An RNA Sequencing Analysis of Glaucoma Genesis in Mice

Glaucoma is the leading cause of irreversible blindness in people over the age of 60, accounting for 6.6 to 8% of all blindness in 2010, but there is still much to be learned about the genetic origins of the eye disease. With the modern development of Next-Generation Sequencing (NGS) technologies, scientists are starting to learn more about the genetic origins of Glaucoma. This research uses differential expression (DE) and gene ontology (GO) analyses to study the genetic differences between mice with severe Glaucoma and multiple control groups. Optical nerve head (ONH) and retina data samples of genome-wide RNA expression from NCBI (NIH) are used for pairwise comparison experimentation. In addition, principal component analysis (PCA) and dispersion visualization methods are employed to perform quality control tests of the sequenced data. Genes with skewed gene counts are also identified, as they may be marker genes for a particular severity of Glaucoma. The gene ontologies found in this experiment support existing knowledge of Glaucoma genesis, providing confidence that the results were valid. Future researchers can thoroughly study the gene lists generated by the DE and GO analyses to find potential activator or protector genes for Glaucoma in mice to develop drug treatments or gene therapies to slow or stop the progression of the disease. The overall goal is that in the future, such treatments can be made for humans as well to improve the quality of life for human patients with Glaucoma and reduce Glaucoma blindness rates.Comment: 6 pages, 6 figure

Modeling a supply chain using a network of queues

International audienceIn this paper, a supply chain is represented as a two-input, three-stage queuing network. An input order to the supply chain is represented by two stochastic variables, one for the occurrence time and the other for the quantity of items to be delivered in each order. The objective of this paper is to compute the minimum response time for the delivery of items to the final destination along the three stages of the network. The average number of items that can be delivered with this minimum response time constitute the optimum capacity of the queuing network. After getting serviced by the last node (a queue and its server) in each stage of the queuing network, a decision is made to route the items to the appropriate node in the next stage which can produce the least response time

Queuing network model of uniformly distributed arrivals in a distributed supply chain using subcontracting

International audienceIn this paper, a supply chain (four-input three-stage queuing network) receives uniformly distributed orders from clients. An input order is represented by two stochastic variables, occurrence time and the quantity of items to be delivered. The objective of this work is to compute the minimum response time, and thus the average number of items (optimum capacity) that can be delivered with this response time. Performance measures such as average queue lengths, average response times, and average waiting times of the jobs in the supply chain, and in the equivalent single-server network are derived, plotted and discussed

Activity routing in a distributed supply chain: Performance evaluation with two inputs

International audienceIn this paper, an industrial system is represented as a 2-input, three-stage queuing network. The two input queuing network receives orders from clients, and the orders are waiting to be served. Each order comprises (i) time of occurrence of the orders and (ii) quantity of items to be delivered in each order. The objective of this paper is to compute the minimum response time for the delivery of items to the final destination along the three stages of the network. The average number of items that can be delivered with this minimum response time constitute the optimum capacity of the queuing network. After getting serviced by the last node (a queue and its server) in each stage of the queuing network, a decision is made to route the items to the appropriate node in the next stage which can produce the least response time. Performance measures such as average queue lengths, average response times, and average waiting times of the jobs in the 2-input network are derived and plotted. Closed-form expressions for the equivalent service rate, equivalent average queue lengths, and equivalent response and waiting times of a single queue with a single server representing the 2-input queuing network are also derived and plotted

A hybrid open queuing network model approach for multi-threaded dataflow architecture

International audienceMulti-threading has been proposed as an execution model for massively built parallel processors. Due to the large amount of potential parallelism, resource management is a critical issue in multi-threaded architecture. The challenge of multi-threading is to hide the latency by switching among a set of ready threads and thus to improve the processor utilization. Threads are dynamically scheduled to execute based on availability of data. In this paper, two hybrid open queuing network models are proposed. Two sets of processors: synchronization processors and execution processors exist. Each processor is modeled as a server serving a single-queue or multiple-servers serving a single-queue. Performance measures like response times, system throughput and average queue lengths are evaluated for both the hybrid models. The utilizations of the two models are derived and compared with each other. A mean value analysis is performed and different performance measures are plotted

Performance of wireless multiple access communications using punctured codes over slowly fading channels in distributed diagnostic systems

International audiencePerformance of wireless multiple access communications using punctured codes over slowly fading channels in distributed diagnostic system

Dataflow modelling in distributed diagnostic processing systems: a closed queuing network model with multiple servers

International audienceIn this paper, a closed queuing network model with multiple servers has been proposed to model dataflow in distributed diagnosticprocessing systems. Multi-threading is useful in reducing the latency by switching among a set of threads in order to improve the processor utilization. Two sets of processors, synchronization and execution processors exist. Synchronization processors handle load/store operations and execution processors handle arithmetic/logic and control operations. A closed queuing network model is suitable for large number of job arrivals. The normalization constant is derived using a recursive algorithm for the given model. Performance measures such as average response times and average system throughput are derived and plotted against the tota

A hybrid closed queuing network approach to model dataflow in networked distributed processors

International audienceIn this paper, a hybrid closed queuing network model has been proposed to model dataflow in networked distributed processing systems. Multi-threading is useful in reducing the latency by switching among a set of threads in order to improve the processor utilization. Two sets of processors, synchronization and execution processors exist. Synchronization processors handle load/store operations and execution processors handle arithmetic/logic and control operations. A closed queuing network model is suitable for large number of job arrivals. Both single server and multiple server models are discussed. The normalization constant is derived using a recursive algorithm for the given model. Performance measures such as average response times and average system throughput are derived and plotted against the total number of processors in the closed queuing network model. Other important performance measures like processor utilizations, average queue lengths, average waiting times and relative utilizations are also derived