Preliminary Results: Complementary C4:C3 Grazing Systems

Native warm-season grasses (NWSG) can produce high quality forage and high rates of gain for beef cattle. However, little data is available on how NWSG affect the productivity of cow-calf operations on a farm scale. Therefore, we implemented an experiment at three sites, Booneville, AR, Linneus, MO and Louisville, TN, with cow-calf pairs (mature cows over ≥ 3 years old, spring calving). We evaluated two forage systems that mix either a drought or drought/flood tolerant native C4 species [big bluestem (BB) blend or eastern gamagrass (EG)] with a cool-season perennial, tall fescue (TF), and compared them to the most frequently used forage system within the Fescue Belt region, one that relies on TF only. The TN study site contains EG, with big bluestem at the MO site, and both big bluestem and EG at the AR site. Cattle (n = 12 pairs per experimental unit) were weighed yearly before initial grazing and again after final removal. Forage samples (n = 15) were collected at the beginning of grazing and once every twenty-eight days during the grazing season, and finally, at the conclusion of grazing. Harvested forages were tested for forage nutritive content (CP, NDF, ADF) using NIRS. Hay produced per forage system was documented by counting bales and weights of subsamples. The AR site was not able to participate in the first year of the study. Overall, there were no statistical differences between treatments in the first grazing season for either cattle or forage measures. However, cattle spent less time on NWSG in 2021 at the TN site to enable renovation of EG to be completed. Also, TF stands had a significant proportion of volunteer warm-season grasses within the pastures. Data from the second year of the study are currently under analysis

Comparison of X-ray and gamma-ray dose-response curves for pink somatic mutations in Tradescantia clone 02

Microdosimetric data indicate that the mean specific energy,zeta, produced by individual charged particles from X rays and gamma rays is different for the two radiation qualities by nearly a factor of two. In order to test whether this influences the initial, linear component in the dose-effect relations, a comparison was made between dose-response curves for pink somatic mutations inTradescantia clone 02 stamen hairs following X and gamma irradiations. Absorbed doses ranged from 2.66 to 300 rad. The results are in agreement with predictions made on the basis of microdosimetric data. At low doses gamma rays are substantially less effective than X rays. The RBE of gamma rays vs. X rays at low doses was approximately 0.6, a value lower than those usually reported in other experimental systems

Suppression of Phase Separation in LiFePO4 Nanoparticles During Battery Discharge

Using a novel electrochemical phase-field model, we question the common belief that LixFePO4 nanoparticles separate into Li-rich and Li-poor phases during battery discharge. For small currents, spinodal decomposition or nucleation leads to moving phase boundaries. Above a critical current density (in the Tafel regime), the spinodal disappears, and particles fill homogeneously, which may explain the superior rate capability and long cycle life of nano-LiFePO4 cathodes.Comment: 27 pages, 8 figure

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed

Antihypertensive, antidyslipidemic and endothelial modulating activities of Orchis mascula

The objective of this study was to investigate the possible mode(s) of action for the medicinal use of Orchis mascula (OM) (family Orchidaceae) in hypertension and dyslipidemia. In spontaneously hypertensive rats (SHRs), OM significantly (

Disturbed Expression of Splicing Factors in Renal Cancer Affects Alternative Splicing of Apoptosis Regulators, Oncogenes, and Tumor Suppressors

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer. One of the processes disturbed in this cancer type is alternative splicing, although phenomena underlying these disturbances remain unknown. Alternative splicing consists of selective removal of introns and joining of residual exons of the primary transcript, to produce mRNA molecules of different sequence. Splicing aberrations may lead to tumoral transformation due to synthesis of impaired splice variants with oncogenic potential. In this paper we hypothesized that disturbed alternative splicing in ccRCC may result from improper expression of splicing factors, mediators of splicing reactions. METHODOLOGY/PRINCIPAL FINDINGS: Using real-time PCR and Western-blot analysis we analyzed expression of seven splicing factors belonging to SR proteins family (SF2/ASF, SC35, SRp20, SRp75, SRp40, SRp55 and 9G8), and one non-SR factor, hnRNP A1 (heterogeneous nuclear ribonucleoprotein A1) in 38 pairs of tumor-control ccRCC samples. Moreover, we analyzed splicing patterns of five genes involved in carcinogenesis and partially regulated by analyzed splicing factors: RON, CEACAM1, Rac1, Caspase-9, and GLI1. CONCLUSIONS/SIGNIFICANCE: We found that the mRNA expression of splicing factors was disturbed in tumors when compared to paired controls, similarly as levels of SF2/ASF and hnRNP A1 proteins. The correlation coefficients between expression levels of specific splicing factors were increased in tumor samples. Moreover, alternative splicing of five analyzed genes was also disturbed in ccRCC samples and splicing pattern of two of them, Caspase-9 and CEACAM1 correlated with expression of SF2/ASF in tumors. We conclude that disturbed expression of splicing factors in ccRCC may possibly lead to impaired alternative splicing of genes regulating tumor growth and this way contribute to the process of carcinogenesis

WaterStressAT - Climate change induced water stress - participatory modeling to identify risks and opportunities in Austrian regions

In Austria, increase in demand as well as climate change might create local and seasonal hot-spots of water stress. It is thus important to understand the status quo and future development of these phenomena to identify potential areas of tension. WaterStressAT assesses water availability and demand in two Austrian case studies under a set of regional development and climate change scenarios