197,657 research outputs found
Fomeshi, Behnam M. The Persian Whitman: Beyond a Literary Reception. Leiden: Leiden University Press, 2019, 256 pp.
No full text[ES]Reseña de Fomeshi, Behnam M. The Persian Whitman: Beyond a Literary Reception
Green Apples, Red Apples: Politics of Comparative Literature in Iran
No full textFomeshi, Behnam M. “Green Apples, Red Apples: Politics of Comparative Literature in Iran.” Comparative Literature Around the World: Global Practice. Eds. Eugene Eoyang, Gang Zhou, and Jonathan Hart. Paris: Honoré Champion, 2021. 201-218
Behnam M. Fomeshi. <i>The Persian Whitman: Beyond a Literary Reception</i>.
No full textReview of Behnam Fomeshi, The Persian Whitman: Beyond a Literary Reception
Visual perceptual learning of feature conjunctions leverages non-linear mixed selectivity
No full textAbstract Visual objects are often defined by multiple features. Therefore, learning novel objects entails learning feature conjunctions. Visual cortex is organized into distinct anatomical compartments, each of which is devoted to processing a single feature. A prime example are neurons purely selective to color and orientation, respectively. However, neurons that jointly encode multiple features (mixed selectivity) also exist across the brain and play critical roles in a multitude of tasks. Here, we sought to uncover the optimal policy that our brain adapts to achieve conjunction learning using these available resources. 59 human subjects practiced orientation-color conjunction learning in four psychophysical experiments designed to nudge the visual system towards using one or the other resource. We find that conjunction learning is possible by linear mixing of pure color and orientation information, but that more and faster learning takes place when both pure and mixed selectivity representations are involved. We also find that learning with mixed selectivity confers advantages in performing an untrained “exclusive or” (XOR) task several months after learning the original conjunction task. This study sheds light on possible mechanisms underlying conjunction learning and highlights the importance of learning by mixed selectivity
Supplementary_Data - The effects of functionalization of carbon nanotubes on toxicological parameters in mice
No full textSupplementary_Data for The effects of functionalization of carbon nanotubes on toxicological parameters in mice by E Mohammadi, M Zeinali, M Mohammadi-Sardoo, M Iranpour, B Behnam and A Mandegary in Human & Experimental Toxicology</p
Supplementary_Data - The effects of functionalization of carbon nanotubes on toxicological parameters in mice
No full textSupplementary_Data for The effects of functionalization of carbon nanotubes on toxicological parameters in mice by E Mohammadi, M Zeinali, M Mohammadi-Sardoo, M Iranpour, B Behnam and A Mandegary in Human & Experimental Toxicology</p
GPU-Accelerated soft error rate analysis of large-scale integrated circuits
No full textIn this article, a team of researchers from Shiraz University and the Shahid Bahonar University of Kerman, Iran, investigates soft error rate (SER) estimation. They propose an analytical framework to estimate SER accurately and an implementation on graphic processing units (GPUs) that is able to scale to circuits composed of thousands of gates. The framework exploits several levels of parallelism in the SER estimation process to map it efficiently onto GPUs.</p
Synthesis of optimal interfaces for hierarchical scheduling with resources
No full textThis paper presents algorithms that (1) facilitate systemindependent synthesis of timing-interfaces for subsystems and (2) system-level selection of interfaces to minimize CPU load. The results presented are developed for hierarchical fixed-priority scheduling of subsystems that may share logical recourses (i.e., semaphores). We show that the use of shared resources results in a tradeoff problem, where resource locking times can be traded for CPU allocation, complicating the problem of finding the optimal interface configuration subject to scheduability. This paper presents a methodology where such a tradeoff can be effectively explored. It first synthesizes a bounded set of interface-candidates for each subsystem, independently of the final system, such that the set contains the interface that minimizes system load for any given system. Then, integrating subsystems into a system, it finds the optimal selection of interfaces. Our algorithms have linear complexity to the number of tasks involved. Thus, o r approach is also suitable for adaptable and reconfigurable systems. ? 2008 IEEE
Protective effects of curcumin against aflatoxicosis: A comprehensive review.
No full textAflatoxicosis is a deleterious medical condition that results from aflatoxins (AFs) or ochratoxins (OTs). Contamination with these toxins exerts detrimental effects on the liver, kidneys, reproductive organs, and also on immunological and cardiovascular systems. Aflatoxicosis is closely associated with overproduction of reactive oxygen species (ROS) as key contributors to oxidative and nitrosative stress responses, and subsequent damages to lipids, proteins, RNA, and DNA. The main target organ for AF toxicity is the liver, where DNA adducts, degranulation of endoplasmic reticulum, increased hepatic lipid peroxide, GSH depletion, mitochondrial dysfunction, and reduction of enzymatic and non-enzymatic antioxidants are manifestations of aflatoxicosis. Curcuma longa L. (turmeric) is a medicinal plant widely utilized all over the world for culinary and phytomedical purposes. Considering the antioxidant characteristic of curcumin, the main active component of turmeric, this review is intended to critically summarize the available evidence supporting possible effectiveness of curcumin against aflatoxicosis. Curcumin can serve as a promising candidate for attenuation of the adverse consequences of aflatoxicosis, acting mainly through intrinsic antioxidant effects aroused from its structure, modulation of the immune system as reflected by interleukin-1 and transforming growth factor-, and interfering with AF's biotransformation by cytochrome P450 isoenzymes CYP1A, CYP3A, CYP2A, CYP2B, and CYP2C
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