123 research outputs found
The role of the amygdala in modulation and storage of emotional memories
No full textThe amygdala has long been known to play a critical role in emotional processing, in particular fear. In this respect it has been shown to play three major roles. First, it mediates the facilitating effects of emotional arousal in memory formation. Second, it is the site of storage for emotional memories themselves, in particular fear. And lastly, it mediates the expression of fear responses. The work presented in this thesis investigates each of these different functions of the amygdala. In the first chapter, I examined how glucocorticoids, which are known to enhance memory consolidation through their actions on the amygdala, affect the electrophysiological properties of the amygdala neurons. I show that glucocorticoids increase the excitability of principal amygdala neurons. In the second chapter, I investigated the role of REM sleep in consolidation of emotional memories. To this end, I examined the interactions between the amygdala, medial prefrontal cortex and hippocampus during sleep following fear learning. I show that theta coordination in this network during REM sleep participates in the consolidation of fear memories. In the third and fourth chapters, I investigated the role of the amygdala in storage and expression of fear memories. I show the different involvements of each amygdala nuclei in mediating conditioned fear expression. Lastly, I investigated the role of anxiety in fear learning. I show that anxiety can interfere with fear learning by resulting in fear generalization to safe cues and environments.Ph. D.Includes bibliographical referencesIncludes vitaby Sevil Duvarc
A course on biomimetic design strategies
No full textAlthough redesigning curricula by integrating the CAD tools into architectural education has been an ongoing interest, a new understanding towards solving design problems holistically should be investigated in architectural education. Because natural systems offer design strategies to increase performance and effectiveness with an extensive formal repertoire; incorporating multi-faceted biomimetic principles into the design process is necessary. It is critical to increase skills of students towards algorithmic thinking, as well as to deal with performance issues and sustainability. This paper aims to discuss an undergraduate elective course titled "Sustainable Design and Environment through Biomimicry" which was taught by the author in architectural degree program of Ozyegin University Faculty of Architecture and Design in Fall 2014-2015. Following the exploration of individual research topics, findings were implemented into design problems. The challenges encountered in the teaching process and future lines of the work are discussed in the paper
Prediction of microdrill breakage using rough sets
No full textAbstractThis study attempts to correlate the nonlinear invariants' with the changing conditions of a drilling process through a series of condition monitoring experiments on small diameter (1 mm) drill bits. Run-to-failure tests are performed on these drill bits, and vibration data are consecutively gathered at equal time intervals. Nonlinear invariants, such as the Kolmogorov entropy and correlation dimension, and statistical parameters are calculated based on the corresponding conditions of the drill bits. By intervariations of these values between two successive measurements, a drop–rise table is created. Any variation that is within a certain threshold (±20% of the measurements in this case) is assumed to be constant. Any fluctuation above or below is assumed to be either a rise or a drop. The reduct and conflict tables then help eliminate incongruous and redundant data by the use of rough sets (RSs). Inconsistent data, which by definition is the boundary region, are classified through certainty and coverage factors. By handling inconsistencies and redundancies, 11 rules are extracted from 39 experiments, representing the underlying rules. Then 22 new experiments are used to check the validity of the rule space. The RS decision frame performs best at predicting no failure cases. It is believed that RSs are superior in dealing with real-life data over fuzzy set logic in that actual measured data are never as consistent as here and may dominate the monitoring of the manufacturing processes as it becomes more widespread.</jats:p
Cost effective localization in distributed sensory networks
No full textThe most important mechanism to occur in biological distributed sensory networks (DSNs) is called lateral inhibition, (LI). LI relies on one simple principle. Each sensor strives to suppress its neighbors in proportion to its own excitation. In this study, LI mechanism is exploited to localize the unknown position of a light source that illuminated the photosensitive sensory network containing high and low quality sensors. Each photosensitive sensor was then calibrated to accurately read the distance to the light source. A series of experiments were conducted employing both quality sensors. Low quality array was allowed to take advantage of LI, whereas the high quality one was not. Results showed that the lateral inhibition mechanism increased the sensitivity of inferior quality sensors, giving the ability to make the localization as sensitive as high quality sensors do. This suggests that the networks with multitude of sensors could be made cost-effective, were these sensory networks equipped with LI
Intuitionistic fuzzy c control charts based on intuitionistic fuzzy ranking method for TIFNs
No full textControl charts are used to control the process in order to supply products with requested properties. Classical control charts are inadequate to control the process that contain vagueness and hesitancy. In this case, extensions of fuzzy set theory could be applied to the control charts. In this study, a novel intuitionistic fuzzy c control chart based on a ranking method for triangular intuitionistic fuzzy numbers is proposed for the first time in the literature. The novelty of the study is to use a novel ranking method to give all decisions about the process in a fuzzy environment for triangular intuitionistic fuzzy numbers. An application is implemented on a data set, and results are interpreted
Genetic transformation of common beans (Phaseolus vulgaris L.) through Agrobacterium tumefaciens carrying Cry1Ab gene
No full textBackground: Seed beetles are one of the most important causes of yield loss in bean production. It is essential to develop resistant varieties in the fight against these pests. Agrobacterium-based gene transformation is the most widely used breeding method worldwide to develop insect-resistant varieties. Methods and results: Embryonic axes and plumule explants were obtained from Agrobacterium tumefciens treated mature zygotic embryos of low and high raw protein-based common bean cultivars Akman 98 and Karacaşehir 90. Agrobacterium tumefaciens contained a synthetic Bacillus thuringiensis insecticidal crystal protein gene (Bt Cry1Ab) controlled by the 35S promoter and NOS terminator sequences. The transformation event was genotype and explant dependent. The plumule explants could not withstand kanamycin-based selection pressure and died. It was possible to get two transgenic plants using embryonic axis explants of low protein cultivar Akman 98. These results were validated using GUS analysis, PCR, RT-PCR, bioassay analysis, and ELISA test from the samples taken from T0 and T1 generations. Bioassay tests showed that these plants were protected from the damage of legume seed insects (Bruchus spp.). Conclusions: The results are very encouraging and may help in producing better transgenic common bean germplasm leading to safe agriculture and reducing environmental pollutions. © 2022, The Author(s), under exclusive licence to Springer Nature B.V
Trait-based heterogeneous populations plus (TbHP+) genetic algorithm
No full textThis study developed a variant of genetic algorithm (GA) model called the trait-based heterogeneous populations plus (TbHP+). The developed TbHP+ model employs a memory concept in the form of immunity and instinct to provide the populations with a more efficient guidance. Also, it has an ability to vary the number of individuals during the search process, thus allowing an automatic determination of the size of the population based on the individual qualities such as character fitness and credit for immunity. The algorithm was tested against the classical GA model in convergence and minimum error performance. For this purpose, 5 different mathematical functions from the literature were employed. The selected functions have different topological characteristics, ranging from simple convex curves with 2 variables to complex trigonometric ones having several hilly shapes with more than 2 variables. The developed model and the classical GA model were applied to finding the global minima of the functions. The comparison of the results revealed that the developed TbHP+ model outperformed the classical GA in faster convergence and minimum errors, which may be explained by the adaptive nature of the new paradigm
Cloud-Based Design Analysis and Optimization Framework
No full textIntegration of analysis into early design phases in support of improved building performance has become increasingly important. It is considered a required response to demands on contemporary building design to meet environmental concerns. The goal is to assist designers in their decision making throughout the design of a building but with growing focus on the earlier phases in design during which design changes consume less effort than similar changes would in later design phases or during construction and occupation.Multi-disciplinary optimization has the potential of providing design teams with information about the potential trade-offs between various goals, some of which may be in conflict with each other. A commonly used class of optimization algorithms is the class of genetic algorithms which mimic the evolutionary process. For effective parallelization of the cascading processes occurring in the application of genetic algorithms in multi-disciplinary optimization we propose a cloud implementation and describe its architecture designed to handle the cascading tasks as efficiently as possible
Graphical Smalltalk with My Optimization System for Urban Planning Tasks
No full textBased on the description of a conceptual framework for the representation of planning problems on various scales, we introduce an evolutionary design optimization system. This system is exemplified by means of the generation of street networks with locally defined properties for centrality. We show three different scenarios for planning requirements and evaluate the resulting structures with respect to the requirements of our framework. Finally the potentials and challenges of the presented approach are discussed in detail
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