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Living environments are likely to differ in traffic-noise levels by neighborhood socioeconomic disadvantage (i.e., high- and low-socioeconomic disadvantaged neighborhoods) (Havard et al. 2011), which may itself be associated with lowered sleep quality.
Most fully-parallel manipulators encountered today have a common disadvantage, i.e., their low rotational capability.
This latter disadvantage (i.e., higher emissions of oxides of nitrogen) is the focus of this review article.
However, these advantages are achieved at the expense of one major disadvantage, i.e., degradation in the quality of synthetic speech [1].
However, the approach using Hukuhara differentiation suffers a grave disadvantage, i.e., the solution has the property that the diameter (operatorname{diam}[x t)]^{alpha}) is nondecreasing in t, and so it is very hard to get any deep results on qualitative theory for fuzzy differential equations, such as asymptotic property, periodicity, bifurcation.
Further, they have the disadvantage (i) of providing no information on whether the genes are indeed expressed under a certain condition or not, and (ii) of missing or incorrectly predicting genes that differ from the considered standard codon scheme [ 7].
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It does, however, present some disadvantages (i.e. water absorption) related to the experimental procedures.
The perceived advantages of electric driving need to offset the perceived disadvantages, i.e. perceived complexity and incompatibility with current driving and fueling patterns.
The FAIR highway, however, has two potential disadvantages: (i) the toll level is increased when subsidizing the low-income commuters and (ii) the divergence of lane utilization is aggravated on the FAIR highways compared to the do-nothing case.
After analyzing this formula, we can find the following disadvantages: (i) Except for space per capita, other objective factors are not considered, which means that it is not a precise formula.
However, PIRF-Nav has three main disadvantages: (i) the computational expense of PIRF-Nav is beyond real-time, (ii) it utilizes a large amount of memory in the redundant process of keeping signatures of places, and (iii) it is ill-suited to an indoor environment.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com