针对一些地方农村公路养护资金投入不足的问题，去年以来，陈燕走访了宁夏20多个乡镇，笔记写了厚厚两大本。在建议中，陈燕呼吁对财力薄弱地区普通省道和农村公路的补助额度进行适当调整，以提升农村公路质量。在建议里，光数据引用就有20多处，都是陈燕走访调研得来的一手数据。陈燕说：“用脚步走出来的建议最真实客观。”
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we assign a minterm id to each of these classes (e.g., 1 for letters, 0 for non-letters), and then compute derivatives based on these ids instead of characters. this is a huge win for performance and results in an absolutely enormous compression of memory, especially with large character classes like \w for word-characters in unicode, which would otherwise require tens of thousands of transitions alone (there’s a LOT of dotted umlauted squiggly characters in unicode). we show this in numbers as well, on the word counting \b\w{12,}\b benchmark, RE# is over 7x faster than the second-best engine thanks to minterm compressionremark here i’d like to correct, the second place already uses minterm compression, the rest are far behind. the reason we’re 7x faster than the second place is in the \b lookarounds :^).