An introduction of small-scale intelligent manufacturing system

Embargoed OA, manuscript version after 24 months from publishing date. Link to publishers version: http://doi.org/10.1109/SIMS.2016.7802896Manufacturing companies in Northern Peripheral and Arctic region are predominately small and medium-sized and face considerable challenges like geographical isolation and a lack of benefits offered by industrial clusters. For the ultimate goal of enhancing their competitiveness in a global market, it is imperative for companies to innovate or adopt innovations in order to quickly response to changes in market, meet customer demands, reduce time-to-market and lower cost. A novel concept for small-scale intelligent manufacturing systems (SIMS) is introduced, in which diverse methods and innovative technologies can be applied and integrated. This paper gives an introduction of SIMS, defines its design objectives, and summarizes major relevant tools, techniques and paradigms for the development of SIMS, to generate a facilitative environment for small and medium-scale manufacturing enterprises to embrace new and innovative technologies

Development of the Lymphoma Enterprise Architecture Database: A caBIG(tm) Silver level compliant System

Lymphomas are the fifth most common cancer in United States with numerous histological subtypes. Integrating existing clinical information on lymphoma patients provides a platform for understanding biological variability in presentation and treatment response and aids development of novel therapies. We developed a cancer Biomedical Informatics Grid™ (caBIG™) Silver level compliant lymphoma database, called the Lymphoma Enterprise Architecture Data-system™ (LEAD™), which integrates the pathology, pharmacy, laboratory, cancer registry, clinical trials, and clinical data from institutional databases. We utilized the Cancer Common Ontological Representation Environment Software Development Kit (caCORE SDK) provided by National Cancer Institute’s Center for Bioinformatics to establish the LEAD™ platform for data management. The caCORE SDK generated system utilizes an n-tier architecture with open Application Programming Interfaces, controlled vocabularies, and registered metadata to achieve semantic integration across multiple cancer databases. We demonstrated that the data elements and structures within LEAD™ could be used to manage clinical research data from phase 1 clinical trials, cohort studies, and registry data from the Surveillance Epidemiology and End Results database. This work provides a clear example of how semantic technologies from caBIG™ can be applied to support a wide range of clinical and research tasks, and integrate data from disparate systems into a single architecture. This illustrates the central importance of caBIG™ to the management of clinical and biological data

Development of small-scale intelligent manufacturing system (SIMS). A case study at Stella Polaris AS

Manufacturers in the resourceful Northern Peripheral and Arctic (NPA) region are mostly small and medium-sized enterprises (SMEs). Facing challenges primarily caused by the size and location of enterprises, these SMEs are constantly driven to take new measures to survive from the fierce competition against its domestic and international competitors, under the industrial environments of globalization of markets, rapidly changing customer needs, manufacturing paradigm shift to personalization, and the coming era of Industry 4.0. Originally aiming at enhancing the competitiveness of SMEs in the NPA region, a novel concept for small-scale intelligent manufacturing systems (SIMS) has been put forward and introduced [5] regarding its design objectives and applicable technologies. The major purpose of this project is to further develop the concept of SIMS in order to support SMEs in overcoming challenges from changing customer needs and unstable market conditions, transforming their manufacturing processes towards personalized production, and adapting themselves to the upcoming Industry 4.0 er

Mutational Analyses of Packaging Signals in Influenza Virus PA, PB1, and PB2 Genomic RNA Segments▿

The influenza A virus genome consists of eight negative-sense RNA segments that must each be packaged to produce an infectious virion. We have previously mapped the minimal cis-acting regions necessary for efficient packaging of the PA, PB1, and PB2 segments, which encode the three protein subunits of the viral RNA polymerase. The packaging signals in each of these RNAs lie within two separate regions at the 3′ and 5′ termini, each encompassing the untranslated region and extending up to 80 bases into the adjacent coding sequence. In this study, we introduced scanning mutations across the coding regions in each of these RNA segments in order to finely define the packaging signals. We found that mutations producing the most severe defects were confined to a few discrete 5′ sites in the PA or PB1 coding regions but extended across the entire (80-base) 5′ coding region of PB2. In sequence comparisons among more than 580 influenza A strains from diverse hosts, these highly deleterious mutations were each found to affect one or more conserved bases, though they did not all lie within the most broadly conserved portions of the regions that we interrogated. We have introduced silent and conserved mutations to the critical packaging sites, which did not affect protein function but impaired viral replication at levels roughly similar to those of their defects in RNA packaging. Interestingly, certain mutations showed strong tendencies to revert to wild-type sequences, which implies that these putative packaging signals are critical for the influenza life cycle

An-1 encodes a basic helix-loop-helix protein that regulates awn development, grain size, and grain number in rice

Long awns are important for seed dispersal in wild rice (Oryza rufipogon), but are absent in cultivated rice (Oryza sativa). The genetic mechanism involved in loss-of-awn in cultivated rice remains unknown. We report here the molecular cloning of a major quantitative trait locus, An-1, which regulates long awn formation in O. rufipogon. An-1 encodes a basic helix-loop-helix protein, which regulates cell division. The nearly-isogenic line (NIL-An-1) carrying a wild allele An-1 in the genetic background of the awnless indica Guangluai4 produces long awns and longer grains, but significantly fewer grains per panicle compared with Guangluai4. Transgenic studies confirmed that An-1 positively regulates awn elongation, but negatively regulates grain number per panicle. Genetic variations in the An-1 locus were found to be associated with awn loss in cultivated rice. Population genetic analysis of wild and cultivated rice showed a significant reduction in nucleotide diversity of the An-1 locus in rice cultivars, suggesting that the An-1 locus was a major target for artificial selection. Thus, we propose that awn loss was favored and strongly selected by humans, as genetic variations at the An-1 locus that cause awn loss would increase grain numbers and subsequently improve grain yield in cultivated rice