![使用宏来简化章节代码以位于基线上](https://linux22.com/image/428681/%E4%BD%BF%E7%94%A8%E5%AE%8F%E6%9D%A5%E7%AE%80%E5%8C%96%E7%AB%A0%E8%8A%82%E4%BB%A3%E7%A0%81%E4%BB%A5%E4%BD%8D%E4%BA%8E%E5%9F%BA%E7%BA%BF%E4%B8%8A.png)
如何自定义编码以获得所需的输出:
当章节标题高度小于 7\baselineskip 时,章节标题后的文本应从第 12 行开始
当章节标题高度小于 8\baselineskip 时,章节标题后的文本应从第 14 行开始
当章节标题增加一行时,文本应从下一个第 16 行开始,依此类推。
我已经尝试了下面的编码,但是我确实使用了多个条件,如何在没有太多条件的情况下简化编码
平均能量损失
\documentclass[openany]{book}
\usepackage{vruler}
\setvruler[12pt][1][1][2][0][32pt][32pt][-1.15pt][\textheight]%%\setvruler[<SCALE>][<INITIAL_COUNT>][<STEP>][<DIGITS>][<MODE>][<ODD_HSHIFT]>][<EVEN_HSHIFT>][<VSHIFT>][<HEIGHT>]
\usepackage{showframe}
\makeatletter
\def\@makechapterhead#1{%
\global\setbox\@tempboxa=\vbox{\parindent \z@ \raggedright \normalfont
\ifnum \c@secnumdepth >\m@ne
\if@mainmatter
\huge\bfseries \@chapapp\space \thechapter
\par\nobreak
\vskip 20\p@
\fi
\fi
\interlinepenalty\@M
\Huge \bfseries #1\par\nobreak
}%
\ifdim\ht\@tempboxa<7\baselineskip
\@tempdima10\baselineskip
\advance\@tempdima-1.5pt
\noindent\fboxsep0pt\fboxrule0.1pt\fbox{\vbox to \@tempdima{\unvbox\@tempboxa\vfill}}
\else%
\ifdim\ht\@tempboxa<8\baselineskip
\@tempdima12\baselineskip
\advance\@tempdima-1.5pt
\noindent\fboxsep0pt\fboxrule0.1pt\fbox{\vbox to \@tempdima{\unvbox\@tempboxa\vfill}}
\fi%
}
\makeatother
\begin{document}
\chapter{Chapter Head}
In 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.
\clearpage
\chapter{Chapter Head turnover into multiline}
In 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.
n 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.
n 2019, Syria experienced its largest outbreak of fires since 2003, when fire occurrence began to be monitored via the MODIS satellite instruments. Here, we combine remotely sensed data on fire, local climatic conditions, and vegetation with spatial data on violence, territorial control, and return of internally displaced persons (IDPs) to explore the underlying causes of Syria's fires at the sub-district, or ADM-3, level. We find evidence for a nuanced story: precipitation and stabilization in Kurdish-controlled territory fueled a bountiful wheat-growing year in 2019. This agricultural resurgence coincided with high fire activity, possibly revealing that people were attempting to jump-start agricultural livelihoods that were lost during the civil war. Restoration of labor forces from IDP returns was not a significant factor in this agricultural recovery. Meanwhile, most sub-districts outside Kurdish-controlled territory were free of fires, which explains the absence of a relationship between vegetation and fire. Thus, Syrian fire patterns in 2019 may be a signal of uneven stabilization, rather than destabilization.
\end{document}