Low-cost and two-cycle hardware structures of PRINCE lightweight block cipher

In this paper, low-cost and two-cycle hardware structures of the PRINCE lightweight block cipher are presented. In the first structure, we proposed an area-constrained structure, and in the second structure, a high-speed implementation of the PRINCE cipher is presented. The substitution box (S-box) and the inverse of S-box (S-box⁻¹) blocks are the most complex blocks in the PRINCE cipher. These blocks are designed by an efficient structure with low critical path delay. In the low-cost structure, the S-boxes and S-boxes⁻¹ are shared between the round computations and the intermediate step of PRINCE cipher. Therefore, the proposed architecture is implemented based on the lowest number of computation resources. The two-cycle implementation of PRINCE cipher is designed by a processing element (PE), which is a general and reconfigurable element. This structure has a regular form with the minimum number of the control signal. Implementation results of the proposed structures in 180-nm CMOS technology and Virtex-4 and Virtex-6 FPGA families are achieved. The proposed structures, based on the results, have better critical path delay and throughput compared with other's related works.     

Extracellular Vesicles in CNS Developmental Disorders

The central nervous system (CNS) is the most complex structure in the body, consisting of multiple cell types with distinct morphology and function. Development of the neuronal circuit and its function rely on a continuous crosstalk between neurons and non-neural cells. It has been widely accepted that extracellular vesicles (EVs), mainly exosomes, are effective entities responsible for intercellular CNS communication. They contain membrane and cytoplasmic proteins, lipids, non-coding RNAs, microRNAs and mRNAs. Their cargo modulates gene and protein expression in recipient cells. Several lines of evidence indicate that EVs play a role in modifying signal transduction with subsequent physiological changes in neurogenesis, gliogenesis, synaptogenesis and network circuit formation and activity, as well as synaptic pruning and myelination. Several studies demonstrate that neural and non-neural EVs play an important role in physiological and pathological neurodevelopment. The present review discusses the role of EVs in various neurodevelopmental disorders and the prospects of using EVs as disease biomarkers and therapeutics.     

New approach to unsupported ReS2 nanorod catalyst for upgrading of heavy crude oil using methane as hydrogen source

Highly active ReS₂ nanocatalysts were prepared by CVD method and characterized by XRD, BET -BJH, Raman spectroscopy, XPS, TPR, NH₃-TPD, SEM, and HRTEM techniques. Catalytic activities were used in upgrading heavy crude oil using methane as hydrogen source. The results showed a significant increase in API and decrease in sulfur and nitrogen content of crude oil. RSM technique was used to investigate the interactive effects of temperature (200–400 °C), pressure (20–40 bar) and dosage of nanocatalyst (0.5–2 wt. %) on the performance of HDS reaction. The results represent that the maximum predicted HDS activity (74.375%) was estimated under the optimal conditions (400 °C, 20 bars, and 2 wt % of nanocatalyst). Also, the effect of reaction temperature, pressure and dosage of ReS₂ nanorods catalyst on HDN of heavy crude oil was investigated and highest efficiency in the HDN process (93%) occurred at 400 °C and 40 bar using 2 wt % ReS₂.     

Photocatalytic degradation of methyl tert‐butyl ether (MTBE) in contaminated water by ZnO nanoparticles

BACKGROUND: Over the past several decades methyl tert‐butyl ether (MTBE) as additive to gasoline, intended to either boost ratings of fuel or to reduce air pollution, has been accepted worldwide. Since MTBE has high water solubility, the occurrence of fuel spills or leaks from underground storage tanks or transferring pipeline has led to the contamination of natural waters. In this study the degradation of aqueous MTBE at relatively high concentrations was investigated by a UV‐visible/ZnO/H₂O₂ photocatalytic process. The effects of important operational parameters such as pH, amount of H₂O₂, catalyst loading and irradiation time were also investigated. Concentration of MTBE and intermediates such as tert‐butyl formate and tert‐butyl alcohol were measured. RESULTS: Time required for complete degradation increased from 20 to 150 min when the initial concentration was increased from 10 to 500 mg L^?1. The first‐order rate constants for degradation of MTBE were estimated to be 0.183–0.022 min^?1 as the concentration increased from 10 to 500 mg L^?1. Study of the overall mineralization monitored by total organic carbon analysis showed that at an initial concentration of 100 mg L^?1 MTBE complete mineralization was obtained after 100 min under UV‐visible/ZnO/H₂O₂ photocatalysis. CONCLUSION: The data presented in this paper clearly indicated that UV‐visible/ZnO/O₂ as an advanced oxidation process provides an efficient treatment alternative for the remediation of MTBE‐contaminated waters. Copyright © 2008 Society of Chemical Industry     

A differential transformer-based force sensor utilizing a magnetic fluid core

Microsystem Technologies - A force sensor utilizing a transformer concept with a ferrofluid core was developed. A ferrofluid reservoir was machined out of Teflon and the open top of the reservoir...     

Effect of Extraordinary Large Floods on at-site Flood Frequency

The peak flow of extraordinary large floods that occur during a period of systematic record is a controversial problem for flood frequency analysis (FFA) using traditional methods. The present study suggests that such floods be treated as historic flood data even though their historical period is unknown. In this paper, the extraordinary large flood peak was first identified using statistical outlier tests and normal probability plots. FFA was then applied with and without the extraordinary large floods. In this step, two goodness-of-fit tests including mean absolute relative deviation and mean squared relative deviation were used to identify the best-fit probability distributions. Next, the generalized extreme value (GEV), three-parameter lognormal (LN3), log-Pearson type III (LP3), and Wakeby (WAK) probability distributions were used to incorporate and adjust the extraordinary large floods with other systematic data. Finally, procedures with and without historical adjustment were compared for the extraordinary large floods in terms of goodness-of-fit and flood return-period quantiles. The results of this comparison indicate that historical adjustment from an operational perspective was more viable than without adjustment procedure. Furthermore, the results without adjustment were unreasonable (subject to over- and under-estimation) and produced physically unrealistic estimates that were not compatible with the study area. The proposed approach substantially improved the probability estimation of rare floods for efficient design of hydraulic structures, risk analysis, and floodplain management.     

Position Unmanned Aerial Vehicles in the Mobile Ad Hoc Network

This paper considers the problem of employing multiple unmanned aerial vehicles (UAVs) to the mobile ad hoc network (MANET) as relay backbone nodes to construct the backbone network, to improve the network connectivity, and to address many issues in the MANET such as linkage, capacity, load balance, and reliability. With considering the dynamic nature of the problem, this study provides several linear location problem models and their extensions to accommodate these issues. Due to the size of linear location models associated with a large number of constraints, the problem becomes computational challenging even with modest size of nodes. To overcome the computational barrier, we recast these location problem models using a quadratic unconstrained binary optimization (QUBO) framework and solve these QUBO models with a Tabu search heuristic with preprocessing. The analysis of the solutions that are produced by QUBO together with the comparisons made with the linear model highlight both the attractiveness and robustness of the proposed approach. The results of this study provide support to future advanced routing protocol development.     

Transforming Vulnerability Indexing for Saltwater Intrusion into Risk Indexing through a Fuzzy Catastrophe Scheme

Mapping vulnerability to Saltwater Intrusion (SWI) in coastal aquifers is studied in this paper using the GALDIT framework but with a novelty of transforming the concept of vulnerability indexing to risk indexing. GALDIT is the acronym of 6 data layers, which are put consensually together to invoke a sense of vulnerability to the intrusion of saltwater against aquifers with freshwater. It is a scoring system of prescribed rates to account for local variations; and prescribed weights to account for relative importance of each data layer but these suffer from subjectivity. Another novelty of the paper is to use fuzzy logic to learn rate values and catastrophe theory to learn weight values and these together are implemented as a scheme and hence Fuzzy-Catastrophe Scheme (FCS). The GALDIT data layers are divided into two groups of Passive Vulnerability Indices (PVI) and Active Vulnerability Indices (AVI), where their sum is Total Vulnerability Index (TVI) and equivalent to GALDIT. Two additional data layers (Pumping and Water table decline) are also introduced to serve as Risk Actuation Index (RAI). The product of TVI and RAI yields Risk Indices. The paper applies these new concepts to a study area, subject to groundwater decline and a possible saltwater intrusion problem. The results provide a proof-of-concept for PVI, AVI, RAI and RI by studying their correlation with groundwater quality samples using the fraction of saltwater (f_sea), Groundwater Quality Indices (GQI) and Piper diagram. Significant correlations between the appropriate values are found and these provide a new insight for the study area.