Interfacially polymerized nanofiltration membranes: Atomic force microscopy and salt rejection studies

Interfacial polymerization is one of the main techniques for producing composite nanofiltration (NF) membranes. In this study, five NF membranes were produced through interfacial polymerization under different conditions of reactions, namely varying reaction time, as well as monomer concentrations. The membranes were then imaged using atomic force microscope (AFM). AFM images provided information of the average pore size, pore size distribution, and surface roughness. For some of the membranes, discrete pore sizes were visible. Increasing the reaction time resulted in decreasing water permeabilities but based on AFM imaging the pore size was of similar value. Increasing the monomer concentration also resulted in decreasing water permeabilities. However, based on AFM imaging the pore size differs considerably. Additional permeation experiments were also carried out using NaCl and Na₂SO₄ solutions with membranes identified as NF. By fitting the rejection data using a model such as the Donnan‐steric‐pore model, the variation in effective charge density of the membranes was also determined. The ability to tailor composite NF membranes with the right properties will significantly improve membrane performance. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 605–612, 2005     

Bed Expansion – Extending Correlations for Fluidized Beds with Inserts to Open Fluidized Beds

Bed expansion occurs during the operation of gas‐fluidized beds and is influenced by particle properties, gas properties and distributor characteristics. It has a significant bearing on heat and mass transfer phenomena within the bed. A method of predicting bed expansion behavior from other fluidizing parameters would be a useful tool in the design process, dispensing with the need for small‐scale trials. This study builds on previous work on fluidized beds with vertical inserts to produce a correlation that links a modified particle terminal velocity, minimum fluidizing velocity and distributor characteristics with bed voidage in the relationship with P as the pitch between holes in the perforated distributor plate.     

Synthesis and Characterization of Sporopollenin-Supported Schiff Bases and Ruthenium(III) Sorption Studies

Two Schiff base derivatives, (2-pycolylimino)benzen-1,4-diol and (2-pyridylimino)benzen-1,4-diol) were immobilized onto sporopollenin (Lycopodium clavatum) surfaces. The compounds were fully characterized by an infrared spectroscopy, elemental analysis, scanning electron microscopy, and X-ray diffraction techniques. The sorption capacities of the immobilized surfaces toward Ru(III) ions were investigated by batch sorption experiments. For the sorption experiment, the Ru(III) concentration, initial pH, and the temperature effects were studied. The isotherm data of Ru(III) ions were correlated reasonably well as a Freundlich sorption isotherm. The thermodynamic studies showed that the Ru(III) sorption onto immobilized sporopollenin derivatives is a non-spontaneous, endothermic and physical reaction.     

Malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. The presented AFSADL-MURLC model intends to differentiate the malicious URLs from genuine URLs. To attain this, AFSADL-MURLC model initially carries out data preprocessing and makes use of glove-based word embedding technique. In addition, the created vector model is then passed onto Gated Recurrent Unit (GRU) classification to recognize the malicious URLs. Finally, AFSA is applied to the proposed model to enhance the efficiency of GRU model. The proposed AFSADL-MURLC technique was experimentally validated using benchmark dataset sourced from Kaggle repository. The simulation results confirmed the supremacy of the proposed AFSADL-MURLC model over recent approaches under distinct measures.     

Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel Energy Aware Data Collection with Routing Planning for 6G-enabled UAV communication (EADCRP-6G) technique. The goal of the proposed EADCRP-6G technique is to conduct energy-efficient cluster-based data collection and optimal route planning for 6G-enabled UAV networks. EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) and organize these clusters. Besides, Artificial Fish Swarm-based Route Planning (AFSRP) technique is applied to choose an optimum set of routes for UAV communication in 6G networks. In order to validated whether the proposed EADCRP-6G technique enhances the performance, a series of simulations was performed and the outcomes were investigated under different dimensions. The experimental results showcase that the proposed model outperformed all other existing models under different evaluation parameters.     

Synthesis,characterization, and enhanced formic acid electrooxidation activity of carbon supported MnOx promoted Pd nanoparticles

Formic acid (HCOOH) is one of the promising fuels for direct liquid fed fuel cells. However, CO poisoning is a major challenge for the development of effective catalytic system for formic acid electrooxidation (FAEO). Herein, a novel CO-resistive activated carbon supported Pd-MnO_x bimetallic catalyst (Pd-MnO_x/C) was presented for FAEO. Pd-MnO_x/C catalyst was prepared via simple and reproducible surfactant-free deposition-reduction technique. The characterization of this novel Pd-MnO_x/C catalyst was performed by inductively coupled plasma-optical emission spectroscopy (ICP-OES), powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), bright field transmission electron microscopy (BFTEM), high resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), and scanning transmission electron microscope-energy dispersive X-ray spectroscopy (STEM-EDX). The characterization results revealed that Pd and MnO_x nanoparticles (NPs) were well dispersed and separately nucleated with a mean diameter of 2.9?nm on the surface of active carbon. FAEO studies were performed on both Pd-MnO_x/C and Pd/C catalysts to comprehend the effect of separately formed MnO_x on the electrocatalytic activity of Pd NPs. The electrochemical measurements were carried out by using Cyclic Voltammetry (CV) and Chronoamperometry (CA), CO-Strriping Voltammetry, Lineer Sweep Voltammetry (LSV), Electrochemical impedance spectroscopy (EIS) techniques. Electrochemical results revealed that FAEO was activated by the addition of MnOx. Pd_0.6-Mn_0.4 exhibited the optimum catalytic activity with 1.05?A/mg Pd current density. The sum of their results clearly points that the existence of MnO_x NPs enhances the electrocatalytic activity of Pd NPs by increasing their CO-resistivity and durability throughout the FAEO.     

Weighted backprojection approach to cone beam 3D projection reconstruction for truncated spherical detection geometry

A new analytical three-dimensional cone beam reconstruction algorithm is presented for truncated spherical detection geometry. The basic idea of the proposed algorithm is the formation of spatially invariant 3D blurred back-projected volumetric image by the use of the weighted backprojection of cone beam projection data and subsequent 3D filtering using an acceptance angle dependent rho filter. The backprojection weighting function is calculated on the basis of each given geometrical condition, i.e. detection geometry or degree of truncation, position of cone beam apex, and backprojection point. The proposed algorithm is derived analytically and is computationally efficient. Performance of the algorithm is evaluated by the reconstruction of 3D volumetric images using simulated data from arbitrarily truncated spherical detector geometries.     

Peak-Average-Power Ratio Techniques for 5G Waveforms Using D-SLM and D-PTS

Multicarrier Waveform (MCW) has several advantages and plays a very important role in cellular systems. Fifth generation (5G) MCW such as Non-Orthogonal Multiple Access (NOMA) and Filter Bank Multicarrier (FBMC) are thought to be important in 5G implementation. High Peak to Average Power Ratio (PAPR) is seen as a serious concern in MCW since it reduces the efficiency of amplifier use in the user devices. The paper presents a novel Divergence Selective Mapping (DSLM) and Divergence Partial Transmission Sequence (D-PTS) for 5G waveforms. It is seen that the proposed D-SLM and PTS lower PAPR with low computational complexity. The work highlighted a combination of multi-data block partial transmit schemes along with tone reservation. In this, an overlapping factor is used to determine the number of data blocks for every group. Here, considering only those data blocks that have minimum signal power, the use of DSLM and DPTS are required to eliminate the segment’s peaks. Simulation results reveal that the suggested hybrid technique proves to be better than the conventional PTS scheme. Furthermore, the power saving performance of FBMC and NOMA is compared with the Orthogonal Frequency Division Multiplexing (OFDM) waveform.     

New spherical PET design with fresnel aperture orientation

A new spherical PET using Fresnel aperture is being designed, and construction is in progress. In the new design, the original spherical geometry is modified to accommodate a more flexible gantry construction and data processing while preserving the focused geometry of the original design. The performance of this new Fresnel aperture-SPET (F-SPET) is expected to follow closely with that of the original S-PET design. An analysis of an F-SPET designed with nine modular layers, with each modular layer being four rings, was performed in terms of the counting statistics and solid angle and compared with the original S-PET as well as the conventional cylindrical PET. According to the simulation results, the sensitivity gain of the Fresnel aperture-SPET remains a factor of 2 over the equivalent cylindrical system and has nearly the same performance as the original S-PET, while offering a simpler means in construction and data handling for the image reconstruction.