Building a text collection for Urdu information retrieval

Urdu is a widely spoken language in the Indian subcontinent with over 300 million speakers worldwide. However, linguistic advancements in Urdu are rare compared to those in other European and Asian languages. Therefore, by following Text Retrieval Conference standards, we attempted to construct an extensive text collection of 85 304 documents from diverse categories covering over 52 topics with relevance judgment sets at 100 pool depth. We also present several applications to demonstrate the effectiveness of our collection. Although this collection is primarily intended for text retrieval, it can also be used for named entity recognition, text summarization, and other linguistic applications with suitable modifications. Ours is the most extensive existing collection for the Urdu language, and it will be freely available for future research and academic education.     

Terpenoids as Human Neutrophil Elastase (HNE) Inhibitors: A Comprehensive Review of Natural Anti-inflammatory Isoprenoids

Human neutrophil elastase (HNE) is an enzyme that plays a key role in the body‘s inflammatory response. It has been linked to several diseases such as chronic obstructive pulmonary disease (COPD), emphysema, and cystic fibrosis. As potential treatments for these diseases, HNE inhibitors are of great interest. Metabolites derived from plants, particularly terpenoids such as β-caryophyllene found in black pepper and other plants, and geraniol present in several essential oils, are recognized as significant sources of inhibitors for HNE. Because of their ability to inhibit HNE, terpenoids are considered promising candidates for developing novel therapies to treat inflammatory conditions such as COPD and emphysema. Furthermore, nature can serve as an excellent designer, and it may offer a safer drug candidate for inhibiting HNE production and activity in the future. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were searched to get relevant and up-to-date literature on terpenoids as human neutrophil elastase inhibitors. This review focuses on the isolation, chemical diversity, and inhibition of human neutrophil elastase (HNE) of various terpenoids reported from natural sources up to 2022. A total of 251 compounds from various terpenoids classes have been reported. Further, it also provides a summary of HNE inhibitors and includes a thorough discussion on the structure-activity relationship.     

Natural fibers and zinc hydroxystannate 3D microspheres based composite paper sheets for modern bendable energy storage application

For modern high-tech flexible energy storage devices, it becomes important to synthesize micro-/nanostructures as per the required shape and morphology with superior physical and electro-active characteristics. This work shares the fabrication and characterization of ZnSn(OH)₆ (Zinc hydroxystannate [ZHS]) prepared by facile microwave-assisted technique and furthermore converted into flexible sheets by employing lignocelluloses (LC) known as natural fibers, collected from Carica papaya leaf petiole as a substrate to provide the flexible matrix. X-ray diffraction measurements confirm the successful crystalline structure of ZHS. Scanning electron microscopy and transmission electron microscopy showed the solid spherical structure of ZHS microspheres. Fourier transform infrared spectrometry and Raman spectroscopy confirmed the composite formation of ZHS and LC-based composite sheets (ZHS/LC sheets). Electrochemical measurements that is, cyclic voltammetry (CV), Galvanostatic charge/discharge, and electrochemical impedance (EIS) spectroscopy revealed the electroactive behavior of ZHS/LC paper sheets as working electrode for energy storage applications. CV measurements revealed the specific capacitance of 100 F/g and EIS measurements confirmed the decrease in the resistance of LC fiber after the growth of ZHS microspheres. Presented flexible ZHS based paper sheets will be highly feasible for the modern bendable/flexible/disposable energy storage applications.     

Synergistic Functionality of Dopants and Defects in Co-Phthalocyanine/B-CN Z-Scheme Photocatalysts for Promoting Photocatalytic CO2 Reduction Reactions

The realization of solar-light-driven CO₂ reduction reactions (CO₂ RR) is essential for the commercial development of renewable energy modules and the reduction of global CO₂ emissions. Combining experimental measurements and theoretical calculations, to introduce boron dopants and nitrogen defects in graphitic carbon nitride (g-C₃N₄), sodium borohydride is simply calcined with the mixture of g-C₃N₄ (CN), followed by the introduction of ultrathin Co phthalocyanine through phosphate groups. By strengthening H-bonding interactions, the resultant CoPc/P-BNDCN nanocomposite showed excellent photocatalytic CO₂ reduction activity, releasing 197.76 and 130.32 µmol h⁻¹ g⁻¹ CO and CH₄, respectively, and conveying an unprecedented 10-26-time improvement under visible-light irradiation. The substantial tuning is performed towards the conduction and valance band locations by B-dopants and N-defects to modulate the band structure for significantly accelerated CO₂ RR. Through the use of ultrathin metal phthalocyanine assemblies that have a lot of single-atom sites, this work demonstrates a sustainable approach for achieving effective photocatalytic CO₂ activation. More importantly, the excellent photoactivity is attributed to the fast charge separation via Z-scheme transfer mechanism formed by the universally facile strategy of dimension-matched ultrathin (≈4 nm) metal phthalocyanine-assisted nanocomposites.     

Drug Usage Safety from Drug Reviews with Hybrid Machine Learning Approach

With the increasing usage of drugs to remedy different diseases, drug safety has become crucial over the past few years. Often medicine from several companies is offered for a single disease that involves the same/similar substances with slightly different formulae. Such diversification is both helpful and dangerous as such medicine proves to be more effective or shows side effects to different patients. Despite clinical trials, side effects are reported when the medicine is used by the mass public, of which several such experiences are shared on social media platforms. A system capable of analyzing such reviews could be very helpful to assist healthcare professionals and companies for evaluating the safety of drugs after it has been marketed. Sentiment analysis of drug reviews has a large potential for providing valuable insights into these cases. Therefore, this study proposes an approach to perform analysis on the drug safety reviews using lexicon-based and deep learning techniques. A dataset acquired from the ‘Drugs.Com’ containing reviews of drug-related side effects and reactions, is used for experiments. A lexicon-based approach, Textblob is used to extract the positive, negative or neutral sentiment from the review text. Review classification is achieved using a novel hybrid deep learning model of convolutional neural networks and long short-term memory (CNN-LSTM) network. The CNN is used at the first level to extract the appropriate features while LSTM is used at the second level. Several well-known machine learning models including logistic regression, random forest, decision tree, and AdaBoost are evaluated using term frequency-inverse document frequency (TF-IDF), a bag of words (BoW), feature union of (TF-IDF + BoW), and lexicon-based methods. Performance analysis with machine learning models, long short term memory and convolutional neural network models, and state-of-the-art approaches indicate that the proposed CNN-LSTM model shows superior performance with an 0.96 accuracy. We also performed a statistical significance T-test to show the significance of the proposed CNN-LSTM model in comparison with other approaches.     

Particle Swarm Optimization for Solving Sine-Gordan Equation

The term ‘optimization’ refers to the process of maximizing the beneficial attributes of a mathematical function or system while minimizing the unfavorable ones. The majority of real-world situations can be modelled as an optimization problem. The complex nature of models restricts traditional optimization techniques to obtain a global optimal solution and paves the path for global optimization methods. Particle Swarm Optimization is a potential global optimization technique that has been widely used to address problems in a variety of fields. The idea of this research is to use exponential basis functions and the particle swarm optimization technique to find a numerical solution for the Sine-Gordan equation, whose numerical solutions show the soliton form and has diverse applications. The implemented optimization technique is employed to determine the involved parameter in the basis functions, which was previously approximated as a random number in the work reported till now in the literature. The obtained results are comparable with the results obtained in the literature. The work is presented in the form of figures and tables and is found encouraging.     

Copper substituted nickel ferrite nanoparticles anchored onto the graphene sheets as electrode materials for supercapacitors fabrication

Nickel ferrites with high theoretical capacitance value as compared to the other metal oxides have been applied as electrode material for energy storage devices i.e. batteries and supercapacitors. High tendency towards aggregation and less specific surface area make the metal oxides poor candidate for electrochemical applications. Therefore, the improvements in the electrochemical properties of nickel ferrites (NiFe₂O₄) are required. Here, we report the synthesis of graphene nano-sheets decorated with spherical copper substituted nickel ferrite nanoparticles for supercapacitors electrode fabrication. The copper substituted and unsubstituted NiFe₂O₄ nanoparticles were prepared via wet chemical co-precipitation route. Reduced graphene oxide (rGO) was prepared via well-known Hummer's method. After structural characterization of both ferrite (Ni_1-xCu_xFe₂O₄) nanoparticles and rGO, the ferrite particles were decorated onto the graphene sheets to obtain Ni_1-xCu_xFe₂O₄@rGO nanocomposites. The confirmation of preparation of these nanocomposites was confirmed by scanning electron microscopy (SEM). The electrochemical measurements of nanoparticles and their nanocomposites (Ni_0.9Cu_0.1Fe₂O₄@rGO) confirmed that the nanocomposites due to highly conductive nature and relatively high surface area showed better capacitive behavior as compared to bare nanoparticles. This enhanced electrochemical energy storage properties of nanocomposites were attributed to the graphene and also supported by electrical (I-V) measurements. The cyclic stability experiments results showed ~65% capacitance retention after 1000 cycles. However this retention was enhanced from 65% to 75% for the copper substituted nanoparticles (Ni_0.9Cu_0.1Fe₂O₄) and 65–85% for graphene based composites. All this data suggest that these nanoparticles and their composites can be utilized for supercapacitors electrodes fabrication.     

Potential of bacteriocinogenic Lactococcus lactis subsp. lactis inhabiting low pH vegetables to produce nisin variants

Antimicrobial behavior of lactic acid bacteria (LAB) has been explored since many years to assess their ability to produce bacteriocin, a natural preservative, to increase the shelf life of food. This study aims to characterize bacteriocin producing strains of lactic acid bacteria isolated from acidic to slightly acidic raw vegetables including tomato, bell pepper and green chili and to investigate their potential to inhibit food related bacteria. Among twenty nine LAB screened for antimicrobial activity, three exhibited antagonism against closely related bacterial isolates which was influenced by varying temperature and pH. They were identified up to strain level as Lactococcus lactis subsp. lactis TI-4, L. lactis subsp. lactis CE-2 and L. lactis subsp. lactis PI-2 based on 16S rRNA gene sequence. Their spectrum of inhibition was observed against food associated strains of Bacillus subtilis and Staphylococcus aureus. Moreover, L. lactis subsp. lactis PI-2 selected on the basis of higher antimicrobial activity was further evaluated for bacteriocin production which was detected as nisin A and nisin Z. These findings suggest the possible use of L. lactis strains of vegetable origin as protective cultures in slightly acidic as well as slightly alkaline food by the bio-preservative action of bacteriocins.     

Control of viscous fingering and mixing in miscible displacements with time-dependent rates

In miscible displacements encountered in enhanced oil recovery processes, the unfavorable viscosity contrast between injected solvent and oil usually leads to viscous fingering (VF), a hydrodynamic instability which may result in a lower sweep efficiency and oil recovery. This phenomenon can be observed in a wide range of flows in subsurface porous media. This study examined a simple cyclic time-dependent displacement rate and its effects on the onset and longer development of VF. It is found that such varying displacement rate can either stabilize or destabilize VF, depending on the cycle period, amplitude, and displacement scenarios. The most important mechanism is that such time-dependent rate can effectively change the competition between convection (destabilizing effect) and dispersion (stabilizing effect). This is different from the widely used constant injection rate where the flow instability is actually determined by the Peclet number and mobility contrast for a given scenario. This study therefore provided a new aspect to control VF, either enhance or reduce, with low additional costs. It is therefore both scientifically and practically important for a wide range of flows in subsurface porous media. © 2017 American Institute of Chemical Engineers AIChE J, 65: 360–371, 2019     

Comparison of chlorination and chloramination practices on microbial inactivation efficiencies within a scaled‐up water distribution network using central composite design

Disinfection practices reduce the incidence of water‐borne diseases but may result in formation of disinfection byproducts (DBPs) in raw water that are reported to be carcinogenic. Central composite design (CCD) was employed in the present study for optimization of disinfectant dose and contact time with the rationale to evaluate if an optimal balance could be achieved between minimal DBPs formation and effective microbial inactivation with either free or combined chlorine in treated water within a lab‐scale prototype network to simulate real water distribution network conditions. After a series of experimental runs based upon design of experiments (DoE) by CCD, dose was found to be the most significant factor (P < 0.01) in determining DBPs formation in both disinfectant’s applications. Where, contact time significantly (P < 0.01) affected bacterial inactivation in chlorination experiments, in contrast, dose was effective in chloramination experiments. Thus, it was concluded that the optimal balance may be achieved in the water networks with the help of multifactorial optimization when disinfectant dose was maintained near 3 mg/L as applied chlorine dose in both disinfection cases, while contact time was 62 and 155 min for chlorine and chloramine, respectively.