Perennial Weed Control During Fallow Periods in the Texas High Plains

6 pp.A three-phase perennial weed control program is detailed in this publication. It includes a chart with chemical suggestions for controlling specific weeds

Sorghum Growth and Development

8 pp., 1 table, 8 photosSorghum is well adapted to Texas, and its ability to yield consistently makes it popular with growers. This publication discusses sorghum plant biology and growth

Sorghum Tillage in the Texas High Plains

6 pp., 1 figure, 1 tableWater management is the most important factor in sorghum production. Tillage practices can affect the water content of the soil and play a large role in successful sorghum production. This publication discusses the types of tillage and ways to reduce evaporation and erosion and conserve water

Weed Control Recommendations in Wheat

24 pp., 7 tables, 2 figuresThis publication offers suggestions for controlling weeds in wheat using cultural, mechanical and chemical methods

Grain sorghum response and Palmer amaranth control with postemergence application of fluthiacet-methyl

Palmer amaranth is a problematic weed in grain sorghum production in central United States. Due to limited herbicide options available and ever increasing herbicide-resistant weed species, there is a demand for new mode-of-action herbicides for use in grain sorghum. Fluthiacet-methyl is a relatively new active ingredient that inhibits the enzyme protoporphyrinogen oxidase in target plants. Field studies were conducted at three sites in central United States in 2010 and 2011 to evaluate crop response and Palmer amaranth control with postemergence application of fluthiacet-methyl in grain sorghum. Treatments included fluthiacet-methyl at 4.8 and 7.2 g active ingredient (a.i.) haˉ¹ alone and tank-mixed with 2,4-D amine at 260 g acid equivalent (a.e.) haˉ¹ or atrazine at 840 g a.i. haˉ¹. Carfentrazone at 8.8 g a.i. haˉ¹, atrazine at 840 g haˉ¹, and a non-treated control were also included. Fluthiacet-methyl treatments caused 9–38% crop injury at 4 ± 1 days after treatment. Tank-mixing atrazine with fluthiacet-methyl seldom affected crop injury, while mixing 2,4-D with fluthiacet-methyl often reduced crop injury. Generally, injury caused by fluthiacet-methyl alone or in combination with atrazine or 2,4-D disappeared within 3 weeks after treatment. Grain yields were reduced in one trial, when 2,4-D mixed with 4.8 or 7.2 g haˉ¹ of fluthiacet-methyl caused 18% and 13% plant lodging and 24% and 14% grain yield loss, respectively. Across site-years, fluthiacet-methyl alone at 4.8 or 7.2 g haˉ¹ provided 55–95% control of Palmer amaranth. Greater Palmer amaranth control (≥75%) with fluthiacet-methyl alone was achieved when weeds were small or density was low at the time of spraying. Tank-mixing atrazine with fluthiacet-methyl increased Palmer amaranth control and sorghum yields considerably. Tank-mixing 2,4-D with fluthiacet-methyl also increased Palmer amaranth control, but to lesser extent and less consistently than with atrazine. Results indicated that fluthiacet-methyl has potential for use in grain sorghum to combat weeds resistant to acetolactase synthase-inhibitors, triazines, and synthetic auxin herbicides. Tank-mixing atrazine or 2,4-D with fluthiacet-methyl is desirable for effective Palmer amaranth control

Yield determination of maize hybrids under limited irrigation

Hybrid adoption, irrigation, and planting density are important factors for maize (Zea mays L.) production in semiarid regions. For this study, a 2-yr field experiment was conducted in the Texas High Plains to investigate maize yield determination, seasonal evapotranspiration (ETc), and water-use efficiency (WUE) under limited irrigation. Two hybrids (N74R, a conventional hybrid, and N75H, a drought-tolerant (DT) hybrid) were planted at three water regimes (I100, I75, and I50, referring to 100%, 75%, and 50% of the evapotranspiration requirement) and three planting densities (PD 6, PD 8, and PD 10, referring to 6, 8, and 10 seeds m−2). At I50, drought stress reduced grain yield by 4.78 t/ha for the conventional hybrid but only 4.22 t/ha for the DT hybrid, when compared to I100. Although ETc decreased at I75 and I50, the highest WUE was found at I75. The DT hybrid did not yield more than the conventional hybrid but had greater yield stability at lower water regimes and extracted less soil water. Drought decreased biomass, harvest index, and kernel weight but did not affect kernel number. Higher planting densities increased biomass and kernel number but decreased kernel weight. Kernel number and kernel weight of the conventional hybrid were more sensitive to planting density than the DT hybrid. These data demonstrated that limited irrigation at I75 is an effective way to save water and maintain the maize yield in semiarid areas, and that DT hybrid shows a greater yield stability to plant density under water stress

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe