text:
\section{Introduction}

Active galactic nuclei (AGNs) are the centres of a special class of galaxies that consist of actively accreting central supermassive black hole (SBH). High-speed collimated outflows are present in a small fraction of AGNs. AGNs show a dichotomy in their radio power - these are referred to as radio-loud (RL) and radio-quiet (RQ) AGNs \citep{Strittmatter1980, Miller1993}.  Historically, AGNs with higher radio-to-optical flux $R\ge10$ where  $R \equiv S_{5~GHz} / S_{B-band}$ are termed as RL AGNs and RQ otherwise \citep{Kellermann1989}. This distinction however, is suggested to be valid only for broad-lined, unobscured AGNs since AGN luminosity estimates may be affected by dust, and therefore  \cite{Padovani2017} suggested a nomenclature based on a fundamental physical difference, namely the presence or absence of relativistic jets.

Based on the radio morphology and power, extended RL AGNs are classified into FR~$\mathtt{I}$ and FR~$\mathtt{II}$ \citep{Fanaroff1974}. FR~$\mathtt{II}$ sources have radio structures consisting of a core, collimated jets, lobes, and hotspots located at the edges of these lobes. FR~$\mathtt{I}$s show extended plume-like structures and tails with no distinct collimated jets or terminal hotspots \cite[{more detailed differences in}][]{Bridle_Perley1984}.  Based on the optical spectra RL AGNs are classified into Type 1 (have broad and narrow emission lines) and Type 2 (have only narrow emission lines).  Type 2 AGNs comprise narrow-line radio galaxies (NLRG); Type 1 AGNs {comprise} broad-line radio galaxies (BLRG) at low luminosity and radio-loud quasars at high luminosity.  The latter are further divided into flat spectrum radio-loud quasars (FSRQ) ($\alpha>0.5$) and steep spectrum radio-loud quasars (SSRQ) ($\alpha<0.5$) (see \cite{Urry1995, Tadhunter2008, Netzer2015, Tadhunter2016} for a review).  SSRQs tend to have lobe-dominated radio structure while FSRQs often have core-dominated structure. Although we see different types of AGN, it is hypothesised that these are intrinsically similar objects but appear different depending on their orientation with respect to the line of sight.  This has come to be known as orientation-based AGN Unification Scheme \citep{Antonucci1993, Urry1995}.

There is compelling evidence in the literature that is consistent with the predictions of the unification scheme.  Some of the evidences include detection of broad emission lines in the polarized intensity spectra of Type 2 AGNs indicating a hidden broad line region obscured from direct view \citep{Antonucci1984, Antonucci_Miller1985, Tran1995, Young1996, Ogle1997, Cohen1999}, detection of ionisation cones of the narrow line region in optical images of Type 2 AGNs \citep{Pogge1988, Wilson1993, Jackson1998}, detection of excess near-IR emission and polarized light perpendicular to the jet axis \citep{Antonucci1990}, apparently superluminal velocities in VLBI observations of compact radio sources \citep{Cohen1977, Kellermann2007}, detection of extended halos around compact sources representing radio lobes viewed face-on \citep{Browne1982, Antonucci_Ulvestad1985}, {and} observed anisotropy in the radio structure {\citep{Laing1983, Barthel1989, Smith1990, Mullin2008}. According to unification, FSRQ form the beamed counterparts of FR~{\tt II} radio galaxies, and SSRQ (and BLRG) are oriented at angles that are in between NLRG and FSRQ.}

This paper is the first in a series of papers in our study of FR~{\tt II} radio-loud AGNs.  Here we present the results from our VLA study of 11 SSRQ that show classical double lobes at GHz frequencies. We have analysed the properties of these quasars along with a sample of 13 FR~$\mathtt{II}$ radio galaxies from \citet{Kharb2008}. Interestingly, several of these quasars and radio galaxies reveal {extended}, winged or asymmetric radio morphologies in the TIFR GMRT Sky Survey (TGSS) at 150~MHz.  {This is in contrast to} the symmetric structures detected with the VLA at GHz frequencies.

Throughout this paper, we assume a cosmology with H$_0$ = 73~km~s$^{-1}$~Mpc$^{-1}$, $\Omega_{mat}$ = 0.27, $\Omega_{vac}$ =  0.73. Spectral index, $\alpha$, is defined such that flux density at frequency $\nu$ is $S_\nu\propto\nu^\alpha$.

\section{The Sample}
\label{sec:data}
The 11 quasars in this study were selected to augment the sample of 55 radio sources with spin determinations described by \citet{Daly2011}.  The parent population is powerful FR~{\tt II} sources that are identified as quasars, where the original published optical classification was used to identify them as quasars, and this identification was confirmed by the follow-up observations of \cite{Mclure2006}; these 11 sources were identified based on the following criterion: (i) the quasar has a black hole mass determination (from \cite{Mclure2006}); (ii) at least one side of the source does not exhibit a radio jet, so that a spectral ageing analysis can be carried out on the non-jetted side; (iii) the non-jetted lobe(s) have angular sizes large enough to allow the spectra of the lobe to be measured at several locations.

\subsection{Observations and Data Reduction}
These 11 quasars were observed with the VLA at 1.4 GHz (L-band) and 5~GHz (C-band) with A and CnB-array configurations, respectively (Project ID: 10C-178) for a total of 22 hours. 5~GHz observations were not scheduled for 3C~336\footnote{One of the observations (for 3C432) had technical issues and was therefore re-observed. However, due to confusion in the sequencing of observations, we missed obtaining data for 3C336. This was realised {late} and could not be rectified}.  Hence, we used archival VLA data\footnote{Project ID: AB0454; C-band B-array configuration} for this source.  Also, due to the noisy 1.4 GHz data on 3C~351, we chose archival data\footnote{Project ID: AD0429; L-band A-array configuration} for this source as well.  For 3C~208 at 5~GHz, since there were issues with amplitude calibration using 3C~48,  the source flux was rescaled using the \textsc{aips} task {\tt RESCALE} and the core flux density from \cite{Yuan2012}.

The data in the SDMset format were pre-calibrated using the \textsc{casa} calibration pipeline\footnote{\textsc{casa} release 4.5.3 with pipeline release 4.6.0}. The final imaging and self-calibration were done in the Astronomical Image Processing System (\textsc{aips}), by iteratively running the tasks {\tt IMAGR} and {\tt CALIB}.  The 1.4$-$5 GHz spectral index images were made using task {\tt COMB} after first creating L and C-band images with identical circular beams (at the poorer L-band resolution), which were then positionally aligned using the {\tt AIPS} task {\tt OGEOM}. We used 3$\sigma$ r.m.s. noise of the respective L and C-band images as the clipping level input to {\tt COMB}. Final flux density and spectral index values were estimated using the {\tt AIPS} verbs {\tt TVWIN} and {\tt IMSTAT}, as well as the Gaussian-fitting task {\tt JMFIT}. All extents were measured in {\tt AIPS} using {\tt IMDIST}. The basic properties and derived parameters are listed in Tables ~\ref{tab:quasar_basic_prop} through ~\ref{tab:quasar_hotspots}.

\subsection{Data from the Literature}
In order to put the results from the 11 quasars in perspective, we have analysed their results along with the sample of {13} FR~$\mathtt{II}$ {narrow-line} radio galaxies that were studied in \citet{Kharb2008}; the radio galaxy study had been carried out at similar frequencies and resolutions {as} the 11 quasars presented in this paper. Some properties of the radio galaxies have been re-estimated (like $R_c$, 1.4 GHz flux density from NVSS) to compare them with the current quasar sample, and are tabulated in Table~\ref{tab:radiogalaxy_prop}. We note that the combined quasar and radio galaxy sample studied here is statistically small and eclectic. Some statistical tests, therefore, suffer from small number statistics.

\subsection{Physical Parameters Estimation Method}
\label{sec:param}
The spectral index is estimated from the spectral index images.  The spectral index of the core is obtained by placing a box around the core using {\tt TVWIN} and {estimating} the mean using {\tt IMSTAT}. The hotspot spectral index is measured at the image position corresponding to the peak intensity in {1.4 and} 5 GHz image, where the peak intensity is determined using {\tt TVMAXFIT}.

The arm-length ratio is defined as the ratio of the longer core-hotspot distance to the shorter core-hotspot distance. The distance is measured from the peak flux position at the core to the peak flux position at the hotspot. The peak flux density was estimated using the procedure {\tt TVMAXFIT}. The 5 GHz radio maps were used in the determination of the arm-length ratio.

The axial ratio is defined as the ratio of the length to the width of the lobe \citep{Leahy1989}. The core-hotspot distance is taken as the length of the lobe.  Although lobe emission is not observed to be extending all the way to the core in the 1.4 GHz emission, lower frequency images (610 MHz GMRT observations, Vaddi et al. 2018  in preparation) show extended emission and thus it is safe to assume the lobe length to be the core-hotspot distance. The FWHM of the lobe is measured using the Gaussian-fitting task {\tt SLFIT} to a one-dimensional slice across the lobe.  The slice is chosen by-eye {to be} perpendicular to and at half the distance between the core and hotspot.
{To account for the finite resolution of the observing beam, we subtract the beam in quadrature from the measured Gaussian fit: $\Theta_{decon}^2 = \Theta_G^2 - \Theta_b^2$ where $\Theta_G$ is the measured FWHM from the Gaussian fit, and $\Theta_b$ is the average FWHM of the observing beam ($\sqrt(FWHM_{major~axis} * FWHM_{minor~axis})$), and $\Theta_{decon}$ is the FWHM of the Gaussian fit deconvolved with the beam.  The lobe width is then taken as 2/$\sqrt 3$ of the deconvolved Gaussian fit \citep{Leahy1989}. Correction for the radio galaxies is negligible since its lobe widths are large compared to the beam size \citep{Daly2010}.}

{The largest linear size (LLS) is defined as the distance between two hotspots (definition consistent with \cite{Kharb2008}).  The distance is estimated by first obtaining the position of the hotspot peak intensity with {\tt TVMAXFIT} and then measuring the distance between the hotspot peak intensity using {\tt IMDIST}.  The 5~GHz maps were used in the estimates.}

{The misalignment angle is the difference between the position angles of the core-hotspot segments on either side of the core. When there is more than one hotspot on one side of the core, the other side is used to define the core-hotspot line segment and misalignment angles to each of the two hotspots on the opposite side are obtained. Figure~\ref{fig:example_fig} in the appendix identifies different components that were estimated using AIPS task {\tt TVDIST}.}

\subsection{Errors}
Uncertainties in the flux measurements were estimated by combining all errors in quadrature. {The errors considered are the calibration errors, rms, and random errors ($\sigma = \sqrt{\sigma^2_{cal} + \sigma^2_{rms} + \sigma^2_{random}}$). We assumed that the calibration errors are 10 per cent of the measured flux densities.  RMS is the error reported in the tasks ({\tt JMFIT}, {\tt IMSTAT}) used for flux measurement.  Random error of 5 per cent accounts for the different values we get when taking repeated measurements; {an average of five} measurements were obtained for a few sources and the per cent standard deviation from the average values was noted. This gives the uncertainties of the order of few mJy~beam$^{-1}$.

The error in the spectral index is estimated by adding in quadrature the noise map produced in the {\tt COMB} task and a 5 per cent random error for $\alpha_{HS}$, 15 per cent random error for the $\alpha_{core}$, and a 10 per cent random error for the $\alpha_{lobe}$.

The uncertainty on the measurement of the lobe width is obtained by adding in quadrature the 5 per cent random error on the measured width and the error in the Gaussian fit to the slice. {The uncertainty of the deconvolved lobe width is obtained using the expression { $\delta\Theta_{decon}^2 = (\Theta_{decon} /\Theta_{G})^2 \delta\Theta_G^2 + (\Theta_{decon}/\Theta_{b})^2 \delta\Theta_b^2$} where $\delta\Theta_G$ is the uncertainty of the lobe width and $\delta\Theta_b$ is the uncertainty of the observing beam.  Lobes whose widths are similar to the beam have larger uncertainty.

The uncertainties on angular size, arm-length ratios are estimated by repeated measurements (five times) on few sources and taking the standard deviation of these measurements.  The ratios are calculated using the usual error propagation. These uncertainties are between 5$-$20 per cent.

The LLS is estimated from peak hotspot-to-hotspot distance which need not be the true LLS and true LLS is usually larger than the hotspot-hotspot distance.  To quote the uncertainty in the LLS due to this, we estimate an average of several lobe edge-to-edge distance measurement obtained using {\tt TVDIST} and the deviation of this estimate with the hotspot-hotspot distance is taken as the uncertainty. The uncertainty of the misalignment angle is estimated based on the uncertainties of the hotspot and core positions.
}

\begin{landscape}
	\begin{table}
		\caption{Basic properties of the radio-loud quasar sample}
		\label{tab:quasar_basic_prop}
		\begin{tabular}{lcccccccccccc}
			\hline
			Name	&	RA	&	DEC	&	z	&	log~$M_{BH}$	&	{S$^{1.4}_{total}$}	&	{S$^{5}_{total}$} 	&	{S$^{150}_{total}$}	&	{LLS}	&	{$\log R_c$}	&	{Arm-length}	&	{Misalignment} 	&	{$Q_{jet}$}\\
				&	J2000	&	J2000	&	&	M$_{\odot}$	&	{(Jy)}	&	{(Jy)}	&	{(Jy)}	&	{(kpc)}	&	{}	&	{Ratio}	&	{Angle (deg)}	&	{($10^{45}$ erg s$^{-1}$)}\\
				(1)&(2)&(3)&(4)&(5)&(6)&(7)&(8)&(9)&(10)&(11)&(12)&(13)\\
			\hline
			3C14 	&	00:36:06.5	&	+18:37:59	&	1.469	&	9.4 	& 	1.97$\pm$0.03	&	0.68$\pm$0.01	&	13.51$\pm$2.03	&	201.9	&	-2.65$\pm$0.05	&	1.59	&	9.3, 24.8	&	9.71$\pm$0.33\\
			3C47	&	01:36:24.4	&	+20:57:27	&	0.425	&	9.2	&	3.59$\pm$0.01	&	1.01$\pm$0.01	&	36.33$\pm$4.46	&	374.1	&	-1.86$\pm$0.05	&	1.23	&	6.4	&	3.63$\pm$0.05\\
			3C109	&	04:13:40.4	&	+11:12:14	&	0.306	&	8.3	&	3.41$\pm$0.02	&	1.26$\pm$0.01	&	20.72$\pm$2.73	&	407.6	&	-1.18$\pm$0.05	&	1.04	&	13.7	&	1.30$\pm$0.04\\
			3C204	&	08:37:44.9	&	+65:13:35	&	1.112	&	9.5	&	1.20$\pm$0.02	&	0.35$\pm$0.01	&	13.88$\pm$1.86	&	282.8	&	-1.68$\pm$0.05	&	1.40	&	3.3, 3.4	&	5.29$\pm$0.24\\
			3C205	&	08:39:06.4	&	+57:54:17	&	1.534	&	9.6	&	2.29$\pm$0.08	&	0.55$\pm$0.02	&	21.53$\pm$3.20	&	130.5	&	-2.33$\pm$0.05	&	1.17	&	0, 7.5	&	15.3$\pm$0.30\\
			3C208	&	08:53:08.8	&	+13:52:55	&	1.11	&	9.4	&	2.39$\pm$0.1	&	0.48$\pm$0.02	&	23.08$\pm$3.56	&	88.60	&	-1.97$\pm$0.05	&	1.28	&	0	&	10.60$\pm$0.23\\
			3C249.1	&	11:04:13.7	&	+76:58:58	&	0.312	&	9.3	&	2.12$\pm$0.01	&	0.68$\pm$0.01	&	18.26$\pm$2.60	&	199.2$^{\dagger}$	&	-1.53$\pm$0.05	&	2.04	&	7.6	&	1.15$\pm$0.05\\
			3C263	&	11:39:57.0	&	+65:47:49	&	0.646	&	9.1	&	2.96$\pm$0.05	&	1.03$\pm$0.02	&	20.37$\pm$3.07	&	320.5	&	-1.53$\pm$0.05	&	1.72	&	1.6	&	4.42$\pm$0.12\\
			3C336	&	16:24:39.1	&	+23:45:12	&	0.927	&	9.2	&	2.64$\pm$0.06	&	0.38$\pm$0.01	&	14.47$\pm$2.23	&	172.0	&	-2.61$\pm$0.05	&	2.00	&	13.6	&	5.83$\pm$0.21\\
			3C351	&	17:04:41.4	&	+60:44:31	&	0.372	&	9.5	&	2.65$\pm$0.03	&	1.08$\pm$0.01	&	16.94$\pm$2.36	&	316.8	&	-2.25$\pm$0.05	&	2.23	&	5.8, 17	&	1.50$\pm$0.06\\
			3C432	&	21:22:46.2	&	+17:04:38	&	1.785	&	10.1	&	1.62$\pm$0.07	&	0.34$\pm$0.01	&	14.64$\pm$2.30	&	109.8	&	-2.87$\pm$0.05	&	1.33	&	11.9	&	11.70$\pm$0.38\\
		\hline
		\multicolumn{13}{p{1.2\textwidth}}{Col.(1-3) give the source name and position. Col(4)- Redshift from NED.  Col.(5)-Logarithm of black hole mass from \citet{Mclure2006}. Col(6-8)- Total flux density at 1.4 GHz, 5 GHz, and 150 MHz respectively in Jy Beam$^{-1}$.  Col(9)- Largest linear size which is the distance between the two hotspots, measured using {\tt IMDIST} {on 5~GHz images}. Col(10)- Logarithm of the radio core prominence.  Col(11)- Arm-length ratio which is the distance between the core to the hotspot, measured using {\tt TVDIST} {on 5~GHz images}.  Col(12)- Misalignment angle in degree.  {Where multiple hotspots are present, angle to each of the hotspots is mentioned separated by a comma. An angle of zero indicates that the hotspots and core all lie on a single line. 5~GHz images are used to get the angles.  The uncertainty on the misalignment angles is about a tenth of a degree.} Col(13)- Jet kinetic power.\newline {$^{\dagger}$ Since this source has only one hotspot, the LLS for this source is measured using {\tt TVDIST} and choosing the end points by eye.}}
		\end{tabular}
	\end{table}
\end{landscape}

	\begin{table}
		\caption{Properties of hotspots}
		\label{tab:quasar_hotspots}
		\begin{tabular}{lccccc}
			\hline
			{Name}	& {Side} &	{S$^{5}_{peak}$}	&	{$\alpha^{5}_{1.4}$}	&	{$\Theta$}\\
			{}	&	{}	&	{(mJy beam$^{-1}$)}	&	{}	&{(arcsec)}\\
			(1)&(2)&(3)&(4)&(5)\\
			\hline
			3C14 	&	N1	&	81.90	&	-0.98$\pm$0.16	&	9.440\\
			&	N2	&	59.00	&	-1.15$\pm$0.18	&	6.960\\
			&	S	&	111.7	&	-0.86$\pm$0.14	&	14.97\\
			3C47	&	N	&	20.6	&	-0.77$\pm$0.15	&	31.19\\
			&	S	&	163.0	&	-0.38$\pm$0.16	&	38.2\\
			3C109	&	N	&	31.9	&	-0.45$\pm$0.11	&	46.09\\
			&	S	&	211.0	&	-0.66$\pm$0.12	&	48.12\\
			3C204	&	E	&	63.90	&	-0.72$\pm$0.12	&	18.13\\
			&	W1	&	85.60	&	-0.62$\pm$0.10	&	13.01\\
			&	W2	&	24.10	&	-1.04$\pm$0.17	&	17.12\\
			3C205	&	N	&	104.8	&	-1.22$\pm$0.19	&	7.230\\
			&	S1	&	211.3	&	-0.94$\pm$0.15	&	8.480\\
			&	S2	&	207.0	&	-1.10$\pm$0.18	&	8.650\\
			3C208	&	E	&	1356.	&	-0.62$\pm$0.10	&	6.220\\
			&	W	&	205.3	&	-0.46$\pm$0.07	&	4.860\\
			3C249.1	&	E	&	83.20	&	-0.75$\pm$0.12	&	7.620\\
			&	W	&	85.80	&	-0.81$\pm$0.13	&	15.51\\
			3C263	&	E	&	27.50	&	-0.52$\pm$0.08	&	27.88\\
			&	W	&	486.7	&	-0.66$\pm$0.11	&	16.24\\
			3C336	&	N	&	110.7	&	-1.36$\pm$0.21	&	15.01\\
			&	S	&	65.90	&	-1.37$\pm$0.22	&	7.530\\
			3C351	&	N1	&	330.0	&	-0.73$\pm$0.12	&	27.29\\
			&	N2	&	194.0	&	-0.76$\pm$0.13	&	25.02\\
			&	S	&	3.366	&	-0.91$\pm$0.16	&	60.79\\
			3C432	&	N	&	130.0	&	-1.31$\pm$0.21	&	5.700\\
			&	S	&	109.0	&	-0.91$\pm$0.15	&	7.590\\
		\hline
			\multicolumn{6}{p{.4\textwidth}}{Col.(2): N, S, E, W denote north, south, east, and west hotspots respectively;N2, S2, W2 are the second brightest hotspots in the north, west, and south sides.  Col.(3):Peak flux density of the hotspot at 5 GHz estimated using {\tt TVMAXFIT}.  {The errors are of the order of a few per cent ($<$5\%).} Col(4): Spectral index of the hotspot between 1.4 and 5 GHz corresponding to the peak flux density position at the hotspot.  This is obtained using {\tt IMVAL} on the spectral images.  Col(5): Distance from core to the hotspot in arcsec obtained using {\tt TVDIST} on 5 GHz intensity images. { The uncertainties are $\ll$1\%.}}
		\end{tabular}
	\end{table}
	\begin{table}
		\caption{Properties of the core}

		\begin{tabular}{lrrc}
		\hline
			{Name} &	{S$^{1.4}_{total}$}	&	{S$^{5}_{total}$}	&	{$\alpha^{5}_{1.4}$}\\
			{}	&	{(mJy)}	&	{(mJy)}	&	{}\\
			(1)&(2)&(3)&(4)\\
		\hline
			3C14	&	24.3$\pm$2.7	&	10.9$\pm$1.6	&   $-$0.68$\pm$0.10\\
			3C47	&	58.2$\pm$6.5	&	69.2$\pm$7.5	&	+0.08$\pm$0.09\\
			3C109	&	248.7$\pm$27.8	&	274.0$\pm$30.1	&	$-$0.04$\pm$0.05\\
			3C204	&	58.1$\pm$6.5	&	50.3$\pm$5.8	&	$-$0.29$\pm$0.08\\
			3C205	&	40.4$\pm$4.5	&	26.6$\pm$3.3	&	$-$0.34$\pm$0.05\\
			3C208	&	59.4$\pm$6.6	&	51.0$\pm$5.9	&	$-$0.03$\pm$0.02\\
			3C249.1	&	76.0$\pm$8.5	&	78.9$\pm$8.8	&	+0.14$\pm$0.05\\
			3C263	&	148.1$\pm$16.6	&	137.6$\pm$15.6	&	+0.05$\pm$0.02\\
			3C336	&	38.9$\pm$4.4	&	11.1$\pm$2.2	&	$-$0.62$\pm$0.09\\
			3C351	&	35.5$\pm$4.0	&	20.3$\pm$2.7	&	$-$0.45$\pm$0.12\\
			3C432	&	10.2$\pm$1.2	&	6.1$\pm$0.8	&	$-$0.47$\pm$0.08\\
		\hline
		\multicolumn{4}{p{.4\textwidth}}{Col(2-3): Core flux density at 1.4 and 5 GHz respectively.  Col(4):Core spectral index between 1.4 and 5 GHz.  This is obtained using {\tt TVWIN} + {\tt IMSTAT} on the spectral index image.}
		\end{tabular}
	\end{table}

	\begin{table*}
		\caption{{Properties of the radio lobes}}
		\label{tab:quasar_prop_lobes}
		\begin{tabular}{lrrrrr}

			\hline
			{Name}	&	{$\alpha^{5}_{1.4}$}	&	{$\Theta_{width}$}	 &{B$_{min}$}	&	{P$_{min}$}	&	{Axial Ratio}\\
			{}	&	{N,S}	&	{N,S} &	{$\mu$G}	&	{10$^{-11}$dyne~cm$^{-2}$}	&	N,S\\
			(1)&(2)&(3)&(4)&(5)&(6)\\
			\hline
			3C14	&	-1.39$\pm$0.14, -1.39$\pm$0.15	&	2.4$\pm$0.3, 1.8$\pm$0.3	&	109.2$\pm$18.3, 95.2$\pm$18.3	&	59.34, 45.11	&	 4.0$\pm$0.5, 8.5$\pm$1.4\\

			3C47	&	-1.28$\pm$0.18, -1.28$\pm$0.18	&	31.0$\pm$4.7, 35.2$\pm$4.9	&	9.5$\pm$1.7, 9.5$\pm$1.7	&	0.45, 0.44	&	1.0$\pm$0.2, 1.1$\pm$0.1\\

			3C109	&	-1.18$\pm$0.18, -1.57$\pm$0.22	&	7.7$\pm$0.8, 15.6$\pm$1.6	&	16.9$\pm$2.4, 16.3$\pm$2.4	&	1.43, 1.32	&	 6.0$\pm$0.6, 3.1$\pm$0.3\\

			3C204$^\ddagger$	&	-1.42$\pm$0.17, -1.5$\pm$0.17	&	5.9$\pm$0.7, 4.9$\pm$0.6	&	35.6$\pm$7.0, 50.7$\pm$7.0	&	6.29, 12.76	&	3.1$\pm$0.4, 2.7$\pm$0.3\\

			3C205	&	-1.42$\pm$0.15, -1.13$\pm$0.11	&	2.1$\pm$0.3, 1.8$\pm$0.3	&	116.4$\pm$22.1, 110.5$\pm$22.1	&	67.44, 60.74	&	3.4$\pm$0.5, 4.7$\pm$0.8\\

			3C208$^\ddagger$	&	-0.75$\pm$0.09, -0.71$\pm$0.08	&	2.0$\pm$0.3, 1.3$\pm$0.3	&	79.7$\pm$7.9, 72.7$\pm$7.9	&	31.56, 26.28	&	3.1$\pm$0.4, 3.7$\pm$1.0\\

			3C249.1$^\ddagger$	&	..., -1.03$\pm$0.11	&	..., 7.6$\pm$0.8	&		..., 20.8$\pm$2.0	&		..., 2.15	&	..., 2.0$\pm$0.2\\

			3C263$^\ddagger$	&	-1.06$\pm$0.14, -0.88$\pm$0.09	&	12.2$\pm$1.5, 9.1$\pm$1.1 	&	18.3$\pm$2.2, 15.0$\pm$2.2	&	1.67, 1.11	&	 2.3$\pm$0.3, 1.8$\pm$0.2\\

			3C336	&	-2.01$\pm$0.2, -1.89$\pm$0.20	&	6.3$\pm$0.7, 4.9$\pm$0.6	&	93.7$\pm$25.6, 93.2$\pm$25.6	&	43.68, 43.22	&	2.4$\pm$0.3, 1.5$\pm$0.2\\

			3C351	&	-1.10$\pm$0.18, -0.92$\pm$0.18	&	14.3$\pm$1.7, 7.4$\pm$0.8	&	15.4$\pm$2.1, 7.2$\pm$2.1	&	1.19, 0.26	&	1.9$\pm$0.2, 8.2$\pm$0.9\\

			3C432	&	-1.20$\pm$0.13, -1.35$\pm$0.15	&	2.8$\pm$0.4, 2.6$\pm$0.4	&	103.5$\pm$16.2, 98.4$\pm$16.2	&	53.27, 48.16	&	2.1$\pm$0.3, 2.9$\pm$0.5\\

			\hline
			\multicolumn{6}{p{0.8\textwidth}}{Col(1): Source name.  Col(2): Spectral index of the lobe between 1.4 GHz and 5 GHz for the northern and southern lobes.  Col(3): Lobe width in arcsec {obtained using the 1.4 GHz images}.  Col(4): Magnetic field at minimum pressure condition obtained using Equation ~\ref{eq:bmin}.  Col(5):  Minimum internal pressure in the lobe obtained using Equation ~\ref{eq:pmin}. Col(6) Axial Ratios i.e., ratio of the lobe length (core-to-hotspot distance) to lobe width.\newline $^\ddagger$ The estimates are for the eastern and western lobe respectively.}

		\end{tabular}
	\end{table*}

		\begin{table}
		\caption{Quasar properties - Jet sidedness}
        \label{tab:quasar_prop_jet}
		\begin{tabular}{lcccc}
			\hline
				{Name}	&	{Jet Side}	&	{Bright HS}	&	{Ratio of HS}	&	{Shorter}\\
				{}	&	{}	&	{Side}	&	{peak flux}	&	{Side}\\
				(1)&(2)&(3)&(4)&(5)\\
			\hline
	    3C14	&	S	&	S	&	1.36	&	N\\
        3C47	&	S	&	S	&	7.91	&	N\\
        3C109	&	S$^{\dagger}$	&	S	&	6.61	&	S\\
        3C204	&	W	&	W	&	1.34	&	W\\
        3C205	&	S	&	S	&	2.02	&	N\\
        3C208	&	E(?)	&	E	&	6.62	&	W\\
        3C249.1$^{\#}$&	-	&	-	&	-	&	N\\
        3C263	&	E	&	E	&	17.70	&	E\\
        3C336	&	S$^{\dagger}$	&	N	&	1.68	&	S\\
        3C351	&	N(?)	&	N	&	98.03	&	N\\
        3C432	&	S(?)	&	N	&	1.19	&	N\\
			\hline
			\multicolumn{5}{p{.47\textwidth}}{$\dagger$ Not observed in the current data, but observed in other high-resolution VLA archival images \citep{Giovannini1987}.\newline
			\# This is a hybrid structure and so jet cannot be defined.\newline
			Jet features that are ambiguous are denoted with a `?'.}
		\end{tabular}
	\end{table}

\begin{table*}
	\caption{Newly estimated properties of the \citet{Kharb2008} radio galaxy sample.}
	\label{tab:radiogalaxy_prop}
	\begin{tabular}{llcllcccc}
		\hline
		{Name}	&	{\it z}	&	{Arm-length}	&	{log~R$_c$}&
		{LLS}	&	{S$^{1.4}_{total}$}	&	{S$^{150}_{total}$}	&	{P$_{min}$(N,S)}	&	Q$_{jet}$\\
		{}	&	{}	&	{Ratio}	&	{}	&	{(kpc)}	&	{Jy}	&	{Jy}	&	{10$^{-11}$dyne~cm$^{-2}$}	&	{10$^{45}$ erg s$^{-1}$}\\
		(1)&(2)&(3)&(4)&(5)&(6)&(7)&(8)&(9)\\
		\hline
		3C6.1	&	0.804	&	1.15	&	-2.90	&	241	&	3.8		&	17.86	&	15.70, 7.51	&	11.48\\
		3C13	&	1.351	&	1.36	&	-4.19	&	276	&	1.92	&	17.11	&	... &	28.46\\
		3C34	&	0.69	&	1.14	&	-3.47	&	346	&	1.78	&	16.03	&	7.46, 2.81	&	6.74\\
		3C41	&	0.794	&	1.11	&	-3.40	&	204	&	3.51	&	12.16	&	15.10, 9.27	&	8.21\\
		3C44	&	0.66	&	1.63	&	-3.94	&	502	&	1.37	&	10.98	&	4.24, 5.27	&	4.82\\
		3C54	&	0.8274	&	1.07	&	-3.96	&	458	&	2.03	&	11.48	&	3.87, 3.16	&	8.21\\
		3C114	&	0.815	&	1.09	&	-2.53	&	451	&	1.01	&	11.56	&	5.36, 2.22	&	6.35\\
		3C142.1	&	0.4061	&	1.87	&	-3.57	&	299	&	3.10	&	28.48	&	4.88, 1.42	&	3.00\\
		3C169.1	&	0.633	&	1.44	&	-3.40	&	367	&	1.297	&	8.00	&	2.18, 1.21	&	3.12\\
		3C172	&	0.5191	&	1.13	&	-4.18	&	676	&	2.84	&	18.85	&	1.45, 0.65	&	4.54\\
		3C441	&	0.707	&	2.45	&	-4.32	&	299	&	2.53$^\dagger$ &	14.56	&	1.49, 2.74	&	7.29\\
		3C469.1	&	1.336	&	1.07	&	-3.40	&	712	&	1.72	&	12.89	&	13.20, 4.15	&	25.79\\
		3C470	&	1.653	&	1.36	&	-3.97	&	255	&	1.72	&	11.92	& ...	&	37.56\\
		\hline

		\multicolumn{9}{p{.8\linewidth}}{$\dagger$ Taken from \citet{Condon1998} \newline Col.(1)- Name of the source. Col(2)- Redshift from NED.  Col(3)- Arm-length ratio.  Col(4)- K-corrected radio core prominence parameter $S_{5\,GHz}(core)/S_{1.4 \,GHz}(lobe)$.  The 1.4 GHz flux density is taken from \citet{White1992} and the 5 GHz flux density is estimated from  8 GHz assuming $\alpha=0.6$.  Col.(5)-  Projected largest linear separation.  Col.(6)- Total flux density of the source at 1.4 GHz taken from \citet{White1992} in units of (Jy). Col(7)- 150 MHz flux density from TGSS-GMRT in units of (Jy).  {Col(8)- Minimum internal pressure in the lobe obtained using Equation ~\ref{eq:pmin}.} Col(9)- Jet kinetic power estimated as described in Section~\ref{sec:jet_power}.}
	\end{tabular}
\end{table*}

\section{Results}

{In our quasar sample, $\sim$ 70 per cent of sources show one-sided radio jets, while the remaining 30 per cent sources do not clearly show a jet. In all but one source (3C~249.1 which shows a hybrid FR I/FR II morphology) two-sided hotspots located at the end of the radio lobe (i.e. FR II type morphology) are seen. For two sources {(3C~109, 3C~336)}, jet-like features are seen in higher resolution images in the literature \citep{Giovannini1987}. In the radio galaxy sample of \citet{Kharb2008}, 30 per cent of the sources show one-sided jet-like features (see Table 6 of \citep{Kharb2008}). The 5 GHz images of the quasars show the presence of multiple hotspots in some sources. The southern lobe of 3C~263 and northern lobe of 3C~351 have off-axis extended emission i.e., the emission is extended on one side of the jet axis.} See the Appendix for the contour images of the quasars at 1.4 GHz and 5 GHz.

We studied various properties of the cores, lobes, and hotspots of quasars and radio galaxies. We have quantified the observed trends with appropriate statistical tests. The significance of the relationship between properties is assessed using the non-parametric Spearman and Kendall rank tests. Both tests produced nearly identical results and so we have quoted here the results from the Spearman rank test. The p-value is a measure of the significance of the null hypothesis that two variables are uncorrelated. To determine if two distributions are the same, we have used the two sample Kolmogorov$-$Smirnov (KS) test. The null hypothesis to be tested in the KS test assumes that both the samples are drawn from the same population. A p-value of 0.05 and lower is considered to be significant to reject the null hypothesis. $1-p$ gives the per cent confidence level at which the null hypothesis is rejected.

\subsection{Structure Asymmetry}
Arm-length ratio is an asymmetry parameter and is defined as the ratio of the longer to the shorter arm-length, where arm-length is the core-to-hotspot distance. For quasars that show two hotspots on one side, we measured the arm-length ratio using both the hotspots. Figure~\ref{fig:redshift_armlenratio} shows the arm-length ratio with respect to the redshift for the quasars and FR~$\mathtt{II}$ radio galaxies. The arm-length ratio distribution for quasars shows that there are both symmetric and asymmetric structures. A larger fraction of the sources in the radio galaxy sample are symmetric sources than in the quasar sample. Combining both the samples, we find that $\sim 65$ per cent of the sources have arm-length ratios lower than the combined average arm-length ratios (=1.49) suggesting symmetric structures. The KS test indicates that there is no substantial difference in arm-length ratios between the two types of AGNs and they may be drawn from the same population ($p=0.15$). The arm-length ratios  appear to be uncorrelated with redshift ($p=0.2$) \citep[see also][]{Kharb2008} suggesting that symmetric and asymmetric structures prevail at all redshifts.

The (brighter) jet side is observed in seven out of 10 quasars (3C~249.1 is excluded because of its hybrid structure). The remaining three sources have ambiguity in the jet feature (see Table~\ref{tab:quasar_prop_jet}).  Of these seven jetted quasars, four quasars have their bright hotspot side on the same side as the shorter lobe. If we also include the ``tentative'' brighter jet sides from our images, 50 per cent (i.e. five out of ten quasars) have their brighter hotspot side on the same side as the shorter lobe. Simple relativistic beaming theories, however expect the longer arm to be the brighter arm {\citep{Ryle_Longair1967}}. Our results suggest that the brighter hotspot side is equally likely to be either on the shorter arm or on the longer arm .  This asymmetry in brightness and morphology may be a result of asymmetric environments, rather than orientation-dependent Doppler effects. The environmental effects that constrained the jet from expanding might also make the hotspot appear brighter {\citep{Saikia1995, gopalkrishna2004}}.
	\begin{figure}
		\includegraphics[width=\columnwidth]{fig/fig1.png}
		\caption{Arm-length ratio (\textit{Q}) {which is the ratio of longer to the shorter core-hotspot distance} vs redshift. Quasars from our sample are indicated by stars and FR~$\mathtt{II}$ radio galaxies by diamond symbols. The radio galaxy sample is from \citet{Kharb2008}.  {Q for sources with multiple hotspots is also plotted}.  The histogram of the \textit{Q} for quasar and radio galaxies is also shown to the right of the y-axis.  {KS test indicates no substantial difference in arm-length ratio between quasars and radio galaxies.}}
		\label{fig:redshift_armlenratio}
	\end{figure}

\subsection{Hotspot Spectral Indices}
	\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig2.png}
	\caption{Spectral index of the hotspot between 1.4 and 5 GHz in the observed frame vs. redshift.  {Multiple hotspots are also plotted.}}
	\label{fig:redshift_spix}
	\end{figure}
The correlation of spectral index with redshift or radio luminosity is well established \citep{Tielens1979, Blumenthal_Miley1979, Wellman1997, Dennett1999, Ishwara2000, Kharb2008}. {The tendency for the integrated spectral index to steepen with redshift is conventionally attributed to a ``k-correction''. At higher redshift, the spectrum gets shifted to lower frequencies bringing the steep part of the spectrum closer to the observed frequency \citep{Bolton1966, Blumenthal_Miley1979, Laing_Peacock1980, gopalkrishna1988}.  This interpretation for the $z-\alpha$ is based on the observation that the SEDs of radio galaxies steepen at high frequencies.  However, the k-correction mechanism has been disputed owing to the remarkable linearity and the lack of evidence for a spectral curvature in wide band radio spectrum of high redshift radio galaxies \citep{Chambers1990, Klamer2006, Klamer2007}.   \cite{gopalkrishna2012} however argue that since the steepness of the spectral index anti-correlates with the spectral curvature \citep{Mangalam1995}, the spectral steepening becomes negligible for sources with steep spectra ($\alpha_{1GHz} \le -1.2$, also reflected in \cite{Klamer2006}).  k-correction being insufficient to explain the observed $z-\alpha$ relation, alternative effects have been proposed.  A density-dependent effect in which the jets are working against a denser environment at higher redshift can result in greater synchrotron losses at higher frequencies \citep{Athreya_Kapahi1998, Klamer2006, Klamer2007, Ker2012}.  It has also been suggested that for high-$z$ sources, there can be an enhanced spectral aging due to increased inverse-Compton losses of the relativistic electrons against the cosmic microwave background (CMB), since the CMB energy density increases as $(1+z)^4$ \citep{gopalkrishna1989, Krolik_Chen1991, Morabito2018}.   High power sources have higher magnetic fields in the hotspots than in the less powerful sources. This can result in higher synchrotron losses, thus steepening the spectra \citep{Meisenheimer1989, gopalkrishna1990, Blundell1999A}. Yet another possibility is that the $z-\alpha$ is an indirect manifestation of an intrinsic correlation between the luminosity and spectral index which when coupled to Malmquist bias translates to the $z-\alpha$ correlation \citep{Laing_Peacock1980, Chambers1990, Blundell1999A}. This, however, seems to be not the case in our sample as we discuss ahead.

Unlike previous studies where integrated spectral index was used, we examine the hotspot spectral index.  Since hotspots are located far away from the galaxy, their study can provide physical insight into the environments of the radio source, and thereby test the effect of ambient density on source properties.}
Figure~\ref{fig:redshift_spix} shows the variation of spectral index of the hotspot with redshift in quasars and radio galaxies. We see a spectral steepening in the quasar and radio galaxies with increasing redshift consistent with earlier findings. The Spearman rank test indicates a statistically significant correlation with the correlation coefficient of {-0.42} at a significance level greater than 99.99 per cent. A stronger dependence of spectral index on the luminosity is also observed in our sample and is shown in Figure~\ref{fig:radiopower_spix}. High radio power sources have steeper spectral indices and follow the relation $\log P_{1.4GHz} \propto \alpha_{HS}^{0.9}$ at a significance level of 99.99 per cent. {However, this $P-\alpha$ correlation turns out to be not significant when the partial correlation \footnote{The ppcor package in R programming language has been used in partial correlation statistics.} coefficient ($\rho=0.2$, $p-value=0.2$) was measured considering the effect of redshift.  The observed $P-\alpha$ correlation is likely due to the strong correlations between $z-\alpha$ (correlation coefficient = 0.7) and $z-P$ (correlation coefficient = 0.5) at > 99.9\% significance.}
	\begin{figure}
		\includegraphics[width=\columnwidth]{fig/fig3.png}
		\caption{Total 1.4~GHz radio power versus $1.4-5$~GHz hotspot spectral indices. {The dashed line is the best-fit line with a slope of $-0.9$.}}
		\label{fig:radiopower_spix}
	\end{figure}

The average spectral index of the hotspots in quasars is {0.88$\pm$0.04} similar to the radio galaxies {which has $\alpha_{HS}$=0.87$\pm$0.02} . The KS test indicates that the $\alpha_{HS}$ distribution  of quasars and radio galaxies are the same ($p-value=0.40$). In $\sim$80 per cent of the quasars, the hotspot with the flatter spectral index is also the one with higher peak {power} at 1.4 GHz; this fraction is $\sim60$ per cent in the case of the radio galaxies.
In 70 per cent of the quasars (i.e., 7 out of 10 quasars excluding the hybrid quasar 3C349.1) where one-sided jets are observed, the jet-sided lobe has a significantly brighter hotspot than the non-jetted side in 6 out these 7 quasars. On the other hand, in the radio galaxies, only $\sim 30$ per cent of them show one-sided jet-like features and again the jet side points to the brightest hotspot. These observations (i.e. a similar distribution of hotspot spectral indices, jet-side pointing to the brightest hotspot in quasars and radio galaxies) imply that the brighter hotspot is likely, not due to Doppler boosting. The hotspots of quasars and radio galaxies considered here, {do not have a bulk motion that is relativistic.}
The hotspot power is between 10-20 per cent of the total power at 1.4 GHz. The hotspot power correlates and increases with the total power in quasars and radio galaxies. The statistical significance of the $\alpha - z$ relation for the hotspot ($p-value=5E-5$) is stronger than the $\alpha - z$ relation for core spectral index ($p-value=0.04$).

\subsection{Radio Core Prominence}

\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig4.png}
	\caption{Logarithm of the radio core prominence {(ratio of core flux to the lobe flux density) }{R$_c$}vs. redshift for quasars and radio galaxies. {Quasars have larger R$_c$ than radio galaxies consistent with the orientation-based unification scheme.}}
	\label{fig:redshift_corepromin}
\end{figure}

The radio core prominence $R_c$, is the ratio of the (beamed) radio core flux density to the (unbeamed) lobe flux density \citep{Orr_Browne1982,Zirbel_Baum1995}. It is a statistical indicator of beaming and thereby orientation \citep{Padovani_Urry1992, Kharb2004}; larger $R_c$ values correspond to smaller viewing angles. The k-corrected radio core prominence is calculated using
\begin{equation}
R_c =\frac{S_{core}}{s_{total}-s_{core}}(1+z)^{\alpha_{core}-\alpha_{ext}}\\
\end{equation}
where $S_{core}$ is the core flux density at 5~GHz and $S_{total}$ is the total radio emission at 1.4~GHz. Figure~\ref{fig:redshift_corepromin} shows log~$R_c$ with respect to redshift for quasars and radio galaxies. For the radio galaxies, the 5~GHz core flux density is estimated from the 8~GHz measurements assuming a spectral index of $-0.6$ {(average core spectral index in \cite{Kharb2008} sample)}, and the total flux density is taken at 1.4~GHz. It can be seen that quasars have larger $R_c$ values when compared to the radio galaxies. This is consistent with the orientation-based unification of quasars with radio galaxies; quasars are oriented at relatively smaller angles compared to the radio galaxies.

The median log~$R_c$ for the quasars and radio galaxies is $-1.97$ and $-3.44$, respectively, consistent with the RL unification scheme. For quasars, $-2.8 < log~R_c < -1.0$, and for the radio galaxies, $-4.3 < log~R_c < -2.5$.
\citet{Kharb2004} (see their Figure 3) have estimated log~$R_c$ values for a large number of AGN ranging from the plane-of-sky narrow-line radio galaxies to nearly pole-on blazars.
{ Using the relations between $R_c$, jet speed and orientation angles presented in Appendix A of \citet{Kharb2004}, a minimum log~$R_c$ ($R_c^{min}$) value of $-4.5$ \citep[see][]{Kharb2004}, bulk jet Lorentz factor of 10 \citep{Kapahi1982}, we deduce that the radio galaxies considered here lie at orientation angles between 34$\pm$1$\degr$ and 74$\pm$2$\degr$, while the quasars lie at orientation angles between 19$\pm$1$\degr$ and 38$\pm$1$\degr$.  85\% of the radio galaxies have orientation angles greater than 45$\degr$.} \cite{Barthel1989} suggested that the average $\theta=31\degr$ for quasars, and $\theta=69\degr$ for radio galaxies. These are, of course, crude representative estimates because $R_c$ is a statistical indicator of orientation and cannot be used to derive orientation angles for individual sources.  It is important to note that while quasars are at relatively small angles compared to the radio galaxies, as indicated by their relative $R_c$ values, the overlapping spread in $R_c$ values indicates that the quasars are not oriented at small enough angles ($\lesssim10\degr$) to qualify as blazars.

	\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig5.png}
	\caption{Arm-length ratio vs. logarithm of radio core prominence $R_c$.  {Arm-length ratio from multiple hotspots is plotted.  The KS test indicates a weak correlation suggesting that arm-length ratio is not strongly affected by projection.}}
	\label{fig:rc_armlenratio}
\end{figure}

Figure~\ref{fig:rc_armlenratio} shows log~$R_c$ plotted against the arm-length ratio, \textit{Q}.  We find a weak anti-correlation {in the combined sample} with a correlation coefficient of $-0.38$ at a significance of 95 per cent ($p-value =0.05$). This marginal relation, which also has a large scatter, might suggest that the arm-length ratio is not strongly affected by projection but is an intrinsic asymmetry.  {We suggest that this weak relation is apparent and may be a result of small sample size, and $R_c$ and arm-length ratio may not be correlated.  This is supported by the orientation independent statistics for the arm-length ratio in this sample {(see Section 3.1)}.}

\subsection{Largest Linear Size}
The jet orientation angle with respect to our line of sight influences the observed size of a radio source such that, $LLS_{proj} = LLS_{true}\times sin\theta$. Sources with jets oriented close to the line of sight will have smaller apparent sizes than sources oriented close to the plane of the sky for sources with similar intrinsic sizes. In the present work, the angular sizes of the radio galaxies appear to be larger than the quasars. The average projected LLS of radio galaxies is 1.6 times larger than those of quasars. Following the Unification scheme, if we assume that quasars and radio galaxies are the same objects and have similar distributions in true linear sizes, then $LLS_{proj_{RG}}/LLS_{proj_{RLQ}} = sin\theta_{RG}/sin\theta_{RLQ}$. { Using an average $\theta_{RLQ}=29\degr$ and $\theta_{RG}=54\degr$ for quasars and radio galaxies, respectively, as indicated by their $R_c$ values, gives $sin\theta_{RG}/sin\theta_{RLQ} \sim 1.6$, fully consistent with $LLS_{proj_{RG}}/LLS_{proj_{RLQ}} = 1.6\pm0.3$.

The LLS ratio can be used to estimate the angle dividing quasars and radio galaxies ($\theta_0$) using the foreshortening calculations given by:
	\begin{equation}
		LLS_{proj_{RG}}/LLS_{proj_{RLQ}} = \frac{sin(cos^{-1}(0.5cos\theta_0))}{sin(cos^{-1}(0.5(1+cos\theta_0)))}
	\end{equation}
For an LLS ratio of 1.6, this gives $\theta_0=51\degr$.
These are in agreement with the torus opening angle estimated from the projected linear sizes of the radio sources. The average projected LLS of quasars is 240$\pm$28~kpc, while the radio galaxies have an average projected LLS of 390$\pm41$~kpc. Using Eq (7) of \cite{Arshakian2005}, the torus opening angle for the quasars in our sample is 57$\degr\pm$8$\degr$.  This yields an average orientation angle of 74$\pm 4\degr$ for radio galaxies and 39$\pm 5\degr$ for quasars.  Encouragingly, this matches with the upper end of the average orientation angles estimated using R$_c$.}

\cite{WanDaly1998b} and \citet{Barthel1989} reported $LLS_{proj_{RG}}/LLS_{proj_{RLQ}}$ ratios of 1.25 and 1.8 respectively {for 3C sources}.  Recently, using galaxies from the Bootes survey observed using LOFAR, \cite{Morabito2017} found the ratio of the average projected linear size of radio galaxies to the quasars to be $3.1\pm1.0$,  and $2.0\pm0.3$ after correcting for redshift evolution.  The LLS estimates in this study are consistent with the LLS estimates in the literature, and minimal difference in the LLS ratio is likely due to the way the samples are selected.  The selection criteria in our study (and \citet{WanDaly1998b}) favours quasars that have well-resolved extended lobes which in turn correspond to quasars at relatively larger viewing angles to the line of sight.

Overall, our results are consistent with the orientation-based unification scheme for quasars and radio galaxies. However, the range of orientation angles might not be large enough to show clear correlations with respect to orientation-indicators like $R_c$ or misalignment angles.  We find the inverse dependence of the angular size with the redshift (widely known as the D-z relation) consistent with previous studies \citep{Miley1968, Kapahi1985, Blundell1999A, Ker2012, Morabito2017}.

\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig6.png}
	\caption{$1.4-5$~GHz hotspot observed spectral index versus projected {core-hotspot distance.} {The $\alpha_{HS}$ for multiple hotspots in each lobe is plotted.}}
	\label{fig:spix_las}
\end{figure}

The dependence of the $1.4-5$~GHz spectral index of the hotspots on the projected {core-hotspot distance} is shown in Figure~\ref{fig:spix_las}. We have plotted the spectral index of the hotspots of both the lobes for each source. We find a correlation between the spectral index and the projected {core-hotspot distance} of the quasars at a {96} per cent significance level. { This apparent correlation, however, disappears once a partial correlation test is performed between $\alpha_{HS}$ and the core-hotspot distance neglecting the effects of redshift.  This is indicative of the evolution of spectral index and size with redshift.}

\subsection{Lobe Axial Ratios}
The axial ratios (lobe length-to-width ratio) for quasars are lower and statistically different from the radio galaxies in our study consistent with results obtained by \cite{Leahy1989}. The intensity maps show more asymmetric and distorted lobes {(such as extended diffuse emission to one side of the jet)} in quasars (e.g. 3C~14, 3C~204, 3C~249.1, 3C~263, 3C~351) than in radio galaxies. The KS test suggests that quasars and radio galaxies have different distributions at 96 per cent significance ($p-value=0.04$). The median axial ratios of quasars and radio galaxies are {3.0} and 4.2 respectively.  The lobe widths of quasars are on an average only {1.3} times fatter (i.e. larger lobe width) than the radio galaxies and their median lobe widths are similar.  Thus, lobe widths of quasars studied here are rather insensitive to projection effects, consistent with \cite{WanDaly1998b} who showed that projection has little effect on lobe width except at very small angles or for source widths measured close to the hotspot. This indicates that the ratio of lobe length to the width i.e. axial ratio is likely governed by the projection of the length.  The average core-hotspot size ratio for similar lobe widths is 1.45. This likely suggests that the different axial ratios can be accounted for by projection effects alone. {\cite{Leahy1989} however find that the differences in axial ratios cannot be explained by projection effects alone. Larger lobe structure distortions seen in quasars (also seen in our quasar sample) can partly explain the low axial ratios.} Such lobe distortions can, for example, arise due to variations in the outflow angles, as discussed in Section~\ref{sec:misalignment}.  {Any evolutionary relationship between quasars and radio galaxies leading to smaller linear sizes in quasars compared to radio galaxies, however, cannot be ruled out ~\citep[e.g.][]{Miley1971,Wardle_Miley1974}.}

The axial ratios show a marginal correlation with the spectral index of the lobes (correlation coefficient = {0.3, $p-value=0.03$}) (see Figure ~\ref{fig:axialratio_lobeflux}) and an anti-correlation with the lobe flux density ({$\rho$=-0.4, $p-value=0.01$}), both at a greater significance level i.e. fatter lobes are brighter and have steeper spectra. This is believed to be due to confinement of the lobes which enhances the radio emission through synchrotron losses while reducing the adiabatic expansion losses \citep[e.g.,][]{Roland1985, Barthel1996}. We further compare the axial ratios against the structure asymmetry using the arm-length ratio in Figure \ref{fig:axialratio_armlenratio}. Individually, the quasars and radio galaxies do not show any correlation, but the combined sample shows an anti-correlation at a significance level of 96 per cent ($p-value=0.04$). This anti-correlation implies that sources that are narrower i.e. with larger axial ratios are also more symmetric in terms of their lobe sizes (i.e., have arm-length ratios closer to unity). The shorter or fatter sources are the more asymmetric. Such an anti-correlation was also observed in the combined radio galaxy sample in \citet{Kharb2008}, who found that the shorter lobe was fatter and had a steeper spectral index.

	\begin{figure}
		\includegraphics[width=\columnwidth]{fig/fig7.png}
		\caption{Axial ratio vs lobe spectral index shows significant marginal anti-correlation ($\rho$=-0.3).}
		\label{fig:axialratio_lobeflux}
	\end{figure}

	\begin{figure}
		\includegraphics[width=\columnwidth]{fig/fig8.png}
		\caption{Plot of the axial ratio vs arm-length ratio for the quasar and radio galaxy sample.}
		\label{fig:axialratio_armlenratio}
	\end{figure}

\subsection{Jet Axis Misalignment}
\label{sec:misalignment}
Misalignment angle is the complement of the angle between the lines joining the core to the two hotspots. This is an asymmetry parameter and is sensitive to the orientation of the source to the line of sight. An intrinsic jet axis misalignment can appear enhanced for small angles to the line of sight, due to projection effects \citep{Reynolds1980, Conway_Murphy1993}. However, the misalignment angle is also found to be sensitive to environmental effects \citep{Kharb2008}. The misalignment angles for quasars are typically greater than $5\degr$ and the average misalignment angle for quasars is about 1.8 times greater than radio galaxies  {(See Table ~\ref{tab:quasar_basic_prop}),  however, we} cannot reject the hypothesis that both the samples have similar distribution at 28 per cent ($p-value=0.28$).  {Although differences in misalignment angles can become amplified due to a geometrical projection effect, the difference seen in our sample is marginal  because amplification is likely to be significant only in sources that are oriented close to the line of sight \citep{Moore1981, Saikia1995}.}

Figure~\ref{fig:misalign_rc} shows the misalignment angle versus the radio core prominence, log~$R_c$. Statistical tests show no correlation for the quasars and radio galaxies taken together ($p-value=0.8$) or separately for quasars ($p-value=0.2$). \citet{Kharb2008} had found a weak positive correlation for a large sample of radio galaxies. The radio core prominence$-$misalignment angle correlation has also been observed in quasars by \citet{Kapahi1982,Hough1989}. This implies that either $R_c$ or the misalignment angles or both are not uniquely orientation-dependent. Environmental factors may be instrumental in this lack of a correlation. $R_c$ could be influenced by environmental asymmetries on parsec-scales, while misalignment angles could be influenced by environmental asymmetries on parsec as well as kpc-scales \citep[][]{Kharb2010}.

\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig9.png}
	\caption{Misalignment angle vs logarithm of the radio core prominence. {Misalignment angle obtained for multiple hotspots is also plotted.}}
	\label{fig:misalign_rc}
\end{figure}

Figure~\ref{fig:misalign_axialratio} shows the misalignment angles against axial ratios (longer and narrower sources have larger axial ratios).  Quasars show smaller axial ratios and larger misalignment angles. This is consistent with the idea that environment plays an important role in tracing the jet and lobe structure. When the jet and the counter-jet plough into {a} medium with different densities, it will cause the jet to {bend} leading to greater misalignment angles {\citep{McCarthy1991}}. {It is also possible that outflow angle is changing with time, as in the \qq{dentist drill} model \citep{Scheuer1982} $-$ the jet axis random walks sending out the jet in different directions.}

\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig10.png}
	\caption{Misalignment angle vs axial ratio for the quasar and radio galaxy sample.}
	\label{fig:misalign_axialratio}
\end{figure}

\subsection{Minimum Internal Pressures}

The internal pressure of the jet when compared with the external gas pressure of the ambient medium can be used to understand whether the ambient medium is sufficient to confine the outer parts of the radio structure.  The non-thermal internal pressure in the radio jets contributed by the relativistic particles and magnetic field can be crudely estimated from the minimum energy arguments for synchrotron radiation.  It assumes equipartition of energy density in the particles and in the magnetic field \citep[e.g.,][]{Burbidge1956, Miley1980}.  This internal pressure will be a lower limit and is given by (following \cite{Odea1987})

\begin{equation}
P_{min} = \frac{B_{min}^2}{8\pi} + \frac{E_{min}}{3\phi V} ~~~ dyne~cm^{-2}
\label{eq:pmin}
\end{equation}
where,
\begin{equation}
B_{min} = [2\pi(1+k)C_{12}L_{rad}(V\phi)^{-1}]^{2/7}		~~~ 10 ~\mu G
\label{eq:bmin}
\end{equation}
is the magnetic field at minimum pressure condition, and
\begin{equation}
E_{min} = \left[\frac{V\phi}{2\pi}\right]^{3/7}[L_{rad}(1+k)C_{12}]^{4/7} ~~~ erg
\end{equation}

is the energy of the particles at minimum pressure. $k$ is the ratio of proton to electron energy and is assumed to be 1, $C_{12}$ is a constant from synchrotron theory that depends on the spectral index, and the upper and lower cut-off frequencies, $L_{rad}$ is the radio luminosity within the upper and lower cut-off frequencies. We use $C_{12}$= 2.8 $\times ~10^7$ by assuming a spectral index of $-0.7$, 10 MHz and 100 GHz as the lower and upper cut-off frequencies, respectively. $\phi$ is the volume filling factor and is assumed to be equal to 1. To estimate the volume V (in cm$^{-3}$), we make an assumption that the radio lobe is cylindrical with half the lobe width as the radius and core-to-hotspot distance as the height of the cylinder. The radio luminosity $L_{rad}$ is calculated using \citep{Odea1987}
\begin{equation}
\begin{split}
L_{rad} = 1.2 \times 10^{27}D_{Mpc}^2S_0\nu_0^{-\alpha}(1+z)^{-(1+\alpha)} \\ \times (\nu_u^{(1+\alpha)} - \nu_l^{(1+\alpha)})(1+\alpha)^{-1}	~~erg~s^{-1}
\end{split}
\end{equation}

The average $P_{min}$ for quasars is $2.60\times 10^{-10}$ dyne cm$^{-2}$.  We follow the same procedure and estimate minimum pressure for the radio galaxies studied here. The average $P_{min}=0.58\times10^{10}$~dynes~cm$^{-2}$ for radio galaxies. This is roughly {a} factor {of} 4 lower than the $P_{min}$ in quasars. {Given that a greater fraction of radio galaxies are below redshift of 1, the lower $P_{min}$ of radio galaxies may likely be a result of the increasing $P_{min}$ with redshift as seen in Figure ~\ref{fig:redshift_pmin} and described below.}

Figure ~\ref{fig:redshift_pmin} shows the minimum lobe pressure as a function of redshift. The lobe pressure correlates strongly with redshift with a correlation coefficient of 0.83 obtained at a significance greater than 99.99 per cent. The slope of the linear fit is 1.32. The plot suggests that high redshift sources have lobes with higher minimum non-thermal internal pressure \citep[see also][]{Odea2009}. This could be an outcome of the increasing radio luminosity and decreasing lobe widths observed in this sample with redshift. This also results in increasing $B_{min}$ with redshift.  \citet{WanDaly1996} suggest that inner regions on radio lobes (close to the core) are in pressure equilibrium with their surroundings and the ambient gas densities are found to have generally no dependence on redshift \citep{Odea2009}. This implies that the actual source magnetic field strengths are lower than the minimum energy magnetic field strengths. Alternatively, high redshift sources are likely interacting with the ambient medium and have not yet reached pressure equilibrium with their surrounding. High redshift sources have denser ambient gas than at low redshift. This requires high pressures in the radio lobes to maintain pressure equilibrium with the ambient dense gas.

\begin{figure}
	\includegraphics[width=\columnwidth]{fig/fig11.png}
	\caption{Minimum pressure in the radio lobes vs redshift for quasars and radio galaxies.}
	\label{fig:redshift_pmin}
\end{figure}

\begin{table}
	\caption{Spearman correlation statistics for different properties of the combined quasars and radio galaxy sample.}
    \label{tab:corr_stats}
    \begin{tabular}{cccc}
    	\hline
        Property 1	&	Property 2	&	Correlation	&	Probability\\
        {}	&	{}	&	{coefficient}	&	{p-value}\\
        \hline
        $z$	&	Arm-length Ratio	&	0.2	&	0.4\\
        $z$	&	$\alpha_{HS}$	&	-0.4	&	0.003	\\
        $\alpha_{HS}$	&	$P_{1.4 GHz}$	&	-0.5	&	0.02\\
        $R_c$	&	Arm-length Ratio	&	-0.4	&	0.05\\
        LLS	&	$\alpha_{HS}$	&	-0.3	&	0.2	\\
        Axial Ratio	&	$\alpha_{HS}$	&	0.3	&	0.01\\
        $R_c$	&	Misalignment Angle	&	0.03	&	0.8\\
        \hline
    \end{tabular}
\end{table}

\section{Low frequency emission in quasars and radio galaxies}
\label{sec:lowfrequency}
TGSS is a radio survey carried out using the GMRT at 150~MHz and covers a declination range of $-55\degr$ to $+90\degr$. It has the highest resolution of $25\arcsec$ in the low frequency regime. The TGSS Alternative Data Release \citep[ADR1,][]{Intema2017} re-processed the TGSS images using a robust automated pipeline SPAM \citep{Intema2014} which employs techniques such as direction dependent calibration of ionospheric phase errors and image-based flagging to deal with the widespread RFI at the low frequency. We use the TGSS ADR1 images to study the morphology of {this} quasar and radio galaxy sample at low frequencies and derive total energy transported by the jets during the lifetime of the AGN. We find that the classical FR~$\mathtt{II}$ type morphology seen in the 1.4 and 5 GHz images is no longer the same at 150~MHz. Several sources (see Figure~\ref{fig:tgss_quasars}) show signatures of wings and extended emission in directions perpendicular {and at an oblique orientation} to the primary lobes observed at GHz frequencies, reminiscent of X-shaped galaxies \citep{Leahy1984,Leahy1992}. Here we simply refer to all such structures as ``distorted''. We note that these wings persist in higher resolution GMRT images at 610~MHz (Vaddi et al. 2018, in preparation), attesting to the reality of these features. These distorted radio morphologies may indicate jet axis re-alignment and/or multiple activity episodes in these AGNs.

\subsection{Jet Kinetic Power}
\label{sec:jet_power}
The synchrotron emitting plasma in the lobes can be used as an indicator of the amount of energy supplied by the jets to the lobes \citep{Godfrey_Shabala2016}. The time-averaged total bulk kinetic jet power, defined as the total energy transported by the jets over the lifetime of the source, is given by (Equation 12 of \cite{Willott1999})
\begin{eqnarray}
Q_{jet} &\approx 3 \times 10^{45}
[(1+z)^{-(1+\alpha)}~4\pi D_L^2~S_{150}]^{6/7} ~~ erg~s^{-1}
\label{eq:jet_power}
\end{eqnarray}

where $S_{150}$ is the total flux density at 150~MHz in W~m$^{-2}$~Hz$^{-1}$, $\alpha$ is the spectral index estimated using the flux density at 150~MHz and 1.4 GHz, and $D_L$ is the luminosity distance.
Equation~\ref{eq:jet_power} assumes that {synchrotron radiation losses are negligible. The average quasar jet power is 6.4$\pm$0.07 $\times$ 10$^{45}$ erg~s$^{-1}$.}  The KS test shows that the time-averaged jet kinetic power for quasars and radio galaxies may have similar distribution ($p-value=0.46$).  The jet power ranges from ${(1 - 38)}\times 10^{45}$~erg~s$^{-1}$, with 3C~470 radio galaxy having the highest jet kinetic power (refer Table ~\ref{tab:quasar_basic_prop}, and Table ~\ref{tab:radiogalaxy_prop}). The jet power and redshift are correlated which is expected from a flux limited 3C sample. {For the quasar sample, we notice that jet power is related to the mass of the supermassive black hole such that higher jet powers are associated with more massive black holes.  However, a partial correlation test between jet power and the black hole mass while ignoring the effect of redshift does not show any correlation ($\rho$=-0.3, $p-value$=0.5) between jet power and black hole mass suggesting that the observed trend is likely a manifestation of Malmquist bias.}

{
\section{Possible Biases}
\subsection{Selection Bias}
The \citet{Kharb2008} radio galaxies have radio power > 10$^{28}$ WHz$^{-1}$ at 178 MHz.  Their angular sizes are > 27" and the sources have a redshift range from 0.4 to 1.65.  The quasars were selected to have BH mass determinations, at least one side of the source without a radio jet, and radio powers $>$ 3$\times$10$^{26}$h$^{-1}$ W~Hz$^{-1}$~sr$^{-1}$ which for our chosen {H$_0$} gives 5$\times$10$^{26}$ WHz$^{-1}$~sr$^{-1}$; the sources have redshift between 0.3 and 1.78.  The black hole masses for the quasars were obtained from \cite{Mclure2006}, who studied the FWHM of the broad-line emission and typically found v $>$ 2000~km~s$^{-1}$. {Based on these selection criteria, we can say the following about its effects on our results}.
{ The selected radio galaxies are NLRG that are mostly in the plane of the sky and lack the broad-lines for BH mass estimates through virial methods.} This BH mass selection criteria for quasars, therefore, does not change the results. Since the quasars in our sample are selected such that spectral ageing can be performed, it automatically selects quasars that have larger lobe extents which in turn selects sources that are {intrinsically larger or are at larger angles to} the line of sight. This gives the quasars in our sample a larger average LLS compared to previous studies. This, however, does not change the general conclusion that quasars have statistically smaller projected sizes than the radio galaxies, in line with unification.

\section{Summary and Conclusions}
We have presented the results from our 1.4 and 5~GHz study with the VLA of 11 FR~$\mathtt{II}$ radio-loud quasars. The $1.4-5$~GHz spectral index images reveal spectral steepening along the lobes, moving away from the hotspots. These maps and results will be used in the spectral ageing analysis, the results of which will be presented in Paper II.  We compare these quasars with FR~$\mathtt{II}$ radio galaxies to study the radio-loud unification scheme. We consider 13 narrow-line FR~$\mathtt{II}$ radio galaxy sample that span similar redshift, luminosity, and have matched frequency/resolution data. We see that radio-loud unification largely holds but environmental factors also play an important role.
We have shown that:
\begin{enumerate}
	\item
{ The radio core prominence ($R_c$) parameter, which is a statistical indicator of beaming and thereby orientation, suggests that the radio galaxies considered in our study lie at orientation angles between $34\degr$ and $74\degr$, while the quasars lie at orientation angles between $19\degr$ and $38\degr$, broadly consistent with the radio-loud unification scheme.}

	\item About 90 per cent of the sources have brighter hotspots on the jetted side and the brighter hotspot is equally likely to be on the shorter or on the longer arm indicating that beaming effects may not be the primary contributor to the observed structural and brightness asymmetry.

	\item The hotspot spectral index ($\alpha_{HS}$) distribution is similar for quasars and radio galaxies.  The $\alpha_{HS}$ is strongly anti-correlated with redshift and it is argued to be due to higher synchrotron losses at higher redshifts due to {density-dependent effects while luminosity-dependent or size-dependent effects are not seen}.

	\item The average projected LLS of radio galaxies is 1.6$\pm$0.3 times larger than those of quasars in our sample. {This is comparable to the ratio of the sine of average orientation angles calculated from $R_c$. This is consistent with the orientation based unification scheme and LLS is likely probing orientation.}

	\item The median axial ratios of quasars are roughly a factor of 1.4 lower than the radio galaxies. This may be explained by projection in length since the differences in lobe widths between quasars and radio galaxies are minimal.  However, larger and significant lobe distortions seen in quasars compared to radio galaxies support the importance of intrinsic/environmental differences.  It is possible that the direction of the quasar jets in our sample is changing with time, {as} in the \qq{dentist drill} model, while radio galaxies have stable long-term collimated jets.  { Alternatively, evolutionary relationship between quasars and radio galaxies, however, cannot be ruled out. }

	\item  The misalignment angles for quasars are roughly 1.8 times greater than radio galaxies likely indicating an orientation effect. However, the radio core prominence which is also a statistical indicator of orientation does not show a correlation with the misalignment angle.  Environmental factors may be instrumental in this lack of correlation.  {R$_c$ could be influenced by small-scale environment asymmetries while the misalignment angle could be influenced by both small scale and large scale environment asymmetries.}

    \item  {The minimum lobe pressure is strongly correlated with redshift. High redshift sources have lobes with higher minimum internal pressure to maintain pressure equilibrium with the denser ambient gas.}

    \item Low frequency emission at 150~MHz with the GMRT reveal the lobes to move away from the classical FR~$\mathtt{II}$ morphologies; many sources reveal extended, winged morphologies that could suggest changes in jet orientation and/or restarted AGN activity in these quasars.

	\item  The time-averaged jet power estimated using the 150~MHz data is similar for quasars and radio galaxies.

\end{enumerate}
{In summary, several of the observed properties of quasars are consistent with the orientation-based radio-loud unification scheme. However, differences and relations between orientation indicators such as axial ratio, misalignment angle, and larger lobe distortions in quasars can be explained by intrinsic/environmental asymmetries.}

\section*{Acknowledgements}
{We thank the referee for constructive and insightful suggestions that have significantly improved the quality of the manuscript.}  The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.  {The work of Stefi Baum and Chris O'Dea was supported by NSERC (Natural Sciences and Engineering Research Council of Canada). The work of Ruth Daly and Trent Barbusca was supported by Penn State University.} This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. We thank the staff of the GMRT who have made these observations possible. GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research.

\newpage

redpajama_set_name: RedPajamaArXiv


Obituary - Eileen J. Frost - Bentz Funeral Service, Inc.
In lieu of flowers, kindly consider the Muscular Dystrophy Association.
Eileen J. Frost, 63, of Doolittle Rd., passed away unexpectedly on Sunday, March 1, 2009, in Florida, with her family by her side. She was born February 13, 1946, in Rome, the daughter of Vera Countryman Hurlbut and the late Kenneth Hurlbut. She was a graduate of Remsen Central School, class of 1964 and the Utica School of Commerce. On September 3, 1966, at St. Patrick's Church, Clayville, she married her soul mate, Franklin J. (Frank) Frost. For many years, Mrs. Frost worked side by side with her husband in the operation of their dairy farm. In 1994, they sold their dairy and continued raising crops. She was a parishioner of St. Bernard's Church, Waterville. Mrs. Frost was a member of the Oneida County Farm Bureau, where she served as editor of the farm bureau news letter for many years and was a past chairperson for the Oneida County Dairy Promotion Committee, where she was the recipient of the "Silver Cow Award" in 1988, for her work in dairy promotion. Eileen was a devoted and loving wife, mother, grandmother, daughter and sister. She enjoyed making crafts, gardening and knitting caps and scarf's for people. She is survived by her husband, Frank; her mother, Vera of Westernville; three children, Michelle Frost and her fiancé James Battista of Canastota, Franklin, Jr. and Natalie Frost of Sauquoit and Cheryl and Marty Thomas of WV; three grandchildren, the "apple of her eye" Kenneth Frost of Sauquoit and Lindsay and Kyler of WV; her brother, Kenneth Hurlbut of Buffalo; her brother-in-law, Edward Kozak of Rome; her sisters-in-law, Carol Capron of Clinton and Jacqueline and Robert Moore of Sauquoit; and many nieces and nephews. She was predeceased by her sister, Audrey Kozak in 1988. A Mass of Christian Burial will be celebrated on Saturday at 10 am at St. Bernard's Church, Waterville. Spring interment will be in St. Paul's Cemetery, Paris Hill. Calling hours are Friday evening from 4-7 at the Kloster-Northrop & Bentz Funeral Home, 210 E. Main St., Waterville. The family wishes to extend many thanks to their very special friends, Donald and Luana Humphreys, and to Dr. Alicia DeTraglia and Dr. Eric Yoss and staff's, for all their kindnesses over the years.
Frank We are sorry to here of your great loss. May you know that our Prayers are with you and your Family.
From Rick, Patrick and the whole crew here at 4 Seasons tire and auto, We are sorry for your loss.


The Colors Of Indian Cooking: A Tale of Two Cauliflowers..The Cheap and The Pricey..Mildly Spicy With A Coconut Kick!
A Tale of Two Cauliflowers..The Cheap and The Pricey..Mildly Spicy With A Coconut Kick!
In Cauliwood every Cauliflower has it's price. This is a tale of one of them.
She sat there in the fading Marin sunshine. It was late afternoon and some wisps of fog whipped across the sky. She was all bright purple with a swirl of tight emerald leaves. A friend of ours, Mr. X we'll call him sidled up to her. He stared admiringly.
"She's a real knock out isn't she?" a voice said.
"Uh. yeah," Mr. X said, embarrassed to have been caught eyeing her.
"She just got into town, there's not another one like her. She's special!" said the Farmer. "Why don't you take her home. Only 7 bucks"
"Isn't that a lot for a cauliflower?"
"You ever seen a purple one before?"
Mr. X took a deep breath and reached for his wallet.
Side note here: Mr. X is a very, very good friend of ours, a world traveler and a frequent guest at our table. He's always my marker for Indian food. I am always asking "is this as good as your friends' wife makes in Trivandrum??"
When he bought the 7 dollar cauliflower, he had me in mind. He brought it over to our house and made me close my eyes while he took it out of a bag and put it on the kitchen table.
"Ever see anything like this before?!!"
I pulled open the refrigerator door and took out the cauliflower that I had bought the same day from the guy down the road for 99 cents.
I hated to do it. But he had to learn. It's Cauliwood Mr. X, and they're all the same.
So that's the origin of the 4 act Indian lunch. When someone gives you a 7 dollar cauliflower you HAVE to cook it, and cook it well.
I decided to blend it with my 99 cent purple special to have enough cauliflower to go around. The great thing about this purple cauliflower is that unlike the blue/purple, non-green beans, this stuff kept its' brilliant color even after cooking. Under the knife it was gorgeous.
I have also been taking advantage of the container of Tropical Traditions Organic Shredded Coconut I was sent and I was eager to show it off. The purple cauliflower was the perfect background.
Wash, dry and cut 1 large or two small cauliflower into little florets..
When the chilies start to turn a darker color, put in the lovely purple cauliflower.
Give it a stir or two.
Then add 3/4 tsp of salt and about 6 Tbs of water.
Cover the pan, turn the heat down and let the magic work.
Cook everything for about 5 minutes, see if the cauliflower is tender, take the lid off the pan and let any liquid cook off. We don't want soggy and purple, we want crisp and purple.
2 Tbs of shredded coconut.
DO NOT eat the whole chilies!!!! You may be tempted but don't. If someone insists they can handle it, you might want them to sign an affidavit first, and get out a fire hose.
So there it is. When all was said and done the pricey mingled with the cheap and no one knew the difference....That's Cauliwood!
If you'd like to score some of Tropical Traditions amazing Organic Shredded Coconut so that you can try this dish yourself, I'll be giving away a container just like the one they sent me to review. Check out my blog tomorrow for the rules on how to get this for yourself.
he's feeling terrible..as he loves a bargain. Of course we rub it in..99 cents neener,neener,neener!
What a great tale! And great flavor and way to add color to the table.
Oh god, even out here in no mans land a purple cauliflower isn't 7.00. Looks very yummy!
Hahaha that's so funny. $7!! I blogged about one I picked up for 99c at an Asian market--where I got an orange one yesterday.
This is also a great way to make cauliflower--I'm going to try it out since I have the orange one in the fridge and those spices from a friend. Thanks!
when ever I get a cauliflower my first thought is almost always indian food... your looks delicious!
Loved the story! The Marin market used to be my favorite, but I haven't been in probably near 20 years. We will definitely have to keep this recipe in mind when I see one of these purple guys... I will check the price though, as I might have spent the $7 too. Can't wait to hear about the coconut tomorrow!
Is it a cousin of Broccoli? Looks very interesting. May not get it here in India. Like the recipe.
Ugh... I hate getting ripped off like that. But I can certainly understand being seduced by the color. Beautiful!
That is bit expensive cauliflower. But the recipe is worth the price.
That purple cauliflower is absolutely stunning. I hate to say it, but in my small corner of the world, $7 would be cheap for that. I love the way you cooked it too; making sure that the color still commands the show. Beautiful.
I love that color! Looks delicious!
Beautiful color and the addition of the coconut is magical!!
Really wonderful story, Kathy. The dish you made sounds wonderful. I'm a big fan of Indian food so may be trying this recipe very soon.
'Cauliwood'! Love it! I'm trying this tomorrow and I SO can't wait! Thanks Kathy!
i had to share this on fb...giggle...not only because of the story but because i LOVE you site header!


The Lemon Law varies by state. The main purpose of the Pennsylvania Lemon Law and the New Jersey Lemon Law is to provide car owners with a no cost method of forcing vehicle makers to repurchase defective vehicles. If the Lemon Law is found to have been violated, the manufacturer must buy the consumer's vehicle back and pay all of their attorney's fees. At Power & Associates, we take our lemon law cases on a no-cost, no-fee basis. We bear the fees and the court costs, win or lose.


text:
National Wireless Safety Alliance announces Board of Governors leadership appointments
In Daily News Briefs by Wireless Estimator December 5, 2018
The National Wireless Safety Alliance (NWSA) has announced that Jim Coleman, National Tower Safety Manager at AT&T, and Paul Roberts, Vice President of Compliance at American Tower Corporation, have been appointed to serve as Chairman and Vice Chairman respectively, of the organization's Board of Governors.
NWSA also announced that J. John Barker, Partner of Barker MacEntee PLLC, Richard Cullum, Director of Safety at Crown Castle, and Nick Wilkerson, Director of Safety at SBA Communications Corporation, have been added as new members of the Alliance's Board of Governors.
Additionally, NWSA announced that five incumbent Governors were recently ratified by the organization's Board of Directors to serve a new 5-year term through October 31, 2023. The reappointed Governors include Chris Mallon, TowerMRL, Inc, Kevin Schmidt, Sioux Falls Tower & Communications, Jose Tarafa, MasTec Network Solutions, Gary Trent, US Cellular and Jocko Vermillion, CITCA.
"NWSA is excited to have both Jim and Paul serve in their new leadership roles with the Board of Governors and we are also thrilled to add the talents of Jay, Richard and Nick as Governors," said Executive Director Duane MacEntee. "Additionally, the ratification of the five incumbent Governors to serve another 5-year term will help provide continuity at a critical time in order for NWSA to continue developing and offering our national, portable and independent worker certification programs," added MacEntee.
NWSA, headquartered in Fairfax, Virginia, is a national non-profit assessment and certification organization established to provide thorough, independent assessments of knowledge and skills and provide verifiable worker certification in order to enhance safety, reduce workplace risk, improve quality, encourage training, and recognize the skilled professionals who work on towers and other non-standard communication structures.
The NWSA Board of Governors consists of representatives from a broad cross-section of the industry and is tasked with developing policy and overseeing the activities of the various committees that will serve under their jurisdiction.
NWSA currently offers two industry-wide certification programs: Telecommunications Tower Technician 1 (TTT-1) and Telecommunications Tower Technician 2 (TTT-2). Additionally, the NWSA Telecommunication Tower Foreman certification is slated to be unveiled during the first quarter of 2019. This new certification will create a credentialing system for industry workers who supervise crews that work on communications structures, whether they are antenna and line crews, construction crews, or structural modification crews.
Other assessment and certification programs NWSA will likely unveil in the future include Rigging, Small Cell/DAS Technician, Structural Modifications, Gin Pole Operations and Broadcast Tall Tower Technician.
Industry workers, companies and stakeholders are encouraged to visit the NWSA website at www.nws-a.org to learn more about the organization and how to begin the process of obtaining certification.
Jim Coleman
Jim Coleman serves as the Vice President of the Tower Industry Family Support Charitable Foundation. He has over 40 years of experience working in the tower construction/maintenance industry and holds a General Radio License. Use of his expertise and knowledge has been sought by many attorneys as Jim has worked with various legal firms. He has been retained on numerous occasions as an expert witness for litigation procedures and counsel on tower safety issues.
Currently, Jim serves on NATE's OSHA Relations Committee. He has attended the United States Department of Labor Trainer Course in OSHA Standards for Construction and holds Certification for the 500, 501 and 502 Courses. Jim is an active member of the Society of Broadcast Engineers (SBE), a Professional Member of the American Society of Safety Professionals (ASSP) and a founding member of the Alabama Wireless Association (AWA). He is a member of the National Wireless Safety Alliance (NWSA) where he serves as Chairman of the Foreman Task Force Committee, as well as a member of the Telecommunications Industry Registered Apprenticeship Program (TIRAP) working group. Additionally, He served as a member of the A10.48 Communication Tower Committee developing the new tower standard, as well as serving as past committee member for the NATE/OSHA National Partnership.
In 2004, he was elected to serve on the Board of Directors for the National Association of Tower Erectors (NATE) and was elected by his peers to serve as Chairman of the Board from 2009 – 2013. Jim currently serves as the National Tower Safety Manager for AT&T.
Paul Roberts is the Vice President of Compliance for American Tower Corporation. In this role, Mr. Roberts guides the Environmental Compliance, FAA/FCC Regulatory Compliance, Safety and Health initiatives of the company as well as regulatory advocacy. Mr. Roberts is actively involved in advocacy efforts across all federal agencies that both regulate and support the telecommunications industry and has been a key voice in helping to shape rulemakings that affect us all. With 15 years managing telecom regulatory operations rooted in legal, systems safety and quality engineering principles, Mr. Roberts brings valuable insight and perspectives that will contribute to the NWSA mission.
J. John Barker
Mr. Barker has over twenty years of telecommunications industry experience having served in executive legal and risk management capacities at tower and construction companies and in the private practice of law. Mr. Barker has an extensive background in construction, safety, vendor management, and risk management. Mr. Barker holds a B.A. in Communications from the University of Central Florida and a J.D. from the Thomas M. Cooley Law School at Western Michigan University.
Richard Cullum
Richard Cullum is the Director of Safety for Crown Castle USA Inc. In his role, Mr. Cullum is responsible for developing standards related to increased worker safety and quality of tower maintenance and condition assessments, construction and maintenance repairs. Mr. Cullum has extensive field experience in tower construction, TIA (Telecommunications Industry Association) maintenance and condition assessments, tower and site engineering, wire rope safety climbs, climbing facilities, maintenance and repair and has worked in various aspects of the tower industry for the past twenty-eight years. Mr. Cullum is a licensed Professional Engineer, Certified Weld Inspector and holds General Contractor licenses in multiple states.
Nick Wilkerson
Nick Wilkerson is the Director of Safety for SBA Communications Corporation's domestic and international operations. He received a Bachelor's of Science degree in Fire & Safety Engineering with an emphasis in Risk Management from Eastern Kentucky University. He is Certified Safety Professional and has over 20 years of safety experience with 9 years in the tower/wireless industry.
Tags: American Tower, AT&T, Crown Castle, NWSA, SBA

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Engineerings
Experimental study and finite element simulation of deformation homogeneity between regions of commercially pure titanium deformed by ECAP
Vagner dos Anjos Costa Universidade Federal de Sergipe https://orcid.org/0000-0001-9162-6030
Késia Filadélfia Dionizio Silva Ramos Universidade Federal de Alagoas https://orcid.org/0000-0003-3514-5472
Wilton Walter Batista Universidade Federal de Sergipe https://orcid.org/0000-0001-6667-8947
Eduardo de Oliveira Santos Instituto Federal de Sergipe https://orcid.org/0000-0002-6834-629X
ECAP; Severe plastic deformation; Titanium; Finite elements; Homogeneity.
ECAP is a process of severe plastic deformation of a material, whose objective is to refine the grain size in the microstructure. The materials processed by ECAP show improvements in their mechanical properties. The process variables that affect the microstructure refinement are: processing route, die types, and number of passes. In the ECAP matrix used in the deformation process, the channel angle and the curvature angle determined the efficiency of the microstructural refinement. This work aims to analyze the deformation homogeneity through the mechanical processing of Ti CP via ECAP in an experimental way and by finite elements, associate the models for comparison between the levels of deformation in the external and internal regions with longitudinal section of the specimen. The Ti CP samples were deformed via ECAP in up to 8 passes, using route A, in a matrix with an intersection angle between the channels of Φ = 120º. Vickers microhardness measurements were performed at each pass to evaluate the changes caused for later association with the numerical simulation. The material was numerically simulated through the Abaqus modeling interface – 2020 version with educational license. The physical parameters were pre-established by recording the physical and mechanical variables in the software. The results were satisfactory in proving the association between the experimental and finite element studies, also indicating that there is a difference between the strain levels for the regions analyzed in both models.
Abd El Aal, M. I. (2017). 3D FEM simulations and experimental validation of plastic deformation of pure aluminum deformed by ECAP and combination of ECAP and direct extrusion. Transactions of Nonferrous Metals Society of China (English Edition), 27(6), 1338–1352. Scopus. https://doi.org/10.1016/S1003-6326(17)60155-9
Abd El Aal, M. I. (2021). Prediction of hardness distribution during SPD process based on FEM simulations: Case study of ECAP and HPT processes. Materials Research Express, 8(8). Scopus. https://doi.org/10.1088/2053-1591/ac1ec9
Adedokun, S. T. (2011). A Review on Equal Channel Angular Extrusion as a Deformation and Grain Refinement Process. Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS), 2, 360–363.
Alateyah, A. I., Ahmed, M. M. Z., Alawad, M. O., Elkatatny, S., Zedan, Y., Nassef, A., & El-Garaihy, W. H. (2022). Effect of ECAP die angle on the strain homogeneity, microstructural evolution, crystallographic texture and mechanical properties of pure magnesium: Numerical simulation and experimental approach. Journal of Materials Research and Technology, 17, 1491–1511. https://doi.org/10.1016/j.jmrt.2022.01.088
Alateyah, A. I., Ahmed, M. M. Z., Zedan, Y., El-Hafez, H. A., Alawad, M. O., & El-Garaihy, W. H. (2021). Experimental and numerical investigation of the ecap processed copper: Microstructural evolution, crystallographic texture and hardness homogeneity. Metals, 11(4). Scopus. https://doi.org/10.3390/met11040607
Awang Sh'ri, D. N., Abu Hassan, M. A. H., Zahari, Z. S., & Wan Harun, W. S. (2019). Finite element simulation of equal channel angular pressing: Effect of die angle and number of passes. International Journal of Automotive and Mechanical Engineering, 16(1), 6402–6414. Scopus. https://doi.org/10.15282/ijame.16.1.2019.22.0484
Banerjee, D., & Williams, J. C. (2013). Perspectives on Titanium Science and Technology. Acta Materialia, 61(3), 844–879. https://doi.org/10.1016/j.actamat.2012.10.043
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Ferrasse, S., Segal, V. M., & Alford, F. (2004). Texture evolution during equal channel angular extrusion (ECAE): Part II. An effect of post-deformation annealing. Materials Science and Engineering: A, 372(1), 235–244. https://doi.org/10.1016/j.msea.2003.12.043
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Huang, Z., Xiao, H., Yu, J., Zhang, H., Huang, H., Yu, K., & Zhou, R. (2022). Effects of Different Annealing Cooling Methods on the Microstructure and Properties of TA10 Titanium Alloys. Journal of Materials Research and Technology. https://doi.org/10.1016/j.jmrt.2022.04.149
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Su, C. W., Lu, L., & Lai, M. O. (2007). 3D finite element analysis on strain uniformity during ECAP process. Materials Science and Technology, 23(6), 727–735. https://doi.org/10.1179/174328407X179728
Valiev, R. Z., Estrin, Y., Horita, Z., Langdon, T. G., Zechetbauer, M. J., & Zhu, Y. T. (2006). Producing bulk ultrafine-grained materials by severe plastic deformation. JOM, 58(4), 33–39. https://doi.org/10.1007/s11837-006-0213-7
Valiev, R. Z., Islamgaliev, R. K., & Alexandrov, I. V. (2000). Bulk nanostructured materials from severe plastic deformation. Progress in Materials Science, 45(2), 103–189. https://doi.org/10.1016/S0079-6425(99)00007-9
Valiev, R. Z., & Langdon, T. G. (2006). Principles of equal-channel angular pressing as a processing tool for grain refinement. Progress in Materials Science, 51(7), 881–981. https://doi.org/10.1016/j.pmatsci.2006.02.003
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Wongsa-Ngam, J., Kawasaki, M., & Langdon, T. G. (2012). The development of hardness homogeneity in a Cu–Zr alloy processed by equal-channel angular pressing. Materials Science and Engineering: A, 556, 526–532. https://doi.org/10.1016/j.msea.2012.07.022
Wongsa-Ngam, J., Noraphaiphipaksa, N., Kanchanomai, C., & Langdon, T. (2021). Numerical Investigation of Plastic Strain Homogeneity During Equal-Channel Angular Pressing of a Cu-Zr Alloy. Crystals, 11, 1505. https://doi.org/10.3390/cryst11121505
Wu, H., Jiang, J., Liu, H., Sun, J., Gu, Y., Tang, R., Zhao, X., & Ma, A. (2017). Fabrication of an Ultra-Fine Grained Pure Titanium with High Strength and Good Ductility via ECAP plus Cold Rolling. Metals, 7(12), Art. 12. https://doi.org/10.3390/met7120563
Zhang, D., Osman, M., li, li, Zheng, Y., & Tong, Y. (2016). Simulation and Experimental Investigation for the Homogeneity of Ti49.2Ni50.8 Alloy Processed by Equal Channel Angular Pressing. Metals, 6, 45. https://doi.org/10.3390/met6030045
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COSTA, V. dos A. .; RAMOS, K. F. D. S. .; BATISTA, W. W. .; SANTOS, E. de O. Experimental study and finite element simulation of deformation homogeneity between regions of commercially pure titanium deformed by ECAP. Research, Society and Development, [S. l.], v. 11, n. 15, p. e241111537139, 2022. DOI: 10.33448/rsd-v11i15.37139. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/37139. Acesso em: 31 jan. 2023.
Copyright (c) 2022 Vagner dos Anjos Costa; Késia Filadélfia Dionizio Silva Ramos; Wilton Walter Batista; Eduardo de Oliveira Santos


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Kilmeen Drama Group
One Act Finals
Nightly Lineup
Confined Groups
Bailieborough Drama Group
Model Box Productions
Navan Theatre Group
New Ross Drama Workshop
Roscommon Drama Group
Open Groups
Coolgreany Amateur Dramatic Society
Corn Mill Theatre Group
Palace Players
Prosperous Dramatic Society
The Moat Club
Official Opening | Joanne Keane
Fringe Events
Officers and Committee Members
Adjudicator | Anna Walker
West Cork Drama Festival
Adjudicator | Paul Brennan
Previous Winners | Three Act Festival
Previous Winners | One Act Festival
ALL-IRELAND ONE ACT DRAMA FINALS 2019
Under the auspices of the ACDI & DLI
Carrigallen, County Leitrim
The tradition of drama in Carrigallen goes back to the late 1800's. The present group was founded in 1963 as The Community Players and there has been no break in activity since that time. The group has competed on the festival circuit since 1970 and has reached the All-Ireland Open Finals in Athlone on twenty three occasions. In 1989 the group opened their own theatre – The Corn Mill Theatre and Arts Centre. The group has won the All-Ireland Open Drama Finals in Athlone on three occasions – in 1998 with Belfry by Billy Roche, in 2005 with Stolen Child by Yvonne Quinn and Bairbre Ni Chaoimh and in 2014 with The Devil's Ceili by Philip Doherty & Kevin McGahern. The group also won the Abbey Theatre Award on two occasions in 2014 (The Devil's Ceili) and 2019 (On Broken Wings).
www.cornmilltheatre.com
Alice Smith Lynch
Annette: Taragh Donohoe
Donal: Larry O'Halloran
Gemma: Julie Ann McKiernan
Paul: Derek O'Reilly
Ronan Ward
Stage Manager: Neville Patterson
Lighting & Sound: Ronan Ward
Set Design & Construction: Loui Finnegan & Ronan Ward
Gemma and her husband Paul haven't seen Annette and her husband Donal since she quit her job a year ago. For good reasons. Gemma would like to keep it like that. However, when they bump into each other at another wedding, can they be civil or will mayhem ensue?
Alice studied Drama and Theatre in NUI Maynooth from 2008-2010 and completed a Masters in Drama and Theatre in UCD in 2011. Her first play, 'Katie's Wake' was shortlisted for the Cork Arts Theatre new writing awards and was produced under the direction of Tess Healy Maguire. She developed an interest in new writing and has mostly appeared in new plays including 'Dole Etiquette' by Catherine McKiernan in 2010, 'A Holy Show' by Padraig McIntyre in 2011 and 'The Mass Rock' by Tara Maria Lovett. Alice co-founded The Moogles Theatre Company in 2011 to produce and promote new writing by women. She wrote and directed 'Intentions' in 2015 and co-wrote 'Waiting for Grenville', directed by Phil Gilbride in 2016. In 2017, Alice was awarded 'Best New Playwright' at The All Ireland One Act Finals with 'Shooting Stars' which she also directed. She has also written a series of ten minute plays which have been performed during the Cootehill Arts Festival and the Cork Arts Theatre in 2018. In 2019, Alice performed with The Corn Mill Theatre award winning play 'On Broken Wings' by Dermot Healy. Her latest play, 'The Aftermath' will be performed by The Corn Mill Theatre Group on the One Act Circuit in 2019.
Mon – Closed
Tue – Closed
Wed – Closed
Thu – 12:00 pm – 7:00 pm
Fri – 12:00 pm – 7:00 pm
Sat – 12:00 pm – 7:00 pm
Sun – 12:00 pm – 7:00 pm
Rossmore Theatre, Rossmore, Clonakilty, County Cork, P85 TA48
info@rossmoretheatre.com
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Q: VAMT doesn't show clients waiting to activate until threshold reached? I'm trying to get the KMS on our network up past the 25+ activation threshold so that users don't freak out until we're finished deploying.  To that end, I'm setting up VMs on a vmware box.
When I type
cscript slmgr.exe /ato
on a 'new' vmware guest win7 ent client, it comes back and says cannot activate because count is insufficient.  This makes sense I guess.  However, if I go to our KMS server box and look at VAMT tools, shouldn't I at least see an entry for the client that I was trying to activate?
Thanks,

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