Optimal Voltage Control Using an Equivalent Model of a Low-Voltage Network Accommodating Inverter-Interfaced Distributed Generators

The penetration of inverter-based distributed generators (DGs), which can control their reactive power outputs, has increased for low-voltage (LV) systems. The power outputs of DGs affect the voltage and power flow of both LV and medium-voltage (MV) systems that are connected to the LV system. Therefore, the effects of DGs should be considered in the volt/var optimization (VVO) problem of LV and MV systems. However, it is inefficient to utilize a detailed LV system model in the VVO problem because the size of the VVO problem is increased owing to the detailed LV system models. Therefore, in order to formulate and solve the VVO problem in an efficient way, in this paper, a new equivalent model for an LV system including inverter-based DGs is proposed. The proposed model is developed based on an analytical approach rather than a heuristic-fitting one, and it therefore enables the VVO problem to be solved using a deterministic algorithm (e.g., interior point method). In addition, a method to utilize the proposed model for the VVO problem is presented. In the case study, the results verify that the computational burden to solve the VVO problem is significantly reduced without loss of accuracy by the proposed model.11Ysciescopu

Assimilation of Precipitation Measurement Missions Microwave Radiance Observations With GEOS-5

The Global Precipitation Mission (GPM) Core Observatory satellite was launched in February, 2014. The GPM Microwave Imager (GMI) is a conically scanning radiometer measuring 13 channels ranging from 10 to 183 GHz and sampling between 65 S 65 N. This instrument is a successor to the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI), which has observed 9 channels at frequencies ranging 10 to 85 GHz between 40 S 40 N since 1997. This presentation outlines the base procedures developed to assimilate GMI and TMI radiances in clear-sky conditions, including quality control methods, thinning decisions, and the estimation of, observation errors. This presentation also shows the impact of these observations when they are incorporated into the GEOS-5 atmospheric data assimilation system

Time-resolved pathogenic gene expression analysis of the plant pathogen Xanthomonas oryzae pv. oryzae

Virulence of wild-type and mutant Xoo strains on rice. (DOCX 16 kb

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

A CRY-BIC negative-feedback circuitry regulating blue light sensitivity of Arabidopsis.

Cryptochromes are blue light receptors that regulate various light responses in plants. Arabidopsis cryptochrome 1 (CRY1) and cryptochrome 2 (CRY2) mediate blue light inhibition of hypocotyl elongation and long-day (LD) promotion of floral initiation. It has been reported recently that two negative regulators of Arabidopsis cryptochromes, Blue light Inhibitors of Cryptochromes 1 and 2 (BIC1 and BIC2), inhibit cryptochrome function by blocking blue light-dependent cryptochrome dimerization. However, it remained unclear how cryptochromes regulate the BIC gene activity. Here we show that cryptochromes mediate light activation of transcription of the BIC genes, by suppressing the activity of CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), resulting in activation of the transcription activator ELONGATED HYPOCOTYL 5 (HY5) that is associated with chromatins of the BIC promoters. These results demonstrate a CRY-BIC negative-feedback circuitry that regulates the activity of each other. Surprisingly, phytochromes also mediate light activation of BIC transcription, suggesting a novel photoreceptor co-action mechanism to sustain blue light sensitivity of plants under the broad spectra of solar radiation in nature