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We have also considered a quadratic model to the new data set. However, and judged by eye from Fig.~\ref{Linfit_NEW_Res}, there is no obvious upward or downward parabolic trend in the data. Nevertheless we added a quadratic term and generated 10 million initial guesses to find a best-fit model. The resulting reduced $\chi^2$ value increased to 165.7 with 54-3 degrees of freedom. We therefore, decide to not consider a quadratic ephemeris in our further analysis.  \section{New dataset with scaled errors: Linear ephemeris + 1-LTT model using MPFIT}  Using scaled uncertainties we have considered a linear + 1-LTT model. We have again used MPFIT. The model is taken from Irwin (19??) and described in Hinse et al. (2012). We considered $10^7$ initial guesses. The initial guess for the reference epoch and binary period were taken from the best-fit obtained from a linear ephemeris model. Inital guesses for the semi-amplitude of the light-time orbit were taken from an estimate of the amplitude as shown in Fig. 2. Initial guesses for the eccentricity covered the interval [0,1]. Initial guess for the argument of pericentre covered the interval [0,360] degrees. Initial guess for the orbital period was also estimated from Fig.~\ref{Linfit_NEW_Res}. Initial guess for the time of pericentre passage were obtained from T0 and the orbital period of the light-time orbit. Initial guesses were drawn at random. The methodology follows the same techniques as described in Hinse et al. (2012). Best-fit parameters were obtained from the best-fit solution covariance matrix as returned by MPFIT. Parameters errors should be considered as formal [OFF-THE-RECORD: FINAL ERRORS WILL USE BOOTSTRAP TECHNIQUE]. The best-fit had a $\chi^2=717.6$ with 47 degrees of freedom resulting in a reduced $\chi^2_{\nu}=15.3$. The corresponding RMS scatter of data points around the best-fit is 20.0 seconds. The best-fit parameters are listed in Table \ref{XXX_BestFitParamsLinPlus1LTT_XXX} \ref{BestFitParamsLinPlus1LTT_New_AllData}  [OFF-THE-RECORD: DO WE NEED TO SHOW THEM, WE WILL SEE LATER...] and shown in Fig.~\ref{BestFitModel_LinPlus1LTT_New_AllData}. Recalling the average timing error to be 6 seconds, that means that the RMS residuals are on a $3.3\sigma$ level indicating a significant signal of some origin. However, upon close inspection of Fig.~\ref{BestFitModel_LinPlus1LTT_New_AllData} the origin of the large scatter is mainly due to data obtained by \cite{Beuermann1988}, \cite{Ferrario_1989} and \cite{Berriman_1988}.$E=mc^2$.  \begin{table}   \begin{tabular}{ c c } 
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RMS (seconds) & 15.7 \\   \end{tabular}   \caption{Best-fit parameters for a linear + 1-LTT model (full data set: 42 data points)}   \label{BestFitParamsLinPlus1LTT} \label{BestFitParamsLinPlus1LTT_New_AllData}  \end{table}  \section{Figures:}