Input: What genre did Margaret Way write in?

Context:
Margaret Way (b. Brisbane d. Cleveland, Queensland, Australia ) was an Australian writer of romance novels and women's fiction. A prolific author, Way wrote more than 120 novels since 1970, many through Mills & Boon, a romance imprint of British publisher Harlequin UK Ltd., owned by Harlequin Enterprises.

Biography
Before her marriage, she was a well-known pianist, teacher, vocal coach and accompanist. She began writing when her son, Laurence Way, was born, a friend took a pile of Mills & Boon books to her, she read all and decided that she also could write these types of novels. She began to write and promote her country with her stories set in Australia. She sold her first novels in 1970. Margaret Way lives with her family in her native Brisbane. Beginning in 2013, Margaret began to self-publish, releasing her first "e-book" mid-July.

Margaret died on the 10th of August 2022 in Cleveland, Queensland.

Bibliography

Single Novels
King Country (1970)
Blaze of Silk (1970)
The Time of the Jacaranda (1970)
Bauhinia Junction (1971)
Man from Bahl Bahla (1971)
Summer Magic (1971)
Return to Belle Amber (1971)
Ring of Jade (1972)
Copper Moon (1972)
Rainbow Bird (1972)
Man Like Daintree (1972)
Noonfire (1972)
Storm Over Mandargi (1973)
Wind River (1973)
Love Theme (1974)
McCabe's Kingdom (1974)
Sweet Sundown (1974)
Reeds of Honey (1975)
Storm Flower (1975)
Lesson in Loving (1975)
Flight into Yesterday (1976)
Red Cliffs of Malpara (1976)
Man on Half-moon (1976)
Swan's Reach (1976)
Mutiny in Paradise (1977)
One Way Ticket (1977)
Portrait of Jaime (1977)
Black Ingo (1977)
Awakening Flame (1978)
Wild Swan (1978)
Ring of Fire (1978)
Wake the Sleeping Tiger (1978)
Valley of the Moon (1979)
White Magnolia (1979)
Winds of Heaven (1979)
Blue Lotus (1979)
Butterfly and the Baron (1979)
Golden Puma (1980)
Temple of Fire (1980)
Lord of the High Valley (1980)
Flamingo Park (1980)
North of Capricorn (1981)
Season for Change (1981)
Shadow Dance (1981)
McIvor Affair (1981)
Home to Morning Star (1981)
Broken Rhapsody (1982)
The Silver Veil (1982)
Spellbound (1982)
Hunter's Moon (1982)
Girl at Cobalt Creek (1983)
No Alternative (1983)
House of Memories (1983)
Almost a Stranger (1984)
A place called Rambulara (1984)
Fallen Idol (1984)
Hunt the Sun (1985)
Eagle's Ridge (1985)
The Tiger's Cage (1986)
Innocent in Eden (1986)
Diamond Valley (1986)
Morning Glory (1988)
Devil Moon (1988)
Mowana Magic (1988)
Hungry Heart (1988)
Rise of an Eagle (1988)
One Fateful Summer (1993)
The Carradine Brand (1994)
Holding on to Alex (1997)
The Australian Heiress (1997)
Claiming His Child (1999)
The Cattleman's Bride (2000)
The Cattle Baron (2001)
The Husbands of the Outback (2001)
Secrets of the Outback (2002)
With This Ring (2003)
Innocent Mistress (2004)
Cattle Rancher, Convenient Wife (2007)
Outback Marriages (2007)
Promoted: Nanny to Wife (2007)
Cattle Rancher, Secret Son (2007)
Genni's Dilemma (2008)
Bride At Briar Ridge (2009)
Outback Heiress, Surprise Proposal (2009)
Cattle Baron, Nanny Needed (2009)

Legends of the Outback Series
Mail Order Marriage (1999)
The Bridesmaid's Wedding (2000)
The English Bride (2000)
A Wife at Kimbara (2000)

Koomera Crossing Series
Sarah's Baby (2003)
Runaway Wife (2003)
Outback Bridegroom (2003)
Outback Surrender (2003)
Home to Eden (2004)

McIvor Sisters Series
The Outback Engagement (2005)
Marriage at Murraree (2005)

Men Of The Outback Series
The Cattleman (2006)
The Cattle Baron's Bride (2006)
Her Outback Protector (2006)
The Horseman (2006)

Outback Marriages Series
Outback Man Seeks Wife (2007)
Cattle Rancher, Convenient Wife (2007)

Barons of the Outback Series Multi-Author
Wedding At Wangaree Valley (2008)
Bride At Briar's Ridge (2008)

Family Ties Multi-Author
Once Burned (1995)

Hitched! Multi-Author
A Faulkner Possession (1996)

Simply the Best Multi-Author
Georgia and the Tycoon (1997)

The Big Event Multi-Author
Beresford's Bride (1998)

Guardian Angels Multi-Author
Gabriel's Mission (1998)

Australians Series Multi-Author
7. Her Outback Man (1998)
17. Master of Maramba (2001)
19. Outback Fire (2001)
22. Mistaken Mistress (2002)
24. Outback Angel (2002)
33. The Australian Tycoon's Proposal (2004)
35. His Heiress Wife (2004)

Marrying the Boss Series Multi-Author
Boardroom Proposal (1999)

Contract Brides Series Multi-Author
Strategy for Marriage (2002)

Everlasting Love Series Multi-Author
Hidden Legacy (2008)

Diamond Brides Series Multi-Author
The Australian's Society Bride (2008)

Collections
Summer Magic / Ring of Jade / Noonfire (1981)
Wife at Kimbara / Bridesmaid's Wedding (2005)

Omnibus in Collaboration
Pretty Witch / Without Any Amazement / Storm Over Mandargi (1977) (with Lucy Gillen and Margaret Malcolm)
Dear Caliban / Heart of the Eagle / Swans' Reach (1978) (with Jane Donnelly and Elizabeth Graham)
The Bonds of Matrimony / Dragon Island / Reeds of Honey (1979) (with Elizabeth Hunter and Henrietta Reid)
The Man Outside / Castles in Spain / McCabe's Kingdom (1979) (with Jane Donnelly and Rebecca Stratton)
Winds From The Sea / Island of Darkness / Wind River (1979) (with Margaret Pargeter and Rebecca Stratton)
Moorland Magic / Tree of Idleness / Sweet Sundown (1980) (with Elizabeth Ashton and Elizabeth Hunter)
The Shifting Sands / Portrait of Jaime / Touched by Fire (1982) (with Jane Donnelly and Kay Thorpe)
Head of Chancery / Wild Heart / One-Way Ticket (1986) (with Betty Beaty and Doris Smith)
Heart of the Scorpion / The Winds of Heaven / Sweet Compulsion (1987) (with Janice Gray and Victoria Woolf)
One Brief Sweet Hour / Once More With Feeling / Blue Lotus (1990) (with Jane Arbor and Natalie Sparks)
Marry Me Cowboy (1995) (with Janet Dailey, Susan Fox and Anne McAllister)
Husbands on Horseback (1996) (with Diana Palmer)
Wedlocked (1999) (with Day Leclaire and Anne McAllister)
Mistletoe Magic (1999) (with Betty Neels and Rebecca Winters)
The Australians (2000) (with Helen Bianchin and Miranda Lee)
Weddings Down Under (2001) (with Helen Bianchin and Jessica Hart)
Outback Husbands (2002) (with Marion Lennox)
The Mother's Day Collection (2002) (with Helen Dickson and Kate Hoffmann)
Australian Nights (2003) (with Miranda Lee)
Outback Weddings (2003) (with Barbara Hannay)
Australian Playboys (2003) (with Helen Bianchin and Marion Lennox)
Australian Tycoons (2004) (with Emma Darcy and Marion Lennox)
A Mother's Day Gift (2004) (with Anne Ashley and Lucy Monroe)
White Wedding (2004) (with Judy Christenberry and Jessica Steele)
A Christmas Engagement (2004) (with Sara Craven and Jessica Matthews)
A Very Special Mother's Day (2005) (with Anne Herries)
All I Want for Christmas... (2005) (with Betty Neels and Jessica Steele)
The Mills and Boon Collection (2006) (with Caroline Anderson and Penny Jordan)
Outback Desire (2006) (with Emma Darcy and Carol Marinelli)
To Mum, with Love (2006) (with Rebecca Winters)
Australian Heroes (2007) (with Marion Lennox and Fiona McArthur)
Tall, Dark and Sexy (2008) (with Caroline Anderson and Helen Bianchin)
The Boss's Proposal (2008) (with Jessica Steele and Patricia Thayer)
Island Heat / Outback Man Seeks Wife / Prince's Forbidden Virgin / One Night Before Marriage / Their Lost-and-found Family / Single Dad's Marriage Wish (2008) (with Robyn Donald, Marion Lennox, Carol Marinelli, Sarah Mayberry and Anne Oliver)
Australian Billionaires (2009) (with Jennie Adams and Amy Andrews)
Cattle Baron : Nanny Needed / Bachelor Dad on Her Doorstep (2009) (with Michelle Douglas)

External links
Margaret Way at Harlequin Enterprises Ltd

Australian romantic fiction writers
Australian women novelists
Living people
Year of birth missing (living people)
Women romantic fiction writers

Answer: Romance novels and women's fiction.


Input: What are the datasets used in this community for research?

Context:
\section{Introduction}
Underwater robot picking is to use the robot to automatically capture sea creatures like holothurian, echinus, scallop, or starfish in an open-sea farm where underwater object detection is the key technology for locating creatures. Until now, the datasets used in this community are released by the Underwater Robot Professional Contest (URPC$\protect\footnote{Underwater Robot Professional Contest: {\bf http://en.cnurpc.org}.}$) beginning from 2017, in which URPC2017 and URPC2018 are most often used for research. Unfortunately, as the information listed in Table \ref{Info}, URPC series datasets do not provide the annotation file of the test set and cannot be downloaded after the contest.
Therefore, researchers \cite{2020arXiv200511552C,2019arXiv191103029L} first have to divide the training data into two subsets, including a new subset of training data and a new subset of testing data, and then train their proposed method and other \emph{SOTA} methods. On the one hand, training other methods results in a significant increase in workload. On the other hand, different researchers divide different datasets in different ways,
\begin{table}[t]
\renewcommand\tabcolsep{3.5pt}
\caption{Information about all the collected datasets. * denotes the test set's annotations are not available. \emph{3} in Class means three types of creatures are labeled, \emph{i.e.,} holothurian, echinus, and scallop. \emph{4} means four types of creatures are labeled (starfish added). Retention represents the proportion of images that retain after similar images have been removed.}
\centering
\begin{tabular}{|l|c|c|c|c|c|}
\hline
Dataset&Train&Test&Class&Retention&Year \\
\hline
URPC2017&17,655&985*&3&15\%&2017 \\
\hline
URPC2018&2,901&800*&4&99\%&2018 \\
\hline
URPC2019&4,757&1,029*&4&86\%&2019 \\
\hline
URPC2020$_{ZJ}$&5,543&2,000*&4&82\%&2020 \\
\hline
URPC2020$_{DL}$&6,575&2,400*&4&80\%&2020 \\
\hline
UDD&1,827&400&3&84\%&2020 \\
\hline

\end{tabular}
\label{Info}
\end{table}
\begin{figure*}[htbp]
\begin{center}
\includegraphics[width=1\linewidth]{example.pdf}
\end{center}
   \caption{Examples in DUO, which show a variety of scenarios in underwater environments.}
\label{exam}
\end{figure*}
causing there is no unified benchmark to compare the performance of different algorithms.
In terms of the content of the dataset images, there are a large number of similar or duplicate images in the URPC datasets. URPC2017 only retains 15\% images after removing similar images compared to other datasets. Thus the detector trained on URPC2017 is easy to overfit and cannot reflect the real performance.
For other URPC datasets, the latter also includes images from the former, \emph{e.g.}, URPC2019 adds 2,000 new images compared to URPC2018; compared with URPC2019, URPC2020$_{ZJ}$ adds 800 new images. The URPC2020$_{DL}$ adds 1,000 new images compared to the URPC2020$_{ZJ}$. It is worth mentioning that the annotation of all datasets is incomplete; some datasets lack the starfish labels and it is easy to find error or missing labels. \cite{DBLP:conf/iclr/ZhangBHRV17} pointed out that although the CNN model has a strong fitting ability for any dataset, the existence of dirty data will significantly weaken its robustness.
Therefore, a reasonable dataset (containing a small number of similar images as well as an accurate annotation) and a corresponding recognized benchmark are urgently needed to promote community development.

To address these issues, we introduce a dataset called Detecting Underwater Objects (DUO) by collecting and re-annotating all the available underwater datasets. It contains 7,782 underwater images after deleting overly similar images and has a more accurate annotation with four types of classes (\emph{i.e.,} holothurian, echinus, scallop, and starfish).
Besides, based on the MMDetection$\protect\footnote{MMDetection is an open source object detection toolbox based on PyTorch. {\bf https://github.com/open-mmlab/mmdetection}}$ \cite{chen2019mmdetection} framework, we also provide a \emph{SOTA} detector benchmark containing efficiency and accuracy indicators, providing a reference for both academic research and industrial applications. It is worth noting that JETSON AGX XAVIER$\protect\footnote{JETSON AGX XAVIER is an embedded development board produced by NVIDIA which could be deployed in an underwater robot. Please refer {\bf https://developer.nvidia.com/embedded/jetson-agx-xavier-developer-kit} for more information.}$ was used to assess all the detectors in the efficiency test in order to simulate robot-embedded environment. DUO will be released in https://github.com/chongweiliu soon.

In summary, the contributions of this paper can be listed as follows.

  $\bullet$ By collecting and re-annotating all relevant datasets, we introduce a dataset called DUO with more reasonable annotations as well as a variety of underwater scenes.

  $\bullet$ We provide a corresponding benchmark of \emph{SOTA} detectors on DUO including efficiency and accuracy indicators which could be a reference for both academic research and industrial applications.

\pagestyle{empty}
\section{Background}
In the year of 2017, underwater object detection for open-sea farming is first proposed in the target recognition track of Underwater Robot Picking Contest 2017$\protect\footnote{From 2020, the name has been changed into Underwater Robot Professional Contest which is also short for URPC.}$ (URPC2017) which aims to promote the development of theory, technology, and industry of the underwater agile robot and fill the blank of the grabbing task of the underwater agile robot. The competition sets up a target recognition track, a fixed-point grasping track, and an autonomous grasping track. The target recognition track concentrates on finding the {\bf high accuracy and efficiency} algorithm which could be used in an underwater robot for automatically grasping.

The datasets we used to generate the DUO are listed below. The detailed information has been shown in Table \ref{Info}.

  {\bf URPC2017}: It contains 17,655 images for training and 985 images for testing and the resolution of all the images is 720$\times$405. All the images are taken from 6 videos at an interval of 10 frames. However, all the videos were filmed in an artificial simulated environment and pictures from the same video look almost identical.

   {\bf URPC2018}: It contains 2,901 images for training and 800 images for testing and the resolutions of the images are 586$\times$480, 704$\times$576, 720$\times$405, and 1,920$\times$1,080. The test set's annotations are not available. Besides, some images were also collected from an artificial underwater environment.

  {\bf URPC2019}: It contains 4,757 images for training and 1029 images for testing and the highest resolution of the images is 3,840$\times$2,160 captured by a GOPro camera. The test set's annotations are also not available and it contains images from the former contests.

  {\bf URPC2020$_{ZJ}$}: From 2020, the URPC will be held twice a year. It was held first in Zhanjiang, China, in April and then in Dalian, China, in August. URPC2020$_{ZJ}$ means the dataset released in the first URPC2020 and URPC2020$_{DL}$ means the dataset released in the second URPC2020. This dataset contains 5,543 images for training and 2,000 images for testing and the highest resolution of the images is 3,840$\times$2,160. The test set's annotations are also not available.

  {\bf URPC2020$_{DL}$}: This dataset contains 6,575 images for training and 2,400 images for testing and the highest resolution of the images is 3,840$\times$2,160. The test set's annotations are also not available.

  {\bf UDD \cite{2020arXiv200301446W}}: This dataset contains 1,827 images for training and 400 images for testing and the highest resolution of the images is 3,840$\times$2,160. All the images are captured by a diver and a robot in a real open-sea farm.

\begin{figure}[t]
\begin{center}
\includegraphics[width=1\linewidth]{pie.pdf}
\end{center}
   \caption{The proportion distribution of the objects in DUO.}
\label{pie}
\end{figure}

\begin{figure*}
  \centering
  \subfigure[]{\includegraphics[width=3.45in]{imagesize.pdf}}
  \subfigure[]{\includegraphics[width=3.45in]{numInstance.pdf}}
  \caption{(a) The distribution of instance sizes for DUO; (b) The number of categories per image.}
  \label{sum}
\end{figure*}
\section{Proposed Dataset}

\subsection{Image Deduplicating}
As we explained in Section 1, there are a large number of similar or repeated images in the series of URPC datasets. Therefore, it is important to delete duplicate or overly similar images and keep a variety of underwater scenarios when we merge these datasets together. Here we employ the Perceptual Hash algorithm (PHash) to remove those images. PHash has the special property that the hash value is dependent on the image content, and it remains approximately the same if the content is not significantly modified. Thus we can easily distinguish different scenarios and delete duplicate images within one scenario.

After deduplicating, we obtain 7,782 images (6,671 images for training; 1,111 for testing). The retention rate of the new dataset is 95\%, which means that there are only a few similar images in the new dataset. Figure \ref{exam} shows that our dataset also retains various underwater scenes.

\subsection{Image Re-annotation}
Due to the small size of objects and the blur underwater environment, there are always missing or wrong labels in the existing annotation files. In addition, some test sets' annotation files are not available and some datasets do not have the starfish annotation. In order to address these issues, we follow the next process which combines a CNN model and manual annotation to re-annotate these images. Specifically, we first train a detector (\emph{i.e.,} GFL \cite{li2020generalized}) with the originally labeled images. After that, the trained detector predicts all the 7,782 images. We treat the prediction as the groundtruth and use it to train the GFL again. We get the final GFL prediction called {\bf the coarse annotation}. Next, we use manual correction to get the final annotation called {\bf the fine annotation}. Notably, we adopt the COCO \cite{Belongie2014} annotation form as the final format.
\subsection{Dataset Statistics}
{\bf The proportion of classes}: The total number of objects is 74,515. Holothurian, echinus, scallop, and starfish are 7,887, 50,156, 1,924, and 14,548, respectively. Figure \ref{pie} shows the proportion of each creatures where echinus accounts for 67.3\% of the total. The whole data distribution shows an obvious long-tail distribution because the different economic benefits of different seafoods determine the different breed quantities.

{\bf The distribution of instance sizes}: Figure \ref{sum}(a) shows an instance size distribution of DUO. \emph{Percent of image size} represents the ratio of object area to image area, and \emph{Percent of instance} represents the ratio of the corresponding number of objects to the total number of objects. Because of these small creatures and high-resolution images, the vast majority of objects occupy 0.3\% to 1.5\% of the image area.

{\bf The instance number per image}: Figure \ref{sum}(b) illustrates the number of categories per image for DUO. \emph{Number of instances} represents the number of objects one image has, and \emph{ Percentage of images} represents the ratio of the corresponding number of images to the total number of images. Most images contain between 5 and 15 instances, with an average of 9.57 instances per image.

{\bf Summary}:
In general, smaller objects are harder to detect. For PASCAL VOC \cite{Everingham2007The} or COCO \cite{Belongie2014}, roughly 50\% of all objects occupy no more than 10\% of the image itself, and others evenly occupy from 10\% to 100\%.
In the aspect of instances number per image, COCO contains 7.7 instances per image and VOC contains 3. In comparison, DUO has 9.57 instances per image and most instances less than 1.5\% of the image size.
Therefore, DUO contains almost exclusively massive small instances and has the long-tail distribution at the same time, which means it is promising to design a detector to deal with massive small objects and stay high efficiency at the same time for underwater robot picking.

\section{Benchmark}
Because the aim of underwater object detection for robot picking is to find {\bf the high accuracy and efficiency} algorithm, we consider both the accuracy and efficiency evaluations in the benchmark as shown in Table \ref{ben}.

\subsection{Evaluation Metrics}
Here we adopt the standard COCO metrics (mean average precision, \emph{i.e.,} mAP) for the accuracy evaluation and also provide the mAP of each class due to the long-tail distribution.

{\bf AP} -- mAP at IoU=0.50:0.05:0.95.

{\bf AP$_{50}$} --  mAP at IoU=0.50.

{\bf AP$_{75}$} --  mAP at IoU=0.75.

{\bf AP$_{S}$} --   {\bf AP} for small objects of area smaller than 32$^{2}$.

{\bf AP$_{M}$} --   {\bf AP} for objects of area between 32$^{2}$ and 96$^{2}$.

{\bf AP$_{L}$} --   {\bf AP} for large objects of area bigger than 96$^{2}$.

{\bf AP$_{Ho}$} --  {\bf AP} in holothurian.

{\bf AP$_{Ec}$} --  {\bf AP} in echinus.

{\bf AP$_{Sc}$} --  {\bf AP} in scallop.

{\bf AP$_{St}$} --  {\bf AP} in starfish.

For the efficiency evaluation, we provide three metrics:

{\bf Param.} --  The parameters of a detector.

{\bf FLOPs} --  Floating-point operations per second.

{\bf FPS} --  Frames per second.

Notably, {\bf FLOPs} is calculated under the 512$\times$512 input image size and {\bf FPS} is tested on a JETSON AGX XAVIER under MODE$\_$30W$\_$ALL.

\subsection{Standard Training Configuration}
We follow a widely used open-source toolbox, \emph{i.e.,} MMDetection (V2.5.0) to produce up our benchmark. During the training, the standard configurations are as follows:

  $\bullet$ We initialize the backbone models (\emph{e.g.,} ResNet50) with pre-trained parameters on ImageNet \cite{Deng2009ImageNet}.

  $\bullet$ We resize each image into 512 $\times$ 512 pixels both in training and testing. Each image is flipped horizontally with 0.5 probability during training.

  $\bullet$ We normalize RGB channels by subtracting 123.675, 116.28, 103.53 and dividing by 58.395, 57.12, 57.375, respectively.

  $\bullet$ SGD method is adopted to optimize the model. The initial learning rate is set to be 0.005 in a single GTX 1080Ti with batchsize 4 and is decreased by 0.1 at the 8th and 11th epoch, respectively. WarmUp \cite{2019arXiv190307071L} is also employed in the first 500 iterations. Totally there are 12 training epochs.

  $\bullet$ Testing time augmentation (\emph{i.e.,} flipping test or multi-scale testing) is not employed.

\subsection{Benchmark Analysis}
Table \ref{ben} shows the benchmark for the \emph{SOTA} methods. Multi- and one- stage detectors with three kinds of backbones (\emph{i.e.,} ResNet18, 50, 101) give a comprehensive assessment on DUO. We also deploy all the methods to AGX to assess efficiency.

In general, the multi-stage (Cascade R-CNN) detectors have high accuracy and low efficiency, while the one-stage (RetinaNet) detectors have low accuracy and high efficiency. However, due to recent studies \cite{zhang2019bridging} on the allocation of more reasonable positive and negative samples in training, one-stage detectors (ATSS or GFL) can achieve both high accuracy and high efficiency.

\begin{table*}[htbp]
\renewcommand\tabcolsep{3.0pt}

\begin{center}
\caption{Benchmark of \emph{SOTA} detectors (single-model and single-scale results) on DUO. FPS is measured on the same machine with a JETSON AGX XAVIER under the same MMDetection framework, using a batch size of 1 whenever possible. R: ResNet.}
\label{ben}
\begin{tabular}{|l|l|c|c|c|ccc|ccc|cccc|}
\hline
Method&Backbone&Param.&FLOPs&FPS&AP&AP$_{50}$&AP$_{75}$&AP$_{S}$&AP$_{M}$&AP$_{L}$&AP$_{Ho}$&AP$_{Ec}$&AP$_{Sc}$&AP$_{St}$ \\
\hline
\emph{multi-stage:} &&&&&&&&&&&&&& \\

\multirow{3}{*}{Faster R-CNN \cite{Ren2015Faster}}
&R-18&28.14M&49.75G&5.7&50.1&72.6&57.8&42.9&51.9&48.7&49.1&60.1&31.6&59.7\\
&R-50&41.14M&63.26G&4.7&54.8&75.9&63.1&53.0&56.2&53.8&55.5&62.4&38.7&62.5\\
&R-101&60.13M&82.74G&3.7&53.8&75.4&61.6&39.0&55.2&52.8&54.3&62.0&38.5&60.4\\
\hline

\multirow{3}{*}{Cascade R-CNN \cite{Cai_2019}}
&R-18&55.93M&77.54G&3.4&52.7&73.4&60.3&\bf 49.0&54.7&50.9&51.4&62.3&34.9&62.3\\
&R-50&68.94M&91.06G&3.0&55.6&75.5&63.8&44.9&57.4&54.4&56.8&63.6&38.7&63.5\\
&R-101&87.93M&110.53G&2.6&56.0&76.1&63.6&51.2&57.5&54.7&56.2&63.9&41.3&62.6\\
\hline

\multirow{3}{*}{Grid R-CNN \cite{lu2019grid}}
&R-18&51.24M&163.15G&3.9&51.9&72.1&59.2&40.4&54.2&50.1&50.7&61.8&33.3&61.9\\
&R-50&64.24M&176.67G&3.4&55.9&75.8&64.3&40.9&57.5&54.8&56.7&62.9&39.5&64.4\\
&R-101&83.24M&196.14G&2.8&55.6&75.6&62.9&45.6&57.1&54.5&55.5&62.9&41.0&62.9\\
\hline

\multirow{3}{*}{RepPoints \cite{yang2019reppoints}}
&R-18&20.11M&\bf 35.60G&5.6&51.7&76.9&57.8&43.8&54.0&49.7&50.8&63.3&33.6&59.2\\
&R-50&36.60M&48.54G&4.8&56.0&80.2&63.1&40.8&58.5&53.7&56.7&65.7&39.3&62.3\\
&R-101&55.60M&68.02G&3.8&55.4&79.0&62.6&42.2&57.3&53.9&56.0&65.8&39.0&60.9\\
\hline
\hline
\emph{one-stage:} &&&&&&&&&&&&&& \\
\multirow{3}{*}{RetinaNet \cite{Lin2017Focal}}
&R-18&19.68M&39.68G&7.1&44.7&66.3&50.7&29.3&47.6&42.5&46.9&54.2&23.9&53.8\\
&R-50&36.17M&52.62G&5.9&49.3&70.3&55.4&36.5&51.9&47.6&54.4&56.6&27.8&58.3\\
&R-101&55.16M&72.10G&4.5&50.4&71.7&57.3&34.6&52.8&49.0&54.6&57.0&33.7&56.3\\
\hline

\multirow{3}{*}{FreeAnchor \cite{2019arXiv190902466Z}}
&R-18&19.68M&39.68G&6.8&49.0&71.9&55.3&38.6&51.7&46.7&47.2&62.8&28.6&57.6\\
&R-50&36.17M&52.62G&5.8&54.4&76.6&62.5&38.1&55.7&53.4&55.3&65.2&35.3&61.8\\
&R-101&55.16M&72.10G&4.4&54.6&76.9&62.9&36.5&56.5&52.9&54.0&65.1&38.4&60.7\\
\hline

\multirow{3}{*}{FoveaBox \cite{DBLP:journals/corr/abs-1904-03797}}
&R-18&21.20M&44.75G&6.7&51.6&74.9&57.4&40.0&53.6&49.8&51.0&61.9&34.6&59.1\\
&R-50&37.69M&57.69G&5.5&55.3&77.8&62.3&44.7&57.4&53.4&57.9&64.2&36.4&62.8\\
&R-101&56.68M&77.16G&4.2&54.7&77.3&62.3&37.7&57.1&52.4&55.3&63.6&38.9&60.8\\
\hline

\multirow{3}{*}{PAA \cite{2020arXiv200708103K}}
&R-18&\bf 18.94M&38.84G&3.0&52.6&75.3&58.8&41.3&55.1&50.2&49.9&64.6&35.6&60.5\\
&R-50&31.89M&51.55G&2.9&56.8&79.0&63.8&38.9&58.9&54.9&56.5&66.9&39.9&64.0\\
&R-101&50.89M&71.03G&2.4&56.5&78.5&63.7&40.9&58.7&54.5&55.8&66.5&42.0&61.6\\
\hline

\multirow{3}{*}{FSAF \cite{zhu2019feature}}
&R-18&19.53M&38.88G&\bf 7.4&49.6&74.3&55.1&43.4&51.8&47.5&45.5&63.5&30.3&58.9\\
&R-50&36.02M&51.82G&6.0&54.9&79.3&62.1&46.2&56.7&53.3&53.7&66.4&36.8&62.5\\
&R-101&55.01M&55.01G&4.5&54.6&78.7&61.9&46.0&57.1&52.2&53.0&66.3&38.2&61.1\\
\hline

\multirow{3}{*}{FCOS \cite{DBLP:journals/corr/abs-1904-01355}}
&R-18&\bf 18.94M&38.84G&6.5&48.4&72.8&53.7&30.7&50.9&46.3&46.5&61.5&29.1&56.6\\
&R-50&31.84M&50.34G&5.4&53.0&77.1&59.9&39.7&55.6&50.5&52.3&64.5&35.2&60.0\\
&R-101&50.78M&69.81G&4.2&53.2&77.3&60.1&43.4&55.4&51.2&51.7&64.1&38.5&58.5\\
\hline

\multirow{3}{*}{ATSS \cite{zhang2019bridging}}
&R-18&\bf 18.94M&38.84G&6.0&54.0&76.5&60.9&44.1&56.6&51.4&52.6&65.5&35.8&61.9\\
&R-50&31.89M&51.55G&5.2&58.2&\bf 80.1&66.5&43.9&60.6&55.9&\bf 58.6&67.6&41.8&64.6\\
&R-101&50.89M&71.03G&3.8&57.6&79.4&65.3&46.5&60.3&55.0&57.7&67.2&42.6&62.9\\
\hline

\multirow{3}{*}{GFL \cite{li2020generalized}}
&R-18&19.09M&39.63G&6.3&54.4&75.5&61.9&35.0&57.1&51.8&51.8&66.9&36.5&62.5\\
&R-50&32.04M&52.35G&5.5&\bf 58.6&79.3&\bf 66.7&46.5&\bf 61.6&55.6&\bf 58.6&\bf 69.1&41.3&\bf 65.3\\
&R-101&51.03M&71.82G&4.1&58.3&79.3&65.5&45.1&60.5&\bf 56.3&57.0&\bf 69.1&\bf 43.0&64.0\\

\hline
\end{tabular}
\end{center}
\end{table*}
Therefore, in terms of accuracy, the accuracy difference between the multi- and the one- stage methods in AP is not obvious, and the AP$_{S}$ of different methods is always the lowest among the three size AP. For class AP, AP$_{Sc}$ lags significantly behind the other three classes because it has the smallest number of instances. In terms of efficiency, large parameters and FLOPs result in low FPS on AGX, with a maximum FPS of 7.4, which is hardly deployable on underwater robot. Finally, we also found that ResNet101 was not significantly improved over ResNet50, which means that a very deep network may not be useful for detecting small creatures in underwater scenarios.

Consequently, the design of high accuracy and high efficiency detector is still the main direction in this field and there is still large space to improve the performance.
In order to achieve this goal, a shallow backbone with strong multi-scale feature fusion ability can be proposed to extract the discriminant features of small scale aquatic organisms; a specially designed training strategy may overcome the DUO's long-tail distribution, such as a more reasonable positive/negative label sampling mechanism or a class-balanced image allocation strategy within a training batch.

\section{Conclusion}
In this paper, we introduce a dataset (DUO) and a corresponding benchmark to fill in the gaps in the community. DUO contains a variety of underwater scenes and more reasonable annotations. Benchmark includes efficiency and accuracy indicators to conduct a comprehensive evaluation of the \emph{SOTA} decoders. The two contributions could serve as a reference for academic research and industrial applications, as well as promote community development.
\bibliographystyle{IEEEbib}

Answer: URPC2017, URPC2018, URPC2019, URPC2020_ZJ and URPC2020_DL.


Input: Is there any evidence of heaven and hell?

Context:
LOL Anonymous I'm here! & I did answer you back there.
kl el kotb el qadema (tawrat + enjel + 9o7f ibrahem) 7orfat w t'3ayarat.. law ma 9ar hal shy chan ma 6ala3 ktab yded ye;3y elly gablah l7ad ma 6ala3 lna el quraan b norah elly allah 7f'6ah don ta7ref w tabdel ela yom el dein .. shlon tyeeb Joan shy ma5ooth 5erah?!
1- Imagine you have two individuals. One truly believes in God but he is a bad husband and father who cheats on his wife and neglects his children. The other man is a nonbeliever; he accepts religion in theory and doctrine but simply does not have faith no matter how hard he tried. He is a good father and a good husband as well. When they stand before God at the Day of Judgment, would the nonbeliever be condemned to eternal hell only for that one flaw in him? Don't the other good traits in that person matter at all? Does being a nonbeliever equal being evil?
2-God knows everything. However, why would He have created when He knows exactly what each person is going to do and where they will end up? For example, let us suppose that tomorrow I will murder someone. God knows that I will do that. And He knows that I will suffer in hell when the time comes. So why does He purposely inflict that pain on me? To teach me a lesson? He knows the outcome of everything and everyone He has created.
3-Since you brought up science in the previous comments section, I am seriously curious (I am not trying to be glib) about dinosaurs and prehistoric humans. We have seen the evolution of humans and we have fossils and hard evidence of it. The science world has traced back "Eve" to Africa. The concept of Adam and Eve seems too mythological to be 100% factual. It has the same tone of Greek and Ancient Egyptian legends.
-Note: I am not trying to corner you here, I just want to know your response to my queries and thoughts. Thanks.
_ ولماذا نصلى ولمن نصلى .. انى لا ارى لصلاتكم هذه اى حكمه ولماذا كل تلك الحركات اما كان يكفى الخشوع..
اعتقد ان المشكلة ليست كما ذكرت..فما ذكرته يعني ان هناك العديد من المسائل الفقهية المتصلة بالعصر الجديد دون حل. على العكس, فالحلال بين والحرام بين. اعتقد المشكلة تكمن بالمسلمين الذين اصابهم الوهن.
You'll be answerd personaly only if; you comment with your blogger's name/nick.
I answered you before & there was no response from your behalf. Why would you think you're worth an answer from me since you can seek answers from good books?
Your questions are very simple, with clean cut answers. Don't use the word corner; it indicates things you don't have the first alphabet for!
Religion was established to calm our fears from the unknown. Freud did write about it in the father figure argument. Try to read it.
I deleted my last comment because in the end of it I inserted some thing that may offend some people (if you read it, I gauss you know what I mean). Abraham did not believe in God until he saw the birds come to life. So, all what I want is a single prove similar to Abraham.
I indeed busy doing my homework; I have to solve the energy equation and the continuity equation to come with another, hopefully, exact solution to the problem.
Do you work? I mean do you have a job, it seems that you are always on line!!!???? It is amazing how some one would stick to the internet. Try to go out more often, play sport or find any other hobby. If you could not disattach yourself from the internet try and seek a professional help… :-). Honestly, I’m not making fun of you it is just an advice… sincere advice.
I measure prosperity of a nation by the degree of its civilization in comparison to others of its time. Islamic civilization was at the peak during the Umayyad and Abbasid reigns, at the time when Moslems conquered other nations and dying civilizations, and mixed with them, and the new comers in Islam started researching for the truth. In their quest they translated Greek philosophy books and dug into ancient ones. Their search for truth led them to the emergence of chemistry, Algebra and other sciences And their findings excelled them in innovative inventions. The maps and astrolabes that Columbus used to sail on his quest to discover the West years later were taken from the Arabs. And in contrary to the scribbles of their holy book, Arabic books were the first that brought the roundedness of earth to world attention. Arabic language romanticized the rigid Latin, poetry and verse advanced. At one time, civilization was dubbed as Arabization in Andalusia and that was evident in Andalusia’s Christian and Jewish ancient books. Islamic Architecture and their aggregation systems portrayed marvels of their time. Islamic libraries were huge and rich for the European knowledge seekers.
And history tells us that those were the times when Moslems were the furthest from the dogma of their religion, there societies were open to controlled prostitution in the name of dancimng Jawari, and alcohol was openly consumed. We also notice in these periods that struggle for power among them mounted, yet they were the most tolerant to other nations and beliefs. There was nothing Islamic about them at that time, only a name. After that time, the Islamic civilization collapsed and kept deteriorating as people clung more to the their religious beliefs that were diverted through different interpretations.
And based on that; I believe that it’s not only Moslems who missread their religion, the problem stemmed from the core of the religion (Quran and tradition) for being vague and subject to different interpretations. If Quran was the true word of God, then it should have contained the miracle of not being subject to different interpretations, at least to keep Moslems united, and then, one would believe that Islam is suitable for every location and time.
Nothing can give a solid proof of the existence of heaven and hell, yet, nothing can disprove it either. Same goes to God. So the chance remain fifty-fifty. You either believe in it for the sake of taking a lesser risk if you don’t believe in blind faith, or discard it all together. Yet, the possibility is there until proved or disproved. As for now; these cases can only be understood through logic. So let’s reiterate your question and narrow it down to make it closer to something that can be measured.
Is there any mention of the stories of prophets outside the holy books? Are there any archeological evidences of each prophet’s reign (and I stress prophet’s)? Are there any mention of each prophet in history books outside its holy book, or the books that were based on it’s holy books? Ok, that was too general, let’s narrow it down a bit since your knowledge of your religion, mashallah, especially in reciting Quran is superb.
Is there any mention of the prophet Mohammad reign in non-Moslem history books other than those referenced to Moslem books? And if there were; did those stories mach? Did archeology of Mohammad’s time match those stories? Did ancient books of other nations confirm those stories? After all Mecca was an open, mid trade center for traders of the South and the North, and supposedly was exposed and open to other nations, and an emergence of a new religion would not have gone unnoticed in the ancient books of those nations.
That's why faith is called "FAITH" to believe in the unseen, you see.
keep in mind that every major religion has gone through various phases from emergence to growth to stagnation to depression and reformation. these are cycles that play out across centuries and i suspect islam is not immune to them.
islam is unique in that it is truly the last 'great' religion and it is here to stay. the future should be one of consilience and consolidation between religions and peoples.
at the end of the day - tolerance of thought will be the salvation of mankind.
I've been asking your first question for as long as I can remember and nobody has given me a convincing answer yet. I also asked the second question verbatim when I was in my high school's Tarbiya Islamiya class, and the teacher had no answer. I kept hounding him until the students yelled at me to shut up and then he kicked me out!
We're all adults here, so why can't you answer Anon's query? I still find it amazing that you named yourself after Saint Joan. A Christian (gasp!) who will burn in hell according to some of the comments here.
All men are my brothers. I would have liked to have said it then, and I would like to say it now: all men are my brothers. But all men are not my brothers. Why? Because all women are my sisters. And the brother who denies the rights of his sister: that brother is not my brother. At the very best, he is my half-brother - by definition. Osama is not my brother.
Religion is sensitive ground, as well it might be. Here we walk on eggshells. Because religion is itself an eggshell. Today, in the West, there are no good excuses for religious belief - unless we think that ignorance, reaction and sentimentality are good excuses. This is of course not so in the East, where, we acknowledge, almost every living citizen in many huge and populous countries is intimately defined by religious belief. The excuses, here, are very persuasive; and we duly accept that 'faith' - recently and almost endearingly defined as 'the desire for the approval of supernatural beings' - is a world-historical force and a world-historical actor. All religions, unsurprisingly, have their terrorists, Christian, Jewish, Hindu, even Buddhist. But we are not hearing from those religions. We are hearing from Islam.
Let us make the position clear. We can begin by saying, not only that we respect Muhammad, but that no serious person could fail to respect Muhammad - a unique and luminous historical being. Judged by the continuities he was able to set in motion, he remains a titanic figure, and, for Muslims, all-answering: a revolutionary, a warrior, and a sovereign, a Christ and a Caesar, 'with a Koran in one hand', as Bagehot imagined him, 'and a sword in the other'. Muhammad has strong claims to being the most extraordinary man who ever lived. And always a man, as he always maintained, and not a god. Naturally we respect Muhammad. But we do not respect Muhammad Atta.
Until recently it was being said that what we are confronted with, here, is 'a civil war' within Islam. That's what all this was supposed to be: not a clash of civilisations or anything like that, but a civil war within Islam. Well, the civil war appears to be over. And Islamism won it. The loser, moderate Islam, is always deceptively well-represented on the level of the op-ed page and the public debate; elsewhere, it is supine and inaudible. We are not hearing from moderate Islam. Whereas Islamism, as a mover and shaper of world events, is pretty well all there is.
So, to repeat, we respect Islam - the donor of countless benefits to mankind, and the possessor of a thrilling history. But Islamism? No, we can hardly be asked to respect a creedal wave that calls for our own elimination. More, we regard the Great Leap Backwards as a tragic development in Islam's story, and now in ours. Naturally we respect Islam. But we do not respect Islamism, just as we respect Muhammad and do not respect Muhammad Atta.
المؤامرات على الأديان وجميع الانقلابات المخربة والثورات على القيم والمبادئ خرجت من هذا التراث .. وان كل معول هدم كان وراءه توجيه يهودي.
•تذكروا أن الشعب الذي لا يهلك غيره يهلك نفسه.
•يجب ان نخلق الجيل الذي لا يخجل من كشف عورته (ألا تفسر لنا هذه الجملة موجة العرى في الافلام والموضات التى تسود العالم الآن).
.علينا ان نشعل حربا بين الشعوب ونضرب الدول بعضها ببعض فبهذا يصبح جميع المتحاربين في حاجة الى أموالنا فنفرض عليهم شروطنا.
•الجماهير عمياء فاشتروها بالمال وسوقوها كالبهائم الى أهدافكم.
•سيطروا على الانتخابات ووسائل الاعلام والصحافة (وهم قد سيطروا عليها بالمال والجنس والمرأة في الغرب الرأسمالي وبالحزب والسلطة في العالم الاشتراكي).
•ادفعوا الجماهير العمياء الى الثورة وسلموهم مقاليد الحكم ليحكموا في غوغائية وغباء (وقد فعلوا هذه في الثورة الفرنسية) وحينئذ نأتي نحن ونعدمهم فنكون منقذين للعالم (وقد اعدموهم جميعاً من روبسبير الى ميرابوا).
•ارفعوا شعار الحرية واهدموا بها الاخلاق والاسرة والقومية والوطنية.
.ارفعوا شعار العلم واهدموا به الدين .. وهذا ما فعله كمال أتاتورك (حفيد مزاراحي) حينما اقام الدولة العلمانية في تركيا ووقف يخطب في البرلمان التركي عام 1923 ساخراً من القرآن.
نحن الآن في القرن العشرين لا نستطيع ان نسير وراء كتاب تشريع يبحث عن التين والزيتون.
•الذي يعرقل مؤامراتكم اوقعوه في فضائح ثم هددوه بكشفها (وقد فعلوها في ووترجيت) او في مآزق مالية ثم تقدموا لانقاذه (وقد فعلها دزرائيلي مع الخديو واستولى على القنال).. وإذ تعذر الامر سارعوا الى اغتياله (وقد فعلوها بكنيدي) ثم اقتلوا قاتله لتدفنوا اسرارنا معه الى الأبد (وقد فعلوها بقاتل كنيدي).
•اقتلوا القوميات والوطنيات بالدعوة الى الاممية والمواطنة العالمية وقد فعلها ماركس في الشيوعية.
•كل ما عدا اليهود حيوانات ناطقة سخرها الله في خدمة اليهود.
واليهودية ترى ان الله واحد ولكنها تحتكره لنفسها فلا عمل لله الا الحفاظ على اسرائيل وتسخير جميع الشعوب لخدمتها.
واللاهوت اليهودي لا يؤمن بآخرة، وقد شطبوا كل ما جاء عن الآخرة في التوراة .. والقيامة عندهم هي قيامة دولتهم في فلسطين والبعث بعثها والنشر نشرها .. ويوم الحساب هو اليوم الذي يحاسبون فيه كل الأمم يوم يعود المسيح ويباركهم ويختارهم نواباً له في حكم العالم وإقامة ملكوت الله على الأرض .. والعجيب انهم كفروا بالمسيح حينما جاء ثم أعلنوا إيمانهم بعودته وشرطوا هذه العودة بانها رجعة من المسيح ليختارهم رؤساء وحكاماً للعالم الى الأبد.
والفكر اليهودي يلقى غلالة من الأسرار والطلاسم والكتمان والغموض على كل شئ .. والكبالا والسحر وعلم الأعداد والحروف وتسخير الشياطين من علومهم التى شغفوا بها وروجوها ونشروها.
وكانت وسيلتهم الى هدم الكتب السماوية هى تفسيرها بالتأويل وذلك برفض المعاني الظاهرة واختراع معان باطنة تهدم الغرض الديني وتفسد هدفه.
ونستطيع ان نرى اثر التوجيه الهودي في الفلسفات العبثية والدمية والمادية والفوضية والإباحية .. واحيانا نلمح اسماء يهودية خلفها مثل : سارتر – فرويد – ماركس – ماركوز.
واذا فتحنا ملف الديانة البهائية فإننا نجد اثر التوجيه اليهودي واضحا في كتبها.
عبد الهاء تأليف سليم قبعين القاهرة مطبعة العمران 1922.
مفواضات عبد البهاء الطبعة الاولى 1928م. موعود كل الامم.
جورج تاوزنه مطبوع بإذن من المحفل الروحاني لمصر والسودان.
•اكثر فلاسفة اليونان تعلموا الحكمة من بنى اسرائيل.
•رسالة عبد البهاء هي توحيد المسلمين والنصارى واليهود وجمعهم على أصل نواميس موسى.
•عمل موسى لا يس

Answer: Unknown.


Input: What position did Simon English hold in the 2008 general election?

Context:
Sir Simon William English  (born 30 December 1961) is a New Zealand former National Party politician who served as the 39th prime minister of New Zealand from 2016 to 2017. He had previously served as the 17th deputy prime minister of New Zealand and minister of finance from 2008 to 2016 under John Key and the Fifth National Government.

A farmer and public servant before entering politics, English was elected to the New Zealand Parliament in  as the National Party's candidate in the Wallace electorate. He was elevated to Cabinet in 1996 and in 1999 was made minister of finance, although he served for less than a year due to his party's loss at the 1999 general election. In October 2001, English replaced Jenny Shipley as the leader of the National Party (and consequently as Leader of the Opposition). He led the party to its worst defeat at the 2002 general election, and as a consequence, in October 2003 he was replaced as leader by Don Brash.

In November 2006, after Brash's resignation, English became deputy leader under John Key. After National's victory at the 2008 general election, he became deputy prime minister and was also made minister of finance for the second time. Under English's direction New Zealand's economy maintained steady growth during National's three terms of government. He became a list-only MP after stepping down as an electorate MP at the 2014 general election.

John Key resigned as leader of the National Party and prime minister in December 2016. English won the resulting leadership election unopposed and was sworn in as prime minister on 12 December 2016. His tenure was only ten months, and included a three-month election campaign. In the 2017 general election, National won the largest number of seats but fell short of a majority. The parties holding the balance of power declined to support the existing government, and English was subsequently replaced as prime minister by Jacinda Ardern, leader of the Labour Party. English initially continued on as Leader of the Opposition, but resigned as leader of the National Party on 27 February 2018 and left parliament two weeks later.

Early life
English was born on 30 December 1961 at Lumsden Maternity Centre in Lumsden. He is the eleventh of twelve children of Mervyn English and Norah (née O'Brien) English. His parents purchased Rosedale, a mixed sheep and cropping farm in Dipton, Southland from Mervyn's uncle, Vincent English, a bachelor, in 1944. English was born in the maternity unit at Lumsden.

English attended St Thomas's School in Winton, then boarded at St. Patrick's College in Upper Hutt, where he became head boy. He played in the first XV of the school's rugby team. English went on to study commerce at the University of Otago, where he was a resident at Selwyn College, and then completed an honours degree in English literature at Victoria University of Wellington.

After finishing his studies, English returned to Dipton and farmed for a few years. From 1987 to 1989, he worked in Wellington as a policy analyst for the New Zealand Treasury, at a time when the free market policies favoured by Labour's finance minister Roger Douglas (known collectively as "Rogernomics") were being implemented.

English joined the National Party in 1980, while at Victoria University. He served for a period as chairman of the Southland branch of the Young Nationals, and became a member of the Wallace electorate committee. After moving to Wellington, he served for periods on the Island Bay and Miramar electorate committees, respectively.

Fourth National Government (1990–1999)

At the 1990 general election, English stood as the National candidate in Wallace, replacing the retiring Derek Angus, and was elected with a large majority. He would hold this seat, renamed Clutha-Southland in 1996, until 2014. He and three other newly elected National MPs (Tony Ryall, Nick Smith, and Roger Sowry) were soon identified as rising stars in New Zealand politics, and at various points were dubbed the "brat pack", the "gang of four", and the "young Turks". In his first term in parliament, English chaired a select committee into social services. He was made a parliamentary under-secretary in 1993, serving under the Minister of Health.

First period in cabinet (1996–1999)
In early 1996, English was elevated to cabinet by Prime Minister Jim Bolger, becoming the Minister for Crown Health Enterprises and Associate Minister of Education (to Wyatt Creech). He was 34 at the time, becoming the cabinet's youngest member. After the 1996 general election, the National Party was forced into a coalition with New Zealand First to retain government. In the resulting cabinet reshuffle, English emerged as Minister of Health. However, as a condition of the coalition agreement, NZ First's Neil Kirton (a first-term MP) was made Associate Minister of Health, effectively becoming English's deputy. This arrangement was described in the press as a "shotgun marriage", and there were frequent differences of opinion between the two ministers. After their relationship became unworkable, Kirton was sacked from the role in August 1997, with the agreement of NZ First leader Winston Peters.

As Minister of Health, English was responsible for continuing the reforms to the public health system that National had begun after the 1990 general election. The reforms were unpopular, and health was perceived as one of the government's weaknesses, with the health portfolio consequently being viewed as a challenge. English believed that the unpopularity of the reforms was in part due to a failure in messaging, and encouraged his National colleagues to avoid bureaucratic and money-focused language (such as references to "balance sheets" and "user charges") and instead talk about the improvements to services the government's reforms would bring. He also rejected the idea that public hospitals could be run as commercial enterprises, a view which some of his colleagues had previously promoted.

By early 1997, as dissatisfaction with Bolger's leadership began to grow, English was being touted as a potential successor, along with Jenny Shipley and Doug Graham. His age (35) was viewed as the main impediment to a successful leadership run. National's leadership troubles were resolved in December 1997, when Bolger resigned and Shipley was elected to the leadership unopposed. English had been a supporter of Bolger as leader, but Shipley reappointed him Minister of Health in her new cabinet.

English was promoted to Minister of Finance in a reshuffle in January 1999, a position which was at the time subordinate to the Treasurer, Bill Birch. After a few months, the pair switched positions as part of Birch's transition to retirement, with English assuming the senior portfolio. In early interviews, he emphasised his wish to be seen as a pragmatist rather than an ideologue, and said that the initiatives of some of his predecessors (Roger Douglas's "Rogernomics" and Ruth Richardson's "Ruthanasia") had focused on "fruitless, theoretical debates" when "people just want to see problems solved".

Opposition (1999–2008)

After the National Party lost the 1999 election to Helen Clark's Labour Party, English continued on in the shadow cabinet as National's spokesperson for finance. He was elected deputy leader of the party in February 2001, following the resignation of Wyatt Creech, with Gerry Brownlee being his unsuccessful opponent.

Leader of the Opposition
In October 2001, after months of speculation, Jenny Shipley resigned as leader of the National Party after being told she no longer had the support of the party caucus. English was elected as her replacement unopposed (with Roger Sowry as his deputy), and consequently became Leader of the Opposition. However, he did not openly organise against Shipley, and according to The Southland Times "there was almost an element of 'aw, shucks, I'll do it then' about Mr English's ascension".

Aged 39 when he was elected, English became the second-youngest leader in the National Party's history, after Jim McLay (who was 38 when elected in 1984). He also became only the third Southlander to lead a major New Zealand political party, after Joseph Ward and Adam Hamilton. However, English failed to improve the party's performance. In the 2002 election, National suffered its worst electoral defeat ever, gaining barely more than twenty percent of the vote. English described it as "the worst day of my political life". Both party insiders and the general public were split as to how much to blame him for the loss, but most of the party believed that English would be able to rebuild National's support.

By late 2003, however, National's performance in opinion polls remained poor. The party had briefly increased its popularity in the year following the election, but by October its support had fallen to levels only slightly better than what it achieved in the last ballot. English also appeared in a boxing match for a charity against entertainer Ted Clarke. This did not boost his polling or that of the National party either, with suggestions that it devalued his image as a serious politician. Don Brash, former governor of the Reserve Bank and a relative newcomer to politics, began to build up support to replace English. On 28 October, Brash gained sufficient backing in Caucus to defeat English in a leadership contest.

Shadow cabinet roles and deputy leader
On 2 November 2003, when Brash changed responsibilities for certain MPs, English became National's spokesman for education, ranked at fifth place in the party's parliamentary hierarchy. He remained in parliament after the 2005 election. In his new shadow education portfolio, English performed strongly, and remained a party favourite despite his election defeat as leader in 2002, eventually being returned to the finance portfolio in August 2004 as deputy spokesman (while still retaining responsibility for education).

In November 2006, Brash resigned as leader. English was considered as a potential replacement leader (running against John Key) or deputy leader (against incumbent Gerry Brownlee) in the ensuing leadership election. However, a contest was avoided when the MPs agreed a Key/English ticket would run unopposed in a display of party unity. English took over the deputy leadership and the finance portfolio in the Key shadow cabinet.

Fifth National Government (2008–2017)

Deputy Prime Minister and Minister of Finance (2008–2016)

At the 2008 election, English was re-elected by his electorate, winning by a margin of about 15,500 votes. He became Deputy Prime Minister of New Zealand and Minister of Finance in the fifth National Government, being sworn into office on 19 November 2008 and continued to serve in those roles until becoming Prime Minister on 12 December 2014. He was also made Minister of Infrastructure in National's first term of government and Minister responsible for Housing New Zealand Corporation and minister responsible for the New Zealand flag consideration process in its third.

He was comfortably re-elected in Clutha-Southland in the 2011 election but opted to run as a party-list candidate in 2014.

The pairing of John Key as leader of the National Party and English as his deputy has been compared to that of Bob Hawke and Paul Keating (in Australia) and Tony Blair and Gordon Brown (in the UK).

English acceded to the role of Finance Minister in the continuing wake of the financial crisis. In response to New Zealand's rising debt, English made budget deficit-reduction his main priority. His first budget outlined three focuses in New Zealand's financial recovery: "improving the business environment and removing roadblocks to growth; investment in productive infrastructure; and improving the way government works". One of his first acts was creating the National Infrastructure Unit, charged with formulating a plan for infrastructure projects and investments. He commissioned a government-wide spending review, with an aim to reducing government expenditure—with the exceptions of a two-year stimulus package and long-term increases on infrastructure spending.

In April 2011, the Opposition criticised English for suggesting that New Zealand businesses could use New Zealand's low wages to help it compete with Australia. The National Government campaigned for re-election in 2011 on its economic record. The Government boasted growth for five consecutive quarters up to mid-2010, totalling 1.6% of real GDP.

Strong growth resulted in a surplus of $473 million for the 2015/16 financial year, projected to rise to $8.5 billion by 2020/21. In his 2016 Economic and Fiscal Update address, English stated that reducing debt and tackling the costs of the 2016 Kaikōura earthquake were higher priorities than reducing rates of tax.

Allowances issue
In 2009, the media, including TVNZ and TV3 revealed that English was receiving about NZ$900 a week as part of a living allowance for ministers, to live in his own NZ$1.2 million Wellington home. At the time, English also received $276,200 in his annual salary as Deputy Prime Minister. It was also revealed other ministers with homes in the capital city were also claiming accommodation allowances. On 3 August 2009, Prime Minister John Key started a review of the housing allowances claimed by cabinet ministers. English subsequently paid back $12,000 and only claimed about $24,000 a year in living allowances. The Auditor-General's office said in September 2009 that they were making "preliminary enquiries" into parliamentary housing expenses in response to a letter of complaint from Progressive party leader Jim Anderton. Two days later English stated that he would no longer take up any housing allowance and had paid back all the allowance he had received since the November 2008 election.

Prime Minister (2016–2017)

John Key resigned on 12 December, and endorsed English as his successor in the resulting leadership election. Following the drop-out of both Judith Collins and Jonathan Coleman from the leadership election, English was sworn in as the 39th Prime Minister of New Zealand on 12 December 2016.

English appointed his first cabinet on 18 December. In a reshuffle, he appointed Steven Joyce to succeed him as Finance Minister, while most ministerial portfolios remained the same.

In February 2017, English did not attend Waitangi Day commemorations at the historic treaty grounds, reportedly in response to the Ngāpuhi iwi's decision to stop the Prime Minister from speaking at the marae. Ngāpuhi have protested the Government's negotiation of the Trans Pacific Partnership Agreement (TPPA), which the iwi believe infringes upon Māori sovereignty, and thus does not adhere to the Treaty of Waitangi. English had been invited to attend in an official capacity; his non-attendance was criticised by a Ngāpuhi elder and Opposition leader Andrew Little.

In his first overseas trip as Prime Minister, English travelled to Europe to discuss trade ties, including a prospective New Zealand–European Union free trade agreement. He first travelled to London on 13 January 2017 to meet British Prime Minister Theresa May. Discussing trade relations, English said the two nations were "natural partners" and would "continue to forge ties" after the UK's withdrawal from the EU. He also arranged to meet with London Mayor Sadiq Khan, Belgian Prime Minister Charles Michel and German Chancellor Angela Merkel.  In a meeting with Merkel, English received crucial backing from Germany for a trade deal with the EU. On 16 January, English stated that his government would continue to promote TPPA, despite the United States' decision to withdraw from the agreement. He explained that Southeast Asian countries would now be treated as a priority in negotiations—he also asserted that the United States was ceding influence to China by its rejection of the trade pact.

At a press conference at the Beehive on 1 February 2017, English announced that the 2017 general election would be held on 23 September. The Prime Minister later confirmed that his party would approach ACT, United Future and the Māori Party if confidence and supply agreements were required to form a government following the election. In his second cabinet reshuffle on 24 April, English appointed Gerry Brownlee as his new Foreign Affairs Minister; he also promoted Nikki Kaye to the portfolio of Education Minister, and moved Mark Mitchell into the cabinet to become Defence Minister. The reshuffle was perceived as an election preparation.

On 13 February 2017, English welcomed Australian Prime Minister Malcolm Turnbull to Wellington. The two leaders reaffirmed their shared trade agenda, and discussed changes to the Australian citizenship pathway which will affect permanent residents originating from New Zealand.

On 19 June, it was reported that Todd Barclay, who succeeded English as MP for Clutha-Southland, had clandestinely recorded one of his employee's conversations the previous year, and that John Key's leaders' budget was used to pay a confidential settlement after the employee resigned. English admitted that he had been aware of the illegal recording and the settlement, and thus implicated in the scandal.

During the 2017 National campaign launch, English introduced a $379 million social investment package including digital learning academies for high school students, more resources for mathematics, and boosting support for teaching second languages in schools, and maintaining National Standards in the school curriculum. Prime Minister English also sought to defend National's financial management and economic track record and claimed that the opposition Labour Party would raise taxes. Early opinion polling had forecast a poor showing in the election for the Labour Party, but in early August 37-year-old Jacinda Ardern took over as Labour leader and seemingly energised younger voters.

At the 2017 general election, National won the largest share of the party vote (44.4%) and the largest number of seats (56) in the House Representatives. However, National lacked enough seats to govern alone due to two of the party's support partners, the Māori Party and United Future, losing their parliamentary seats. In response, English stated that the party would be entering into talks to form a coalition with New Zealand First. Following talks with the two largest parties, New Zealand First entered a coalition arrangement with the Labour Party. English was succeeded as prime minister by Jacinda Ardern on 26 October.

Opposition (2017–2018)

Leader of the Opposition
English was re-elected as National Party leader on 24 October 2017. At the time of his re-election, English announced his intention to stay on as leader until the next general election. On 13 February 2018, however, he stood down as National Party leader due to personal reasons, and instructed the party to put into motion the processes to elect a new leader. He also retired from Parliament. English's resignation followed weeks of speculation that he would step aside for a new leader. On 27 February, he was succeeded as party leader by Simon Bridges as the result of the leadership election held that day.

Post-premiership
In 2018, English joined the board of Australian conglomerate, Wesfarmers. English serves in Chairmanships of Mount Cook Alpine Salmon, Impact Lab Ltd and Manawanui Support Ltd. He is also a director of The Instillery, Centre for Independent Studies and The Todd Corporation Limited, and is a member of the Impact Advisory Group of Macquarie Infrastructure and Real Assets.

Political and social views

English is regarded as more socially conservative than his predecessor, John Key. He has stated his opposition to voluntary euthanasia and physician-assisted suicide, same-sex civil unions, and the decriminalisation of prostitution. As Prime Minister he opposed any "liberalisation" of abortion law.

In 2004, English voted against a bill to establish civil unions for both same-sex and opposite-sex couples. In 2005, he voted for the Marriage (Gender Clarification) Amendment Bill, which would have amended the Marriage Act to define marriage as only between a man and a woman. English voted against the Marriage (Definition of Marriage) Amendment Bill, a bill that legalised same-sex marriage in New Zealand. However, in December 2016 he stated, "I'd probably vote differently now on the gay marriage issue. I don't think that gay marriage is a threat to anyone else's marriage".

In 2009, English voted against the Misuse of Drugs (Medicinal Cannabis) Amendment Bill, a bill aimed at amending the Misuse of Drugs Act so that cannabis could be used for medical purposes.

Personal life
English met his future wife, Mary Scanlon, at university. She was studying medicine at the time, and became a general practitioner. Both her parents were immigrants, her father being Samoan and her mother Italian, born on the island of Stromboli. They have six children: a daughter and five sons.

English is a practising Roman Catholic, but has stated that he considers his religious beliefs personal and thus separate from politics.

In June 2002, English took part in TV3's Fight For Life, a celebrity boxing fundraiser to raise money for the Yellow Ribbon anti-youth-suicide campaign, influenced by the death of a teenage nephew in 1997. He lost a split decision to former university colleague Ted Clarke.

Honours
In the 2018 Queen's Birthday Honours, English was appointed a Knight Companion of the New Zealand Order of Merit, for services of over 27 years to the State.

See also

List of New Zealand governments
Politics of New Zealand

References

External links

Profile at National Party
Profile on Parliament.nz
Releases and speeches at Beehive.govt.nz

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1961 births
21st-century New Zealand politicians
Candidates in the 2017 New Zealand general election
Deputy Prime Ministers of New Zealand
Leaders of the Opposition (New Zealand)
Living people
Members of the Cabinet of New Zealand
Members of the New Zealand House of Representatives
New Zealand farmers
New Zealand finance ministers
New Zealand list MPs
New Zealand MPs for South Island electorates
New Zealand National Party MPs
New Zealand National Party leaders
New Zealand Roman Catholics
New Zealand people of Irish descent
People educated at St. Patrick's College, Silverstream
People from Dipton, New Zealand
People from Lumsden, New Zealand
Prime Ministers of New Zealand
University of Otago alumni
Victoria University of Wellington alumni
Knights Companion of the New Zealand Order of Merit
New Zealand politicians awarded knighthoods

Answer: He became deputy prime minister and minister of finance.