Ultrasonographic abdominal adipose tissue thickness for the prediction of gestational diabetes mellitus: A meta-analysis

Obesity has been linked to the risk of gestational diabetes mellitus (GDM). The meta-analysis aimed to assess the predictive role of ultrasonographic measurements of the abdominal adipose tissue thickness for GDM in pregnant women. Cohort studies evaluating the association between abdominal subcutaneous and/or visceral adipose thickness (SAT and/or VAT) and subsequent risk of GDM were retrieved from PubMed, Embase, and Web of Science databases. Only studies with SAT/VAT measured before the diagnosis of GDM were included. Random-effects models incorporating the influence of potential heterogeneity were used to pool the results. A total of 13 studies involving 5616 pregnant women were included. Pooled results showed that both a high abdominal SAT (odds ratio [OR] for per 1-cm increment: 1.23, 95% confidence interval [CI]: 1.07 to 1.41, P = 0.003, I2 = 13%; OR for high versus low category: 3.42, 95% CI: 2.31 to 5.07, P < 0.001, I2 = 0%) and VAT (OR for per 1-cm increment: 1.54, 95% CI: 1.16 to 2.06, P = 0.003, I2 = 63%; OR for high versus low category: 5.73, 95% CI: 3.39 to 9.77, P < 0.001, I2 = 31%) at early stages of pregnancy were associated with a higher subsequent risk of GDM. Subgroup analysis based on study design, timing of ultrasound examination, GDM diagnostic criteria, and study quality score showed consistent results. In conclusion, ultrasound-measured abdominal adipose tissue thickness may be useful for predicting the subsequent risk of GDM in pregnant women

Pre-Jordan Algebras

The purpose of this paper is to introduce and study a notion of pre-Jordan algebra. Pre-Jordan algebras are regarded as the underlying algebraic structures of the Jordan algebras with a nondcgenerate symplectic form. They are the algebraic structures behind the Jordan Yang-Baxter equation and Rota-Baxter operators in terms of O-operators of Jordan algebras introduced in this paper. Pre-Jordan algebras are analogues for Jordan algebras of pre-Lie algebras and fit into a bigger framework with a close relationship with dendriform algebras. The anticommutator of a pre-Jordan algebra is a Jordan algebra and the left multiplication operators give a representation of the Jordan algebra, which is the beauty of such a structure. Furthermore, we introduce a notion of O-operator of a pre-Jordan algebra which gives an analogue of the classical Yang-Baxter equation in a pre-Jordan algebra

Optimizing Grain Yield and Water Use Efficiency Based on the Relationship between Leaf Area Index and Evapotranspiration

Achieving optimal balance between maize yield and water use efficiency is an important challenge for irrigation maize production in arid areas. In this study, we conducted an experiment in Xinjiang China in 2016 and 2017 to quantify the response of maize yield and water use to plant density and irrigation schedules. The treatments included four irrigation levels: 360 (W1), 480 (W2), 600 (W3), and 720 mm (W4), and five plant densities: 7.5 (D1), 9.0 (D2), 10.5 (D3), 12.0 (D4), and 13.5 plants m−2 (D5). The results showed that increasing the plant density and the irrigation level could both significantly increase the leaf area index (LAI). However, LAI expansion significantly increased evapotranspiration (ETa) under irrigation. The combination of irrigation level 600 mm (W3) and plant density 12.0 plants m−2 (D4) produced the highest maize yield (21.0–21.2 t ha−1), ETa (784.1–797.8 mm), and water use efficiency (WUE) (2.64–2.70 kg m−3), with an LAI of 8.5–8.7 at the silking stage. The relationship between LAI and grain yield and evapotranspiration were quantified, and, based on this, the relationship between water use and maize productivity was analyzed. Moreover, the optimal LAI was established to determine the reasonable irrigation level and coordinate the relationship between the increase in grain yield and the decrease in water use efficiency

Optimizing Planting Density to Increase Maize Yield and Water Use Efficiency and Economic Return in the Arid Region of Northwest China

High grain yield and water use efficiency (WUE) are the key goals when producing maize (Zea mays L.) under irrigation in arid areas. Increasing the planting density and optimizing irrigation are important agronomic practices for increasing the maize grain yield and WUE. A two-year field experiment was conducted to investigate the effects of planting density and irrigation on the maize grain yield, WUE, and economic return of spring maize under a mulch drip irrigation system in Xinjiang, Northwest China. The experiment included four irrigation levels and five planting densities. The results showed that the reduction of irrigation decreased the yield and evapotranspiration (ETc) but improved the WUE. Increasing the planting density increased the ETc, but there was a quadratic curve relationship between yield and WUE and planting density. Treatment with 600 mm of water and 12 plants m&minus;2 obtained the highest grain yield (21.0&ndash;21.2 t ha&minus;1) and economic return (3036.0 USD ha&minus;1) and a relatively high WUE (2.64&ndash;2.70 kg kg&minus;1). Therefore, a reasonable increase in planting density and an appropriate reduction of irrigation combined with drip irrigation under a mulch system can simultaneously achieve high yields and economic return and high WUE in maize production

Surface reconstruction models of DEM.

<p>Surface reconstruction models of DEM.</p

Surface reconstruction of car wheel.

<p>Surface reconstruction of car wheel.</p

Select seeds, find the points near voronoi edges and construct meshes in 2D manifold case.

<p>Select seeds, find the points near voronoi edges and construct meshes in 2D manifold case.</p