Enhancing thermal performance of phase change materials using conductive rods with length dependent melting dynamics.

Phase change materials (PCMs) suffer from slow melting rates due to their low thermal conductivity, limiting their efficiency in thermal energy storage systems. This study numerically investigates the novel use of copper rods as conductive enhancers to accelerate PCM melting in a horizontally placed hemispherical cell. Using the ANSYS/FLUENT 16 with an enthalpy-porosity model, the impact of rod integration is examined to determine the optimal rod configuration for maximising heat transfer while minimising melting time.

Integrating double techniques of statistical downscaling and bias correction to reduce bias in projections trends of future climate datasets.

Climate change is one of the most significant challenges of the 21st century, particularly its impact on surface water availability in arid and hyper-arid regions within the Euphrates River Basin. This study aims to analyze the impacts of climate change using five global climate models (GCMs) within the Coupled Model Intercomparison Project Phase 6 (CMIP6, IPCC 2021). Model outputs were statistically downscaled using Statistical Downscaling Model (SDSM 6.

The impact of para-hydroxycinnamic acid on myofibroblast trans-differentiation in MRC-5 and A549 cell lines: in silico and in vitro evaluation.

Fibrosis-related disorders like pulmonary fibrosis are chronically progressive disorders characterized by tissue scarring with a gradual decline in function. Transforming growth factor-beta1 (TGF-β1), myofibroblast trans-differentiation, and epithelial to mesenchymal transition (EMT) play a central role in fibrosis progression. Para-hydroxycinnamic acid is a naturally occurring phenolic acid metabolite having different biological activities.

Trust and explainability in robotic hand control via adversarial multiple machine learning models with EEG sensor data fusion: A fuzzy decision-making solution.

In the field of brain‒computer interfaces (BCIs), developing a reliable machine learning (ML) model for real-time robotic hand control systems based on motor imagery (MI) brain signals requires substantial research. For this purpose, a set of ML models has been developed and tested to identify robust models via MI sensor data fusion under both nonadversarial and adversarial attack conditions. This paper addresses numerous essential areas, including the development of ML models for electroencephalography (EEG) MI signal datasets, with a focus on proper preprocessing and evaluation under both nonadversarial and adversarial attack conditions.

The (Re)-emerging And ePidemic Infectious Diseases (RAPID) Stigma Scales: a cross-outbreak scale development and pyschometric validation study.

Reducing stigma during infectious disease outbreaks is crucial for delivering an effective response. However, no validated stigma scales exist for use across outbreaks, and outbreak-specific scales are developed too slowly to guide timely interventions. To enable more real-time monitoring and mitigation of stigma across outbreak contexts, we developed and validated the (Re)-emerging and ePidemic Infectious Diseases (RAPID) Stigma Scales.

Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach.

This study presents a novel approach for optimizing UAV (unmanned aerial vehicle) Multicircular flight control by developing a fractional order proportional integral derivative (FOPID)-based hybrid Eagle strategy particle swarm optimization ant lion optimizer (HESPSOALO). The proposed algorithm combines the strengths of particle swarm optimization (PSO) and the ant lion optimizer (ALO), which are enhanced by the Eagle strategy to systematically fine-tune the FOPID controller parameters. This hybrid optimization method aims to improve system stability, responsiveness, and disturbance rejection in UAVs, particularly in challenging dynamic flight conditions.

Numerical investigations of hockey groynes performance on hydrodynamic of open channels flow by using computational fluid dynamics (CFD).

Protecting river banks from turbulent flow is crucial for sustainable development. This study aims to evaluate the performance of submerged hockey groynes on river flow characteristics. This study employs numerical simulations were conducted using ANSYS Fluent, a computational fluid dynamics (CFD) software, to examine flow patterns, mean streamlines, mean velocity profiles, bed shear stresses, and vortex kinetic energy around the groynes.

Histomorphological evaluation of docetaxel effects on testes and epididymides in Wistar rats.

Background: Chemotherapy drugs, such as Docetaxel, which are crucial for treating cancer, frequently cause unknowingly damage to healthy tissues.

Aim: To investigate the histomorphological effects of docetaxel chemotherapy on certain parameters in testes and epididymides.

Method: For this purpose, 24 Wistar Albino rats were divided randomly into one control group and three treatment groups.

Metabolic Reprogramming of Anti-cancer T Cells: Targeting AMPK and PPAR to Optimize Cancer Immunotherapy.

Cancer treatment era has been revolutionized by the novel therapeutic methods such as immunotherapy in recent years. Immunotherapy-based approaches are considered effective and reliable methods that has brought hope to eradicate certain cancers. Nonetheless, there are some issues, considered as critical obstacles in successful cancer immunotherapy.

Fluorescent Sensing of Fe in Acidic Environment by Carbon Dots Derived From Empty Fruit Bunch Biochar: Central Composite Design Optimization.

A rapid, eco-friendly, and selective monitoring of Fe(III) in real media utilizing carbon dots (CDs) as a luminescence detector has been reported. CDs were fabricated by a hydrothermal route from empty fruit bunch biochar. The as-synthesized CDs were analyzed using various analytical tools.

Synergistic Interactions Between Probiotics and Anticancer Drugs: Mechanisms, Benefits, and Challenges.

Research into the role of probiotics-often referred to as "living supplements"-in cancer therapy is still in its early stages, and uncertainties regarding their effectiveness remain. Relevantly, chemopreventive and therapeutic effects of probiotics have been determined. There is also substantial evidence supporting their potential in cancer treatment such as immunotherapy.

Retraction Note: COVID-CheXNet: hybrid deep learning framework for identifying COVID-19 virus in chest X-rays images.

[This retracts the article DOI: 10.1007/s00500-020-05424-3.].

Improve power quality and stability of grid - Connected PV system by using series filter.

As the world increasingly focuses on renewable energy sources, grid-connected PV systems will continue to play a critical role in meeting our energy needs. This integration has brought many benefits, but has also created various problems related to power quality and stability at the connection points. Various techniques are used to improve the power quality, such as passive filters, tuned passive harmonic filters, and active filters.

Advanced design and Engi-economical evaluation of an automatic sugarcane seed cutting machine based RGB color sensor.

There are many problems related to the use of machine learning and machine vision technology on a commercial scale for cutting sugarcane seeds. These obstacles are related to complex systems and the way the farmers operate them, the possibility of damage to the buds during the cleaning process, and the high cost of such technology. In order to address these issues, a set of RGB color sensors was used to develop an automated sugarcane seed cutting machine (ASSCM) capable of identifying the buds that had been manually marked with a unique color and then cutting them mechanically, and the sugarcane seed exit chute was provided with a sugarcane seed monitoring unit.

Drying kinetics and thermo-environmental analysis of a PV-operated tracking indirect solar dryer for tomato slices.

The purpose of this study is to investigate how a tracking indirect solar dryer (SD) powered by photovoltaic cells affected the drying kinetics (DK) and thermo-environmental conditions of tomato slices. In this current investigation, three air speeds (1, 1.5, and 2 m/s) are used, as well as three slice thicknesses (ST) (4, 6, and 8 mm) and two SD, one of which is integrated with fixed collector motion (FCM) and another with SD tracking collector motion (TCM).

Detection and isolation of brain tumors in cancer patients using neural network techniques in MRI images.

MRI imaging primarily focuses on the soft tissues of the human body, typically performed prior to a patient's transfer to the surgical suite for a medical procedure. However, utilizing MRI images for tumor diagnosis is a time-consuming process. To address these challenges, a new method for automatic brain tumor diagnosis was developed, employing a combination of image segmentation, feature extraction, and classification techniques to isolate the specific region of interest in an MRI image corresponding to a brain tumor.

Design, and dynamic evaluation of a novel photovoltaic pumping system emulation with DS1104 hardware setup: Towards innovative in green energy systems.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose's challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems.

Performance Evaluation of Carrier-Frequency Offset as a Radiometric Fingerprint in Time-Varying Channels.

The authentication of wireless devices through physical layer attributes has attracted a fair amount of attention recently. Recent work in this area has examined various features extracted from the wireless signal to either identify a uniqueness in the channel between the transmitter-receiver pair or more robustly identify certain transmitter behaviors unique to certain devices originating from imperfect hardware manufacturing processes. In particular, the carrier frequency offset (CFO), induced due to the local oscillator mismatch between the transmitter and receiver pair, has exhibited good detection capabilities in stationary and low-mobility transmission scenarios.

Exosomal Non-coding RNA Derived from Mesenchymal Stem Cells (MSCs) in Autoimmune Diseases Progression and Therapy; an Updated Review.

Inflammation and autoimmune diseases (AD) are common outcomes of an overactive immune system. Inflammation occurs due to the immune system reacting to damaging stimuli. Exosomes are being recognized as an advanced therapeutic approach for addressing an overactive immune system, positioning them as a promising option for treating AD.

A Novel Evaluation Framework for Medical LLMs: Combining Fuzzy Logic and MCDM for Medical Relation and Clinical Concept Extraction.

Artificial intelligence (AI) has become a crucial element of modern technology, especially in the healthcare sector, which is apparent given the continuous development of large language models (LLMs), which are utilized in various domains, including medical beings. However, when it comes to using these LLMs for the medical domain, there's a need for an evaluation platform to determine their suitability and drive future development efforts. Towards that end, this study aims to address this concern by developing a comprehensive Multi-Criteria Decision Making (MCDM) approach that is specifically designed to evaluate medical LLMs.

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation of osteoarthritis severity. The utilisation of DL is expected to increase, owing to its ability to present accurate diagnoses more efficiently than traditional methods in many scenarios.