Artificially Engineered Protein Polymers.

Science.gov (United States)

Yang, Yun Jung; Holmberg, Angela L; Olsen, Bradley D

2017-06-07

Modern polymer science increasingly requires precise control over macromolecular structure and properties for engineering advanced materials and biomedical systems. The application of biological processes to design and synthesize artificial protein polymers offers a means for furthering macromolecular tunability, enabling polymers with dispersities of ∼1.0 and monomer-level sequence control. Taking inspiration from materials evolved in nature, scientists have created modular building blocks with simplified monomer sequences that replicate the function of natural systems. The corresponding protein engineering toolbox has enabled the systematic development of complex functional polymeric materials across areas as diverse as adhesives, responsive polymers, and medical materials. This review discusses the natural proteins that have inspired the development of key building blocks for protein polymer engineering and the function of these elements in material design. The prospects and progress for scalable commercialization of protein polymers are reviewed, discussing both technology needs and opportunities.

Artificial Intelligence in Unity Game Engine

OpenAIRE

Yu, Li

2017-01-01

This thesis was conducted for Oulu Game Lab. The aim of this bachelor thesis was to develop in Oulu Game Lab a game called the feels good to be evil. The main purpose of the project was to develop a game and learn game development focus in the artificial intelligence area. This thesis has explained the theory behind Artificial Intelligence. The game was developed in Unity Game Engine with C# language, and also Panda Behavior Tree was used in this project as an asset. The result was the ...

Genetically engineered foods

Science.gov (United States)

Bioengineered foods; GMOs; Genetically modified foods ... helps speed up the process of creating new foods with desired traits. The possible benefits of genetic engineering include: More nutritious food Tastier food Disease- and ...

Synthetic alienation of microbial organisms by using genetic code engineering: Why and how?

Science.gov (United States)

Kubyshkin, Vladimir; Budisa, Nediljko

2017-08-01

The main goal of synthetic biology (SB) is the creation of biodiversity applicable for biotechnological needs, while xenobiology (XB) aims to expand the framework of natural chemistries with the non-natural building blocks in living cells to accomplish artificial biodiversity. Protein and proteome engineering, which overcome limitation of the canonical amino acid repertoire of 20 (+2) prescribed by the genetic code by using non-canonic amino acids (ncAAs), is one of the main focuses of XB research. Ideally, estranging the genetic code from its current form via systematic introduction of ncAAs should enable the development of bio-containment mechanisms in synthetic cells potentially endowing them with a "genetic firewall" i.e. orthogonality which prevents genetic information transfer to natural systems. Despite rapid progress over the past two decades, it is not yet possible to completely alienate an organism that would use and maintain different genetic code associations permanently. In order to engineer robust bio-contained life forms, the chemical logic behind the amino acid repertoire establishment should be considered. Starting from recent proposal of Hartman and Smith about the genetic code establishment in the RNA world, here the authors mapped possible biotechnological invasion points for engineering of bio-contained synthetic cells equipped with non-canonical functionalities. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genetic Engineering Workshop Report, 2010

Energy Technology Data Exchange (ETDEWEB)

Allen, J; Slezak, T

2010-11-03

The Lawrence Livermore National Laboratory (LLNL) Bioinformatics group has recently taken on a role in DTRA's Transformation Medical Technologies (TMT) program. The high-level goal of TMT is to accelerate the development of broad-spectrum countermeasures. To achieve this goal, there is a need to assess the genetic engineering (GE) approaches, potential application as well as detection and mitigation strategies. LLNL was tasked to coordinate a workshop to determine the scope of investments that DTRA should make to stay current with the rapid advances in genetic engineering technologies, so that accidental or malicious uses of GE technologies could be adequately detected and characterized. Attachment A is an earlier report produced by LLNL for TMT that provides some relevant background on Genetic Engineering detection. A workshop was held on September 23-24, 2010 in Springfield, Virginia. It was attended by a total of 55 people (see Attachment B). Twenty four (44%) of the attendees were academic researchers involved in GE or bioinformatics technology, 6 (11%) were from DTRA or the TMT program management, 7 (13%) were current TMT performers (including Jonathan Allen and Tom Slezak of LLNL who hosted the workshop), 11 (20%) were from other Federal agencies, and 7 (13%) were from industries that are involved in genetic engineering. Several attendees could be placed in multiple categories. There were 26 attendees (47%) who were from out of the DC area and received travel assistance through Invitational Travel Orders (ITOs). We note that this workshop could not have been as successful without the ability to invite experts from outside of the Beltway region. This workshop was an unclassified discussion of the science behind current genetic engineering capabilities. US citizenship was not required for attendance. While this may have limited some discussions concerning risk, we felt that it was more important for this first workshop to focus on the scientific state of

Modularity in developmental biology and artificial organs: a missing concept in tissue engineering.

Science.gov (United States)

Lenas, Petros; Luyten, Frank P; Doblare, Manuel; Nicodemou-Lena, Eleni; Lanzara, Andreina Elena

2011-06-01

Tissue engineering is reviving itself, adopting the concept of biomimetics of in vivo tissue development. A basic concept of developmental biology is the modularity of the tissue architecture according to which intermediates in tissue development constitute semiautonomous entities. Both engineering and nature have chosen the modular architecture to optimize the product or organism development and evolution. Bioartificial tissues do not have a modular architecture. On the contrary, artificial organs of modular architecture have been already developed in the field of artificial organs. Therefore the conceptual support of tissue engineering by the field of artificial organs becomes critical in its new endeavor of recapitulating in vitro the in vivo tissue development. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Selected Readings in Genetic Engineering

Science.gov (United States)

Mertens, Thomas R.; Robinson, Sandra K.

1973-01-01

Describes different sources of readings for understanding issues and concepts of genetic engineering. Broad categories of reading materials are: concerns about genetic engineering; its background; procedures; and social, ethical and legal issues. References are listed. (PS)

Engineering a Light-Attenuating Artificial Iris

Science.gov (United States)

Shareef, Farah J.; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

2016-01-01

Purpose Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. Methods The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Results Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Conclusions Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage. PMID:27116547

Engineering a Light-Attenuating Artificial Iris.

Science.gov (United States)

Shareef, Farah J; Sun, Shan; Kotecha, Mrignayani; Kassem, Iris; Azar, Dimitri; Cho, Michael

2016-04-01

Discomfort from light exposure leads to photophobia, glare, and poor vision in patients with congenital or trauma-induced iris damage. Commercial artificial iris lenses are static in nature to provide aesthetics without restoring the natural iris's dynamic response to light. A new photo-responsive artificial iris was therefore developed using a photochromic material with self-adaptive light transmission properties and encased in a transparent biocompatible polymer matrix. The implantable artificial iris was designed and engineered using Photopia, a class of photo-responsive materials (termed naphthopyrans) embedded in polyethylene. Photopia was reshaped into annular disks that were spin-coated with polydimethylsiloxane (PDMS) to form our artificial iris lens of controlled thickness. Activated by UV and blue light in approximately 5 seconds with complete reversal in less than 1 minute, the artificial iris demonstrates graded attenuation of up to 40% of visible and 60% of UV light. There optical characteristics are suitable to reversibly regulate the incident light intensity. In vitro cell culture experiments showed up to 60% cell death within 10 days of exposure to Photopia, but no significant cell death observed when cultured with the artificial iris with protective encapsulation. Nuclear magnetic resonance spectroscopy confirmed these results as there was no apparent leakage of potentially toxic photochromic material from the ophthalmic device. Our artificial iris lens mimics the functionality of the natural iris by attenuating light intensity entering the eye with its rapid reversible change in opacity and thus potentially providing an improved treatment option for patients with iris damage.

International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems

CERN Document Server

Dash, Subhransu; Panigrahi, Bijaya

2015-01-01

  The book is a collection of high-quality peer-reviewed research papers presented in Proceedings of International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems (ICAEES 2014) held at Noorul Islam Centre for Higher Education, Kumaracoil, India. These research papers provide the latest developments in the broad area of use of artificial intelligence and evolutionary algorithms in engineering systems. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

Hardness Optimization for Al6061-MWCNT Nanocomposite Prepared by Mechanical Alloying Using Artificial Neural Networks and Genetic Algorithm

Directory of Open Access Journals (Sweden)

Mehrdad Mahdavi Jafari

2017-06-01

Full Text Available Among artificial intelligence approaches, artificial neural networks (ANNs and genetic algorithm (GA are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (ANN and genetic algorithm (GA were applied to find the optimal conditions for achieving the maximum hardness of Al6061 reinforced by multiwall carbon nanotubes (MWCNTs through modeling of nanocomposite characteristics. After examination the different ANN architectures an optimal structure of the model, i.e. 6-18-1, is obtained with 1.52% mean absolute error and R2 = 0.987. The proposed structure was used as fitting function for genetic algorithm. The results of GA simulation predicted that the combination sintering temperature 346 °C, sintering time 0.33 h, compact pressure 284.82 MPa, milling time 19.66 h and vial speed 310.5 rpm give the optimum hardness, (i.e., 87.5 micro Vickers in the composite with 0.53 wt% CNT. Also, sensitivity analysis shows that the sintering time, milling time, compact pressure, vial speed and amount of MWCNT are the significant parameter and sintering time is the most important parameter. Comparison of the predicted values with the experimental data revealed that the GA–ANN model is a powerful method to find the optimal conditions for preparing of Al6061-MWCNT.

Three-Dimensional Human iPSC-Derived Artificial Skeletal Muscles Model Muscular Dystrophies and Enable Multilineage Tissue Engineering

Directory of Open Access Journals (Sweden)

Sara Martina Maffioletti

2018-04-01

Full Text Available Summary: Generating human skeletal muscle models is instrumental for investigating muscle pathology and therapy. Here, we report the generation of three-dimensional (3D artificial skeletal muscle tissue from human pluripotent stem cells, including induced pluripotent stem cells (iPSCs from patients with Duchenne, limb-girdle, and congenital muscular dystrophies. 3D skeletal myogenic differentiation of pluripotent cells was induced within hydrogels under tension to provide myofiber alignment. Artificial muscles recapitulated characteristics of human skeletal muscle tissue and could be implanted into immunodeficient mice. Pathological cellular hallmarks of incurable forms of severe muscular dystrophy could be modeled with high fidelity using this 3D platform. Finally, we show generation of fully human iPSC-derived, complex, multilineage muscle models containing key isogenic cellular constituents of skeletal muscle, including vascular endothelial cells, pericytes, and motor neurons. These results lay the foundation for a human skeletal muscle organoid-like platform for disease modeling, regenerative medicine, and therapy development. : Maffioletti et al. generate human 3D artificial skeletal muscles from healthy donors and patient-specific pluripotent stem cells. These human artificial muscles accurately model severe genetic muscle diseases. They can be engineered to include other cell types present in skeletal muscle, such as vascular cells and motor neurons. Keywords: skeletal muscle, pluripotent stem cells, iPS cells, myogenic differentiation, tissue engineering, disease modeling, muscular dystrophy, organoids

Genetically Engineering Entomopathogenic Fungi.

Science.gov (United States)

Zhao, H; Lovett, B; Fang, W

2016-01-01

Entomopathogenic fungi have been developed as environmentally friendly alternatives to chemical insecticides in biocontrol programs for agricultural pests and vectors of disease. However, mycoinsecticides currently have a small market share due to low virulence and inconsistencies in their performance. Genetic engineering has made it possible to significantly improve the virulence of fungi and their tolerance to adverse conditions. Virulence enhancement has been achieved by engineering fungi to express insect proteins and insecticidal proteins/peptides from insect predators and other insect pathogens, or by overexpressing the pathogen's own genes. Importantly, protein engineering can be used to mix and match functional domains from diverse genes sourced from entomopathogenic fungi and other organisms, producing insecticidal proteins with novel characteristics. Fungal tolerance to abiotic stresses, especially UV radiation, has been greatly improved by introducing into entomopathogens a photoreactivation system from an archaean and pigment synthesis pathways from nonentomopathogenic fungi. Conversely, gene knockout strategies have produced strains with reduced ecological fitness as recipients for genetic engineering to improve virulence; the resulting strains are hypervirulent, but will not persist in the environment. Coupled with their natural insect specificity, safety concerns can also be mitigated by using safe effector proteins with selection marker genes removed after transformation. With the increasing public concern over the continued use of synthetic chemical insecticides and growing public acceptance of genetically modified organisms, new types of biological insecticides produced by genetic engineering offer a range of environmentally friendly options for cost-effective control of insect pests. Copyright © 2016 Elsevier Inc. All rights reserved.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

Science.gov (United States)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Medical applications of membranes: Drug delivery, artificial organs and tissue engineering

NARCIS (Netherlands)

Stamatialis, Dimitrios; Papenburg, B.J.; Girones nogue, Miriam; Saiful, S.; Bettahalli Narasimha, M.S.; Schmitmeier, Stephanie; Wessling, Matthias

2008-01-01

This paper covers the main medical applications of artificial membranes. Specific attention is given to drug delivery systems, artificial organs and tissue engineering which seem to dominate the interest of the membrane community this period. In all cases, the materials, methods and the current

Development and evaluation of a removable tissue-engineered muscle with artificial tendons.

Science.gov (United States)

Nakamura, Tomohiro; Takagi, Shunya; Kamon, Takafumi; Yamasaki, Ken-Ichi; Fujisato, Toshia

2017-02-01

Tissue-engineered skeletal muscles were potentially useful as physiological and biochemical in vitro models. Currently, most of the similar models were constructed without tendons. In this study, we aimed to develop a simple, highly versatile tissue-engineered muscle with artificial tendons, and to evaluate the contractile, histological and molecular dynamics during differentiation. C2C12 cells were embedded in a cold type-І collagen gel and placed between two artificial tendons on a silicone sheet. The construct shrank and tightly attached to the artificial tendons with differentiation, finally detaching from the silicone sheet within 1 week of culture onset. We successfully developed a tissue-engineered skeletal muscle with two artificial tendons from C2C12 myoblasts embedded in type-І collagen gel. The isometric twitch contractile force (TCF) significantly increased during differentiation. Time to Peak Tension (TPT) and Half-Relaxation Time (1/2RT) were significantly shortened during differentiation. Myogenic regulatory factors were maximally expressed at 2 weeks, and subsequently decreased at 3 weeks of culture. Histological analysis indicated that myotube formation increased markedly from 2 weeks and well-ordered sarcomere structures were observed on the surface of the 3D engineered muscle at 3 weeks of culture. These results suggested that robust muscle structure occurred by 3 weeks in the tissue-engineered skeletal muscle. Moreover, during the developmental process, the artificial tendons might contribute to well-ordered sarcomere formation. Our results indicated that this simple culture system could be used to evaluate the effects of various pharmacological and mechanical cues on muscle contractility in a variety of research areas. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Artificial engineering of secondary lymphoid organs.

Science.gov (United States)

Tan, Jonathan K H; Watanabe, Takeshi

2010-01-01

Secondary lymphoid organs such as spleen and lymph nodes are highly organized immune structures essential for the initiation of immune responses. They display distinct B cell and T cell compartments associated with specific stromal follicular dendritic cells and fibroblastic reticular cells, respectively. Interweaved through the parenchyma is a conduit system that distributes small antigens and chemokines directly to B and T cell zones. While most structural aspects between lymph nodes and spleen are common, the entry of lymphocytes, antigen-presenting cells, and antigen into lymphoid tissues is regulated differently, reflecting the specialized functions of each organ in filtering either lymph or blood. The overall organization of lymphoid tissue is vital for effective antigen screening and recognition, and is a feature which artificially constructed lymphoid organoids endeavor to replicate. Synthesis of artificial lymphoid tissues is an emerging field that aims to provide therapeutic application for the treatment of severe infection, cancer, and age-related involution of secondary lymphoid tissues. The development of murine artificial lymphoid tissues has benefited greatly from an understanding of organogenesis of lymphoid organs, which has delineated cellular and molecular elements essential for the recruitment and organization of lymphocytes into lymphoid structures. Here, the field of artificial lymphoid tissue engineering is considered including elements of lymphoid structure and development relevant to organoid synthesis. (c) 2010 Elsevier Inc. All rights reserved.

Recombination-mediated genetic engineering of a bacterial artificial chromosome clone of modified vaccinia virus Ankara (MVA)

DEFF Research Database (Denmark)

Cottingham, Matthew G; Andersen, Rikke F; Spencer, Alexandra J

2008-01-01

-length, rescuable clones were obtained, which had indistinguishable immunogenicity in mice. One clone was shotgun sequenced and found to be identical to the parent. We employed GalK recombination-mediated genetic engineering (recombineering) of MVA-BAC to delete five selected viral genes. Deletion of C12L, A44L, A...

Genetically engineered nanocarriers for drug delivery

Directory of Open Access Journals (Sweden)

Shi P

2014-03-01

Full Text Available Pu Shi, Joshua A Gustafson, J Andrew MacKayDepartment of Pharmacology and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USAAbstract: Cytotoxicity, low water solubility, rapid clearance from circulation, and off-target side-effects are common drawbacks of conventional small-molecule drugs. To overcome these shortcomings, many multifunctional nanocarriers have been proposed to enhance drug delivery. In concept, multifunctional nanoparticles might carry multiple agents, control release rate, biodegrade, and utilize target-mediated drug delivery; however, the design of these particles presents many challenges at the stage of pharmaceutical development. An emerging solution to improve control over these particles is to turn to genetic engineering. Genetically engineered nanocarriers are precisely controlled in size and structure and can provide specific control over sites for chemical attachment of drugs. Genetically engineered drug carriers that assemble nanostructures including nanoparticles and nanofibers can be polymeric or non-polymeric. This review summarizes the recent development of applications in drug and gene delivery utilizing nanostructures of polymeric genetically engineered drug carriers such as elastin-like polypeptides, silk-like polypeptides, and silk-elastin-like protein polymers, and non-polymeric genetically engineered drug carriers such as vault proteins and viral proteins.Keywords: polymeric drug carrier, non-polymeric drug carrier, gene delivery, GE drug carriers

Modularization of genetic elements promotes synthetic metabolic engineering.

Science.gov (United States)

Qi, Hao; Li, Bing-Zhi; Zhang, Wen-Qian; Liu, Duo; Yuan, Ying-Jin

2015-11-15

In the context of emerging synthetic biology, metabolic engineering is moving to the next stage powered by new technologies. Systematical modularization of genetic elements makes it more convenient to engineer biological systems for chemical production or other desired purposes. In the past few years, progresses were made in engineering metabolic pathway using synthetic biology tools. Here, we spotlighted the topic of implementation of modularized genetic elements in metabolic engineering. First, we overviewed the principle developed for modularizing genetic elements and then discussed how the genetic modules advanced metabolic engineering studies. Next, we picked up some milestones of engineered metabolic pathway achieved in the past few years. Last, we discussed the rapid raised synthetic biology field of "building a genome" and the potential in metabolic engineering. Copyright © 2015 Elsevier Inc. All rights reserved.

Moral Fantasy in Genetic Engineering.

Science.gov (United States)

Boone, C. Keith

1984-01-01

Discusses the main ethical issues generated by the new genetics and suggests ways to think about them. Concerns include "playing God," violation of the natural order of the universe, and abuse of genetic technology. Critical distinctions for making difficult decisions about genetic engineering issues are noted. (DH)

Possible people, complaints, and the distinction between genetic planning and genetic engineering.

Science.gov (United States)

Delaney, James J

2011-07-01

Advances in the understanding of genetics have led to the belief that it may become possible to use genetic engineering to manipulate the DNA of humans at the embryonic stage to produce certain desirable traits. Although this currently cannot be done on a large scale, many people nevertheless object in principle to such practices. Most often, they argue that genetic enhancements would harm the children who were engineered, cause societal harms, or that the risks of perfecting the procedures are too high to proceed. However, many of these same people do not have serious objections to what is called 'genetic planning' procedures (such as the selection of sperm donors with desirable traits) that essentially have the same ends. The author calls the view that genetic engineering enhancements are impermissible while genetic planning enhancements are permissible the 'popular view', and argues that the typical reasons people give for the popular view fail to distinguish the two practices. This paper provides a principle that can salvage the popular view, which stresses that offspring from genetic engineering practices have grounds for complaint because they are identical to the pre-enhanced embryo, whereas offspring who are the result of genetic planning have no such grounds.

Safe genetically engineered plants

International Nuclear Information System (INIS)

Rosellini, D; Veronesi, F

2007-01-01

The application of genetic engineering to plants has provided genetically modified plants (GMPs, or transgenic plants) that are cultivated worldwide on increasing areas. The most widespread GMPs are herbicide-resistant soybean and canola and insect-resistant corn and cotton. New GMPs that produce vaccines, pharmaceutical or industrial proteins, and fortified food are approaching the market. The techniques employed to introduce foreign genes into plants allow a quite good degree of predictability of the results, and their genome is minimally modified. However, some aspects of GMPs have raised concern: (a) control of the insertion site of the introduced DNA sequences into the plant genome and of its mutagenic effect; (b) presence of selectable marker genes conferring resistance to an antibiotic or an herbicide, linked to the useful gene; (c) insertion of undesired bacterial plasmid sequences; and (d) gene flow from transgenic plants to non-transgenic crops or wild plants. In response to public concerns, genetic engineering techniques are continuously being improved. Techniques to direct foreign gene integration into chosen genomic sites, to avoid the use of selectable genes or to remove them from the cultivated plants, to reduce the transfer of undesired bacterial sequences, and make use of alternative, safer selectable genes, are all fields of active research. In our laboratory, some of these new techniques are applied to alfalfa, an important forage plant. These emerging methods for plant genetic engineering are briefly reviewed in this work

Safe genetically engineered plants

Energy Technology Data Exchange (ETDEWEB)

Rosellini, D; Veronesi, F [Dipartimento di Biologia Vegetale e Biotecnologie Agroambientali e Zootecniche, Universita degli Studi di Perugia, Borgo XX giugno 74, 06121 Perugia (Italy)

2007-10-03

The application of genetic engineering to plants has provided genetically modified plants (GMPs, or transgenic plants) that are cultivated worldwide on increasing areas. The most widespread GMPs are herbicide-resistant soybean and canola and insect-resistant corn and cotton. New GMPs that produce vaccines, pharmaceutical or industrial proteins, and fortified food are approaching the market. The techniques employed to introduce foreign genes into plants allow a quite good degree of predictability of the results, and their genome is minimally modified. However, some aspects of GMPs have raised concern: (a) control of the insertion site of the introduced DNA sequences into the plant genome and of its mutagenic effect; (b) presence of selectable marker genes conferring resistance to an antibiotic or an herbicide, linked to the useful gene; (c) insertion of undesired bacterial plasmid sequences; and (d) gene flow from transgenic plants to non-transgenic crops or wild plants. In response to public concerns, genetic engineering techniques are continuously being improved. Techniques to direct foreign gene integration into chosen genomic sites, to avoid the use of selectable genes or to remove them from the cultivated plants, to reduce the transfer of undesired bacterial sequences, and make use of alternative, safer selectable genes, are all fields of active research. In our laboratory, some of these new techniques are applied to alfalfa, an important forage plant. These emerging methods for plant genetic engineering are briefly reviewed in this work.

Seeking perfection: a Kantian look at human genetic engineering.

Science.gov (United States)

Gunderson, Martin

2007-01-01

It is tempting to argue that Kantian moral philosophy justifies prohibiting both human germ-line genetic engineering and non-therapeutic genetic engineering because they fail to respect human dignity. There are, however, good reasons for resisting this temptation. In fact, Kant's moral philosophy provides reasons that support genetic engineering-even germ-line and non-therapeutic. This is true of Kant's imperfect duties to seek one's own perfection and the happiness of others. It is also true of the categorical imperative. Kant's moral philosophy does, however, provide limits to justifiable genetic engineering.

Genetic engineering in biotechnology

Energy Technology Data Exchange (ETDEWEB)

Bedate, C.A.; Morales, J.C.; Lopez, E.H.

1981-09-01

The objective of this book is to encourage the use of genetic engineering for economic development. The report covers: (1) Precedents of genetic engineering; (2) a brief description of the technology, including the transfer of DNA in bacteria (vectors, E. coli and B. subtilis hosts, stages, and technical problems), practical examples of techniques used and their products (interferon; growth hormone; insulin; treatment of blood cells, Talasemia, and Lesch-Nyhan syndrome; and more nutritious soya), transfer to higher organisms, and cellular fusion; (3) biological risks and precautions; (4) possible applications (production of hydrogen, hydrocarbons, alcohol, chemicals, enzymes, peptides, viral antigens, monoclonal antibodies, genes, proteins, and insecticides; metal extraction; nitrogen fixation; biodegradation; and new varieties of plants and animals; and (5) international activities.

Genetic Engineering of Alfalfa (Medicago sativa L.).

Science.gov (United States)

Wang, Dan; Khurshid, Muhammad; Sun, Zhan Min; Tang, Yi Xiong; Zhou, Mei Liang; Wu, Yan Min

2016-01-01

Alfalfa is excellent perennial legume forage for its extensive ecological adaptability, high nutrition value, palatability and biological nitrogen fixation. It plays a very important role in the agriculture, animal husbandry and ecological construction. It is cultivated in all continents. With the development of modern plant breeding and genetic engineering techniques, a large amount of work has been carried out on alfalfa. Here we summarize the recent research advances in genetic engineering of alfalfa breeding, including transformation, quality improvement, stress resistance and as a bioreactor. The review article can enables us to understand the research method, direction and achievements of genetic engineering technology of Alfalfa.

A scenario for a genetically controlled fission of artificial vesicles

DEFF Research Database (Denmark)

Bönzli, Eva; Hadorn, Maik; Jørgensen, Mikkel Girke

2011-01-01

to vesicles (Hanczyc et al. 2003). In the present work, we developed a scenario how a genetically controlled fission of vesicles may be achieved by the synthesis of a special class of viral proteins within artificial vesicles. Because the authors already have a lot of experience in the water-in-oil emulsion...... be incorporated into vesicles, and therefore allow the synthesis of a large number of proteins (Noireaux et al. 2005). However, vesicle fission remains one of the upcoming challenges in the artificial cell project (Noireaux et al. 2011). So far, vesicle fission is implemented by applying mechanical stress...

Teacher-to-Teacher: An Annotated Bibliography on DNA and Genetic Engineering.

Science.gov (United States)

Mertens, Thomas R., Comp.

1984-01-01

Presented is an annotated bibliography of 24 books on DNA and genetic engineering. Areas considered in these books include: basic biological concepts to help understand advances in genetic engineering; applications of genetic engineering; social, legal, and moral issues of genetic engineering; and historical aspects leading to advances in…

Paper Genetic Engineering.

Science.gov (United States)

MacClintic, Scott D.; Nelson, Genevieve M.

Bacterial transformation is a commonly used technique in genetic engineering that involves transferring a gene of interest into a bacterial host so that the bacteria can be used to produce large quantities of the gene product. Although several kits are available for performing bacterial transformation in the classroom, students do not always…

Genetic engineering of stem cells for enhanced therapy.

Science.gov (United States)

Nowakowski, Adam; Andrzejewska, Anna; Janowski, Miroslaw; Walczak, Piotr; Lukomska, Barbara

2013-01-01

Stem cell therapy is a promising strategy for overcoming the limitations of current treatment methods. The modification of stem cell properties may be necessary to fully exploit their potential. Genetic engineering, with an abundance of methodology to induce gene expression in a precise and well-controllable manner, is particularly attractive for this purpose. There are virus-based and non-viral methods of genetic manipulation. Genome-integrating viral vectors are usually characterized by highly efficient and long-term transgene expression, at a cost of safety. Non-integrating viruses are also highly efficient in transduction, and, while safer, offer only a limited duration of transgene expression. There is a great diversity of transfectable forms of nucleic acids; however, for efficient shuttling across cell membranes, additional manipulation is required. Both physical and chemical methods have been employed for this purpose. Stem cell engineering for clinical applications is still in its infancy and requires further research. There are two main strategies for inducing transgene expression in therapeutic cells: transient and permanent expression. In many cases, including stem cell trafficking and using cell therapy for the treatment of rapid-onset disease with a short healing process, transient transgene expression may be a sufficient and optimal approach. For that purpose, mRNA-based methods seem ideally suited, as they are characterized by a rapid, highly efficient transfection, with outstanding safety. Permanent transgene expression is primarily based on the application of viral vectors, and, due to safety concerns, these methods are more challenging. There is active, ongoing research toward the development of non-viral methods that would induce permanent expression, such as transposons and mammalian artificial chromosomes.

Genome editing and genetic engineering in livestock for advancing agricultural and biomedical applications.

Science.gov (United States)

Telugu, Bhanu P; Park, Ki-Eun; Park, Chi-Hun

2017-08-01

Genetic modification of livestock has a longstanding and successful history, starting with domestication several thousand years ago. Modern animal breeding strategies predominantly based on marker-assisted and genomic selection, artificial insemination, and embryo transfer have led to significant improvement in the performance of domestic animals, and are the basis for regular supply of high quality animal derived food. However, the current strategy of breeding animals over multiple generations to introduce novel traits is not realistic in responding to the unprecedented challenges such as changing climate, pandemic diseases, and feeding an anticipated 3 billion increase in global population in the next three decades. Consequently, sophisticated genetic modifications that allow for seamless introgression of novel alleles or traits and introduction of precise modifications without affecting the overall genetic merit of the animal are required for addressing these pressing challenges. The requirement for precise modifications is especially important in the context of modeling human diseases for the development of therapeutic interventions. The animal science community envisions the genome editors as essential tools in addressing these critical priorities in agriculture and biomedicine, and for advancing livestock genetic engineering for agriculture, biomedical as well as "dual purpose" applications.

Genetically Engineered Immunotherapy for Advanced Cancer

Science.gov (United States)

In this trial, doctors will collect T lymphocytes from patients with advanced mesothelin-expressing cancer and genetically engineer them to recognize mesothelin. The gene-engineered cells will be multiplied and infused into the patient to fight the cancer

International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

CERN Document Server

Bhaskar, M; Panigrahi, Bijaya; Das, Swagatam

2016-01-01

The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES -2015) held at Velammal Engineering College (VEC), Chennai, India during 22 – 23 April 2015. The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Power Technologies.

German politics of genetic engineering and its deconstruction.

Science.gov (United States)

Gottweis, H

1995-05-01

Policy-making, as exemplified by biotechnology policy, can be understood as an attempt to manage a field of discursivity, to construct regularity in a dispersed multitude of combinable elements. Following this perspective of politics as a textual process, the paper interprets the politicization of genetic engineering in Germany as a defence of the political as a regime of heterogeneity, as a field of 'dissensus' rather than 'consensus', and a rejection of the idea that the framing of technological transformation is an autonomous process. From its beginning in the early 1970s, genetic engineering was symbolically entrenched as a key technology of the future, and as an integral element of the German politics of modernization. Attempts by new social movements and the Green Party to displace the egalitarian imaginary of democratic discourse into the politics of genetic engineering were construed by the political élites as an attack on the political order of post-World War II Germany. The 1990 Genetic Engineering Law attempted a closure of this controversy. But it is precisely the homogenizing idiom of this 'settlement' which continues to nourish the social movements and their radical challenge to the definitions and codings of the politics of genetic engineering.

Recombination-mediated genetic engineering of a bacterial artificial chromosome clone of modified vaccinia virus Ankara (MVA.

Directory of Open Access Journals (Sweden)

Matthew G Cottingham

2008-02-01

Full Text Available The production, manipulation and rescue of a bacterial artificial chromosome clone of Vaccinia virus (VAC-BAC in order to expedite construction of expression vectors and mutagenesis of the genome has been described (Domi & Moss, 2002, PNAS99 12415-20. The genomic BAC clone was 'rescued' back to infectious virus using a Fowlpox virus helper to supply transcriptional machinery. We apply here a similar approach to the attenuated strain Modified Vaccinia virus Ankara (MVA, now widely used as a safe non-replicating recombinant vaccine vector in mammals, including humans. Four apparently full-length, rescuable clones were obtained, which had indistinguishable immunogenicity in mice. One clone was shotgun sequenced and found to be identical to the parent. We employed GalK recombination-mediated genetic engineering (recombineering of MVA-BAC to delete five selected viral genes. Deletion of C12L, A44L, A46R or B7R did not significantly affect CD8(+ T cell immunogenicity in BALB/c mice, but deletion of B15R enhanced specific CD8(+ T cell responses to one of two endogenous viral epitopes (from the E2 and F2 proteins, in accordance with published work (Staib et al., 2005, J. Gen. Virol.86, 1997-2006. In addition, we found a higher frequency of triple-positive IFN-gamma, TNF-alpha and IL-2 secreting E3-specific CD8+ T-cells 8 weeks after vaccination with MVA lacking B15R. Furthermore, a recombinant vaccine capable of inducing CD8(+ T cells against an epitope from Plasmodium berghei was created using GalK counterselection to insert an antigen expression cassette lacking a tandem marker gene into the traditional thymidine kinase locus of MVA-BAC. MVA continues to feature prominently in clinical trials of recombinant vaccines against diseases such as HIV-AIDS, malaria and tuberculosis. Here we demonstrate in proof-of-concept experiments that MVA-BAC recombineering is a viable route to more rapid and efficient generation of new candidate mutant and recombinant

Engineering of metabolic pathways by artificial enzyme channels

Directory of Open Access Journals (Sweden)

Marlene ePröschel

2015-10-01

Full Text Available Application of industrial enzymes for production of valuable chemical compounds has greatly benefited from recent developments in Systems and Synthetic Biology. Both, in vivo and in vitro systems have been established, allowing conversion of simple into complex compounds. Metabolic engineering in living cells needs to be balanced which is achieved by controlling gene expression levels, translation, scaffolding, compartmentation and flux control. In vitro applications are often hampered by limited protein stability/half-life and insufficient rates of substrate conversion. To improve stability and catalytic activity, proteins are post-translationally modified and arranged in artificial metabolic channels. Within the review article we will first discuss the supramolecular organization of enzymes in living systems and secondly summarize current and future approaches to design artificial metabolic channels by additive manufacturing for the efficient production of desired products.

Genetically engineered orange petunias on the market

OpenAIRE

Bashandy, Hany; Teeri, Teemu Heikki

2017-01-01

Main conclusion Unauthorized genetically engineered orange petunias were found on the market. Genetic engineering of petunia was shown to lead to novel flower color some 20?years ago. Here we show that petunia lines with orange flowers, generated for scientific purposes, apparently found their way to petunia breeding programmes, intentionally or unintentionally. Today they are widely available, but have not been registered for commerce. Electronic supplementary material The online version of ...

The artificial beetle, or a brief manifesto for engineered biomimicry

Science.gov (United States)

Bartl, Michael H.; Lakhtakia, Akhlesh

2015-03-01

The artificial beetle is possibly the Holy Grail for practitioners of engineered biomimicry. An artificial beetle could gather and relay data and images from compromised environments on earth and other planets to decision makers. It could also be used for surveillance of foes and friends alike, and will require ethical foresight and oversight. What would it take to develop an artificial beetle? Several biotemplating techniques can be harnessed for the replication of external structural features of beetle bodies, and thus preserve functionalities such as coloration of the exoskeleton and the hydrophobicity of wings. The body cavity must host a power supply, motors to move the wings for flight, sensors to capture ambient conditions and images, and data transmitters and receivers to communicate with a remote command center. All of these devices must be very small and reliable.

Genetic engineering for skeletal regenerative medicine.

Science.gov (United States)

Gersbach, Charles A; Phillips, Jennifer E; García, Andrés J

2007-01-01

The clinical challenges of skeletal regenerative medicine have motivated significant advances in cellular and tissue engineering in recent years. In particular, advances in molecular biology have provided the tools necessary for the design of gene-based strategies for skeletal tissue repair. Consequently, genetic engineering has emerged as a promising method to address the need for sustained and robust cellular differentiation and extracellular matrix production. As a result, gene therapy has been established as a conventional approach to enhance cellular activities for skeletal tissue repair. Recent literature clearly demonstrates that genetic engineering is a principal factor in constructing effective methods for tissue engineering approaches to bone, cartilage, and connective tissue regeneration. This review highlights this literature, including advances in the development of efficacious gene carriers, novel cell sources, successful delivery strategies, and optimal target genes. The current status of the field and the challenges impeding the clinical realization of these approaches are also discussed.

Computational Genetic Regulatory Networks Evolvable, Self-organizing Systems

CERN Document Server

Knabe, Johannes F

2013-01-01

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. In differentiated multicellular organisms, tremendous complexity has arisen in the course of evolution of life on earth. Engineering and science have so far achieved no working system that can compare with this complexity, depth and scope of organization. Abstracting the dynamics of genetic regulatory control to a computational framework in which artificial GRNs in artificial simulated cells differentiate while connected in a changing topology, it is possible to apply Darwinian evolution in silico to study the capacity of such developmental/differentiated GRNs to evolve. In this volume an evolutionary GRN paradigm is investigated for its evolvability and robustness in models of biological clocks, in simple differentiated multicellularity, and in evolving artificial developing 'organisms' which grow and express an ontogeny starting fr...

Perspectives of genetic engineering in radiobiology

International Nuclear Information System (INIS)

Khanson, K.P.; Zvonareva, N.B.; Evtushenko, V.I.

1988-01-01

Present evidence on the use of genetic engineering methods in studying the molecular mechanism of radiation damage and repair of DNA, as well as radiation mutagenesis and carcinogenesis has been summarized. The new approach to radiobiological research has proved to be extremely fruitful. Some previously unknown types of structural disorders in DNA molecule have been discovered, some repair genes isolated and their primary structure established, some aspects of radiation mutagenesis elucidated, and research into disiphering the molecular bases of neoplastic transformations of exposed cells are being successfully investigated. The perspectives of using genetic engineering methods in radiobiology are discussed

Artificial intelligence in nuclear engineering: developments, lesson learned and future directions

Energy Technology Data Exchange (ETDEWEB)

Ruan, Da [The Belgian Nuclear Research Centre (SCK.CEN), Mol (Belgium)]. E-mail: druan@sckcen.be

2005-07-01

Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)

Artificial intelligence in nuclear engineering: developments, lesson learned and future directions

International Nuclear Information System (INIS)

Ruan, Da

2005-01-01

Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)

Recent Advances in Genetic Engineering - A Review

OpenAIRE

Sobiah Rauf; Zubair Anwar; Hussain Mustatab Wahedi; Jabar Zaman Khan Khattak; Talal Jamil

2012-01-01

Humans have been doing genetic engineering, a technology which is transforming our world, for thousands of years on a wide range of plants, animals and micro organism and have applications in the field of medicine, research, industry and agriculture. The rapid developments in the field of genetic engineering have given a new impetus to biotechnology. This introduces the possibility of tailoring organisms in order to optimize the production of established or novel metabolites of commercial imp...

Can Man Control His Biological Evolution? A Symposium on Genetic Engineering. Genetic Engineering

Science.gov (United States)

Ramsey, Paul

1972-01-01

Presented are issues related to genetic engineering. Increased knowledge of techniques to manipulate genes are apt to create confusion about moral values in relation to unborn babies and other living organisms on earth. Human beings may use this knowledge to disturb the balance maintained by nature. (PS)

Genetic Engineering: The Modification of Man

Science.gov (United States)

Sinsheimer, Robert L.

1970-01-01

Describes somatic and genetic manipulations of individual genotypes, using diabetes control as an example of the first mode that is potentially realizable be derepression or viral transduction of genes. Advocates the use of genetic engineering of the second mode to remove man from his biological limitations, but offers maxims to ensure the…

Artificial neural networks in the nuclear engineering (Part 2)

International Nuclear Information System (INIS)

Baptista Filho, Benedito Dias

2002-01-01

The field of Artificial Neural Networks (ANN), one of the branches of Artificial Intelligence has been waking up a lot of interest in the Nuclear Engineering (NE). ANN can be used to solve problems of difficult modeling, when the data are fail or incomplete and in high complexity problems of control. The first part of this work began a discussion with feed-forward neural networks in back-propagation. In this part of the work, the Multi-synaptic neural networks is applied to control problems. Also, the self-organized maps is presented in a typical pattern classification problem: transients classification. The main purpose of the work is to show that ANN can be successfully used in NE if a carefully choice of its type is done: the application sets this choice. (author)

Engineering artificial machines from designable DNA materials for biomedical applications.

Science.gov (United States)

Qi, Hao; Huang, Guoyou; Han, Yulong; Zhang, Xiaohui; Li, Yuhui; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng; Wang, Lin

2015-06-01

Deoxyribonucleic acid (DNA) emerges as building bricks for the fabrication of nanostructure with complete artificial architecture and geometry. The amazing ability of DNA in building two- and three-dimensional structures raises the possibility of developing smart nanomachines with versatile controllability for various applications. Here, we overviewed the recent progresses in engineering DNA machines for specific bioengineering and biomedical applications.

Exploring the Role of Genetic Algorithms and Artificial Neural Networks for Interpolation of Elevation in Geoinformation Models

Science.gov (United States)

Bagheri, H.; Sadjadi, S. Y.; Sadeghian, S.

2013-09-01

One of the most significant tools to study many engineering projects is three-dimensional modelling of the Earth that has many applications in the Geospatial Information System (GIS), e.g. creating Digital Train Modelling (DTM). DTM has numerous applications in the fields of sciences, engineering, design and various project administrations. One of the most significant events in DTM technique is the interpolation of elevation to create a continuous surface. There are several methods for interpolation, which have shown many results due to the environmental conditions and input data. The usual methods of interpolation used in this study along with Genetic Algorithms (GA) have been optimised and consisting of polynomials and the Inverse Distance Weighting (IDW) method. In this paper, the Artificial Intelligent (AI) techniques such as GA and Neural Networks (NN) are used on the samples to optimise the interpolation methods and production of Digital Elevation Model (DEM). The aim of entire interpolation methods is to evaluate the accuracy of interpolation methods. Universal interpolation occurs in the entire neighbouring regions can be suggested for larger regions, which can be divided into smaller regions. The results obtained from applying GA and ANN individually, will be compared with the typical method of interpolation for creation of elevations. The resulting had performed that AI methods have a high potential in the interpolation of elevations. Using artificial networks algorithms for the interpolation and optimisation based on the IDW method with GA could be estimated the high precise elevations.

An existential analysis of genetic engineering and human rights ...

African Journals Online (AJOL)

Genetic engineering for purposes of human enhancement poses risks that justify regulation. However, this paper argues philosophically that it is inappropriate to use human rights treaties to prohibit germ-line genetic engineering whether therapeutic or for purposes of enhancement. When also looked at existentially, the ...

A genetic-neural artificial intelligence approach to resins optimization

International Nuclear Information System (INIS)

Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A.

2005-01-01

This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

Tissue engineering and cell-based therapy toward integrated strategy with artificial organs.

Science.gov (United States)

Gojo, Satoshi; Toyoda, Masashi; Umezawa, Akihiro

2011-09-01

Research in order that artificial organs can supplement or completely replace the functions of impaired or damaged tissues and internal organs has been underway for many years. The recent clinical development of implantable left ventricular assist devices has revolutionized the treatment of patients with heart failure. The emerging field of regenerative medicine, which uses human cells and tissues to regenerate internal organs, is now advancing from basic and clinical research to clinical application. In this review, we focus on the novel biomaterials, i.e., fusion protein, and approaches such as three-dimensional and whole-organ tissue engineering. We also compare induced pluripotent stem cells, directly reprogrammed cardiomyocytes, and somatic stem cells for cell source of future cell-based therapy. Integrated strategy of artificial organ and tissue engineering/regenerative medicine should give rise to a new era of medical treatment to organ failure.

Genetic engineering possibilities for CELSS: A bibliography and summary of techniques

Science.gov (United States)

Johnson, E. J.

1982-01-01

A bibliography of the most useful techniques employed in genetic engineering of higher plants, bacteria associated with plants, and plant cell cultures is provided. A resume of state-of-the-art genetic engineering of plants and bacteria is presented. The potential application of plant bacterial genetic engineering to CELSS (Controlled Ecological Life Support System) program and future research needs are discussed.

What Ideas Do Students Associate with "Biotechnology" and "Genetic Engineering"?

Science.gov (United States)

Hill, Ruaraidh; Stanisstreet, Martin; Boyes, Edward

2000-01-01

Explores the ideas that students aged 16-19 associate with the terms 'biotechnology' and 'genetic engineering'. Indicates that some students see biotechnology as risky whereas genetic engineering was described as ethically wrong. (Author/ASK)

Artificial intelligence applications in offshore oil and gas production

International Nuclear Information System (INIS)

Attia, F.G.

1994-01-01

The field of Artificial Intelligence (AI) has gained considerable acceptance in virtually all fields, of engineering applications. Artificial intelligence is now being applied in several areas of offshore oil and gas operations, such as drilling, well testing, well logging and interpretation, reservoir engineering, planning and economic evaluation, process control, and risk analysis. Current AI techniques offer a new and exciting technology for solving problems in the oil and gas industry. Expert systems, fuzzy logic systems, neural networks and genetic algorithms are major AI technologies which have made an impact on the petroleum industry. Presently, these technologies are at different stages of maturity with expert systems being the most mature and genetic algorithms the least. However, all four technologies have evolved such that practical applications were produced. This paper describes the four major Al techniques and their many applications in offshore oil and gas production operations. A summary description of future developments in Al technology that will affect the execution and productivity of offshore operations will be also provided

Bacterial Artificial Chromosome Mutagenesis Using Recombineering

Directory of Open Access Journals (Sweden)

Kumaran Narayanan

2011-01-01

Full Text Available Gene expression from bacterial artificial chromosome (BAC clones has been demonstrated to facilitate physiologically relevant levels compared to viral and nonviral cDNA vectors. BACs are large enough to transfer intact genes in their native chromosomal setting together with flanking regulatory elements to provide all the signals for correct spatiotemporal gene expression. Until recently, the use of BACs for functional studies has been limited because their large size has inherently presented a major obstacle for introducing modifications using conventional genetic engineering strategies. The development of in vivo homologous recombination strategies based on recombineering in E. coli has helped resolve this problem by enabling facile engineering of high molecular weight BAC DNA without dependence on suitably placed restriction enzymes or cloning steps. These techniques have considerably expanded the possibilities for studying functional genetics using BACs in vitro and in vivo.

Genetic engineering applied to agriculture has a long row to hoe.

Science.gov (United States)

Miller, Henry I

2018-01-02

In spite of the lack of scientific justification for skepticism about crops modified with molecular techniques of genetic engineering, they have been the most scrutinized agricultural products in human history. The assumption that "genetically engineered" or "genetically modified" is a meaningful - and dangerous - classification has led to excessive and dilatory regulation. The modern molecular techniques are an extension, or refinement, of older, less precise, less predictable methods of genetic modification, but as long as today's activists and regulators remain convinced that so called "GMOs" represent a distinct and dangerous category of research and products, genetic engineering will fall short of its potential.

Effects of genetic engineering on the pharmacokinetics of antibodies

International Nuclear Information System (INIS)

Colcher, D.; Goel, A.; Pavlinkova, G.; Beresford, G.; Booth, B.; Batra, S.K.

1999-01-01

Monoclonal antibodies (MAbs) may be considered 'magic bullets' due to their ability to recognize and eradicate malignant cells. MAbs, however, have practical limitations for their rapid application in the clinics. The structure of the antibody molecules can be engineered to modify functional domains such as antigen-binding sites and/or effectors functions. Advanced in genetic engineering have provided rapid progress the development of new immunoglobulin constructs of MAbs with defined research and therapeutic application. Recombinant antibody constructs are being engineered, such as human mouse chimeric, domain-dispositioned, domain-deleted, humanized and single-chain Fv fragments. Genetically-engineered antibodies differ in size and rate of catabolism. Pharmacokinetics studies show that the intact IgG (150 kD), enzymatically derived fragments Fab' (50 kD) and single chain Fv (28 kD) have different clearance rates. These antibody forms clear 50% from the blood pool in 2.1 days, 30 minutes and 10 minutes, respectively. Genetically-engineered antibodies make a new class of immunotherapeutic tracers for cancer treatment

Genetic Optimization Algorithm for Metabolic Engineering Revisited

Directory of Open Access Journals (Sweden)

Tobias B. Alter

2018-05-01

Full Text Available To date, several independent methods and algorithms exist for exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives, as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and the proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i multiple, non-linear engineering objectives; (ii the identification of gene target-sets according to logical gene-protein-reaction associations; (iii minimization of the number of network perturbations; and (iv the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems

CERN Document Server

Vijayakumar, K; Panigrahi, Bijaya; Das, Swagatam

2017-01-01

The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to deliberate and state their research findings, discuss the latest advancements and explore the future directions in the emerging areas of engineering and technology. The book presents original work and novel ideas, information, techniques and applications in the field of communication, computing and power technologies.

Rabbit defensin (NP-1) genetic engineering of plant | Ting | African ...

African Journals Online (AJOL)

Rabbit defensin (NP-1) genetic engineering of plant. ... Log in or Register to get access to full text downloads. ... defensin genetic engineering of plant in recent years, and also focuses on the existing problems and new strategies in this area.

Plant Genetic Resources: Selected Issues from Genetic Erosion to Genetic Engineering

Directory of Open Access Journals (Sweden)

Karl Hammer

2008-04-01

Full Text Available Plant Genetic Resources (PGR continue to play an important role in the development of agriculture. The following aspects receive a special consideration:1. Definition. The term was coined in 1970. The genepool concept served as an important tool in the further development. Different approaches are discussed.2. Values of Genetic Resources. A short introduction is highlighting this problem and stressing the economic usfulness of PGR.3. Genetic Erosion. Already observed by E. Baur in 1914, this is now a key issue within PGR. The case studies cited include Ethiopia, Italy, China, S Korea, Greece and S. Africa. Modern approaches concentrate on allelic changes in varieties over time but neglect the landraces. The causes and consequences of genetic erosion are discussed.4. Genetic Resources Conservation. Because of genetic erosion there is a need for conservation. PGR should be consigned to the appropriate method of conservation (ex situ, in situ, on-farm according to the scientific basis of biodiversity (genetic diversity, species diversity, ecosystem diversity and the evolutionary status of plants (cultivated plants, weeds, related wild plants (crop wild relatives.5. GMO. The impact of genetically engineered plants on genetic diversity is discussed.6. The Conclusions and Recommendations stress the importance of PGR. Their conservation and use are urgent necessities for the present development and future survival of mankind.

Genetic engineering of cyanobacteria as biodiesel feedstock.

Energy Technology Data Exchange (ETDEWEB)

Ruffing, Anne.; Trahan, Christine Alexandra; Jones, Howland D. T.

2013-01-01

Algal biofuels are a renewable energy source with the potential to replace conventional petroleum-based fuels, while simultaneously reducing greenhouse gas emissions. The economic feasibility of commercial algal fuel production, however, is limited by low productivity of the natural algal strains. The project described in this SAND report addresses this low algal productivity by genetically engineering cyanobacteria (i.e. blue-green algae) to produce free fatty acids as fuel precursors. The engineered strains were characterized using Sandias unique imaging capabilities along with cutting-edge RNA-seq technology. These tools are applied to identify additional genetic targets for improving fuel production in cyanobacteria. This proof-of-concept study demonstrates successful fuel production from engineered cyanobacteria, identifies potential limitations, and investigates several strategies to overcome these limitations. This project was funded from FY10-FY13 through the President Harry S. Truman Fellowship in National Security Science and Engineering, a program sponsored by the LDRD office at Sandia National Laboratories.

Engineering Values Into Genetic Engineering: A Proposed Analytic Framework for Scientific Social Responsibility.

Science.gov (United States)

Sankar, Pamela L; Cho, Mildred K

2015-01-01

Recent experiments have been used to "edit" genomes of various plant, animal and other species, including humans, with unprecedented precision. Furthermore, editing the Cas9 endonuclease gene with a gene encoding the desired guide RNA into an organism, adjacent to an altered gene, could create a "gene drive" that could spread a trait through an entire population of organisms. These experiments represent advances along a spectrum of technological abilities that genetic engineers have been working on since the advent of recombinant DNA techniques. The scientific and bioethics communities have built substantial literatures about the ethical and policy implications of genetic engineering, especially in the age of bioterrorism. However, recent CRISPr/Cas experiments have triggered a rehashing of previous policy discussions, suggesting that the scientific community requires guidance on how to think about social responsibility. We propose a framework to enable analysis of social responsibility, using two examples of genetic engineering experiments.

The complementarity of the technical tools of tissue engineering and the concepts of artificial organs for the design of functional bioartificial tissues.

Science.gov (United States)

Lenas, Petros; Moreno, Angel; Ikonomou, Laertis; Mayer, Joerg; Honda, Hiroyuki; Novellino, Antonio; Pizarro, Camilo; Nicodemou-Lena, Eleni; Rodergas, Silvia; Pintor, Jesus

2008-09-01

Although tissue engineering uses powerful biological tools, it still has a weak conceptual foundation, which is restricted at the cell level. The design criteria at the cell level are not directly related with the tissue functions, and consequently, such functions cannot be implemented in bioartificial tissues with the currently used methods. On the contrary, the field of artificial organs focuses on the function of the artificial organs that are treated in the design as integral entities, instead of the optimization of the artificial organ components. The field of artificial organs has already developed and tested methodologies that are based on system concepts and mathematical-computational methods that connect the component properties with the desired global organ function. Such methodologies are needed in tissue engineering for the design of bioartificial tissues with tissue functions. Under the framework of biomedical engineering, artificial organs and tissue engineering do not present competitive approaches, but are rather complementary and should therefore design a common future for the benefit of patients.

[Research progress of genetic engineering on medicinal plants].

Science.gov (United States)

Teng, Zhong-qiu; Shen, Ye

2015-02-01

The application of genetic engineering technology in modern agriculture shows its outstanding role in dealing with food shortage. Traditional medicinal plant cultivation and collection have also faced with challenges, such as lack of resources, deterioration of environment, germplasm of recession and a series of problems. Genetic engineering can be used to improve the disease resistance, insect resistance, herbicides resistant ability of medicinal plant, also can improve the medicinal plant yield and increase the content of active substances in medicinal plants. Thus, the potent biotechnology can play an important role in protection and large area planting of medicinal plants. In the development of medicinal plant genetic engineering, the safety of transgenic medicinal plants should also be paid attention to. A set of scientific safety evaluation and judgment standard which is suitable for transgenic medicinal plants should be established based on the recognition of the particularity of medicinal plants.

Artificial intelligence and engineering curricula - are changes needed?

International Nuclear Information System (INIS)

Jenkins, J.P.

1988-01-01

The purpose of this paper is to identify the expected impact of artificial intelligence (AI) on curricula and training courses. From this examination, new elements are proposed for the academic preparation and training of engineers who will evaluate and use these systems and capabilities. Artificial intelligence, from an operational viewpoint, begins with a set of rules governing the operation of logic, implemented via computer software and userware. These systems apply logic and experience to handling problems in an intelligent approach, especially when the number of alternatives to problem solution is beyond the scope of the human user. Usually, AI applications take the form of expert systems. An expert system embodies in the computer the knowledge-based component of an expert, such as domain knowledge and reasoning techniques, in such a form that the system can offer intelligent advice and, on demand, justify its own line of reasoning. Two languages predominate, LISP and Prolog. The AI user may interface with the knowledge base via one of these languages or by means of menu displays, cursor selections, or other conventional user interface methods

TMTI Task 1.6 Genetic Engineering Methods and Detection

Energy Technology Data Exchange (ETDEWEB)

Slezak, T; Lenhoff, R; Allen, J; Borucki, M; Vitalis, E; Gardner, S

2009-12-04

A large number of GE techniques can be adapted from other microorganisms to biothreat bacteria and viruses. Detection of GE in a microorganism increases in difficulty as the size of the genetic change decreases. In addition to the size of the engineered change, the consensus genomic sequence of the microorganism can impact the difficulty of detecting an engineered change in genomes that are highly variable from strain to strain. This problem will require comprehensive databases of whole genome sequences for more genetically variable biothreat bacteria and viruses. Preliminary work with microarrays for detecting synthetic elements or virulence genes and analytic bioinformatic approaches for whole genome sequence comparison to detect genetic engineering show promise for attacking this difficult problem but a large amount of future work remains.

Genetic Engineering and Crop Production.

Science.gov (United States)

Jones, Helen C.; Frost, S.

1991-01-01

With a spotlight upon current agricultural difficulties and environmental dilemmas, this paper considers both the extant and potential applications of genetic engineering with respect to crop production. The nonagricultural factors most likely to sway the impact of this emergent technology upon future crop production are illustrated. (JJK)

Genetic algorithms and artificial neural networks for loading pattern optimisation of advanced gas-cooled reactors

Energy Technology Data Exchange (ETDEWEB)

Ziver, A.K. E-mail: a.k.ziver@imperial.ac.uk; Pain, C.C; Carter, J.N.; Oliveira, C.R.E. de; Goddard, A.J.H.; Overton, R.S

2004-03-01

A non-generational genetic algorithm (GA) has been developed for fuel management optimisation of Advanced Gas-Cooled Reactors, which are operated by British Energy and produce around 20% of the UK's electricity requirements. An evolutionary search is coded using the genetic operators; namely selection by tournament, two-point crossover, mutation and random assessment of population for multi-cycle loading pattern (LP) optimisation. A detailed description of the chromosomes in the genetic algorithm coded is presented. Artificial Neural Networks (ANNs) have been constructed and trained to accelerate the GA-based search during the optimisation process. The whole package, called GAOPT, is linked to the reactor analysis code PANTHER, which performs fresh fuel loading, burn-up and power shaping calculations for each reactor cycle by imposing station-specific safety and operational constraints. GAOPT has been verified by performing a number of tests, which are applied to the Hinkley Point B and Hartlepool reactors. The test results giving loading pattern (LP) scenarios obtained from single and multi-cycle optimisation calculations applied to realistic reactor states of the Hartlepool and Hinkley Point B reactors are discussed. The results have shown that the GA/ANN algorithms developed can help the fuel engineer to optimise loading patterns in an efficient and more profitable way than currently available for multi-cycle refuelling of AGRs. Research leading to parallel GAs applied to LP optimisation are outlined, which can be adapted to present day LWR fuel management problems.

Engineering an artificial amoeba propelled by nanoparticle-triggered actin polymerization

Energy Technology Data Exchange (ETDEWEB)

Yi Jinsoo; Schmidt, Jacob; Chien Aichi; Montemagno, Carlo D [Department of Bioengineering, University of California Los Angeles, 420 Westwood Plaza, 7523 Boelter Hall, Los Angeles, CA 90095-1600 (United States)], E-mail: montemcd@ucmail.uc.edu

2009-02-25

We have engineered an amoeba system combining nanofabricated inorganic materials with biological components, capable of propelling itself via actin polymerization. The nanofabricated materials have a mechanism similar to the locomotion of the Listeria monocytogenes, food poisoning bacteria. The propulsive force generation utilizes nanoparticles made from nickel and gold functionalized with the Listeria monocytogenes transmembrane protein, ActA. These Listeria-mimic nanoparticles were in concert with actin, actin binding proteins, ATP (adenosine triphosphate) and encapsulated within a lipid vesicle. This system is an artificial cell, such as a vesicle, where artificial nanobacteria and actin polymerization machinery are used in driving force generators inside the cell. The assembled structure was observed to crawl on a glass surface analogously to an amoeba, with the speed of the movement dependent on the amount of actin monomers and ATP present.

Genetic engineering including superseding microinjection: new ways to make GM pigs.

Science.gov (United States)

Galli, Cesare; Perota, Andrea; Brunetti, Dario; Lagutina, Irina; Lazzari, Giovanna; Lucchini, Franco

2010-01-01

Techniques for genetic engineering of swine are providing genetically modified animals of importance for the field of xenotransplantation, animal models for human diseases and for a variety of research applications. Many of these modifications have been directed toward avoiding naturally existing cellular and antibody responses to species-specific antigens. A number of techniques are today available to engineering the genome of mammals, these range from the well established less efficient method of DNA microinjection into the zygote, the use of viral vectors, to the more recent use of somatic cell nuclear transfer. The use of enzymatic engineering that are being developed now will refine the precision of the genetic modification combined with the use of new vectors like transposons. The use of somatic cell nuclear transfer is currently the most efficient way to generate genetically modified pigs. The development of enzymatic engineering with zinc-finger nucleases, recombinases and transposons will revolutionize the field. Nevertheless, genetic engineering in large domesticated animals will remain a challenging task. Recent improvements in several fields of cell and molecular biology offer new promises and opportunities toward an easier, cost-effective and efficient generation of transgenic pigs. © 2010 John Wiley & Sons A/S.

Refresher Course in Plant Genetic Engineering

Indian Academy of Sciences (India)

A Refresher Course in Plant Genetic Engineering for postgraduate College ... that the teachers can perform the same set of experiments in their respective College/ ... research. The teachers are encouraged to add a note on their 'expectations' ...

A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

Science.gov (United States)

Hancock, Thomas M., III

1994-01-01

This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

GPR utilization in artificial freezing engineering

International Nuclear Information System (INIS)

Song, Lei; Yang, Weihao; Huang, Jiahui; Li, Haipeng; Zhang, Xiaojun

2013-01-01

To utilize ground penetrating radar (GPR) in artificial freezing engineering (AFE), the electromagnetic parameters (EMP) of frozen soil were measured using a vector network analyser, which showed that the dielectric permittivity and electric conductivity change abruptly at the boundary between the frozen and the non-frozen soil. Then similarity criteria of GPR model experiments were deduced, and GPR laboratory model experiments and field explorations of AFE were carried out. It was found that for AFE, the GPR travel time and profile characters of anomalies in model experiments were similar to those in field explorations, while the amplitude of GPR signals in laboratory model experiments were much stronger than those in field explorations. Numerical simulations were also implemented to analyse the relationship between model experiments and field explorations, which further told us why we could easily find the targets by GPR in the laboratory but not in field explorations. The outputs showed that GPR could be used to detect the thickness of the frozen wall and to find unfrozen soil defects, even though the amplitude of the reflective signals were much weaker than those of laboratory experiments. The research findings have an important theoretical value for AFE and permafrost region engineering, and the deduced GPR similarity criteria could be widely used in other GPR model experiments. (paper)

Human Genetic Engineering: A Survey of Student Value Stances

Science.gov (United States)

Wilson, Sara McCormack; And Others

1975-01-01

Assesses the values of high school and college students relative to human genetic engineering and recommends that biology educators explore instructional strategies merging human genetic information with value clarification techniques. (LS)

Artificial neural network modeling of jatropha oil fueled diesel engine for emission predictions

Directory of Open Access Journals (Sweden)

Ganapathy Thirunavukkarasu

2009-01-01

Full Text Available This paper deals with artificial neural network modeling of diesel engine fueled with jatropha oil to predict the unburned hydrocarbons, smoke, and NOx emissions. The experimental data from the literature have been used as the data base for the proposed neural network model development. For training the networks, the injection timing, injector opening pressure, plunger diameter, and engine load are used as the input layer. The outputs are hydrocarbons, smoke, and NOx emissions. The feed forward back propagation learning algorithms with two hidden layers are used in the networks. For each output a different network is developed with required topology. The artificial neural network models for hydrocarbons, smoke, and NOx emissions gave R2 values of 0.9976, 0.9976, and 0.9984 and mean percent errors of smaller than 2.7603, 4.9524, and 3.1136, respectively, for training data sets, while the R2 values of 0.9904, 0.9904, and 0.9942, and mean percent errors of smaller than 6.5557, 6.1072, and 4.4682, respectively, for testing data sets. The best linear fit of regression to the artificial neural network models of hydrocarbons, smoke, and NOx emissions gave the correlation coefficient values of 0.98, 0.995, and 0.997, respectively.

Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation.

Energy Technology Data Exchange (ETDEWEB)

Saffer, Shelley (Sam) I.

2014-12-01

This is a final report of the DOE award DE-SC0001132, Advanced Artificial Science. The development of an artificial science and engineering research infrastructure to facilitate innovative computational modeling, analysis, and application to interdisciplinary areas of scientific investigation. This document describes the achievements of the goals, and resulting research made possible by this award.

Molecular research and genetic engineering of resistance to ...

African Journals Online (AJOL)

This paper reviews the recent research progress on genetic methods of resistance, the status and existing problems, traditional breeding, the main resistance mechanism, molecular markers and genetic engineering of resistance genes. It is hoped that new breeding methods and new varieties resistant to Verticillium wilt will ...

Genetic engineering and sustainable production of ornamentals

DEFF Research Database (Denmark)

Lütken, Henrik Vlk; Clarke, Jihong Liu; Müller, Renate

2012-01-01

Abstract Through the last decades, environmentally and health-friendly production methods and conscientious use of resources have become crucial for reaching the goal of a more sustainable plant production. Protection of the environment requires careful consumption of limited resources and reduct......Abstract Through the last decades, environmentally and health-friendly production methods and conscientious use of resources have become crucial for reaching the goal of a more sustainable plant production. Protection of the environment requires careful consumption of limited resources....... This review presents the more recent progress of genetic engineering in ornamental breeding, delivers an overview of the biological background of the used technologies and critically evaluates the usefulness of the strategies to obtain improved ornamental plants. First, genetic engineering is addressed......, compactness can be accomplished by using a natural transformation approach without recombinant DNA technology. Secondly, metabolic engineering approaches targeting elements of the ethylene signal transduction pathway are summarized as a possible alternative to avoid the use of chemical ethylene inhibitors...

Genetic engineering, a hope for sustainable biofuel production: review

Directory of Open Access Journals (Sweden)

Sudip Paudel

2014-06-01

Full Text Available The use of recently developed genetic engineering tools in combination with organisms that have the potential to produce precursors for the production of biodiesel, promises a sustainable and environment friendly energy source. Enhanced lipid production in wild type and/or genetically engineered organisms can offer sufficient raw material for industrial transesterification of plant-based triglycerides. Bio-diesel, produced with the help of genetically modified organisms, might be one of the best alternatives to fossil fuels and to mitigate various environmental hazards. DOI: http://dx.doi.org/10.3126/ije.v3i2.10644 International Journal of the Environment Vol.3(2 2014: 311-323

Non-genetic engineering of cells for drug delivery and cell-based therapy.

Science.gov (United States)

Wang, Qun; Cheng, Hao; Peng, Haisheng; Zhou, Hao; Li, Peter Y; Langer, Robert

2015-08-30

Cell-based therapy is a promising modality to address many unmet medical needs. In addition to genetic engineering, material-based, biochemical, and physical science-based approaches have emerged as novel approaches to modify cells. Non-genetic engineering of cells has been applied in delivering therapeutics to tissues, homing of cells to the bone marrow or inflammatory tissues, cancer imaging, immunotherapy, and remotely controlling cellular functions. This new strategy has unique advantages in disease therapy and is complementary to existing gene-based cell engineering approaches. A better understanding of cellular systems and different engineering methods will allow us to better exploit engineered cells in biomedicine. Here, we review non-genetic cell engineering techniques and applications of engineered cells, discuss the pros and cons of different methods, and provide our perspectives on future research directions. Copyright © 2014 Elsevier B.V. All rights reserved.

Silk fibroin based biomimetic artificial extracellular matrix for hepatic tissue engineering applications

International Nuclear Information System (INIS)

Kasoju, Naresh; Bora, Utpal

2012-01-01

Hepatic tissue engineering, which aims to construct artificial liver tissues, requires a suitable extracellular matrix (ECM) for growth and proliferation of metabolically active hepatocytes. The current paper describes the development of a biomimetic artificial ECM, for hepatic tissue engineering applications, by mimicking the architectural features and biochemical composition of native ECM. Electrospinning was chosen as the fabrication technique of choice, while regenerated silk fibroin (RSF) and galactosylated chitosan (GalCS) were chosen as materials of choice. Poly(ethylene oxide) was used as a processing aid. Methodical optimization studies were performed to obtain smooth and continuous nanofibers with homogenous size distribution. Extensive characterization studies were performed to determine its morphological, physical, chemical/structural, thermal and cytotoxicity properties. Subsequently, detailed in vitro hepatocyte compatibility studies were performed using HepG2 cell line. Remarkably, the studies revealed that the growth, viability, metabolic activity and proliferation of hepatocytes were relatively superior on RSF–GalCS scaffold than on pure RSF and pure GalCS. In summary, the electrospun nanofibrous RSF–GalCS scaffold tries to mimic both architectural and biochemical features of native ECM, and hence could be an appropriate scaffold for in vitro engineering of hepatic tissue. However, additional experiments are needed to confirm the superiority in characteristic functionality of hepatocytes growing on RSF–GalCS scaffold in relation to RSF and GalCS scaffolds, and to test its behavior in vivo. (paper)

Industry and genetic engineering of plants

International Nuclear Information System (INIS)

Posada, Mario

1995-01-01

The paper is about the importance of the genetic engineering and their development in the plants like is the resistance to the insects, to the mushrooms, retard in the maturation of the fruits and improvement of the quality of vegetables oils, among other aspects

Stirling engine with hydraulic power output for powering artificial hearts

International Nuclear Information System (INIS)

Johnston, R.P.; Noble, J.E.; Emigh, S.G.; White, M.A.; Griffith, W.R.; Perrone, R.E.

1975-01-01

The DWDL heart power source combines the high efficiency of Stirling engines with the reliability, efficiency, and flexibility of hydraulic power transfer and control to ensure long system life and physiological effectiveness. Extended life testing has already been achieved with an engine module; animal in-vivo tests with an assist heart have consistently demonstrated required performance by biological synchronization and effective ventricle relief. The present System 5 can reliably meet near-term thousand-hour animal in-vivo test goals as far as the durability and efficacy of the power source are concerned. Carefully planned development of System 6 has produced major reductions in size and required input power. Research engine tests have provided the basis for achieving performance goals and the approach for further improvement is well established. The near term goal is 33 W heat input with 16 W input projected for normal physical activity. The goal of reduction of engine module volume to 0.9 liter has been achieved. Demonstrated reliability of 292 d for the engine and 35 d for the full system, as well as effectiveness of the artificial heart power source in short-term in-vivo tests indicate that life-limiting problems are now blood pump reliability and the machine-animal interface

Biomedical engineering for health research and development.

Science.gov (United States)

Zhang, X-Y

2015-01-01

Biomedical engineering is a new area of research in medicine and biology, providing new concepts and designs for the diagnosis, treatment and prevention of various diseases. There are several types of biomedical engineering, such as tissue, genetic, neural and stem cells, as well as chemical and clinical engineering for health care. Many electronic and magnetic methods and equipments are used for the biomedical engineering such as Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, Electroencephalography (EEG), Ultrasound and regenerative medicine and stem cell cultures, preparations of artificial cells and organs, such as pancreas, urinary bladders, liver cells, and fibroblasts cells of foreskin and others. The principle of tissue engineering is described with various types of cells used for tissue engineering purposes. The use of several medical devices and bionics are mentioned with scaffold, cells and tissue cultures and various materials are used for biomedical engineering. The use of biomedical engineering methods is very important for the human health, and research and development of diseases. The bioreactors and preparations of artificial cells or tissues and organs are described here.

From Genetics to Genetic Algorithms

Indian Academy of Sciences (India)

artificial genetic system) string feature or ... called the genotype whereas it is called a structure in artificial genetic ... assigned a fitness value based on the cost function. Better ..... way it has produced complex, intelligent living organisms capable of ...

How to teach artificial organs.

Science.gov (United States)

Zapanta, Conrad M; Borovetz, Harvey S; Lysaght, Michael J; Manning, Keefe B

2011-01-01

Artificial organs education is often an overlooked field for many bioengineering and biomedical engineering students. The purpose of this article is to describe three different approaches to teaching artificial organs. This article can serve as a reference for those who wish to offer a similar course at their own institutions or incorporate these ideas into existing courses. Artificial organ classes typically fulfill several ABET (Accreditation Board for Engineering and Technology) criteria, including those specific to bioengineering and biomedical engineering programs.

76 FR 5780 - Determination of Regulated Status of Alfalfa Genetically Engineered for Tolerance to the...

Science.gov (United States)

2011-02-02

...] Determination of Regulated Status of Alfalfa Genetically Engineered for Tolerance to the Herbicide Glyphosate... decision and determination on the petition regarding the regulated status of alfalfa genetically engineered... regulated status of alfalfa genetically engineered for tolerance to the herbicide glyphosate based on an...

Artificially Expanded Genetic Information Systems for New Aptamer Technologies

Directory of Open Access Journals (Sweden)

Elisa Biondi

2018-05-01

Full Text Available Directed evolution was first applied to diverse libraries of DNA and RNA molecules a quarter century ago in the hope of gaining technology that would allow the creation of receptors, ligands, and catalysts on demand. Despite isolated successes, the outputs of this technology have been somewhat disappointing, perhaps because the four building blocks of standard DNA and RNA have too little functionality to have versatile binding properties, and offer too little information density to fold unambiguously. This review covers the recent literature that seeks to create an improved platform to support laboratory Darwinism, one based on an artificially expanded genetic information system (AEGIS that adds independently replicating nucleotide “letters” to the evolving “alphabet”.

Genetically engineered rice. The source of β-carotene

Directory of Open Access Journals (Sweden)

Karol Terlecki

2014-04-01

Full Text Available β-carotene is a precursor of vitamin A. It is converted to vitamin A in the humans intestine by the β-carotene-15,15’-monooxygenase. Vitamin A is essential to support vision, as an antioxidant it protects the body from free radicals, it helps to integrate the immune system, as well as takes part in cellular differentiation and proliferation. Vitamin A deficiency is a major public health problem especially among developing countries. Nyctalopia, commonly known as „Night Blindness” is one of the major symptoms of Vitamin A deficiency (VAD. Plants such as apricots, broccoli, carrots, and sweet potatoes are rich in β-carotene. Some of the plants are characterized by a higher content of provitamin-A. Among vegetables rich sources of β-carotene are: carrots, pumpkin, spinach, lettuce, green peas, tomatoes, watercress, broccoli and parsley leaves. Amongst fruits the highest content of β-carotene is in apricot, cherry, sweet cherry, plum, orange and mango. The aim of the present study was to analyze available literature data of increasing the content of β-carotene in genetically engineered rice. The genetically modified cultivar contains additional genes: PSY and CRTI thanks to which rice seed endosperm contains β-carotene. Genetically engineered rice with β-carotene is an effective source of vitamin A, it contains approximately 30 μg β-carotene per 1 g. Fortunately some of the advantages of Genetically Modified Food give an opportunity to reduce VAD worldwide, by introducing the rice which has been genetically engineered to be rich in β-carotene. The popularity of this plant as an element of nutrition is simultaneously a source of vitamin A.

A genetic-neural artificial intelligence approach to resins optimization; Uma metodologia baseada em inteligencia artificial para otimizacao de resinas

Energy Technology Data Exchange (ETDEWEB)

Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: lapa@ien.gov.br; mbarros@ien.gov.br

2005-07-01

This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

Science.gov (United States)

Tong, S. S.

1986-01-01

The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

Optimization the Initial Weights of Artificial Neural Networks via Genetic Algorithm Applied to Hip Bone Fracture Prediction

Directory of Open Access Journals (Sweden)

Yu-Tzu Chang

2012-01-01

Full Text Available This paper aims to find the optimal set of initial weights to enhance the accuracy of artificial neural networks (ANNs by using genetic algorithms (GA. The sample in this study included 228 patients with first low-trauma hip fracture and 215 patients without hip fracture, both of them were interviewed with 78 questions. We used logistic regression to select 5 important factors (i.e., bone mineral density, experience of fracture, average hand grip strength, intake of coffee, and peak expiratory flow rate for building artificial neural networks to predict the probabilities of hip fractures. Three-layer (one hidden layer ANNs models with back-propagation training algorithms were adopted. The purpose in this paper is to find the optimal initial weights of neural networks via genetic algorithm to improve the predictability. Area under the ROC curve (AUC was used to assess the performance of neural networks. The study results showed the genetic algorithm obtained an AUC of 0.858±0.00493 on modeling data and 0.802 ± 0.03318 on testing data. They were slightly better than the results of our previous study (0.868±0.00387 and 0.796±0.02559, resp.. Thus, the preliminary study for only using simple GA has been proved to be effective for improving the accuracy of artificial neural networks.

Genetic engineering for improvement of Musa production in Africa ...

African Journals Online (AJOL)

The transgenic approach shows potential for the genetic improvement of the crop using a wide set of transgenes currently available which may confer resistance to nematode pests, fungal, bacterial and viral diseases. This article discusses the applications of genetic engineering for the enhancement of Musa production.

Estimation of operational parameters for a direct injection turbocharged spark ignition engine by using regression analysis and artificial neural network

Directory of Open Access Journals (Sweden)

Tosun Erdi

2017-01-01

Full Text Available This study was aimed at estimating the variation of several engine control parameters within the rotational speed-load map, using regression analysis and artificial neural network techniques. Duration of injection, specific fuel consumption, exhaust gas at turbine inlet, and within the catalytic converter brick were chosen as the output parameters for the models, while engine speed and brake mean effective pressure were selected as independent variables for prediction. Measurements were performed on a turbocharged direct injection spark ignition engine fueled with gasoline. A three-layer feed-forward structure and back-propagation algorithm was used for training the artificial neural network. It was concluded that this technique is capable of predicting engine parameters with better accuracy than linear and non-linear regression techniques.

Induction of atherosclerosis in mice and hamsters without germline genetic engineering

DEFF Research Database (Denmark)

Bjørklund, Martin Mæng; Hollensen, Anne Kruse; Hagensen, Mette Kallestrup

2014-01-01

RATIONALE: Atherosclerosis can be achieved in animals by germline genetic engineering, leading to hypercholesterolemia, but such models are constrained to few species and strains, and they are difficult to combine with other powerful techniques involving genetic manipulation or variation. OBJECTIVE......: To develop a method for induction of atherosclerosis without germline genetic engineering. METHODS AND RESULTS: Recombinant adeno-associated viral vectors were engineered to encode gain-of-function proprotein convertase subtilisin/kexin type 9 mutants, and mice were given a single intravenous vector...... injection followed by high-fat diet feeding. Plasma proprotein convertase subtilisin/kexin type 9 and total cholesterol increased rapidly and were maintained at high levels, and after 12 weeks, mice had atherosclerotic lesions in the aorta. Histology of the aortic root showed progression of lesions...

Exergetic optimization of turbofan engine with genetic algorithm method

Energy Technology Data Exchange (ETDEWEB)

Turan, Onder [Anadolu University, School of Civil Aviation (Turkey)], e-mail: onderturan@anadolu.edu.tr

2011-07-01

With the growth of passenger numbers, emissions from the aeronautics sector are increasing and the industry is now working on improving engine efficiency to reduce fuel consumption. The aim of this study is to present the use of genetic algorithms, an optimization method based on biological principles, to optimize the exergetic performance of turbofan engines. The optimization was carried out using exergy efficiency, overall efficiency and specific thrust of the engine as evaluation criteria and playing on pressure and bypass ratio, turbine inlet temperature and flight altitude. Results showed exergy efficiency can be maximized with higher altitudes, fan pressure ratio and turbine inlet temperature; the turbine inlet temperature is the most important parameter for increased exergy efficiency. This study demonstrated that genetic algorithms are effective in optimizing complex systems in a short time.

Molecular profiling techniques as tools to detect potential unintended effects in genetically engineered maize

CSIR Research Space (South Africa)

Barros, E

2010-05-01

Full Text Available Molecular Profiling Techniques as Tools to Detect Potential Unintended Effects in Genetically Engineered Maize Eugenia Barros Introduction In the early stages of production and commercialization of foods derived from genetically engineered (GE) plants... systems. In a recent paper published in Plant Biotechnology Journal,4 we compared two transgenic white maize lines with the non-transgenic counterpart to investigate two possible sources of variation: genetic engineering and environmental variation...

human genetic engineering and social justice in south africa

African Journals Online (AJOL)

resources, are also acutely visible in the health-care sector. Genetic ... engineering (GE)2 from a South African perspective might not, initially, seem like an obvious ... prevalence of so-called genetic tourism, where couples from developed countries travel to countries in the developing world to undergo in vitro fertilisation ...

Artificial intelligence applied to fuel management in BWR type reactors; Inteligencia artificial aplicada a la administracion de combustible en reactores BWR

Energy Technology Data Exchange (ETDEWEB)

Ortiz S, J.J

1998-10-01

In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

"Genetic Engineering" Gains Momentum (Science/Society Case Study).

Science.gov (United States)

Moore, John W.; Moore, Elizabeth A., Eds.

1980-01-01

Reviews the benefits and hazards of genetic engineering, or "recombinant-DNA" research. Recent federal safety rules issued by NIH which ease the strict prohibitions on recombinant-DNA research are explained. (CS)

Chromosome engineering: power tools for plant genetics.

Science.gov (United States)

Chan, Simon W L

2010-12-01

The term "chromosome engineering" describes technologies in which chromosomes are manipulated to change their mode of genetic inheritance. This review examines recent innovations in chromosome engineering that promise to greatly increase the efficiency of plant breeding. Haploid Arabidopsis thaliana have been produced by altering the kinetochore protein CENH3, yielding instant homozygous lines. Haploid production will facilitate reverse breeding, a method that downregulates recombination to ensure progeny contain intact parental chromosomes. Another chromosome engineering success is the conversion of meiosis into mitosis, which produces diploid gametes that are clones of the parent plant. This is a key step in apomixis (asexual reproduction through seeds) and could help to preserve hybrid vigor in the future. New homologous recombination methods in plants will potentiate many chromosome engineering applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

Engineered artificial antigen presenting cells facilitate direct and efficient expansion of tumor infiltrating lymphocytes

Directory of Open Access Journals (Sweden)

Coukos George

2011-08-01

Full Text Available Abstract Background Development of a standardized platform for the rapid expansion of tumor-infiltrating lymphocytes (TILs with anti-tumor function from patients with limited TIL numbers or tumor tissues challenges their clinical application. Methods To facilitate adoptive immunotherapy, we applied genetically-engineered K562 cell-based artificial antigen presenting cells (aAPCs for the direct and rapid expansion of TILs isolated from primary cancer specimens. Results TILs outgrown in IL-2 undergo rapid, CD28-independent expansion in response to aAPC stimulation that requires provision of exogenous IL-2 cytokine support. aAPCs induce numerical expansion of TILs that is statistically similar to an established rapid expansion method at a 100-fold lower feeder cell to TIL ratio, and greater than those achievable using anti-CD3/CD28 activation beads or extended IL-2 culture. aAPC-expanded TILs undergo numerical expansion of tumor antigen-specific cells, remain amenable to secondary aAPC-based expansion, and have low CD4/CD8 ratios and FOXP3+ CD4+ cell frequencies. TILs can also be expanded directly from fresh enzyme-digested tumor specimens when pulsed with aAPCs. These "young" TILs are tumor-reactive, positively skewed in CD8+ lymphocyte composition, CD28 and CD27 expression, and contain fewer FOXP3+ T cells compared to parallel IL-2 cultures. Conclusion Genetically-enhanced aAPCs represent a standardized, "off-the-shelf" platform for the direct ex vivo expansion of TILs of suitable number, phenotype and function for use in adoptive immunotherapy.

Functional evaluation of artificial skeletal muscle tissue constructs fabricated by a magnetic force-based tissue engineering technique.

Science.gov (United States)

Yamamoto, Yasunori; Ito, Akira; Fujita, Hideaki; Nagamori, Eiji; Kawabe, Yoshinori; Kamihira, Masamichi

2011-01-01

Skeletal muscle tissue engineering is currently applied in a variety of research fields, including regenerative medicine, drug screening, and bioactuator development, all of which require the fabrication of biomimic and functional skeletal muscle tissues. In the present study, magnetite cationic liposomes were used to magnetically label C2C12 myoblast cells for the construction of three-dimensional artificial skeletal muscle tissues by an applied magnetic force. Skeletal muscle functions, such as biochemical and contractile properties, were evaluated for the artificial tissue constructs. Histological studies revealed that elongated and multinucleated myotubes were observed within the tissue. Expression of muscle-specific markers, such as myogenin, myosin heavy chain and tropomyosin, were detected in the tissue constructs by western blot analysis. Further, creatine kinase activity increased during differentiation. In response to electric pulses, the artificial tissue constructs contracted to generate a physical force (the maximum twitch force, 33.2 μN [1.06 mN/mm2]). Rheobase and chronaxie of the tissue were determined as 4.45 V and 0.72 ms, respectively. These results indicate that the artificial skeletal muscle tissue constructs fabricated in this study were physiologically functional and the data obtained for the evaluation of their functional properties may provide useful information for future skeletal muscle tissue engineering studies.

Genetic Engineering In BioButanol Production And Tolerance

Directory of Open Access Journals (Sweden)

Ashok Rao

Full Text Available ABSTRACT The growing need to address current energy and environmental problems has sparked an interest in developing improved biological methods to produce liquid fuels from renewable sources. Higher-chain alcohols possess chemical properties that are more similar to gasoline. Ethanol and butanol are two products which are used as biofuel. Butanol production was more concerned than ethanol because of its high octane number. Unfortunately, these alcohols are not produced efficiently in natural microorganisms, and thus economical production in industrial volumes remains a challenge. The synthetic biology, however, offers additional tools to engineer synthetic pathways in user-friendly hosts to help increase titers and productivity of bio-butanol. Knock out and over-expression of genes is the major approaches towards genetic manipulation and metabolic engineering of microbes. Yet there are TargeTron Technology, Antisense RNA and CRISPR technology has a vital role in genome manipulation of C.acetobutylicum. This review concentrates on the recent developments for efficient production of butanol and butanol tolerance by various genetically engineered microbes.

Reliability analysis of C-130 turboprop engine components using artificial neural network

Science.gov (United States)

Qattan, Nizar A.

In this study, we predict the failure rate of Lockheed C-130 Engine Turbine. More than thirty years of local operational field data were used for failure rate prediction and validation. The Weibull regression model and the Artificial Neural Network model including (feed-forward back-propagation, radial basis neural network, and multilayer perceptron neural network model); will be utilized to perform this study. For this purpose, the thesis will be divided into five major parts. First part deals with Weibull regression model to predict the turbine general failure rate, and the rate of failures that require overhaul maintenance. The second part will cover the Artificial Neural Network (ANN) model utilizing the feed-forward back-propagation algorithm as a learning rule. The MATLAB package will be used in order to build and design a code to simulate the given data, the inputs to the neural network are the independent variables, the output is the general failure rate of the turbine, and the failures which required overhaul maintenance. In the third part we predict the general failure rate of the turbine and the failures which require overhaul maintenance, using radial basis neural network model on MATLAB tool box. In the fourth part we compare the predictions of the feed-forward back-propagation model, with that of Weibull regression model, and radial basis neural network model. The results show that the failure rate predicted by the feed-forward back-propagation artificial neural network model is closer in agreement with radial basis neural network model compared with the actual field-data, than the failure rate predicted by the Weibull model. By the end of the study, we forecast the general failure rate of the Lockheed C-130 Engine Turbine, the failures which required overhaul maintenance and six categorical failures using multilayer perceptron neural network (MLP) model on DTREG commercial software. The results also give an insight into the reliability of the engine

Food safety evaluation of crops produced through genetic engineering--how to reduce unintended effects?

Science.gov (United States)

Jelenić, Srećko

2005-06-01

Scientists started applying genetic engineering techniques to improve crops two decades ago; about 70 varieties obtained via genetic engineering have been approved to date. Although genetic engineering offers the most precise and controllable genetic modification of crops in entire history of plant improvement, the site of insertion of a desirable gene cannot be predicted during the application of this technology. As a consequence, unintended effects might occur due to activation or silencing of genes, giving rise to allergic reactions or toxicity. Therefore, extensive chemical, biochemical and nutritional analyses are performed on each new genetically engineered variety. Since the unintended effects may be predictable on the basis of what is known about the insertion place of the transgenic DNA, an important aim of plant biotechnology is to define techniques for the insertion of transgene into the predetermined chromosomal position (gene targeting). Although gene targeting cannot be applied routinely in crop plants, given the recent advances, that goal may be reached in the near future.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

Science.gov (United States)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

A New Approach to Tuning Heuristic Parameters of Genetic Algorithms

Czech Academy of Sciences Publication Activity Database

Holeňa, Martin

2006-01-01

Roč. 3, č. 3 (2006), s. 562-569 ISSN 1790-0832. [AIKED'06. WSEAS International Conference on Artificial Intelligence , Knowledge Engineering and Data Bases. Madrid, 15.02.2006-17.02.2006] R&D Projects: GA ČR(CZ) GA201/05/0325; GA ČR(CZ) GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary optimization * genetic algorithms * heuristic parameters * parameter tuning * artificial neural networks * convergence speed * population diversity Subject RIV: IN - Informatics, Computer Science

Artificial neural network approach to predicting engine-out emissions and performance parameters of a turbo charged diesel engine

Directory of Open Access Journals (Sweden)

Özener Orkun

2013-01-01

Full Text Available This study details the artificial neural network (ANN modelling of a diesel engine to predict the torque, power, brake-specific fuel consumption and pollutant emissions, including carbon dioxide, carbon monoxide, nitrogen oxides, total hydrocarbons and filter smoke number. To collect data for training and testing the neural network, experiments were performed on a four cylinder, four stroke compression ignition engine. A total of 108 test points were run on a dynamometer. For the first part of this work, a parameter packet was used as the inputs for the neural network, and satisfactory regression was found with the outputs (over ~95%, excluding total hydrocarbons. The second stage of this work addressed developing new networks with additional inputs for predicting the total hydrocarbons, and the regression was raised from 75 % to 90 %. This study shows that the ANN approach can be used for accurately predicting characteristic values of an internal combustion engine and that the neural network performance can be increased using additional related input data.

Genetically engineered tissue to screen for glycan function in tissue formation

DEFF Research Database (Denmark)

M., Adamopoulou; E.M., Pallesen; A., Levann

2017-01-01

engineered GlycoSkin tissue models can be used to study biological interactions involving glycan structure on lipids, or glycosaminoglycans. This engineering approach will allow us to investigate the functions of glycans in homeostasis and elucidate the role of glycans in normal epithelial formation....... We use genetic engineering with CRISPR/Cas9 combined with 3D organotypic skin models to examine how distinct glycans influence epithelial formation. We have performed knockout and knockin of more than 100 select genes in the genome of human immortalized human keratinocytes, enabling a systematic...... analysis of the impact of specific glycans in the formation and transformation of the human skin. The genetic engineered human skin models (GlycoSkin) was designed with and without all major biosynthetic pathways in mammalian glycan biosynthesis, including GalNAc-O-glycans, O-fucosylation, O...

Engineering of frustration in colloidal artificial ices realized on microfeatured grooved lattices

Science.gov (United States)

Tierno, Pietro

Artificial spin-ice systems, namely lattices of interacting single domain ferromagnetic islands, have been used to date as microscopic models of frustration induced by lattice topology, allowing for the direct visualization of spin arrangements and textures. However, the engineering of frustrated ice states in which individual spins can be manipulated in situ and the real-time observation of their collective dynamics remain both challenging tasks. Inspired by recent theoretical advances, we realize a colloidal version of an artificial spin ice system using interacting polarizable particles confined to lattices of bistable gravitational traps. We show quantitatively that ice-selection rules emerge in this frustrated soft matter system by tuning the strength of the pair-interactions between the microscopic units. Via independent control of particle positioning and dipolar coupling, we introduce monopole-like defects and strings and use loops with defined chirality as an elementary unit to store binary information.

A comparative study on genetic effects of artificial and natural habitat fragmentation on Loropetalum chinense (Hamamelidaceae) in Southeast China.

Science.gov (United States)

Yuan, N; Comes, H P; Cao, Y N; Guo, R; Zhang, Y H; Qiu, Y X

2015-06-01

Elucidating the demographic and landscape features that determine the genetic effects of habitat fragmentation has become fundamental to research in conservation and evolutionary biology. Land-bridge islands provide ideal study areas for investigating the genetic effects of habitat fragmentation at different temporal and spatial scales. In this context, we compared patterns of nuclear microsatellite variation between insular populations of a shrub of evergreen broad-leaved forest, Loropetalum chinense, from the artificially created Thousand-Island Lake (TIL) and the Holocene-dated Zhoushan Archipelago of Southeast China. Populations from the TIL region harboured higher levels of genetic diversity than those from the Zhoushan Archipelago, but these differences were not significant. There was no correlation between genetic diversity and most island features, excepting a negative effect of mainland-island distance on allelic richness and expected heterozygosity in the Zhoushan Archipelago. In general, levels of gene flow among island populations were moderate to high, and tests of alternative models of population history strongly favoured a gene flow-drift model over a pure drift model in each region. In sum, our results showed no obvious genetic effects of habitat fragmentation due to recent (artificial) or past (natural) island formation. Rather, they highlight the importance of gene flow (most likely via seed) in maintaining genetic variation and preventing inter-population differentiation in the face of habitat 'insularization' at different temporal and spatial scales.

Genetic Engineering of Mesenchymal Stem Cells for Regenerative Medicine.

Science.gov (United States)

Nowakowski, Adam; Walczak, Piotr; Janowski, Miroslaw; Lukomska, Barbara

2015-10-01

Mesenchymal stem cells (MSCs), which can be obtained from various organs and easily propagated in vitro, are one of the most extensively used types of stem cells and have been shown to be efficacious in a broad set of diseases. The unique and highly desirable properties of MSCs include high migratory capacities toward injured areas, immunomodulatory features, and the natural ability to differentiate into connective tissue phenotypes. These phenotypes include bone and cartilage, and these properties predispose MSCs to be therapeutically useful. In addition, MSCs elicit their therapeutic effects by paracrine actions, in which the metabolism of target tissues is modulated. Genetic engineering methods can greatly amplify these properties and broaden the therapeutic capabilities of MSCs, including transdifferentiation toward diverse cell lineages. However, cell engineering can also affect safety and increase the cost of therapy based on MSCs; thus, the advantages and disadvantages of these procedures should be discussed. In this review, the latest applications of genetic engineering methods for MSCs with regenerative medicine purposes are presented.

Genetic engineering: a matter that requires further refinement in Spanish secondary school textbooks

Science.gov (United States)

Martínez-Gracia, M. V.; Gil-Quýlez, M. J.

2003-09-01

Genetic engineering is now an integral part of many high school textbooks but little work has been done to assess whether it is being properly addressed. A checklist with 19 items was used to analyze how genetic engineering is presented in biology textbooks commonly used in Spanish high schools, including the content, its relationship with fundamental genetic principles, and how it aims to improve the genetic literacy of students. The results show that genetic engineering was normally introduced without a clear reference to the universal genetic code, protein expression or the genetic material shared by all species. In most cases it was poorly defined, without a clear explanation of all the relevant processes involved. Some procedures (such as vectors) were explained in detail without considering previous student knowledge or skills. Some books emphasized applications such as the human genome project without describing DNA sequencing. All books included possible repercussions, but in most cases only fashionable topics such as human cloning. There was an excess of information that was not always well founded and hence was unsuitable to provide a meaningful understanding of DNA technology required for citizens in the twenty-first century.

Role of plant biotechnology and genetic engineering in crop-improvement, with special emphases on cotton: A review

International Nuclear Information System (INIS)

Akhtar, L.H.; Siddiq, S.Z.; Tariq, A.H.; Arshad, M.; Gorham, J.

2003-01-01

Plant biotechnology and genetic engineering offer novel approaches to plant-breeding, production, propagation and preservation of germplasm. In this manuscript, the population and food-requirements of Pakistan, role of biotechnology and genetic engineering in crop-improvement, along with potential uses in cotton, have been discussed. The latest position of plant biotechnology and genetic engineering in Pakistan and the advantages of biotechnology and genetic-engineering techniques over conventional plant-breeding techniques, along with critical views of various scientists have been reviewed. (author)

Possible Health Hazards from Genetically Engineered Crops ...

African Journals Online (AJOL)

The paradox of Genetic Engineering of crops is evident from the unending revolution in the seeding and growth of new multibillion naira industries while it also poses the greatest hazards to life on the planet Earth. Recombination DNA technology is used to insert, delete, transpose and substitute new genes in plants that ...

Genetic engineering: frost damage trial halted.

Science.gov (United States)

Budiansky, S

The University of California at Berkeley has announced the postponement of a planned experiment involving the field testing of bacteria genetically engineered to reduce frost damage to crops. The action came after Jeremy Rifkin, who had earlier filed suit against the National Institutes of Health after its Recombinant DNA Advisory Committee had approved the experiment, threatened to seek a temporary restraining order against the university to halt the experiment.

Prediction of biodiesel ignition delay in a diesel engine using artificial neural networks

International Nuclear Information System (INIS)

Piloto-Rodríguez, Ramón; Sánchez-Borroto, Yisel

2017-01-01

Ignition delay is one of the most important parameters of the combustion process and have a strong influence in exhaust emissions and engines performance. In the present work, the results of the mathematical modeling of ignition delay through artificial neural networks are shown. The modeling starts from input values that cover thermodynamic variables, engines parameters and biodiesel properties. The model obtained is only useful for biodiesel samples and several neural network algorithms were applied in order to predict the ignition delay. From its correlation coefficient, prediction capability and lowest absolute error, the best model was selected. Among other network’s input parameters, the cetane number was taken into account, also previously predicted by the use of ANN. (author)

Genetic Engineering: A Matter that Requires Further Refinement in Spanish Secondary School Textbooks

Science.gov (United States)

Martinez-Gracia, M. V.; Gil-Quylez, M. J.; Osada, J.

2003-01-01

Genetic engineering is now an integral part of many high school textbooks but little work has been done to assess whether it is being properly addressed. A checklist with 19 items was used to analyze how genetic engineering is presented in biology textbooks commonly used in Spanish high schools, including the content, its relationship with…

Agrobacterium: nature's genetic engineer.

Science.gov (United States)

Nester, Eugene W

2014-01-01

Agrobacterium was identified as the agent causing the plant tumor, crown gall over 100 years ago. Since then, studies have resulted in many surprising observations. Armin Braun demonstrated that Agrobacterium infected cells had unusual nutritional properties, and that the bacterium was necessary to start the infection but not for continued tumor development. He developed the concept of a tumor inducing principle (TIP), the factor that actually caused the disease. Thirty years later the TIP was shown to be a piece of a tumor inducing (Ti) plasmid excised by an endonuclease. In the next 20 years, most of the key features of the disease were described. The single-strand DNA (T-DNA) with the endonuclease attached is transferred through a type IV secretion system into the host cell where it is likely coated and protected from nucleases by a bacterial secreted protein to form the T-complex. A nuclear localization signal in the endonuclease guides the transferred strand (T-strand), into the nucleus where it is integrated randomly into the host chromosome. Other secreted proteins likely aid in uncoating the T-complex. The T-DNA encodes enzymes of auxin, cytokinin, and opine synthesis, the latter a food source for Agrobacterium. The genes associated with T-strand formation and transfer (vir) map to the Ti plasmid and are only expressed when the bacteria are in close association with a plant. Plant signals are recognized by a two-component regulatory system which activates vir genes. Chromosomal genes with pleiotropic functions also play important roles in plant transformation. The data now explain Braun's old observations and also explain why Agrobacterium is nature's genetic engineer. Any DNA inserted between the border sequences which define the T-DNA will be transferred and integrated into host cells. Thus, Agrobacterium has become the major vector in plant genetic engineering.

Artificial hammerhead ribozymes: engineering and applications

International Nuclear Information System (INIS)

Vorobjeva, M A; Davydova, A S; Venyaminova, Aliya G

2011-01-01

The properties of hammerhead ribozymes are described. Various hammerhead ribozyme constructs for target RNA cleavage were considered. Approaches to enhancement of the stability of artificial ribozymes in biological media and to regulation of the catalytic activity of hammerhead ribozymes using effector molecules are described. The effect of ribozymes on extended structured natural RNAs is discussed. Applications of artificial hammerhead ribozymes as inhibitors of gene expression at matrix RNA level were considered.

76 FR 8707 - Syngenta Seeds, Inc.; Determination of Nonregulated Status for Corn Genetically Engineered To...

Science.gov (United States)

2011-02-15

... Organisms and Products Altered or Produced Through Genetic Engineering Which Are Plant Pests or Which There... genetic engineering that are plant pests or that there is reason to believe are plant pests. Such...

Artificial intelligence applied to fuel management in BWR type reactors

International Nuclear Information System (INIS)

Ortiz S, J.J.

1998-01-01

In this work two techniques of artificial intelligence, neural networks and genetic algorithms were applied to a practical problem of nuclear fuel management; the determination of the optimal fuel reload for a BWR type reactor. This is an important problem in the design of the operation cycle of the reactor. As a result of the application of these techniques, comparable or even better reloads proposals than those given by expert companies in the subject were obtained. Additionally, two other simpler problems in reactor physics were solved: the determination of the axial power profile and the prediction of the value of some variables of interest at the end of the operation cycle of the reactor. Neural networks and genetic algorithms have been applied to solve many problems of engineering because of their versatility but they have been rarely used in the area of fuel management. The results obtained in this thesis indicates the convenience of undertaking further work on this area and suggest the application of these techniques of artificial intelligence to the solution of other problems in nuclear reactor physics. (Author)

Artificial playing surfaces research: a review of medical, engineering and biomechanical aspects.

Science.gov (United States)

Dixon, S J; Batt, M E; Collop, A C

1999-05-01

In this paper, current knowledge of artificial playing surfaces is reviewed. Research status in the fields of sports medicine, engineering and biomechanics is described. A multidisciplinary approach to the study of artificial sports surface properties is recommended. The development of modelling techniques to characterise fundamental material properties is described as the most appropriate method for the unique specification of material properties such as stiffness and damping characteristics. It is suggested that the systematic manipulation of fundamental surface material properties in biomechanics research will allow the identification of subject responses to clearly defined surface variation. It is suggested that subjects should be grouped according to characteristic behaviour on specific sports surfaces. It is speculated that future biomechanics research will identify subject criterion related to differing group responses. The literature evidence of interactions between sports shoes and sports surfaces leads to the suggestion that sports shoe and sports surface companies should work together in the development of ideal shoe - surface combinations for particular groups of subjects.

The experimental study of genetic engineering human neural stem cells mediated by lentivirus to express multigene.

Science.gov (United States)

Cai, Pei-qiang; Tang, Xun; Lin, Yue-qiu; Martin, Oudega; Sun, Guang-yun; Xu, Lin; Yang, Yun-kang; Zhou, Tian-hua

2006-02-01

To explore the feasibility to construct genetic engineering human neural stem cells (hNSCs) mediated by lentivirus to express multigene in order to provide a graft source for further studies of spinal cord injury (SCI). Human neural stem cells from the brain cortex of human abortus were isolated and cultured, then gene was modified by lentivirus to express both green fluorescence protein (GFP) and rat neurotrophin-3 (NT-3); the transgenic expression was detected by the methods of fluorescence microscope, dorsal root ganglion of fetal rats and slot blot. Genetic engineering hNSCs were successfully constructed. All of the genetic engineering hNSCs which expressed bright green fluorescence were observed under the fluorescence microscope. The conditioned medium of transgenic hNSCs could induce neurite flourishing outgrowth from dorsal root ganglion (DRG). The genetic engineering hNSCs expressed high level NT-3 which could be detected by using slot blot. Genetic engineering hNSCs mediated by lentivirus can be constructed to express multigene successfully.

From Precaution to Peril: Public Relations Across Forty Years of Genetic Engineering.

Science.gov (United States)

Hogan, Andrew J

2016-12-01

The Asilomar conference on genetic engineering in 1975 has long been pointed to by scientists as a model for internal regulation and public engagement. In 2015, the organizers of the International Summit on Human Gene Editing in Washington, DC looked to Asilomar as they sought to address the implications of the new CRISPR gene editing technique. Like at Asilomar, the conveners chose to limit the discussion to a narrow set of potential CRISPR applications, involving inheritable human genome editing. The adoption by scientists in 2015 of an Asilomar-like script for discussing genetic engineering offers historians the opportunity to analyze the adjustments that have been made since 1975, and to identify the blind spots that remain in public engagement. Scientists did take important lessons from the fallout of their limited engagement with public concerns at Asilomar. Nonetheless, the scientific community has continued to overlook some of the longstanding public concerns about genetic engineering, in particular the broad and often covert genetic modification of food products. Copyright © 2016 Elsevier Ltd. All rights reserved.

76 FR 78232 - Monsanto Co.; Determination of Nonregulated Status for Soybean Genetically Engineered To Have a...

Science.gov (United States)

2011-12-16

... peer review of safety tests, and health effects of genetically modified organisms and glyphosate. APHIS...] Monsanto Co.; Determination of Nonregulated Status for Soybean Genetically Engineered To Have a Modified... that there is reason to believe are plant pests. Such genetically engineered organisms and products are...

U.S. Adults with Agricultural Experience Report More Genetic Engineering Familiarity than Those Without

Science.gov (United States)

Stofer, Kathryn A.; Schiebel, Tracee M.

2017-01-01

Researchers and pollsters still debate the acceptance of genetic engineering technology among U.S. adults, and continue to assess their knowledge as part of this research. While decision-making may not rely entirely on knowledge, querying opinions and perceptions rely on public understanding of genetic engineering terms. Experience with…

A new optimization framework using genetic algorithm and artificial neural network to reduce uncertainties in petroleum reservoir models

Science.gov (United States)

Maschio, Célio; José Schiozer, Denis

2015-01-01

In this article, a new optimization framework to reduce uncertainties in petroleum reservoir attributes using artificial intelligence techniques (neural network and genetic algorithm) is proposed. Instead of using the deterministic values of the reservoir properties, as in a conventional process, the parameters of the probability density function of each uncertain attribute are set as design variables in an optimization process using a genetic algorithm. The objective function (OF) is based on the misfit of a set of models, sampled from the probability density function, and a symmetry factor (which represents the distribution of curves around the history) is used as weight in the OF. Artificial neural networks are trained to represent the production curves of each well and the proxy models generated are used to evaluate the OF in the optimization process. The proposed method was applied to a reservoir with 16 uncertain attributes and promising results were obtained.

Intrinsic Value and the Genetic Engineering of Animals.

NARCIS (Netherlands)

Vries, R.B.M. de

2008-01-01

The concept of intrinsic value is often invoked to articulate objections to the genetic engineering of animals, particularly those objections that are not directed at the negative effects the technique might have on the health and welfare of the modified animals. However, this concept was not

University Students' Knowledge and Attitude about Genetic Engineering

Science.gov (United States)

Bal, Senol; Samanci, Nilay Keskin; Bozkurt, Orçun

2007-01-01

Genetic engineering and biotechnology made possible of gene transfer without discriminating microorganism, plant, animal or human. However, although these scientific techniques have benefits, they cause arguments because of their ethical and social impacts. The arguments about ethical ad social impacts of biotechnology made clear that not only…

Genetic engineering with T cell receptors.

Science.gov (United States)

Zhang, Ling; Morgan, Richard A

2012-06-01

In the past two decades, human gene transfer research has been translated from a laboratory technology to clinical evaluation. The success of adoptive transfer of tumor-reactive lymphocytes to treat the patients with metastatic melanoma has led to new strategies to redirect normal T cells to recognize tumor antigens by genetic engineering with tumor antigen-specific T cell receptor (TCR) genes. This new strategy can generate large numbers of defined antigen-specific cells for therapeutic application. Much progress has been made to TCR gene transfer systems by optimizing gene expression and gene transfer protocols. Vector and protein modifications have enabled excellent expression of introduced TCR chains in human lymphocytes with reduced mis-pairing between the introduced and endogenous TCR chains. Initial clinical studies have demonstrated that TCR gene-engineered T cells could mediate tumor regression in vivo. In this review, we discuss the progress and prospects of TCR gene-engineered T cells as a therapeutic strategy for treating patients with melanoma and other cancers. Published by Elsevier B.V.

Optimal approximation of linear systems by artificial immune response

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

History and future of genetically engineered food animal regulation: an open request.

Science.gov (United States)

Wells, Kevin D

2016-06-01

Modern biotechnology resulted from of a series of incremental improvements in the understanding of DNA and the enzymes that nature evolved to manipulate it. As the potential impact of genetic engineering became apparent, scientists began the process of trying to identify the potential unintended consequences. Restrictions to recombinant DNA experimentation were at first self-imposed. Collaborative efforts between scientists and lawyers formalized an initial set of guidelines. These guidelines have been used to promulgate regulations around world. However, the initial guidelines were only intended as a starting point and were motivated by a specific set of concerns. As new data became available, the guidelines and regulations should have been adapted to the new knowledge. Instead, other social drivers drove the development of regulations. For most species and most applications, the framework that was established has slowly allowed some products to reach the market. However, genetically engineered livestock that are intended for food have been left in a regulatory state of limbo. To date, no genetically engineered food animal is available in the marketplace. A short history and a U.S.-based genetic engineer's perspective are presented. In addition, a request to regulatory agencies is presented for consideration as regulation continues to evolve. Regulators appear to have shown preference for the slow, random progression of evolution over the efficiency of intentional design.

Perception of risks and benefits of in vitro fertilization, genetic engineering and biotechnology.

Science.gov (United States)

Macer, D R

1994-01-01

The use of new biotechnology in medicine has become an everyday experience, but many people still express concern about biotechnology. Concerns are evoked particularly by the phrases genetic engineering and in vitro fertilization (IVF), and these concerns persist despite more than a decade of their use in medicine. Mailed nationwide opinion surveys on attitudes to biotechnology were conducted in Japan, among samples of the public (N = 551), high school biology teachers (N = 228), scientists (N = 555) and nurses (N = 301). People do see more benefits coming from science than harm when balanced against the risks. There were especially mixed perceptions of benefit and risk about IVF and genetic engineering, and a relatively high degree of worry compared to other developments of science and technology. A discussion of assisted reproductive technologies and surrogacy in Japan is also made. The opinions of people in Japan were compared to the results of previous surveys conducted in Japan, and international surveys conducted in Australia, China, Europe, New Zealand, U.K. and U.S.A. Japanese have a very high awareness of biotechnology, 97% saying that they had heard of the word. They also have a high level of awareness of IVF and genetic engineering. Genetic engineering was said to be a worthwhile research area for Japan by 76%, while 58% perceived research on IVF as being worthwhile, however 61% were worried about research on IVF or genetic engineering. Japanese expressed more concern about IVF and genetic engineering than New Zealanders. The major reason cited for rejection of genetic manipulation research in Japan and New Zealand was that it was seen as interfering with nature, playing God or as unethical. The emotions concerning these technologies are complex, and we should avoid using simplistic public opinion data as measures of public perceptions. The level of concern expressed by scientists and teachers in Japan suggest that public education "technology promotion

Genetic Engineering and Human Mental Ecology: Interlocking Effects and Educational Considerations

OpenAIRE

Affifi, Ramsey

2017-01-01

This paper describes some likely semiotic consequences of genetic engineering on what Gregory Bateson has called ?the mental ecology? (1979) of future humans, consequences that are less often raised in discussions surrounding the safety of GMOs (genetically modified organisms). The effects are as follows: an increased 1) habituation to the presence of GMOs in the environment, 2) normalization of empirically false assumptions grounding genetic reductionism, 3) acceptance that humans are capabl...

The Effect of Case Teaching on Meaningful and Retentive Learning When Studying Genetic Engineering

Science.gov (United States)

Güccük, Ahmet; Köksal, Mustafa Serdar

2017-01-01

The purpose of this study is to investigate the effects of case teaching on how students learn about genetic engineering, in terms of meaningful learning and retention of learning. The study was designed as quasi-experimental research including 63 8th graders (28 boys and 35 girls). To collect data, genetic engineering achievement tests were…

Application of Artificial Intelligence for Optimization in Pavement Management

Directory of Open Access Journals (Sweden)

Reus Salini

2015-07-01

Full Text Available Artificial intelligence (AI is a group of techniques that have quite a potential to be applied to pavement engineering and management. In this study, we developed a practical, flexible and out of the box approach to apply genetic algorithms to optimizing the budget allocation and the road maintenance strategy selection for a road network. The aim is to provide an alternative to existing software and better fit the requirements of an important number of pavement managers. To meet the objectives, a new indicator, named Road Global Value Index (RGVI, was created to contemplate the pavement condition, the traffic and the economic and political importance for each and every road section. This paper describes the approach and its components by an example confirming that genetic algorithms are very effective for the intended purpose.

Artificial neural network applications in the calibration of spark-ignition engines: An overview

Directory of Open Access Journals (Sweden)

Richard Fiifi Turkson

2016-09-01

Full Text Available Emission legislation has become progressively tighter, making the development of new internal combustion engines very challenging. New engine technologies for complying with these regulations introduce an exponential dependency between the number of test combinations required for obtaining optimum results and the time and cost outlays. This makes the calibration task very expensive and virtually impossible to carry out. The potential use of trained neural networks in combination with Design of Experiments (DoE methods for engine calibration has been a subject of research activities in recent times. This is because artificial neural networks, compared with other data-driven modeling techniques, perform better in satisfying a majority of the modeling requirements for engine calibration including the curse of dimensionality; the use of DoE for obtaining few measurements as practicable, with the aim of reducing engine calibration costs; the required flexibility that allows model parameters to be optimized to avoid overfitting; and the facilitation of automated online optimization during the engine calibration process that eliminates the need for user intervention. The purpose of this review is to give an overview of the various applications of neural networks in the calibration of spark-ignition engines. The identified and discussed applications include system identification for rapid prototyping, virtual sensing, use of neural networks as look-up table surrogates, emerging control strategies and On-Board Diagnostic (OBD applications. The demerits of neural networks, future possibilities and alternatives were also discussed.

Reversible immortalisation enables genetic correction of human muscle progenitors and engineering of next-generation human artificial chromosomes for Duchenne muscular dystrophy.

Science.gov (United States)

Benedetti, Sara; Uno, Narumi; Hoshiya, Hidetoshi; Ragazzi, Martina; Ferrari, Giulia; Kazuki, Yasuhiro; Moyle, Louise Anne; Tonlorenzi, Rossana; Lombardo, Angelo; Chaouch, Soraya; Mouly, Vincent; Moore, Marc; Popplewell, Linda; Kazuki, Kanako; Katoh, Motonobu; Naldini, Luigi; Dickson, George; Messina, Graziella; Oshimura, Mitsuo; Cossu, Giulio; Tedesco, Francesco Saverio

2018-02-01

Transferring large or multiple genes into primary human stem/progenitor cells is challenged by restrictions in vector capacity, and this hurdle limits the success of gene therapy. A paradigm is Duchenne muscular dystrophy (DMD), an incurable disorder caused by mutations in the largest human gene: dystrophin. The combination of large-capacity vectors, such as human artificial chromosomes (HACs), with stem/progenitor cells may overcome this limitation. We previously reported amelioration of the dystrophic phenotype in mice transplanted with murine muscle progenitors containing a HAC with the entire dystrophin locus (DYS-HAC). However, translation of this strategy to human muscle progenitors requires extension of their proliferative potential to withstand clonal cell expansion after HAC transfer. Here, we show that reversible cell immortalisation mediated by lentivirally delivered excisable hTERT and Bmi1 transgenes extended cell proliferation, enabling transfer of a novel DYS-HAC into DMD satellite cell-derived myoblasts and perivascular cell-derived mesoangioblasts. Genetically corrected cells maintained a stable karyotype, did not undergo tumorigenic transformation and retained their migration ability. Cells remained myogenic in vitro (spontaneously or upon MyoD induction) and engrafted murine skeletal muscle upon transplantation. Finally, we combined the aforementioned functions into a next-generation HAC capable of delivering reversible immortalisation, complete genetic correction, additional dystrophin expression, inducible differentiation and controllable cell death. This work establishes a novel platform for complex gene transfer into clinically relevant human muscle progenitors for DMD gene therapy. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Non-linear nuclear engineering models as genetic programming application

International Nuclear Information System (INIS)

Domingos, Roberto P.; Schirru, Roberto; Martinez, Aquilino S.

1997-01-01

This work presents a Genetic Programming paradigm and a nuclear application. A field of Artificial Intelligence, based on the concepts of Species Evolution and Natural Selection, can be understood as a self-programming process where the computer is the main agent responsible for the discovery of a program able to solve a given problem. In the present case, the problem was to find a mathematical expression in symbolic form, able to express the existent relation between equivalent ratio of a fuel cell, the enrichment of fuel elements and the multiplication factor. Such expression would avoid repeatedly reactor physics codes execution for core optimization. The results were compared with those obtained by different techniques such as Neural Networks and Linear Multiple Regression. Genetic Programming has shown to present a performance as good as, and under some features superior to Neural Network and Linear Multiple Regression. (author). 10 refs., 8 figs., 1 tabs

76 FR 80869 - Monsanto Co.; Determination of Nonregulated Status of Corn Genetically Engineered for Drought...

Science.gov (United States)

2011-12-27

... and products altered or produced through genetic engineering that are plant pests or that there is... in 7 CFR part 340, ``Introduction of Organisms and Products Altered or Produced Through Genetic Engineering Which Are Plant Pests or Which There Is Reason to Believe Are Plant Pests,'' regulate, among other...

Using Genetically Engineered Animal Models in the Postgenomic Era to Understand Gene Function in Alcoholism

Science.gov (United States)

Reilly, Matthew T.; Harris, R. Adron; Noronha, Antonio

2012-01-01

Over the last 50 years, researchers have made substantial progress in identifying genetic variations that underlie the complex phenotype of alcoholism. Not much is known, however, about how this genetic variation translates into altered biological function. Genetic animal models recapitulating specific characteristics of the human condition have helped elucidate gene function and the genetic basis of disease. In particular, major advances have come from the ability to manipulate genes through a variety of genetic technologies that provide an unprecedented capacity to determine gene function in the living organism and in alcohol-related behaviors. Even newer genetic-engineering technologies have given researchers the ability to control when and where a specific gene or mutation is activated or deleted, allowing investigators to narrow the role of the gene’s function to circumscribed neural pathways and across development. These technologies are important for all areas of neuroscience, and several public and private initiatives are making a new generation of genetic-engineering tools available to the scientific community at large. Finally, high-throughput “next-generation sequencing” technologies are set to rapidly increase knowledge of the genome, epigenome, and transcriptome, which, combined with genetically engineered mouse mutants, will enhance insight into biological function. All of these resources will provide deeper insight into the genetic basis of alcoholism. PMID:23134044

Artificial infestation of Boophilus microplus in beef cattle heifers of four genetic groups

Directory of Open Access Journals (Sweden)

Ana Mary da Silva

2007-01-01

Full Text Available Resistance of beef cattle heifers to the cattle tick Boophilus microplus was evaluated by artificial infestation of 66 beef cattle heifers of the following genetic groups: 16 Nelore (NE, 18 Canchim x Nelore (CN, 16 Angus x Nelore (AN and 16 Simmental x Nelore (SN. The animals, with a mean age of 16.5 months, were maintained with no chemical tick control in a Brachiaria decumbens pasture. Four artificial infestations with 20,000 B. microplus larvae were carried out 14 days apart and from day 18 to day 22 of each infestation the number of engorged female ticks (> 4.5 mm was counted on the left side of each heifer. Data were analyzed as the percentage of return (PR = percentage of ticks counted relative to the number infested, transformed to (PR¼, and as log10 (Cij + 1, in which Cij is the number of ticks in each infestation, using the least squares method with a model that included the effects of genetic group (GG, animal within GG (error a, infestation number (I, GG x I and the residual (error b. Results indicated a significant GG x I interaction, because AN and SN heifers had a higher percentage of return than CN and NE heifers, while CN heifers showed a higher percentage of return than the NE heifers only in infestations 3 and 4. Transformed percentages of return were NE = 0.35 ± 0.06, AN = 0.89 ± 0.06, CN = 0.54 ± 0.05 and SN = 0.85 ± 0.06.

76 FR 63278 - Bayer CropScience LP; Determination of Nonregulated Status for Cotton Genetically Engineered for...

Science.gov (United States)

2011-10-12

... part 340, ``Introduction of Organisms and Products Altered or Produced Through Genetic Engineering... regulations governing the introduction of certain genetically engineered organisms. Our determination is based... things, the introduction (importation, interstate movement, or release into the environment) of organisms...

76 FR 63279 - Monsanto Co.; Determination of Nonregulated Status for Soybean Genetically Engineered for Insect...

Science.gov (United States)

2011-10-12

... and products altered or produced through genetic engineering that are plant pests or that there is... regulations in 7 CFR part 340, ``Introduction of Organisms and Products Altered or Produced Through Genetic Engineering Which Are Plant Pests or Which There Is Reason to Believe Are Plant Pests,'' regulate, among other...

Measurement of DNA biomarkers for the safety of tissue-engineered medical products, using artificial skin as a model.

Science.gov (United States)

Rodriguez, Henry; O'Connell, Catherine; Barker, Peter E; Atha, Donald H; Jaruga, Pawel; Birincioglu, Mustafa; Marino, Michael; McAndrew, Patricia; Dizdaroglu, Miral

2004-01-01

To test the hypothesis that the process of tissue engineering introduces genetic damage to tissue-engineered medical products, we employed the use of five state-of-the-art measurement technologies to measure a series of DNA biomarkers in commercially available tissue-engineered skin as a model. DNA was extracted from the skin and compared with DNA from cultured human neonatal control cells (dermal fibroblasts and epidermal keratinocytes) and adult human fibroblasts from a 55-year-old donor and a 96-year-old donor. To determine whether tissue engineering caused oxidative DNA damage, gas chromatography/isotope-dilution mass spectrometry and liquid chromatography/isotope-dilution mass spectrometry were used to measure six oxidatively modified DNA bases as biomarkers. Normal endogenous levels of the modified DNA biomarkers were not elevated in tissue-engineered skin when compared with control cells. Next, denaturing high-performance liquid chromatography and capillary electrophoresis-single strand conformation polymorphism were used to measure genetic mutations. Specifically, the TP53 tumor suppressor gene was screened for mutations, because it is the most commonly mutated gene in skin cancer. The tissue-engineered skin was found to be free of TP53 mutations at the level of sensitivity of these measurement technologies. Lastly, fluorescence in situ hybridization was employed to measure the loss of Y chromosome, which is associated with excessive cell passage and aging. Loss of Y chromosome was not detected in the tissue-engineered skin and cultured neonatal cells used as controls. In this study, we have demonstrated that tissue engineering (for TestSkin II) does not introduce genetic damage above the limits of detection of the state-of-the-art technologies used. This work explores the standard for measuring genetic damage that could be introduced during production of novel tissue-engineered products. More importantly, this exploratory work addresses technological

Genetic engineering of microorganisms for biodiesel production

Science.gov (United States)

Lin, Hui; Wang, Qun; Shen, Qi; Zhan, Jumei; Zhao, Yuhua

2013-01-01

Biodiesel, as one type of renewable energy, is an ideal substitute for petroleum-based diesel fuel and is usually made from triacylglycerides by transesterification with alcohols. Biodiesel production based on microbial fermentation aiming to establish more efficient, less-cost and sustainable biodiesel production strategies is under current investigation by various start-up biotechnology companies and research centers. Genetic engineering plays a key role in the transformation of microbes into the desired cell factories with high efficiency of biodiesel production. Here, we present an overview of principal microorganisms used in the microbial biodiesel production and recent advances in metabolic engineering for the modification required. Overexpression or deletion of the related enzymes for de novo synthesis of biodiesel is highlighted with relevant examples. PMID:23222170

Identifying artificial selection signals in the chicken genome.

Directory of Open Access Journals (Sweden)

Yunlong Ma

Full Text Available Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF, Jinghong (JH, Araucanas (AR, White Leghorn (WL, Pekin-Bantam (PB, Shamo (SH, Gallus-Gallus-Spadiceus (GA, Rheinlander (RH and Vorwerkhuhn (VO. Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a 'two-step' strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study.

Genetic engineering of syringyl-enriched lignin in plants

Science.gov (United States)

Chiang, Vincent Lee; Li, Laigeng

2004-11-02

The present invention relates to a novel DNA sequence, which encodes a previously unidentified lignin biosynthetic pathway enzyme, sinapyl alcohol dehydrogenase (SAD) that regulates the biosynthesis of syringyl lignin in plants. Also provided are methods for incorporating this novel SAD gene sequence or substantially similar sequences into a plant genome for genetic engineering of syringyl-enriched lignin in plants.

Non-Genetic Engineering Approaches for Isolating and Generating Novel Yeasts for Industrial Applications

Science.gov (United States)

Chambers, P. J.; Bellon, J. R.; Schmidt, S. A.; Varela, C.; Pretorius, I. S.

Generating novel yeast strains for industrial applications should be quite straightforward; after all, research into the genetics, biochemistry and physiology of Baker's Yeast, Saccharomyces cerevisiae, has paved the way for many advances in the modern biological sciences. We probably know more about this humble eukaryote than any other, and it is the most tractable of organisms for manipulation using modern genetic engineering approaches. In many countries, however, there are restrictions on the use of genetically-modified organisms (GMOs), particularly in foods and beverages, and the level of consumer acceptance of GMOs is, at best, variable. Thus, many researchers working with industrial yeasts use genetic engineering techniques primarily as research tools, and strain development continues to rely on non-GM technologies. This chapter explores the non-GM tools and strategies available to such researchers.

Gender and Health Impacts of Genetically Engineered Crops in ...

International Development Research Centre (IDRC) Digital Library (Canada)

Gender and Health Impacts of Genetically Engineered Crops in Developing Countries ... exists, the gender and health impacts have so far received only cursory attention. ... New funding opportunity for gender equality and climate change ... social inequality, promote greater gender parity, and empower women and girls.

Modeling Self-Healing of Concrete Using Hybrid Genetic Algorithm-Artificial Neural Network.

Science.gov (United States)

Ramadan Suleiman, Ahmed; Nehdi, Moncef L

2017-02-07

This paper presents an approach to predicting the intrinsic self-healing in concrete using a hybrid genetic algorithm-artificial neural network (GA-ANN). A genetic algorithm was implemented in the network as a stochastic optimizing tool for the initial optimal weights and biases. This approach can assist the network in achieving a global optimum and avoid the possibility of the network getting trapped at local optima. The proposed model was trained and validated using an especially built database using various experimental studies retrieved from the open literature. The model inputs include the cement content, water-to-cement ratio (w/c), type and dosage of supplementary cementitious materials, bio-healing materials, and both expansive and crystalline additives. Self-healing indicated by means of crack width is the model output. The results showed that the proposed GA-ANN model is capable of capturing the complex effects of various self-healing agents (e.g., biochemical material, silica-based additive, expansive and crystalline components) on the self-healing performance in cement-based materials.

[Artificial organs].

Science.gov (United States)

Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

2017-01-01

Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

Agrobacterium: nature’s genetic engineer

Science.gov (United States)

Nester, Eugene W.

2015-01-01

Agrobacterium was identified as the agent causing the plant tumor, crown gall over 100 years ago. Since then, studies have resulted in many surprising observations. Armin Braun demonstrated that Agrobacterium infected cells had unusual nutritional properties, and that the bacterium was necessary to start the infection but not for continued tumor development. He developed the concept of a tumor inducing principle (TIP), the factor that actually caused the disease. Thirty years later the TIP was shown to be a piece of a tumor inducing (Ti) plasmid excised by an endonuclease. In the next 20 years, most of the key features of the disease were described. The single-strand DNA (T-DNA) with the endonuclease attached is transferred through a type IV secretion system into the host cell where it is likely coated and protected from nucleases by a bacterial secreted protein to form the T-complex. A nuclear localization signal in the endonuclease guides the transferred strand (T-strand), into the nucleus where it is integrated randomly into the host chromosome. Other secreted proteins likely aid in uncoating the T-complex. The T-DNA encodes enzymes of auxin, cytokinin, and opine synthesis, the latter a food source for Agrobacterium. The genes associated with T-strand formation and transfer (vir) map to the Ti plasmid and are only expressed when the bacteria are in close association with a plant. Plant signals are recognized by a two-component regulatory system which activates vir genes. Chromosomal genes with pleiotropic functions also play important roles in plant transformation. The data now explain Braun’s old observations and also explain why Agrobacterium is nature’s genetic engineer. Any DNA inserted between the border sequences which define the T-DNA will be transferred and integrated into host cells. Thus, Agrobacterium has become the major vector in plant genetic engineering. PMID:25610442

Volatile terpenoids: multiple functions, biosynthesis, modulation and manipulation by genetic engineering.

Science.gov (United States)

Abbas, Farhat; Ke, Yanguo; Yu, Rangcai; Yue, Yuechong; Amanullah, Sikandar; Jahangir, Muhammad Muzammil; Fan, Yanping

2017-11-01

Terpenoids play several physiological and ecological functions in plant life through direct and indirect plant defenses and also in human society because of their enormous applications in the pharmaceutical, food and cosmetics industries. Through the aid of genetic engineering its role can by magnified to broad spectrum by improving genetic ability of crop plants, enhancing the aroma quality of fruits and flowers and the production of pharmaceutical terpenoids contents in medicinal plants. Terpenoids are structurally diverse and the most abundant plant secondary metabolites, playing an important role in plant life through direct and indirect plant defenses, by attracting pollinators and through different interactions between the plants and their environment. Terpenoids are also significant because of their enormous applications in the pharmaceutical, food and cosmetics industries. Due to their broad distribution and functional versatility, efforts are being made to decode the biosynthetic pathways and comprehend the regulatory mechanisms of terpenoids. This review summarizes the recent advances in biosynthetic pathways, including the spatiotemporal, transcriptional and post-transcriptional regulatory mechanisms. Moreover, we discuss the multiple functions of the terpene synthase genes (TPS), their interaction with the surrounding environment and the use of genetic engineering for terpenoid production in model plants. Here, we also provide an overview of the significance of terpenoid metabolic engineering in crop protection, plant reproduction and plant metabolic engineering approaches for pharmaceutical terpenoids production and future scenarios in agriculture, which call for sustainable production platforms by improving different plant traits.

Optimal groundwater remediation using artificial neural networks and the genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Rogers, Leah L. [Stanford Univ., CA (United States)

1992-08-01

An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ``recycle`` or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models.

Optimal groundwater remediation using artificial neural networks and the genetic algorithm

International Nuclear Information System (INIS)

Rogers, L.L.

1992-08-01

An innovative computational approach for the optimization of groundwater remediation is presented which uses artificial neural networks (ANNs) and the genetic algorithm (GA). In this approach, the ANN is trained to predict an aspect of the outcome of a flow and transport simulation. Then the GA searches through realizations or patterns of pumping and uses the trained network to predict the outcome of the realizations. This approach has advantages of parallel processing of the groundwater simulations and the ability to ''recycle'' or reuse the base of knowledge formed by these simulations. These advantages offer reduction of computational burden of the groundwater simulations relative to a more conventional approach which uses nonlinear programming (NLP) with a quasi-newtonian search. Also the modular nature of this approach facilitates substitution of different groundwater simulation models

Artificial Selection Response due to Polygenic Adaptation from a Multilocus, Multiallelic Genetic Architecture.

Science.gov (United States)

Zan, Yanjun; Sheng, Zheya; Lillie, Mette; Rönnegård, Lars; Honaker, Christa F; Siegel, Paul B; Carlborg, Örjan

2017-10-01

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A Simple Interactive Introduction to Teaching Genetic Engineering

Science.gov (United States)

Child, Paula

2013-01-01

In the UK, at key stage 4, students aged 14-15 studying GCSE Core Science or Unit 1 of the GCSE Biology course are required to be able to describe the process of genetic engineering to produce bacteria that can produce insulin. The simple interactive introduction described in this article allows students to consider the problem, devise a model and…

Integration of Artificial Neural Network Modeling and Genetic Algorithm Approach for Enrichment of Laccase Production in Solid State Fermentation by Pleurotus ostreatus

OpenAIRE

Potu Venkata Chiranjeevi; Moses Rajasekara Pandian; Sathish Thadikamala

2014-01-01

Black gram husk was used as a solid substrate for laccase production by Pleurotus ostreatus, and various fermentation conditions were optimized based on an artificial intelligence method. A total of six parameters, i.e., temperature, inoculum concentration, moisture content, CuSO4, glucose, and peptone concentrations, were optimized. A total of 50 experiments were conducted, and the obtained data were modeled by a hybrid of artificial neural network (ANN) and genetic algorithm (GA) approaches...

Genetic Engineering--A Lesson on Bioethics for the Classroom.

Science.gov (United States)

Armstrong, Kerri; Weber, Kurt

1991-01-01

A unit designed to cover the topic of genetic engineering and its ethical considerations is presented. Students are expected to learn the material while using a debate format. A list of objectives for the unit, the debate format, and the results from an opinion questionnaire are described. (KR)

Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

International Nuclear Information System (INIS)

Tong, S.S.; Powell, D.; Goel, S.

1992-02-01

A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

A FIELD STUDY WITH GENETICALLY ENGINEERED ALFALFA INOCULATED WITH RECOMBINANT SINORHIZOBIUM MELILOTI: EFFECTS ON THE SOIL ECOSYSTEM

Science.gov (United States)

The agricultural use of genetically engineered plants and microorganisms has become increasingly common. Because genetically engineered plants and microorganisms can produce compounds foreign to their environment, there is concern that they may become established outside of thei...

A tailored biocatalyst achieved by the rational anchoring of imidazole groups on a natural polymer: furnishing a potential artificial nuclease by sustainable materials engineering.

Science.gov (United States)

Ferreira, José G L; Grein-Iankovski, Aline; Oliveira, Marco A S; Simas-Tosin, Fernanda F; Riegel-Vidotti, Izabel C; Orth, Elisa S

2015-04-11

Foreseeing the development of artificial enzymes by sustainable materials engineering, we rationally anchored reactive imidazole groups on gum arabic, a natural biocompatible polymer. The tailored biocatalyst GAIMZ demonstrated catalytic activity (>10(5)-fold) in dephosphorylation reactions with recyclable features and was effective in cleaving plasmid DNA, comprising a potential artificial nuclease.

Artificial intelligence for the modeling and control of combustion processes: a review

Energy Technology Data Exchange (ETDEWEB)

Kalogirou, S.A. [Higher Technical Inst., Nicosia, Cyprus (Greece). Dept. of Mechanical Engineering

2003-07-01

Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. Al systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how Al techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of Al as a design tool in many areas of combustion engineering. (author)

The beneficial effect of genetically engineered Schwann cells with enhanced motility in peripheral nerve regeneration: review.

Science.gov (United States)

Gravvanis, A I; Lavdas, A A; Papalois, A; Tsoutsos, D A; Matsas, R

2007-01-01

The importance of Schwann cells in promoting nerve regeneration across a conduit has been extensively reported in the literature, and Schwann cell motility has been acknowledged as a prerequisite for myelination of the peripheral nervous system during regeneration after injury. Review of recent literature and retrospective analysis of our studies with genetically modified Schwann Cells with increased motility in order to identify the underlying mechanism of action and outline the future trends in peripheral nerve repair. Schwann cell transduction with the pREV-retrovirus, for expression of Sialyl-Transferase-X, resulting in conferring Polysialyl-residues (PSA) on NCAM, increases their motility in-vitro and ensures nerve regeneration through silicone tubes after end-to-side neurorraphy in the rat sciatic nerve model, thus significantly promoting fiber maturation and functional outcome. An artificial nerve graft consisting of a type I collagen tube lined with the genetically modified Schwann cells with increased motility, used to bridge a defect in end-to-end fashion in the rat sciatic nerve model, was shown to promote nerve regeneration to a level equal to that of a nerve autograft. The use of genetically engineered Schwann cells with enhanced motility for grafting endoneural tubes promotes axonal regeneration, by virtue of the interaction of the transplanted cells with regenerating axonal growth cones as well as via the recruitment of endogenous Schwann cells. It is envisaged that mixed populations of Schwann cells, expressing PSA and one or more trophic factors, might further enhance the regenerating and remyelinating potential of the lesioned nerves.

Artificial Intelligence Project

Science.gov (United States)

1990-01-01

Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

Genetic and metabolic engineering in diatoms.

Science.gov (United States)

Huang, Weichao; Daboussi, Fayza

2017-09-05

Diatoms have attracted considerable attention due to their success in diverse environmental conditions, which probably is a consequence of their complex origins. Studies of their metabolism will provide insight into their adaptation capacity and are a prerequisite for metabolic engineering. Several years of investigation have led to the development of the genome engineering tools required for such studies, and a profusion of appropriate tools is now available for exploring and exploiting the metabolism of these organisms. Diatoms are highly prized in industrial biotechnology, due to both their richness in natural lipids and carotenoids and their ability to produce recombinant proteins, of considerable value in diverse markets. This review provides an overview of recent advances in genetic engineering methods for diatoms, from the development of gene expression cassettes and gene delivery methods, to cutting-edge genome-editing technologies. It also highlights the contributions of these rapid developments to both basic and applied research: they have improved our understanding of key physiological processes; and they have made it possible to modify the natural metabolism to favour the production of specific compounds or to produce new compounds for green chemistry and pharmaceutical applications.This article is part of the themed issue 'The peculiar carbon metabolism in diatoms'. © 2017 The Author(s).

The Plant Genetic Engineering Laboratory For Desert Adaptation

Science.gov (United States)

Kemp, John D.; Phillips, Gregory C.

1985-11-01

The Plant Genetic Engineering Laboratory for Desert Adaptation (PGEL) is one of five Centers of Technical Excellence established as a part of the state of New Mexico's Rio Grande Research Corridor (RGRC). The scientific mission of PGEL is to bring innovative advances in plant biotechnology to bear on agricultural productivity in arid and semi-arid regions. Research activities focus on molecular and cellular genetics technology development in model systems, but also include stress physiology investigations and development of desert plant resources. PGEL interacts with the Los Alamos National Laboratory (LANL), a national laboratory participating in the RGRC. PGEL also has an economic development mission, which is being pursued through technology transfer activities to private companies and public agencies.

EU member states' voting for authorizing genetically engineered crops

NARCIS (Netherlands)

Smart, Richard D.; Blum, Matthias; Wesseler, Justus

2015-01-01

Several authors suggest a gridlock of the European Union's (EU's) approval process for genetically engineered (GE) crops. We analyse the voting behaviour of EU Member States (MSs) for voting results from 2003 to 2015 on the approval of GE crops to test for a gridlock; no reliable data are

Chapter VIII. Contributions of propagation techniques and genetic modification to breeding - genetic engineering for disease resistance

Science.gov (United States)

Genetic engineering offers an opportunity to develop flower bulb crops with resistance to fungal, viral, and bacterial pathogens. Several of the flower bulb crops, Lilium spp., Gladiolus, Zantedeschia, Muscari, Hyacinthus, Narcissus, Ornithogalum, Iris, and Alstroemeria, have been transformed with t...

Perspectives for genetic engineering for the phytoremediation of arsenic-contaminated environments: from imagination to reality?

Science.gov (United States)

Zhu, Yong-Guan; Rosen, Barry P

2009-04-01

Phytoremediation to clean up arsenic-contaminated environments has been widely hailed as environmentally friendly and cost effective, and genetic engineering is believed to improve the efficiency and versatility of phytoremediation. Successful genetic engineering requires the thorough understanding of the mechanisms involved in arsenic tolerance and accumulation by natural plant species. Key mechanisms include arsenate reduction, arsenic sequestration in vacuoles of root or shoot, arsenic loading to the xylem, and volatilization through the leaves. Key advances include the identification of arsenic (As) translocation from root to shoot in the As hyperaccumulator, Pteris vittata, and the characterization of related key genes from hyperaccumulator and nonaccumulators. In this paper we have proposed three pathways for genetic engineering: arsenic sequestration in the root, hyperaccumulation of arsenic in aboveground tissues, and phytovolatilization.

14th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications

CERN Document Server

2016-01-01

This edited book presents scientific results of the 14th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2016) held on June 8-10, 2016 at Towson University, USA. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rigorous rounds of review. This publication capture...

14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

Studies in Computational Intelligence : Volume 492

2013-01-01

This edited book presents scientific results of the 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), held in Honolulu, Hawaii, USA on July 1-3, 2013. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 17 outstanding papers from those papers accepted for presentation at the conference.  

15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

2015-01-01

This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 – July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.

Artificial intelligence

International Nuclear Information System (INIS)

Perret-Galix, D.

1992-01-01

A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

A field release of genetically engineered gypsy moth (Lymantria dispar L.) Nuclear Polyhedrosis Virus (LdNPV)

Science.gov (United States)

Vincent D' Amico; Joseph S. Elkinton; John D. Podgwaite; James M. Slavicek; Michael L. McManus; John P. Burand

1999-01-01

The gypsy moth (Lymantria dispar L.) nuclear polyhedrosis virus was genetically engineered for nonpersistence by removal of the gene coding for polyhedrin production and stabilized using a coocclusion process. A β-galactosidase marker gene was inserted into the genetically engineered virus (LdGEV) so that infected larvae could be tested for...

American chestnut: A test case for genetic engineering?

Science.gov (United States)

Leila Pinchot

2014-01-01

The thought of genetically engineered (GE) trees might conjure images of mutant trees with unnatural and invasive tendencies, but there is much more to the story. GE trees are a new reality that, like it or not, will probably be part of the future of forestry. The basic inclination of most Forest Guild stewards is to reject GE trees as violating our principle to...

Current status of genetic engineering in cotton (Gossypium hirsutum L): an assessment.

Science.gov (United States)

Chakravarthy, Vajhala S K; Reddy, Tummala Papi; Reddy, Vudem Dashavantha; Rao, Khareedu Venkateswara

2014-06-01

Cotton is considered as the foremost commercially important fiber crop and is deemed as the backbone of the textile industry. The productivity of cotton crop, worldwide, is severely hampered by the occurrence of pests, weeds, pathogens apart from various environmental factors. Several beneficial agronomic traits, viz., early maturity, improved fiber quality, heat tolerance, etc. have been successfully incorporated into cotton varieties employing conventional hybridization and mutation breeding. Crop losses, due to biotic factors, are substantial and may be reduced through certain crop protection strategies. In recent years, pioneering success has been achieved through the adoption of modern biotechnological approaches. Genetically engineered cotton varieties, expressing Bacillus thuringiensis cry genes, proved to be highly successful in controlling the bollworm complex. Various other candidate genes responsible for resistance to insect pests and pathogens, tolerance to major abiotic stress factors such as temperature, drought and salinity, have been introduced into cotton via genetic engineering methods to enhance the agronomic performance of cotton cultivars. Furthermore, genes for improving the seed oil quality and fiber characteristics have been identified and introduced into cotton cultivars. This review provides a brief overview of the various advancements made in cotton through genetic engineering approaches.

The effect of genetically engineered glucagon on glucose recovery after hypoglycaemia in man

DEFF Research Database (Denmark)

Hvidberg, A; Jørgensen, S; Hilsted, J

1992-01-01

To compare the effect on glucose recovery after insulin-induced hypoglycaemia of intramuscular genetically engineered glucagon, intramuscular glucagon from pancreatic extraction and intravenous glucose, we examined 10 healthy subjects during blockage of glucose counterregulation with somatostatin...... appearance rate were far more protracted after i.m. glucagon than after i.v. glucose. These results suggest that genetically engineered glucagon and glucagon from pancreatic extraction have a similar effect on hepatic glucose production rate. Due to the protracted effect of intramuscular glucagon, a combined......, propranolol and phentolamine. Each subject was studied on three separate occasions. Thirty min after a bolus injection of 0.075 iu soluble insulin per kilogram body weight the subjects received one of the following treatments: 1 mg glucagon from pancreatic extraction intramuscularly; 1 mg genetically...

Production of amino acids - Genetic and metabolic engineering approaches.

Science.gov (United States)

Lee, Jin-Ho; Wendisch, Volker F

2017-12-01

The biotechnological production of amino acids occurs at the million-ton scale and annually about 6milliontons of l-glutamate and l-lysine are produced by Escherichia coli and Corynebacterium glutamicum strains. l-glutamate and l-lysine production from starch hydrolysates and molasses is very efficient and access to alternative carbon sources and new products has been enabled by metabolic engineering. This review focusses on genetic and metabolic engineering of amino acid producing strains. In particular, rational approaches involving modulation of transcriptional regulators, regulons, and attenuators will be discussed. To address current limitations of metabolic engineering, this article gives insights on recent systems metabolic engineering approaches based on functional tools and method such as genome reduction, amino acid sensors based on transcriptional regulators and riboswitches, CRISPR interference, small regulatory RNAs, DNA scaffolding, and optogenetic control, and discusses future prospects. Copyright © 2017 Elsevier Ltd. All rights reserved.

The ethics of using genetic engineering for sex selection.

Science.gov (United States)

Liao, S Matthew

2005-02-01

It is quite likely that parents will soon be able to use genetic engineering to select the sex of their child by directly manipulating the sex of an embryo. Some might think that this method would be a more ethical method of sex selection than present technologies such as preimplantation genetic diagnosis (PGD) because, unlike PGD, it does not need to create and destroy "wrong gendered" embryos. This paper argues that those who object to present technologies on the grounds that the embryo is a person are unlikely to be persuaded by this proposal, though for different reasons.

Engineering Courses on Computational Thinking Through Solving Problems in Artificial Intelligence

Directory of Open Access Journals (Sweden)

Piyanuch Silapachote

2017-09-01

Full Text Available Computational thinking sits at the core of every engineering and computing related discipline. It has increasingly emerged as its own subject in all levels of education. It is a powerful cornerstone for cognitive development, creative problem solving, algorithmic thinking and designs, and programming. How to effectively teach computational thinking skills poses real challenges and creates opportunities. Targeting entering computer science and engineering undergraduates, we resourcefully integrate elements from artificial intelligence (AI into introductory computing courses. In addition to comprehension of the essence of computational thinking, practical exercises in AI enable inspirations of collaborative problem solving beyond abstraction, logical reasoning, critical and analytical thinking. Problems in machine intelligence systems intrinsically connect students to algorithmic oriented computing and essential mathematical foundations. Beyond knowledge representation, AI fosters a gentle introduction to data structures and algorithms. Focused on engaging mental tool, a computer is never a necessity. Neither coding nor programming is ever required. Instead, students enjoy constructivist classrooms designed to always be active, flexible, and highly dynamic. Learning to learn and reflecting on cognitive experiences, they rigorously construct knowledge from collectively solving exciting puzzles, competing in strategic games, and participating in intellectual discussions.

OligArch: A software tool to allow artificially expanded genetic information systems (AEGIS to guide the autonomous self-assembly of long DNA constructs from multiple DNA single strands

Directory of Open Access Journals (Sweden)

Kevin M. Bradley

2014-08-01

Full Text Available Synthetic biologists wishing to self-assemble large DNA (L-DNA constructs from small DNA fragments made by automated synthesis need fragments that hybridize predictably. Such predictability is difficult to obtain with nucleotides built from just the four standard nucleotides. Natural DNA's peculiar combination of strong and weak G:C and A:T pairs, the context-dependence of the strengths of those pairs, unimolecular strand folding that competes with desired interstrand hybridization, and non-Watson–Crick interactions available to standard DNA, all contribute to this unpredictability. In principle, adding extra nucleotides to the genetic alphabet can improve the predictability and reliability of autonomous DNA self-assembly, simply by increasing the information density of oligonucleotide sequences. These extra nucleotides are now available as parts of artificially expanded genetic information systems (AEGIS, and tools are now available to generate entirely standard DNA from AEGIS DNA during PCR amplification. Here, we describe the OligArch (for "oligonucleotide architecting" software, an application that permits synthetic biologists to engineer optimally self-assembling DNA constructs from both six- and eight-letter AEGIS alphabets. This software has been used to design oligonucleotides that self-assemble to form complete genes from 20 or more single-stranded synthetic oligonucleotides. OligArch is therefore a key element of a scalable and integrated infrastructure for the rapid and designed engineering of biology.

Perspectives for genetic engineering for the phytoremediation of arsenic-contaminated environments: from imagination to reality?

OpenAIRE

Zhu, Yong-Guan; Rosen, Barry P

2009-01-01

Phytoremediation to clean up arsenic-contaminated environments has been widely hailed as environmentally friendly and cost effective, and genetic engineering is believed to improve the efficiency and versatility of phytoremediation. Successful genetic engineering requires the thorough understanding of the mechanisms involved in arsenic tolerance and accumulation by natural plant species. Key mechanisms include arsenate reduction, arsenic sequestration in vacuoles of root or shoot, arsenic loa...

Artificial Intelligence in Space Platforms.

Science.gov (United States)

1984-12-01

computer algorithms, there still appears to be a need for Artificial Inteligence techniques in the navigation area. The reason is that navigaion, in...RD-RI32 679 ARTIFICIAL INTELLIGENCE IN SPACE PLRTFORNSMU AIR FORCE 1/𔃼 INST OF TECH WRIGHT-PRTTERSON AFB OH SCHOOL OF ENGINEERING M A WRIGHT DEC 94...i4 Preface The purpose of this study was to analyze the feasibility of implementing Artificial Intelligence techniques to increase autonomy for

Artificial Intelligence and Economic Theories

OpenAIRE

Marwala, Tshilidzi; Hurwitz, Evan

2017-01-01

The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

Classification of Atrial Septal Defect and Ventricular Septal Defect with Documented Hemodynamic Parameters via Cardiac Catheterization by Genetic Algorithms and Multi-Layered Artificial Neural Network

Directory of Open Access Journals (Sweden)

Mustafa Yıldız

2012-08-01

Full Text Available Introduction: We aimed to develop a classification method to discriminate ventricular septal defect and atrial septal defect by using severalhemodynamic parameters.Patients and Methods: Forty three patients (30 atrial septal defect, 13 ventricular septal defect; 26 female, 17 male with documentedhemodynamic parameters via cardiac catheterization are included to study. Such parameters as blood pressure values of different areas,gender, age and Qp/Qs ratios are used for classification. Parameters, we used in classification are determined by divergence analysismethod. Those parameters are; i pulmonary artery diastolic pressure, ii Qp/Qs ratio, iii right atrium pressure, iv age, v pulmonary arterysystolic pressure, vi left ventricular sistolic pressure, vii aorta mean pressure, viii left ventricular diastolic pressure, ix aorta diastolicpressure, x aorta systolic pressure. Those parameters detected from our study population, are uploaded to multi-layered artificial neuralnetwork and the network was trained by genetic algorithm.Results: Trained cluster consists of 14 factors (7 atrial septal defect and 7 ventricular septal defect. Overall success ratio is 79.2%, andwith a proper instruction of artificial neural network this ratio increases up to 89%.Conclusion: Parameters, belonging to artificial neural network, which are needed to be detected by the investigator in classical methods,can easily be detected with the help of genetic algorithms. During the instruction of artificial neural network by genetic algorithms, boththe topology of network and factors of network can be determined. During the test stage, elements, not included in instruction cluster, areassumed as in test cluster, and as a result of this study, we observed that multi-layered artificial neural network can be instructed properly,and neural network is a successful method for aimed classification.

The Discussions around Precision Genetic Engineering: Role of and Impact on Disabled People

Directory of Open Access Journals (Sweden)

Gregor Wolbring

2016-09-01

Full Text Available Genetic researchers are advancing in their abilities to extract precise genetic information from biological and human entities bringing genetic research steps closer to accurately modifying genes of biological entities, including that of humans. In this analytical essay, we focus on the discussions about precision genetic intervention that have taken place since March 2015 as they pertain to disabled people. We focus on two areas; one being the role of disabled people in the recent gene editing discussions and the second being the utility of existing legal instruments. Within our first focus we address the following questions: (a What is the visibility of disabled people in the gene-editing discussions that have taken place since March 2015? (b What has been the impact of those discussions on disabled people? (c Were social problems which disabled people face taken into account in those discussions; (d How does the reality of engagement with disabled people in these discussions fit with science, technology and innovation governance discourses that ask for more stakeholder, bottom up and anticipatory involvement? Within our second focus we address the following questions: (a What is the utility of the United Nations Convention on the Right of Persons with Disabilities (UNCRPD; and (b What is the utility of existing legal instruments covering genetic interventions: for preventing negative social consequences of genetic engineering developments for disabled people. We argue that (a the genetic engineering debates since March 2015 have portrayed disabled people dominantly through a medical lens; (b that the governance of science, technology and innovation of genetic engineering including anticipatory governance and responsible innovation discourses has not yet engaged with the social impact of gene editing on disabled people; (c that few scholars that focus on the social situation of disabled people are visible in the governance discussions of gene

Phage Genetic Engineering Using CRISPR–Cas Systems

Directory of Open Access Journals (Sweden)

Asma Hatoum-Aslan

2018-06-01

Full Text Available Since their discovery over a decade ago, the class of prokaryotic immune systems known as CRISPR–Cas have afforded a suite of genetic tools that have revolutionized research in model organisms spanning all domains of life. CRISPR-mediated tools have also emerged for the natural targets of CRISPR–Cas immunity, the viruses that specifically infect bacteria, or phages. Despite their status as the most abundant biological entities on the planet, the majority of phage genes have unassigned functions. This reality underscores the need for robust genetic tools to study them. Recent reports have demonstrated that CRISPR–Cas systems, specifically the three major types (I, II, and III, can be harnessed to genetically engineer phages that infect diverse hosts. Here, the mechanisms of each of these systems, specific strategies used, and phage editing efficacies will be reviewed. Due to the relatively wide distribution of CRISPR–Cas systems across bacteria and archaea, it is anticipated that these immune systems will provide generally applicable tools that will advance the mechanistic understanding of prokaryotic viruses and accelerate the development of novel technologies based on these ubiquitous organisms.

Molecular engineering with artificial atoms: designing a material platform for scalable quantum spintronics and photonics

Science.gov (United States)

Doty, Matthew F.; Ma, Xiangyu; Zide, Joshua M. O.; Bryant, Garnett W.

2017-09-01

Self-assembled InAs Quantum Dots (QDs) are often called "artificial atoms" and have long been of interest as components of quantum photonic and spintronic devices. Although there has been substantial progress in demonstrating optical control of both single spins confined to a single QD and entanglement between two separated QDs, the path toward scalable quantum photonic devices based on spins remains challenging. Quantum Dot Molecules, which consist of two closely-spaced InAs QDs, have unique properties that can be engineered with the solid state analog of molecular engineering in which the composition, size, and location of both the QDs and the intervening barrier are controlled during growth. Moreover, applied electric, magnetic, and optical fields can be used to modulate, in situ, both the spin and optical properties of the molecular states. We describe how the unique photonic properties of engineered Quantum Dot Molecules can be leveraged to overcome long-standing challenges to the creation of scalable quantum devices that manipulate single spins via photonics.

Expanding the Lotus japonicus reverse genetics toolbox – Development of LORE1 retrotransposon mutagenesis and artificial miRNA-mediated silencing

DEFF Research Database (Denmark)

Urbanski, Dorian Fabian

2011-01-01

. The protocols developed in the current project are now the cornerstone of a new LORE1 reverse genetics resource characterized by efficient mutant line generation and accurate mutation annotation. In parallel, artificial microRNAs (amiRNAs) were designed based on both Arabidopsis and Lotus backbones......Currently, the most common approach to studying Lotus japonicus (Lotus) genes is forward genetics in which a gene responsible for the studied phenotype is identified through map-based cloning. In reverse genetics, the activity of a gene of interest is modified to discover its mutant phenotype....... Prior to this project, the only reverse genetics resource available in Lotus was the TILLING resource. In an attempt to advance Lotus genetic studies, present study is focused on the development of two additional resources. The first is based on insertional mutagenesis and the second on harnessing post...

Reproductive cloning, genetic engineering and the autonomy of the child: the moral agent and the open future.

Science.gov (United States)

Mameli, M

2007-02-01

Some authors have argued that the human use of reproductive cloning and genetic engineering should be prohibited because these biotechnologies would undermine the autonomy of the resulting child. In this paper, two versions of this view are discussed. According to the first version, the autonomy of cloned and genetically engineered people would be undermined because knowledge of the method by which these people have been conceived would make them unable to assume full responsibility for their actions. According to the second version, these biotechnologies would undermine autonomy by violating these people's right to an open future. There is no evidence to show that people conceived through cloning and genetic engineering would inevitably or even in general be unable to assume responsibility for their actions; there is also no evidence for the claim that cloning and genetic engineering would inevitably or even in general rob the child of the possibility to choose from a sufficiently large array of life plans.

Genetic engineering and sustainable production of ornamentals: current status and future directions.

Science.gov (United States)

Lütken, Henrik; Clarke, Jihong Liu; Müller, Renate

2012-07-01

Through the last decades, environmentally and health-friendly production methods and conscientious use of resources have become crucial for reaching the goal of a more sustainable plant production. Protection of the environment requires careful consumption of limited resources and reduction of chemicals applied during production of ornamental plants. Numerous chemicals used in modern plant production have negative impacts on human health and are hazardous to the environment. In Europe, several compounds have lost their approval and further legal restrictions can be expected. This review presents the more recent progress of genetic engineering in ornamental breeding, delivers an overview of the biological background of the used technologies and critically evaluates the usefulness of the strategies to obtain improved ornamental plants. First, genetic engineering is addressed as alternative to growth retardants, comprising recombinant DNA approaches targeting relevant hormone pathways, e.g. the gibberellic acid (GA) pathway. A reduced content of active GAs causes compact growth and can be facilitated by either decreased anabolism, increased catabolism or altered perception. Moreover, compactness can be accomplished by using a natural transformation approach without recombinant DNA technology. Secondly, metabolic engineering approaches targeting elements of the ethylene signal transduction pathway are summarized as a possible alternative to avoid the use of chemical ethylene inhibitors. In conclusion, molecular breeding approaches are dealt with in a way allowing a critical biological assessment and enabling the scientific community and public to put genetic engineering of ornamental plants into a perspective regarding their usefulness in plant breeding.

6th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

2016-01-01

This edited book presents scientific results of the 16th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2015) which was held on June 1 – 3, 2015 in Takamatsu, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing

CERN Document Server

SNPD 2016

2016-01-01

This edited book presents scientific results of the 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2016) which was held on May 30 - June 1, 2016 in Shanghai, China. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.

Commodifying animals: ethical issues in genetic engineering of animals.

Science.gov (United States)

Almond, B

2000-03-01

The genetic modification of living beings raises special ethical concerns which go beyond general discussion of animal rights or welfare. Although the goals may be similar, biotechnology has accelerated the process of modification of types traditionally carried out by cross-breeding. These changes are discussed in relation to two areas: biomedicine, and animal husbandry. Alternative ethical approaches are reviewed, and it is argued that the teleological thesis underlying virtue ethics has special relevance here. The case for and the case against genetic engineering and patenting of life-forms are examined, and conclusions are drawn which favour regulation, caution and respect for animals and animal species.

An active artificial cornea with the function of inducing new corneal tissue generation in vivo-a new approach to corneal tissue engineering

International Nuclear Information System (INIS)

Huang Yaoxiong; Li Qinhua

2007-01-01

An active artificial cornea which can perform the function of inducing new cornea generation in vivo but does not need culture cells in vitro and which has similar optical and mechanical properties to those of the human cornea was constructed. An animal keratoplasty experiment using the artificial cornea as the implant showed that the animals' corneas could keep smooth surface and clear stroma postoperatively, and that the repopulation of the host's keratocytes, the degradation of the implant and new corneal tissue generation were completed at 5-6 months after surgery. Such an artificial cornea has several advantages over other corneal equivalents constructed in the typical way of tissue engineering: in having similar mechanical and optical properties to those of the human cornea and with no exogenetic cells, it can be used universally in different implantation surgeries without immunoreaction; it is easy to prepare and process into different shapes and sizes on a large scale, and suitable for long-distance transportation and long-term storage. All these characteristics make it a new approach to cornea tissue engineering having potential in many clinical applications

Physiology of SLC12 transporters: lessons from inherited human genetic mutations and genetically engineered mouse knockouts.

Science.gov (United States)

Gagnon, Kenneth B; Delpire, Eric

2013-04-15

Among the over 300 members of the solute carrier (SLC) group of integral plasma membrane transport proteins are the nine electroneutral cation-chloride cotransporters belonging to the SLC12 gene family. Seven of these transporters have been functionally described as coupling the electrically silent movement of chloride with sodium and/or potassium. Although in silico analysis has identified two additional SLC12 family members, no physiological role has been ascribed to the proteins encoded by either the SLC12A8 or the SLC12A9 genes. Evolutionary conservation of this gene family from protists to humans confirms their importance. A wealth of physiological, immunohistochemical, and biochemical studies have revealed a great deal of information regarding the importance of this gene family to human health and disease. The sequencing of the human genome has provided investigators with the capability to link several human diseases with mutations in the genes encoding these plasma membrane proteins. The availability of bacterial artificial chromosomes, recombination engineering techniques, and the mouse genome sequence has simplified the creation of targeting constructs to manipulate the expression/function of these cation-chloride cotransporters in the mouse in an attempt to recapitulate some of these human pathologies. This review will summarize the three human disorders that have been linked to the mutation/dysfunction of the Na-Cl, Na-K-2Cl, and K-Cl cotransporters (i.e., Bartter's, Gitleman's, and Andermann's syndromes), examine some additional pathologies arising from genetically modified mouse models of these cotransporters including deafness, blood pressure, hyperexcitability, and epithelial transport deficit phenotypes.

Artificial intelligence for the modeling and control of combustion processes: a review

Energy Technology Data Exchange (ETDEWEB)

Soteris A. Kalogirou, [Higher Technical Institute, Nicosia (Cyprus). Department of Mechanical Engineering

2003-07-01

Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. AI systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how AI techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of AI as a design tool in many areas of combustion engineering. 109 refs., 31 figs., 11 tabs.

Implanted artificial heart with radioisotope power source

Energy Technology Data Exchange (ETDEWEB)

Shumakov, V I; Griaznov, G M; Zhemchuzhnikov, G N; Kiselev, I M; Osipov, A P

1983-02-01

An atomic artificial heart for orthotopic implantation was developed with the following characteristics: volume, 1.2 L; weight, 1.5 kg; radioisotope power, 45 W; operating life, up to 5 years; hemodynamics, similar to natural hemodynamics. The artificial heart includes a thermal drive with systems for regulating power, feeding steam into the cylinders, return of the condensate to the steam generator, and delivery of power to the ventricles and heat container. The artificial heart is placed in an artificial pericardium partially filled with physiologic solution. It uses a steam engine with two operating cylinders that separately drive the left and right ventricles. There is no electronic control system in the proposed design. The operation of the heat engine is controlled, with preservation of autoregulation by the vascular system of the body. The separate drives for the ventricles is of primary importance as it provides for operation of the artificial heart through control of cardiac activity by venous return. Experimental testing on a hydromechanical bench demonstrated effective autoregulation.

Reusable rocket engine preventive maintenance scheduling using genetic algorithm

International Nuclear Information System (INIS)

Chen, Tao; Li, Jiawen; Jin, Ping; Cai, Guobiao

2013-01-01

This paper deals with the preventive maintenance (PM) scheduling problem of reusable rocket engine (RRE), which is different from the ordinary repairable systems, by genetic algorithm. Three types of PM activities for RRE are considered and modeled by introducing the concept of effective age. The impacts of PM on all subsystems' aging processes are evaluated based on improvement factor model. Then the reliability of engine is formulated by considering the accumulated time effect. After that, optimization model subjected to reliability constraint is developed for RRE PM scheduling at fixed interval. The optimal PM combination is obtained by minimizing the total cost in the whole life cycle for a supposed engine. Numerical investigations indicate that the subsystem's intrinsic reliability characteristic and the improvement factor of maintain operations are the most important parameters in RRE's PM scheduling management

De-Problematizing 'GMOs': Suggestions for Communicating about Genetic Engineering.

Science.gov (United States)

Blancke, Stefaan; Grunewald, Wim; De Jaeger, Geert

2017-03-01

The public debates concerning genetic engineering (GE) involve many non-scientific issues. The ensuing complexity is one reason why biotechnologists are reluctant to become involved. By sharing our personal experiences in science communication and suggesting ways to de-problematize GE, we aim to inspire our colleagues to engage with the public. Copyright © 2016 Elsevier Ltd. All rights reserved.

Field cage studies and progressive evaluation of genetically-engineered mosquitoes.

Directory of Open Access Journals (Sweden)

Luca Facchinelli

Full Text Available A genetically-engineered strain of the dengue mosquito vector Aedes aegypti, designated OX3604C, was evaluated in large outdoor cage trials for its potential to improve dengue prevention efforts by inducing population suppression. OX3604C is engineered with a repressible genetic construct that causes a female-specific flightless phenotype. Wild-type females that mate with homozygous OX3604C males will not produce reproductive female offspring. Weekly introductions of OX3604C males eliminated all three targeted Ae. aegypti populations after 10-20 weeks in a previous laboratory cage experiment. As part of the phased, progressive evaluation of this technology, we carried out an assessment in large outdoor field enclosures in dengue endemic southern Mexico.OX3604C males were introduced weekly into field cages containing stable target populations, initially at 10:1 ratios. Statistically significant target population decreases were detected in 4 of 5 treatment cages after 17 weeks, but none of the treatment populations were eliminated. Mating competitiveness experiments, carried out to explore the discrepancy between lab and field cage results revealed a maximum mating disadvantage of up 59.1% for OX3604C males, which accounted for a significant part of the 97% fitness cost predicted by a mathematical model to be necessary to produce the field cage results.Our results indicate that OX3604C may not be effective in large-scale releases. A strain with the same transgene that is not encumbered by a large mating disadvantage, however, could have improved prospects for dengue prevention. Insights from large outdoor cage experiments may provide an important part of the progressive, stepwise evaluation of genetically-engineered mosquitoes.

Genetically engineering adenoviral vectors for gene therapy.

Science.gov (United States)

Coughlan, Lynda

2014-01-01

Adenoviral (Ad) vectors are commonly used for various gene therapy applications. Significant advances in the genetic engineering of Ad vectors in recent years has highlighted their potential for the treatment of metastatic disease. There are several methods to genetically modify the Ad genome to incorporate retargeting peptides which will redirect the natural tropism of the viruses, including homologous recombination in bacteria or yeast. However, homologous recombination in yeast is highly efficient and can be achieved without the need for extensive cloning strategies. In addition, the method does not rely on the presence of unique restriction sites within the Ad genome and the reagents required for this method are widely available and inexpensive. Large plasmids containing the entire adenoviral genome (~36 kbp) can be modified within Saccharomyces cerevisiae yeast and genomes easily rescued in Escherichia coli hosts for analysis or amplification. A method for two-step homologous recombination in yeast is described in this chapter.

Artificial Intelligence

CERN Document Server

Warwick, Kevin

2011-01-01

if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

Analysis of genetic variation and potential applications in genome-scale metabolic modeling

DEFF Research Database (Denmark)

Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

2015-01-01

scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

Engineering Values into Genetic Engineering: A Proposed Analytic Framework for Scientific Social Responsibility

OpenAIRE

Sankar, Pamela L.; Cho, Mildred K.

2015-01-01

Recent experiments have been used to “edit” genomes of various plant, animal and other species, including humans, with unprecedented precision. Furthermore, editing Cas9 endonuclease gene with a gene encoding the desired guide RNA into an organism, adjacent to an altered gene, could create a “gene drive” that could spread a trait through an entire population of organisms. These experiments represent advances along a spectrum of technological abilities that genetic engineers have been working ...

Open field release of genetically engineered sterile male Aedes aegypti in Malaysia.

Directory of Open Access Journals (Sweden)

Renaud Lacroix

Full Text Available BACKGROUND: Dengue is the most important mosquito-borne viral disease. In the absence of specific drugs or vaccines, control focuses on suppressing the principal mosquito vector, Aedes aegypti, yet current methods have not proven adequate to control the disease. New methods are therefore urgently needed, for example genetics-based sterile-male-release methods. However, this requires that lab-reared, modified mosquitoes be able to survive and disperse adequately in the field. METHODOLOGY/PRINCIPAL FINDINGS: Adult male mosquitoes were released into an uninhabited forested area of Pahang, Malaysia. Their survival and dispersal was assessed by use of a network of traps. Two strains were used, an engineered 'genetically sterile' (OX513A and a wild-type laboratory strain, to give both absolute and relative data about the performance of the modified mosquitoes. The two strains had similar maximum dispersal distances (220 m, but mean distance travelled of the OX513A strain was lower (52 vs. 100 m. Life expectancy was similar (2.0 vs. 2.2 days. Recapture rates were high for both strains, possibly because of the uninhabited nature of the site. CONCLUSIONS/SIGNIFICANCE: After extensive contained studies and regulatory scrutiny, a field release of engineered mosquitoes was safely and successfully conducted in Malaysia. The engineered strain showed similar field longevity to an unmodified counterpart, though in this setting dispersal was reduced relative to the unmodified strain. These data are encouraging for the future testing and implementation of genetic control strategies and will help guide future field use of this and other engineered strains.

Profitability of a dairy sheep genetic improvement program using artificial insemination.

Science.gov (United States)

Valergakis, G E; Gelasakis, A I; Oikonomou, G; Arsenos, G; Fortomaris, P; Banos, G

2010-10-01

This simulation study investigated the farm-level economic benefits of a genetic improvement scheme using artificial insemination (AI) with fresh ram semen in dairy sheep of the Chios breed in Greece. Data were collected from 67 farms associated with the Chios Sheep Breeders' Cooperative 'Macedonia', describing the percentage of ewes that would be artificially inseminated in the flock, pregnancy rate, annual ram costs that could be saved using AI rather than natural mating, expected improvement in milk production, annual costs of semen and feed, milk price and number of years of AI usage. The study considered 77 760 possible scenarios in a 3 × 4 × 4 × 3 × 3 × 3 × 4 × 15 factorial arrangement. Analysis of variance was used to investigate the effect of each factor on farm profitability. All factors considered were statistically significant (P profitability and farmers should become aware that using AI is a long-term investment. Semen price, pregnancy rate and improvement in milk production also had substantial effects. The price of milk and feed had a considerably lower effect on profitability, as did the annual cost of maintaining rams that would be replaced by AI. A positive annual and cumulative return was achieved in the model within the first 6 years. The cost of semen was estimated at 8€ to 10€ per dose for the first 5 years. Where the annual improvement in milk production was 1% of annual phenotypic mean (e.g. 3.0 kg) profitability of the scheme was improved greatly.

Engineering Technology Of Fish Farming Floating Nets Cages On Polka Dot Grouper (Cromileptes Altivelis) Used Artificial Feed Enriched Phytase Enzyme

Science.gov (United States)

Samidjan, Istiyanto; Rachmawati, Diana

2018-02-01

One solution is to utilize engineering technology cultivation floating cage net polka dot grouper (ducker grouper), which is given artificial feed enriched with phytase enzymes. The objectives of this study was to examine the use of technology engineering floating net on ducker grouper on artificial feed that is enriched with different dose phytase enzymes to accelerate growth and survival. The research method used ducker grouper fish size 15,5 ± 0,5 cm in the net cages unit (1 m x 1 m x 1 m), 250 fish per cage, using 12 cages. Each net-cages was made of polyethylens netting, mesh size 12.5 mm. with complete randomized design (CRD) 4 treatment and 3 replication were feed Artificial enriched of phytase enzyme with the doses of A (0 FTU · kg-1 diet), B (200 FTU · kg-1 diet), C (500 FTU · kg-1 diet), and D (800 FTU · kg-1 diet) phytase enzyme. Feed was given 2 times a day in the morning and afternoon with 5% biomass per day. Data includes the growth of absolute weight polka dot grouper, FCR, and survival rate analyzed variety and Test Tukey.The result of the research showed that the difference of artificial feeding enriched phytase enzyme significantly (P <0,05) to growth, food conversion ratio (FCR), survival rete of polka dot grouper. The best treatment at C (500 mg / kg of feed) increase growth of absolute weight of 128.75 g, 1.75 (FCR), and a survival rate of 93.5%.

Software and Network Engineering

CERN Document Server

2012-01-01

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.   The purpose of the first ACIS International Symposium on Software and Network Engineering held on Decembe...

Natural genetic engineering: intelligence & design in evolution?

DEFF Research Database (Denmark)

Ussery, David

2011-01-01

There are many things that I like about James Shapiro's new book "Evolution: A View from the 21st Century" (FT Press Science, 2011). He begins the book by saying that it is the creation of novelty, and not selection, that is important in the history of life. In the presence of heritable traits...... function. Shapiro argues that what we see in genomes is 'Natural Genetic Engineering', or designed evolution: "Thinking about genomes from an informatics perspective, it is apparent that systems engineering is a better metaphor for the evolutionary process than the conventional view of evolution...... as a select-biased random walk through limitless space of possible DNA configurations" (page 6). In this review, I will have a look at four topics: 1.) why I think genomics is not the whole story; 2.) my own perspective of E. coli genomics, and how I think it relates to this book; 3.) a brief discussion...

Study on biofortification of rice by targeted genetic engineering

Directory of Open Access Journals (Sweden)

Sumon M. Hossain

2012-12-01

Full Text Available Micronutrient malnutrition is a major health problem in Bangladesh and also in many other developing countries, where a diversified diet is not affordable for the majority. In the present world- one, out of seven people suffers from hunger. Yet, there is a stealthier form of hunger than lack of food: micronutrient malnutrition or hidden hunger. While often providing enough calories, monotonous diets (of rural poor frequently fail to deliver sufficient quantities of essential minerals and vitamins. Due to micronutrient deficiencies different characteristic features have been observed to the victims. Various estimates indicate that over two-thirds of the world population, for the most part women and children specially, pre-school children are deficient in at least one micronutrient. This can have devastating consequences for the life, health and well being of the individuals concerned (like premature death, blindness, weakened immune systems etc. Genetic engineering approach is the upcoming strategy to solve this problem. Genetically engineered biofortified staple crops specially, rice that are high in essential micronutrients (Fe, Zn, vitamin A and adapted to local growing environments have the potential to significantly reduce the prevalence of micronutrient deficiencies specially to the rural poor.

Genetic engineering in nonhuman primates for human disease modeling.

Science.gov (United States)

Sato, Kenya; Sasaki, Erika

2018-02-01

Nonhuman primate (NHP) experimental models have contributed greatly to human health research by assessing the safety and efficacy of newly developed drugs, due to their physiological and anatomical similarities to humans. To generate NHP disease models, drug-inducible methods, and surgical treatment methods have been employed. Recent developments in genetic and developmental engineering in NHPs offer new options for producing genetically modified disease models. Moreover, in recent years, genome-editing technology has emerged to further promote this trend and the generation of disease model NHPs has entered a new era. In this review, we summarize the generation of conventional disease model NHPs and discuss new solutions to the problem of mosaicism in genome-editing technology.

Engineering genetic circuit interactions within and between synthetic minimal cells

Science.gov (United States)

Adamala, Katarzyna P.; Martin-Alarcon, Daniel A.; Guthrie-Honea, Katriona R.; Boyden, Edward S.

2017-05-01

Genetic circuits and reaction cascades are of great importance for synthetic biology, biochemistry and bioengineering. An open question is how to maximize the modularity of their design to enable the integration of different reaction networks and to optimize their scalability and flexibility. One option is encapsulation within liposomes, which enables chemical reactions to proceed in well-isolated environments. Here we adapt liposome encapsulation to enable the modular, controlled compartmentalization of genetic circuits and cascades. We demonstrate that it is possible to engineer genetic circuit-containing synthetic minimal cells (synells) to contain multiple-part genetic cascades, and that these cascades can be controlled by external signals as well as inter-liposomal communication without crosstalk. We also show that liposomes that contain different cascades can be fused in a controlled way so that the products of incompatible reactions can be brought together. Synells thus enable a more modular creation of synthetic biology cascades, an essential step towards their ultimate programmability.

Genetic engineering microbes for bioremediation/ biorecovery of uranium

International Nuclear Information System (INIS)

Apte, S.K.; Rao, A.S.; Appukuttan, D.; Nilgiriwala, K.S.; Acharya, C.

2005-01-01

Bioremediation (both bioremoval and biorecovery) of metals is considered a feasible, economic and eco-friendly alternative to chemical methods of metal extraction, particularly when the metal concentration is very low. Scanty distribution along with poor ore quality makes biomining of uranium an attractive preposition. Biosorption, bioprecipitation or bioaccumulation of uranium, aided by recombinant DNA technology, offer a promising technology for recovery of uranium from acidic or alkaline nuclear waste, tailings or from sea-water. Genetic engineering of bacteria, with a gene encoding an acid phosphatase, has yielded strains that can bioprecipitate uranium from very low concentrations at acidic-neutral pH, in a relatively short time. Organisms overproducing alkaline phosphatase have been selected for uranium precipitation from alkaline waste. Such abilities have now been transferred to the radioresistant microbe Deinococcus radiodurans to facilitate in situ bioremediation of nuclear waste, with some success. Sulfate-reducing bacteria are being characterized for bioremediation of uranium in tailings with the dual objective of uranium precipitation and reduction of sulfate to sulphide. Certain marine cyanobacteria have shown promise for uranium biosorption to extracellular polysaccharides, and intracellular accumulation involving metal sequestering metallothionin proteins. Future work is aimed at understanding the genetic basis of these abilities and to engineer them into suitable organisms subsequently. As photosynthetic, nitrogen-fixing microbes, which are considerably resistant to ionizing radiations, cyanobacteria hold considerable potential for bioremediation of nuclear waste. (author)

Training Software in Artificial-Intelligence Computing Techniques

Science.gov (United States)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Genetic engineering of crops: a ray of hope for enhanced food security.

Science.gov (United States)

Gill, Sarvajeet Singh; Gill, Ritu; Tuteja, Renu; Tuteja, Narendra

2014-01-01

Crop improvement has been a basic and essential chase since organized cultivation of crops began thousands of years ago. Abiotic stresses as a whole are regarded as the crucial factors restricting the plant species to reach their full genetic potential to deliver desired productivity. The changing global climatic conditions are making them worse and pointing toward food insecurity. Agriculture biotechnology or genetic engineering has allowed us to look into and understand the complex nature of abiotic stresses and measures to improve the crop productivity under adverse conditions. Various candidate genes have been identified and transformed in model plants as well as agriculturally important crop plants to develop abiotic stress-tolerant plants for crop improvement. The views presented here are an attempt toward realizing the potential of genetic engineering for improving crops to better tolerate abiotic stresses in the era of climate change, which is now essential for global food security. There is great urgency in speeding up crop improvement programs that can use modern biotechnological tools in addition to current breeding practices for providing enhanced food security.

[Progress of research on genetic engineering antibody and its application in prevention and control of parasitic diseases].

Science.gov (United States)

Yao, Yuan; Yu, Chuan-xin

2013-08-01

Antibody has extensive application prospects in the biomedical field. The inherent disadvantages of traditional polyclonal antibody and monoclonal antibody limit their application values. The humanized and fragmented antibody remodeling has given a rise to a series of genetic engineered antibody variant. This paper reviews the progress of research on genetic engineering antibody and its application in prevention and control of parasitic diseases.

Artificial Immune Networks: Models and Applications

Directory of Open Access Journals (Sweden)

Xian Shen

2008-06-01

Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.

Optimization the initial weights of artificial neural networks via genetic algorithm applied to hip bone fracture prediction

OpenAIRE

Chang, Y-T; Lin, J; Shieh, J-S; Abbod, MF

2012-01-01

This paper aims to find the optimal set of initial weights to enhance the accuracy of artificial neural networks (ANNs) by using genetic algorithms (GA). The sample in this study included 228 patients with first low-trauma hip fracture and 215 patients without hip fracture, both of them were interviewed with 78 questions. We used logistic regression to select 5 important factors (i.e., bone mineral density, experience of fracture, average hand grip strength, intake of coffee, and peak expirat...

IMPROVING PLANT GENETIC ENGINEERING BY MANIPULATING THE HOST. (R829479C001)

Science.gov (United States)

Agrobacterium-mediated transformation is a major technique for the genetic engineering of plants. However, there are many economically important crop and tree species that remain highly recalcitrant to Agrobacterium infection. Although attempts have been made to ...

Genetic-evolution-based optimization methods for engineering design

Science.gov (United States)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Analysis of Mental Processes Represented in Models of Artificial Consciousness

Directory of Open Access Journals (Sweden)

Luana Folchini da Costa

2013-12-01

Full Text Available The Artificial Consciousness concept has been used in the engineering area as being an evolution of the Artificial Intelligence. However, consciousness is a complex subject and often used without formalism. As a main contribution, in this work one proposes an analysis of four recent models of artificial consciousness published in the engineering area. The mental processes represented by these models are highlighted and correlations with the theoretical perspective of cognitive psychology are made. Finally, considerations about consciousness in such models are discussed.

Artificial Intelligence (AI) Studies in Water Resources

OpenAIRE

Ay, Murat; Özyıldırım, Serhat

2018-01-01

Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

Telos, conservation of welfare, and ethical issues in genetic engineering of animals.

Science.gov (United States)

Rollin, Bernard E

2015-01-01

The most long-lived metaphysics or view of reality in the history of Western thought is Aristotle's teleology, which reigned for almost 2,000 years. Biology was expressed in terms of function or telos, and accorded perfectly with common sense. The rise of mechanistic, Newtonian science vanquished teleological explanations. Understanding and accommodating animal telos was essential to success in animal husbandry, which involved respect for telos, and was presuppositional to our "ancient contract" with domestic animals. Telos was further abandoned with the rise of industrial agriculture, which utilized "technological fixes" to force animal into environments they were unsuited for, while continuing to be productive. Loss of husbandry and respect for telos created major issues for farm animal welfare, and forced the creation of a new ethic demanding respect for telos. As genetic engineering developed, the notion arose of modifying animals to fit their environment in order to avoid animal suffering, rather than fitting them into congenial environments. Most people do not favor changing the animals, rather than changing the conditions under which they are reared. Aesthetic appreciation of husbandry and virtue ethics militate in favor of restoring husbandry, rather than radically changing animal teloi. One, however, does not morally wrong teloi by changing them-one can only wrong individuals. In biomedical research, we do indeed inflict major pain, suffering and disease on animals. And genetic engineering seems to augment our ability to create animals to model diseases, particularly more than 3,000 known human genetic diseases. The disease, known as Lesch-Nyhan's syndrome or HPRT deficiency, which causes self-mutilation and mental retardation, provides us with a real possibility for genetically creating "animal models" of this disease, animals doomed to a life of great and unalleviable suffering. This of course creates a major moral dilemma. Perhaps one can use the very

Bacterial Artificial Chromosome Clones of Viruses Comprising the Towne Cytomegalovirus Vaccine

Directory of Open Access Journals (Sweden)

Xiaohong Cui

2012-01-01

Full Text Available Bacterial artificial chromosome (BAC clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines.

Bacterial artificial chromosome clones of viruses comprising the towne cytomegalovirus vaccine.

Science.gov (United States)

Cui, Xiaohong; Adler, Stuart P; Davison, Andrew J; Smith, Larry; Habib, El-Sayed E; McVoy, Michael A

2012-01-01

Bacterial artificial chromosome (BAC) clones have proven invaluable for genetic manipulation of herpesvirus genomes. BAC cloning can also be useful for capturing representative genomes that comprise a viral stock or mixture. The Towne live attenuated cytomegalovirus vaccine was developed in the 1970s by serial passage in cultured fibroblasts. Although its safety, immunogenicity, and efficacy have been evaluated in nearly a thousand human subjects, the vaccine itself has been little studied. Instead, genetic composition and in vitro growth properties have been inferred from studies of laboratory stocks that may not always accurately represent the viruses that comprise the vaccine. Here we describe the use of BAC cloning to define the genotypic and phenotypic properties of viruses from the Towne vaccine. Given the extensive safety history of the Towne vaccine, these BACs provide a logical starting point for the development of next-generation rationally engineered cytomegalovirus vaccines.

Soft computing in artificial intelligence

CERN Document Server

Matson, Eric

2014-01-01

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

The Significance of Content Knowledge for Informal Reasoning regarding Socioscientific Issues: Applying Genetics Knowledge to Genetic Engineering Issues

Science.gov (United States)

Sadler, Troy D.; Zeidler, Dana L.

2005-01-01

This study focused on informal reasoning regarding socioscientific issues. It sought to explore how content knowledge influenced the negotiation and resolution of contentious and complex scenarios based on genetic engineering. Two hundred and sixty-nine students drawn from undergraduate natural science and nonnatural science courses completed a…

Pile-up correction by Genetic Algorithm and Artificial Neural Network

Science.gov (United States)

Kafaee, M.; Saramad, S.

2009-08-01

Pile-up distortion is a common problem for high counting rates radiation spectroscopy in many fields such as industrial, nuclear and medical applications. It is possible to reduce pulse pile-up using hardware-based pile-up rejections. However, this phenomenon may not be eliminated completely by this approach and the spectrum distortion caused by pile-up rejection can be increased as well. In addition, inaccurate correction or rejection of pile-up artifacts in applications such as energy dispersive X-ray (EDX) spectrometers can lead to losses of counts, will give poor quantitative results and even false element identification. Therefore, it is highly desirable to use software-based models to predict and correct any recognized pile-up signals in data acquisition systems. The present paper describes two new intelligent approaches for pile-up correction; the Genetic Algorithm (GA) and Artificial Neural Networks (ANNs). The validation and testing results of these new methods have been compared, which shows excellent agreement with the measured data with 60Co source and NaI detector. The Monte Carlo simulation of these new intelligent algorithms also shows their advantages over hardware-based pulse pile-up rejection methods.

Genetic engineering: Rifkin strikes at corn this time.

Science.gov (United States)

Budiansky, S

As a result of a threatened suit by Jeremy Rifkin, Stanford University has postponed an experiment involving a test plot of genetically-engineered corn. At issue is an injunction forbidding the Recombinant DNA Advisory Committee of the National Institutes of Health from approving federal funding of experiments entailing the release of recombinant DNA into the environment. Rifkin's legal argument is that an environmnental impact statement must be filed for both commercially- and federally-funded research. It is expected that Rifkin's demand for equal treatment regardless of funding source will be agreed to by NIH.

An application of artificial intelligence for rainfall–runoff modeling

Indian Academy of Sciences (India)

This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

Parametric optimization design for supercritical CO2 power cycle using genetic algorithm and artificial neural network

International Nuclear Information System (INIS)

Wang Jiangfeng; Sun Zhixin; Dai Yiping; Ma Shaolin

2010-01-01

Supercritical CO 2 power cycle shows a high potential to recover low-grade waste heat due to its better temperature glide matching between heat source and working fluid in the heat recovery vapor generator (HRVG). Parametric analysis and exergy analysis are conducted to examine the effects of thermodynamic parameters on the cycle performance and exergy destruction in each component. The thermodynamic parameters of the supercritical CO 2 power cycle is optimized with exergy efficiency as an objective function by means of genetic algorithm (GA) under the given waste heat condition. An artificial neural network (ANN) with the multi-layer feed-forward network type and back-propagation training is used to achieve parametric optimization design rapidly. It is shown that the key thermodynamic parameters, such as turbine inlet pressure, turbine inlet temperature and environment temperature have significant effects on the performance of the supercritical CO 2 power cycle and exergy destruction in each component. It is also shown that the optimum thermodynamic parameters of supercritical CO 2 power cycle can be predicted with good accuracy using artificial neural network under variable waste heat conditions.

Artificial intelligence in power system optimization

CERN Document Server

Ongsakul, Weerakorn

2013-01-01

With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

Development of a New Aprepitant Liquisolid Formulation with the Aid of Artificial Neural Networks and Genetic Programming.

Science.gov (United States)

Barmpalexis, Panagiotis; Grypioti, Agni; Eleftheriadis, Georgios K; Fatouros, Dimitris G

2018-02-01

In the present study, liquisolid formulations were developed for improving dissolution profile of aprepitant (APT) in a solid dosage form. Experimental studies were complemented with artificial neural networks and genetic programming. Specifically, the type and concentration of liquid vehicle was evaluated through saturation-solubility studies, while the effect of the amount of viscosity increasing agent (HPMC), the type of wetting (Soluplus® vs. PVP) and solubilizing (Poloxamer®407 vs. Kolliphor®ELP) agents, and the ratio of solid coating (microcrystalline cellulose) to carrier (colloidal silicon dioxide) were evaluated based on in vitro drug release studies. The optimum liquisolid formulation exhibited improved dissolution characteristics compared to the marketed product Emend®. X-ray diffraction (XRD), scanning electron microscopy (SEM) and a novel method combining particle size analysis by dynamic light scattering (DLS) and HPLC, revealed that the increase in dissolution rate of APT in the optimum liquisolid formulation was due to the formation of stable APT nanocrystals. Differential scanning calorimetry (DSC) and attenuated total reflection FTIR spectroscopy (ATR-FTIR) revealed the presence of intermolecular interactions between APT and liquisolid formulation excipients. Multilinear regression analysis (MLR), artificial neural networks (ANNs), and genetic programming (GP) were used to correlate several formulation variables with dissolution profile parameters (Y 15min and Y 30min ) using a full factorial experimental design. Results showed increased correlation efficacy for ANNs and GP (RMSE of 0.151 and 0.273, respectively) compared to MLR (RMSE = 0.413).

Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Ghobadian, B.; Rahimi, H.; Nikbakht, A.M.; Najafi, G. [Tarbiat Modares University, P.O. Box 14115-111, Tehran (Iran); Yusaf, T.F. [University of Southern Queensland, Toowoomba 4350 QLD (Australia)

2009-04-15

This study deals with artificial neural network (ANN) modeling of a diesel engine using waste cooking biodiesel fuel to predict the brake power, torque, specific fuel consumption and exhaust emissions of the engine. To acquire data for training and testing the proposed ANN, a two cylinders, four-stroke diesel engine was fuelled with waste vegetable cooking biodiesel and diesel fuel blends and operated at different engine speeds. The properties of biodiesel produced from waste vegetable oil was measured based on ASTM standards. The experimental results revealed that blends of waste vegetable oil methyl ester with diesel fuel provide better engine performance and improved emission characteristics. Using some of the experimental data for training, an ANN model was developed based on standard Back-Propagation algorithm for the engine. Multi layer perception network (MLP) was used for non-linear mapping between the input and output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the ANN model can predict the engine performance and exhaust emissions quite well with correlation coefficient (R) 0.9487, 0.999, 0.929 and 0.999 for the engine torque, SFC, CO and HC emissions, respectively. The prediction MSE (Mean Square Error) error was between the desired outputs as measured values and the simulated values were obtained as 0.0004 by the model. (author)

Biological Systems Thinking for Control Engineering Design

Directory of Open Access Journals (Sweden)

D. J. Murray-Smith

2004-01-01

Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

Effect of heat stress on contractility of tissue-engineered artificial skeletal muscle.

Science.gov (United States)

Takagi, Shunya; Nakamura, Tomohiro; Fujisato, Toshia

2018-01-23

The effects of heat stress on tissue like skeletal muscle have been widely studied. However, the mechanism responsible for the effect of heat stress is still unclear. A useful experimental tissue model is necessary because muscle function in cell culture may differ from native muscle and measuring its contractility is difficult. We previously reported three-dimensional tissue-engineered artificial skeletal muscle (TEM) that can be easily set in a measurement apparatus for quantitative evaluation of contractility. We have now applied TEM to the investigation of heat stress. We analyzed contractility immediately after thermal exposure at 39 °C for 24 or 48 h to evaluate the acute effects and after thermal exposure followed by normal culture to evaluate the aftereffects. Peak twitch contractile force and time-to-peak twitch were used as contractile parameters. Heat stress increased the TCF in the early stage (1 week) after normal culture; the TCF decreased temporarily in the middle to late stages (2-3 weeks). These results suggest that heat stress may affect both myoblast fusion and myotube differentiation in the early stage of TEM culture, but not myotube maturation in the late stage. The TCF increase rate with thermal exposure was significantly higher than that without thermal exposure. Although detailed analysis at the molecular level is necessary for further investigation, our artificial skeletal muscle may be a promising tool for heat stress investigation.

Application of Genetic Engineering for Chromium Removal from Industrial Wastewater

OpenAIRE

N. K. Srivastava; M. K. Jha; I. D. Mall; Davinder Singh

2010-01-01

The treatment of the industrial wastewater can be particularly difficult in the presence of toxic compounds. Excessive concentration of Chromium in soluble form is toxic to a wide variety of living organisms. Biological removal of heavy metals using natural and genetically engineered microorganisms has aroused great interest because of its lower impact on the environment. Ralston metallidurans, formerly known as Alcaligenes eutrophus is a LProteobacterium colonizing indus...

Notification: Evaluation of Office of Pesticide Programs’ Genetically Engineered Corn Insect Resistance Management

Science.gov (United States)

Project #OPE-FY15-0055, July 09, 2015. The EPA OIG plans to begin preliminary research on the EPA's ability to manage and prevent increased insect resistance to genetically engineered Bacillus thuringiensis (Bt) corn.

Engineer Ethics

International Nuclear Information System (INIS)

Lee, Dae Sik; Kim, Yeong Pil; Kim, Yeong Jin

2003-03-01

This book tells of engineer ethics such as basic understanding of engineer ethics with history of engineering as a occupation, definition of engineering and specialized job and engineering, engineer ethics as professional ethics, general principles of ethics and its limitation, ethical theory and application, technique to solve the ethical problems, responsibility, safety and danger, information engineer ethics, biotechnological ethics like artificial insemination, life reproduction, gene therapy and environmental ethics.

Flow discharge prediction in compound channels using linear genetic programming

Science.gov (United States)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

Genetic engineering and chemical conjugation of potato virus X.

Science.gov (United States)

Lee, Karin L; Uhde-Holzem, Kerstin; Fischer, Rainer; Commandeur, Ulrich; Steinmetz, Nicole F

2014-01-01

Here we report the genetic engineering and chemical modification of potato virus X (PVX) for the presentation of various peptides, proteins, and fluorescent dyes, or other chemical modifiers. Three different ways of genetic engineering are described and by these means, peptides are successfully expressed not only when the foot and mouth disease virus (FMDV) 2A sequence or a flexible glycine-serine linker is included, but also when the peptide is fused directly to the PVX coat protein. When larger proteins or unfavorable peptide sequences are presented, a partial fusion via the FMDV 2A sequence is preferable. When these PVX chimeras retain the ability to assemble into viral particles and are thus able to infect plants systemically, they can be utilized to inoculate susceptible plants for isolation of sufficient amounts of virus particles for subsequent chemical modification. Chemical modification is required for the display of nonbiological ligands such as fluorophores, polymers, and small drug compounds. We present three methods of chemical bioconjugation. For direct conjugation of small chemical modifiers to solvent exposed lysines, N-hydroxysuccinimide chemistry can be applied. Bio-orthogonal reactions such as copper-catalyzed azide-alkyne cycloaddition or hydrazone ligation are alternatives to achieve more efficient conjugation (e.g., when working with high molecular weight or insoluble ligands). Furthermore, hydrazone ligation offers an attractive route for the introduction of pH-cleavable cargos (e.g., therapeutic molecules).

FY1995 establishment of extracellular matrix engineering by the combination of genetic engineering and polymer engineering and the application to super-bioartifical liver; 1995 nendo idenshi kogaku to kobunshi kogaku wo yugoshita atarashii saibogai matrix kogaku no sosei to super bio jinko zoki kaihatsu eno tenkai

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

Cellular and tissue engineering for bioartificial organs need lots of information about extra-cellular matrices and cytokines network which play important roles for the regulation of cellular function. In order to develop high performance artificial livers, we made establishment of extracellular matrix (ECM) engineering by the combination of genetic engineering and polymer engineering. We designed a superglycoprotein-like polymer (PVLA) as a specific model ligand to asialoglycoprotein receptors (ASGP-R) on hepatocytes. Hepatocytes morphology was remarkably affected by PVLA concentration for coating on polystyrene dishes. In addition, hepatic functions such as differentiation and proliferation were closely related with cell morphology. Especially, round hepatocytes on the polystyrene surface coated with high concentration of PVLA were found to reconstruct 3D liver-like tissue stimulated by EGF. It turned out that the adsorptive states of PVLA polymeric micells can switch the function of EGF to be motogenic or mitogenic. The mechanisms of 3D-tissue formation on two types of substrata mediated by ASGP-R were examined. The proliferation and cell death (apoptosis) in hepatitis of hepatocytes were also examined in the viewpoint of cytokine network such as TNF - {alpha} and interferon-{gamma}. The highly efficient gene-transfection into hepatocytes was also successfully made using PVLA as ECM for cell attachment. As one of the trials to clarify liver cells society formation the mechanism of the final differentiation of kupffer cells and the role of HGF in embryonic construction of liver were successfully examined. (NEDO)

IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN

Directory of Open Access Journals (Sweden)

K. Prasada Rao

2017-09-01

Full Text Available Biodiesel is receiving increasing attention each passing day because of its fuel properties and compatibility. This study investigates the performance and emission characteristics of single cylinder four stroke indirect diesel injection (IDI engine fueled with Rice Bran Methyl Ester (RBME with Isopropanol additive. The investigation is done through a combination of experimental data analysis and artificial neural network (ANN modeling. The study used IDI engine experimental data to evaluate nine engine performance and emission parameters including Exhaust Gas Temperature (E.G.T, Brake Specific Fuel Consumption (BSFC, Brake Thermal Efficiency (B.The and various emissions like Hydrocarbons (HC, Carbon monoxide (CO, Carbon dioxide (CO2, Oxygen (O2, Nitrogen oxides (NOX and smoke. For the ANN modeling standard back propagation algorithm was found to be the optimum choice for training the model. A multi-layer perception (MLP network was used for non-linear mapping between the input and output parameters. It was found that ANN was able to predict the engine performance and exhaust emissions with a correlation coefficient of 0.995, 0.980, 0.999, 0.985, 0.999, 0.999, 0.980, 0.999, and 0.999 for E.G.T, BSFC, B.The, HC, O2, CO2, CO, NOX, smoke respectively.

Genetic Engineering and Sustainable Crop Disease Management: Opportunities for Case-by-Case Decision-Making

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Paul Vincelli

2016-05-01

Full Text Available Genetic engineering (GE offers an expanding array of strategies for enhancing disease resistance of crop plants in sustainable ways, including the potential for reduced pesticide usage. Certain GE applications involve transgenesis, in some cases creating a metabolic pathway novel to the GE crop. In other cases, only cisgenessis is employed. In yet other cases, engineered genetic changes can be so minimal as to be indistinguishable from natural mutations. Thus, GE crops vary substantially and should be evaluated for risks, benefits, and social considerations on a case-by-case basis. Deployment of GE traits should be with an eye towards long-term sustainability; several options are discussed. Selected risks and concerns of GE are also considered, along with genome editing, a technology that greatly expands the capacity of molecular biologists to make more precise and targeted genetic edits. While GE is merely a suite of tools to supplement other breeding techniques, if wisely used, certain GE tools and applications can contribute to sustainability goals.

Bioengineering of Artificial Lymphoid Organs.

Science.gov (United States)

Nosenko, M A; Drutskaya, M S; Moisenovich, M M; Nedospasov, S A

2016-01-01

This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed.

Epistasis analysis using artificial intelligence.

Science.gov (United States)

Moore, Jason H; Hill, Doug P

2015-01-01

Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of expert knowledge as a guide. The methodology presented here is based on computational evolution, which is a type of genetic programming. The ability to generate interesting solutions while at the same time learning how to solve the problem at hand distinguishes computational evolution from other genetic programming approaches. We provide a general overview of this approach and then present a few examples of its application to real data.

Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

Science.gov (United States)

Dechow, C D; Rogers, G W

2018-05-01

Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Artificial membrane-binding proteins stimulate oxygenation of stem cells during engineering of large cartilage tissue

Science.gov (United States)

Armstrong, James P. K.; Shakur, Rameen; Horne, Joseph P.; Dickinson, Sally C.; Armstrong, Craig T.; Lau, Katherine; Kadiwala, Juned; Lowe, Robert; Seddon, Annela; Mann, Stephen; Anderson, J. L. Ross; Perriman, Adam W.; Hollander, Anthony P.

2015-06-01

Restricted oxygen diffusion can result in central cell necrosis in engineered tissue, a problem that is exacerbated when engineering large tissue constructs for clinical application. Here we show that pre-treating human mesenchymal stem cells (hMSCs) with synthetic membrane-active myoglobin-polymer-surfactant complexes can provide a reservoir of oxygen capable of alleviating necrosis at the centre of hyaline cartilage. This is achieved through the development of a new cell functionalization methodology based on polymer-surfactant conjugation, which allows the delivery of functional proteins to the hMSC membrane. This new approach circumvents the need for cell surface engineering using protein chimerization or genetic transfection, and we demonstrate that the surface-modified hMSCs retain their ability to proliferate and to undergo multilineage differentiation. The functionalization technology is facile, versatile and non-disruptive, and in addition to tissue oxygenation, it should have far-reaching application in a host of tissue engineering and cell-based therapies.

Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity.

Directory of Open Access Journals (Sweden)

Miles Miller

Full Text Available Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism, demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in

Modular design of artificial tissue homeostasis: robust control through synthetic cellular heterogeneity.

Science.gov (United States)

Miller, Miles; Hafner, Marc; Sontag, Eduardo; Davidsohn, Noah; Subramanian, Sairam; Purnick, Priscilla E M; Lauffenburger, Douglas; Weiss, Ron

2012-01-01

Synthetic biology efforts have largely focused on small engineered gene networks, yet understanding how to integrate multiple synthetic modules and interface them with endogenous pathways remains a challenge. Here we present the design, system integration, and analysis of several large scale synthetic gene circuits for artificial tissue homeostasis. Diabetes therapy represents a possible application for engineered homeostasis, where genetically programmed stem cells maintain a steady population of β-cells despite continuous turnover. We develop a new iterative process that incorporates modular design principles with hierarchical performance optimization targeted for environments with uncertainty and incomplete information. We employ theoretical analysis and computational simulations of multicellular reaction/diffusion models to design and understand system behavior, and find that certain features often associated with robustness (e.g., multicellular synchronization and noise attenuation) are actually detrimental for tissue homeostasis. We overcome these problems by engineering a new class of genetic modules for 'synthetic cellular heterogeneity' that function to generate beneficial population diversity. We design two such modules (an asynchronous genetic oscillator and a signaling throttle mechanism), demonstrate their capacity for enhancing robust control, and provide guidance for experimental implementation with various computational techniques. We found that designing modules for synthetic heterogeneity can be complex, and in general requires a framework for non-linear and multifactorial analysis. Consequently, we adapt a 'phenotypic sensitivity analysis' method to determine how functional module behaviors combine to achieve optimal system performance. We ultimately combine this analysis with Bayesian network inference to extract critical, causal relationships between a module's biochemical rate-constants, its high level functional behavior in isolation, and

Bayesian artificial intelligence

CERN Document Server

Korb, Kevin B

2003-01-01

As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

Beyond AI: Artificial Dreams Conference

CERN Document Server

Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

2015-01-01

This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

Improving industrial yeast strains: exploiting natural and artificial diversity.

Science.gov (United States)

Steensels, Jan; Snoek, Tim; Meersman, Esther; Picca Nicolino, Martina; Voordeckers, Karin; Verstrepen, Kevin J

2014-09-01

Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity. © 2014 The Authors. FEMS Microbiology Reviews published by John Wiley & Sons Ltd on behalf of Federation of European Microbiological Societies.

Advances in Artificial Neural Networks – Methodological Development and Application

Directory of Open Access Journals (Sweden)

Yanbo Huang

2009-08-01

Full Text Available Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

Tuning the allosteric regulation of artificial muscarinic and dopaminergic ligand-gated potassium channels by protein engineering of G protein-coupled receptors

Science.gov (United States)

Moreau, Christophe J.; Revilloud, Jean; Caro, Lydia N.; Dupuis, Julien P.; Trouchet, Amandine; Estrada-Mondragón, Argel; Nieścierowicz, Katarzyna; Sapay, Nicolas; Crouzy, Serge; Vivaudou, Michel

2017-01-01

Ligand-gated ion channels enable intercellular transmission of action potential through synapses by transducing biochemical messengers into electrical signal. We designed artificial ligand-gated ion channels by coupling G protein-coupled receptors to the Kir6.2 potassium channel. These artificial channels called ion channel-coupled receptors offer complementary properties to natural channels by extending the repertoire of ligands to those recognized by the fused receptors, by generating more sustained signals and by conferring potassium selectivity. The first artificial channels based on the muscarinic M2 and the dopaminergic D2L receptors were opened and closed by acetylcholine and dopamine, respectively. We find here that this opposite regulation of the gating is linked to the length of the receptor C-termini, and that C-terminus engineering can precisely control the extent and direction of ligand gating. These findings establish the design rules to produce customized ligand-gated channels for synthetic biology applications. PMID:28145461

An analysis of the genetic diversity and genetic structure of ...

African Journals Online (AJOL)

Scientific approaches to conservation of threatened species depend on a good understanding of the genetic information of wild and artificial population. The genetic diversity and structure analysis of 10 Eucommia ulmoides population was analyzed using inter-simple sequence repeat (ISSR) markers in this paper.

Consumer attitudes and decision-making with regard to genetically engineered food products: A review of the literature and a presentation of models for future research

DEFF Research Database (Denmark)

Bredahl, Lone; Grunert, Klaus G.; Frewer, Lynn

Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard t...... Likelihood Model and Social Judgment Theory. The model specifically takes into account the impact of credibility and various informational factors, such as persuasive content of the information provided, on attitudes.......Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard...... engineering in food production in general as additional determinants of behavioural intentions. 5. How consumers' attitudes towards genetically engineered food products are affected by various information strategies is explained in an attitude change model, which integrates aspects of the Elaboration...

Consumer attitudes and decision-making with regard to genetically engineered food products: A review of the literature and a presentation of models for future research

DEFF Research Database (Denmark)

Bredahl, Lone; Grunert, Klaus G.; Frewer, Lynn

1998-01-01

Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard t...... Likelihood Model and Social Judgment Theory. The model specifically takes into account the impact of credibility and various informational factors, such as persuasive content of the information provided, on attitudes.......Executive summary 1. Few studies have to date explained consumer attitudes and purchase decisions with regard to genetically engineered food products. However, the increased marketing of genetically engineered food products and the considerable concern that consumers seem to express with regard...... engineering in food production in general as additional determinants of behavioural intentions. 5. How consumers' attitudes towards genetically engineered food products are affected by various information strategies is explained in an attitude change model, which integrates aspects of the Elaboration...

Novel method to load multiple genes onto a mammalian artificial chromosome.

Directory of Open Access Journals (Sweden)

Anna Tóth

Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

Novel method to load multiple genes onto a mammalian artificial chromosome.

Science.gov (United States)

Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

2014-01-01

Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

Science, law, and politics in the Food and Drug Administration's genetically engineered foods policy: FDA's 1992 policy statement.

Science.gov (United States)

Pelletier, David L

2005-05-01

The US Food and Drug Administration's (FDA's) 1992 policy statement was developed in the context of critical gaps in scientific knowledge concerning the compositional effects of genetic transformation and severe limitations in methods for safety testing. FDA acknowledged that pleiotropy and insertional mutagenesis may cause unintended changes, but it was unknown whether this happens to a greater extent in genetic engineering compared with traditional breeding. Moreover, the agency was not able to identify methods by which producers could screen for unintended allergens and toxicants. Despite these uncertainties, FDA granted genetically engineered foods the presumption of GRAS (Generally Recognized As Safe) and recommended that producers use voluntary consultations before marketing them.

Scheduling with artificial neural networks

OpenAIRE

Gürgün, Burçkaan

1993-01-01

Ankara : Department of Industrial Engineering and The Institute of Engineering and Sciences of Bilkent Univ., 1993. Thesis (Master's) -- Bilkent University, 1993. Includes bibliographical references leaves 59-65. Artificial Neural Networks (ANNs) attempt to emulate the massively parallel and distributed processing of the human brain. They are being examined for a variety of problems that have been very difficult to solve. The objective of this thesis is to review the curren...

Naturally occurring minichromosome platforms in chromosome engineering: an overview.

Science.gov (United States)

Raimondi, Elena

2011-01-01

Artificially modified chromosome vectors are non-integrating gene delivery platforms that can shuttle very large DNA fragments in various recipient cells: theoretically, no size limit exists for the chromosome segments that an engineered minichromosome can accommodate. Therefore, genetically manipulated chromosomes might be potentially ideal vector systems, especially when the complexity of higher eukaryotic genes is concerned. This review focuses on those chromosome vectors generated using spontaneously occurring small markers as starting material. The definition and manipulation of the centromere domain is one of the main obstacles in chromosome engineering: naturally occurring minichromosomes, due to their inherent small size, were helpful in defining some aspects of centromere function. In addition, several distinctive features of small marker chromosomes, like their appearance as supernumerary elements in otherwise normal karyotypes, have been successfully exploited to use them as gene delivery vectors. The key technologies employed for minichromosome engineering are: size reduction, gene targeting, and vector delivery in various recipient cells. In spite of the significant advances that have been recently achieved in all these fields, several unsolved problems limit the potential of artificially modified chromosomes. Still, these vector systems have been exploited in a number of applications where the investigation of the controlled expression of large DNA segments is needed. A typical example is the analysis of genes whose expression strictly depends on the chromosomal environment in which they are positioned, where engineered chromosomes can be envisaged as epigenetically regulated expression systems. A novel and exciting advance concerns the use of engineered minichromosomes to study the organization and dynamics of local chromatin structures.

Research of performance on a spark ignition engine fueled by alcohol–gasoline blends using artificial neural networks

International Nuclear Information System (INIS)

Kapusuz, Murat; Ozcan, Hakan; Yamin, Jehad Ahmad

2015-01-01

In this paper, we investigate various alcohol–unleaded gasoline mixtures that can be used with no modifications in a spark-ignition engine. The mixtures consisted of 5%, 10% and 15% ethanol, methanol together and separately. Based on the recommendations of the Jordanian Petroleum Company (JoPetrol), total alcohol content should not exceed 15–20% owing to safety and ignition hazards. Optimizations for the use of alcohol were made for the maximum torque, maximum power and minimum specific fuel consumption values. For torque 0.9906, for brake power 0.997, and for brake specific fuel consumption 0.9312 regression values for tests have been obtained from models generated by the neural network. According to the modeling and optimizations, use of fuel mixture containing 11% methanol–1% ethanol for performance, and fuel mixture containing 2% methanol for BSFC were found to have better results. Moreover, the paper demonstrates that ANN (Artificial Neural Network) can be used successfully as an alternative type of modeling technique for internal combustion engines. - Highlights: • ANN model was developed and verified. • Effects of alcohol–gasoline blends on performance of a SI engine are fairly simulated. • Effects of alcohol–gasoline blends on performance of a SI engine are optimized.

Improving itaconic acid production through genetic engineering of an industrial Aspergillus terreus strain.

Science.gov (United States)

Huang, Xuenian; Lu, Xuefeng; Li, Yueming; Li, Xia; Li, Jian-Jun

2014-08-11

Itaconic acid, which has been declared to be one of the most promising and flexible building blocks, is currently used as monomer or co-monomer in the polymer industry, and produced commercially by Aspergillus terreus. However, the production level of itaconic acid hasn't been improved in the past 40 years, and mutagenesis is still the main strategy to improve itaconate productivity. The genetic engineering approach hasn't been applied in industrial A. terreus strains to increase itaconic acid production. In this study, the genes closely related to itaconic acid production, including cadA, mfsA, mttA, ATEG_09969, gpdA, ATEG_01954, acoA, mt-pfkA and citA, were identified and overexpressed in an industrial A. terreus strain respectively. Overexpression of the genes cadA (cis-aconitate decarboxylase) and mfsA (Major Facilitator Superfamily Transporter) enhanced the itaconate production level by 9.4% and 5.1% in shake flasks respectively. Overexpression of other genes showed varied effects on itaconate production. The titers of other organic acids were affected by the introduced genes to different extent. Itaconic acid production could be improved through genetic engineering of the industrially used A. terreus strain. We have identified some important genes such as cadA and mfsA, whose overexpression led to the increased itaconate productivity, and successfully developed a strategy to establish a highly efficient microbial cell factory for itaconate protuction. Our results will provide a guide for further enhancement of the itaconic acid production level through genetic engineering in future.

Pertussis toxins, other antigens become likely targets for genetic engineering

Energy Technology Data Exchange (ETDEWEB)

Marwick, C.

1990-11-14

Genetically engineered pertussis vaccines have yet to be fully tested clinically. But early human, animal, and in vitro studies indicate effectiveness in reducing toxic effects due to Bordetella pertussis. The licensed pertussis vaccines consists of inactivated whole cells of the organism. Although highly effective, they have been associated with neurologic complications. While the evidence continues to mount that these complications are extremely rare, if they occur at all, it has affected the public's acceptance of pertussis immunization.

[Preparation of nano-nacre artificial bone].

Science.gov (United States)

Chen, Jian-ting; Tang, Yong-zhi; Zhang, Jian-gang; Wang, Jian-jun; Xiao, Ying

2008-12-01

To assess the improvements in the properties of nano-nacre artificial bone prepared on the basis of nacre/polylactide acid composite artificial bone and its potential for clinical use. The compound of nano-scale nacre powder and poly-D, L-lactide acid (PDLLA) was used to prepare the cylindrical hollow artificial bone, whose properties including raw material powder scale, pore size, porosity and biomechanical characteristics were compared with another artificial bone made of micron-scale nacre powder and PDLLA. Scanning electron microscope showed that the average particle size of the nano-nacre powder was 50.4-/+12.4 nm, and the average pore size of the artificial bone prepared using nano-nacre powder was 215.7-/+77.5 microm, as compared with the particle size of the micron-scale nacre powder of 5.0-/+3.0 microm and the pore size of the resultant artificial bone of 205.1-/+72.0 microm. The porosities of nano-nacre artificial bone and the micron-nacre artificial bone were (65.4-/+2.9)% and (53.4-/+2.2)%, respectively, and the two artificial bones had comparable compressive strength and Young's modulus, but the flexural strength of the nano-nacre artificial bone was lower than that of the micro-nacre artificial bone. The nano-nacre artificial bone allows better biodegradability and possesses appropriate pore size, porosity and biomechanical properties for use as a promising material in bone tissue engineering.

Molecular Cloning Designer Simulator (MCDS: All-in-one molecular cloning and genetic engineering design, simulation and management software for complex synthetic biology and metabolic engineering projects

Directory of Open Access Journals (Sweden)

Zhenyu Shi

2016-12-01

Full Text Available Molecular Cloning Designer Simulator (MCDS is a powerful new all-in-one cloning and genetic engineering design, simulation and management software platform developed for complex synthetic biology and metabolic engineering projects. In addition to standard functions, it has a number of features that are either unique, or are not found in combination in any one software package: (1 it has a novel interactive flow-chart user interface for complex multi-step processes, allowing an integrated overview of the whole project; (2 it can perform a user-defined workflow of cloning steps in a single execution of the software; (3 it can handle multiple types of genetic recombineering, a technique that is rapidly replacing classical cloning for many applications; (4 it includes experimental information to conveniently guide wet lab work; and (5 it can store results and comments to allow the tracking and management of the whole project in one platform. MCDS is freely available from https://mcds.codeplex.com. Keywords: BioCAD, Genetic engineering software, Molecular cloning software, Synthetic biology, Workflow simulation and management

AN ARTIFICIAL NEURAL NETWORK EVALUATION OF TUBERCULOSIS USING GENETIC AND PHYSIOLOGICAL PATIENT DATA

International Nuclear Information System (INIS)

Griffin, William O.; Darsey, Jerry A.; Hanna, Josh; Razorilova, Svetlana; Kitaev, Mikhael; Alisherov, Avtandiil; Tarasenko, Olga

2010-01-01

When doctors see more cases of patients with tell-tale symptoms of a disease, it is hoped that they will be able to recognize an infection administer treatment appropriately, thereby speeding up recovery for sick patients. We hope that our studies can aid in the detection of tuberculosis by using a computer model called an artificial neural network. Our model looks at patients with and without tuberculosis (TB). The data that the neural network examined came from the following: patient' age, gender, place, of birth, blood type, Rhesus (Rh) factor, and genes of the human Leukocyte Antigens (HLA) system (9q34.1) present in the Major Histocompatibility Complex. With availability in genetic data and good research, we hope to give them an advantage in the detection of tuberculosis. We try to mimic the doctor's experience with a computer test, which will learn from patient data the factors that contribute to TB.

Crop Resources Ethic in Plant Genetic Engineering and Fortune Transfer Between Generations

Institute of Scientific and Technical Information of China (English)

WANG Xiaowei; DING Guangzhou; LIANG Xueqing

2006-01-01

The relation between human and crop resources belongs to the ethic of resources exploitation. The purposes of discussing the ethic of crop resources are to protect the ecology and safety of crops, to gain sustainable development, furthermore, to choose and form the production structure that is favorable to saving crop resources and protecting the ecology of crops. Plant genetic engineering is the technology of molecule breeding of rearrangement of inheritance materials at the level of molecule directionally, of improving plant properties and of breeding high quality and yield varieties of crops. The prominent effects of the technology on the crop ecological system are human subjective factors increasing as well as violating the nature and intensifying the conflict between human being and nature.Therefore, in plant genetic engineering, crop resources exploitation should follow certain ethic principles. Under the theory of ethics of natural resources, by the means of biologioal statistics, the author systematically analyzed the possible model of crop resources transfer between generations as well as the transfer mode of magnitude of real materials and magnitude of value.

The morality of socioscientific issues: Construal and resolution of genetic engineering dilemmas

Science.gov (United States)

Sadler, Troy D.; Zeidler, Dana L.

2004-01-01

The ability to negotiate and resolve socioscientific issues has been posited as integral components of scientific literacy. Although philosophers and science educators have argued that socioscientific issues inherently involve moral and ethical considerations, the ultimate arbiters of morality are individual decision-makers. This study explored the extent to which college students construe genetic engineering issues as moral problems. Twenty college students participated in interviews designed to elicit their ideas, reactions, and feelings regarding a series of gene therapy and cloning scenarios. Qualitative analyses revealed that moral considerations were significant influences on decision-making, indicating a tendency for students to construe genetic engineering issues as moral problems. Students engaged in moral reasoning based on utilitarian analyses of consequences as well as the application of principles. Issue construal was also influenced by affective features such as emotion and intuition. In addition to moral considerations, a series of other factors emerged as important dimensions of socioscientific decision-making. These factors included personal experiences, family biases, background knowledge, and the impact of popular culture. The implications for classroom science instruction and future research are discussed.

Genetic Engineering and the Amelioration of Genetic Defect

Science.gov (United States)

Lederberg, Joshua

1970-01-01

Discusses the claims for a brave new world of genetic manipulation" and concludes that if we could agree upon applying genetic (or any other effective) remedies to global problems we probably would need no rescourse to them. Suggests that effective methods of preventing genetic disease are prevention of mutations and detection and…

Artificial sensory organs: latest progress.

Science.gov (United States)

Nakamura, Tatsuo; Inada, Yuji; Shigeno, Keiji

2018-03-01

This study introduces the latest progress on the study of artificial sensory organs, with a special emphasis on the clinical results of artificial nerves and the concept of in situ tissue engineering. Peripheral nerves have a strong potential for regeneration. An artificial nerve uses this potential to recover a damaged peripheral nerve. The polyglycolic acid collagen tube (PGA-C tube) is a bio-absorbable tube stuffed with collagen of multi-chamber structure that consists of thin collagen films. The clinical application of the PGA-C tube began in 2002 in Japan. The number of PGA-C tubes used is now beyond 300, and satisfactory results have been reported on peripheral nerve repairs. This PGA-C tube is also effective for patients suffering from neuropathic pain.

Projecting potential adoption of genetically engineered freeze-tolerant Eucalyptus in the United States

Science.gov (United States)

David N. Wear; Ernest Dixon IV; Robert C. Abt; Navinder Singh

2015-01-01

Development of commercial Eucalyptus plantations has been limited in the United States because of the species’ sensitivity to freezing temperatures. Recently developed genetically engineered clones of a Eucalyptus hybrid, which confer freeze tolerance, could expand the range of commercial plantations. This study explores how...

Predictive modeling of performance of a helium charged Stirling engine using an artificial neural network

International Nuclear Information System (INIS)

Özgören, Yaşar Önder; Çetinkaya, Selim; Sarıdemir, Suat; Çiçek, Adem; Kara, Fuat

2013-01-01

Highlights: ► Max torque and power values were obtained at 3.5 bar Pch, 1273 K Hst and 1.4:1 r. ► According to ANOVA, the most influential parameter on power was Hst with 48.75%. ► According to ANOVA, the most influential parameter on torque was Hst with 41.78%. ► ANN (R 2 = 99.8% for T, P) was superior to regression method (R 2 = 92% for T, 81% for P). ► LM was the best learning algorithm in predicting both power and torque. - Abstract: In this study, an artificial neural network (ANN) model was developed to predict the torque and power of a beta-type Stirling engine using helium as the working fluid. The best results were obtained by 5-11-7-1 and 5-13-7-1 network architectures, with double hidden layers for the torque and power respectively. For these network architectures, the Levenberg–Marquardt (LM) learning algorithm was used. Engine performance values predicted with the developed ANN model were compared with the actual performance values measured experimentally, and substantially coinciding results were observed. After ANN training, correlation coefficients (R 2 ) of both engine performance values for testing and training data were very close to 1. Similarly, root-mean-square error (RMSE) and mean error percentage (MEP) values for the testing and training data were less than 0.02% and 3.5% respectively. These results showed that the ANN is an acceptable model for prediction of the torque and power of the beta-type Stirling engine

EGG transformation through the use of irradiated pollen: 'Poor man's genetic engineering'

International Nuclear Information System (INIS)

Pandey, K.K.

1981-01-01

There is no way that the 'fertilization cummutation hypothesis' can be considered to be an alternative to transformation. 'Poor man's genetic engineering' as a tool for plant breeders should be the development and application of the knowledge about growth-promothing genes which are thought to occur in self-compatible as well as in self-incompatible species. (AJ)

Fluxonium-Based Artificial Molecule with a Tunable Magnetic Moment

Science.gov (United States)

Kou, A.; Smith, W. C.; Vool, U.; Brierley, R. T.; Meier, H.; Frunzio, L.; Girvin, S. M.; Glazman, L. I.; Devoret, M. H.

2017-07-01

Engineered quantum systems allow us to observe phenomena that are not easily accessible naturally. The LEGO®-like nature of superconducting circuits makes them particularly suited for building and coupling artificial atoms. Here, we introduce an artificial molecule, composed of two strongly coupled fluxonium atoms, which possesses a tunable magnetic moment. Using an applied external flux, one can tune the molecule between two regimes: one in which the ground-excited state manifold has a magnetic dipole moment and one in which the ground-excited state manifold has only a magnetic quadrupole moment. By varying the applied external flux, we find the coherence of the molecule to be limited by local flux noise. The ability to engineer and control artificial molecules paves the way for building more complex circuits for quantum simulation and protected qubits.

Analysis and design of a genetic circuit for dynamic metabolic engineering.

Science.gov (United States)

Anesiadis, Nikolaos; Kobayashi, Hideki; Cluett, William R; Mahadevan, Radhakrishnan

2013-08-16

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Status and headway of the clinical application of artificial ligaments

Directory of Open Access Journals (Sweden)

Tianwu Chen

2015-01-01

Full Text Available The authors first reviewed the history of clinical application of artificial ligaments. Then, the status of clinical application of artificial ligaments was detailed. Some artificial ligaments possessed comparable efficacy to, and fewer postoperative complications than, allografts and autografts in ligament reconstruction, especially for the anterior cruciate ligament. At the end, the authors focused on the development of two types of artificial ligaments: polyethylene glycol terephthalate artificial ligaments and tissue-engineered ligaments. In conclusion, owing to the advancements in surgical techniques, materials processing, and weaving methods, clinical application of some artificial ligaments so far has demonstrated good outcomes and will become a trend in the future.

Artificial Promoters for Metabolic Optimization

DEFF Research Database (Denmark)

Jensen, Peter Ruhdal; Hammer, Karin

1998-01-01

In this article, we review some of the expression systems that are available for Metabolic Control Analysis and Metabolic Engineering, and examine their advantages and disadvantages in different contexts. In a recent approach, artificial promoters for modulating gene expression in micro-organisms...

Optimization of Aero Engine Acceleration Control in Combat State Based on Genetic Algorithms

Science.gov (United States)

Li, Jie; Fan, Ding; Sreeram, Victor

2012-03-01

In order to drastically exploit the potential of the aero engine and improve acceleration performance in the combat state, an on-line optimized controller based on genetic algorithms is designed for an aero engine. For testing the validity of the presented control method, detailed joint simulation tests of the designed controller and the aero engine model are performed in the whole flight envelope. Simulation test results show that the presented control algorithm has characteristics of rapid convergence speed, high efficiency and can fully exploit the acceleration performance potential of the aero engine. Compared with the former controller, the designed on-line optimized controller (DOOC) can improve the security of the acceleration process and greatly enhance the aero engine thrust in the whole range of the flight envelope, the thrust increases an average of 8.1% in the randomly selected working states. The plane which adopts DOOC can acquire better fighting advantage in the combat state.

Synthetic constructs in/for the environment: managing the interplay between natural and engineered Biology.

Science.gov (United States)

Schmidt, Markus; de Lorenzo, Víctor

2012-07-16

The plausible release of deeply engineered or even entirely synthetic/artificial microorganisms raises the issue of their intentional (e.g. bioremediation) or accidental interaction with the Environment. Containment systems designed in the 1980s-1990s for limiting the spread of genetically engineered bacteria and their recombinant traits are still applicable to contemporary Synthetic Biology constructs. Yet, the ease of DNA synthesis and the uncertainty on how non-natural properties and strains could interplay with the existing biological word poses yet again the challenge of designing safe and efficacious firewalls to curtail possible interactions. Such barriers may include xeno-nucleic acids (XNAs) instead of DNA as information-bearing molecules, rewriting the genetic code to make it non-understandable by the existing gene expression machineries, and/or making growth dependent on xenobiotic chemicals. Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

DECOMPOSTION OF GENETICALLY ENGINEERED TOBACCO UNDER FIELD CONDITIONS: PERSISTENCE OF THE PROTEINASE INHIBITOR I PRODUCT AND EFFECTS OF SOIL MICROBIAL RESPIRATION AND PROTOZOA, NEMATODE AND MICROARTHR

Science.gov (United States)

1. To evaluate the potential effects of genetically engineered (transgenic) plants on soil ecosystems, litterbags containing leaves of non-engineered (parental) and transgenic tobacco plants were buried in field plots. The transgenic tobacco plants were genetically engineered to ...

Toward a generalized and high-throughput enzyme screening system based on artificial genetic circuits.

Science.gov (United States)

Choi, Su-Lim; Rha, Eugene; Lee, Sang Jun; Kim, Haseong; Kwon, Kilkoang; Jeong, Young-Su; Rhee, Young Ha; Song, Jae Jun; Kim, Hak-Sung; Lee, Seung-Goo

2014-03-21

Large-scale screening of enzyme libraries is essential for the development of cost-effective biological processes, which will be indispensable for the production of sustainable biobased chemicals. Here, we introduce a genetic circuit termed the Genetic Enzyme Screening System that is highly useful for high-throughput enzyme screening from diverse microbial metagenomes. The circuit consists of two AND logics. The first AND logic, the two inputs of which are the target enzyme and its substrate, is responsible for the accumulation of a phenol compound in cell. Then, the phenol compound and its inducible transcription factor, whose activation turns on the expression of a reporter gene, interact in the other logic gate. We confirmed that an individual cell harboring this genetic circuit can present approximately a 100-fold higher cellular fluorescence than the negative control and can be easily quantified by flow cytometry depending on the amounts of phenolic derivatives. The high sensitivity of the genetic circuit enables the rapid discovery of novel enzymes from metagenomic libraries, even for genes that show marginal activities in a host system. The crucial feature of this approach is that this single system can be used to screen a variety of enzymes that produce a phenol compound from respective synthetic phenyl-substrates, including cellulase, lipase, alkaline phosphatase, tyrosine phenol-lyase, and methyl parathion hydrolase. Consequently, the highly sensitive and quantitative nature of this genetic circuit along with flow cytometry techniques could provide a widely applicable toolkit for discovering and engineering novel enzymes at a single cell level.

Degradation of phenanthrene and pyrene using genetically engineered dioxygenase producing Pseudomonas putida in soil

Directory of Open Access Journals (Sweden)

Mardani Gashtasb

2016-01-01

Full Text Available Bioremediation use to promote degradation and/or removal of contaminants into nonhazardous or less-hazardous substances from the environment using microbial metabolic ability. Pseudomonas spp. is one of saprotrophic soil bacterium and can be used for biodegradation of polycyclic aromatic hydrocarbons (PAHs but this activity in most species is weak. Phenanthrene and pyrene could associate with a risk of human cancer development in exposed individuals. The aim of the present study was application of genetically engineered P. putida that produce dioxygenase for degradation of phenanthrene and pyrene in spiked soil using high-performance liquid chromatography (HPLC method. The nahH gene that encoded catechol 2,3-dioxygenase (C23O was cloned into pUC18 and pUC18-nahH recombinant vector was generated and transformed into wild P. putida, successfully. The genetically modified and wild types of P. putida were inoculated in soil and pilot plan was prepared. Finally, degradation of phenanthrene and pyrene by this bacterium in spiked soil were evaluated using HPLC measurement technique. The results were showed elimination of these PAH compounds in spiked soil by engineered P. putida comparing to dishes containing natural soil with normal microbial flora and inoculated autoclaved soil by wild type of P. putida were statistically significant (p0.05 but it was few impact on this process (more than 2%. Additional and verification tests including catalase, oxidase and PCR on isolated bacteria from spiked soil were indicated that engineered P. putida was alive and functional as well as it can affect on phenanthrene and pyrene degradation via nahH gene producing. These findings indicated that genetically engineered P. putida generated in this work via producing C23O enzyme can useful and practical for biodegradation of phenanthrene and pyrene as well as petroleum compounds in polluted environments.

'HoneySweet' plum - a valuable genetically engineered fruit-tree cultivar and germplasm resource

Science.gov (United States)

‘HoneySweet’ is a plum variety developed through genetic engineering to be highly resistant to plum pox potyvirus (PPV), the causal agent of sharka disease, that threatens stone-fruit industries world-wide and most specifically, in Europe. Field testing for over 15 years in Europe has demonstrated ...

Signature pathway expression of xylose utilization in the genetically engineered industrial yeast Saccharomyces cerevisiae

Science.gov (United States)

Background: The limited xylose utilizing ability of native Saccharomyces cerevisiae has been a major obstacle for efficient cellulosic ethanol production from lignocellulosic materials. Haploid laboratory strains of S. cerevisiae are commonly used for genetic engineering to enable its xylose utiliza...

Efficient transformation and artificial miRNA gene silencing in Lemna minor.

Science.gov (United States)

Cantó-Pastor, A; Mollá-Morales, A; Ernst, E; Dahl, W; Zhai, J; Yan, Y; Meyers, B C; Shanklin, J; Martienssen, R

2015-01-01

Despite rapid doubling time, simple architecture and ease of metabolic labelling, a lack of genetic tools in the Lemnaceae (duckweed) has impeded the full implementation of this organism as a model for biological research. Here, we present technologies to facilitate high-throughput genetic studies in duckweed. We developed a fast and efficient method for producing Lemna minor stable transgenic fronds via Agrobacterium-mediated transformation and regeneration from tissue culture. Additionally, we engineered an artificial microRNA (amiRNA) gene silencing system. We identified a Lemna gibba endogenous miR166 precursor and used it as a backbone to produce amiRNAs. As a proof of concept we induced the silencing of CH42, a magnesium chelatase subunit, using our amiRNA platform. Expression of CH42 in transgenic L. minor fronds was significantly reduced, which resulted in reduction of chlorophyll pigmentation. The techniques presented here will enable tackling future challenges in the biology and biotechnology of Lemnaceae. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

A New Artificial Immune System Algorithm for Multiobjective Fuzzy Flow Shop Problems

Directory of Open Access Journals (Sweden)

Cengiz Kahraman

2009-12-01

Full Text Available In this paper a new artificial immune system (AIS algorithm is proposed to solve multi objective fuzzy flow shop scheduling problems. A new mutation operator is also described for this AIS. Fuzzy sets are used to model processing times and due dates. The objectives are to minimize the average tardiness and the number of tardy jobs. The developed new AIS algorithm is tested on real world data collected at an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed AIS is demonstrated by comparing it with genetic algorithms. Computational results demonstrate that the proposed AIS algorithm is more effective meta-heuristic for multi objective flow shop scheduling problems with fuzzy processing time and due date.

78 FR 13302 - Syngenta Biotechnology, Inc.; Determination of Nonregulated Status of Corn Genetically Engineered...

Science.gov (United States)

2013-02-27

...] Syngenta Biotechnology, Inc.; Determination of Nonregulated Status of Corn Genetically Engineered for... are advising the public of our determination that a corn line developed by the Syngenta Biotechnology... evaluation of data submitted by Syngenta Biotechnology, Inc., in its petition for a determination of...

Engineering control of bacterial cellulose production using a genetic toolkit and a new cellulose-producing strain

Science.gov (United States)

Florea, Michael; Hagemann, Henrik; Santosa, Gabriella; Micklem, Chris N.; Spencer-Milnes, Xenia; de Arroyo Garcia, Laura; Paschou, Despoina; Lazenbatt, Christopher; Kong, Deze; Chughtai, Haroon; Jensen, Kirsten; Freemont, Paul S.; Kitney, Richard; Reeve, Benjamin; Ellis, Tom

2016-01-01

Bacterial cellulose is a strong and ultrapure form of cellulose produced naturally by several species of the Acetobacteraceae. Its high strength, purity, and biocompatibility make it of great interest to materials science; however, precise control of its biosynthesis has remained a challenge for biotechnology. Here we isolate a strain of Komagataeibacter rhaeticus (K. rhaeticus iGEM) that can produce cellulose at high yields, grow in low-nitrogen conditions, and is highly resistant to toxic chemicals. We achieved external control over its bacterial cellulose production through development of a modular genetic toolkit that enables rational reprogramming of the cell. To further its use as an organism for biotechnology, we sequenced its genome and demonstrate genetic circuits that enable functionalization and patterning of heterologous gene expression within the cellulose matrix. This work lays the foundations for using genetic engineering to produce cellulose-based materials, with numerous applications in basic science, materials engineering, and biotechnology. PMID:27247386

Artificial lateral line with biomimetic neuromasts to emulate fish sensing

International Nuclear Information System (INIS)

Yang Yingchen; Chen Nannan; Tucker, Craig; Hu Huan; Liu Chang; Nguyen, Nam; Lockwood, Michael; Jones, Douglas L; Bleckmann, Horst

2010-01-01

Hydrodynamic imaging using the lateral line plays a critical role in fish behavior. To engineer such a biologically inspired sensing system, we developed an artificial lateral line using MEMS (microelectromechanical system) technology and explored its localization capability. Arrays of biomimetic neuromasts constituted an artificial lateral line wrapped around a cylinder. A beamforming algorithm further enabled the artificial lateral line to image real-world hydrodynamic events in a 3D domain. We demonstrate that the artificial lateral line system can accurately localize an artificial dipole source and a natural tail-flicking crayfish under various conditions. The artificial lateral line provides a new sense to man-made underwater vehicles and marine robots so that they can sense like fish.

De novo formed satellite DNA-based mammalian artificial chromosomes and their possible applications.

Science.gov (United States)

Katona, Robert L

2015-02-01

Mammalian artificial chromosomes (MACs) are non-integrating, autonomously replicating natural chromosome-based vectors that may carry a vast amount of genetic material, which in turn enable potentially prolonged, safe, and regulated therapeutic transgene expression and render MACs as attractive genetic vectors for "gene replacement" or for controlling differentiation pathways in target cells. Satellite-DNA-based artificial chromosomes (SATACs) can be made by induced de novo chromosome formation in cells of different mammalian and plant species. These artificially generated accessory chromosomes are composed of predictable DNA sequences, and they contain defined genetic information. SATACs have already passed a number of obstacles crucial to their further development as gene therapy vectors, including large-scale purification, transfer of purified artificial chromosomes into different cells and embryos, generation of transgenic animals and germline transmission with purified SATACs, and the tissue-specific expression of a therapeutic gene from an artificial chromosome in the milk of transgenic animals. SATACs could be used in cell therapy protocols. For these methods, the most versatile target cell would be one that was pluripotent and self-renewing to address multiple disease target cell types, thus making multilineage stem cells, such as adult derived early progenitor cells and embryonic stem cells, as attractive universal host cells.

Simulating Evolution of Drosophila melanogaster Ebony Mutants Using a Genetic Algorithm

DEFF Research Database (Denmark)

Helles, Glennie

2009-01-01

Genetic algorithms are generally quite easy to understand and work with, and they are a popular choice in many cases. One area in which genetic algorithms are widely and successfully used is artificial life where they are used to simulate evolution of artificial creatures. However, despite...... their suggestive name, simplicity and popularity in artificial life, they do not seem to have gained a footing within the field of population genetics to simulate evolution of real organisms --- possibly because genetic algorithms are based on a rather crude simplification of the evolutionary mechanisms known...

Phytosequestration: Carbon biosequestration by plants and the prospects of genetic engineering

Energy Technology Data Exchange (ETDEWEB)

Jansson, C.; Wullschleger, S.D.; Kalluri, U.C.; Tuskan, G.A.

2010-07-15

Photosynthetic assimilation of atmospheric carbon dioxide by land plants offers the underpinnings for terrestrial carbon (C) sequestration. A proportion of the C captured in plant biomass is partitioned to roots, where it enters the pools of soil organic C and soil inorganic C and can be sequestered for millennia. Bioenergy crops serve the dual role of providing biofuel that offsets fossil-fuel greenhouse gas (GHG) emissions and sequestering C in the soil through extensive root systems. Carbon captured in plant biomass can also contribute to C sequestration through the deliberate addition of biochar to soil, wood burial, or the use of durable plant products. Increasing our understanding of plant, microbial, and soil biology, and harnessing the benefits of traditional genetics and genetic engineering, will help us fully realize the GHG mitigation potential of phytosequestration.

[Assisted reproduction and artificial insemination and genetic manipulation in the Criminal Code of the Federal District, Mexico].

Science.gov (United States)

Brena Sesma, Ingrid

2004-01-01

The article that one presents has for purpose outline and comment on the recent modifications to the Penal Code for the Federal District of México which establish, for the first time, crimes related to the artificial procreation and to the genetic manipulation. Also one refers to the interaction of the new legal texts with the sanitary legislation of the country. Since it will be stated in some cases they present confrontations between the penal and the sanitary reglamentation and some points related to the legality or unlawfulness of a conduct that stayed without the enough development. These lacks will complicate the application of the new rules of the Penal Code of the Federal District.

Genetically engineered yeast

DEFF Research Database (Denmark)

2014-01-01

A genetically modified Saccharomyces cerevisiae comprising an active fermentation pathway producing 3-HP expresses an exogenous gene expressing the aminotransferase YhxA from Bacillus cereus AH1272 catalysing a transamination reaction between beta-alanine and pyruvate to produce malonate semialde......A genetically modified Saccharomyces cerevisiae comprising an active fermentation pathway producing 3-HP expresses an exogenous gene expressing the aminotransferase YhxA from Bacillus cereus AH1272 catalysing a transamination reaction between beta-alanine and pyruvate to produce malonate...... semialdehyde. The yeast may also express a 3-hydroxyisobutyrate dehydrogenase (HIBADH) and a 3-hydroxypropanoate dehydrogenase (3-HPDH) and aspartate 1-decarboxylase. Additionally the yeast may express pyruvate carboxylase and aspartate aminotransferase....

Breeding technique of Anastrepha fraterculus (Wied.) for genetic studies

International Nuclear Information System (INIS)

Manso, F.

1999-01-01

Various samples of Anastrepha fraterculus from different areas in Argentina were obtained to develop artificial breeding in the laboratory. Based on a modification of Salles's method, an improved artificial rearing of the species was developed with satisfactory results for genetic analysis. The advances made will contribute towards the search for genetic mechanisms for control. (author)

Development of enzymes and enzyme systems by genetic engineering to convert biomass to sugars

Science.gov (United States)

TITLE Development of Enzymes and Enzyme Systems by Genetic Engineering to Convert Biomass to Sugars ABSTRACT Plant cellulosic material is one of the most viable renewable resources for the world’s fuel and chemical feedstock needs. Currently ethanol derived from corn starch is the most common li...

Artificial Lipid Membranes: Past, Present, and Future.

Science.gov (United States)

Siontorou, Christina G; Nikoleli, Georgia-Paraskevi; Nikolelis, Dimitrios P; Karapetis, Stefanos K

2017-07-26

The multifaceted role of biological membranes prompted early the development of artificial lipid-based models with a primary view of reconstituting the natural functions in vitro so as to study and exploit chemoreception for sensor engineering. Over the years, a fair amount of knowledge on the artificial lipid membranes, as both, suspended or supported lipid films and liposomes, has been disseminated and has helped to diversify and expand initial scopes. Artificial lipid membranes can be constructed by several methods, stabilized by various means, functionalized in a variety of ways, experimented upon intensively, and broadly utilized in sensor development, drug testing, drug discovery or as molecular tools and research probes for elucidating the mechanics and the mechanisms of biological membranes. This paper reviews the state-of-the-art, discusses the diversity of applications, and presents future perspectives. The newly-introduced field of artificial cells further broadens the applicability of artificial membranes in studying the evolution of life.

The deconvolution of complex spectra by artificial immune system

Science.gov (United States)

Galiakhmetova, D. I.; Sibgatullin, M. E.; Galimullin, D. Z.; Kamalova, D. I.

2017-11-01

An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization.

Using word spotting to evaluate ROILA: a speech recognition friendly artificial language

NARCIS (Netherlands)

Mubin, O.; Bartneck, C.; Feijs, L.M.G.

2010-01-01

In our research we argue for the benefits that an artificial language could provide to improve the accuracy of speech recognition. We briefly present the design and implementation of a vocabulary of our intended artificial language (ROILA), the latter by means of a genetic algorithm that attempted

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

OpenAIRE

Jerzy Balicki

2015-01-01

The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to p...

Desktop Genetics

OpenAIRE

Hough, Soren H; Ajetunmobi, Ayokunmi; Brody, Leigh; Humphryes-Kirilov, Neil; Perello, Edward

2016-01-01

Desktop Genetics is a bioinformatics company building a gene-editing platform for personalized medicine. The company works with scientists around the world to design and execute state-of-the-art clustered regularly interspaced short palindromic repeats (CRISPR) experiments. Desktop Genetics feeds the lessons learned about experimental intent, single-guide RNA design and data from international genomics projects into a novel CRISPR artificial intelligence system. We believe that machine learni...

Ethics of Reproductive Engineering

Science.gov (United States)

Buuck, R. John

1977-01-01

Artificial insemination, in vitro fertilization, artificial placentas, and cloning are examined from a ethical viewpoint. The moral, social, and legal implications of reproductive engineering are considered important to biology as well as medicine. The author suggests that these ethical issues should be included in the biology curriculum and lists…

In Defense of Artificial Replacement.

Science.gov (United States)

Shiller, Derek

2017-06-01

If it is within our power to provide a significantly better world for future generations at a comparatively small cost to ourselves, we have a strong moral reason to do so. One way of providing a significantly better world may involve replacing our species with something better. It is plausible that in the not-too-distant future, we will be able to create artificially intelligent creatures with whatever physical and psychological traits we choose. Granted this assumption, it is argued that we should engineer our extinction so that our planet's resources can be devoted to making artificial creatures with better lives. © 2017 John Wiley & Sons Ltd.

An improved ARS2-derived nuclear reporter enhances the efficiency and ease of genetic engineering in Chlamydomonas

DEFF Research Database (Denmark)

Specht, Elizabeth A; Nour-Eldin, Hussam Hassan; Hoang, Kevin T D

2015-01-01

The model alga Chlamydomonas reinhardtii has been used to pioneer genetic engineering techniques for high-value protein and biofuel production from algae. To date, most studies of transgenic Chlamydomonas have utilized the chloroplast genome due to its ease of engineering, with a sizeable suite o...

Genetic engineering of plant volatile terpenoids: effects on a herbivore, a predator and a parasitoid

NARCIS (Netherlands)

Kos, M.; Houshyani, B.; Overeem, A.J.; Bouwmeester, H.J.; Weldegergis, B.T.; van Loon, J.J.A.; Dicke, M.; Vet, L.E.M.

2013-01-01

BACKGROUND: Most insect-resistant transgenic crops employ toxins to control pests. A novel approach is to enhance the effectiveness of natural enemies by genetic engineering of the biosynthesis of volatile organic compounds (VOCs). Before the commercialisation of such transgenic plants can be

Recent Progress in Micro/Nanoreactors toward the Creation of Artificial Organelles

DEFF Research Database (Denmark)

Gallardo, Maria Godoy; York-Durán, María José; Hosta-Rigau, Leticia

2018-01-01

Artificial organelles created from a bottom up approach are a new type of engineered materials, which are not designed to be living but, instead, to mimic some specific functions inside cells. By doing so, artificial organelles are expected to become a powerful tool in biomedicine. They can act a...

Genetically engineered plants in the product development pipeline in India.

Science.gov (United States)

Warrier, Ranjini; Pande, Hem

2016-01-02

In order to proactively identify emerging issues that may impact the risk assessment and risk management functions of the Indian biosafety regulatory system, the Ministry of Environment, Forests and Climate Change sought to understand the nature and diversity of genetically engineered crops that may move to product commercialization within the next 10 y. This paper describes the findings from a questionnaire designed to solicit information about public and private sector research and development (R&D) activities in plant biotechnology. It is the first comprehensive overview of the R&D pipeline for GE crops in India.

A Constrained Genetic Algorithm with Adaptively Defined Fitness Function in MRS Quantification

Science.gov (United States)

Papakostas, G. A.; Karras, D. A.; Mertzios, B. G.; Graveron-Demilly, D.; van Ormondt, D.

MRS Signal quantification is a rather involved procedure and has attracted the interest of the medical engineering community, regarding the development of computationally efficient methodologies. Significant contributions based on Computational Intelligence tools, such as Neural Networks (NNs), demonstrated a good performance but not without drawbacks already discussed by the authors. On the other hand preliminary application of Genetic Algorithms (GA) has already been reported in the literature by the authors regarding the peak detection problem encountered in MRS quantification using the Voigt line shape model. This paper investigates a novel constrained genetic algorithm involving a generic and adaptively defined fitness function which extends the simple genetic algorithm methodology in case of noisy signals. The applicability of this new algorithm is scrutinized through experimentation in artificial MRS signals interleaved with noise, regarding its signal fitting capabilities. Although extensive experiments with real world MRS signals are necessary, the herein shown performance illustrates the method's potential to be established as a generic MRS metabolites quantification procedure.

Directed evolution combined with synthetic biology strategies expedite semi-rational engineering of genes and genomes.

Science.gov (United States)

Kang, Zhen; Zhang, Junli; Jin, Peng; Yang, Sen

2015-01-01

Owing to our limited understanding of the relationship between sequence and function and the interaction between intracellular pathways and regulatory systems, the rational design of enzyme-coding genes and de novo assembly of a brand-new artificial genome for a desired functionality or phenotype are difficult to achieve. As an alternative approach, directed evolution has been widely used to engineer genomes and enzyme-coding genes. In particular, significant developments toward DNA synthesis, DNA assembly (in vitro or in vivo), recombination-mediated genetic engineering, and high-throughput screening techniques in the field of synthetic biology have been matured and widely adopted, enabling rapid semi-rational genome engineering to generate variants with desired properties. In this commentary, these novel tools and their corresponding applications in the directed evolution of genomes and enzymes are discussed. Moreover, the strategies for genome engineering and rapid in vitro enzyme evolution are also proposed.

Perturbing engine performance measurements to determine optimal engine control settings

Science.gov (United States)

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2014-12-30

Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initial value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.

Stakeholder views on the creation and use of genetically-engineered animals in research.

Science.gov (United States)

Ormandy, Elisabeth H

2016-05-01

This interview-based study examined the diversity of views relating to the creation and use of genetically-engineered (GE) animals in biomedical science. Twenty Canadian participants (eight researchers, five research technicians and seven members of the public) took part in the interviews, in which four main themes were discussed: a) how participants felt about the genetic engineering of animals as a practice; b) governance of the creation and use of GE animals in research, and whether current guidelines are sufficient; c) the Three Rs (Replacement, Reduction, Refinement) and how they are applied during the creation and use of GE animals in research; and d) whether public opinion should play a greater role in the creation and use of GE animals. Most of the participants felt that the creation and use of GE animals for biomedical research purposes (as opposed to food purposes) is acceptable, provided that tangible human health benefits are gained. However, obstacles to Three Rs implementation were identified, and the participants agreed that more effort should be placed on engaging the public on the use of GE animals in research. 2016 FRAME.

Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

Science.gov (United States)

Taheri, Mahboobeh; Mohebbi, Ali

2008-08-30

In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.

Cotton genotypes selection through artificial neural networks.

Science.gov (United States)

Júnior, E G Silva; Cardoso, D B O; Reis, M C; Nascimento, A F O; Bortolin, D I; Martins, M R; Sousa, L B

2017-09-27

Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar's development. Differently from these analyses, the computational intelligence approach has been little explored in genetic improvement of cotton. Thus, this study was carried out with the objective of presenting the use of artificial neural networks as auxiliary tools in the improvement of the cotton to improve fiber quality. To demonstrate the applicability of this approach, this research was carried out using the evaluation data of 40 genotypes. In order to classify the genotypes for fiber quality, the artificial neural networks were trained with replicate data of 20 genotypes of cotton evaluated in the harvests of 2013/14 and 2014/15, regarding fiber length, uniformity of length, fiber strength, micronaire index, elongation, short fiber index, maturity index, reflectance degree, and fiber quality index. This quality index was estimated by means of a weighted average on the determined score (1 to 5) of each characteristic of the HVI evaluated, according to its industry standards. The artificial neural networks presented a high capacity of correct classification of the 20 selected genotypes based on the fiber quality index, so that when using fiber length associated with the short fiber index, fiber maturation, and micronaire index, the artificial neural networks presented better results than using only fiber length and previous associations. It was also observed that to submit data of means of new genotypes to the neural networks trained with data of repetition, provides better results of classification of the genotypes. When observing the results obtained in the present study, it was verified that the artificial neural networks present great potential to be used in the different stages of a genetic improvement program of the cotton, aiming at the improvement of the fiber quality of the future cultivars.

Application of temporal LNC logic in artificial intelligence

Science.gov (United States)

Adamek, Marek; Mulawka, Jan

2016-09-01

This paper presents the temporal logic inference engine developed in our university. It is an attempt to demonstrate implementation and practical application of temporal logic LNC developed in Cardinal Stefan Wyszynski University in Warsaw.1 The paper describes the fundamentals of LNC logic, architecture and implementation of inference engine. The practical application is shown by providing the solution for popular in Artificial Intelligence problem of Missionaries and Cannibals in terms of LNC logic. Both problem formulation and inference engine are described in details.

Genetic Engineering of Energy Crops to Reduce Recalcitrance and Enhance Biomass Digestibility

Directory of Open Access Journals (Sweden)

Monika Yadav

2018-06-01

Full Text Available Bioenergy, biofuels, and a range of valuable chemicals may be extracted from the abundantly available lignocellulosic biomass. To reduce the recalcitrance imposed by the complex cell wall structure, genetic engineering has been proposed over the years as a suitable solution to modify the genes, thereby, controlling the overall phenotypic expression. The present review provides a brief description of the plant cell wall structure and its compositional array i.e., lignin, cellulose, hemicellulose, wall proteins, and pectin, along with their effect on biomass digestibility. Also, this review discusses the potential to increase biomass by gene modification. Furthermore, the review highlights the potential genes associated with the regulation of cell wall structure, which can be targeted for achieving energy crops with desired phenotypes. These genetic approaches provide a robust and assured method to bring about the desired modifications in cell wall structure, composition, and characteristics. Ultimately, these genetic modifications pave the way for achieving enhanced biomass yield and enzymatic digestibility of energy crops, which is crucial for maximizing the outcomes of energy crop breeding and biorefinery applications.

European accomplishments in regulation of the family status of the child conceived by artificial reproduction technologies

Directory of Open Access Journals (Sweden)

Kovaček-Stanić Gordana

2015-01-01

Full Text Available In this paper, the author analyzes family status of the child conceived by artificial reproduction technologies using the following treatments: homologues artificial insemination, heterologus artificial insemination (artificial insemination by donor, ovum donation, embryo donation and surrogate motherhood. One specific situation of homologues artificial insemination is posthumous insemination, insemination after the death of the husband/partner. This procedure is allowed in, for instance, United Kingdom, but not allowed in France, Switzerland, and Italy. Considering genetics elements in this situation there is no doubt on fatherhood - father is a man whose sperm is used for insemination, regardless of the fact if frozen sperm or frozen embryo is used in the procedure. Nevertheless, until 2008 in United Kingdom, the husband/partner was not considered as legal father, because of the fact that the child was born after his death. Heterologous artificial insemination could be used in three different situations. First, when subjects are spouses or unmarried partners of different sexes. Second, when subjects are spouses or unmarried partners of the same sex and the third if a single woman is an only subject. Most recent procedure is the one in which subjects are spouses or unmarried partners of the same sex, specifically two women. This procedure is allowed in the United Kingdom and Sweden. In these legislatures, there is a rule that the woman who delivers the child is legal mother, and her spouse/partner is a second parent of the child. The most recent procedure of egg donation is a donation of only a part of an egg, mitochondrial DNA. In this case, there are in fact three genetic parents of the child: two genetic mothers and a father. Legally, the child has one mother (the woman who delivers a child and a father. One of potential outcomes of the recent research is the ability to create human embryo without any male genetic contribution - by

Artificial intelligence as a means to moral enhancement

OpenAIRE

Klincewicz, Michał

2016-01-01

This paper critically assesses the possibility of moral enhancement with ambient intelligence technologies and artificial intelligence presented in Savulescu and Maslen (2015). The main problem with their proposal is that it is not robust enough to play a normative role in users’ behavior. A more promising approach, and the one presented in the paper, relies on an artificial moral reasoning engine, which is designed to present its users with moral arguments grounded in first-order normative t...

Artificial organic networks artificial intelligence based on carbon networks

CERN Document Server

Ponce-Espinosa, Hiram; Molina, Arturo

2014-01-01

This monograph describes the synthesis and use of biologically-inspired artificial hydrocarbon networks (AHNs) for approximation models associated with machine learning and a novel computational algorithm with which to exploit them. The reader is first introduced to various kinds of algorithms designed to deal with approximation problems and then, via some conventional ideas of organic chemistry, to the creation and characterization of artificial organic networks and AHNs in particular. The advantages of using organic networks are discussed with the rules to be followed to adapt the network to its objectives. Graph theory is used as the basis of the necessary formalism. Simulated and experimental examples of the use of fuzzy logic and genetic algorithms with organic neural networks are presented and a number of modeling problems suitable for treatment by AHNs are described: ·        approximation; ·        inference; ·        clustering; ·        control; ·        class...

Mode Choice Modeling Using Artificial Neural Networks

OpenAIRE

Edara, Praveen Kumar

2003-01-01

Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...

Site-specific selfish genes as tools for the control and genetic engineering of natural populations.

Science.gov (United States)

Burt, Austin

2003-05-07

Site-specific selfish genes exploit host functions to copy themselves into a defined target DNA sequence, and include homing endonuclease genes, group II introns and some LINE-like transposable elements. If such genes can be engineered to target new host sequences, then they can be used to manipulate natural populations, even if the number of individuals released is a small fraction of the entire population. For example, a genetic load sufficient to eradicate a population can be imposed in fewer than 20 generations, if the target is an essential host gene, the knockout is recessive and the selfish gene has an appropriate promoter. There will be selection for resistance, but several strategies are available for reducing the likelihood of it evolving. These genes may also be used to genetically engineer natural populations, by means of population-wide gene knockouts, gene replacements and genetic transformations. By targeting sex-linked loci just prior to meiosis one may skew the population sex ratio, and by changing the promoter one may limit the spread of the gene to neighbouring populations. The proposed constructs are evolutionarily stable in the face of the mutations most likely to arise during their spread, and strategies are also available for reversing the manipulations.

SOME PARADIGMS OF ARTIFICIAL INTELLIGENCE IN FINANCIAL COMPUTER SYSTEMS

Directory of Open Access Journals (Sweden)

Jerzy Balicki

2015-12-01

Full Text Available The article discusses some paradigms of artificial intelligence in the context of their applications in computer financial systems. The proposed approach has a significant po-tential to increase the competitiveness of enterprises, including financial institutions. However, it requires the effective use of supercomputers, grids and cloud computing. A reference is made to the computing environment for Bitcoin. In addition, we characterized genetic programming and artificial neural networks to prepare investment strategies on the stock exchange market.

Enhancing Artificial Bee Colony Algorithm with Self-Adaptive Searching Strategy and Artificial Immune Network Operators for Global Optimization

Directory of Open Access Journals (Sweden)

Tinggui Chen

2014-01-01

Full Text Available Artificial bee colony (ABC algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA, artificial colony optimization (ACO, and particle swarm optimization (PSO. However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.

Could a functional artificial skeletal muscle be useful in muscle wasting?

Science.gov (United States)

Fuoco, Claudia; Cannata, Stefano; Gargioli, Cesare

2016-05-01

Regardless of the underlying cause, skeletal muscle wasting is detrimental for a person's life quality, leading to impaired strength, locomotion, and physiological activity. Here, we propose a series of studies presenting tissue engineering-based approaches to reconstruct artificial muscle in vitro and in vivo. Skeletal muscle tissue engineering is attracting more and more attention from scientists, clinicians, patients, and media, thanks to the promising results obtained in the last decade with animal models of muscle wasting. The use of novel and refined biomimetic scaffolds mimicking three-dimensional muscle environment, thus supporting cell survival and differentiation, in combination with well characterized myogenic stem/progenitor cells, revealed the noteworthy potential of these technologies for creating artificial skeletal muscle tissue. In vitro, the production of three-dimensional muscle structures offer the possibility to generate a drug-screening platform for patient-specific pharmacological treatment, opening new frontiers in the development of new compounds with specific therapeutic actions. In vivo, three-dimensional artificial muscle biomimetic constructs offer the possibility to replace, in part or entirely, wasted muscle by means of straight reconstruction and/or by enhancing endogenous regeneration. Reports of tissue engineering approaches for artificial muscle building appeared in large numbers in the specialized press lately, advocating the suitability of this technology for human application upon scaling up and a near future applicability for medical care of muscle wasting. http://links.lww.com/COCN/A9

The true meaning of 'exotic species' as a model for genetically engineered organisms.

Science.gov (United States)

Regal, P J

1993-03-15

The exotic or non-indigenous species model for deliberately introduced genetically engineered organisms (GEOs) has often been misunderstood or misrepresented. Yet proper comparisons of of ecologically competent GEOs to the patterns of adaptation of introduced species have been highly useful among scientists in attempting to determine how to apply biological theory to specific GEO risk issues, and in attempting to define the probabilities and scale of ecological risks with GEOs. In truth, the model predicts that most projects may be environmentally safe, but a significant minority may be very risky. The model includes a history of institutional follies that also should remind workers of the danger of oversimplifying biological issues, and warn against repeating the sorts of professional misjudgements that have too often been made in introducing organisms to new settings. We once expected that the non-indigenous species model would be refined by more analysis of species eruptions, ecological genetics, and the biology of select GEOs themselves, as outlined. But there has been political resistance to the effective regulation of GEOs, and a bureaucratic tendency to focus research agendas on narrow data collection. Thus there has been too little promotion by responsible agencies of studies to provide the broad conceptual base for truly science-based regulation. In its presently unrefined state, the non-indigenous species comparison would overestimate the risks of GEOs if it were (mis)applied to genetically disrupted, ecologically crippled GEOs, but in some cases of wild-type organisms with novel engineered traits, it could greatly underestimate the risks. Further analysis is urgently needed.

Evolution under domestication: ongoing artificial selection and divergence of wild and managed Stenocereus pruinosus (Cactaceae) populations in the Tehuacan Valley, Mexico.

Science.gov (United States)

Parra, Fabiola; Casas, Alejandro; Peñaloza-Ramírez, Juan Manuel; Cortés-Palomec, Aurea C; Rocha-Ramírez, Víctor; González-Rodríguez, Antonio

2010-09-01

The Tehuacán Valley in Mexico is a principal area of plant domestication in Mesoamerica. There, artificial selection is currently practised on nearly 120 native plant species with coexisting wild, silvicultural and cultivated populations, providing an excellent setting for studying ongoing mechanisms of evolution under domestication. One of these species is the columnar cactus Stenocereus pruinosus, in which we studied how artificial selection is operating through traditional management and whether it has determined morphological and genetic divergence between wild and managed populations. Semi-structured interviews were conducted with 83 households of three villages to investigate motives and mechanisms of artificial selection. Management effects were studied by comparing variation patterns of 14 morphological characters and population genetics (four microsatellite loci) of 264 plants from nine wild, silvicultural and cultivated populations. Variation in fruit characters was recognized by most people, and was the principal target of artificial selection directed to favour larger and sweeter fruits with thinner or thicker peel, fewer spines and pulp colours other than red. Artificial selection operates in agroforestry systems favouring abundance (through not felling plants and planting branches) of the preferred phenotypes, and acts more intensely in household gardens. Significant morphological divergence between wild and managed populations was observed in fruit characters and plant vigour. On average, genetic diversity in silvicultural populations (H(E) = 0.743) was higher than in wild (H(E) = 0.726) and cultivated (H(E) = 0.700) populations. Most of the genetic variation (90.58 %) occurred within populations. High gene flow (Nm(FST) > 2) was identified among almost all populations studied, but was slightly limited by mountains among wild populations, and by artificial selection among wild and managed populations. Traditional management of S. pruinosus involves

Satellite DNA-based artificial chromosomes for use in gene therapy.

Science.gov (United States)

Hadlaczky, G

2001-04-01

Satellite DNA-based artificial chromosomes (SATACs) can be made by induced de novo chromosome formation in cells of different mammalian species. These artificially generated accessory chromosomes are composed of predictable DNA sequences and they contain defined genetic information. Prototype human SATACs have been successfully constructed in different cell types from 'neutral' endogenous DNA sequences from the short arm of the human chromosome 15. SATACs have already passed a number of hurdles crucial to their further development as gene therapy vectors, including: large-scale purification; transfer of purified artificial chromosomes into different cells and embryos; generation of transgenic animals and germline transmission with purified SATACs; and the tissue-specific expression of a therapeutic gene from an artificial chromosome in the milk of transgenic animals.

Genetic engineering of microbial pesticides

Science.gov (United States)

Bruce C. Carlton

1985-01-01

Recent advances in genetics and molecular biology make possible the cloning and genetic manipulation of genes for insecticidal activities from natural insect pathogens. Using recombinant DNA methods and site-directed mutagenesis of specific gene regions, production of new and improved biorationals should be possible.

A CAL Program to Teach the Basic Principles of Genetic Engineering--A Change from the Traditional Approach.

Science.gov (United States)

Dewhurst, D. G.; And Others

1989-01-01

An interactive computer-assisted learning program written for the BBC microcomputer to teach the basic principles of genetic engineering is described. Discussed are the hardware requirements software, use of the program, and assessment. (Author/CW)

Closed-Loop Artificial Pancreas Systems: Engineering the Algorithms

OpenAIRE

Doyle, Francis J.; Huyett, Lauren M.; Lee, Joon Bok; Zisser, Howard C.; Dassau, Eyal

2014-01-01

In this two-part Bench to Clinic narrative, recent advances in both the preclinical and clinical aspects of artificial pancreas (AP) development are described. In the preceding Bench narrative, Kudva and colleagues provide an in-depth understanding of the modified glucoregulatory physiology of type 1 diabetes that will help refine future AP algorithms. In the Clinic narrative presented here, we compare and evaluate AP technology to gain further momentum toward outpatient trials and eventual a...

Genetic engineering and therapy for inherited and acquired cardiomyopathies.

Science.gov (United States)

Day, Sharlene; Davis, Jennifer; Westfall, Margaret; Metzger, Joseph

2006-10-01

The cardiac myofilaments consist of a highly ordered assembly of proteins that collectively generate force in a calcium-dependent manner. Defects in myofilament function and its regulation have been implicated in various forms of acquired and inherited human heart disease. For example, during cardiac ischemia, cardiac myocyte contractile performance is dramatically downregulated due in part to a reduced sensitivity of the myofilaments to calcium under acidic pH conditions. Over the last several years, the thin filament regulatory protein, troponin I, has been identified as an important mediator of this response. Mutations in troponin I and other sarcomere genes are also linked to several distinct inherited cardiomyopathic phenotypes, including hypertrophic, dilated, and restrictive cardiomyopathies. With the cardiac sarcomere emerging as a central player for such a diverse array of human heart diseases, genetic-based strategies that target the myofilament will likely have broad therapeutic potential. The development of safe vector systems for efficient gene delivery will be a critical hurdle to overcome before these types of therapies can be successfully applied. Nonetheless, studies focusing on the principles of acute genetic engineering of the sarcomere hold value as they lay the essential foundation on which to build potential gene-based therapies for heart disease.

Loading pattern optimization of PWR reactors using Artificial Bee Colony

International Nuclear Information System (INIS)

Safarzadeh, O.; Zolfaghari, A.; Norouzi, A.; Minuchehr, H.

2011-01-01

Highlights: → ABC algorithm is comparable to the canonical GA algorithm and PSO. → The performance of ABC shows that the algorithm is quiet promising. → The final band width of search fitness values by ABC is narrow. → The ABC algorithm is relatively easy to implement. - Abstract: In this paper a core reloading technique using Artificial Bee Colony algorithm, ABC, is presented in the context of finding an optimal configuration of fuel assemblies. The proposed method can be used for in-core fuel management optimization problems in pressurized water reactors. To evaluate the proposed technique, the power flattening of a VVER-1000 core is considered as an objective function although other variables such as K eff , power peaking factor, burn up and cycle length can also be taken into account. The proposed optimization method is applied to a core design optimization problem previously solved with Genetic and Particle Swarm Intelligence Algorithm. The results, convergence rate and reliability of the new method are quite promising and show that the ABC algorithm performs very well and is comparable to the canonical Genetic Algorithm and Particle Swarm Intelligence, hence demonstrating its potential for other optimization applications in nuclear engineering field as, for instance, the cascade problems.

Bottom-up synthetic biology: modular design for making artificial platelets

Science.gov (United States)

Majumder, Sagardip; Liu, Allen P.

2018-01-01

Engineering artificial cells to mimic one or multiple fundamental cell biological functions is an emerging area of synthetic biology. Reconstituting functional modules from biological components in vitro is a challenging yet an important essence of bottom-up synthetic biology. Here we describe the concept of building artificial platelets using bottom-up synthetic biology and the four functional modules that together could enable such an ambitious effort.

Teaching methodology for modeling reference evapotranspiration with artificial neural networks

OpenAIRE

Martí, Pau; Pulido Calvo, Inmaculada; Gutiérrez Estrada, Juan Carlos

2015-01-01

[EN] Artificial neural networks are a robust alternative to conventional models for estimating different targets in irrigation engineering, among others, reference evapotranspiration, a key variable for estimating crop water requirements. This paper presents a didactic methodology for introducing students in the application of artificial neural networks for reference evapotranspiration estimation using MatLab c . Apart from learning a specific application of this software wi...

Multi-objective optimal design of magnetorheological engine mount based on an improved non-dominated sorting genetic algorithm

Science.gov (United States)

Zheng, Ling; Duan, Xuwei; Deng, Zhaoxue; Li, Yinong

2014-03-01

A novel flow-mode magneto-rheological (MR) engine mount integrated a diaphragm de-coupler and the spoiler plate is designed and developed to isolate engine and the transmission from the chassis in a wide frequency range and overcome the stiffness in high frequency. A lumped parameter model of the MR engine mount in single degree of freedom system is further developed based on bond graph method to predict the performance of the MR engine mount accurately. The optimization mathematical model is established to minimize the total of force transmissibility over several frequency ranges addressed. In this mathematical model, the lumped parameters are considered as design variables. The maximum of force transmissibility and the corresponding frequency in low frequency range as well as individual lumped parameter are limited as constraints. The multiple interval sensitivity analysis method is developed to select the optimized variables and improve the efficiency of optimization process. An improved non-dominated sorting genetic algorithm (NSGA-II) is used to solve the multi-objective optimization problem. The synthesized distance between the individual in Pareto set and the individual in possible set in engineering is defined and calculated. A set of real design parameters is thus obtained by the internal relationship between the optimal lumped parameters and practical design parameters for the MR engine mount. The program flowchart for the improved non-dominated sorting genetic algorithm (NSGA-II) is given. The obtained results demonstrate the effectiveness of the proposed optimization approach in minimizing the total of force transmissibility over several frequency ranges addressed.

A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

Science.gov (United States)

1987-01-01

Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

Artificial Atoms: from Quantum Physics to Applications

International Nuclear Information System (INIS)

2014-01-01

The primary objective of this workshop is to survey the most recent advances of technologies enabling single atom- and artificial atom-based devices. These include the assembly of artificial molecular structures with magnetic dipole and optical interactions between engineered atoms embedded in solid-state lattices. The ability to control single atoms in diamond or similar solids under ambient operating conditions opens new perspectives for technologies based on nanoelectronics and nanophotonics. The scope of the workshop is extended towards the physics of strong coupling between atoms and radiation field modes. Beyond the traditional atom-cavity systems, artificial dipoles coupled to microwave radiation in circuit quantum electrodynamics is considered. All these technologies mutually influence each other in developing novel devices for sensing at the quantum level and for quantum information processing.

Development of salt tolerant plants through genetic engineering (abstract)

International Nuclear Information System (INIS)

Mukhtar, Z.; Khan, S.A.; Zafar, Y.

2005-01-01

Salinity stress is one of the most serious factors limiting the productivity of agricultural crops. Genetic engineering provides a useful tool for tailoring plants with enhanced salt tolerance characteristics. Many organisms have evolved mechanisms to survive and grow under such extreme environments. These organisms provide us with a useful source of genes which can be used to improve salt tolerance in plants. The present study aims at identification and cloning of useful halo tolerance conferring genes from fungi and plants and to develop salt tolerant transgenic plants. Here we describe the cloning and use of HSR1 gene (a yeast transcription factor known to confer salt tolerance) and Na/sup +//H/sup +/ antiporter gene AtNHX1 (3016 bp) from Arabidopsis thaliana, and transformation of tobacco with HSR1 and AtNHX1 genes through Agrobacterium method. A number of transgenic tobacco plants were regenerated from leaf explants transformed with Agrobacterium tumefaciens (LBA4404) having HSR1 and AtNHX1 genes by leaf disc method. The putative transgenic plants were analyzed by PCR and dot blot analysis. Screening of these transgenic plants at different salinity levels is in progress which will help identify the suitable plant lines and thus the promising genes which can be further exploited to engineer salt tolerant crop plants. (author)

Genetic engineering of grass cell wall polysaccharides for biorefining.

Science.gov (United States)

Bhatia, Rakesh; Gallagher, Joe A; Gomez, Leonardo D; Bosch, Maurice

2017-09-01

Grasses represent an abundant and widespread source of lignocellulosic biomass, which has yet to fulfil its potential as a feedstock for biorefining into renewable and sustainable biofuels and commodity chemicals. The inherent recalcitrance of lignocellulosic materials to deconstruction is the most crucial limitation for the commercial viability and economic feasibility of biomass biorefining. Over the last decade, the targeted genetic engineering of grasses has become more proficient, enabling rational approaches to modify lignocellulose with the aim of making it more amenable to bioconversion. In this review, we provide an overview of transgenic strategies and targets to tailor grass cell wall polysaccharides for biorefining applications. The bioengineering efforts and opportunities summarized here rely primarily on (A) reprogramming gene regulatory networks responsible for the biosynthesis of lignocellulose, (B) remodelling the chemical structure and substitution patterns of cell wall polysaccharides and (C) expressing lignocellulose degrading and/or modifying enzymes in planta. It is anticipated that outputs from the rational engineering of grass cell wall polysaccharides by such strategies could help in realizing an economically sustainable, grass-derived lignocellulose processing industry. © 2017 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Genetic engineering, a potential aid to conventional plant breeding

International Nuclear Information System (INIS)

Baloch, M.J.; Soomro, B.A.

1993-01-01

To develop improve crop varieties, the most basic elements are crossing of desirable parents to provide genetic variation for evaluation and selection of desirable plants among the progenies. In conventional plant breeding, gene transfer is achieved by back crossing or less frequently by recurrent selection. Both processes take several generations to reach to a point where genetic milieu of the parents remains. Plant breeders also face the most difficult situation when the desired gene is present in the entirely diverse species where wide crosses become inevitable. In addition, genomic disharmony, unfavourable genic interaction and chromosomal instability also account for limited success of wide hybridization in the field crops. Under such circumstances, tissue culture techniques, such as somaclonal variation, Embryo Rescue Technique and Somatic hybridization are the ultimate options. There may be other cases where desired genes are present in entirely different genera or organisms and crossings of donor with recipient is no more a concern. Plant breeders also spend much of their time manipulating quantitatively inherited traits such as yield, that have low heritability. These characters are assumed to be determined by a large number of genes each with minor and additive effects. Direct selection for such traits is less effective. Genetic Engineering approaches like isozymes and Restriction Fragment Length Polymorphism (RFLP) with heritability of 1.0 make the selection very efficient and accurate as indirect selection criteria for quantitatively inherited traits. Hence isozymes and RFLPs techniques can easily be exercised at cellular or seedling stages thus reducing the time and labour oriented screening of plants at maturity. Rather new approach such as polymerase chain reaction (PCR) will also be discussed in this article. (Orig./A.B.)

Artificial intelligence and visco-elastic analyses for modelling of pavement structures

OpenAIRE

CHABOT, Armelle

2009-01-01

Since January 1, 2009, Maryam Miradi is working as a software engineer at Logica, Rotterdam. Before that she was working as a PhD student at the department of Road and Railway Engineering of the faculty of Civil Engineering and Geosciences, Delft University of Technology. In 1998 she graduated in software engineering at the Mashad University in Iran. In 2003 she became PhD student at the Road and Railway Engineering Department. The objective of her study was to use Artificial Intelligence (AI...

Trends in approval times for genetically engineered crops in the United States and the European Unio

NARCIS (Netherlands)

Smart, Richard D.; Blum, Matthias; Wesseler, J.H.H.

2017-01-01

Genetically engineered (GE) crops are subject to regulatory oversight to Ensure their safety for humans and the environment. Their approval in the European Union (EU) starts with an application in a given Member State followed by a scientific risk assessment, and ends with a political

Growing adaptive machines combining development and learning in artificial neural networks

CERN Document Server

Bredeche, Nicolas; Doursat, René

2014-01-01

The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

Перспективы генетически модифицированных организмов в Казахстане

OpenAIRE

Конуркулжаева, Н.З.; Алиева, М.М.; Сон, Л.Э.

2015-01-01

Genetically modified organism – organism whose genotype has been artificially modified by means of genetic engineering methods. This definition can be applied to plants, animals and microorganisms. Genetic changes are usually made in scientific or economic purposes . Genetic modification differs purposeful changes in the genotype of an organism as opposed to random, characteristic of natural and artificial mutation. The main type of genetic modification is currently using transgenes to ...

Artificial Intelligence Software Engineering (AISE) model

Science.gov (United States)

Kiss, Peter A.

1990-01-01

The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

A case for the revision of power engineering syllabi at Kenyan universities

Energy Technology Data Exchange (ETDEWEB)

Abungu, N.; Akumu, A. [Jomo Kenyatta Univ. of Agriculture and Technology, Nairobi (Kenya). Dept. of Electrical and Electronic Engineering; Munda, J. [Tshwane Univ. of Technology, Pretoria (South Africa). Dept. of Power Engineering

2005-07-01

A summary of electrical power engineering education in Kenyan universities was presented. Industry expectations for power systems graduates were discussed. Despite rapid changes in electrical power industries around the world, electrical power engineering in Kenya has remained the same for several years. Curriculum changes were last initiated in the 1980s. Universities have not promoted power engineering and its importance to society, and misunderstandings have led to a lack of employment opportunities for graduates and low enrolment levels. Recent advances in artificial neural networks, genetic algorithms, and fuzzy logic within power systems engineering are not currently taught at Kenyan universities. The deregulation of the power industry calls for a re-assessment of how power engineering is taught. Accidents related to poor engineering designs are relatively common in Kenya and have led to the loss of lives. Severe capacity shortfalls experienced in the country have led to a renewed interest in alternative sources of electricity generation. Environmental studies will help students appreciate the importance of using energy sources that do not degrade the environment. It was concluded that the introduction of new approaches to power engineering will result in increased interest from students. The establishment of industry-university collaborations was recommended, as well as active links with international universities. 12 refs.

Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

CERN Document Server

Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

2016-01-01

This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

Constructs and methods for genome editing and genetic engineering of fungi and protists

Science.gov (United States)

Hittinger, Christopher Todd; Alexander, William Gerald

2018-01-30

Provided herein are constructs for genome editing or genetic engineering in fungi or protists, methods of using the constructs and media for use in selecting cells. The construct include a polynucleotide encoding a thymidine kinase operably connected to a promoter, suitably a constitutive promoter; a polynucleotide encoding an endonuclease operably connected to an inducible promoter; and a recognition site for the endonuclease. The constructs may also include selectable markers for use in selecting recombinations.

Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

Energy Technology Data Exchange (ETDEWEB)

Santos de Oliveira, Iona Maghali, E-mail: ioliveira@con.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil); Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Nuclear Engineering Program, Federal University of Rio de Janeiro, P.O. Box 68509, Zip Code 21945-970, Rio de Janeiro, RJ (Brazil)

2011-05-15

Research highlights: > We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. > Its performance is examined through the optimization of a Brazilian '2-loop' PWR. > Feasibility of using ABCRK is shown against some well known population-based algorithms. > Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

International Nuclear Information System (INIS)

Santos de Oliveira, Iona Maghali; Schirru, Roberto

2011-01-01

Research highlights: → We present Artificial Bee Colony with Random Keys (ABCRK) for In-Core Fuel Management Optimization. → Its performance is examined through the optimization of a Brazilian '2-loop' PWR. → Feasibility of using ABCRK is shown against some well known population-based algorithms. → Additional advantage includes the utilization of fewer control parameters. - Abstract: Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian '2-loop' Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.

Conditions that impact artificial hybridization of Arachis hypogaea L.

Science.gov (United States)

Modern farming is dependent on continual development of improved cultivars and efficient cultural management practices. In addition, dissecting genetic components of heritable traits also relies on the development of large mapping populations. Artificial hybridization is the critical initial step ...

Complex laterally ordered InGaAs and InAs quantum dots by guided self-organized anisotropic strain engineering on artificially patterned GaAs (3 1 1)B substrates

NARCIS (Netherlands)

Selçuk, E.; Hamhuis, G.J.; Nötzel, R.

2009-01-01

Self-organized anisotropic strain engineering is combined with growth on artificially patterned GaAs (3 1 1)B substrates to realize complex lateral ordering of InGaAs and InAs quantum dots (QDs) guided by steps and facets generated along the pattern sidewalls. Depending on the pattern design, size,

Desktop Genetics.

Science.gov (United States)

Hough, Soren H; Ajetunmobi, Ayokunmi; Brody, Leigh; Humphryes-Kirilov, Neil; Perello, Edward

2016-11-01

Desktop Genetics is a bioinformatics company building a gene-editing platform for personalized medicine. The company works with scientists around the world to design and execute state-of-the-art clustered regularly interspaced short palindromic repeats (CRISPR) experiments. Desktop Genetics feeds the lessons learned about experimental intent, single-guide RNA design and data from international genomics projects into a novel CRISPR artificial intelligence system. We believe that machine learning techniques can transform this information into a cognitive therapeutic development tool that will revolutionize medicine.

Quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria by gas chromatography-mass spectrometry.

Science.gov (United States)

Guan, Wenna; Zhao, Hui; Lu, Xuefeng; Wang, Cong; Yang, Menglong; Bai, Fali

2011-11-11

Simple and rapid quantitative determination of fatty-acid-based biofuels is greatly important for the study of genetic engineering progress for biofuels production by microalgae. Ideal biofuels produced from biological systems should be chemically similar to petroleum, like fatty-acid-based molecules including free fatty acids, fatty acid methyl esters, fatty acid ethyl esters, fatty alcohols and fatty alkanes. This study founded a gas chromatography-mass spectrometry (GC-MS) method for simultaneous quantification of seven free fatty acids, nine fatty acid methyl esters, five fatty acid ethyl esters, five fatty alcohols and three fatty alkanes produced by wild-type Synechocystis PCC 6803 and its genetically engineered strain. Data obtained from GC-MS analyses were quantified using internal standard peak area comparisons. The linearity, limit of detection (LOD) and precision (RSD) of the method were evaluated. The results demonstrated that fatty-acid-based biofuels can be directly determined by GC-MS without derivation. Therefore, rapid and reliable quantitative analysis of fatty-acid-based biofuels produced by wild-type and genetically engineered cyanobacteria can be achieved using the GC-MS method founded in this work. Copyright © 2011 Elsevier B.V. All rights reserved.

50. Brazilian congress on genetics. 50 years developing genetics. Abstracts

International Nuclear Information System (INIS)

2004-01-01

Use of radioisotopes and ionizing radiations in genetics is presented. Several aspects related to men, animals,plants and microorganisms are reported highlighting biological radiation effects, evolution, mutagenesis and genetic engineering. Genetic mapping, gene mutations, genetic diversity, DNA damages, plant cultivation and plant grow are studied as well

Enhancing the Internationalisation of Distance Education in the Biological Sciences: The DUNE Project and Genetic Engineering.

Science.gov (United States)

Leach, C. K.; And Others

1997-01-01

Describes the Distance Educational Network of Europe (DUNE) project that aims at enhancing the development of distance education in an international context. Highlights issues relating to the delivery of distance-learning courses in a transnational forum. Describes the genetic engineering course that aims at explaining the core techniques of…

A review on the integration of artificial intelligence into coastal modeling.

Science.gov (United States)

Chau, Kwokwing

2006-07-01

With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.

Dynamic route guidance algorithm based algorithm based on artificial immune system

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.

Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Najafi, G.; Ghobadian, B.; Tavakoli, T.; Faizollahnejad, M. [Tarbiat Modares University, Jalale-E-Aleahmad Highway, Tehran, P.O. Box: 14115-111 (Iran); Buttsworth, D.R.; Yusaf, T.F. [University of Southern Queensland, Toowoomba, 4350 QLD (Australia)

2009-05-15

The purpose of this study is to experimentally analyse the performance and the pollutant emissions of a four-stroke SI engine operating on ethanol-gasoline blends of 0%, 5%, 10%, 15% and 20% with the aid of artificial neural network (ANN). The properties of bioethanol were measured based on American Society for Testing and Materials (ASTM) standards. The experimental results revealed that using ethanol-gasoline blended fuels increased the power and torque output of the engine marginally. For ethanol blends it was found that the brake specific fuel consumption (bsfc) was decreased while the brake thermal efficiency ({eta}{sub b.th.}) and the volumetric efficiency ({eta}{sub v}) were increased. The concentration of CO and HC emissions in the exhaust pipe were measured and found to be decreased when ethanol blends were introduced. This was due to the high oxygen percentage in the ethanol. In contrast, the concentration of CO{sub 2} and NO{sub x} was found to be increased when ethanol is introduced. An ANN model was developed to predict a correlation between brake power, torque, brake specific fuel consumption, brake thermal efficiency, volumetric efficiency and emission components using different gasoline-ethanol blends and speeds as inputs data. About 70% of the total experimental data were used for training purposes, while the 30% were used for testing. A standard Back-Propagation algorithm for the engine was used in this model. A multi layer perception network (MLP) was used for nonlinear mapping between the input and the output parameters. It was observed that the ANN model can predict engine performance and exhaust emissions with correlation coefficient (R) in the range of 0.97-1. Mean relative errors (MRE) values were in the range of 0.46-5.57%, while root mean square errors (RMSE) were found to be very low. This study demonstrates that ANN approach can be used to accurately predict the SI engine performance and emissions. (author)

RAVEN: a GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework

Energy Technology Data Exchange (ETDEWEB)

C. Rabiti; D. Mandelli; A. Alfonsi; J. Cogliati; R. Kinoshita; D. Gaston; R. Martineau; C. Curtis

2013-06-01

Increases in computational power and pressure for more accurate simulations and estimations of accident scenario consequences are driving the need for Dynamic Probabilistic Risk Assessment (PRA) [1] of very complex models. While more sophisticated algorithms and computational power address the back end of this challenge, the front end is still handled by engineers that need to extract meaningful information from the large amount of data and build these complex models. Compounding this problem is the difficulty in knowledge transfer and retention, and the increasing speed of software development. The above-described issues would have negatively impacted deployment of the new high fidelity plant simulator RELAP-7 (Reactor Excursion and Leak Analysis Program) at Idaho National Laboratory. Therefore, RAVEN that was initially focused to be the plant controller for RELAP-7 will help mitigate future RELAP-7 software engineering risks. In order to accomplish this task, Reactor Analysis and Virtual Control Environment (RAVEN) has been designed to provide an easy to use Graphical User Interface (GUI) for building plant models and to leverage artificial intelligence algorithms in order to reduce computational time, improve results, and help the user to identify the behavioral pattern of the Nuclear Power Plants (NPPs). In this paper we will present the GUI implementation and its current capability status. We will also introduce the support vector machine algorithms and show our evaluation of their potentiality in increasing the accuracy and reducing the computational costs of PRA analysis. In this evaluation we will refer to preliminary studies performed under the Risk Informed Safety Margins Characterization (RISMC) project of the Light Water Reactors Sustainability (LWRS) campaign [3]. RISMC simulation needs and algorithm testing are currently used as a guidance to prioritize RAVEN developments relevant to PRA.

Expertik: Experience with Artificial Intelligence and Mobile Computing

Directory of Open Access Journals (Sweden)

José Edward Beltrán Lozano

2013-06-01

Full Text Available This article presents the experience in the development of services based in Artificial Intelligence, Service Oriented Architecture, mobile computing. It aims to combine technology offered by mobile computing provides techniques and artificial intelligence through a service provide diagnostic solutions to problems in industrial maintenance. It aims to combine technology offered by mobile computing and the techniques artificial intelligence through a service to provide diagnostic solutions to problems in industrial maintenance. For service creation are identified the elements of an expert system, the knowledge base, the inference engine and knowledge acquisition interfaces and their consultation. The applications were developed in ASP.NET under architecture three layers. The data layer was developed conjunction in SQL Server with data management classes; business layer in VB.NET and the presentation layer in ASP.NET with XHTML. Web interfaces for knowledge acquisition and query developed in Web and Mobile Web. The inference engine was conducted in web service developed for the fuzzy logic model to resolve requests from applications consulting knowledge (initially an exact rule-based logic within this experience to resolve requests from applications consulting knowledge. This experience seeks to strengthen a technology-based company to offer services based on AI for service companies Colombia.

Computers in engineering. 1988

International Nuclear Information System (INIS)

Tipnis, V.A.; Patton, E.M.

1988-01-01

These proceedings discuss the following subjects: Knowledge base systems; Computers in designing; uses of artificial intelligence; engineering optimization and expert systems of accelerators; and parallel processing in designing

[Fishery resource protection by artificial propagation in hydroelectric development: Lixianjiang River drainage in Yunnan as an example].

Science.gov (United States)

Yang, Yong-Hong; Yang, Jun-Xing; Pan, Xiao-Fu; Zhou, Wei; Yang, Mei-Lin

2011-04-01

Hydroelectric developments can result in a number of negative environmental consequences. Conservation aquaculture is a branch of science derived from conservation and population recovery studies on endangered fishes. Here we discuss the impacts on fishes caused by hydropower projects in Lixianjiang, and evaluate effects and problems on the propagation of Parazacco spilurus, Hemibagrus pluriradiatus, Neolissochilus benasi and Semilabeo obscurus. A successful propagation project includes foraging ecology in fields, pond cultivation, juvenile fish raising, prevention and curing on fish disease, genetic management, artificial releasing and population monitoring. Artificial propagation is the practicable act on genetic intercommunication, preventing population deterioration for fishes in upper and lower reaches of the dam. For long-term planning, fish stocks are not suitable for many kind of fishes, but can prevent fishes from going extinct in the wild. Basic data collection on fish ecology, parent fish hunting, prevention on fish disease are the most important factors on artificial propagation. Strengthening the genetic management of stock population for keeping a higher genetic diversity can increase the success of stock enhancement. The works on Lixianjiang provide a new model for river fish protection. To make sure the complicated project works well, project plans, commission contracts, base line monitoring and techniques on artificial reproduction must be considered early. Last, fishery conservation should be considered alongside location development.

[Artificial intelligence--the knowledge base applied to nephrology].

Science.gov (United States)

Sancipriano, G P

2005-01-01

The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

Crystals of Serum Albumin for Use in Genetic Engineering and Rational Drug Design

Science.gov (United States)

Carter, Daniel C. (Inventor)

1996-01-01

Serum albumin crystal forms have been produced which exhibit superior x-ray diffraction quality. The crystals are produced from both recombinant and wild-type human serum albumin, canine, and baboon serum albumin and allow the performance of drug-binding studies as well as genetic engineering studies. The crystals are grown from solutions of polyethylene glycol or ammonium sulphate within prescribed limits during growth times from one to several weeks and include the following space groups: P2(sub 1), C2, P1.

Development of an Intelligent Car Engine Fault Troubleshooting ...

African Journals Online (AJOL)

Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS) ... and also provides a troubleshooting framework for other researchers to work on. Keywords: ... inference engine, knowledge acquisition, artificial intelligence.

Construction of genetically engineered Candida tropicalis for conversion of l-arabinose to l-ribulose.

Science.gov (United States)

Yeo, In-Seok; Shim, Woo-Yong; Kim, Jung Hoe

2018-05-20

For the biological production of l-ribulose, conversion by enzymes or resting cells has been investigated. However, expensive or concentrated substrates, an additional purification step to remove borate and the requirement for cell cultivation and harvest steps before utilization of resting cells make the production process complex and unfavorable. Microbial fermentation may help overcome these limitations. In this study, we constructed a genetically engineered Candida tropicalis strain to produce l-ribulose by fermentation with a glucose/l-arabinose mixture. For the uptake of l-arabinose as a substrate and conversion of l-arabinose to l-ribulose, two heterologous genes coding for l-arabinose transporter and l-arabinose isomerase, were constitutively expressed in C. tropicalis under the GAPDH promoter. The Arabidopsis thaliana-originated l-arabinose transporter gene (STP2)-expressing strain exhibited a high l-arabinose uptake rate of 0.103 g/g cell/h and the expression of l-arabinose isomerase from Lactobacillus sakei 23 K showed 30% of conversion (9 g/L) from 30 g/L of l-arabinose. This genetically engineered strain can be used for l-ribulose production by fermentation using mixed sugars of glucose and l-arabinose. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular Cloning Designer Simulator (MCDS): All-in-one molecular cloning and genetic engineering design, simulation and management software for complex synthetic biology and metabolic engineering projects.

Science.gov (United States)

Shi, Zhenyu; Vickers, Claudia E

2016-12-01

Molecular Cloning Designer Simulator (MCDS) is a powerful new all-in-one cloning and genetic engineering design, simulation and management software platform developed for complex synthetic biology and metabolic engineering projects. In addition to standard functions, it has a number of features that are either unique, or are not found in combination in any one software package: (1) it has a novel interactive flow-chart user interface for complex multi-step processes, allowing an integrated overview of the whole project; (2) it can perform a user-defined workflow of cloning steps in a single execution of the software; (3) it can handle multiple types of genetic recombineering, a technique that is rapidly replacing classical cloning for many applications; (4) it includes experimental information to conveniently guide wet lab work; and (5) it can store results and comments to allow the tracking and management of the whole project in one platform. MCDS is freely available from https://mcds.codeplex.com.

NUTRITIONAL ENHANCEMENT OF ALFALFA THROUGH GENETIC ENGINEERING

Directory of Open Access Journals (Sweden)

J. Faragó

2008-09-01

Full Text Available Alfalfa (Medicago sativa L. is a pasture legume crop of primary importance to animal production throughout the world. The nutritional quality of alfalfa, as of other leguminous forage crops, is mainly determined by their content in selected essential amino acids (EAAs, such as methionine (Met and cysteine (Cys. In alfalfa, however, these S-containing amino acids constitute only about 1% or less of crude proteins (Frame et al., 1998. This is significantly less than the 3.5% Met+Cys content in the recommended FAO reference protein (FAO, 1973. Recent advances in genetic engineering allow to use the transgenic approach to increase the content of specific essential amino acids in target plant species. A number of different molecular approaches have been developed to address this issue, such as over-expression of a heterologous or homologous Met-rich protein, expression of a synthetic protein, modification of protein sequence, and metabolic engineering of the free amino acid pool and protein sink. To study the possibility of transgenic enhancement of nutritional quality of alfalfa, we used the approach of expression of a heterologous protein rich in Met+Cys in cells of alfalfa. The T-DNA introduced into the genome of alfalfa, using Agrobacterium tumefaciens-mediated genetic transformation, contained the selectable merker gene nptII for kanamycin (Kn resistance, and a cDNA of Ov gene from Japanese quail (Coturnix coturnix coding for a high Met+Cys containing ovalbumine (Mucha et al., 1991, both under constitutive promoters. After cocultivation of petiole segment- and leaf blade-explants of two highly embryogenic alfalfa genotypes Rg9/I-14-22 and Rg11/I-10-68 (Faragó et al., 1997 with cells of A. tumefaciens strain AGL1 carrying the nptII and Ov genes, and selection of transgenic cells on Kn containing selective media, more than one hundred putatively transgenic regenerants were obtained through somatic embryogenesis. Biological (Kn rooting assay

Genetically engineered mesenchymal stromal cells produce IL-3 and TPO to further improve human scaffold-based xenograft models.

Science.gov (United States)

Carretta, Marco; de Boer, Bauke; Jaques, Jenny; Antonelli, Antonella; Horton, Sarah J; Yuan, Huipin; de Bruijn, Joost D; Groen, Richard W J; Vellenga, Edo; Schuringa, Jan Jacob

2017-07-01

Recently, NOD-SCID IL2Rγ -/- (NSG) mice were implanted with human mesenchymal stromal cells (MSCs) in the presence of ceramic scaffolds or Matrigel to mimic the human bone marrow (BM) microenvironment. This approach allowed the engraftment of leukemic samples that failed to engraft in NSG mice without humanized niches and resulted in a better preservation of leukemic stem cell self-renewal properties. To further improve our humanized niche scaffold model, we genetically engineered human MSCs to secrete human interleukin-3 (IL-3) and thrombopoietin (TPO). In vitro, these IL-3- and TPO-producing MSCs were superior in expanding human cord blood (CB) CD34 + hematopoietic stem/progenitor cells. MLL-AF9-transduced CB CD34 + cells could be transformed efficiently along myeloid or lymphoid lineages on IL-3- and TPO-producing MSCs. In vivo, these genetically engineered MSCs maintained their ability to differentiate into bone, adipocytes, and other stromal components. Upon transplantation of MLL-AF9-transduced CB CD34 + cells, acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) developed in engineered scaffolds, in which a significantly higher percentage of myeloid clones was observed in the mouse compartments compared with previous models. Engraftment of primary AML, B-cell ALL, and biphenotypic acute leukemia (BAL) patient samples was also evaluated, and all patient samples could engraft efficiently; the myeloid compartment of the BAL samples was better preserved in the human cytokine scaffold model. In conclusion, we show that we can genetically engineer the ectopic human BM microenvironment in a humanized scaffold xenograft model. This approach will be useful for functional study of the importance of niche factors in normal and malignant human hematopoiesis. Copyright © 2017 ISEH - International Society for Experimental Hematology. All rights reserved.

Genetic engineering of cell lines using lentiviral vectors to achieve antibody secretion following encapsulated implantation.

Science.gov (United States)

Lathuilière, Aurélien; Bohrmann, Bernd; Kopetzki, Erhard; Schweitzer, Christoph; Jacobsen, Helmut; Moniatte, Marc; Aebischer, Patrick; Schneider, Bernard L

2014-01-01

The controlled delivery of antibodies by immunoisolated bioimplants containing genetically engineered cells is an attractive and safe approach for chronic treatments. To reach therapeutic antibody levels there is a need to generate renewable cell lines, which can long-term survive in macroencapsulation devices while maintaining high antibody specific productivity. Here we have developed a dual lentiviral vector strategy for the genetic engineering of cell lines compatible with macroencapsulation, using separate vectors encoding IgG light and heavy chains. We show that IgG expression level can be maximized as a function of vector dose and transgene ratio. This approach allows for the generation of stable populations of IgG-expressing C2C12 mouse myoblasts, and for the subsequent isolation of clones stably secreting high IgG levels. Moreover, we demonstrate that cell transduction using this lentiviral system leads to the production of a functional glycosylated antibody by myogenic cells. Subsequent implantation of antibody-secreting cells in a high-capacity macroencapsulation device enables continuous delivery of recombinant antibodies in the mouse subcutaneous tissue, leading to substantial levels of therapeutic IgG detectable in the plasma.

Artificial Muscles Based on Electroactive Polymers as an Enabling Tool in Biomimetics

Science.gov (United States)

Bar-Cohen, Y.

2007-01-01

Evolution has resolved many of nature's challenges leading to working and lasting solutions that employ principles of physics, chemistry, mechanical engineering, materials science, and many other fields of science and engineering. Nature's inventions have always inspired human achievements leading to effective materials, structures, tools, mechanisms, processes, algorithms, methods, systems, and many other benefits. Some of the technologies that have emerged include artificial intelligence, artificial vision, and artificial muscles, where the latter is the moniker for electroactive polymers (EAPs). To take advantage of these materials and make them practical actuators, efforts are made worldwide to develop capabilities that are critical to the field infrastructure. Researchers are developing analytical model and comprehensive understanding of EAP materials response mechanism as well as effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available; however, in recent years, significant progress has been made and commercial products have already started to appear. In the current paper, the state-of-the-art and challenges to artificial muscles as well as their potential application to biomimetic mechanisms and devices are described and discussed.

Comparison of Two Classifiers; K-Nearest Neighbor and Artificial Neural Network, for Fault Diagnosis on a Main Engine Journal-Bearing

Directory of Open Access Journals (Sweden)

A. Moosavian

2013-01-01

Full Text Available Vibration analysis is an accepted method in condition monitoring of machines, since it can provide useful and reliable information about machine working condition. This paper surveys a new scheme for fault diagnosis of main journal-bearings of internal combustion (IC engine based on power spectral density (PSD technique and two classifiers, namely, K-nearest neighbor (KNN and artificial neural network (ANN. Vibration signals for three different conditions of journal-bearing; normal, with oil starvation condition and extreme wear fault were acquired from an IC engine. PSD was applied to process the vibration signals. Thirty features were extracted from the PSD values of signals as a feature source for fault diagnosis. KNN and ANN were trained by training data set and then used as diagnostic classifiers. Variable K value and hidden neuron count (N were used in the range of 1 to 20, with a step size of 1 for KNN and ANN to gain the best classification results. The roles of PSD, KNN and ANN techniques were studied. From the results, it is shown that the performance of ANN is better than KNN. The experimental results dèmonstrate that the proposed diagnostic method can reliably separate different fault conditions in main journal-bearings of IC engine.

Occupational chemical exposures in artificial organic fiber industries

Energy Technology Data Exchange (ETDEWEB)

Guirguis, S S; Cohen, M B

1984-05-01

This review discusses artificial organic fibers that are produced from materials of natural origin such as rayons, cellulose triacetates and proteins; or made from polymerised chemicals such as polyamides, polyesters, polyvinyls, modacrylics, carbon fibers, polyolefins, polyurethane and polytetrafluoroethylene. Chemicals involved include monomers, solvents, flame retardants, pigments and other additives. Occupational exposure to chemicals in the production stages are discussed and also the potential health hazards involved are reviewed. Current exposure levels, engineering controls and work practices for some of the chemicals used in the Ontario artificial fiber industry are discussed. Recommendations are made for areas that need further study and/or investigation.

Genetic algorithm to optimize the design of main combustor and gas generator in liquid rocket engines

Science.gov (United States)

Son, Min; Ko, Sangho; Koo, Jaye

2014-06-01

A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.

The potential of genetic engineering of plants for the remediation of soils contaminated with heavy metals.

Science.gov (United States)

Fasani, Elisa; Manara, Anna; Martini, Flavio; Furini, Antonella; DalCorso, Giovanni

2018-05-01

The genetic engineering of plants to facilitate the reclamation of soils and waters contaminated with inorganic pollutants is a relatively new and evolving field, benefiting from the heterologous expression of genes that increase the capacity of plants to mobilize, stabilize and/or accumulate metals. The efficiency of phytoremediation relies on the mechanisms underlying metal accumulation and tolerance, such as metal uptake, translocation and detoxification. The transfer of genes involved in any of these processes into fast-growing, high-biomass crops may improve their reclamation potential. The successful phytoextraction of metals/metalloids and their accumulation in aerial organs have been achieved by expressing metal ligands or transporters, enzymes involved in sulfur metabolism, enzymes that alter the chemical form or redox state of metals/metalloids and even the components of primary metabolism. This review article considers the potential of genetic engineering as a strategy to improve the phytoremediation capacity of plants in the context of heavy metals and metalloids, using recent case studies to demonstrate the practical application of this approach in the field. © 2017 John Wiley & Sons Ltd.

Application of genetically engineered microorganisms to bioremediation and wastewater treatment. Idenshi sosa biseibutsu no kankyo joka mizushori eno tekiyo

Energy Technology Data Exchange (ETDEWEB)

Fujita, M; Ike, M [Osaka University, Osaka (Japan). Faculty of Engineering

1993-11-10

This paper summarizes the following techniques: a gene engineering method for bioremediation and wastewater treatment, microorganism breeding using the former method, and a monitoring technique for genetical and ecological stability of genetically engineered microorganisms. Recombination bacteria reinforced with PH genes showed higher phenol removing rate than wild strains, but presented accumulation of catechol in such a large quantity as cannot be seen in wild strains, with the complete degradation rate rather decreased. Gene recombined bacteria structured by introducing the recombined plasmid, pBH500, had high genetic stability when P.putida BH-1 is used as a host. E.coli C600 having recombined plasmid and P.putida BH were added and cultivated in activated sludge. As a result, both recombined bacteria showed rapid logarithmic decrease just after the addition, then, maintained the relatively stable population groups, and remained in the activated sludge for an extended period of time. In monitoring techniques, the colony hybridization process detected clearly the gene recombined bacteria. 9 refs., 7 figs., 1 tab.

Barriers and paths to market for genetically engineered crops.

Science.gov (United States)

Rommens, Caius M

2010-02-01

Each year, billions of dollars are invested in efforts to improve crops through genetic engineering (GE). These activities have resulted in a surge of publications and patents on technologies and genes: a momentum in basic research that, unfortunately, is not sustained throughout the subsequent phases of product development. After more than two decades of intensive research, the market for transgenic crops is still dominated by applications of just a handful of methods and genes. This discrepancy between research and development reflects difficulties in understanding and overcoming seven main barriers-to-entry: (1) trait efficacy in the field, (2) critical product concepts, (3) freedom-to-operate, (4) industry support, (5) identity preservation and stewardship, (6) regulatory approval and (7) retail and consumer acceptance. In this review, I describe the various roadblocks to market for transgenic crops and also discuss methods and approaches on how to overcome these, especially in the United States.

Towards artificial tissue models: past, present, and future of 3D bioprinting.

Science.gov (United States)

Arslan-Yildiz, Ahu; El Assal, Rami; Chen, Pu; Guven, Sinan; Inci, Fatih; Demirci, Utkan

2016-03-01

Regenerative medicine and tissue engineering have seen unprecedented growth in the past decade, driving the field of artificial tissue models towards a revolution in future medicine. Major progress has been achieved through the development of innovative biomanufacturing strategies to pattern and assemble cells and extracellular matrix (ECM) in three-dimensions (3D) to create functional tissue constructs. Bioprinting has emerged as a promising 3D biomanufacturing technology, enabling precise control over spatial and temporal distribution of cells and ECM. Bioprinting technology can be used to engineer artificial tissues and organs by producing scaffolds with controlled spatial heterogeneity of physical properties, cellular composition, and ECM organization. This innovative approach is increasingly utilized in biomedicine, and has potential to create artificial functional constructs for drug screening and toxicology research, as well as tissue and organ transplantation. Herein, we review the recent advances in bioprinting technologies and discuss current markets, approaches, and biomedical applications. We also present current challenges and provide future directions for bioprinting research.

10th ACIS International Conference on Software Engineering Research, Management and Applications (SERA 2012)

CERN Document Server

Software Engineering Research, Management and Applications 2012

2012-01-01

The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence-quickly and with a high quality.  The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.  The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution-this permits a rapid and broad dissemination of research results.  The purpose of the 10th International Conference on Software Engineering Research, Management and Applications(...

History of Civil Engineering Modal Analysis

DEFF Research Database (Denmark)

Brincker, Rune

2008-01-01

techniques are available for civil engineering modal analysis. The testing of civil structures defers from the traditional modal testing in the sense, that very often it is difficult, or sometimes impossible, to artificially excite a large civil engineering structure. Also, many times, even though...

'HoneySweet' (C5), the first genetically engineered Plum pox virus-resistant plum (Prunus domestica L.) cultivar

Science.gov (United States)

‘HoneySweet’ plum was released by the U.S. Department of Agriculture, Agricultural Research Service, to provide U.S. growers and P. domestica plum breeders with a high fruit quality plum cultivar resistant to Plum pox virus (PPV). ‘HoneySweet’ was developed through genetic engineering utilizing the...

Systems with artificial intelligence in nuclear power plant operation

International Nuclear Information System (INIS)

Bastl, W.; Felkel, L.

1989-01-01

The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

Exploring expressivity and emotion with artificial voice and speech technologies.

Science.gov (United States)

Pauletto, Sandra; Balentine, Bruce; Pidcock, Chris; Jones, Kevin; Bottaci, Leonardo; Aretoulaki, Maria; Wells, Jez; Mundy, Darren P; Balentine, James

2013-10-01

Emotion in audio-voice signals, as synthesized by text-to-speech (TTS) technologies, was investigated to formulate a theory of expression for user interface design. Emotional parameters were specified with markup tags, and the resulting audio was further modulated with post-processing techniques. Software was then developed to link a selected TTS synthesizer with an automatic speech recognition (ASR) engine, producing a chatbot that could speak and listen. Using these two artificial voice subsystems, investigators explored both artistic and psychological implications of artificial speech emotion. Goals of the investigation were interdisciplinary, with interest in musical composition, augmentative and alternative communication (AAC), commercial voice announcement applications, human-computer interaction (HCI), and artificial intelligence (AI). The work-in-progress points towards an emerging interdisciplinary ontology for artificial voices. As one study output, HCI tools are proposed for future collaboration.

Evolution under domestication: ongoing artificial selection and divergence of wild and managed Stenocereus pruinosus (Cactaceae) populations in the Tehuacán Valley, Mexico

Science.gov (United States)

Parra, Fabiola; Casas, Alejandro; Peñaloza-Ramírez, Juan Manuel; Cortés-Palomec, Aurea C.; Rocha-Ramírez, Víctor; González-Rodríguez, Antonio

2010-01-01

Background and Aims The Tehuacán Valley in Mexico is a principal area of plant domestication in Mesoamerica. There, artificial selection is currently practised on nearly 120 native plant species with coexisting wild, silvicultural and cultivated populations, providing an excellent setting for studying ongoing mechanisms of evolution under domestication. One of these species is the columnar cactus Stenocereus pruinosus, in which we studied how artificial selection is operating through traditional management and whether it has determined morphological and genetic divergence between wild and managed populations. Methods Semi-structured interviews were conducted with 83 households of three villages to investigate motives and mechanisms of artificial selection. Management effects were studied by comparing variation patterns of 14 morphological characters and population genetics (four microsatellite loci) of 264 plants from nine wild, silvicultural and cultivated populations. Key Results Variation in fruit characters was recognized by most people, and was the principal target of artificial selection directed to favour larger and sweeter fruits with thinner or thicker peel, fewer spines and pulp colours others than red. Artificial selection operates in agroforestry systems favouring abundance (through not felling plants and planting branches) of the preferred phenotypes, and acts more intensely in household gardens. Significant morphological divergence between wild and managed populations was observed in fruit characters and plant vigour. On average, genetic diversity in silvicultural populations (HE = 0·743) was higher than in wild (HE = 0·726) and cultivated (HE = 0·700) populations. Most of the genetic variation (90·58 %) occurred within populations. High gene flow (NmFST > 2) was identified among almost all populations studied, but was slightly limited by mountains among wild populations, and by artificial selection among wild and managed populations. Conclusions

Ground Motion Prediction Model Using Artificial Neural Network

Science.gov (United States)

Dhanya, J.; Raghukanth, S. T. G.

2018-03-01

This article focuses on developing a ground motion prediction equation based on artificial neural network (ANN) technique for shallow crustal earthquakes. A hybrid technique combining genetic algorithm and Levenberg-Marquardt technique is used for training the model. The present model is developed to predict peak ground velocity, and 5% damped spectral acceleration. The input parameters for the prediction are moment magnitude ( M w), closest distance to rupture plane ( R rup), shear wave velocity in the region ( V s30) and focal mechanism ( F). A total of 13,552 ground motion records from 288 earthquakes provided by the updated NGA-West2 database released by Pacific Engineering Research Center are utilized to develop the model. The ANN architecture considered for the model consists of 192 unknowns including weights and biases of all the interconnected nodes. The performance of the model is observed to be within the prescribed error limits. In addition, the results from the study are found to be comparable with the existing relations in the global database. The developed model is further demonstrated by estimating site-specific response spectra for Shimla city located in Himalayan region.

Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

Science.gov (United States)

Cipresso, Pietro; Riva, Giuseppe

2015-01-01

There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

A case study of technology transfer: Rehabilitative engineering at Rancho Los Amigos Hospital. [prosthetic devices engineering

Science.gov (United States)

Hildred, W.

1973-01-01

The transfer of NASA technolgy to rehabilitative applications of artificial limbs is studied. Human factors engineering activities range from orthotic manipulators to tiny dc motors and transducers to detect and transmit voluntary control signals. It is found that bicarbon implant devices are suitable for medical equipment and artificial limbs because of their biological compatibility with human body fluids and tissues.

The development of artificial organs and prostheses worldwide and in the Ottoman Empire.

Science.gov (United States)

Birdane, Leman; Cingi, Cemal; Elçioğlu, Ömür; Muluk, Nuray Bayar

2016-08-01

An artificial organ or prosthesis is a man-made device that is implanted or integrated into a human to replace a natural organ. There were many historical steps in the development of artificial organs and prostheses. New surgical techniques, the development of prosthetic materials and the creative ideas of engineers led to progress in this field. © The European Society of Cardiology 2014.

Synthetic and Bio-Artificial Tactile Sensing: A Review

Directory of Open Access Journals (Sweden)

Maria Chiara Carrozza

2013-01-01

Full Text Available This paper reviews the state of the art of artificial tactile sensing, with a particular focus on bio-hybrid and fully-biological approaches. To this aim, the study of physiology of the human sense of touch and of the coding mechanisms of tactile information is a significant starting point, which is briefly explored in this review. Then, the progress towards the development of an artificial sense of touch are investigated. Artificial tactile sensing is analysed with respect to the possible approaches to fabricate the outer interface layer: synthetic skin versus bio-artificial skin. With particular respect to the synthetic skin approach, a brief overview is provided on various technologies and transduction principles that can be integrated beneath the skin layer. Then, the main focus moves to approaches characterized by the use of bio-artificial skin as an outer layer of the artificial sensory system. Within this design solution for the skin, bio-hybrid and fully-biological tactile sensing systems are thoroughly presented: while significant results have been reported for the development of tissue engineered skins, the development of mechanotransduction units and their integration is a recent trend that is still lagging behind, therefore requiring research efforts and investments. In the last part of the paper, application domains and perspectives of the reviewed tactile sensing technologies are discussed.

Artificial intelligence metamodel comparison and application to wind turbine airfoil uncertainty analysis

Directory of Open Access Journals (Sweden)

Yaping Ju

2016-05-01

Full Text Available The Monte Carlo simulation method for turbomachinery uncertainty analysis often requires performing a huge number of simulations, the computational cost of which can be greatly alleviated with the help of metamodeling techniques. An intensive comparative study was performed on the approximation performance of three prospective artificial intelligence metamodels, that is, artificial neural network, radial basis function, and support vector regression. The genetic algorithm was used to optimize the predetermined parameters of each metamodel for the sake of a fair comparison. Through testing on 10 nonlinear functions with different problem scales and sample sizes, the genetic algorithm–support vector regression metamodel was found more accurate and robust than the other two counterparts. Accordingly, the genetic algorithm–support vector regression metamodel was selected and combined with the Monte Carlo simulation method for the uncertainty analysis of a wind turbine airfoil under two types of surface roughness uncertainties. The results show that the genetic algorithm–support vector regression metamodel can capture well the uncertainty propagation from the surface roughness to the airfoil aerodynamic performance. This work is useful to the application of metamodeling techniques in the robust design optimization of turbomachinery.

Measurement correction method for force sensor used in dynamic pressure calibration based on artificial neural network optimized by genetic algorithm

Science.gov (United States)

Gu, Tingwei; Kong, Deren; Shang, Fei; Chen, Jing

2017-12-01

We present an optimization algorithm to obtain low-uncertainty dynamic pressure measurements from a force-transducer-based device. In this paper, the advantages and disadvantages of the methods that are commonly used to measure the propellant powder gas pressure, the applicable scope of dynamic pressure calibration devices, and the shortcomings of the traditional comparison calibration method based on the drop-weight device are firstly analysed in detail. Then, a dynamic calibration method for measuring pressure using a force sensor based on a drop-weight device is introduced. This method can effectively save time when many pressure sensors are calibrated simultaneously and extend the life of expensive reference sensors. However, the force sensor is installed between the drop-weight and the hammerhead by transition pieces through the connection mode of bolt fastening, which causes adverse effects such as additional pretightening and inertia forces. To solve these effects, the influence mechanisms of the pretightening force, the inertia force and other influence factors on the force measurement are theoretically analysed. Then a measurement correction method for the force measurement is proposed based on an artificial neural network optimized by a genetic algorithm. The training and testing data sets are obtained from calibration tests, and the selection criteria for the key parameters of the correction model is discussed. The evaluation results for the test data show that the correction model can effectively improve the force measurement accuracy of the force sensor. Compared with the traditional high-accuracy comparison calibration method, the percentage difference of the impact-force-based measurement is less than 0.6% and the relative uncertainty of the corrected force value is 1.95%, which can meet the requirements of engineering applications.

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Science.gov (United States)

Boonjing, Veera; Intakosum, Sarun

2016-01-01

This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

Estimation of hydrogen production in genetically modified E. coli fermentations using an artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Rosales-Colunga, Luis Manuel; De Leon Rodriguez, Antonio [Division de Biologia Molecular, Instituto Potosino de Investigacion Cientifica y Tecnologica, Camino a la Presa San Jose 2055, Col. Lomas 4a secc, San Luis Potosi, SLP 78216 (Mexico); Garcia, Raul Gonzalez [Centro de Investigacion y Estudios de Posgrado, Facultad de Ciencias Quimicas, Universidad Autonoma de San Luis Potosi, Av. Dr. Manuel Nava 6, San Luis Potosi, SLP 78210 (Mexico)

2010-12-15

Biological hydrogen production is an active research area due to the importance of this gas as an energy carrier and the advantages of using biological systems to produce it. A cheap and practical on-line hydrogen determination is desired in those processes. In this study, an artificial neural network (ANN) was developed to estimate the hydrogen production in fermentative processes. A back propagation neural network (BPNN) of one hidden layer with 12 nodes was selected. The BPNN training was done using the conjugated gradient algorithm and on-line measurements of dissolved CO{sub 2}, pH and oxidation-reduction potential during the fermentations of cheese whey by Escherichia coli {delta}hycA {delta}lacI (WDHL) strain with or without pH control. The correlation coefficient between the hydrogen production determined by gas chromatography and the hydrogen production estimated by the BPNN was 0.955. Results showed that the BPNN successfully estimated the hydrogen production using only on-line parameters in genetically modified E. coli fermentations either with or without pH control. This approach could be used for other hydrogen production systems. (author)

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Directory of Open Access Journals (Sweden)

Montri Inthachot

2016-01-01

Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

Challenges and opportunities for tissue-engineering polarized epithelium.

Science.gov (United States)

Paz, Ana C; Soleas, John; Poon, James C H; Trieu, Dennis; Waddell, Thomas K; McGuigan, Alison P

2014-02-01

The epithelium is one of the most important tissue types in the body and the specific organization of the epithelial cells in these tissues is important for achieving appropriate function. Since many tissues contain an epithelial component, engineering functional epithelium and understanding the factors that control epithelial maturation and organization are important for generating whole artificial organ replacements. Furthermore, disruption of the cellular organization leads to tissue malfunction and disease; therefore, engineered epithelium could provide a valuable in vitro model to study disease phenotypes. Despite the importance of epithelial tissues, a surprisingly limited amount of effort has been focused on organizing epithelial cells into artificial polarized epithelium with an appropriate structure that resembles that seen in vivo. In this review, we provide an overview of epithelial tissue organization and highlight the importance of cell polarization to achieve appropriate epithelium function. We next describe the in vitro models that exist to create polarized epithelium and summarize attempts to engineer artificial epithelium for clinical use. Finally, we highlight the opportunities that exist to translate strategies from tissue engineering other tissues to generate polarized epithelium with a functional structure.

Surveys suck: Consumer preferences when purchasing genetically engineered foods.

Science.gov (United States)

Powell, Douglas A

2013-01-01

Many studies have attempted to gauge consumers' acceptance of genetically engineered or modified (GM) foods. Surveys, asking people about attitudes and intentions, are easy-to-collect proxies of consumer behavior. However, participants tend to respond as citizens of society, not discrete individuals, thereby inaccurately portraying their potential behavior. The Theory of Planned Behavior improved the accuracy of self-reported information, but its limited capacity to account for intention variance has been attributed to the hypothetical scenarios to which survey participants must respond. Valuation methods, asking how much consumers may be willing to pay or accept for GM foods, have revealed that consumers are usually willing to accept them at some price, or in some cases willing to pay a premium. Ultimately, it's consumers' actual--not intended--behavior that is of most interest to policy makers and business decision-makers. Real choice experiments offer the best avenue for revealing consumers' food choices in normal life.

An investigation of genetic algorithms

International Nuclear Information System (INIS)

Douglas, S.R.

1995-04-01

Genetic algorithms mimic biological evolution by natural selection in their search for better individuals within a changing population. they can be used as efficient optimizers. This report discusses the developing field of genetic algorithms. It gives a simple example of the search process and introduces the concept of schema. It also discusses modifications to the basic genetic algorithm that result in species and niche formation, in machine learning and artificial evolution of computer programs, and in the streamlining of human-computer interaction. (author). 3 refs., 1 tab., 2 figs

Accelerating artificial intelligence with reconfigurable computing

Science.gov (United States)

Cieszewski, Radoslaw

Reconfigurable computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated by placing the computationally intense portions of an algorithm into reconfigurable hardware. Reconfigurable computing combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be changed over the lifetime of the system. Similar to an ASIC, reconfigurable systems provide a method to map circuits into hardware. Reconfigurable systems therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Such a field, where there is many different algorithms which can be accelerated, is an artificial intelligence. This paper presents example hardware implementations of Artificial Neural Networks, Genetic Algorithms and Expert Systems.

Whispering galleries and the control of artificial atoms.

Science.gov (United States)

Forrester, Derek Michael; Kusmartsev, Feodor V

2016-04-28

Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms.

Enhancement of contractile force generation of artificial skeletal muscle tissues by mild and transient heat treatment.

Science.gov (United States)

Sato, Masanori; Ikeda, Kazushi; Kanno, Shota; Ito, Akira; Kawabe, Yoshinori; Kamihira, Masamichi

2014-01-01

Artificial skeletal muscle tissues composed of cells are expected to be used for applications of regenerative medicine and drug screening. Generally, however, the physical forces generated by tissue-engineered skeletal muscle are lower than those of skeletal muscle tissues found in the body. Local hyperthermia is used for many diseases including muscle injuries. It was recently reported that mild heat treatment improved skeletal muscle functions. In this study, we investigated the effects of mild heat treatment on the tissue-engineered skeletal muscle tissues in vitro. We used magnetite cationic liposomes to label C2C12 myoblast cells magnetically, and constructed densely packed artificial skeletal muscle tissues by using magnetic force. Cell culture at 39°C promoted the differentiation of myoblast cells into myotubes. Moreover, the mild and transient heat treatment improved the contractile properties of artificial skeletal muscle tissue constructs. These findings indicate that the culture method using heat treatment is a useful approach to enhance functions of artificial skeletal muscle tissue.

Genetic programming in microorganisms

Energy Technology Data Exchange (ETDEWEB)

Hopwood, D A

1981-11-01

Formerly, when microbiologists had only existing organisms at their disposal whose characteristics could only be changed randomly by genetic experiments, they used to dream of programmed genetic changes. This dream has come true with modern genetic engineering.

1st Global Conference on Biomedical Engineering & 9th Asian-Pacific Conference on Medical and Biological Engineering

CERN Document Server

Wang, Shyh-Hau; Yeh, Ming-Long

2015-01-01

This volume presents the proceedings of the 9th Asian-Pacific Conference on Medical and Biological Engineering (APCMBE 2014). The proceedings address a broad spectrum of topics from Bioengineering and Biomedicine, like Biomaterials, Artificial Organs, Tissue Engineering, Nanobiotechnology and Nanomedicine, Biomedical Imaging, Bio MEMS, Biosignal Processing, Digital Medicine, BME Education. It helps medical and biological engineering professionals to interact and exchange their ideas and experiences.

A Pseudomonas putida strain genetically engineered for 1,2,3-trichloropropane bioremediation.

Science.gov (United States)

Samin, Ghufrana; Pavlova, Martina; Arif, M Irfan; Postema, Christiaan P; Damborsky, Jiri; Janssen, Dick B

2014-09-01

1,2,3-Trichloropropane (TCP) is a toxic compound that is recalcitrant to biodegradation in the environment. Attempts to isolate TCP-degrading organisms using enrichment cultivation have failed. A potential biodegradation pathway starts with hydrolytic dehalogenation to 2,3-dichloro-1-propanol (DCP), followed by oxidative metabolism. To obtain a practically applicable TCP-degrading organism, we introduced an engineered haloalkane dehalogenase with improved TCP degradation activity into the DCP-degrading bacterium Pseudomonas putida MC4. For this purpose, the dehalogenase gene (dhaA31) was cloned behind the constitutive dhlA promoter and was introduced into the genome of strain MC4 using a transposon delivery system. The transposon-located antibiotic resistance marker was subsequently removed using a resolvase step. Growth of the resulting engineered bacterium, P. putida MC4-5222, on TCP was indeed observed, and all organic chlorine was released as chloride. A packed-bed reactor with immobilized cells of strain MC4-5222 degraded >95% of influent TCP (0.33 mM) under continuous-flow conditions, with stoichiometric release of inorganic chloride. The results demonstrate the successful use of a laboratory-evolved dehalogenase and genetic engineering to produce an effective, plasmid-free, and stable whole-cell biocatalyst for the aerobic bioremediation of a recalcitrant chlorinated hydrocarbon. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Enhancement of myocardial regeneration through genetic engineering of cardiac progenitor cells expressing Pim-1 kinase.

Science.gov (United States)

Fischer, Kimberlee M; Cottage, Christopher T; Wu, Weitao; Din, Shabana; Gude, Natalie A; Avitabile, Daniele; Quijada, Pearl; Collins, Brett L; Fransioli, Jenna; Sussman, Mark A

2009-11-24

Despite numerous studies demonstrating the efficacy of cellular adoptive transfer for therapeutic myocardial regeneration, problems remain for donated cells with regard to survival, persistence, engraftment, and long-term benefits. This study redresses these concerns by enhancing the regenerative potential of adoptively transferred cardiac progenitor cells (CPCs) via genetic engineering to overexpress Pim-1, a cardioprotective kinase that enhances cell survival and proliferation. Intramyocardial injections of CPCs overexpressing Pim-1 were given to infarcted female mice. Animals were monitored over 4, 12, and 32 weeks to assess cardiac function and engraftment of Pim-1 CPCs with echocardiography, in vivo hemodynamics, and confocal imagery. CPCs overexpressing Pim-1 showed increased proliferation and expression of markers consistent with cardiogenic lineage commitment after dexamethasone exposure in vitro. Animals that received CPCs overexpressing Pim-1 also produced greater levels of cellular engraftment, persistence, and functional improvement relative to control CPCs up to 32 weeks after delivery. Salutary effects include reduction of infarct size, greater number of c-kit(+) cells, and increased vasculature in the damaged region. Myocardial repair is significantly enhanced by genetic engineering of CPCs with Pim-1 kinase. Ex vivo gene delivery to enhance cellular survival, proliferation, and regeneration may overcome current limitations of stem cell-based therapeutic approaches.

Genetic and phenotypic parameters of body weight in Zandi sheep

African Journals Online (AJOL)

DR. TONUKARI NYEROVWO

2011-11-02

Nov 2, 2011 ... In the mating season, artificial insemination (AI) was initially performed, but animals ... direct additive genetic effects; m = maternal genetic effects; c = per- .... food intake and performance in the young lamb; although this trend ...

Progress toward isolation of strains and genetically engineered strains of microalgae for production of biofuel and other value added chemicals: A review

International Nuclear Information System (INIS)

Ghosh, Ashmita; Khanra, Saumyakanti; Mondal, Madhumanti; Halder, Gopinath; Tiwari, O.N.; Saini, Supreet; Bhowmick, Tridib Kumar; Gayen, Kalyan

2016-01-01

Highlights: • Sample collection, isolation and identification to obtain a pure microalgal species. • Isolation of microalgal strains worldwide based on continent and habitat. • Genetic engineering tools for enhanced production of biodiesel and value added chemicals. • Cultivation systems for genetically modified strain. - Abstract: Microalgae and cyanobacteria are promising sources of biodiesel because of their high oil content (∼10 fold higher) and shorter cultivation time (∼4 fold lesser) than conventional oil producing territorial plants (e.g., soybean, corn and jatropha). These organisms also provide source of several valuable natural chemicals including pigments, food supplements like eicosapentanoic acid [EPA], decosahexaenoic acid [DHA] and vitamins. In addition, many cellular components of these organisms are associated with therapeutic properties like antioxidant, anti-inflammatory, immunostimulating, and antiviral. Isolation and identification of high-yielding strains with the faster growth rate is the key for successful implementation of algal biodiesel (or other products) at a commercial level. A number of research groups in Europe, America, and Australia are thus extensively involved in exploration of novel microalgal strain. Further, genetic engineering provides a tool to engineer the native strain resulting in transgenic strain with higher yields. Despite these efforts, no consensus has yet been reached so far in zeroing on the best microalgal strain for sustainable production of biofuel at reasonable cost. The search for novel microalgal strain and transgenesis of microalgae, are continuing side by side with the hope of commercial scale production of microalgae biofuel in near future. However, no consolidated review report exists which guides to isolate and identify a uncontaminated microalgal strain along with their transgenesis. The present review is focused on: (i) key factors for sample collection, isolation, and identification to

Abstracts of the 48. Brazilian congress on genetics. Genetics in social inclusion

International Nuclear Information System (INIS)

2002-01-01

Use of radioisotopes and ionizing radiations in genetics is presented. Several aspects related to men, animals, plants and microorganisms are reported highlighting biological radiation effects, evolution, mutagenesis and genetic engineering. Genetic mapping, polymerase chain reaction, gene mutations, genetic diversity, DNA hybridization, DNA sequencing, plant cultivation and plant grow are studied as well

Artificial Neural Networks and the Mass Appraisal of Real Estate

Directory of Open Access Journals (Sweden)

Gang Zhou

2018-03-01

Full Text Available With the rapid development of computer, artificial intelligence and big data technology, artificial neural networks have become one of the most powerful machine learning algorithms. In the practice, most of the applications of artificial neural networks use back propagation neural network and its variation. Besides the back propagation neural network, various neural networks have been developing in order to improve the performance of standard models. Though neural networks are well known method in the research of real estate, there is enormous space for future research in order to enhance their function. Some scholars combine genetic algorithm, geospatial information, support vector machine model, particle swarm optimization with artificial neural networks to appraise the real estate, which is helpful for the existing appraisal technology. The mass appraisal of real estate in this paper includes the real estate valuation in the transaction and the tax base valuation in the real estate holding. In this study we focus on the theoretical development of artificial neural networks and mass appraisal of real estate, artificial neural networks model evolution and algorithm improvement, artificial neural networks practice and application, and review the existing literature about artificial neural networks and mass appraisal of real estate. Finally, we provide some suggestions for the mass appraisal of China's real estate.

Domesticated, Genetically Engineered, and Wild Plant Relatives Exhibit Unintended Phenotypic Differences: A Comparative Meta-Analysis Profiling Rice, Canola, Maize, Sunflower, and Pumpkin

Directory of Open Access Journals (Sweden)

Alejandra Hernández-Terán

2017-12-01

Full Text Available Agronomic management of plants is a powerful evolutionary force acting on their populations. The management of cultivated plants is carried out by the traditional process of human selection or plant breeding and, more recently, by the technologies used in genetic engineering (GE. Even though crop modification through GE is aimed at specific traits, it is possible that other non-target traits can be affected by genetic modification due to the complex regulatory processes of plant metabolism and development. In this study, we conducted a meta-analysis profiling the phenotypic consequences of plant breeding and GE, and compared modified cultivars with wild relatives in five crops of global economic and cultural importance: rice, maize, canola, sunflower, and pumpkin. For these five species, we analyzed the literature with documentation of phenotypic traits that are potentially related to fitness for the same species in comparable conditions. The information was analyzed to evaluate whether the different processes of modification had influenced the phenotype in such a way as to cause statistical differences in the state of specific phenotypic traits or grouping of the organisms depending on their genetic origin [wild, domesticated with genetic engineering (domGE, and domesticated without genetic engineering (domNGE]. In addition, we tested the hypothesis that, given that transgenic plants are a construct designed to impact, in many cases, a single trait of the plant (e.g., lepidopteran resistance, the phenotypic differences between domGE and domNGE would be either less (or inexistent than between the wild and domesticated relatives (either domGE or domNGE. We conclude that (1 genetic modification (either by selective breeding or GE can be traced phenotypically when comparing wild relatives with their domesticated relatives (domGE and domNGE and (2 the existence and the magnitude of the phenotypic differences between domGE and domNGE of the same crop

Genetic engineering of a temperate phage-based delivery system for CRISPR/Cas9 antimicrobials against Staphylococcus aureus.

Science.gov (United States)

Park, Joo Youn; Moon, Bo Youn; Park, Juw Won; Thornton, Justin A; Park, Yong Ho; Seo, Keun Seok

2017-03-21

Discovery of clustered, regularly interspaced, short palindromic repeats and the Cas9 RNA-guided nuclease (CRISPR/Cas9) system provides a new opportunity to create programmable gene-specific antimicrobials that are far less likely to drive resistance than conventional antibiotics. However, the practical therapeutic use of CRISPR/Cas9 is still questionable due to current shortcomings in phage-based delivery systems such as inefficient delivery, narrow host range, and potential transfer of virulence genes by generalized transduction. In this study, we demonstrate genetic engineering strategies to overcome these shortcomings by integrating CRISPR/Cas9 system into a temperate phage genome, removing major virulence genes from the host chromosome, and expanding host specificity of the phage by complementing tail fiber protein. This significantly improved the efficacy and safety of CRISPR/Cas9 antimicrobials to therapeutic levels in both in vitro and in vivo assays. The genetic engineering tools and resources established in this study are expected to provide an efficacious and safe CRISPR/Cas9 antimicrobial, broadly applicable to Staphylococcus aureus.

[Effect of gene optimization on the expression and purification of HDV small antigen produced by genetic engineering].

Science.gov (United States)

Ding, Jun-Ying; Meng, Qing-Ling; Guo, Min-Zhuo; Yi, Yao; Su, Qiu-Dong; Lu, Xue-Xin; Qiu, Feng; Bi, Sheng-Li

2012-10-01

To study the effect of gene optimization on the expression and purification of HDV small antigen produced by genetic engineering. Based on the colon preference of E. coli, the HDV small antigen original gene from GenBank was optimized. Both the original gene and the optimized gene expressed in prokaryotic cells, SDS-PAGE was made to analyze the protein expression yield and to decide which protein expression style was more proportion than the other. Furthermore, two antigens were purified by chromatography in order to compare the purity by SDS-PAGE and Image Lab software. SDS-PAGE indicated that the molecular weight of target proteins from two groups were the same as we expected. Gene optimization resulted in the higher yield and it could make the product more soluble. After chromatography, the purity of target protein from optimized gene was up to 96.3%, obviously purer than that from original gene. Gene optimization could increase the protein expression yield and solubility of genetic engineering HDV small antigen. In addition, the product from the optimized gene group was easier to be purified for diagnosis usage.

Control of bovine spongiform encephalopathy by genetic engineering: possible approaches and regulatory considerations

International Nuclear Information System (INIS)

Gavora, J.S.; Kochhar, H.P.S.; Gifford, G.A.

2005-01-01

Transmissible spongiform encephalopathies (TSE) include bovine spongiform encephalopathy (BSE), scrapie in sheep and Creutzfeldt-Jakob disease (CJD) in humans. A new CJD variant (nvCJD) is believed to be related to consumption of meat from BSE cattle. In TSE individuals, prion proteins (PrP) with approximately 250 amino acids convert to the pathogenic prion PrP Sc , leading to a dysfunction of the central neural system. Research elsewhere with mice has indicated a possible genetic engineering approach to the introduction of BSE resistance: individuals with amino acid substitutions at positions 167 or 218, inoculated with a pathogenic prion protein, did not support PrP Sc replication. This raises the possibility of producing prion-resistant cattle with a single PrP amino acid substitution. Since prion-resistant animals might still harbour acquired prion infectivity, regulatory assessment of the engineered animals would need to ascertain that such possible 'carriers' do not result in a threat to animal and human health. (author)

Exploring the Properties of Genetically Engineered Silk-Elastin-Like Protein Films.

Science.gov (United States)

Machado, Raul; da Costa, André; Sencadas, Vitor; Pereira, Ana Margarida; Collins, Tony; Rodríguez-Cabello, José Carlos; Lanceros-Méndez, Senentxu; Casal, Margarida

2015-12-01

Free standing films of a genetically engineered silk-elastin-like protein (SELP) were prepared using water and formic acid as solvents. Exposure to methanol-saturated air promoted the formation of aggregated β-strands rendering aqueous insolubility and improved the mechanical properties leading to a 10-fold increase in strain-to-failure. The films were optically clear with resistivity values similar to natural rubber and thermally stable up to 180 °C. Addition of glycerol showed to enhance the flexibility of SELP/glycerol films by interacting with SELP molecules through hydrogen bonding, interpenetrating between the polymer chains and granting more conformational freedom. This detailed characterization provides cues for future and unique applications using SELP based biopolymers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms

Science.gov (United States)

Gladwin, D.; Stewart, P.; Stewart, J.

2011-02-01

This article addresses the problem of maintaining a stable rectified DC output from the three-phase AC generator in a series-hybrid vehicle powertrain. The series-hybrid prime power source generally comprises an internal combustion (IC) engine driving a three-phase permanent magnet generator whose output is rectified to DC. A recent development has been to control the engine/generator combination by an electronically actuated throttle. This system can be represented as a nonlinear system with significant time delay. Previously, voltage control of the generator output has been achieved by model predictive methods such as the Smith Predictor. These methods rely on the incorporation of an accurate system model and time delay into the control algorithm, with a consequent increase in computational complexity in the real-time controller, and as a necessity relies to some extent on the accuracy of the models. Two complementary performance objectives exist for the control system. Firstly, to maintain the IC engine at its optimal operating point, and secondly, to supply a stable DC supply to the traction drive inverters. Achievement of these goals minimises the transient energy storage requirements at the DC link, with a consequent reduction in both weight and cost. These objectives imply constant velocity operation of the IC engine under external load disturbances and changes in both operating conditions and vehicle speed set-points. In order to achieve these objectives, and reduce the complexity of implementation, in this article a controller is designed by the use of Genetic Programming methods in the Simulink modelling environment, with the aim of obtaining a relatively simple controller for the time-delay system which does not rely on the implementation of real time system models or time delay approximations in the controller. A methodology is presented to utilise the miriad of existing control blocks in the Simulink libraries to automatically evolve optimal control

Current progress and challenges in engineering viable artificial leaf for solar water splitting

Directory of Open Access Journals (Sweden)

Phuc D. Nguyen

2017-12-01

Full Text Available Large scale production of H2, a clean fuel, can be realized with just water and solar light energy by employing a viable energy conversion device called artificial leaf. In this tutorial review, we discuss on advances achieved recently and technical challenges remained toward the creation of such a leaf. Development of key components like catalysts for water electrolysis process and light harvester for harvesting solar energy as well as strategies being developed for assembling these components to create a complete artificial leaf will be highlighted.

Artificial Consciousness or Artificial Intelligence

OpenAIRE

Spanache Florin

2017-01-01

Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

Artificial Bee Colony Algorithm for Transient Performance Augmentation of Grid Connected Distributed Generation

Science.gov (United States)

Chatterjee, A.; Ghoshal, S. P.; Mukherjee, V.

In this paper, a conventional thermal power system equipped with automatic voltage regulator, IEEE type dual input power system stabilizer (PSS) PSS3B and integral controlled automatic generation control loop is considered. A distributed generation (DG) system consisting of aqua electrolyzer, photovoltaic cells, diesel engine generator, and some other energy storage devices like flywheel energy storage system and battery energy storage system is modeled. This hybrid distributed system is connected to the grid. While integrating this DG with the onventional thermal power system, improved transient performance is noticed. Further improvement in the transient performance of this grid connected DG is observed with the usage of superconducting magnetic energy storage device. The different tunable parameters of the proposed hybrid power system model are optimized by artificial bee colony (ABC) algorithm. The optimal solutions offered by the ABC algorithm are compared with those offered by genetic algorithm (GA). It is also revealed that the optimizing performance of the ABC is better than the GA for this specific application.

Application of artificial neural networks to improve power transfer ...

African Journals Online (AJOL)

Application of artificial neural networks to improve power transfer capability through OLTC. ... International Journal of Engineering, Science and Technology ... Numerical results show that the setting of OLTC transformer in terms of the load model has a major effect on the maximum power transfer in power systems and the ...

Advances in Computer Science and Engineering

CERN Document Server

Second International Conference on Advances in Computer Science and Engineering (CES 2012)

2012-01-01

This book includes the proceedings of the second International Conference on Advances in Computer Science and Engineering (CES 2012), which was held during January 13-14, 2012 in Sanya, China. The papers in these proceedings of CES 2012 focus on the researchers’ advanced works in their fields of Computer Science and Engineering mainly organized in four topics, (1) Software Engineering, (2) Intelligent Computing, (3) Computer Networks, and (4) Artificial Intelligence Software.

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

Directory of Open Access Journals (Sweden)

Marocchi Alessandro

2008-05-01

Full Text Available Abstract Background Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Results Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31% and from 69.1 to 86.2% (average 76.6% respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%. This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background.

Science.gov (United States)

Penco, Silvana; Buscema, Massimo; Patrosso, Maria Cristina; Marocchi, Alessandro; Grossi, Enzo

2008-05-30

Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial

Artificial Intelligence Research at General Electric

OpenAIRE

Sweet, Larry

1985-01-01

General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors. Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-tim...

Genetic algorithms used to optimize an artificial neural network design used in neutron spectrometry

International Nuclear Information System (INIS)

Arteaga A, T.; Ortiz R, J. M.; Vega C, H. R.

2016-10-01

Artificial neural networks (Ann) are widely used; it which consist of an input layer, one or more hidden layers and an output layer; these layers contain neurons and each has connections called weights, where the knowledge are allowed and let to Ann solve problems proposed. These Ann is used to reconstruction of the energy spectrum of neutrons from count rates and develop Bonner sphere neutron dosimetry. Currently, we have developed Ann with high performance and generalization ability. Determine your optimal architecture is usually a difficult task, an exhaustive search of all possible combinations of parameters is rarely possible further training of the neural network with random initial weights can cause two major drawbacks: it can stuck in local minima or converge very slowly. In this project it will be used Genetic Algorithms (Ga); which are based on the principle or analogy of evolution through natural selection and has shown to be very effective in optimizing complex search functions and large spaces or to find a near optimal overall efficiency. The aim is to decrease the architecture in number of hidden neurons and therefore the total number of connections is reducing. The benefits obtained by optimizing the network are that the number of connections would be considerably smaller and thus the computational complexity, hardware integration, resources will be lower such that will allow to be even more viable implemented. To use the Ga three problems must be solve: 1) coding the problem into chromosomes. 2) Construct a fitness function. 3) Proper selection of genetic operators; crossover, selection, mutation. As a result, the scientific knowledge obtained can to be applied to similar problems having a reference parameters used and their impact on the optimization would to be generated. It concluded that the input layer and output are subject to the problem; the Ga propose the optimal number of neurons in the hidden layer without losing the quality of the

Liquefaction Microzonation of Babol City Using Artificial Neural Network

DEFF Research Database (Denmark)

Farrokhzad, F.; Choobbasti, A.J.; Barari, Amin

2012-01-01

that will be less susceptible to damage during earthquakes. The scope of present study is to prepare the liquefaction microzonation map for the Babol city based on Seed and Idriss (1983) method using artificial neural network. Artificial neural network (ANN) is one of the artificial intelligence (AI) approaches...... microzonation map is produced for research area. Based on the obtained results, it can be stated that the trained neural network is capable in prediction of liquefaction potential with an acceptable level of confidence. At the end, zoning of the city is carried out based on the prediction of liquefaction...... that can be classified as machine learning. Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. In order to address the collective knowledge built-up in conventional liquefaction engineering, an alternative general regression neural network model...

A glossary of terms in measuring and automation engineering

International Nuclear Information System (INIS)

Schruefer, E.

1992-01-01

This German-language glossary has been compiled by cooperative work of more than sixty authors. It contains 1800 terms and their definitions relating to measuring engineering, sensor science and engineering, testing engineering, display and read-out techniques, physical quantities, control systems, fundamentals of control engineering, engineered reliability, process control engineering, robot technology, artificial intelligence and expert systems, simulation and modelling, navigation, electronic and electromechanical components, and microtechnology. (RHM) [de

The Slippery Slope Argument in the Ethical Debate on Genetic Engineering of Humans.

Science.gov (United States)

Walton, Douglas

2017-12-01

This article applies tools from argumentation theory to slippery slope arguments used in current ethical debates on genetic engineering. Among the tools used are argumentation schemes, value-based argumentation, critical questions, and burden of proof. It is argued that so-called drivers such as social acceptance and rapid technological development are also important factors that need to be taken into account alongside the argumentation scheme. It is shown that the slippery slope argument is basically a reasonable (but defeasible) form of argument, but is often flawed when used in ethical debates because of failures to meet the requirements of its scheme.

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

Science.gov (United States)

Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

2018-02-01

Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising

Artificial Virus as Trump-card to Resolve Exigencies in Targeted Gene Delivery.

Science.gov (United States)

Ajithkumar, K C; Pramod, Kannissery

2018-01-01

Viruses are potent pathogens that can effectively deliver the genetic material to susceptible host cells. This capability is beneficially utilized to successfully deliver the genetic material. However, the use of virus mediated gene delivery is considered divisive, because the potentially replicable genomes recombine or integrate with the cell DNA resulting in immunogenicity, ranging from inflammation to death. Thus, the need for potentially effective non-viral gene delivery vehicles arises. Non-viral vectors, protein only particles and virus like particles (VLP) can be constructed which contain all the necessary functional moieties. These resemble viruses and are called artificial or synthetic virus. The artificial virus eliminates the disadvantages of viral vectors but retain the beneficial effects of the viruses. Need for further functionalization can be avoided by this approach because incorporation of requisite agents such as cell ligands, membrane active peptides, etc. into proteins is possible. The protein- DNA complexes resemble bacterial inclusion bodies. Nucleic acids influence conformation of protein units which subsequently result in cell uptake and finally to the cell nucleus. Such tunable systems mimic the activities of infected viruses and are used for the safe and effective delivery of drugs and genetic material in gene therapy. The versatility, stability and biocompatible nature of artificial virus along with high transfection efficacy have made it favorite for gene delivery purposes, in addition to being useful for various biomedical and drug delivery applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.