Synthesis of "Ice Cube" Shaped Zeolite A Type and Cu Ion-Exchanged Zeolites and Study of Their CO Adsorption Performance.

In this study, zeolite type A and four Cu ion-exchanged zeolites were synthesized through cationic ion exchange process with Cu concentrations of 0.05, 0.1, 0.

Deep Learning for Parkinson's Disease Diagnosis: A Graph Neural Network (GNN) Based Classification Approach with Graph Wavelet Transform (GWT) Using Protein-Peptide Datasets.

An important neurological disorder of Parkinson's Disease (PD) is characterized by motor and non-motor activity of the patients. Empirical condition of the patient: PD assessment uses the Movement Disorder Society Unified Parkinson's Rating Scale part III (MDS-UPDRS-III) measures for identifying the prediction of PD. Due to the unstable value of the measurement, the PD prediction and tracking lead to a lower prediction rate.

Neuro connect: Integrating data-driven and BiGRU classification for enhanced autism prediction from fMRI data.

Autism Spectrum Disorder (ASD) poses a significant challenge in early diagnosis and intervention due to its multifaceted clinical presentation and lack of objective biomarkers. This research presents a novel approach, termed Neuro Connect, which integrates data-driven techniques with Bidirectional Gated Recurrent Unit (BiGRU) classification to enhance the prediction of ASD using functional Magnetic Resonance Imaging (fMRI) data. This study uses both structural and functional neuroimaging data to investigate the complex brain underpinnings of autism spectrum disorder (ASD).

Impact of Nitrogen-Enriched 1T/2H-MoS/CdS as an Electrode Material for Hybrid Supercapacitor.

Transition metal chalcogenides (TMX) have attracted energy researchers due to their role as high-performance electrode materials for energy storage devices. A facile one-pot hydrothermal technique was adopted to synthesize a molybdenum disulfide/cadmium sulfide (MoS/CdS) (MCS) composite. The as-prepared samples were subjected to characterization techniques such as XRD, FT-IR, SEM, TEM, and XPS to assess their structure, morphology, and oxidation states.

Sensitivity assessment of optimal control strategies and cost-effectiveness analysis of a novel Candida Auris environmental transmission model in intensive care facilities.

Candida Auris is an emerging fungal pathogen flagged by CDC as a serious global health threat among nosocomial infections in the recent times. As an evolving pathogen that often goes misidentified or unidentified under standard laboratory tests, it has the ability to cause fatal infections among the target population involving patients with serious medical conditions admitted to intensive care facilities, due to its capacity to resist anti-fungal treatment and the ability to persist in the hospital environment for long periods. The subject of this paper is to develop a deterministic model to study the transmission nature of Candida Auris wherein measures like apt admission screening methods with weekly screening follow-ups, transmission prevention, proper treatment protocols and environmental disinfection procedures are introduced as constant mitigating controls into the model initially which are later redefined as variable control functions during the optimal control analysis.

A study on microstructural, mechanical properties, and optimization of wear behaviour of friction stir processed AZ31/TiC composites using response surface methodology.

The primary objective of this study is to investigate the microstructural, mechanical, and wear behaviour of AZ31/TiC surface composites fabricated through friction stir processing (FSP). TiC particles are reinforced onto the surface of AZ31 magnesium alloy to enhance its mechanical properties for demanding industrial applications. The FSP technique is employed to achieve a uniform dispersion of TiC particles and grain refinement in the surface composite.

Study on fresh and hardened state properties of eco-friendly foamed concrete incorporating waste soda-lime glass.

Improper waste management is causing global environmental problems. Waste glass may have adverse impacts on the ecosystem. While a substantial amount of soda-lime glass bottle (SGB) undergoes recycling to create new glass items, a significant volume still ends up in landfills.

Machine Learning-Based Prediction of Cyclic Voltammetry Behavior of Substitution of Zinc and Cobalt in BiFeO/BiFeO for Supercapacitor Applications.

Artificial intelligence and machine learning have become indispensable tools across various disciplines in the present century. In that way, the role of artificial intelligence and machine learning in energy storage devices was investigated. As a preliminary study, the data derived from electrochemical studies were used for the prediction.

In-vitro and in-vivo investigation of wound healing efficacy of Syzygium cumini leaf extracts loaded carboxymethylcellulose film.

The study focused on Syzygium cumini Leaf Extract (SCLE) loaded into Carboxymethylcellulose (CMC) film via Solution casting. Phytochemical screening revealed carbohydrates, and HPLC analysis identified quercetin, known for promoting wound healing. FT-IR spectroscopy confirmed various functional groups.

Evaluation of microwave irradiated Polyacrylamide grafted Opuntia leaf mucilage graft copolymer (OPM-g-PAM) as effective controlled release polymer for release of Rosuvastastin as model drug.

Controlled drug delivery systems offer numerous advantages. This research evaluates Opuntia leaf mucilage grafted with polyacrylamide (OPM-g-PAM) as a promising controlled-release polymer. PAM chains were grafted onto the backbone of OPM using a microwave-assisted method.

Nanofibers Embedded with Nanoparticles as Carriers for the Controlled Release of Anticancer Drug: Promoting the Apoptosis of Breast Cancer Cell Line and Growth Inhibition of Microbial Strains.

The polymeric nanofiber mats were produced from polylactic acid, methylcellulose, and polyethylene glycol with 5-fluorouracil (5Fu) drug and iron oxide (FeO) nanoparticles. Spectral and crystallographic studies clearly elucidated the ionic interactions, structure and nature of the mats. FeO nanoparticles <10 nm in size, along with methyl cellulose and polyethylene glycol, have significantly reduced the size of nanofiber mats.

Identifying pests in precision agriculture using low-cost image data acquisition.

Unmanned Aerial Vehicles (UAVs), often called drones, have gained progressive prevalence for their swift operational ability as well as their extensive applicability in diverse real-world situations. Of late, UAV usage in precision agriculture has attracted much interest from scientific community. This study will look at drone aid in precise farming.

Artificial neural network, machine learning modelling of compressive strength of recycled coarse aggregate based self-compacting concrete.

This research study aims to understand the application of Artificial Neural Networks (ANNs) to forecast the Self-Compacting Recycled Coarse Aggregate Concrete (SCRCAC) compressive strength. From different literature, 602 available data sets from SCRCAC mix designs are collected, and the data are rearranged, reconstructed, trained and tested for the ANN model development. The models were established using seven input variables: the mass of cementitious content, water, natural coarse aggregate content, natural fine aggregate content, recycled coarse aggregate content, chemical admixture and mineral admixture used in the SCRCAC mix designs.

Facile fabrication of amorphous Al/Fe based metal-organic framework as effective heterogeneous fenton catalyst for environmental remediation.

This study presents a facile preparation and durable amorphous Fe and Al-based MOF nanoplate (AlFe-BTC MOFs) catalyst with notable stability in Fenton reactions. Rigorous characterization using XRD, HR-TEM, and BET confirms the amorphous nature of the synthesized AlFe-BTC MOFs, revealing mesopores (3.4 nm diameter), a substantial surface area (232 m/g), and a pore volume of 0.

Enhanced fresh and hardened properties of foamed concrete modified with nano-silica.

Nowadays, the application of nanotechnology has gained increased attention in the concrete technology field. Several applications of concrete require light weight; one such concrete used is foamed concrete (FC), which has more voids in the microstructure. In this study, nano-silica (NS) was utilized, which exhibits a pozzolanic nature, and it reacts with other pozzolanic compositions (like lime, alumina, etc.

Machine learning, a powerful tool for the prediction of BiVO nanoparticles efficiency in photocatalytic degradation of organic dyes.

Wastewater pollution caused by organic dyes is a growing concern due to its negative impact on human health and aquatic life. To tackle this issue, the use of advanced wastewater treatment with nano photocatalysts has emerged as a promising solution. However, experimental procedures for identifying the optimal conditions for dye degradation could be time-consuming and expensive.

Virtual registration of comminuted bone fracture and preoperative assessment of reconstructed bone model using the Procrustes algorithm based on CT dataset.

A research work was undergone in a virtual bone reduction process for reconstruction of the comminuted pelvic bone fracture using a CT scan dataset of patients. This includes segmentation, 3D model optimization and bone registration technique. The accuracy of the reconstructed bone model was validated using Finite Element Method.

A novel attention-based cross-modal transfer learning framework for predicting cardiovascular disease.

Cardiovascular disease (CVD) remains a leading cause of death globally, presenting significant challenges in early detection and treatment. The complexity of CVD arises from its multifaceted nature, influenced by a combination of genetic, environmental, and lifestyle factors. Traditional diagnostic approaches often struggle to effectively integrate and interpret the heterogeneous data associated with CVD.

Unpacking Phthalates from Obscurity in the Environment.

Phthalates (PAEs) are a group of synthetic esters of phthalic acid compounds mostly used as plasticizers in plastic materials but are widely applied in most industries and products. As plasticizers in plastic materials, they are not chemically bound to the polymeric matrix and easily leach out. Logically, PAEs should be prevalent in the environment, but their prevalence, transport, fate, and effects have been largely unknown until recently.

Polymer-assisted synthesis of CoO/CoO microballs decorated N-doped carbon for symmetric supercapacitor.

Cobalt oxide (Co) and cobalt oxide/N-doped carbon composites (Co-NC) were synthesized and applied as electrode materials for supercapacitors. The pristine cobalt oxide was prepared hydrothermally at 160 °C (CoH160) and further calcined at three different temperatures of 300, 400, and 500 °C (CoC300, CoC400, and CoC500). The cobalt oxide prepared at 300 °C was composited with N-doped carbon prepared from g-CN at four different weight ratios 1 : 0.

A Novel partial sequence technique based Chaotic biogeography optimization for PAPR reduction in eneralized frequency division multiplexing waveform.

For Orthogonal Frequency Division Multiplexing (OFDM) systems, the most significant problem is the peak-to-average power ratio. The utilisation of partial transmission sequence, often known as PTS, is an efficient method for reducing PAPR. When it comes to minimizing the peak-to-average power ratio (PAPR) in Orthogonal Frequency Division Multiplexing (OFDM) Systems, PTS is one of the most effective approaches that may be used.

In vitro-in vivo wound healing efficacy of Tridax Procumbens extract loaded Carboxymethylcellulose film.

In this work, Tridax Procumbens Extracts (TPE) were blended with Carboxymethylcellulose (CMC), and film was developed through the casting method. The phytochemical screening of the TPE/CMC film was carried out and found the presence of carbohydrates, tannins, saponins, and cardiac glycosides. The presence of elements such as C, O, Na, P, Cl, K, Ca, Mn, and Nb in TP/CMC film was confirmed through EDX.

Attempt to identify antimicrobial Tridax procumbens (TP) mechanical properties using experimental work coupled with FEM model for biomedical applications.

Medicinal plants play a prodigious role in the wound-healing process. Tridax procumbens (TP) has been proven to show strong antimicrobial activity against Staphylococcus aureus and could heal skin infections. Identifying mechanical properties of TP in his solid state and mixed with carboxymethylcellulose (CMC) have never been studied before.