Toxicological effects of the chemical and green ZnO NPs on Cyprinus carpio L. observed under light and scanning electron microscopy

Nanoparticles in aquatic bodies cause serious harm to the aquatic organisms when accumulated in high amounts. However, green nanoparticles synthesized using plants can be less toxic as compared to chemical nanoparticles. Hence, we designed our study to investigate the toxicological effects of chemical and green zinc oxide nanoparticles (ZnO NPs) on the biological activity of juvenile Cyprinus carpio. The green ZnO NPs were synthesized from Solieria robusta, and chemical ZnO NPs were synthesized using zinc chloride solution and ammonium hydroxide. Characterization was done by using light microscopy, scanning electron microscope (SEM), Fourier transmission infrared radiation, and X-ray diffraction (XRD) techniques. The highest absorbance of nanoparticles was observed at 360 which confirmed the synthesis of ZnO. The SEM analysis showed that green nanoparticles were hexagonal while the chemical nanoparticles were spherical to cubic in shape. Definite peaks were observed in XRD of green and chemical NPs at 2θ angles 45.84° and 32.18°, respectively. Oxidative stress was determined by chemical analysis of catalase, glutathione S-transferase (GST), glutathione (GSH), and lipid peroxidation (LPO) activities. The toxicological effects of chemical ZnO NPs on the catalase, LPO, GST, and GSH activities were more than green ZnO NPs. The histopathological investigation proved that the effect of chemical nanoparticles was worse than green ZnO NPs. More tissue damage was found in chemical nanoparticles than green synthesized nanoparticles. It was concluded that chemical nanoparticles can be replaced by green nanoparticles, as green nanoparticles are eco-friendly with less toxicological effects. This replacement can limit the toxic effect of nanoparticles when they get accumulated in high amounts in water bodies.     

Application of Novel Modified Chitosan Hydrogel Composite for the Efficient Removal of Eriochrome Black T and Methylene Blue Dyes from Aqueous Media

Journal of Inorganic and Organometallic Polymers and Materials - In this paper, chitosan/Fe3O4/graphene oxide hydrogel was synthesized then modified with 2,6-pyridinedicarbonyl dichloride to obtain...     

Facile Hydrothermal Synthesis of Copper Chromite Nanoparticles for Efficient Photocatalytic Degradation of Acid Orange 7 Dye

In this paper, the hydrothermal method was utilized for the facile synthesis of copper chromite nanoparticles in the absence (abbreviated as CC1) and presence of citric acid (abbreviated as CC2) and tartaric acid (abbreviated as CC3) as templates. The synthesized nanoparticles were characterized using different tools such as XRD, FT-IR, UV–Vis, FE-SEM, HR-TEM, and BET. The average crystallite size of the CC1, CC2, and CC3 samples is 25.45, 20.26, and 12.75 nm, respectively. The FT-IR spectra show two bands in the range 613–616 cm^?1 and 511–514 cm^?1, which are characteristic of the spinel copper chromite crystalline structure. The optical energy gaps of the CC1, CC2, and CC3 samples are 1.25, 1.88, and 1.92 eV, respectively. The synthesized nanoparticles were used for the degradation of the acid orange 7 dye under visible light irradiations. The highest % degradation was obtained at pH?2.5 and irradiation time?=?40 min. The % degradation of the acid orange 7 dye using CC1, CC2, and CC3 photocatalysts at pH?2.50 and time?=?40 min is 87.38, 96.52, and 98.81, respectively. The degradation of the acid orange 7 dye was markedly reduced with the addition of isopropyl alcohol or disodium ethylenediaminetetraacetate, confirming that the hydroxyl radicals and holes routes play a fundamental role in the degradation process of the acid orange 7 dye. The degradation of the acid orange 7 dye is slightly affected by the addition of ascorbic acid, confirming a minor concentration of oxygen anion radicals.

     

Fusion Rules Effects on Lifetime Maximization of Multi-channel Cooperative Spectrum Sensing

Cooperative spectrum sensing (CSS) is an efficient method to detect the reliability of the free spectrum, however, with great overhead and energy consumption. In this paper, we study a much broader application of CSS, where the sensors are used to sense multiple channels. On the one hand, since the tiny and low-cost sensors do not have high-speed analog-to-digital-convertors, they cannot simultaneously sense more than one channel. Therefore, the simultaneous multi-channel CSS is an important issue in a cognitive sensor network (CSN). On the other hand, these tiny sensors do not have high-power batteries, which makes the network lifetime as an important metric. In this paper, node selection is proposed for the multi-channel CSS to maximize the lifetime of a CSN under some detection constraints with lower overhead than cooperative sensing by all the sensors simultaneously. We analyze the problem for the OR and the AND rules, which can be implemented at the fusion center. The problem is solved by using convex optimization methods where assignment indices for every sensor are assumed. We provide a performance analysis through simulations using MATLAB, which shows that the sensor selection scheme provides a significant long lifetime for a CSN compared to the case where sensors are selected randomly and where all sensors are just classified to sense the channels simultaneously.

     

Convex optimization with an interpolation-based projection and its application to deep learning

Machine Learning - Convex optimizers have known many applications as differentiable layers within deep neural architectures. One application of these convex layers is to project points into a...     

Applying Non-Local Means Filter on Seismic Exploration

The seismic reflection method is one of the most important methods in geophysical exploration. There are three stages in a seismic exploration survey: acquisition, processing, and interpretation. This paper focuses on a pre-processing tool, the Non-Local Means (NLM) filter algorithm, which is a powerful technique that can significantly suppress noise in seismic data. However, the domain of the NLM algorithm is the whole dataset and 3D seismic data being very large, often exceeding one terabyte (TB), it is impossible to store all the data in Random Access Memory (RAM). Furthermore, the NLM filter would require a considerably long runtime. These factors make a straightforward implementation of the NLM algorithm on real geophysical exploration data infeasible. This paper redesigned and implemented the NLM filter algorithm to fit the challenges of seismic exploration. The optimized implementation of the NLM filter is capable of processing production-size seismic data on modern clusters and is 87 times faster than the straightforward implementation of NLM.     

An analytical investigation on the effect of porous conductive cellulose acetate composite morphology on the detection of organic compounds

A smart porous conductive polymer composite (CPC) consisting of cellulose acetate as matrix and multiwalled carbon nanotubes as conductive filler was prepared to detect a set of lung cancer biomarkers. The solvent evaporation-induced phase separation was used to introduce porosity into the conductive composite. The prepared sensitive layers exhibited high response intensity, low response time, and good recovery behavior toward the mentioned analytes. A thorough investigation was conducted on the morphology, response behavior, sensitivity, and selectivity of the prepared CPC transducer. The selectivity of responses was considered based on the thermodynamic and kinetic characteristics of polymer and analytes such as Hansen solubility parameters, Flory-Huggins interaction parameter, and diffusion coefficient of analytes into the polymer membrane. Moreover, the microstructure of porous layers was characterized by using SEM, contact angle, and BET. The volume porosity and specific surface area of the sensitive layers were increased by the introduction of porosity into the polymer composite, causing the improvement of sensing parameters. The obtained responses further confirmed the promising potential of the prepared porous CPC structure, for the detection of lung cancer biomarkers, from exhaled breath as an inexpensive, repeatable, accurate, and noninvasive method.     

A successive sampling control chart using multiple dependent state sampling over two successive occasions

In this paper, successive sampling (SS) mean monitoring control chart is proposed for two successive occasions using multiple dependent state (MDS) sampling and characterized as MDS-SS control chart. The sample size is selected on the basis of SS for the control statistic in two pairs of the control limits. The average run length is evaluated, and the performance of the proposed concept over the existing SS control chart is presented using a real-life example. The SS monitoring chart concept is compiled with MDS, and it becomes more sophisticated in detection of warning signs.     

Takagi-Sugeno tracking control of a fermentation process with respect to asymmetric constraints

This article deals with the tracking problem for nonlinear biological process with asymmetric constraints on the controller. Using the fuzzy logic Takagi-Sugeno (TS), the nonlinear process is modeled by a fuzzy model and a parallel distributed compensation (PDC) controller with respect asymmetric constraints is designed. The main contribution of this work is to extend the available results, in the context of a TS formulation, for symmetrical constraints to asymmetrical ones. Hence, sufficient conditions are obtained for the first time, in terms of linear matrix inequalities (LMIs), for the existence of an asymmetrical constrained PDC controller. Moreover, fuzzy observer based controller with unmeasured premise variables is designed. The performance and effectiveness of the method are illustrated in simulation by considering a fermentation process.     

Fungal mediated synthesis of silver nanoparticles and evaluation of antibacterial activity

Nanoparticles as biomedicine has made a crucial role in health biotechnology. Different transition metals in various forms playing role in nanotechnological advances and biological applications. Silver as one of the nontoxic, safe inorganic antibacterial agents and can serve as replacement of antibiotics. Present research is based on biogenic synthesis of silver nanoparticles (Ag‐NPs) as potential antibiotics from fungal metabolites of Penicillium oxalicum. We used different analytical techniques X‐ray diffraction (XRD) and scanning electron microscopy (SEM) for characterization of biosynthesized silver nanoparticles. Furthermore, the antibacterial activity of biosynthesized silver nanoparticles was checked against Staphylococcus aureus, S. dysenteriae, and Salmonella typhi by using well diffusion method and UV visible spectrophotometer. Maximum zone of inhibition recorded against S. aureus, Shigella dysenteriae was 17.5 ± 0.5 mm (mm) for both species and 18.3 ± 0.60 mm for Salmonella typhi. The biosynthesized silver nanoparticles of P. oxalicum showed excellent antibacterial activity. It was concluded from our results that biosynthesized silver nanoparticles have significant potential and might be useful for a wide range of biological applications such as bactericidal agent against resistant bacteria, preventing infections, healing wounds, and anti‐inflammation.