Chitosan-based hydrogel system for efficient removal of Cu[II] and sustainable utilization of spent adsorbent as a catalyst for environmental applications.

The growing requirement for clean potable water requires sustainable methods of eliminating heavy metal ions and other organic contaminants. Herein, we synthesized a novel dual-purpose magnetically separable chitosan-based hydrogel system (CSGO-R@IO) that can efficiently remove toxic Cu2+ pollutants from water. FT-IR, XRD, SEM-EDX, VSM, XPS analyses were used to characterize the synthesized hydrogel. The CSGO-R@IO hydrogel showed high swelling capacity (1036.06 %), prominent adsorption capacity for Cu2+ ions (119.5 mg/g), and good recyclability up to four cycles. The adsorption data of Cu+2 ions on hydrogel fitted better to the Langmuir isotherm model (R2 = 0.9942), indicating spontaneous monolayer adsorption of Cu2+ ions on a homogenous surface. The adsorption kinetic studies fitted better with the pseudo-second-order model (R2 = 0.9992), suggesting that the adsorption process was controlled by chemisorption. We also showed a sustainable way to convert harmful Cu2+ pollutants into valuable Cu nanoparticles for catalysis, and Cu nanoparticles loaded hydrogel (CSGO-R@IO/Cu) had high catalytic activity. Hence, building attractive multipurpose hydrogel systems will give us new ideas about how to design and use new adsorbents to clean water in real life. They will also help in recycle metals (copper and maybe others) to conserve resources.

Challenges and opportunities of pharmaceutical cocrystals: a focused review on non-steroidal anti-inflammatory drugs.

The focus of the review is to discuss the relevant and essential aspects of pharmaceutical cocrystals in both academia and industry with an emphasis on non-steroidal anti-inflammatory drugs (NSAIDs). Although cocrystals have been prepared for a plethora of drugs, NSAID cocrystals are focused due to their humongous application in different fields of medication such as antipyretic, anti-inflammatory, analgesic, antiplatelet, antitumor, and anti-carcinogenic drugs. The highlights of the review are (a) background of cocrystals and other solid forms of an active pharmaceutical ingredient (API) based on the principles of crystal engineering, (b) why cocrystals are an excellent opportunity in the pharma industry, (c) common methods of preparation of cocrystals from the lab scale to bulk quantity, (d) some latest case studies of NSAIDs which have shown better physicochemical properties for example; mechanical properties (tabletability), hydration, solubility, bioavailability, and permeability, and (e) latest guidelines of the US FDA and EMA opening new opportunities and challenges.

In acid-aminopyrimidine continuum: experimental and computational studies of furan tetracarboxylate-2-aminopyrimidinium salt.

Salts and cocrystals are the two important solid forms when a carboxylic acid crystallizes with an aminopyrimidine base such that the extent of proton transfer distinguishes between them. The ΔpK a value (pK a(base) - pK a(acid)) predicts whether the proton transfer will occur or not. However, the ΔpK a range, 0 < ΔpK a < 3, is elusive where the formation of cocrystal or salt cannot be predicted. The current study has been done to obtain a generalization in this elusive range with the Cambridge Structural Database (CSD). Based on the generalization, a novel salt (FTCA)-(2-AP)+ of furantetracarboxylic acid (FTCA) with 2-aminopyrimidine (2-AP) is obtained. The structural confirmation was done by single-crystal X-ray diffraction (SCXRD). Density functional theory (DFT) calculations were performed at the IEF-PCM-B3LYP-D3/6-311G(d,p) level to optimize the geometrical coordinates of salt for frontier molecular orbitals (FMOs) and molecular electrostatic potential (MESP). The geometrical parameters of most of the atoms of the optimized salt structure were comparable with SCXRD data. Additionally, results of other computational methods such as ab initio (Hartree-Fock; HF and second-order-Møller-Plesset perturbation; MP2) and semi-empirical were also compared with experimental results of the salt. Quantum theory of atoms in molecules (QTAIM), reduced density gradient (RDG), and natural bond orbital (NBO) analyses were done to calculate the strength and nature of non-covalent interactions present in the salt. Furthermore, Hirshfeld surface analysis, interaction energy calculations, and total energy frameworks were performed for qualitative and quantitative estimations of strong and weak intermolecular interactions.

CNN Fixations: An Unraveling Approach to Visualize the Discriminative Image Regions.

Deep convolutional neural networks (CNNs) have revolutionized the computer vision research and have seen unprecedented adoption for multiple tasks, such as classification, detection, and caption generation. However, they offer little transparency into their inner workings and are often treated as black boxes that deliver excellent performance. In this paper, we aim at alleviating this opaqueness of CNNs by providing visual explanations for the network's predictions. Our approach can analyze a variety of CNN-based models trained for computer vision applications, such as object recognition and caption generation. Unlike the existing methods, we achieve this via unraveling the forward pass operation. The proposed method exploits feature dependencies across the layer hierarchy and uncovers the discriminative image locations that guide the network's predictions. We name these locations CNN fixations, loosely analogous to human eye fixations. Our approach is a generic method that requires no architectural changes, additional training, or gradient computation, and computes the important image locations (CNN fixations). We demonstrate through a variety of applications that our approach is able to localize the discriminative image locations across different network architectures, diverse vision tasks, and data modalities.