ILipo-PseAAC: Identification of Lipoylation Sites Using Statistical Moments and General PseAAC

Lysine Lipoylation is a protective and conserved Post Translational Modification (PTM) in proteomics research like prokaryotes and eukaryotes. It is connected with many biological processes and closely linked with many metabolic diseases. To develop a perfect and accurate classification model for identifying lipoylation sites at the protein level, the computational methods and several other factors play a key role in this purpose. Usually, most of the techniques and different traditional experimental models have a very high cost. They are time-consuming; so, it is required to construct a predictor model to extract lysine lipoylation sites. This study proposes a model that could predict lysine lipoylation sites with the help of a classification method known as Artificial Neural Network (ANN). The ANN algorithm deals with the noise problem and imbalance classification in lipoylation sites dataset samples. As the result shows in ten-fold cross-validation, a brilliant performance is achieved through the predictor model with an accuracy of 99.88%, and also achieved 0.9976 as the highest value of MCC. So, the predictor model is a very useful and helpful tool for lipoylation sites prediction. Some of the residues around lysine lipoylation sites play a vital part in prediction, as demonstrated during feature analysis. The wonderful results reported through the evaluation and prediction of this model can provide an informative and relative explanation for lipoylation and its molecular mechanisms.     

Network restoration under dual failures using path-protecting preconfigured cycles

This paper presents a design algorithm for networks with a restoration mechanism that provides end-to-end path protection to a set of demands with specified working routes, where demands must survive one or two failures in optical networks and these failures may occur almost instantaneously. Each of the demands protected from two failures is assigned two restoration routes and restoration wavelengths on a cycle. A demand protected from a single failure is assigned one restoration route and restoration wavelengths on a cycle. These assignments are preconfigured so that switching and wavelength conversions are not needed at intermediate nodes of restoration routes. Splitting of demand across multiple restoration routes upon a failure occurrence is not allowed. The algorithm generates a large number of candidate Path-Protecting Preconfigured Cycles (PP-PCs). A candidate cycle may provide protection to a mix of demands requiring different protection levels, where demands may share under certain conditions restoration wavelengths even if they are exposed to common failure scenarios and have overlapping restoration routes. A near-optimal set of preconfigured cycles is selected from among all candidates, attempting to minimize the total cost of restoration wavelengths while ensuring that each demand is assigned to a single preconfigured cycle. This is achieved by solving a set covering problem followed by deleting duplicate demand assignments and by resolving wavelength assignment conflicts.     

Synchronized manufacturing at final assembly and feeder shops

Many manufacturing environments consist of a final assembly shop that receives components from various feeder shops. Suppose the final assembly shop assembles a mix of products, each requiring varying amounts of different components. Thus, the sequence in which products are assembled imposes time-dependent demands on the feeder shops. Such problems are often found in the assembly of high-tech telecommunications systems and in the assembly of mixed models of automobiles. We develop a variety of models that link the work-in-process inventory in the feeder shop and the finished component inventory to the component production interval and the final assembly sequence. The manufacturing disciplines considered include push, look-ahead and kanban. Feeder shops are assumed to manufacture components continuously, periodically, or at a fixed lot size. Simple performance characteristics of the feeder shop are derived to provide insight into synchronized manufacturing issues and to help evaluate the effect of different final assembly sequences on feeder shops.     

Integrated demand-responsive scheduling of maintenance and transportation operations in military supply chains

The management of a military supply chain (SC) involves the integration of production, packaging, warehousing, repair, maintenance and transportation of army supplies. In this paper, we focus on the integrated demand-responsive scheduling of maintenance and transportation operations within the SC. We consider a modular representation of a SC, in which the maintenance and transportation operations constitute the corresponding modules. An efficient integration of these operations is carried out by an additional controlling (commanding) module. We describe and analyse the optimisation problems arising in each module. The main contribution of the paper is that the analysis and optimisation of the controlling module permit to enhance the performance of the entire SC. Computational experiments prove the validity and effectiveness of the suggested models.