Tripartite degrons confer diversity and specificity on regulated protein degradation in the ubiquitin-proteasome system

Specific signals (degrons) regulate protein turnover mediated by the ubiquitin-proteasome system. Here we systematically analyse known degrons and propose a tripartite model comprising the following: (1) a primary degron (peptide motif) that specifies substrate recognition by cognate E3 ubiquitin ligases, (2) secondary site(s) comprising a single or multiple neighbouring ubiquitinated lysine(s) and (3) a structurally disordered segment that initiates substrate unfolding at the 26S proteasome. Primary degron sequences are conserved among orthologues and occur in structurally disordered regions that undergo E3-induced folding-on-binding. Posttranslational modifications can switch primary degrons into E3-binding-competent states, thereby integrating degradation with signalling pathways. Degradation-linked lysines tend to be located within disordered segments that also initiate substrate degradation by effective proteasomal engagement. Many characterized mutations and alternative isoforms with abrogated degron components are implicated in disease. These effects result from increased protein stability and interactome rewiring. The distributed nature of degrons ensures regulation, specificity and combinatorial control of degradation. © 2016 Nature America, Inc

Implementation of Adaptive Neural Networks Controller for NXT SCARA Robot System

Several neural network controllers for robotic manipulators have been developed during the last decades due to their capability to learn the dynamic properties and the improvements in the global stability of the system. In this paper, an adaptive neural controller has been designed with self learning to resolve the problems caused by using a classical controller. A comparison between the improved unsupervised adaptive neural network controller and the P controller for the NXT SCARA robot system is done, and the result shows the improvement of the self learning controller to track the determined trajectory of robotic automated controllers with uncertainties. Implementation and practical results were designed to guarantee online real-time

Management of citrus nematode (Tylenchulus semipenetrans) by certain plant species

The effect of five plant species (Tagetes erecta L., Datura stramonium L., Nerium oleander L., Ipomea palmata L. and Santolina chamaecyparissus L.) on severity of Tylenchulus semipenetrans on citrus rootstocks (Citrus sinensis, C. reticulate grafted on C. aurantium and C. sinensis grafted on C. aurantium) was investigated in greenhouse and laboratory conditions. All plant species reduced the larval population of T. semipenetrans and their effect increase as the period increase. I. palmata gave the highest percentage of reduction when intercropped with C.sinensis and C. reticulate grafted on C. aurantium 20.5 and 25% respectively. N. oleander and D. stramonium came next when intercropped with C. reticulate grafted on C. aurantium 13.5 and 11% respectively, While D. stramonium gave the highest percentage of reduction when intercropped with C. sinensisgrafted on C. aurantium. And T. erecta gave the lowest percentage of reduction when intercropped with the three rootstocks

Breakup of Round Nonturbulent Liquid Jets in Gaseous Crossflow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76074/1/AIAA-3749-644.pd

Breakup of turbulent liquid jets in still gases

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76376/1/AIAA-1999-3759-754.pd

Improving collaborative filtering using lexicon-based sentiment analysis

Since data is available increasingly on the Internet, efforts are needed to develop and improve recommender systems to produce a list of possible favorite items. In this paper, we expand our work to enhance the accuracy of Arabic collaborative filtering by applying sentiment analysis to user reviews, we also addressed major problems of the current work by applying effective techniques to handle the scalability and sparsity problems. The proposed approach consists of two phases: the sentiment analysis and the recommendation phase. The sentiment analysis phase estimates sentiment scores using a special lexicon for the Arabic dataset. The item-based and singular value decomposition-based collaborative filtering are used in the second phase. Overall, our proposed approach improves the experiments’ results by reducing average of mean absolute and root mean squared errors using a large Arabic dataset consisting of 63,000 book reviews