The Emerging Role of Non-Coding RNAs in the Regulation of Virus Replication and Resultant Cellular Pathologies

Non-coding RNAs, particularly lncRNAs and miRNAs, have recently been shown to regulate different steps in viral infections and induction of immune responses against viruses. Expressions of several host and viral lncRNAs have been found to be altered during viral infection. These lncRNAs can exert antiviral function via inhibition of viral infection or stimulation of antiviral immune response. Some other lncRNAs can promote viral replication or suppress antiviral responses. The current review summarizes the interaction between ncRNAs and herpes simplex virus, cytomegalovirus, and Epstein–Barr infections. The data presented in this review helps identify viral-related regulators and proposes novel strategies for the prevention and treatment of viral infection.     

Flexural and Charpy impact behaviour of epoxy/glass fabric treated by nano-SiO2 and silane blend

A sizing formulation, containing compatible and incompatible silane coupling agents with epoxy resin in conjunction with nanoscale colloidal silica, was used to modify the surface of glass fabric. The modified glass fabric/epoxy resin composite panels were fabricated and characterised by flexural test, Charpy impact test and scanning electron microscope (SEM). By combining nano silica with silane blend in the fabric sizing, more energy was consumed under bending and impacting, which resulted in an improvement of the toughness in composites. The flexural strength, bending stain and Charpy impact strength of the epoxy composite/glass fabric treated with 1?wt-% nano silica and silane blend were ～42, ～22 and 35%, respectively, higher than those of silane blend coated glass fabric-reinforced composites (without nano silica). Furthermore, the change of the brittle fracture of the composite into ductile fracture was investigated by SEM micrographs. A possible toughening mechanism was also proposed.     

Effect of green manure and supplemental fertility amendments on selected soil quality parameters in an organic potato rotation in Eastern Canada

The effects of green manure, crop sequence and off-farm composts on selected soil quality parameters were assessed in a three-year organic potato (Solanum tuberosum L.) rotation in Eastern Canada. Three crop sequences varying in preceding green manure [red clover (RCl) + RCl, and beans/buckwheat or carrots + oats/peas/vetch mixture (OPV)] as main plots and four fertility treatments applied in the potato phase only [control; inorganic fertilizer; municipal solid waste compost (MSW); composted paper mill biosolid (PMB)] as subplots were compared. In 2008 and 2010, changes in selected soil quality parameters (0–15 cm) were assessed prior to planting of potatoes and at potato tuber initiation stage. Potentially mineralizable nitrogen (N) and the acid phosphatase enzyme activity average values across years were greater following RCl (1.51 abs and 622 kg ha^?1) compared with OPV (1.32 abs and 414 kg ha^?1) at potato planting. Soil NO₃–N average value was greater following RCl compared with OPV (63 vs. 52 kg ha^?1) at tuber initiation. For the other measured parameters, OPV and RCl were similar. The soil organic carbon (C) and particulate organic matter-C were greater under PMB and MSW (31.1 and 7.57 kg ha^?1) compared with fertilizer treatment (27.9 and 6.05 kg ha^?1). The microbial biomass C and microbial biomass quotient were greater under MSW (216 kg ha^?1 and 0.73 %) than PMB and fertilizer (147 kg ha^?1 and 0.50 %) across crop rotations. Annual legume green manures and off-farm composts can be used to satisfy potato N requirement and maintains soil quality in organic potato rotations.     

Modelling qualitative and quantitative parameters of groundwater using a new wavelet conjunction heuristic method: wavelet extreme learning machine versus wavelet neural networks

In recent years, as a result of climate change as well as rainfall reduction in arid and semi‐arid regions, modelling qualitative and quantitative parameters belonging to aquifers has become crucially important. In Iran, as aquifers are treated as the most commonly used drinking water resources, modelling their qualitative and quantitative parameters is enormously important. In this paper, for the first time, values of salinity, total dissolved solids (TDS), groundwater level (GWL) and electrical conductivity (EC) of the Arak Plain, located in Markazi Province, Iran, are simulated by means of four modern artificial intelligence models including extreme learning machine (ELM), wavelet extreme learning machine (WELM), online sequential extreme learning machine (OSELM) and wavelet online sequential extreme learning machine (WOSELM) as well as the MODFLOW software for a 15‐year period monthly. To develop the hybrid artificial intelligence models, the wavelet is employed. First, the effective lags in estimating the qualitative and quantitative parameters of the groundwater are identified using the autocorrelation function (ACF) and the partial autocorrelation function (PACF) analysis. After that, four different models are developed by the selected input combinations and also the ACF and the PACF in the form of different lags for each of ELM, WAELM, OSELM and WOSELM methods. Then, the superior models in simulating the groundwater qualitative and qualitative parameters are detected by conducting a sensitivity analysis. To forecast the electrical conductivity (EC) by the best WOSELM model, the values of the Nash–Sutcliffe efficiency coefficient (NSC), Mean Absolute Error (MAE) and the scatter index (SI) are obtained to be 0.991, 18.005 and 4.28E‐03, respectively. In addition, the most effective lags in estimating these parameters are introduced. Subsequently, the results found by the MODFLOW model are compared with those of the artificial intelligence models and it is concluded that the latter are more accurate. For instance, the scatter index and Nash–Sutcliffe efficiency coefficient values calculated by WOSELM for TDS, respectively, are 5.34E‐03 and 0.991. Finally, an uncertainty analysis is conducted to evaluate the performance of different numerical models. For example, MODFLOW has an underestimated performance in simulating the salinity parameter.     

The Falling Lake Victoria Water Level: GRACE,TRIMM and CHAMP Satellite Analysis of the Lake Basin

In the last 5 years, Lake Victoria water level has seen a dramatic fall that has caused alarm to water resource managers. Since the lake basin contributes about 20% of the lakes water in form of discharge, with 80% coming from direct rainfall, this study undertook a satellite analysis of the entire lake basin in an attempt to establish the cause of the decline. Gravity Recovery And Climate Experiment (GRACE), Tropical Rainfall Measuring Mission (TRMM) and CHAllenging Minisatellite Payload (CHAMP) satellites were employed in the analysis. Using 45 months of data spanning a period of 4 years (2002–2006), GRACE satellite data are used to analyse the variation of the geoid (equipotential surface approximating the mean sea level) triggered by variation in the stored waters within the lake basin. TRMM Level 3 monthly data for the same period of time are used to compute mean rainfall for a spatial coverage of .25°×.25° (25×25 km) and the rainfall trend over the same period analyzed. To assess the effect of evaporation, 59 CHAMP satellite’s occultation for the period 2001 to 2006 are analyzed for tropopause warming. GRACE results indicate an annual fall in the geoid by 1.574 mm/year during the study period 2002–2006. This fall clearly demonstrates the basin losing water over these period. TRMM results on the other hand indicate the rainfall over the basin (and directly over the lake) to have been stable during this period. The CHAMP satellite results indicate the tropopause temperature to have fallen in 2002 by about 3.9 K and increased by 2.2 K in 2003 and remained above the 189.5 K value of 2002. The tropopause heights have shown a steady increase from a height of 16.72 m in 2001 and has remained above this value reaching a maximum of 17.59 km in 2005, an increase in height by 0.87 m. Though the basin discharge contributes only 20%, its decline has contributed to the fall in the lake waters. Since rainfall over the period remained stable, and temperatures did not increase drastically to cause massive evaporation, the remaining major contributor is the discharge from the expanded Owen Falls dam.     

Simulation and energy optimization of the stabilizer tower of a pyrolysis gasoline hydrogenation unit

Energy optimization of second distillation tower of a pyrolysis gasoline hydrogenation unit has been studied by the thermal cycle of vapor recompression method. The mentioned cycle is connected to the second distillation tower of the stabilizer of pyrolysis gasoline, and the results are found promising. The composite pinch curve for both the current and the optimized methods are shown. Moreover, an increase in the heat transfer rate in heat exchanger E-1014 causes energy recovery in reboiler. According to simulation results, by vapor recompression to 1970 kPa and using this heat source for thermal integration, condenser and reboiler’s energies are decreased by 56.93 and 30.4 percentage, respectively.     

All two-input logic gates by a single-stage single electron box

In this paper, the design of all two-input logic gates is presented by only a single-stage single electron box (SEB) for the first time. All gates are constructed based on a same circuit. We have used unique periodic characteristics of SEB to design these gates and present all two-input logic gates (monotonic/non-monotonic, symmetric/non-symmetric) by a single-stage design. In conventional monotonic devices, such as MOSFETs, implementing non-monotonic logic gates such as XOR and XNOR is impossible by only a single-stage design, and a multistage design is required which leads to more complexity, higher power consumption and less speed of the gates. We present qualitative design at first and then detailed designs are investigated and optimised by using our previous works. All designs are verified by a single electron simulator which shows correct operation of the gates.     

Underlay Device to Device Communication with Imperfect Interference Channel Knowledge

The objective of any night vision system is to enable a person to see in the dark. A low-contrast image puts a contrast constraint on the human observer visibility at night. This is the basic reason for the large number of accidents at night. This research presents two proposed approaches to enhance the visibility of the infrared (IR) night vision images through an efficient histogram processing. The first approach is based on contrast limited adaptive histogram equalization. The second proposed approach depends on histogram matching. The histogram matching uses a reference visual image for converting night vision images into good quality images. The obtained results are evaluated with quality metrics such as entropy, average gradient, contrast improvement factor and sobel edge magnitude.     

The application of internet of things in healthcare: a systematic literature review and classification

Universal Access in the Information Society - The Internet of Things (IoT) is an ecosystem that integrates physical objects, software and hardware to interact with each other. Aging of population,...