Review: the latest advances in biomedical applications of chitosan hydrogel as a powerful natural structure with eye-catching biological properties

Journal of Materials Science - Chitosan is one of the natural cationic polymers with unique properties such as non-toxicity, biodegradability, biocompatibility, environmentally friendly that has...     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

CuxNi1-xO nanostructures and their nanocomposites with reduced graphene oxide: Synthesis,characterization, and photocatalytic applications

NiO nanostructure was synthesized using a simple co-precipitation method and was embedded on reduced graphene oxide surface via ultrasonication. Structural investigations were made through X-ray diffraction (XRD) and functional groups were confirmed by Fourier transform infrared spectroscopy (FTIR). XRD analysis revealed the grain size reduction with doping. Fourier transform infrared spectroscopy confirmed the presence of metal-oxygen bond in pristine and doped NiO nanostructure as well as the presence of carbon containing groups. Scanning electron microscopy (SEM) indicated that the particle size decreased when NiO nanostructure was doped with copper. BET surface area was found to increase almost up to 43 m²/g for Cu doped NiO nanostructure/rGO composite. Current-voltage measurements were performed using two probe method. UV–Visible spectroscopic profiles showed the blue and red shift for Cu doped NiO nanostructure and Cu doped NiO Nanostructure/rGO composite respectively. Rate constant for Cu doped NiO nanostructure/rGO composite found to increase 4.4 times than pristine NiO nanostructure.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

Molecular structure and granule morphology of native and heat‐moisture‐treated pinhão starch

Pinhão seed is an unconventional source of starch and the pines grow up in native forests of southern Latin America. In this study, pinhão starch was adjusted at 15, 20 and 25% moisture content and heated to 100, 110 and 120 °C for 1 h. A decrease in λ max (starch/iodine complex) was observed as a result of increase in temperature and moisture content of HMT. The ratio of crystalline to amorphous phase in pinhão starch was determined via Fourier transform infra red by taking 1045/1022 band ratio. A decrease in crystallinity occurred as a result of HMT. Polarised light microscopy indicated a loss of birefringence of starch granules under 120 °C at 25% moisture content. Granule size distribution was further confirmed via scanning electron microscopy which showed the HMT effects. These results increased the understanding on molecular and structural properties of HMT pinhão starch and broadened its food and nonfood industrial applications.     

Amination of biochar surface from watermelon peel for toxic chromium removal enhancement

Watermelon peel residues were used to produce a new biochar by dehydration method. The new biochar has undergone two methods of chemical modification and the effect of this chemical modification on its ability to adsorb Cr(VI) ions from aqueous solution has been investigated. Three biochars, Melon-B, Melon-BO-NH_2 and Melon-BO-TETA, were made from watermelon peel via dehydration with 50% sulfuric acid to give Melon-B followed by oxidation with ozone and amination using ammonium hydroxide to give Melon-BO-NH_2 or Triethylenetetramine(TETA) to give Melon-BO-TETA. The prepared biochars were characterized by BET, BJH,SEM, FT-IR, TGA, DSC and EDAX analyses. The highest removal percentage of Cr(VI) ions was 69% for Melon-B,98% for Melon-BO-NH_2 and 99% for Melon-BO-TETA biochars of 100 mg·L~(-1) Cr(VI) ions initial concentration and 1.0 g·L~(-1) adsorbents dose. The unmodified biochar(Melon-B) and modified biochars(Melon-BO-NH_2 and Melon-BO-TETA) had maximum adsorption capacities(Qm) of 72.46, 123.46, and 333.33 mg·g~(-1), respectively.The amination of biochar reduced the pore size of modified biochar, whereas the surface area was enhanced.The obtained data of isotherm models were tested using different error function equations. The Freundlich,Tempkin and Langmuir isotherm models were best fitted to the experimental data of Melon-B, Melon-BO-NH_2 and Melon-BO-TETA, respectively. The adsorption rate was primarily controlled by pseudo-second–order rate model. Conclusively, the functional groups interactions are important for adsorption mechanisms and expected to control the adsorption process. The adsorption for the Melon-B, Melon-BO-NH_2 and Melon-BO-TETA could be explained for acid–base interaction and hydrogen bonding interaction.     

Electrophoretic deposition of graphene oxide on carbon brush as bioanode for microbial fuel cell operated with real wastewater

Microbial fuel cell (MFC) is a promising technology for simultaneous wastewater treatment and energy harvesting. The properties of the anode material play a critical role in the performance of the MFC. In this study, graphene oxide was prepared by a modified hummer's method. A thin layer of graphene oxide was incorporated on the carbon brush using an electrophoretic technique. The deoxygenated graphene oxide formed on the surface of the carbon brush (RGO-CB) was investigated as a bio-anode in MFC operated with real wastewater. The performance of the MFC using the RGO-CB was compared with that using plain carbon brush anode (PCB). Results showed that electrophoretic deposition of graphene oxide on the surface of carbon brush significantly enhanced the performance of the MFC, where the power density increased more than 10 times (from 33 mWm^?2 to 381 mWm^?2). Although the COD removal was nearly similar for the two MFCs, i.e., with PCB and RGO-CB; the columbic efficiency significantly increased in the case of RGO-CB anode. The improved performance in the case of the modified electrode was related to the role of the graphene in improving the electron transfer from the microorganism to the anode surface, as confirmed from the electrochemical impedance spectroscopy measurements.