A comprehensive review on nanoparticle-based photo acoustic: current application and future prospective.

In vivo, molecular imaging is prevalent for biology research and therapeutic practice. Among advanced imaging technologies, photoacoustic (PA) imaging and sensing is gaining interest around the globe due its exciting features like high resolution and good (~ few cm) penetration depth. PA imaging is a recent development in ultrasonic technology that generates acoustic waves by absorbing optical energy.

Correction to: Sustained attention detection in humans using a prefrontal theta-EEG rhythm.

[This corrects the article DOI: 10.1007/s11571-024-10113-0.].

Correction: Construction of efficient Pb(II) carboxylate catalysts for the oxygen and hydrogen evolution reactions.

Correction for 'Construction of efficient Pb(II) carboxylate catalysts for the oxygen and hydrogen evolution reactions' by Janak , , 2024, https://doi.org/10.1039/d4dt02958e.

Recent advances in dark fermentative hydrogen production from vegetable waste: role of inoculum, consolidated bioprocessing, and machine learning.

Waste-centred-bioenergy generation have been garnering interest over the years due to environmental impact presented by fossil fuels. Waste generation is an unavoidable consequence of urbanization and population growth. Sustainable waste management techniques that are long term and environmentally benign are required to achieve sustainable development.

Investigating the genomic and metabolic abilities of PGPR Pseudomonas fluorescens in promoting plant growth and fire blight management.

Pseudomonas fluorescens is commonly found in diverse environments and is well known for its metabolic and antagonistic properties. Despite its remarkable attributes, its potential role in promoting plant growth remains unexplored. This study examines these traits across 14 strains residing in diverse rhizosphere environments through pangenome and comparative genome analysis, alongside molecular docking studies against Erwinia amylovora to combat fire blight.

Ship detection using ensemble deep learning techniques from synthetic aperture radar imagery.

Synthetic Aperture Radar (SAR) integrated with deep learning has been widely used in several military and civilian applications, such as border patrolling, to monitor and regulate the movement of people and goods across land, air, and maritime borders. Amongst these, maritime borders confront different threats and challenges. Therefore, SAR-based ship detection becomes essential for naval surveillance in marine traffic management, oil spill detection, illegal fishing, and maritime piracy.

Sustained attention detection in humans using a prefrontal theta-EEG rhythm.

This research highlights the importance of the prefrontal theta-EEG rhythm in sustained attention monitoring over the Fp1 electrode. In an experiment conducted with 20 participants, four successive mental tasks are sent briefly by an automated computer program connected to a speakerphone: wait, relax, get ready, and concentrate. Furthermore, each individual participated in this experiment 20 times.

Engineering considerations in the design of tissue specific bioink for 3D bioprinting applications.

Over eight million surgical procedures are conducted annually in the United Stats to address organ failure or tissue losses. In response to this pressing need, recent medical advancements have significantly improved patient outcomes, primarily through innovative reconstructive surgeries utilizing tissue grafting techniques. Despite tremendous efforts, repairing damaged tissues remains a major clinical challenge for bioengineers and clinicians.

Autoencoder-based drug synergy framework for malignant diseases.

Drug combination emerges as a viable option for the treatment of malignant diseases. Drug combination outperforms monotherapy by improving therapeutic efficacy, reducing toxicity, and overcoming drug resistance. To find viable drug combinations it is difficult to traverse empirically because of enormous combinational space.

Green synthesized nitrogen-doped nickel hexacyanoferrate incorporated in guar gum-xanthan gel for efficient sunlight-driven degradation of water pollutants.

Herein, nitrogen-doped nickel hexacyanoferrate (N@NiHCF) nanoparticles were prepared via co-precipitation and incorporated in guar gum (GG)-Xanthan gum (Xa) based-polymeric-matrix (GGXa@N@NiHCF) for efficient removal of rose bengal (RB) dye and nonyl phenol (NP) pollutants under sunlight. PXRD, FESEM, XPS, and FTIR analysis verified successful integration of N@NiHCF nanoparticles into GGXa matrix. Scherrer and Williamson-Hall equations estimated average-crystallite sizes of GGXa@N@NiHCF nanoparticles to be 16.

Synergistic effect of Zn-AgInS/CdS Z-scheme heterojunction and S-doped rGO for efficient removal of chromium from contaminated water.

This study aimed to synthesize a Zn-AgInS/CdS/SrGO nanocomposite for Cr(vi) removal from contaminated water under solar irradiation. To prevent photo corrosion of CdS, a Z-scheme heterojunction was formed between CdS and Zn-AgInS. The introduction of Ag plasmonic materials extended the light absorption range and stabilized the photocatalyst.

Machine learning approaches for adequate prediction of flow resistance in alluvial channels with bedforms.

In natural rivers, flow conditions are mainly dependent on flow resistance and type of roughness. The interactions among flow and bedforms are complex in nature as bedform dynamics primarily regulate the flow resistance. Manning's equation is the most frequently used equation for this purpose.

Fatigue analysis of ambient-cured geopolymer concrete for high-traffic pavements.

The building sector is growing at a rapid rate, leading to an increased demand for construction materials. Concrete made with Ordinary Portland Cement (OPC) has long been the preferred choice due to its excellent bonding properties and versatility as demanded by construction process. However, the manufacturing of Ordinary Portland Cement (OPC) leads to negative impacts on the environment, with the cement sector responsible for around 5-8% of global CO emissions.

Highly Sensitive and Selective Fluorescence and Smartphone-Based Sensor for Detection of Rutin Using Boron Nitrogen Co-doped Graphene Quantum Dots.

This research explores the fluorescence properties and photostability of boron nitrogen co-doped graphene quantum dots (BN-GQDs), evaluating their effectiveness as sensors for rutin (RU). BN-GQDs are biocompatible and exhibit notable absorbance and fluorescence characteristics, making them suitable for sensing applications. The study utilized various analytical techniques to investigate the chemical composition, structure, morphology, optical attributes, elemental composition, and particle size of BN-GQDs.

Biodegradable plastics: mechanisms of degradation and generated bio microplastic impact on soil health.

Conventional petroleum-derived polymers are valued for their versatility and are widely used, owing to their characteristics such as cost-effectiveness, diverse physical and chemical qualities, lower molecular weight, and easy processability for large-scale production. However, the extensive accumulation of such plastics leads to serious environmental issues. To combat this existing situation, an alternative lies in the production of bioplastics from natural and renewable sources such as plants, animals, microbes, etc.

Harnessing the power of hybrid deep learning algorithm for the estimation of global horizontal irradiance.

Accurately and precisely estimating global horizontal irradiance (GHI) poses significant challenges due to the unpredictable nature of climate parameters and geographical limitations. To address this challenge, this study proposes a forecasting framework using an integrated model of the convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU). The proposed model uses a dataset of four different districts in Rajasthan, each with unique solar irradiance patterns.

Construction of a novel ternary synergistic CuFeO-SnO-rGO heterojunction for efficient removal of cyanide from contaminated water.

Many industrial effluents release cyanide, a well-known hazardous and bio-recalcitrant pollutant, and thus, the treatment of cyanide wastewater is a major challenge. In the current study, a CuFeO-SnO-rGO nanocomposite was synthesized to remove cyanide from an aqueous system. The structural and morphological characterizations of the nanomaterials were investigated by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and energy dispersive spectra (EDX) analysis.

Synthesis and characterization of novel guar gum based waste material derived nanocomposite for effective removal of hexabromocyclododecane and lindane.

Herein, efficient degradation of hexabromocyclododecane (HBCD) and Lindane, a persistent organic pollutant using guar gum based calcium oxide doped silicon dioxide (GG-CaO@SiO) has been reported. The nanocomposite was prepared by waste egg shell (CaO) and rice husk (SiO) was well characterized. The maximum degradation of HBCD and Lindane were observed at 8 mg catalyst loading, neutral pH, and 2 mg L of pollutant amount.

Recent Advances in Two-Dimensional Nanomaterials for Healthcare Monitoring.

The development of advanced technologies for the fabrication of functional nanomaterials, nanostructures, and devices has facilitated the development of biosensors for analyses. Two-dimensional (2D) nanomaterials, with unique hierarchical structures, a high surface area, and the ability to be functionalized for target detection at the surface, exhibit high potential for biosensing applications. The electronic properties, mechanical flexibility, and optical, electrochemical, and physical properties of 2D nanomaterials can be easily modulated, enabling the construction of biosensing platforms for the detection of various analytes with targeted recognition, sensitivity, and selectivity.