**Acknowledgements**

We would like to thank the Ministry of Health of the Republic of Indonesia for facilitating the use of baby growth measuring devices and socializing research on maternal and infant health and stunting. To the Jakarta 1 Health Polytechnic for promoting research on maternal and infant health and stunting.


iv.Coffee husk ash

The use of different replacing of cement materials has become a popular practice in the industry of construction. The chemical composition of coffee husk ash has a significant value of Al2O3 and SiO2, which are major components of cement. It can replace cement about 10% and concrete produced from CHA has high potential as a source of environmental-friendly cementitious material that reduces pollution and provides a sound coffee waste management option.


*3.2. Economic Results*

### 3.2.1. Base Case Analyses

A 33% reduction from the Henriksen et al. meta-analysis was used in the budget impact analysis (OR: 0.67; 0.46–0.98; *p* = 0.04), as established from the results of the literature review [28]. We considered that when the incidence of an outcome of interest was common (>10%), the adjusted OR that was derived from the logistic regression could no longer approximate the risk ratio. We therefore approximated a risk ratio from an adjusted OR ratio and derived an estimate of an SSI reduction that better represented the true RR [43]. The obtained RR (95% CI) was 0.70 (0.49–0.98), and, accordingly, a 30% SSI reduction for TCS introduction was used in the model.

The budget impact analysis estimated an additional annual cost of €600 for a complete conversion of CS to TCS. TCS reduced the number of SSIs by 30%, which led to the avoidance of 3.2 SSIs—over 100 surgeries performed—and associated hospital resources totaling €15,385 (€13,230 for additional LOS and €2155 for additional resource use). The use of TCS resulted in an overall annual net saving of €14,785. The additional €600 associated with using TCS compared with CS were o ffset by the SSI reduction. The model also calculated the minimal SSI reduction required to cancel out the incremental cost of TCS: The additional cost of €600 for advancing wound closure technology was o ffset by an SSI reduction rate of approximately 1.2%, equaling less than a single avoided SSI (0.1 episodes).

### 3.2.2. Scenario and Sensitivity Analyses

When assuming an SSI reduction rate of 2%, the economic model resulted in an overall annual net saving of €426. In this scenario, 0.2 SSI episodes were avoided, thus accounting for a saving of €1026. The incremental expenditure of €600 was o ffset by the SSI reduction risk. Conversely, when the SSI reduction was set at 51%, the annual net saving for the hospital was €25,554 with 5.4 SSI avoided episodes accounting for €26,154 of hospital resources.

The results of the one-way sensitivity analysis, represented as a tornado chart, are presented in Figure 1. The variables with the greatest influence on the annual savings in the model were related to efficacy parameters (SSI risk reduction and baseline SSI rate), with other parameters that were related to cost events found to demonstrate a minor influence on the annual savings. The annual savings remained positive across a broad variation in the ranges for each parameter.

**Figure 1.** Tornado diagram with one-way sensitivity analysis results. Abbreviations: SSI, surgical site infection.

The results of 1000 Monte-Carlo simulations of the annual savings are presented in Figure 2, and the number of avoided SSIs, based on PSA, are presented in Figure 3. The analysis demonstrated that the reduction of SSI episodes due to TCS ranged between 1 and 6 cases in 90% of the simulations. The mean (interquartile range (IQR)) annual savings that were obtained from the PSA was €13,935 (9068–18,665). The whiskers extended the IQR by 1.5 to a maximum of €32,369 and a minimum of −€4987. The analysis demonstrated a 98% probability of TCS being cost saving, based on the assumptions made.

**Figure 2.** Histogram of the number of avoided SSI episodes according the probabilistic sensitivity analysis. Abbreviations: SSI, surgical site infection.


**4. The work of tax practitioners**

Tax laws are increasingly voluminous, and the law provisions are sometimes terribly complicated to be fully understood. It takes a lot of time and effort to meet the tax obligations, and even if they pay much attention enough to avoid inadvertent errors and mistakes, tax liabilities are often subject to uncertainty from varying interpretations of ambiguous tax situations. For a further understanding, the following section discusses the issues of tax law complexity

In practice, many taxpayers are faced with the complexity of tax laws and the uncertainty of enforcement. In most developed countries, tax law is complex, and it requires a very high reading age to be correctly understood [14]. Taxation cost (taxes and compliance cost) is perceived to be much more painful loss for small business taxpayers because they lack sufficient

If tax laws are vague and complicated, it may be difficult to fully comply with the law even with no intention to evade. Owing to the complex nature, ordinary taxpayers cannot cope well with tax requirements. Sakurai and Braithwaite [16] showed that the most important reason that their survey respondents gave for using tax service was that the desire to avoid the risk of potential tax penalties resulting from inaccurate tax returns. The professional tax knowledge that prevents the taxpayer from unintentional overpayment as well as underpayment can be purchased from the tax practitioners. Thus, an aspect of tax practitioner compliance can be better construed in connection with professional competence that ensures correct tax reporting. McKerchar [17] maintains that tax complexity is a double edge sword for practitioners: on one side, it induces taxpayers into the arms of practitioners facilitating the market for tax service; but sometimes, it is too much a burden even for them to juggle. Although compliance duties can be addressed more correctly by the tax practitioner, the assistance of the tax practitioner cannot eliminate the risk of inadvertent noncompliance due to the complexity inherent in

Carnes and Cuccia [18] argue that complexity is a source of unintentional noncompliance, and it may represent opportunities for intentional noncompliance as well. More often, tax practitioners can only reduce the uncertainty by assessing the likelihood a tax treatment will be sustained on its merits [19]. That said, inadvertent noncompliance is in part attributable to tax law ambiguity. A tax situation is ambiguous if its proper tax treatment is not *ex-ante* deterministic. Aggressive tax treatment involves a reasonable probability that the reporting position will not be upheld in a tax audit [20]. Aggressive tax practitioners are more likely to

Studies on tax practitioner behavior attempt to discover the conditions in which tax advisors would recommend more aggressive reporting position [21]. A number of studies have been conducted investigating factors that impact tax practitioners' willingness to accept aggressive reporting positions; among them are attitude toward risk [22], the threat of penalties [23], and client's risk preference [24]. In particular, Prospect theory [25] may also serve as a theoretical

interpret the ambiguous tax situation to the benefit of their clients.

and ambiguity.

234 Taxes and Taxation Trends

the law.

**3. Tax law complexity and ambiguity**

resources to manage their business [15].

There are a variety of motives in hiring tax practitioners. As it is, the role of tax practitioners in tax compliance process can be best understood considering the multifaceted aspects of tax service. Frecknall-Hughes and Moizer [29] argue that the work of tax practitioners in its broadest way can be divided into two kinds: tax compliance and tax planning/avoidance advice; the formal relates to resolve uncertainty in which tax position can be correctly settled, and the latter is associated with ambiguous tax situations in which legitimate tax position is not deterministic. Stephenson [30] discovered four separate constructs underlying the demands for tax practice: legal compliance, time savings, money savings, and protection from the tax authority.

Many taxpayers tend to claim accuracy as their main objective in tax preparation [31]. In that case, the quality of tax service is to ensure the tax returns do not contain inadvertent errors or omissions. It is somewhat evident that taxpayers hire tax practitioners to save time and effort required to achieve compliance. They will delegate tax return preparation to the practitioner, if the opportunity cost of self-reporting exceeds the service fee. Tax practitioners are also expected by their clients to reduce the chances of audit and penalty, thereby lowering monetary and psychic costs associated with audits that would otherwise have occurred [32]. Tax practitioners may provide professional assurance of compliance by verifying and assessing acceptable tax positions in the SAS [33].

Every tax legislation, however, contains "gray" areas that produce ambiguous tax situations. Tax practitioners cannot get rid of entire uncertainty, but they can only gauge the likelihood the position not being upheld by the tax court. The tax position is subject to some uncertainty and hence may step into a process of negotiation with the tax authorities [29]. Indeed, Frecknall-Hughes and Kirchler [34] came up with negotiation theory as a conceptual framework for understanding the nature of tax practice. They argue that the tax advisor/preparer and the tax inspector (who are the employee of revenue authority) are negotiators who act respectively on behalf of a client and the tax authority. While laypersons may see the task of trials and tax audits as revealing the truth about the matter, many practitioners approach their job as being able to negotiate the best settlement for their clients [35].

that if a tax practitioner provides aggressive tax advice, the taxpayer is likely to take the aggressive tax position that might not be upheld in a tax audit. On the contrary, Hite and McGill [47] argue that taxpayers tended to disagree with aggressive advice and to agree instead with conservative advice. Or, there is also evidence that conservative taxpayers defer to the opinion of aggressive tax practitioners [48]. Not surprisingly, there are taxpayers who will still accept

Tax Practitioner Compliance

237

http://dx.doi.org/10.5772/intechopen.74216

For the tax practitioner, clients' risk preferences could influence the willingness of practitioners to recommend aggressive positions [49]. Cloyd [50], Cuccia et al. [51], and Schisler [24] indicate tax practitioners' tendency to recommend more aggressive positions when taxpayers are more aggressive (risk seeking). Notably, Duncan et al. [52] found the opposite evidence showing the more risk-averse the taxpayer, the more aggressive the tax practitioner, and the more aggressive the taxpayer, the more conservative tax position recommended by the practitioner. Furthermore, Bobek et al. [53] examined how the role of client advocacy influenced tax professionals' decision processes and outcomes and provided empirical results revealing that client characteristics influence tax professionals' advocacy attitudes. These findings suggest that taxpayers and tax practitioners' decisions are interdependent, and studies on their interaction dynamics could be a promising approach to find new insights into tax compliance. Wurth and Braithwaite [54] underline that practitioners are responsive to influences from many sources—clients, tax authorities, professional associations, governments, international bodies, and the organizations and cultures. For example, Doyle et al. [55] investigated the moral reasoning of tax practitioners in social contexts and in tax contexts, and they found tax practitioners' significantly lower level moral reasoning than nonpractitioners in tax contexts. The study implies that client advocacy may deter tax practitioners' moral reasoning. Reckers et al. [23] pointed out that less important taxpayers are more likely to receive more conservative advice from the tax practitioners. On the contrary, Bandy et al. [56] asserted that economic importance of the taxpayer had little effect on tax practitioners' willingness to be aggressive in terms of providing advice or signing aggressive tax return. Spilker et al. [57] provide evidence that tax practitioners interpret ambiguity in the tax law differently in planning than in compliance stage because they are more vulnerable to problematic tax advice

In connection with taxpayer compliance, Practitioner-Client role model developed by Tan [58] recognizes two parties' expectations, and behavioral dynamics can emphasize that how taxpayers and tax practitioners interact with each others are likely to affect each other's tax decisions. Similarly, The Wheel of Social Alignments put forth by Braithwaite and Wenzel [59] synthesizes the drivers of tax compliance regarding tax practitioners as alternative authorities to tax officials. Some taxpayers exhibit their preference of conservative advice over aggressive one. However, Sakurai and Braithwaite [60] show that some taxpayers prefer "no risk no fuss" type. As with their diverse motivational postures [40], it is natural of taxpayers to exhibit diversity in their preference over tax advice as well as tax position. It is therefore in communicating with their clients, tax practitioners should educate, persuade, and encourage taxpayers to acknowledge the responsibility for their decisions in order to reduce expectation gap [61]. In many cases, ineffective communication is attributable to the failure to achieve compliance procedures

whatever types of advice their practitioners recommend.

that might result in litigations and reputational loss.

Some tax practitioners promote unacceptable tax minimization arrangements, assisting their clients in devising strategies to exploit legal ambiguities [36]. They are inclined to view testing the outer limits of the tax law as a natural and acceptable feature [37]. In recent decades, their role has become more complicated and sophisticated with the special tax knowledge required to facilitate tax avoidance [38]. For example, Sikka and Hampton [39] criticize that accountancy firms have sold tax avoidance schemes to corporations and wealthy individuals, which they refer to as tax solutions or tax strategies.

Nevertheless, it is important to distinguish legally permissible tax planning from potentially unacceptable tax scheme. Adapting motivational postures theory [40], Kang [41] coined two terms indicating differentiated features of tax avoidance: deferential avoidance and defiant avoidance, while deferential avoiders stand firm within the boundaries of the law, defiant avoiders try to push the boundaries of the law's intent by self-serving in terms of law interpretation.

The role of tax practitioners has been viewed as representative of both taxpayers and the government [42]. One might argue that they have to act as advocates for their clients and to serve as intermediaries in the tax system. Tax practitioners should be concerned not only with their client's interest but also with general publics in conducting their practices. Indeed, OECD [43] published a report highlighting the importance of trilateral relationships among tax authorities, taxpayers, and tax intermediaries in promoting taxpayer compliance. In a nutshell, tax practitioners have a legitimate and efficient function as intermediaries or "knowledge brokers" between taxpayers and revenue authorities [44]. They can provide a useful line of communication between tax inspectors and taxpayers. Furthermore, tax professionals can provide a check-and-balance function that prevents tax authorities' possible extortion or tax inspectors' harassment on the part of taxpayers, thereby safeguarding the equity of a tax system [7].

There are a variety of expectations for tax practitioner work, and sometimes an "expectation gap" arises from the misperception of each other's expectation. Expectations gap refers to the difference between client expectations and the professional's perceptions of those expectations and vice versa [20]. Christensen [45] argues that tax preparers' perceptions of what clients expect from tax service differ significantly from clients' expectations. Tax preparers may rationalize it is their clients who demand aggressive tax reporting. Schisler [24] maintains that many taxpayers insist on aggressive tax advice. In contrast, according to Tan [46], taxpayers favor conservative tax advice if the taxpayers' main objective is filing an accurate tax return. This issue is worthwhile to be explored in more depth in the following section.


**1. Introduction**

GR 290 (M 33 V0532 = Romano's Star)1 is a variable star in M 33 galaxy discovered by Giuliano Romano [1] who originally constructed its light curve and classified it as a Hubble-Sandage variable based on its photometric properties. Later, in 1984, Peter Conti [2] introduced a new class of objects which assimilated Hubble-Sandage variables—luminous blue variables (LBV), and thus GR 290 became an LBV candidate [3,4]. This classification has later been supported by the spectroscopic [5] and photometric [6] studies, as well as by its large bolometric luminosity [7]. However, some arguments suggest that the objects is rather on a post-LBV stage already [8–10].

1 The object has coordinates *α* = 01 : 35 : 09.701, *δ* = +30 : 41 : 57.17 at J2000 epoch.

Romano's star displays both strong spectral and photometric variability, with several significant (about 1.5–2 mag) increases of brightness detected during its long monitoring (Polcaro et al. [10] and references therein). Such variability is typical for LBV stars, while in the Hertzsprung-Russell (H-R) GR 290 lies in Wolf-Rayet (WR) stars region, beyond LBV instability strip [10]. GR 290 is presently in a short, and thus very rare, transition phase between the LBV evolutionary phase and the nitrogen rich WR stellar class (WN). It is an extremely important target for studies of massive star evolution, especially the evolutionary link between LBVs, WR stars and supernovae (SNe).

In this paper we summarise the main results achieved in the study of Romano's star. We combine new studies of GR 290's vicinity (Section 2) with its updated century-long photometric light curve (Section 3). Then, based on spectral data, numerical simulations of its stellar atmosphere (Section 4) and the nebula surrounding it (Section 5), we discuss the current evolutionary stage of the star in Section 6.

### **2. Stellar Vicinity of Romano's Star**

GR 290 is located in the outer spiral arm of the M 33 galaxy, and lies to the east of the OB 88 and OB 89 associations [11–13], located at 0.5 and 0.125 kpc projected distances2, respectively. The most detailed information about photometry of stars in this area may be found in Massey et al. [15]. Figure 1 shows the identification chart of the object and its vicinity, with red symbols corresponding to the stars which were spectrally classified by Massey et al. [16]. Coordinates and spectral classes of the stars are listed in Table 1.

Massey and Johnson [17] found a couple of carbon-rich Wolf-Rayet (WC) stars in these associations, J013458.89+304129.0 (WC4) in OB 88 and J013505.37+304114.9 (WC4-5) in OB 89. Moreover, the OB 88 association contains the star J013500.30+304150.9 classified as an LBV candidate by Massey et al. [18], and later reclassified by Humphreys et al. [9] as a FeII emission-line star. The presence of evolved massive stars in the associations indicates that their age is close to that of GR 290 and that they might have a common origin. Therefore, it is quite reasonable to suppose that GR 290 might have been originally ejected from the OB 89 association. Then, assuming a median escape velocity for runaway stars of 40–200 km/s [19], this ejection would have to have occurred 3.0–0.6 Myr ago, which is consistent with the evolutionary age of GR 290 and with the age of the OB 89 association.

2 The adopted distance to M 33 is 847 ± 61 kpc (distance module 24.64 ± 0.15) from Galleti et al. [14].

**Table 1.** Stars in the vicinity of GR 290 spectrally classified by Massey et al. [16] (and references therein). Names and coordinates are given according to Massey et al. [15]. The three stars also included in Table 2 are marked by boldface.

*a* later classified as Of/late-WN by Humphreys et al. [20]; *b* later classified as a FeII emission-line star by Humphreys et al. [9].

**Figure 1.** Identification chart of GR 290 vicinity and OB 88 and OB 89 associations. The colour picture is a combination of three direct images, with blue corresponding to B filter, green—to V and red—to R filter, all obtained with 2.5 m telescope of the Caucasian Mountain Observatory (CMO) of the Sternberg Astronomical Institute of Moscow State University. Green circles mark the stars studied in this work and red ones studied by Massey et al. [15,16]. Red squares are stars considered to be foreground objects by Massey et al. [15].

The field around GR 290 is not yet sufficiently explored as it consists mostly of faint (*V* > 18 mag) stars that require large telescopes for acquiring the spectra. Fortunately, some of the surrounding stars happened to lay on the slit during the long-slit observations of the object, thus that analysis of such data may provide additional information on the stellar contents and interstellar extinction in the vicinity of Romano's star. Therefore, we retrieved from General observational archive of Special Astrophysical observatory of Russian Academy of Sciences (SAO RAS)3 all long-slit spectra of GR 290 obtained on Russian 6-m telescope with the Spectral Camera with Optical Reducer for Photometric and Interferometric Observations (SCORPIO) [21] during the years 2005–2016. We also utilised the spectra obtained with the OSIRIS spectrograph on the *Gran Telescopio Canarias (GTC)* and analysed by Maryeva et al. [22] and Maryeva et al. [23]. We reduced these spectra in a uniform way using the ScoRe package4 initially created for the SCORPIO data reduction, and extracted the spectra of all stars crossed by the slit. To perform the spectral classification of these stars, we used an automatic code based on the *χ*2 fitting with spectral standards from STELIB5 (see Le Borgne et al. [24]) in the same way as used by Maryeva et al. [25]. The stars with spectra extracted and analysed in this way are

3 General observational archive of Special Astrophysical observatory is available at https://www.sao.ru/oasis/cgi-bin/fetch? lang=en.

4 ScoRE package available at http://www.sao.ru/hq/ssl/maryeva/score.htm.

5 STELIB is availabte at http://webast.ast.obs-mip.fr/stelib.

marked with green circles in Figure 1, and their estimated spectral classes, measured positions and photometric magnitudes are listed in Table 2. The resulting spectra of the stars in flux units are shown in Figures A1–A5.

**Table 2.** The sample of stars in the field around GR 290 studied in this work. N corresponds to the labels in Figure 1. *V* and (*B* − *V*) taken from Massey et al. [15].

*a*,*e* Stars classified as RSG by Massey et al. [16]; *b* star classified as O6III(f)+Neb by Massey et al. [16]; *c*,*d* stars classified as foreground objects by Massey et al. [15].

As we can see in Figure 1, our sample of stars partially intersect with the ones studied by Massey et al. [15,16]. We were able to refine the estimates of spectral classes for J013459.81+304156.9 and J013507.43+304132.6, classified earlier as just red supergiants (RSG) [16], as well as for J013506.17+304129.1 and J013507.18+304156.4 as foreground objects according to Massey *et al.* [15]. Our sample contains three more RSGs, which were not previously reported, and four hot stars, with only one (J013505.74+304101.9 with O6III(f)+Neb spectral class) known before [16]. Among three others, the spectrum of J013505.76+304102.21 displays the He I emission and strong nebular lines. The second one, J013514.1+304423.21, has a spectral slope corresponding to high temperature, and shows H and He absorption lines, while the last, J013501.87+304157.3, was preliminary classified as B5–B7 supergiant.

Knowing the spectral classes of these stars, and therefore their intrinsic colour indices, allows us to estimate the interstellar extinction around GR 290. Its value is comparable to the galactic foreground extinction value of *E*(*B*−*V*) = 0.052 (according to the NED extinction calculator [26]). We did not register any star with higher reddening in the vicinity of GR 290.