test
In previous studies, Puttaswamy (2014) merged AOD measurements from ground-based data sources by Universal Kriging (UK) approach (CV R2=0.64) and spatial statistical data fusion (SSDF) (CV R2=0.34), and missing rates dropped to around 48% in USA; Lv (2016) developed city-specific linear regression model to fill missing AOD data with seasonal averaged AOD data in each grid (CV R2=0.45), then interpolated by UK method to achieve the full spatial coverage in North China; Qing (2017) used multiple Imputation (MI) method with chemical transport model (CTM) simulations to achieve the full coverage (R2=0.77) in Yangtze River Delta of China; Yang and Hu (2018) used spatiotemporal-interpolated method, and missing rates dropped to around 32.7% in China (MAE=0.07). Compared with previous studies, instead of predicting the missing AOD values with seasonal average values (Lv et al., 2016) or values from few days ago (Yang and Hu, 2018), we only use same-day Terra data in a mixed-effect model to estimate the missing Aqua values, which makes full use of satellite-derived AOD data and preserves day-to-day temporal variability or distribution at a large extent. Moreover, we set maximum number of nearest observations and the max distance radius by CV result to restrict the neighbor area for search in spatial interpolation, which ensures the higher out-of-sample spatial predictive ability (CV R2=0.76), but it is hard to get the full coverage. Therefore, we also developed the Non-AOD model for those day-grid data not covered (Table A.8).
Grammar and spelling errors:
Line 1, column 1164, Rule ID: THE_SUPERLATIVE[2]
Message: A determiner is probably missing here: 'of the nearest'.
Suggestion: of the nearest
...extent. Moreover, we set maximum number of nearest observations and the max distance radiu...
^^^^^^^^^^
Transition Words or Phrases used:
also, but, moreover, so, then, therefore
Attributes: Values AverageValues Percentages(Values/AverageValues)% => Comments
Performance on Part of Speech:
To be verbs : 1.0 13.1623246493 8% => More to be verbs wanted.
Auxiliary verbs: 0.0 7.85571142285 0% => OK
Conjunction : 10.0 10.4138276553 96% => OK
Relative clauses : 2.0 7.30460921844 27% => More relative clauses wanted.
Pronoun: 5.0 24.0651302605 21% => OK
Preposition: 35.0 41.998997996 83% => OK
Nominalization: 4.0 8.3376753507 48% => More nominalizations (nouns with a suffix like: tion ment ence ance) wanted.
Performance on vocabulary words:
No of characters: 1274.0 1615.20841683 79% => OK
No of words: 238.0 315.596192385 75% => More content wanted.
Chars per words: 5.35294117647 5.12529762239 104% => OK
Fourth root words length: 3.92775363542 4.20363070211 93% => OK
Word Length SD: 3.22043954225 2.80592935109 115% => OK
Unique words: 149.0 176.041082164 85% => More unique words wanted.
Unique words percentage: 0.626050420168 0.561755894193 111% => OK
syllable_count: 379.8 506.74238477 75% => OK
avg_syllables_per_word: 1.6 1.60771543086 100% => OK
A sentence (or a clause, phrase) starts by:
Pronoun: 3.0 5.43587174349 55% => OK
Article: 0.0 2.52805611222 0% => OK
Subordination: 0.0 2.10420841683 0% => More adverbial clause wanted.
Conjunction: 3.0 0.809619238477 371% => Less conjunction wanted as sentence beginning.
Preposition: 2.0 4.76152304609 42% => More preposition wanted as sentence beginning.
Performance on sentences:
How many sentences: 4.0 16.0721442886 25% => Need more sentences. Double check the format of sentences, make sure there is a space between two sentences, or have enough periods. And also check the lengths of sentences, maybe they are too long.
Sentence length: 59.0 20.2975951904 291% => The Avg. Sentence Length is relatively long.
Sentence length SD: 235.428333044 49.4020404114 477% => The lengths of sentences changed so frequently.
Chars per sentence: 318.5 106.682146367 299% => Less chars_per_sentence wanted.
Words per sentence: 59.5 20.7667163134 287% => Less words per sentence wanted.
Discourse Markers: 10.0 7.06120827912 142% => OK
Paragraphs: 1.0 4.38176352705 23% => More paragraphs wanted.
Language errors: 1.0 5.01903807615 20% => OK
Sentences with positive sentiment : 1.0 8.67935871743 12% => More positive sentences wanted.
Sentences with negative sentiment : 2.0 3.9879759519 50% => More negative sentences wanted.
Sentences with neutral sentiment: 1.0 3.4128256513 29% => More facts, knowledge or examples wanted.
What are sentences with positive/Negative/neutral sentiment?
Coherence and Cohesion:
Essay topic to essay body coherence: 0.0 0.244688304435 0% => The similarity between the topic and the content is low.
Sentence topic coherence: 0.0 0.084324248473 0% => Sentence topic similarity is low.
Sentence topic coherence SD: 0.0 0.0667982634062 0% => Sentences are similar to each other.
Paragraph topic coherence: 0.0 0.151304729494 0% => Maybe some paragraphs are off the topic.
Paragraph topic coherence SD: 0.0 0.056905535591 0% => Paragraphs are similar to each other. Some content may get duplicated or it is not exactly right on the topic.
Essay readability:
automated_readability_index: 33.5 13.0946893788 256% => Automated_readability_index is high.
flesch_reading_ease: 11.59 50.2224549098 23% => Flesch_reading_ease is low.
smog_index: 15.9 7.44779559118 213% => Smog_index is high.
flesch_kincaid_grade: 26.3 11.3001002004 233% => Flesch kincaid grade is high.
coleman_liau_index: 14.64 12.4159519038 118% => OK
dale_chall_readability_score: 11.8 8.58950901804 137% => OK
difficult_words: 79.0 78.4519038076 101% => OK
linsear_write_formula: 61.0 9.78957915832 623% => Linsear_write_formula is high.
gunning_fog: 25.6 10.1190380762 253% => Gunning_fog is high.
text_standard: 26.0 10.7795591182 241% => The average readability is very high. Good job!
What are above readability scores?
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Minimum 250 words wanted.
Minimum four paragraphs wanted.
It is not exactly right on the topic in the view of e-grader. Maybe there is a wrong essay topic.
Rates: 11.2359550562 out of 100
Scores by essay e-grader: 0.67 Out of 6
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Note: the e-grader does NOT examine the meaning of words and ideas. VIP users will receive further evaluations by advanced module of e-grader and human graders.