This does not mean confusables.txt is wrong. It means confusables.txt is a visual-similarity claim that has never been empirically validated at scale. Many entries map characters to the same abstract target under NFKC decomposition (mathematical bold A to A, for instance), and the mapping is semantically correct even if the glyphs look nothing alike. But if you treat every confusables.txt entry as equally dangerous for UI security, you are generating massive false positive rates for 96.5% of the dataset.
当然，它也面临一些挑战：亚利桑那州整体医疗人才短缺，预计到2030年，还需要额外1941名初级护理医生；而且医院高度依赖Medicare，报销率低，也会影响对人才的吸引力。但总体来说，Sun City的吸引力，已经远超亚利桑那州的农村地区，属于中等偏上水平。
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