There are two approaches for simulating Memory as well as learning in artificial intelligence; the functionalistic approach and the cognitive approach. The necessary condition to put the second approach into account is to provide a model of brain activity that contains a quite good congruence with observational facts such as mistakes and forgotten experiences. Given that human Memory has a solid core that includes the components of our identity, our family and our hometown, the major and determinative events of our lives, and the countless repeated and accepted facts of our culture, the more we go to the peripheral spots the data becomes flimsier and more easily exposed to oblivion. It was essential to propose a model in which the topographical differences are quite distinguishable. In our proposed model, we have translated this topographical situation into quantities, which are attributed to the nodes. The result is an edge-weighted graph with mass-based values on the nodes which demonstrates the importance of each atomic proposition, as a truth, for an intelligent being. Furthermore, it dynamically develops and modifies, and in successive phases, it changes the mass of the nodes and weight of the edges depending on gathered inputs from the environment.

Hash or B-Tree based composite indexes, are the two most commonly used techniques for searching and re-trieving data from Memory. Although these techniques have a serious Memory limitation, that restricts free-dom to search by any combination of single key/data attribute, that comprises the composite search key, the techniques are still accepted considering the trade o s with better performance on insert and update opera-tions. But when the data is semi-Static, which does not change often, there is a need and scope for a better tech-nique that provides the exibility and freedom to e-ciently search by any possible key, without creating any composite index. This paper explains such algorithmic technique along with its data structures.

This paper introduces a peculiar approach of designing Static Random Access Memory (SRAM) Memory cell in Quantum-dot Cellular Automata (QCA) technique. The proposed design consists of one 3-input MG, one 5-input MG in addition to a (2×1) Multiplexer block utilizing the loop-based approach. The simulation results reveals the excellence of the proposed design. The proposed SRAM cell achieves 16% and 15% improvement in terms of total number of Cell counts and Area. Similarly, the proposed design structure realizes the overall power dissipation savings up to 35. 3% at maximum energy dissipation of circuit, 38. 6% at average energy dissipation of circuit, 36. 1% at minimum energy dissipation of circuit, 36. 4% at average energy dissipation of circuit and 40. 1% at average switching energy dissipation compared to the latest reported designs. The power analysis and structural analysis of the proposed design is compared with its state-of-the-art counterpart designs, using QCAPro and QCADesigner 2. 0. 3 tools. The proposed QCA based SRAM cell design can be taken as a base design in building an ultra-low power information generating systems like Microprocessors.

Background and Aim: The aim of the present study was to investigate the effect of the Hand Static Rest Splint on reducing the pain and other compliance of Rheumatoid Arthritis (RA). Materials and Methods: In the present clinical trial, 12 patients, aged 35-50 (average: 39 years) with RA, referring to the Occupational Therapy Unit of Taleghani hospital and meeting America College of Rheumatology diagnostic criteria, were included. Visual Analogue Scale (VAS) was administered and swelling, tenderness and morning stiffness were assessed. Moreover, assessments of active range of motion using goniometry and grip strength with Jamar dynamometer in both hands were performed. Statistical analysis of data was performed using t-test and Mann-Whitney Test for two independent samples and willcoxon tests and paired t-test for paired samples run in SPSS, version 18. The level of significance was set at p˂ 0. 05. Results: The findings showed that the Static Rest Splint led to improvement in the wrist range of motion (flexion p=0/005, extension p=0/03) when the two groups were compared, but it did not have a significant effect on Morning Stiffness (p=1), pain (p=0/1), Swelling (p=0/06), and Tenderness (p=0/2). However, when compared between after and before intervention in hand with splint, pain (p=0/02) and wrist range of motion (p=0/004) improved. Conclusion: Based on the findings of the current study, and since using splints only improve range of motion in the wrist compared between two groups and pain relief before and after the intervention, it seems that using hand Static Rest Splint to reduce other symptoms need further investigation and also given that the use of this position without stress on the tendon can be effective in reducing the causes deformity, further studies are needed to more delineate these points.

In this research article, an Ultra-low-power 1-bit SRAM cell is introduced using Tunneling Field Effect Transistor (TFET). This paper investigates feasible 6T SRAM configurations on improved N-type and P-type TFETs integrated on both InAs (Homojunction) and GaSb-InAs (Heterojunction) platforms. The voltage transfer characteristics and basic parameters of both Homo and Heterojunctions are examined and compared. The proposed TFET based SRAM enhances the stability in the hold, read, and write operations. This work evaluates the potential of TFET which can replace MOSFET due to the improved performance with low-power consumption, high speed, low sub-threshold slope, and supply voltage (VDD = 0.2 V). The results are correlated with CMOS 32nm technology. The proposed SRAM TFET cell is implemented using 30nm technology and simulated using an H-SPICE simulator with the help of Verilog-A models. The proposed SRAM TFET cell architecture achieves low power dissipation and attains high performance as compared to the CMOS and FINFET.

Shape Memory Alloys (SMAs) are a type of Shape Memory Materials (SMMs) which can recover large deformation and return to their primary shape by rising temperature. In this study, numerical simulation of thermo mechanical behavior of composites reinforced with shape Memory alloys under Static uniaxial loading was conducted. By inserting SMA wires inside the host composite the macro mechanical behavior of hybrid composite changed to a bilinear curve which is due to the phase transformation of SMA wires and nonlinear behavior of host composite. Simulated results are compared with available data in the literature.Validated model is used to evaluate the effect of various parameters as, wires pre-strain, temperature, interface conditions between SMA wires and Epoxy matrix on hybrid composite behavior. Also a theoretical method was developed to calculate the compressive and tensile strain induced in host composites and wires, after releasing of SMA wires. According to the results obtained, considering weak interface between SMAs wires and matrix improved simulation results rather than perfect bonding assumption. Pre-strained SMA wires would cause initial compressive stress in the host composite and its value will increased by increasing service temperature, however, it will increased interface separation of SMA and host materials, too.Therefore, in design of Shape Memory alloys hybrid composites, optimum amount of applied pre-strain on SMA wires and working temperature should be selected.

Fungi release wide spectrum of volatile organic compounds (VOCs) that belong to several chemical groups with different biochemical origins such as monoterpenes, sesquiterpenes, alcohols, aldehydes, aromatic compounds, esters, furans, ketones, sulfur and nitrogen compounds. Trichoderma species are the most studied fungal biocontrol agents and are successfully used as biofungicides and biofertilizers in greenhouse and field. Volatile metabolites play a key role in mycoparasitism of Trichoderma spp., as well as in their interactions with plants and other organisms in their environments. Based on the antibiotic activity of these fungi against the fungal pathogens, further consideration of their VOCs profiles, has been offered. In this study, VOCs of native Trichoderma species from Iran (T. harzianum, T. virens (6011), T. atroviridae (1-3)) have been identified by Static headspace gas chromatography-mass spectrometry The most of detected compounds were related to monoterpenes and sesquiterpenes. These are including; dl-limonene; beta-himachalene; beta-cubebene; cadinene; caryophyllene; alpha-gurjunene; farnesol; thujopsene; beta-bisabolene and alpha-farnesene. Based on antifungal effects of these compounds, biological control of these Trichoderma species can be related to them. These VOCs could be potential sources for purposes of chemotaxonomy and natural fungicides to protect crops from the fungal pathogens without environmental problems.

Background & Objective: In addition to pyramidal neurons and interneurons, the hippocampus contains Astrocytes that play important roles in regulating ion flux currents, energy production, neurotransmitter release and Memory. Learning needs some instrument for information storage and information maintenances mechanisms resemble to Memory. The aim of this study was determination of spatial Memory effect on the number of astrocytes in rat’s hippocampus.Materials & Methods: In this experimental study, with usage of Morris Water Maze and Reference Memory technique, we used 10 male albino wistar rats. 5 rats were in control group and 5 rats in Reference Memory group. After histological preparation, the slides were stained with PTAH staining for showing the Astrocytes. Results: The findings of this study showed significant difference in astrocytes number in CA1, CA2 and CA3 area of hippocampus between control and reference Memory group. The mean and SD of astrocytes in CA1, CA2 and CA3 of reference Memory group were 118.57±25.29, 58.91±23.59 and 116.6±31.14, that they are more than control group with 49±17.29 in CA1, 48.8±25.21 in CA2 and 41.95±11.22 in CA3. Conclusion: We concluded that the number of astrocytes increased due to spatial learning (e.g. reference Memory method).

With current progress in engineering science and in order to improve the performance of structures, the issue of strengthening of extant structures has caught many researchers’ attention due to different reasons such as application change, loading increase after construction, and modification of regulations. In this study, the role of pre-stressed cables made of steel and Nitinol in a steel beam under dynamic and Static loads along with some different mechanisms was examined. Initially, to locate optimal points, a three-floor structure was designed as the extant structure. Then, a beam was arbitrarily modeled using some different mechanisms that included strengthening with steel and Nitinol pre-stressed cables placed under the lower beam wing at the end of it in V-shaped form from the two sides of the beam to its center. Finally, the structure was analyzed and examined via non-linear Static and dynamic analysis of time history. The obtained results finally indicated a positive role of applied mechanisms in the steel beam. Further, the results also showed that the performance of steel beam strengthened with steel and Nitinol pre-stressed cables was better than that of the beam with steel cables. In general, it might be observed that the deflection of the beam center in Static and dynamic states had an average reduction of 55 and 60% when compared with the ordinary state.