Deep-piRNA: Bi-Layered Prediction Model for PIWI-Interacting RNA Using Discriminative Features

Piwi-interacting Ribonucleic acids (piRNAs) molecule is a well-known subclass of small non-coding RNA molecules that are mainly responsible for maintaining genome integrity, regulating gene expression, and germline stem cell maintenance by suppressing transposon elements. The piRNAs molecule can be used for the diagnosis of multiple tumor types and drug development. Due to the vital roles of the piRNA in computational biology, the identification of piRNAs has become an important area of research in computational biology. This paper proposes a two-layer predictor to improve the prediction of piRNAs and their function using deep learning methods. The proposed model applies various feature extraction methods to consider both structure information and physicochemical properties of the biological sequences during the feature extraction process. The outcome of the proposed model is extensively evaluated using the k-fold cross-validation method. The evaluation result shows that the proposed predictor performed better than the existing models with accuracy improvement of 7.59% and 2.81% at layer I and layer II respectively. It is anticipated that the proposed model could be a beneficial tool for cancer diagnosis and precision medicine.     

Synthesis of Au/UiO-66-NH2/Graphene composites as efficient visible-light photocatalysts to convert CO2

The production of new solar fuel through CO₂ photocatalytic reduction has aroused tremendous attention in recent years because of the increased demand of global energy sources and global warming caused by the mass concentration of CO₂ in the earth's atmosphere. In this work, UiO-66-NH₂ was co-modified by the Au nanoparticles (Au-NPs) and Graphene (GR). The resultant nanocomposite exhibits a strong absorption edge in visible light owing to the surface plasmon resonance (SPR) of Au-NPs. More attractively, Au/UiO-66-NH₂/GR displays much higher photocatalytic activity (49.9 μmol) and selectivity (80.9%) than that of UiO-66-NH₂/GR (selectivity: 71.6%) and pure UiO-66-NH₂ (selectivity: 38.3%) for the CO₂ reduction under visible light. The enhanced photocatalytic performance is primarily dued to the surface plasmon resonance (SPR) of Au-NPs, which could enhance the visible light absorption. The GR sheets could play as an electron acceptor with superior conductivity and thus suppress the recombination of electrons and holes. Besides, the GR could also improve the dispersibility of UiO-66-NH₂ so as to expose more active sites and strengthen the capture of CO₂. The contact effect and synergy effect among different samples are strengthened in the ternary composites and the photocatalytic performance is therefore improved. This study demonstrates a MOF based hybrid composite for efficient photocatalytic CO₂ reduction, the findings not only prove great potential for the design and application of MOFs-based materials but also bring light to novel chances in the development of new high performance photocatalysts.     

Geothermal and solar energy–based multigeneration system for a district

In this study, parabolic trough collector with an integrated source of geothermal water is used with regenerative Rankine cycle with an open feedwater heater, an electrolyzer, and an absorption cooling system. The absorption fluids used in the solar collectors were Al₂O₃‐ and Fe₂O₃‐based nanofluids. Detailed energetic and exergetic analyses are done for the whole system including all the components. A comparative analysis of both the used working fluids is done and plotted against their different results. The parameters that are varied to change the output of the system are ambient temperature, solar irradiance, the percentage of nanofluids, the mass flow rate of the geothermal well, the temperature gradient of the geothermal well that had an effect on the net power produced, and the outlet temperature of the solar collector overall energetic and exergetic efficiencies. Other useful outputs by this domestic integrated multigeneration system are the heating of domestic water, space heating (maintaining the temperature at 40°C‐50°C), and desalination of seawater (flash distillation). The hydrogen production rate for both the fluids diverges with each other, both producing average from 0.00490 to 0.0567 g/s.     

A novel efficient image encryption algorithm based on affine transformation combine with linear fractional transformation

Multidimensional Systems and Signal Processing - Algebraic structures and their hardware–software implementation gain considerable attention in the field of information security and coding...     

Analysis of malware propagation behavior in Social Internet of Things

Social Internet of Things (SIoT) is an evolution of the Internet of Things, where objects interact socially with each other in the sense that they can independently establish new relationships, offer, or discover services, in order to accomplish their tasks with minimum involvement of the user. This additional convenience comes at the expense of higher risk of speeding up malware propagation through the dynamically created relationships. Because of the undesirable effects of malware (eg, disruption of device operation), it is essential to understand their spreading behavior in order to minimize their negative impacts. In this paper, we analyze malware propagation behavior in SIoT and investigate different parameters that influence spreading of malware. Toward that end, a simulator has been developed to simulate the spreading process of malware in SIoT. Many propagation scenarios were analyzed using the proposed simulator. Simulation results show that adding more relationships in the SIoT or increasing the number of owned objects per user has increased malware spreading rate. For example, the time to infect all objects is faster by 45% when objects communicate through four relationships compared with the case when objects communicate through only two relationships in SIoT. We also investigated ways to restrict the malware spreading. Results show that preventing objects from establishing dynamic social relationship slows down the infection by 40% compared with the next best scenario (ie, blocking co‐location relationships), which means more time for vendors to patch up their products.     

Comparison of total ozone column observations from space-borne Ozone Monitoring Instrument with ground-based Dobson Ozone Spectrophotometer measurements at an urban location in Indo-Gangetic Basin

This article presents a comparison analysis of OMIT (Ozone Monitoring Instrument retrieved overpass total ozone column (TOC)), and DOST (Dobson Ozone Spectrophotometer observed TOC) over Delhi during a period from October 2004 to June 2011. Megacity Delhi, located in Indo-Gangetic Basin, is an important site for comparison of ground-based and satellite retrieved TOCs due to significant anthropogenic emissions of ozone precursors, large shift in seasons, and large-scale crop residue burning in the region. DOST and OMIT data show an overall bias of 3.07% and significant correlation with coefficient of determination R² = 0.73. Large seasonal fluctuations in the biases and correlations have been observed ranging from 2.46% (winter) to 3.82% (spring), and R² = 0.84 (winter) to R² = 0.09 (summer), respectively. The large biases are attributed to changes in temperature, cloud cover, pollutants emissions from urban area, and crop-residue burning events. We also find notable variations in correlations between the datasets due to the varying burden of absorbing aerosols from open field crop-residue burning. The R² has changed from 0.67 (for aerosol optical depth, AOD 1.5–3.5) to 0.77 (for AOD 0–0.99). The dependence of the bias on solar zenith angle, cloud fraction, and satellite distance is also discussed. A simple linear regression analysis is applied to check the linkage between DOST and OMIT. The influence of atmospheric air temperature and relative humidity on OMIT at different pressure levels between 1000 and 20 hPa has been discussed.     

Controlling the material removal and roughness of Inconel 718 in laser machining

Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRR_act) equals to the theoretical material removal rate (MRR_th) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR_% = 100.1%) with minimum surface roughness (R_a = 2.67 µm).     

Inhibition of FLT3: A Prototype for Molecular Targeted Therapy in Acute Myeloid Leukemia

Modern therapy of acute myeloid leukemia (AML) began in 1973 with the first report of the successful combination of daunorubicin and cytarabine, which led to complete remission in approximately 45% of patients. Accurate AML diagnosis was dependent on morphology, aided initially only by cytochemistry. Unlike acute lymphoblastic leukemia (ALL), immunophenotyping offered little in the diagnosis of AML, at least during the 1970s and 1980s. The advent of reliable cytogenetics changed the entire prognostic outlook of AML. With karyotypic analysis, different groups of AML could be classified and stratified for various therapies. Unique mutational profiling was a major advance in further categorizing AML patients, aided by the immunophenotypic identification of antigenic markers on the cells. All these advances were occurring as the understanding of the importance of the tumor burden—known as minimal residual disease (MRD)—became crucial for the management of AML patients. The efficacy of MRD has rapidly progressed in the past decade, from a specificity of 10⁻³ with immunophenotyping to 10⁻⁴ with polymerase chain reaction (PCR), which is only appropriate for some patients with AML, and finally to 10⁻⁵ or even 10⁻⁶ cells with the extraordinary sensitivity of next-generation sequencing (NGS). All of these advances have promoted the concept of personalized medicine, which has led to the advent of targeted agents that can accurately be used for specific diagnostic subtypes. Responses can be predicted and measured accurately. Such targeted agents have now become a cornerstone in the management of AML, increasing efficacy and dramatically reducing toxicity. The focus of this review is on one of the most well-studied targeted agents in AML: the FMS-like tyrosine kinase 3 (FLT3) inhibitors, which have impacted the prognostication and therapeutics of AML. This review selectively discusses the FLT3 inhibitors in detail, as a model for the other burgeoning targeted agents that have already been approved, as well as those that are currently in development.     

Comparative photocatalytic performance and therapeutic applications of zinc oxide (ZnO) and neodymium-doped zinc oxide (Nd–ZnO) nanocatalysts against Acid Yellow-3 dye: kinetic and thermodynamic study of the reaction and effect of various parameters

Zinc oxide (ZnO) nanoparticles (NPs) were synthesized hydrothermally and doped with 4% Neodymium (Nd). The produced NPs were characterized using UV–Vis spectroscopy, X-ray diffraction (XRD), Energy dispersive X-ray analysis, Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), Thermogravimetric analysis (TGA) and Photoluminescence (PL) spectroscopy. With the addition of 4% Nd, the bandgap reduced from 3.20 to 3.00 eV which confirmed successful doping with Nd which also evident from FTIR study. The XRD study showed hexagonal structure of the synthesized material, while SEM study confirmed that Nd-doped ZnO (Nd–ZnO) NPs are well dispersed as compare to ZnO. TGA study revealed that synthesized NPs were much stable to temperature and only 11.3% and 7.2% the total loss occurred during heating range (40–600 °C) in case of ZnO and Nd–ZnO NPs, respectively. The PL intensity of the visible peaks of ZnO reduced after doping with Nd. The degradation of Acid yellow-3 over both the catalysts followed first-order kinetics. The activation energy calculated for the photodegradation reaction was 43.8 and 33.7 kJ/mol using pure ZnO and Nd–ZnO NPs, respectively. About 91% and 80% dye was degraded at the time interval of 160 min using Nd–ZnO and ZnO NPs, respectively. High percent degradation of dye was found at low concentration (10 ppm) and at optimal dosage (0.035 g) of the catalyst. The rate of Acid yellow-3 dye degradation was found to increase with increase in temperature (up to 50 °C) and pH(8) of the medium. The recyclability study showed that both pure ZnO and Nd–ZnO NPs could be reused for the degradation of the given dye. With the addition of H₂O₂ up to 5 µL, the rate of reaction increased clearly indicating the effect of OH^· generation during photocatalysis. When compared with Nd–ZnO NPs at low concentrations, ZnO NPs at higher concentrations were found to be less hazardous. Both the NPs showed best antibacterial activities against Staphylococcus aureus. The hemolytic study indicated that at low concentration, pure ZnO was non-hemolytic as compared to Nd–ZnO.

     

Towards Ensuring Reliability of Vehicular Ad Hoc Networks Using a Relay Selection Techniques and D2D Communications in 5G Networks

Wireless Personal Communications - Benefiting from unlimited power supply, vehicular ad hoc networks (VANETs), in a 5G platform, can deal superiorly with the challenges of providing high...