Block QCA Fault-Tolerant Logic Gates

Suitably patterned arrays (blocks) of quantum-dot cellular automata (QCA) have been proposed as fault-tolerant universal logic gates. These block QCA gates could be used to realize the potential of QCA for further miniaturization, reduction of power consumption, increase in switching speed, and increased degree of integration of very-large-scale integrated (VLSI) electronic circuits. The limitations of conventional VLSI circuitry, the basic principle of operation of QCA, and the potential advantages of QCA-based VLSI circuitry were described in several NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35; and Hybrid VLSI/QCA Architecture for Computing FFTs (NPO-20923), which follows this article. To recapitulate the principle of operation (greatly oversimplified because of the limitation on space available for this article): A quantum-dot cellular automata contains four quantum dots positioned at or between the corners of a square cell. The cell contains two extra mobile electrons that can tunnel (in the quantummechanical sense) between neighboring dots within the cell. The Coulomb repulsion between the two electrons tends to make them occupy antipodal dots in the cell. For an isolated cell, there are two energetically equivalent arrangements (denoted polarization states) of the extra electrons. The cell polarization is used to encode binary information. Because the polarization of a nonisolated cell depends on Coulomb-repulsion interactions with neighboring cells, universal logic gates and binary wires could be constructed, in principle, by arraying QCA of suitable design in suitable patterns. Heretofore, researchers have recognized two major obstacles to realization of QCA-based logic gates: One is the need for (and the difficulty of attaining) operation of QCA circuitry at room temperature or, for that matter, at any temperature above a few Kelvins. It has been theorized that room-temperature operation could be made possible by constructing QCA as molecular-scale devices. However, in approaching the lower limit of miniaturization at the molecular level, it becomes increasingly imperative to overcome the second major obstacle, which is the need for (and the difficulty of attaining) high precision in the alignments of adjacent QCA in order to ensure the correct interactions among the quantum dots

Hybrid VLSI/QCA Architecture for Computing FFTs

A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes

Technical and Environmental Impacts of Coal Waste Used as a Soil Stabilizer in Construction Projects of Forest Roads

Many pozzolans are waste products from industrial processes. Every year a huge amount of coal waste is gathered from the coal washing plant in the Hyrcanian forests of Iran. These materials can be used for soil stabilization in construction and maintenance projects of forest roads. This paper aims to (a) investigate the role of coal waste (CW) as a soil stabilizer and (b) determine the changes in soil specification regarding the environmental pollution in different combinations of materials (soil, lime (4 and 6%) and CW (3, 6, 9 and 12%)). For this purpose, different technical and environmental analysis and laboratory tests were performed. Technical tests showed that the soil liquid limit and maximum dry density decreased with an increase in lime and CW contents. Addition of CW could increase the soil CBR, UCS and OMC. According to XRD test, the addition of CW and lime can increase the size of crystals in stabilized soil samples. Environmental analysis showed that the use of stabilizer significantly reduced the concentration of heavy metals such as Cd, Cr and Pb. Also, all of the metal concentrations leached from samples satisfied the required criteria, but the addition of lime and CW increased the concentration of N, P, and K. These changes can increase the invasive species consistent with calcareous soil conditions along the roads. According to the results, the combination of coal waste and lime can be one of the best methods for in situ remediation. It would, however, be better to use a minimum amount of stabilizer in pavement layers of access roads due to environmental sensitivity

Optimum Utilization of Rice Husk Ash for Stabilization of Sub-base Materials in Construction and Repair Project of Forest Roads

Forest roads play an important role in forest management, timber transportation and forest protection. However, minimum standards are considered for pavement materials due to the traffic volume and economic situation of forestry projects. Therefore, this paper aims to (a) evaluate the role of Rice Husk Ash (RHA) as a soil stabilizer of sub-base layer to improve the quality of materials and (b) determine the optimum utilization among 10 combinations of soil, lime and RHA regarding the environmental factors. The results of laboratory studies on soil A–6 (AASHTOO classification) indicates a general decrease in the maximum dry density (MDD) and an increase (21.9%) in optimum moisture content (OMC) with increase in RHA content. Adding RHA (9%) causes a decrease (13.3%) in liquid limit and plasticity index (PI) of soil. However, this improving effect is not as much as the influence of lime. The California bearing ratio (CBR) of stabilized soil in both saturated condition and optimum water content was 28% and 37.5% more than the natural soil, respectively. The maximum unconfined compressive strength (UCS) values were recorded for 9% RHA, 237 KN m-2 after 28 days curing time, which was 23 KN m-2 more than the natural soil. According to the results, the combination of Soil+4% Lime+9% RHA could be used as the optimum consumption of materials for stabilization of sub-base layer in construction of forest roads

Slope stability analysis considering weight of trees and root reinforcement

We study the effect of roots of alder trees on soil reinforcement and slope stabilization. Two types of soil, i.e. Marl and Clayey soils and alders of three ages are considered. The slope stability is studied according to the tree indices based on tree age and soil type. The effect of root reinforcement on slope stability is considered by an additional cohesion. The stability analyses are carried out by the FEM. We perform parameter studies considering tree age, soil type and surcharge. The results indicate that soil type is effective on cohesion. The results also showed that with increasing age of trees from 7 to 15 years, the amount of additional root cohesion increased and with the increase of the age of trees to 20 years this amount slightly decreased. Also, with regard to a constant slope geometry, the type of soil and the uniform surcharge pressure, 7-year-old trees have shown better performance in slope stabilization. It has been observed that as the age of alder trees grows, although the amount of additional root cohesion increases, however, due to increased surcharge pressure, the overall slope stability factor decreases

Machine Learning Approaches to predict Intra-Uterine Insemination Success Rate- Application of Artificial Intelligence in Infertility

Introduction: Assisted Reproductive Technology (ART) has been widely utilized for infertility management. Despite its low success rate, Intra-Uterine Insemination (IUI) is one of the first alternatives and most important approaches regarding many cases of infertility treatment. Given the numerous influencing factors and limitations associated with time and resources, the development of a reliable model to predict the success rate of ART methods can significantly contribute to decision-making processes. Materials and methods: We reviewed the demographic, clinical, and laboratory data regarding 157 IUI treatment cycles among 124 women using their partner’s sperm from May2017 to June2019. Primary outcome measures were clinical pregnancy and live birth. Some prediction models were constructed and compared to the logistic regression analysis. Results: Woman’s mean age was 30.1 ± 5.2 years and the infertility had a female cause in 24.3% of the cases, male cause in 32.6% of cases, and combined causes in 32.6% of the cases. Concerning the first IUI cycle, the clinical pregnancy rate per cycle was 16.9% (N= 21). Data were prepared according to cross-industry standard process for data mining (CRISP-DM) methodology, and the following models were fitted to the data: J48 Decision Tree, Perceptron Multilayer (MLP) Neural Network, Support Vector Machine (SVM) with radial basis function (RBF) kernel, K-Nearest Neighbors (KNN) with one neighborhood, and Bayesian Network. J48 Decision Tree, with a sensitivity of 95% and specificity of 98%, had the most optimal performance, and the KNN model was the weakest one. Conclusion: To predict the results of IUI as a simple and less invasive therapy for infertile couples, some models were applied based on artificial intelligence and J48 Decision Tree was recommended

In vitro models and systems for evaluating the dynamics of drug delivery to the healthy and diseased brain

The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and transport of drugs to the brain. The conventional animal and Transwell BBB models along with emerging microfluidic-based BBB-on-chip systems have provided fundamental functionalities of the BBB and facilitated the testing of drug delivery to the brain tissue. However, developing biomimetic and predictive BBB models capable of reasonably mimicking essential characteristics of the BBB functions is still a challenge. In addition, detailed analysis of the dynamics of drug delivery to the healthy or diseased brain requires not only biomimetic BBB tissue models but also new systems capable of monitoring the BBB microenvironment and dynamics of barrier function and delivery mechanisms. This review provides a comprehensive overview of recent advances in microengineering of BBB models with different functional complexity and mimicking capability of healthy and diseased states. It also discusses new technologies that can make the next generation of biomimetic human BBBs containing integrated biosensors for real-time monitoring the tissue microenvironment and barrier function and correlating it with the dynamics of drug delivery. Such integrated system addresses important brain drug delivery questions related to the treatment of brain diseases. We further discuss how the combination of in vitro BBB systems, computational models and nanotechnology supports for characterization of the dynamics of drug delivery to the brain. © 2018 Elsevier B.V

Curcumin and Berberine Arrest Maturation and Activation of Dendritic CellsDerived from Lupus Erythematosus Patients

Background: Systemic lupus erythematosus (SLE) is a complex autoimmune disease recognized by elevated activity of autoimmune cells, loss of tolerance, and decreased regulatory T cells producing inhibitory cytokines. Despite many efforts, the definitive treatment for lupus has not been fully understood. Curcumin (CUR) and berberine (BBR) have significant immunomodulatory roles and anti-inflammatory properties that have been demonstrated in various studies. This study aimed to investigate the anti-inflammatory properties of CUR and BBR on human monocyte-derived dendritic cells (DCs) with an special focus on the maturation and activation of DCs. Methods: Human monocytes were isolated from the heparinized blood of SLE patients and healthy individuals, which were then exposed to cytokines (IL-4 and GM-CSF) for five days to produce immature DCs. Then, the obtained DCs were characterized by FITC-uptake assay and then cultured in the presence of CUR, BBR, or lipopolysaccharide (LPS) for 48 h. Finally, the maturation of DCs was analyzed by the level of maturation using flow cytometry or real-time PCR methods. Results: The results showed promising anti-inflammatory effects of CUR and BBR in comparison with LPS, supported by a significant reduction of not only co-stimulatory and antigen-presenting factors such as CD80, CD86, CD83, CD1a, CD14, and HLA-DR but also inflammatory cytokines such as IL-12. Conclusion: CUR and BBR could arrest DC maturation and develop a tolerogenic DC phenotype that subsequently promoted the expression of inhibitory cytokines and reduced the secretion of proinflammatory markers