertaken regardless of the stage of the tidal cycle, due to the relatively low tidal range of 0.9 m (Table 1). H owever, at VB surveys were always performed at LLWL during spring tides. Surveys took two days, and thus the tidal range did not change appreciably during this monitoring. Cross-shore profiles were separated by 50 m alongshore and extended from the sea wall to the toe of the profile, even if submerged (the toe of the profile was always 1 m below LLWL). Bathymetries were considered unnecessary and would also likely have a large error due to the random roughness of the rock. Therefore, the maximum error detected for the levellings performed with a total station theodolite (according to the technique described in [35]) was <1 cm, and standard deviation was <0.5 cm.

In addition, VB is more gently sloping than RHB, at 4.5% compared to 13.3% (Table 1). This means that variations in the water level due to spring and neap tides could have a significant influence on volume measurements, as this can cause the sand level to vary by up to 0.67 m under negligible wave conditions at Cadiz [36].An additional difference in the post-nourishment monitoring was in the alongshore spacing of the cross-shore beach profiles. Some recommendations regarding beach profile spacing range from 300 m on long straight beaches with a 50% reduction close to structures or special points [31,37], to less than 150 m, according to the recommendation of the Coastal Engineering Manual [38]. Nevertheless, generally pre- and post-nourishment profile surveys are routinely collected at higher resolutions (with alongshore spacing of 60 m or less) to determine placement volumes accurately for payment purposes. Profiles at RHB were established at the relatively small spacing of 30 m, presumably to increase accuracy and decrease error associated with discretizing the domain. Although increasing the number of profiles measured decreases the error associated with discretizing the domain, it also increases the survey budget. Therefore, in order to find a compromise between a 5% allowable error of estimation and the available monitoring budget, the methodology developed in [35] was used to determine a 50 m profile spacing at VB [39,40]. Optimizing profile spacing is important for cost savings, however, while techniques exist for sandy beaches, it is not clear how reef variability influences the spacing required to capture key changes with sufficient alongshore variability.

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

#### *4.1. Performance of Nourishment Works*

The methods of nourishment material transport and distribution have significant implications for the resulting beach sediment characteristics. Habel et al. suggested that the truck haul method caused chemical compaction of nourished sands, which has important implications for slope stability [41] and ecological function [42]. In contrast, at VB sand porosity increased after the renourishments. This opposite behavior is probably due to the aforementioned differences in transport and distribution of nourishment material. While trucks transported dewatered sand at RHB, at VB there was a massive dumping of a mixture of sediment (20%) and water (80%) onto the backshore and foreshore from a trailing suction hopper dredge. According to Roman-Sierra [43] this procedure causes a significant increase in sand porosity, which subsequently decreases until it reaches its native value (about a year later), due to wave action driving spatial re-accommodation of the grains. Moreover, much of the volume loss after beach nourishment procedure can be due to a decrease in porosity. A detailed analysis of the impacts on porosity of the sand transport and nourishment method, as well as an accurate and

novel application of in situ measurements of the porosity of beach sand using a high-quality nuclear densimeter gauge, are also described in [43]. We suggest that measuring sediment porosity in future nourishments is advisable to determine if the transportation and distribution method significantly affects porosity, and hence beach slope stability and sand volume. The RHB nourishment project plans to maintain beach width for 20 years, with the initial replenishment plus an additional second phase after 10 years. This compares to a design life of 25 years for VB, although a small replenishment (about 25% of the original nourishment volume) was undertaken after 12 years, due to high social demand.

#### *4.2. Nourishment Volumes*

In reference to the measurements of placed sand volume conducted daily by contractors in RHB, a total estimated volume of 17,551 m3 was established. However, using the meritorious interpolation error methodology presented by Habel et al. [22], a beach volume increase of 12,700 ± 3700 m3 and a system volume increase of 13,700 ± 6300 m3 were confirmed. Revisiting some explanations about "beach" and "system" concepts are noteworthy. According to the aforementioned authors, the beach area extends a nominal 20 m seaward of the initial post-nourishment beach toe, while the system area extends an additional 150 m seaward. Regrettably, despite the laudability of the method, estimation of error becomes 30% at the "beach" zone and rises to 46% when the "system" zone is considered.

The error in sand volume estimation was somewhat lower in VB, probably due to the larger volume poured; 260,000 m3 was measured into the hopper of the dredger vs. 283,000 m3 surveyed on the beach, due to the increase of the porosity [43]. Another source of error was probably the existence of a problem at VB similar to that of RHB: the great variability of the levellings over the fringing reef. Ultimately, it was decided to exclude the reef from the surveying zone due to the lack of credibility.

Related to the seasonal erosion/accretion cycle, an unexpected volume gain occurred at RHB following increases in incident wave energy flux above 10,000 kg m3 /s 3 . As Habel et al. [22] stated, it would be interesting to obtain elevation data from regions further offshore of their present study area which could confirm the existence of a proximal sediment source/sink. That would permit finding the relationship between the pattern of erosion/accretion and cross-shore sediment transport. On the contrary, significant gaining was never detected at VB. An average erosion value of 10,000 m3 /year, which resulted in an irreversible loss [26], was obtained. However, this erosion rate was much smaller than for non-reef protected profiles subjected to similar wave energy on the same beach (30,000 m3 /year).

#### *4.3. Nourishment Costs*

There was a large difference in nourishment costs between the two beaches. At RHB, the cost was 2.9 million USD for recovery, dewatering, and emplacement of 18,350 m3 along a 520 m segment of coastline. This investment represents an overall average price of \$158 USD/m3 . It should be noted that the cost of removal of two dilapidated sandbag groin structures has not been subtracted, because is not available. In comparison, the cost of nourishment at VB, where sand was dredged locally from the seabed, ranged from 12 to 15 €/m3 (13–17 USD/m3 at the current rate of exchange) for the various nourishments, excluding taxes. Moreover, distance from the borrow site in Cadiz (close to the Cape of Trafalgar) was 37–46 km, compared to just 0.6 km at RHB. However, costs of mobilization and demobilization of equipment in Hawaii account for much of the project costs, due to how remote the islands are. It is also true that supplied volumes were far superior in VB, with over 200,000 m3 at all nourishment actions, thus allowing for a lower unit cost of sand. Further details about beach nourishments carried out from 1999 to 2010, storm climate, and sea level seasonal cycle in the Gulf of Cadiz, can be found in [44–46] respectively.

#### *4.4. Fine Sediments*

Consideration of the fine sediment fraction in nourishment material is important, not only because of its contribution to elevated turbidity, but also because fines almost immediately are transported offshore, leading to immediate loss of sediment volume on the beach [22]. At RHB, Habel et al. stated that no fines were present in the mined sand field prior to dredging and transport. Thus, the existence of a fine sediment plume observed during the nourishment procedure was probably due to carbonate dissolution [22]. This point is interesting, because the fine-sediment percentage was also negligible at the samples taken from Trafalgar (the borrow site used for VB), but nevertheless, there was always dredging-induced turbidity which decreased with time, reaching natural conditions approximately 9 min after the operations ceased [47]. Since Trafalgar sand is siliceous (and therefore the possibility of calcareous solution must be discarded), we should consider the plausibility of losses of the fine-sediment fraction when a Van Veen grab is used to sample the sediment, instead of another procedure which guarantees good fine material retention and undisturbed samples.

#### *4.5. Considering Reefs in Nourishment Design*

No specific methodology was applied to consider the reef in the design process of RHB fill. Habel et al. [22] used a similar sand, and beach slope was predicted to reach an equilibrium profile similar to the pre-nourished beach, which presumably was in equilibrium with the hydrodynamic conditions created by the reef. For a case where borrowed and native sands are not identical, wave energy dissipation over the reef (due to wave breaking or bottom friction) should be taken into account [48]. These fringing reef beaches are so usual that some numerical models (e.g., SBEACH or SMC) have been modified, trying to allow calculation of the profile [49,50]. Moreover, there are a lot of characteristics typical of this kind of beach. It is often assumed that perched beaches are more stable in time than non-perched beaches [51–53], through wave energy dissipation (e.g., [11,13]) and reducing rates of longshore sediment transport [54]. However, Gallop et al. [6] found that depending on the reef topography, reefs can generate current jets that can increase sediment transport on and off the beachface over hourly timescales. Moreover, over seasonal timescales, reefs can create highly dynamic seasonal changes in beach morphology [28].

Annual and interannual changes in beach morphology are also important on reef beaches [55]. The temporal and spatial variability of these oscillations can be large (e.g., [7,55]), but are difficult to measure, let alone incorporate into nourishment design. Leaving aside some easy-to-apply remedies, such as the modification on the *A* parameter of the Dean's formula [56], there are few engineering tools developed to take into account the idiosyncrasy of reef fringing beaches in nourishment design. Understanding the influence of these fringing reefs on beach behavior is imperative for coastal management, not only from the scientific point of view, but also the economic.

Finally, although not the focus of this paper, the potential impacts of sea level rise due to climate change on nourishment projects in fringing reef environments should be highlighted as a future line of research. Some research has already been undertaken on this topic at study sites, such as simulation of groundwater inundation in Honolulu [57], assessing vulnerability of low-lying areas in Maui [58] or in Oahu [59], or criticizing elevation levels for flooding due to sea level rise in Hawaii [60]. Moreover, mapping inundation probability has already been performed in some zones of the Gulf of Cadiz, Spain [61]. Due to concerns about the long-term performance of beach nourishment with sea level rise, different types of adaptation measures are been considered, such as seawalls or breakwaters, accommodating sea level rise by raising buildings, and even managed retreat. However, plans for these two sites have not yet been decided.

#### **5. Conclusions**

Characteristics of two reef protected beaches, RHB in Hawaii, USA, and VB in Cádiz, Spain, were compared to provide transferable information for future projects in areas with similar fringing reef environments. Results show that the complexity of the spreading method is a key determinant of overall cost, as well as total nourishment volume, which impacts on the cost per unit volume. This comparison has shown that more research is needed for determining optimal profile spacing, because while techniques exist for sandy beaches, it is not clear how reef variability influences the spacing required to capture key changes. It is also unclear how to include variable reef topography when estimating total nourishment volumes to determine nourishment volumes, and hence costs. Moreover, erosion and accretion mechanisms, and their temporal and spatial variability on reef beaches, are little understood, and hence difficult to incorporate into nourishment design. Sediment porosity surveying would be advisable in future nourishments to determine how porosity (and hence beach slope stability and sand volume) is affected by the transportation and distribution method. Publishing of studies of nourishment projects on reef beaches is rare. More dialogue and sharing of experiences are key to improving coastal zone management, optimizing nourishment projects, and preserving our precious beaches.

**Author Contributions:** All authors contributed equally. All authors have read and agreed to the published version of the manuscript.

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

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

#### **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


*3.12. Determination of Catalytic Parameters*

Kinetic parameters were calculated by plotting the rate of p-NPP and bis-p-NPP splitting at concentrations from 5 to 15 mM in a buffer containing 25 mM Tris-HCl, pH 9.0, 2 mM CoCl2, 2 mM FeCl3. The reaction was carried out at 25 ◦C. The Michaelis constant Km, the maximum reaction rate Vmax, and the turnover number kcat were determined by plotting the Layuver–Burk graph using the OriginPro 8.5 program.

#### *3.13. Molecular Modeling*

The target template alignment customization of the modeling process and 3D model building for CamPhoD (GenBank: WP\_043333989) were carried out using the Molecular Operating Environment (MOE) version 2018.01 package, using the Amber12: EHT forcefield (EHT-Extended Hueckel Theory) [62]. The alkaline phosphatase D from *B. subtilis* (PDB code: 2YEQ) was used as a template, which had a high-resolution crystal structure. The evaluation of structural parameters, contact structure analysis, physicochemical properties, and visualization of the results were carried out with the ligand interaction and dock modules in the MOE 2018.01 program [62].


**4.2.2 Substrate preparation for HR repair**

1. Set up PCR reaction as below:

Alternative: the two DNA fragments used for HR can also be generated by using a combination of restriction endonucleases *Bgl*II/*Nhe*I and *Pst*I/*Bam*HI for pRL-CMV (Progema). The use of former restriction enzymes will produce a DNA fragment containing

Application of Host Cell Reactivation in Evaluating the Effects of Anticancer Drugs

formation of DNA-LipofectamineTM 2000 complexes.

experimental design.

4. Perform dual-luciferase assay as section 4.1.4.

extracts on homologous recombination repair.

precise and overall NHEJ repair activities, respectively.

**4.3 HCR for NHEJ repair**

and Environmental Toxicants on Cellular DNA Repair Activity in Head and Neck Cancer 475

3. Add the 100 μl of DNA-LipofectamineTM 2000 complexes to each well and incubate at 37°C in a CO2 incubator for 6 h. Then the cells can be treated with toxicants (such as areca nut extracts, ANE) or anticancer drugs for another 24 h. Note: cells can be treated with toxicants or anticancer drugs prior to transfection that is dependent on

5. Determine the HR activity by comparing the firefly luciferase-calibrated *Renilla* luciferase activities between the environmental toxicants- or anticancer drugs-treated cells and vehicle-treated control cells. For examples, the treatment of anticancer drug camptothecin (CPT, a topoisomerase I inhibitor) can potentiate HR repair activity but

the areca nut extracts (ANE) repress HR repair in HEp-2 cells (Fig. 3).

Fig. 3. The use of HCR assays in evaluating the effects of camptothecin and areca nut

(A) Using the method illustrated in Fig. 2D, the *Renilla* luciferase activity (reflecting the HCR activity in Y-axis) can only be detected in the presence of both two DNA fragments (N+P, lane 3) but not in cells transfected with only one fragment (NheI or PstI, lanes 1 and 2). Treatment of camptothecin (CPT) stimulates HR repair efficiency in the cells (lane 4). (B) Dose-dependent repression of HR repair activity by areca nut extracts (ANE).

NHEJ is another DNA repair mechanism responsible to DSB. Unlike HR repair using sisterchromatids as templates, NHEJ directly joins the broken DNA ends by trimming a few nucleotides on the ends. Therefore, it is thought as an error-prone repair system. In this regard, we prepare two kinds of reporter DNA substrates that are suitable for analyzing the

For overall NHEJ repair, pRL-CMV is linearized with *Hin*dIII that cuts the flanking sequence between CMV promoter and the Renilla luciferase coding sequence. The luciferase will express after re-ligation regardless the loss of some nucleotides. For examining precise

c. Combine the diluted DNA with the diluted LipofectamineTM 2000 (total volume is 100 μl). Mix gently and incubate for 20 min at room temperature to allow the

CMV IE promoter and 5'-part of *Renilla* luciferase gene, the later ones result in 3'-part of *Renilla* luciferase gene and the poly-A signal. These two DNA fragments contain a 222-bp overlapping region for recombination (Fig. 2D).

Fig. 2. Schematic representation of substrate preparation for HCR assay of homologous recombination (HR) repair.

(A) Location of PCR primers on the pRL-CMV reporter plasmid.


IESVE

IES Virtual Environment (IESVE) IESVE [80] is an in-depth suite of building performance analysis tools. It allows the design and operation of energy efficient buildings. Whether working on a new building or existing building renovation project, IESVE offers the ability to test different options, identify the optimal passive solutions, compare low-emission and renewable-energy technologies, and formulate conclusions on building energy indicators. It includes numerous utilities providing sustainable analysis compatible with the needs of different design team members and design stages. The main modules included in this software are the following:

• Model, IT geometry creation and editing

Murray et al. [81] applied IESVE to plan a retrofitting project of a case study building located at Cork University College, for which both modelling and actual interventions were applied. This approach allowed the comparison between simulated and measured data and a good agreement between them was concluded. Ouedraogo et al. [82] used IESVE to investigate the impact of climate change on future trends of electricity demand for air conditioning in public buildings within the period 2010–2080. Their study highlights the fact that the predicted mean temperature using a specific climate-change data scenario will increase by about 2 ◦C by 2050, yielding to a significant increase in air-conditioning energy consumption for case-study buildings in the Burkina Faso built environment. For this specific region, they concluded that shading devices could reduce the cooling load by 40%; thus, they could play an important role in climate-change resilience strategies for buildings. Recently, the tool was used to investigate the energy-saving potential obtained by the application of bio-based wall construction in rural residential buildings in Northeast China [83]. Interestingly, it was found that reductions of 45.82–204.07 kWh/m2/year in heating energy demand and more than 40% in coal consumption are possible through the application of bio-based wall constructions.