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Brain tumors are the most common and vigorous cause of death in the modern era. The medical community is working hard to develop effective methods to detect brain tumors in an early stage. Machine learning-based optimized classifiers can provide an efficient, accurate, and timely solution to detect brain tumors. Herein, a three-step least complex optimal linear support vector network-based computer-aided healthcare system for tumor cell detection using magnetic resonance imaging (MRI) is proposed. In the first step, features obtained from the Handcrafted features (HF) and a 14-layered convolutional neural network (CNN) operating in parallel are concatenated. Initially, these combined features are used for tumor classification. In the second step, to reduce the computational complexity, the bag of feature vector (BoFV) technique followed by principal component analysis (PCA) is introduced to select quality features. As this research focuses on the early-stage detection of brain tumors, an optimized linear support vector network (oLSVN) was introduced for classification in the third step. oLSVN sends tumors-classified images for segmentation to detect the exact area of the tumors, whereas the images in which the tumor is not detected due to poor visibility and noise undergo contrast-limited adaptive histogram equalization (CLAHE) process for noise filtration and image enhancement. These enhanced images are classified again for brain tumor detection in an early stage. A comparative analysis shows that the proposed model outperforms some already existing models. The execution time of the proposed model is 1.32seconds with 98.25%accuracy. As compared to some already existing approaches, the proposed model has an F1-Score of 98.27%,precision of 97.28%, specificity of 97.22%, and a Mathew's Correlation Coefficient of 96.52%.These results validate that the proposed state-of-the-art methodology can thus help the medical industry in the timely and efficient detection of brain tumors.

To increase the effectiveness of both the cathodic hydrogen evolution reaction (HER) and the anodic oxygen evolution reaction (OER), significant efforts are made to produce bifunctional water‐splitting electrocatalysts. In this study, bismuth oxide/nickel oxide (Bi2O3/NiO)‐based composite is supported over the nickel foam (Bi2O3/NiO‐NF) and carbon nanotube fiber (Bi2O3/NiO‐CNTF) to develop two different electrode systems for water‐splitting studies. For OER, Bi2O3/NiO‐NF and Bi2O3/NiO‐CNTF require overpotential of 401 and 369 mV, respectively, to achieve the current density of 50 mA cm−2in alkaline media, while the current density of 50 mA cm−2is achieved at overpotential of 398 and 304 mV, respectively, in neutral media. For HER, Bi2O3/NiO‐NF and Bi2O3/NiO‐CNTF achieve the current density of 50 mA cm−2at overpotential of 301 and 268 mV, respectively, in neutral media. For overall water splitting in neutral media, Bi2O3/NiO‐CNTF achieves the current density of 50 mA cm−2at cell voltage of 1.654 V. The promising performance of synthesized electrocatalysts reveals that the mixed metal oxides (p‐block and d‐block elements)‐based electrocatalysts can be potential candidates for practical water splitting in basic (1 M KOH) as well as neutral media (1 M phosphate‐buffered saline). Bismuth oxide/nickel oxide (Bi2O3/NiO) based composite is synthesized and fabricated over nickel foam (Bi2O3/NiO‐NF) and carbon nanotube fiber (Bi2O3/NiO‐CNTF) to develop bifunctional catalyst for overall water‐splitting studies. In the results, it is suggested that the development of mixed metal (p‐ and d‐block) oxides can be a suitable replacement of precious metal‐based electrocatalysts for renewable energy conversion and storage.

AbstractIn search of achieving less toxic and more potent chemotherapeutics, three novel heterocyclic benzimidazole derivatives: 2-(1H-benzo[d]imidazol-2-yl)-4-chlorophenol (BM1), 4-chloro-2-(6-methyl-1H-benzo[d]imidazol-2-yl)phenol (BM2) and 4-chloro-2-(6-nitro-1H-benzo[d]imidazol-2-yl)phenol (BM3) with DNA-targeting properties, were synthesized and fully characterized by important physicochemical techniques. The DNA binding properties of the compounds were investigated by UV–Visible absorption titrations and thermal denaturation experiments. These molecules exhibited a good binding propensity to fish sperm DNA (FS-DNA), as evident from the high binding constants (Kb) values: 1.9 × 105, 1.39 × 105and 1.8 × 104 M‒1for BM1, BM2 and BM3, respectively. Thermal melting studies of DNA further validated the absorption titration results and best interaction was manifested by BM1with ΔTm = 4.96 °C. The experimental DNA binding results were further validated theoretically by molecular docking study. It was confirmed that the molecules (BM1–BM3) bind to DNA viaan intercalative and groove binding mode. The investigations showed a correlation between binding constants and energies obtained experimentally and through molecular docking, indicating a binding preference of benzimidazole derivatives with the minor groove of DNA. BM1 was the preferential candidate for DNA binding because of its flat structure, π–π interactions and less steric hindrance. To complement the DNA interaction, antimicrobial assays (antibacterial & antifungal) were performed. It was observed that compound BM2showed promising activity against all bacterial strains (Micrococcus luteus, Staphylococcus aureus, Enterobacter aerogenesand Escherichia coli) and fungi (Aspergillus flavus, Aspergillus fumigatusand Fusarium solani), while rest of the compounds were active against selective strains. The MIC values of BM2were found to be in the range of 12.5 ± 2.2–25 ± 1.5 µg/mL. Thus, the compound BM2was found to be the effective DNA binding antimicrobial agent. Furthermore, the preliminary cytotoxic properties of synthesized compounds were evaluated by brine shrimps lethality assay to check their nontoxic nature towards healthy normal cells.Communicated by Ramaswamy H. Sarma

In the quest for better supercapacitor performance, materials with high energy storage, rapid charge transfer and excellent charge-discharge capabilities are crucial. However, improving energy density and optimizing electrode materials for supercapacitors remains a challenge. Within this perspective, we developed a novel aniline-derived polybenzoxazole-reduced graphene oxide composite (Mn3O4-pBOA-rGO) for supercapacitor applications. An electrode for supercapacitor applications was then fabricated using the synthesized composite. Various characterization techniques, such as X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy and nuclear magnetic resonance spectroscopy, were employed to analyze the structure of the material and cyclic voltammetry, electrochemical impedance spectroscopy and galvanostatic charge-discharge tests were performed to evaluate the supercapacitive performance. Remarkably, the Mn3O4-pBOA-rGO ternary nanocomposite-based electrode exhibited enhanced electrochemical performance achieving an energy density of 116 Wh kg−1in a 1 M aqueous Na2SO4electrolyte at a current density of 1 A g−1. In comparison, the Mn3O4-pBOA binary nanocomposite recorded an energy density of 25 Wh kg−1, while bare Mn3O4yielded 10 Wh kg−1. The significantly improved electrochemical properties of the Mn3O4-pBOA-rGO composite present a promising and viable solution for supercapacitor applications.