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In the present scenario, cancerous tumours are common in humans due to major changes in nearby environments. Skin cancer is a considerable disease detected among people. This cancer is the uncontrolled evolution of atypical skin cells. It occurs when DNA injury to skin cells, or a genetic defect, leads to an increase quickly and establishes malignant tumors. However, in rare instances, many types of skin cancer occur from DNA changes tempted by infrared light affecting skin cells. This disease is a worldwide health problem, so an accurate and appropriate diagnosis is needed for efficient treatment. Current developments in medical technology, like smart recognition and analysis utilizing machine learning (ML) and deep learning (DL) techniques, have transformed the analysis and treatment of these conditions. These approaches will be highly effective for the recognition of skin cancer utilizing biomedical imaging. This study develops a Multi-scale Feature Fusion of Deep Convolutional Neural Networks on Cancerous Tumor Detection and Classification (MFFDCNN-CTDC) model. The main aim of the MFFDCNN-CTDC model is to detect and classify cancerous tumours using biomedical imaging. To eliminate unwanted noise, the MFFDCNN-CTDC method initially utilizes a sobel filter (SF) for the image preprocessing stage. For the segmentation process, Unet3+ is employed, providing precise localization of tumour regions. Next, the MFFDCNN-CTDC model incorporates multi-scale feature fusion by combining ResNet50 and EfficientNet architectures, capitalizing on their complementary strengths in feature extraction from varying depths and scales of the input images. The convolutional autoencoder (CAE) model is utilized for the classification method. Finally, the parameter tuning process is performed through a hybrid fireworks whale optimization algorithm (FWWOA) to enhance the classification performance of the CAE model. A wide range of experiments is performed to authorize the performance of the MFFDCNN-CTDC approach. The experimental validation of the MFFDCNN-CTDC approach exhibited a superior accuracy value of 98.78% and 99.02% over existing techniques under ISIC 2017 and HAM10000 datasets., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

In recent decades, poorly insulated windows have increased the energy consumption of heating and cooling systems, thus contributing to excessive carbon dioxide emissions and other related pollution issues. From this perspective, the electrochromic (EC) windows could be a tangible solution as the indoor conditions are highly controllable by these smart devices even at a low applied voltage. Literally, vanadium pentoxide (V 2 O 5 ) is a renowned candidate for the EC application due to its multicolor appearance and substantial lithium insertion capacity. Despite the growing interest in V 2 O 5 thin films, only limited literature study is available for V 2 O 5 films specifically the annealing effects of these films at lower temperatures (< 300 °C). It is noteworthy that a low temperature is advantageous for glass-based EC devices, as it prevents deformation, cracking, and structural damage to the transparent conductive glass. In this study, V 2 O 5 thin films were fabricated using the sol-gel spin coating technique prior to annealing over the temperature range of 100-300 °C. Subsequently, V 2 O 5 thin films were assembled into a device form to analyze their EC characteristics. The V 2 O 5 device, featuring thin film annealed at 200 °C, demonstrated excellent EC performance with high optical contrast of 42.32%, high coloration efficiency (CE) of 34.93 cm 2 /C, as well as rapid coloring and bleaching times of 0.4 s and 3 s, respectively. These results shed light on the importance of annealing temperature control towards the EC performance of V 2 O 5 devices for future applications., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

The widespread discharge of organic dyes into the wastewater from various industrial processes has develop a major environmental apprehension in the modern world. To tackle such environmental issues, we are synthesizing a novel catalyst of composition, Ba 1 - x Co x Dy y Fe 12-y O 19 (x = y = 0.02-0.06) using sol-gel auto-combustion (SGAC) for the photocatalytic eradication of malachite green dye (MGD). The fabricated sample show single-phase hexagonal structure. The hexagonal-shaped grains are seen in the field emission spectroscopy (FESEM) visuals of prepared hexaferrites. The oxidation states of every element present in the developed specimens are investigated using the X-ray photoelectron spectrophotometer scrutinized. The specific surface area (SSA) of the HF1 sample is 3.523 m 2 /g, whereas the band gap values of co-doped barium hexaferrites are found within the range of 1.61 to 1.75 eV. The magnetic analysis of developed hexaferrites indicates that increasing the concentration of Dy and Co, raised in the saturation magnetization and declines in coercivity. The conducted photocatalytic evaluations reveal that the removal efficiencies of 89.85%, 91.12%, and 94.36% are obtained for the prepared HF1, HF2, and HF3 hexaferrites after 90 min of natural irradiation. Moreover, the capability for the reusability of the synthesized hexaferrites is assessed over a series of five consecutive experimental cycles. As a result, this research delves at potential applications of co-doped BaFe 12 O 19 hexaferrites in the photocatalytic eradication of MGD for environmental applications., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs. Several statistical indices and graphical approaches are used as accuracy performance indicators. The results show that virtually all the gathered datapoints are suitable for the purpose of model development. The sensitivity analysis indicated that pressure, temperature and crude oil API all negatively affect the IFT, with pressure being the most effective factor. The evaluation study proved that Random Forest is the most accurate developed intelligent model as it was characterized with acceptable R-squared (0.959), mean square error (1.65), average absolute relative error (6.85%) of unseen test datapoints as well as with correct trend prediction of IFT with regard to all input parameters of pressure, temperature and crude oil API. The developed model can be considered an accurate an easy-to-use tool for the prediction of crude oil/N 2 IFT values for enhance oil recovery study optimization and upstream reservoir investigations., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

This theoretical work focuses on the application of Tamm resonance-based biosensing using a one-dimensional photonic crystal for detecting skin vitiligo, a condition caused by the loss of pigment in the body. This biosensor utilizes the interaction of light with the photonic structure to identify the specific biomarkers associated with vitiligo. The proposed structure is composed of prism/Ag/skin-sample/(GaP/PS) N /glass. The MATLAB simulations are used to obtain numerical results pertaining to the work by using the transfer matrix method (TMM). The analysis of transmission spectra of the proposed structure shows its minute sensing ability of detecting skin vitiligo. The proposed sensor possesses a higher sensitivity of 1200 nm/RIU which is higher than the sensitivities of the sensor reported earlier. Moreover, the suggested biosensor possesses an extremely high-quality factor value of 40,650 with an exceptionally small full-width-half-maximum value of 0.04 nm., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Many aquatic organisms utilize suction-based organs to adhere to diverse substrates in unpredictable environments. For multiple fish species, these adhesive discs include a softer disc margin consisting of surface structures called papillae, which stabilize and seal on variable substrates. The size, arrangement, and density of these papillae are quite diverse among different species, generating complex disc patterns produced by these structures. Considering papillae arrangements in three fish species, the Northern Clingfish (Gobiesox maeandricus), Tidepool Snailfish (Liparis florae), and Chilean Clingfish (Sicyases sanguineus), we fabricated physical disc models that tested relevant surface pattern parameters under shear loading conditions. Parameters of interest included the area of papillae-like structures, the spacing between adjacent structures (channel spacing), and the percent coverage of elements relative to the total disc area. To create our models, a soft silicone elastomer was added to a stiff circular suction cup, which was then "stamped" using a laser-etched and thermoformed mold base to create the desired surface patterning. Discs were tested using a robotic arm equipped with a force sensor, which sheared them across smooth and rough surfaces at a fixed speed and distance. The arm was also used to vary the initial compression to test performance under both suction-dominant and friction-dominant preloads. For our designs, patterns with smaller papillae-like structures and channel spacing often produced higher peak forces than those with larger features. However, the design that withstood the highest shear load featured an intermediate pad size and channel spacing, potentially highlighting a balance between overall surface area and fluid channeling. Additionally, discs with surface patterns often outperformed the control discs (no pattern) on both smooth and rough surfaces, but performance was highly dependent on preload, with patterned discs exhibiting benefits with the higher "friction-dominant" preloads., Competing Interests: Declarations. Competing Interests: Author Robert J. Wood holds stock in Fleet Robotics, Inc., a marine robotics company focused on robotic anti-biofouling., (© 2024. The Author(s).)

This study presents an in-depth analysis and evaluation of the performance of a standard 200 W solar cell, focusing on the energy and exergy aspects. A significant research gap exists in the comprehensive integration of numerical models with advanced machine-learning approaches, specifically emotional artificial neural networks (EANN), to simulate and optimize the electrical characteristics and efficiency of solar panels. To address this gap, a numerical model alongside a novel EANN was employed to simulate the system's electrical characteristics, including open-circuit voltage, short-circuit current, system resistances, maximum power point characteristics, and characteristic curves. Mathematical equations for calculating efficiency levels under varying operational conditions were developed. The system's operational and electrical parameters, alongside environmental conditions such as solar radiation, wind speed, and ambient temperature, were empirically observed and documented over a day. A comparative analysis was conducted to validate the model by comparing its results with manufacturer data and experimental observations. During the trial from 7:00 to 17:00, energy efficiency varied from 10.34 to 14.00%, averaging 13.6%, while exergy efficiency ranged from 13.57 to 16.41%, with an average of 15.70%. The results from the EANN model indicate that the proposed method for forecasting energy, exergy, and power is feasible, offering a significant reduction in computational expense compared to traditional numerical models. The integration of numerical modeling with EANN enhances simulation accuracy and the developed equations enable real-time efficiency calculations. Empirical validation under varying environmental conditions improves predictive capabilities for solar panel performance. Additionally, operational efficiency assessments aid in better design and deployment of solar energy systems, and computational costs for large-scale solar energy simulations are reduced., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

In this work a novel method for synthesis of 1,8-dihydroxynaphthalene melanin was presented, as well as the physicochemical properties, molecular structure, and characteristics of the pigment. The proposed synthesis protocol is simple and cost-effective with no enzymes or catalysts needed. The final product is not adsorbed on any surface, since the pigment is the result of autooxidation of 1,8-dihydroxynaphthalene. Performed analyses revealed that the solubility, optical and paramagnetic properties are typical for melanins, and in the EPR spectra an unusual hyperfine structure was observed. The molecular structure of the pigment consists of three different layers forming polar and non-polar surfaces. Additionally, the presence of ether bonds presence was revealed. The developed method creates new opportunities for melanin research and eliminates the need to extract melanins from biological samples, which often lead to structural changes in isolated melanins, which undermines the reliability of analyses of the properties and structure of these polymers. On the other hand, the ubiquity of melanins in living organisms and the diversity of their biological functions have let to the growing interest of researchers in this group of pigments. The analyses carried out show that the obtained synthetic DHN polymer can be considered as a model DHN-melanin in mycological studies and material research., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Integrating the Internet of Things (IoT) in smart grids has revolutionized the energy sector, enabling real-time data collection and efficient energy distribution. However, this integration also introduces significant security challenges, particularly data encryption. Traditional encryption algorithms used in IoT are vulnerable to various attacks, and the advent of quantum computing exacerbates these vulnerabilities. To address the above challenges, this paper proposes a novel encryption mechanism, the Quantum-Resistant Hybrid Encryption for IoT (QRHE-IoT), designed to enhance the security of communications in IoT-enabled smart grids. QRHE-IoT combines the strengths of symmetric and asymmetric encryption algorithms and incorporates quantum-resistant algorithms to provide robust security. This paper explains the QRHE-IoT mechanism, its theoretical basis, and how it addresses the security challenges in smart grid communications. It also presents the results of tests conducted to evaluate the effectiveness of QRHE-IoT in a simulated smart grid environment. The proposed QRHE-IoT mechanism presents a promising solution to these challenges, offering robust security for smart grid communications in the face of emerging threats, including quantum computing., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Smart wearable devices detection and recording of people's everyday activities is critical for health monitoring, helping persons with disabilities, and providing care for the elderly. Most of the research that is being conducted uses a machine learning-based methodology; however, these approaches frequently have issues with high computing resource consumption, burdensome training data gathering, and restricted scalability across many contexts. This research suggests a behaviour detection technology based on multi-source sensing and logical reasoning to address these problems. In order to realize the natural fusion of signal processing and logical reasoning in behavior recognition research, this work designs a lightweight behavior recognition solution using the pertinent theories of ontology reasoning in classical artificial intelligence. Machine learning technology is also employed for behavior recognition using the same data set. Once the best model has been chosen, the cross-person recognition results after testing and modification of parameters are 90.8% and 92.1%, respectively. This technology was used to create a behaviour recognition system, and several tests were run to assess how well it worked. The findings demonstrate that the suggested strategy achieves over 90% recognition accuracy for 11 different daily activities, including jogging, walking, and stair climbing. Additionally, the suggested strategy dramatically minimises the quantity of user-provided training data needed in comparison to machine learning-based behaviour identification techniques., Competing Interests: Declarations. Competing interests: This research does not involve any human or animal participation. Ethical consent: Informed Consent was obtained from all the participants involved in the study. Bioethics and guidelines: The protocol was approved by Model Institute of Engineering and Technology Review Board in accordance with the relevant guidelines of the Model Institute of Engineering and Technology, Jammu, J&K, India., (© 2024. The Author(s).)

The swift rise of hazardous dye effluent from diverse sectors continues to be a severe public health problem and a top priority for environmental preservation, presenting a significant obstacle to the current conventional water treatment systems. This study aims to develop an efficient and reusable approach for removing cresyl fast violet dye using mullite nanoparticles. Some factors such as pH, nano-mullite dosage, agitation speed, time, and others that affect the removal process were studied. The mullite nanoparticles' shape, particle size, pore diameters, and crystal phase structure are characterized using many techniques such as Brunauer-Emmett-Teller (BET) surface area, X-ray diffraction (XRD), transmission electron microscopy (TEM), Contact angle, Zeta potential, scanning electron microscope (SEM) as well as energy dispersive X-ray analysis (EDX). The optimal conditions were pH 7 and 600 rpm for 30 min at room temperature. Using statistical programs such as ANOVA and Design Expert, the dye removal parameters were modeled and optimized, where the removal percentage was about 99%. In addition, the experimental elimination process exceeded 90% after just 10 min. Langmuir, Freundlich, Dubinin-Kaganer-Raduskevich (DKR), and Temkin isotherm equations were examined to find the adsorption isotherm. The experimental data fits the pseudo-second-order model and the Freundlich isotherm. Thermodynamic investigations confirmed that the adsorption process was endothermic and spontaneous. The nano-mullite was employed for the removal process, and its recycling ability supports its economic benefits. It was found that the high percentage of elimination remained consistent for more than 3 cycles., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration. Model based active learning (AL) data sampling strategies have shown potential for further optimization. This paper introduces a workflow for conducting DOE comparative studies using automated machine learning. Based on a practical definition of model complexity in the context of machine learning, the interplay of systematic data generation and model performance is examined considering various sources of uncertainty: this includes uncertainties caused by stochastic sampling strategies, imprecise data, suboptimal modeling, and model evaluation. Results obtained from electrical circuit models with varying complexity show that not all AL sampling strategies outperform conventional DOE strategies, depending on the available data volume, the complexity of the dataset, and data uncertainties. Trade-offs in resource allocation strategies, in particular between identical replication of data points for statistical noise reduction and broad sampling for maximum parameter space exploration, and their impact on subsequent machine learning analysis are systematically investigated. Results indicate that replication oriented strategies should not be dismissed but may prove advantageous for cases with non-negligible noise impact and intermediate resource availability. The provided workflow can be used to simulate practical experimental conditions for DOE testing and DOE selection., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Cultivating insect cells in glass vessels can be challenging. Due to uncontrolled cell adhesion and associated cell loss as well as clumping, the replication of experiments is put at risk. A cost-effective solution to improve and stabilize cultivation may be to silanize glass vessels, making them more hydrophobic and chemically inert. Therefore, the cell growth parameters of Spodoptera frugiperda (Sf) 9 cells were characterized in an experiment comparing silanized and non-silanized vessels of three different sizes. Silanization had a significantly positive effect on living cell count and viability in small-scale cultivation (10 ml culture tubes and 50 ml culture flasks) by reducing adhesion of cells to the vessel walls. The treatment also improved the comparability of the biological replicates by reducing the variance of measurements. No such effects could be observed for larger 250 ml culture flasks. Overall, the results indicate that silanization can improve cultivation, especially when working with small glass vessels., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

In response to climate change mitigation efforts, improving the efficiency of heat networks is becoming increasingly important. An efficient operation of energy systems depends on faultless performance. Following the need for effective fault detection and elimination methods, this study suggests a three-step workflow for increasing automation in managing defective substations on the user level within heat networks. The work focuses on a model region in northern Germany. The local heat network provides data in roughly hourly intervals, including the supply and return temperatures and the volume flow of the substations. Firstly, this study identifies common indicators of faults using k-means clustering analysis of the temperature data and expert knowledge: an exceeded return temperature level, very low cooling, and inverted temperature readings. With these indicators, the subsequent statistical identification approach confirms the successful detection of affected substations, with common diagnoses including disabled return temperature limitation units, defective motoric valves, and faults in the storage control. Lastly, the study evaluates the impact of faults on the system efficiency. Combining the temperature and the volume flow data, the workflow quantifies the negative influence of a fault, enabling the prioritization of fault elimination measures in practical application to enhance the overall system efficiency., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is the cervical smear (Pap smear) testing; however, due to human negligence, this examination method has an elevated probability of negative findings. Cervical cancer classification using machine learning (ML) and deep learning (DL) has been extensively studied to enhance the conventional diagnostic process. Robust classification results were achieved through the pre-segmented imagery in most current investigations. Conversely, cellular grouping makes reliable cervical cellular segmentation difficult. Additionally, the deep learning methods used in the existing works perform poorly on a multiclass classification when the data distribution is skewed, which is common in the cervical cancer dataset. To mitigate these restrictions in cervical cancer research, this proposed work uses a combination of four different deep-learning methods in various phases of this research. The proposed work is segregated into five phases: pre-processing, data augmentation, segmentation, feature extraction, and classification. Contrast maximization is performed in the pre-processing phase, and the images are augmented using Multi-modal Generative Adversarial Networks (m-GAN) in the second phase. In the third phase, cervical cancer images are segmented using the Seg-UNet model, which is forwarded to the feature extraction phase that employs denoising autoencoders. Finally, the classification is implemented using the Dense CapsNet model and applied to the SIPaKMeD dataset to categorize between normal, abnormal, and benign classes. The proposed system achieves an accuracy of 99.65%, which is higher than the other works in the literature., Competing Interests: Competing interests: The authors declare that they have no competing interests., (© 2024. The Author(s).)

Acute pancreatitis (AP) is a severe inflammatory condition affecting the pancreas, often leading to systemic inflammation and organ dysfunction. This study evaluated the effects of resveratrol (RES) and β-carotene (βC) on L-arginine-induced AP in rats. Forty-eight male Sprague Dawley rats were divided into six groups: Control (C), RES (20 mg/kg), βC (50 mg/kg), AP, AP + RES, and AP + βC. The AP model was induced with 250 mg/100 g L-arginine intraperitoneally twice daily with a 1-h interval. The AP group showed significantly elevated oxidative stress (MDA) and reduced GSH levels (p < 0.001). Immunohistochemical (IHC) staining with anti-insulin antibody revealed reduced β + langerhans islet size in the AP group. qPCR analysis indicated significant upregulation of inflammatory genes NF-κB, TNF-α, and IL-1β (p < 0.001), and apoptotic genes Bax and Caspase-3, with downregulation of Bcl-2 (p < 0.001). RES and βC treatments significantly reduced MDA levels and increased GSH levels (p < 0.01 for both) compared to the AP group. The AP + RES and AP + βC groups exhibited preserved β + Langerhans islet size (p < 0.01), suppressed NF-κB, TNF-α, and IL-1β expression, reduced Bax and Caspase-3 levels, and increased Bcl-2 levels (p < 0.01). Histopathological findings supported these results. RES and βC confer significant effects against L-arginine-induced acute pancreatitis by reducing oxidative stress, preserving pancreatic islet integrity, suppressing inflammatory responses, and modulating apoptotic pathways. RES demonstrated a slightly superior efficacy in reducing inflammation and oxidative stress markers, suggesting it may be more effective in treating acute pancreatitis., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Rational utilization of natural resources is crucial in arid and semi-arid areas due to their vulnerable ecosystems and low resource resilience. Achieving a balance between grassland production and livestock grazing, known as the pasture-livestock balance, is essential for the sustainable development of grassland resources on the Mongolian Plateau (MP). This study focuses on the grassland regions of 8 provinces in eastern Mongolia (MNG) and 7 leagues in Inner Mongolia (IMNG), China, during the period from 2018 to 2022. Machine learning methods were employed for land cover classification and above-ground biomass (AGB) estimation. The grassland carrying capacity was assessed using the grassland carrying capacity index (GCC). The results indicate that: (1) The grassland classification accuracy on the MP exceeds 95%, with grassland area accounting for approximately 47% of the total.(2)The AGB of the grasslands exhibits a clear spatial heterogeneity, increasing from southwest to northeast. Additionally, nearly 80% of the grassland productivity is of high quality, reaching up to 250 g/m 2 .(3) Between 2018 and 2022, the MP exhibited a relatively high grassland carrying capacity, with an average of 1.8 SU/ha. However, the overall grassland carrying condition has gradually deteriorated, primarily due to factors such as grassland fires and an increase in livestock numbers. Based on the varying degrees of grassland degradation, different policy recommendations have been proposed. This study approach, findings and policy suggestions are significant for the development of livestock farming and grassland management on the MP., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The application of pesticides may adversely impact a variety of non-target organisms. The use of side-effect-free herbal remedies to protect against the toxicity of harmful pesticides such as etoxazole has gained attention in recent times. The current study aimed to reveal the potential mitigating efficacy of Achillea millefolium L. extract against etoxazole toxicity in Allium cepa L. A. cepa bulbs in the control group were applied with tap water, while bulbs in the treatment groups were applied with etoxazole at dose of 0.5 m/L and two different doses of A. millefolium extract (200 mg/L and 400 mg/L). The impact of the treatments on certain parameters was evaluated. The molecular docking analysis was employed to investigate the potential interactions of etoxazole with DNA species, DNA topoisomerases, tubulin proteins, glutamate-1-semialdehyde aminotransferase, and protochlorophyllide reductase. The phenolic profile of A. millefolium was assessed. Etoxazole exposure reduced rooting percentage, root length, weight gain, mitotic index, and levels of chlorophyll a and chlorophyll b. Conversely, etoxazole treatment led to an increase in chromosomal aberrations and micronuclei occurrence. The most frequently observed chromosomal aberrations induced by etoxazole, which serve as bioindicators of genotoxicity, were fragment, vagrant chromosome, sticky chromosome, unequal chromatin distribution, bridge, reverse polarization, and vacuolated nucleus. The levels of malondialdehyde and antioxidant enzyme (superoxide dismutase and catalase) activities were also elevated. Epidermis cell damage, flattened cell nucleus, thickened cortex cell wall, and thickened conduction tissue were the meristematic cell disorders triggered by etoxazole. Molecular docking studies showed that etoxazole can interact directly with DNA, tubulins, and the enzymes mentioned above. A. millefolium extract was found to contain a substantial quantity of phenolic compounds. A. millefolium extract, when co-administered with etoxazole, attenuated all toxic effects of etoxazole dose-dependently. In conclusion, A. millefolium may potentially serve as a reliable pharmacological shield against the toxicity of pesticides in non-target organisms., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Correspondence and requests for materials should be addressed to T.K.M., (© 2024. The Author(s).)

Manual segmentation of lesions, required for radiotherapy planning and follow-up, is time-consuming and error-prone. Automatic detection and segmentation can assist radiologists in these tasks. This work explores the automated detection and segmentation of brain metastases (BMs) in longitudinal MRIs. It focuses on several important aspects: identifying and segmenting new lesions for screening and treatment planning, re-segmenting lesions in successive images using prior lesion locations as an additional input channel, and performing multi-component segmentation to distinguish between enhancing tissue, edema, and necrosis. The key component of the proposed approach is to propagate the lesion mask from the previous time point to improve the detection performance, which we refer to as "re-segmentation". The retrospective data includes 518 metastases in 184 contrast-enhanced T1-weighted MRIs originating from 49 patients (63% male, 37% female). 131 time-points (36 patients, 418 BMs) are used for cross-validation, the remaining 53 time-points (13 patients, 100 BMs) are used for testing. The lesions were manually delineated with label 1: enhancing lesion, label 2: edema, and label 3: necrosis. One-tailed t-tests are used to compare model performance including multiple segmentation and detection metrics. Significance is considered as p < 0.05. A Dice Similarity Coefficient (DSC) of 0.79 and F 1 -score of 0.80 are obtained for the segmentation of new lesions. On follow-up scans, the re-segmentation model significantly outperforms the segmentation model (DSC and F 1 0.78 and 0.88 vs 0.56 and 0.60). The re-segmentation model also significantly outperforms the simple segmentation model on the enhancing lesion (DSC 0.76 vs 0.53) and edema (0.52 vs 0.47) components, while similar scores are obtained on the necrosis component (0.62 vs 0.63). Additionally, we analyze the correlation between lesion size and segmentation performance, as demonstrated in various studies that highlight the challenges in segmenting small lesions. Our findings indicate that this correlation disappears when utilizing the re-segmentation approach and evaluating with the unbiased normalized DSC. In conclusion, the automated segmentation of new lesions and subsequent re-segmentation in follow-up images was achievable, with high level of performance obtained for single- and multiple-component segmentation tasks., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

This paper introduces an innovative, adaptive Fractional Open-Circuit Voltage (FOCV) algorithm combined with a robust Improved Model Reference Adaptive Controller (IMRAC) for Maximum Power Point Tracking (MPPT) in standalone photovoltaic (PV) systems. The proposed two-stage control strategy enhances energy efficiency, simplifies system operation, and addresses limitations in conventional MPPT methods, such as slow convergence, high oscillations, and susceptibility to environmental fluctuations. The first stage dynamically estimates the Maximum Power Point (MPP) voltage using a novel adaptive FOCV method, which eliminates the need for irradiance sensors or physical disconnection of PV modules. This stage incorporates a real-time adjustment of the kv factor based on variations in PV power, ensuring precise voltage estimation. In the second stage, the IMRAC controller ensures accurate tracking of the MPP by adapting swiftly to changes in irradiance and temperature, while minimizing ripple and power loss. Validation of the proposed system was carried out using Processor-in-the-Loop (PIL) testing on an Arduino Due microcontroller, showcasing real-world applicability. Comparative analysis with state-of-the-art MPPT controllers, including P&O-PI, InC-SMC, FLC, and VS P&O Backstepping, demonstrates superior tracking efficiency exceeding 99.49% under EN 50,530 standard test conditions. The system also maintains exceptional performance with minimal efficiency loss across a wide range of temperature and irradiance variations. By combining simplicity, robustness, and sustainability, this work establishes a cutting-edge solution for standalone PV systems, paving the way for more efficient and reliable renewable energy applications., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Persuasive appeals frequently prove ineffective or produce unintended outcomes, due to the presence of motivated reasoning. Using the example of electric cars adoption, this research delves into the impact of emotional content, message valence, and the coherence of pre-existing attitudes on biased information evaluation. By conducting a factorial survey (N = 480) and incorporating a computational model of attitude formation, we aim to gain a deeper insight into the cognitive-affective mechanisms driving motivated reasoning. Our experimental findings reveal that motivated reasoning is most pronounced when persuasive appeals employ a combination of emotional and rational elements within a negatively valenced argument. Furthermore, our computational model, which estimates belief and affect adjustments underlying attitude changes, elucidates how message framing influences cognitive-affective processes through emotional coherence. The results provide support for a negative correlation between shifts in coherence in response to new information and the propensity for motivated reasoning. The research contributes to computational models of opinion dynamics and social influence, offering a psychologically realistic framework for exploring the impact of individual reasoning on population-level dynamics, particularly in policy contexts, where it can enhance communication and informed policy discussions., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Finger millet blast caused by Pyricularia grisea hinders crop's growth and is a serious threat to economic yield. It can lead to massive yield losses i.e. up to 80%, which is a cause of major concern. In this study, we evaluated 200 accessions of finger millet at Banda University of Agriculture & Technology in Banda, India, under natural conditions to determine their resistance against leaf, neck, & finger blast diseases. Nine accessions displayed strong resistance against all forms of blast. The genetic variability analysis revealed high phenotypic & genotypic coefficients of variation. This was especially true for seed yield, plant height, & days to flowering. Most traits had heritability estimates exceeding 80%. Such results indicate a significant potential for effective selection in breeding programs. Leaf blast ratings had a significant but weaker correlation to both neck blast (r = 0.31) and finger blast (r = 0.31) whereas neck and finger blast ratings were very highly correlated and significant (r = 0.97). All types of blast had negative correlation with various agronomic traits studied. Furthermore, DNA fingerprinting of resistant genotypes with SSR markers displayed 10 polymorphic markers with an average of 2.6 alleles per locus. This points to the genetic diversity present within the germplasm. In summary, these findings provide vital insights for breeding initiatives focused on enhancing blast resistance in finger millet. Such efforts are crucial for maintaining the sustainability of this important crop for global food security., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Competing interests: Authors declare that there is no conflict of interest exists., (© 2024. The Author(s).)

Alzheimer's disease (AD) is a brain disorder that causes memory loss and behavioral and thinking problems. The symptoms of Alzheimer's are similar throughout its development stages, which makes it difficult to diagnose manually. Therefore, artificial intelligence (AI) techniques address the limitations of manual diagnosis. In this study, the images were enhanced and the active contour algorithm (ACA) was used to extract regions of interest (ROI) such as soft tissue and white matter. Strategies have been developed to diagnose AD and differentiate its stages. The first strategy is using XGBoost and ANN networks with the features of MobileNet, DenseNet, and GoogLeNet models. The second strategy is by XGBoost and ANN networks with combined features of MobileNet-DenseNet121, DenseNet121-GoogLeNet and MobileNet-GoogLeNet. The third strategy combines XGBoost and ANN networks with combined features of MobileNet-DenseNet121-Handcrafted, DenseNet121-GoogLeNet-Handcrafted, and MobileNet-GoogLeNet-Handcrafted leading to improved accuracy of the strategies and improved efficiency. XGBoost with hybrid features of DenseNet-GoogLeNet-Handcrafted achieved an AUC of 98.82%, accuracy of 98.8%, sensitivity of 98.9%, accuracy of 97.08%, and specificity of 99.5%., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The Restriction Spectrum Imaging restriction score (RSIrs) has been shown to improve the accuracy for diagnosis of clinically significant prostate cancer (csPCa) compared to standard DWI. Both diffusion and T 2 properties of prostate tissue contribute to the signal measured in DWI, and studies have demonstrated that each may be valuable for distinguishing csPCa from benign tissue. The purpose of this retrospective study was to (1) determine whether prostate T 2 varies across RSI compartments and in the presence of csPCa, and (2) evaluate whether csPCa detection with RSIrs is improved by acquiring multiple scans at different TEs to measure compartmental T 2 (cT 2 ). Data includes two cohorts scanned for csPCa with 3T multi-b-value diffusion-weighted sequences acquired at multiple TEs. cT 2 values were computed from multi-TE RSI data and compared by compartment. CsPCa detection was compared between RSIrs and a logistic regression model (LRM) to predict the probability of csPCa using cT 2 in combination with RSI measurements. Two-sample t-tests (α = 0.05) and the area under the receiver operating characteristic curve (AUC) were used for the statistical analyses. In both cohorts, T 2 was different (p < 0.05) across the four RSI compartments (C 1, C 2, C 3, C 4 ). Voxel-level, cohort 1: T 2 was different in csPCa for C 1, C 2, C 3 (p < 0.001). Patient-level, cohort 1: T 2 was different in csPCa patients in C 3 (p = 0.02); cohort 2: T 2 differed in csPCa patients in C 1 (p = 0.01), C 3 (p = 0.01) and C 4 (p < 0.01). Voxel-level csPCa detection: cT 2 did not improve discrimination over RSIrs alone (p = 0.9). Patient-level: RSIrs and the LRM performed better than diffusion alone (p < 0.001), but the difference in AUCs between RSIrs and the LRM was not significantly different (p = 0.54). In conclusion, significant differences in cT 2 were observed between normal and cancerous prostatic tissue. With our data, however, consideration of cT 2 in addition to diffusion did not significantly improve cancer detection performance., Competing Interests: Declarations. Competing interests: M.E.H. reports honoraria from Multimodal Imaging Services Corporation and research funding from GE Healthcare. R.R.P. has an equity interest in CorTechs Labs and Curemetrix, serves on the scientific advisory board of Imagine Scientific, and has received consulting fees from Bayer and research funding from GE Healthcare. A.M.D. is a founder of and holds equity in CorTechs Labs, Inc, and serves on its scientific advisory board; he also is a member of the scientific advisory board of Human Longevity, Inc, and receives funding through research agreements with GE Healthcare. T.M.S. reports honoraria from CorTechs Labs, Varian Medical Systems, WebMD, GE Healthcare, and Janssen; has an equity interest in CorTechs Labs, Inc, and serves on its scientific advisory board; and has received in-kind research support from GE Healthcare via a research agreement with the University of California, San Diego. These companies might potentially benefit from the research results. The terms of these arrangements have been reviewed and approved by the University of California, San Diego in accordance with its conflict-of-interest policies. All the remaining authors declare no conflict of interest., (© 2024. The Author(s).)

The industrial sector faces a significant challenge in finding the highly effective and efficient treatments for harmful dye-based color effluents. In this study, pure and cobalt doped barium hexaferrite of chemical formula, Ba 1-x Co x Fe 12 O 19 (x = 0-0.06) are made via sol-gel auto-combustion (SC) methodology. These nano hexaferrite based catalysts are employed for the photodegradation of Congo Red (CR) pollutant. X-rays diffraction investigation confirms the creation of pristine M-type with a hexagonal structure for the prepared hexaferrites. Field emission scanning electron microscopy analysis shows the existence of the hexagonal-shaped grains with well-defined grain boundaries. The reduction in the band gap of prepared hexaferrites are observed with the cobalt doping which is helpful in enhancing the photocatalytic performance. The X-ray photoelectron spectroscopy examination verifies the oxidation states of all elements found in the fabricated specimens. From the photocatalytic measurements, it is observed that the CR dye attains the removal percentage of 87.90%, 90.73%, 91.86% and 94.88% for the BaFe 12 O 19 (x = 0.00), Ba 0.08 Co 0.02 Fe 12 O 19 (x = 0.02), Ba 0.06 Co 0.04 Fe 12 O 19 (x = 0.04), and Ba 0.04 Co 0.06 Fe 12 O 19 (x = 0.06) hexaferrites under the natural sunlight of two hours. In addition, the reusability potential of prepared hexaferrites is also studied over the six consecutive experimental cycles. The excellent photodegradation performance of the Co- doped barium M-type hexaferrites for the removal of CR dye makes them highly useful for the wastewater remediation., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Physical activity (PA) and fruit and vegetable consumption (FVC) are crucial factors jointly affecting young adults' physical and mental health. However, the psychosocial interactive mechanisms of these behaviors remain understudied. Using a two-wave prospective design over two months, this study investigated the psychological mechanisms underlying multiple health behavior change (MHBC) through a novel two-layer social-cognitive framework, the Compensatory Carry-Over Action Model (CCAM), among 322 Chinese college students (19.47 ± 0.99 years; 55.6% female). Structural equation modeling with path analysis was conducted using Mplus 8.8 for data analysis. Results indicated an acceptable model fit for the hypothesized model, with χ 2  = 120.845, df = 41, χ 2 /df = 2.947, CFI = 0.940, TLI = 0.901, RMSEA = 0.078 [90% CI = 0.062 to 0.094], and SRMR = 0.079. The model explained 54.9% and 50.0% of the variance in PA and FVC, respectively. In the first layer, focusing on the individual behavior change process, both volitional self-efficacy and planning were identified as significant mediators in the intention-behavior relationship for PA and FVC (indirect effects = 0.03 to 0.14, all p < .01). In the second layer, targeting the interaction between the two behaviors, the mediating role of compensatory cognition (e.g., PA/FVC can compensate for FVC/PA) in the relationship between intention and behavior was not supported (all p > .05). However, volitional self-efficacy and planning played a significant mediating role in the interaction between PA/FVC intention and FVC/PA behavior (indirect effects = 0.01 to 0.04, all p < .05). Future interventions aiming at promoting MHBC should address compensatory cognition and the carry-over effects between diverse behaviors., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval: The current study was approved by the Research Ethics Committee of Hong Kong Baptist University (FRG2/15–16/032). All participants have provided written informed consent to participate., (© 2024. The Author(s).)

The SARS-CoV-2 virus that resulted in the COVID-19 pandemic has been implicated in a range of neurological issues, such as encephalopathy, stroke, and cognitive decline. Although the precise mechanism causing these issues is unknown, mounting evidence shows that blood-brain barrier (BBB) disruption is probable2 a major factor. The integrity of the blood-brain barrier (BBB), a highly selective barrier that divides the brain from the systemic circulation, is crucial for preserving normal brain function. By analysing the multi-transcriptome data, this work explores the neurological impacts of the SARS-CoV-2 virus and provides insight into the molecular mechanisms behind BBB breakdown and neurological symptoms in COVID-19 patients. The endothelial cells of BBB expresses inflammatory genes in response to the systemic inflammation induced due to SARS-CoV-2 remnants in the body. This raises the possibility that systemic inflammation brought on by SARS-CoV-2 and BBB integrity are correlated. Furthermore, the study highlights the pathways involved in oxidative stress and endothelial cell activation, revealing their role in COVID-19 passage through BBB and induction of systemic inflammation and advancement toward neurological disorders. The article showcases the evidence that mitochondrial dysfunction is a major aftermath associated with SARS-CoV-2 infection as the impaired Mitochondria leads to an accumulation of reactive oxygen species (ROS), triggering endothelial dysfunction, and leading to the passage of harmful molecules across the BBB. This study offers insightful information that may open up the possibilities for new treatment plans by targeting biomarkers specifically associated with inflammation and BBB dysfunctioning conditions., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Gastrointestinal carriage of antimicrobial-resistant bacteria, especially carbapenemase-producing Enterobacterales (CPE), presents a critical public health threat globally. However, in many resource-constrained countries, epidemiological data on CPE is limited. Here, we assessed gastrointestinal carriage and associated factors of CPE among inpatient and outpatient children (≤ 5 years). This hospital-based cross-sectional study was conducted at Thika Level 5 Hospital in Kenya from February to June 2023. In total, 540 participants were recruited from outpatient (270) and inpatient (270) children, excluding those admitted for < 48 h and outpatients with ≤ 3 months hospitalization history. Demographic data were collected using a questionnaire, and stool or swab samples were cultured following standard microbiology methods. Automated platforms were used for isolates identification and antimicrobial susceptibility testing. Gastrointestinal carriage rate of CPE was 9.6%, 95% confidence interval (CI): 6.39-13.79% (26/270) among the inpatients and 5.9%, 95% CI: 3.42-9.45% (16/270) among the outpatients. The carbapenemase-producing Enterobacterales were predominated by multidrug-resistant Escherichia coli from inpatients (22/22, 100%) and outpatients (8/10, 80%). The colonization rate was higher among inpatients who were presenting with chills (aOR = 10.57, p = 0.008). We report a high gastrointestinal carriage of CPE among children (≤ 5 years). Strict adherence to colonization screening, and antimicrobial stewardship policies are critical to control CPE dissemination in the current study area and beyond., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: The study was approved by Kenyatta University’s ethical research committee, reference number (PKU/2620/E1745) as well as the National Commission of Science, Technology, and Innovation (NACOSTI), reference number (P/22/22147). Approval for collection of samples was obtained from Ethical Research Committee, Thika Level 5 hospital (Ref. MOH/TKA/GEN/VOL. VI/017). Additionally, the parent or guardian of each child who participated in the study gave their informed consent. Results and patient identification were both kept confidential. The findings of this study will guide in infection prevention and control interventions which will minimise infections of the patients. The findings will also guide in the correct selection of the antibiotics for treating the patients., (© 2024. The Author(s).)

Modifying ZnO nanorods with graphene oxide (GO) is crucial for enhancing photocatalytic degradation by boosting the concentration of reactive oxygen species (ROS) in the reaction medium. In this study, we present a straightforward chemical synthesis of ZnO nanorods embedded on GO, forming a novel nanocomposite, GOZ. This composite serves as an efficient photocatalyst for the sunlight-driven degradation of methylene blue (MB) and ciprofloxacin (CIP). Rietveld refined X-ray diffraction (RXRD), Fourier-transform infrared (FTIR), and transmission electron microscopy (TEM) confirmed the formation of ZnO nanorods and GOZ nanocomposite. The possible defect states and oxygen vacancies were confirmed using the emission spectra that played a significant role in the photocatalytic activity. The values of the optical bandgap for GOZ-7 (7% GO) and GOZ-10 (10% GO) were found to be 2.8 eV and 2.7 eV using Tauc plot, respectively, showing a red shift as a result of increasing the concentration of GO. The photocatalytic efficiency of GOZ-7, GOZ-10 were evaluated under direct sunlight for degradation of MB dye and CIP antibiotic in an aqueous solution. The highest photocatalytic activity was observed by GOZ-10. The scavenging study confirmed that the photocatalysis occurred due to the generation of reactive oxygen species (ROS), especially by hydroxyl radical (OH . ). The cost-effective GOZ-10 nanocomposite emerges as a promising candidate for the rapid photocatalytic degradation of both cationic dyes and antibiotics, demonstrating its potential in environmental remediation applications., Competing Interests: Competing interests: I declare on behalf of all co-authors, there is no conflict of interest in this study. Ethical Approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable., (© 2024. The Author(s).)

The rapid development in agriculture and industrial sectors has raised some serious global issues like heavy metals pollution of water resources. Cadmium (Cd) is amongst the major water pollutants worldwide. In this study, two novel sorbents were prepared by using post-consumer textile waste (PCTW). The waste denim fabric was recycled with environmentally friendly H 2 O 2 and Ozone through oxidation under alkaline conditions to produce several functional groups at the surface (named as ODF@H 2 0 2 and ODF@0 3 respectively) that could trap the heavy metal cations from contaminated water. The functionalized fabric sorbents were characterized by Fourier transform infrared spectroscopy (FT-IR), X-Ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X-Ray (EDX) that revealed the presence of carboxylic acid, hydroxyl, and amine functional groups on their surfaces. The sorption isotherm, sorption kinetics and sorption thermodynamics were carried out to unravel the sorption process mechanism. The ODF@H 2 0 2 sorbent was proved more effective by giving maximum adsorption capacity of (238.09 mg g -1 ) compared to Ozone treatment (175.44 mg g -1 ) for Cd 2+ and achieved within just 20 min for both sorbents. Pseudo 2nd order and Langmuir models confirmed the chemosorption as dominant mechanism for the monolayer sorption of Cd 2+ ions onto ODF@H202 and ODF@0 3 . The sorption thermodynamic revealed the sorption process as endothermic and spontaneous in nature. The results showed that both ODF@H 2 0 2 and ODF@0 3 sorbents have an efficient potential for sorbing Cd from contaminated water. Furthermore, both ODF@H 2 0 2 and ODF@0 3 sorbents were also tested in a regeneration study to investigate the reuse of these sorbents, and we achieved marvelous results. Both sorbents gave up to 90% of the sorption capacity even after 10 recycles. Conclusively, both sorbents can have their implications for the preparation of filters that can be used for the treatment of wastewater. This study has practical significance by tackling the two environmental problems i.e. heavy metal pollution and denim waste., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

New therapeutic approaches for alcohol dependence (AD) include virtual reality (VR)-based treatments offering scalable options for cue exposure (CE), a well-established strategy in cognitive behavioral therapy. This study aimed to evaluate the feasibility and tolerability of a new VR-CE paradigm. On an explorative basis, factors influencing the induction of craving were examined. This single-arm monocentric clinical study included n = 21 patients with AD in inpatient rehabilitation treatment, that completed one VR-CE session including confrontation with alcohol-associated stimuli. Measurements of subjective craving before, during and after exposure, affective states, VR side effects as cybersickness and the sense of presence in VR were conducted. Craving levels during and directly after VR-CE were significantly higher than before the intervention. Craving levels 20 min after VR-CE did not significantly differ compared to those before VR-CE. Patients described a pronounced sense of presence and only mild symptoms of cybersickness. Craving was significantly correlated with cybersickness. While positive affect decreased throughout the VR exposure, negative affect did not differ significantly in pre-post-comparisons. This study shows that craving induction through our VR-CE paradigm is feasible and well-tolerated by patients with AD in long-term rehabilitation. These results contribute to the development and future research of therapeutic VR-CE approaches., Competing Interests: Declarations. Competing interests: NT, SG, AB, SLM and AL cooperate with neomento GmbH without financial interests for the development of a VR software for VirtuCueR, a VR treatment for patients with alcohol use disorder, currently developed and supported by the Berlin Institute of Health (Digital Health Accelerator Program) and Charité - Universitätsmedizin Berlin. TW is a shareholder of neomento GmbH. MS, RS, FB, AH have no competing interest to declare. Ethics approval and consent to participate: Ethical approval was provided by the local Ethics Committee of Charité - Universitätsmedizin Berlin (EA1/190/22, 23.05.2023). All participants gave written informed consent prior to enrolment. All methods were carried out in accordance with the Declaration of Helsinki and its amendments., (© 2024. The Author(s).)

Magnetic field effects (MFEs) in thermally activated delayed fluorescence (TADF) materials have been shown to influence the reverse intersystem crossing (RISC) and to impact on electroluminescence (EL) and conductivity. Here, we present a novel model combining Cole-Cole and Lorentzian functions to describe low and high magnetic field effects originating from hyperfine coupling, the Δg mechanism, and triplet processes. We applied this approach to organic light-emitting devices of third generation based on tris(4-carbazoyl-9-ylphenyl)amine (TCTA) and 2,2',2″-(1,3,5-benzinetriyl)-tris(1-phenyl-1-H-benzimidazole) (TPBi), exhibiting blue emission, to unravel their loss mechanisms. The quality of the regression function was evaluated using k-fold cross-validation. The scoring was compared to various alternative fitting functions, which were previously proposed in literature. Density functional theory calculations, photoluminescence, and electroluminescence studies validated the formation of a TADF exciplex system. Furthermore, we propose successful encapsulation using a semi-permeable polymer, showing promising results for magnetic field sensing applications on arbitrary geometry. This study provides insights into the origin of magnetic field effects in exciplex-TADF materials, with potential applications in optoelectronic devices and sensing technologies., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

While the potential of Artificial Intelligence (AI)-particularly Natural Language Processing (NLP) models-for detecting symptoms of depression from text has been vastly researched, only a few studies examine such potential for the detection of social anxiety symptoms. We investigated the ability of the large language model (LLM) GPT-4 to correctly infer social anxiety symptom strength from transcripts obtained from semi-structured interviews. N = 51 adult participants were recruited from a convenience sample of the German population. Participants filled in a self-report questionnaire on social anxiety symptoms (SPIN) prior to being interviewed on a secure online teleconference platform. Transcripts from these interviews were then evaluated by GPT-4. GPT-4 predictions were highly correlated (r = 0.79) with scores obtained on the social anxiety self-report measure. Following the cut-off conventions for this population, an F 1 accuracy score of 0.84 could be obtained. Future research should examine whether these findings hold true in larger and more diverse datasets., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Selecting pretrained models for image classification often involves computationally intensive finetuning. This study addresses a research gap in the standardized evaluation of transferability scores, which could simplify model selection by ranking pretrained models without exhaustive finetuning. The motivation is to reduce the computational burden of model selection through a consistent approach that guides practitioners in balancing accuracy and efficiency across tasks. This study evaluates 14 transferability scores on 11 benchmark datasets. It includes both Convolutional Neural Network (CNN) and Vision Transformer (ViT) models and ensures consistency in experimental conditions to counter the variability in previous research. Key findings reveal significant variability in score effectiveness based on dataset characteristics (e.g., fine-grained versus coarse-grained classes) and model architectures. ViT models generally show superior transferability, especially for fine-grained datasets. While no single score is best in all cases, some scores excel in specific contexts. In addition to predictive accuracy, the study also evaluates computational efficiency and identifies scores that are suitable for resource-constrained scenarios. This research provides insights for selecting appropriate transferability scores to optimize model selection strategies to facilitate efficient deployment in practice., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Our study aimed to report on variables associated with communicative health literacy (COM-HL) in European adults. The HLS 19 survey was conducted in 2019-2021 including nine countries which measured COM-HL by using a validated questionnaire (HLS 19 -COM-P-Q6 with a score ranging from 0 to 100). Linear regression models were used to study variables associated with COM-HL globally (multilevel model with random intercepts and slopes and at country level) and in each country. Additional models studied each of the HLS 19 -COM-P-Q6 items separately. The mean COM-HL score ranged between 62.5 and 76.6 across countries. Among the 18,137 pooled participants, COM-HL was positively associated with age, a higher self-perceived social status, previous training in healthcare, an increasing number of general practitioner visits; and negatively associated with female sex, reported financial difficulties, having a chronic condition and an increasing number of specialist visits. These effects were heterogeneous from one country to another, and from one item to another when analysing the different COM-HL items separately. However, there was a consistent statistically significant association between COM-HL (score and each item) and financial difficulties as well as self-perceived social status in all countries. Interventions to improve communication between patients and physicians should be a high priority to limit communication disparities., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The Underwater Sensor Network (UWSN) comprises sensor nodes with sensing, data processing, and communication capabilities. Due to the limitation of underwater radio wave propagation, nodes rely on acoustic signals to communicate. The data gathered by these nodes is transmitted to coordinating nodes or ground stations for additional processing and analysis. The characteristics of UWSN with underwater channels make them vulnerable to malicious attacks. UWSN communication networks are particularly susceptible to malicious attacks owing to high bit error rates, significant propagation delay variations, and low bandwidth. Moreover, because of the challenging and erratic underwater conditions, limited bandwidth, slow data transmission speed, and power constraints of underwater sensor nodes establishing secure communication in UWSN presents a significant challenge. To address the issues mentioned above, we have introduced the Multipath Malicious Avoidance Routing Protocol (M2ARP) and Foldable Matrix based Padding Rail Fence Encryption Scheme (FM-PRFES) methods to enhance secure communication in UWSNs. The proposed FM-PRFES method encrypts the input data to prevent unauthorized access during transmission within the network. Subsequently, the proposed Energy Efficiency Node Selection (EENS) method is used to identify the significant nodes in the network. Additionally, the Cuckoo Search Optimization (CSO) method is utilized to select the Cluster Head (CH) for data transmission. Subsequently, M2ARP is employed to analyze various routes and avoid adversarial nodes in the network. As a result, the proposed experimental analysis yields more efficient results regarding security, Packet Delivery Ratio (PDR), and throughput performance than traditional approaches., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Consent to publish: All authors gave permission to consent to publish., (© 2024. The Author(s).)

Understanding how mechanical stress affects erythropoiesis is crucial to produce transfusable erythrocytes in fluid-turbulent bioreactors. We investigated the effects of shear-stress on differentiating CD49d + CD235a + primary human erythroblasts (EBL) at molecular, cellular, and functional level. Shear-stress, at differentiation onset, enhanced EBL maturation and induced upregulation of genes regulating cholesterol/lipids biosynthesis, causing changes in cell lipid composition. Of note, the osmotic resistance, and the expression of 3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the rate-limiting enzyme of the cholesterol biosynthesis pathway, were higher in dynamic cultures. Inhibition of the S1P-induced proteolytic cleavage, activating SREBPs, led to abrogation of HMCGR expression, and loss of EBL in dynamic cultures, similar to lovastatin administration. This data reveals a role for the S1P-SREBP-HMGCR-axis in the regulation of shear-stress induced adaptation during erythropoiesis, shedding light into mechanisms that will assist the upscaling of erythroid differentiation into bioreactors. Moreover, as shear-stress on hematopoietic cells occurs within the bone-marrow, these results introduce a novel signalling axis in the transduction pathways controlling erythropoiesis., Competing Interests: Competing interests:: The author(s) declare no competing interests., (© 2024. The Author(s).)

Recent laboratory tests and large-scale observations have revealed the complex interplays between aseismic and seismic deformation, as well as the progressive localization of the rock failure process. To investigate these processes, we conducted triaxial tests that combined distributed strain sensing (DSS) with acoustic emission (AE) sensors. Progressive strain localization was detected by DSS at 80% of the peak stress but did not produce measurable AEs. Closer to the peak stress, regions exhibiting strain localizations began to show clusters of AEs. This reveals that DSS measurements are more informative during the preparatory stage of brittle rock failure. The frequency-magnitude distribution of the AEs showed an inverse correlation with the volumetric deformation rate a few seconds preceding catastrophic failure. Our results are consistent with recent large-scale observations and offer crucial insights into progressive failure assessment., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Initially, 4,4'-(1,4-phenylene)di(sulfonic)pyridinium tetrachloroferrate (PDSPTCF) as a novel organic-inorganic hybrid salt was synthesized and identified by elemental mapping, energy-dispersive X-ray spectroscopy, inductively coupled plasma atomic emission spectrometer, Raman spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, field emission scanning electron microscopy, vibrating-sample magnetometry, and thermal gravimetric (TG) techniques. Then, the catalytic performance of this hybrid salt was assessed for the producing benzo[a]benzo[6,7]chromeno[2,3-c]phenazine derivatives via one-pot multicomponent domino reaction (MDR) of benzene-1,2-diamine, 2-hydroxynaphthalene-1,4-dione and aldehydes under optimal conditions (70 °C, solvent-free, 5 mol% PDSPTCF) in short reaction times and high yields. Highly efficacy of the PDSPTCF for the production of benzo[a]pyrano[2,3-c]phenazines can be assigned to the synergistic effect of Lewis and Brønsted acids, and having two positions of each acid (i.e., FeCl 4 - and -SO 3 H). In addition, this catalyst showed good reproducibility with six cycles of recycling., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethical approval: This declaration is not applicable. Consent for publication: We have confirmed., (© 2024. The Author(s).)

It has been established that the Hydrazone derivatives have important pharmacological effects. In the first step, hydrazine (NH 2 NH 2 ) reacts with a compound containing a carbonyl group (C = O) in the presence of ethanol and heat, leading to the formation of hydrazone compound (H1). The second step is the formation of the Schiff base (H2) by the reaction of compound (H1) with indole, ethanol, and acetic acid, which contain a double bond (C = N). In the third step, the (H1) reacts with thiophene, ethanol, and acetic acid to form a compound (H3) containing multiple bonds between the indole and thiophene rings. The synthetic test compounds underwent characterization using TLC, IR, 1 H - NMR, and ¹ 3 C NMR spectral examinations. Both compounds, H2 and H3, exhibit antioxidant activity at different concentrations (from 12.5 to 100 µgmL - 1 ), where the effect increases gradually with the increase in concentration. The compounds (H2 and H3) exhibited an apparent inhibitory effect on the growth of Staphylococcus aureus, Escherichia coli, and Candida albicans. Calculations have been performed for DFT, molecular docking, molecular dynamics simulations, and the ADMET protocol, and they are essential for describing the interaction and stability. In hydrazone derivatives, groups like amine, hydroxy, thiophene, and indole form hydrogen bonds and electrostatic interactions with amino acids such as arginine, lysine, glutamic acid, and aspartic acid. These interactions are crucial to evaluating the compound's stability and its potential to inhibit enzyme activity. The results indicate that the compound shows strong binding and stability at the active site, making it a promising candidate for further studies as an anti-colon cancer agent., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The tumor-suppressing p-53 binding protein is a crucial protein that is involved in the prevention of cancer via its regulatory effect on a number of cellular processes. Recent evidence indicates that it interacts with a number of other proteins involved in cancer in ways that are not fully understood. An understanding of such interactions could provide insights into novel ways p53 further exerts its tumour prevention role via its interactions with diverse proteins. Thus, this study aimed to examine the interactions of the p53 protein with other proteins (peptides and histones) using molecular simulation dynamics. We opted for a total of seven proteins, namely 2LVM, 2MWO, 2MWP, 4CRI, 4 × 34, 5Z78, and 6MYO (control), and had their PBD files retrieved from the protein database. These proteins were then docked against the p-53 protein and the resulting interactions were examined using molecular docking simulations run at 500 ns. The result of the interactions revealed the utilisation of various amino acids in the process. The peptide that interacted with the highest number of amino acids was 5Z78 and these were Lys10, Gly21, Trp24, Pro105, His106, and Arg107, indicating a stronger interaction. The RMSD and RMSF values indicate that the complexes formed were stable, with 4CRI, 6MYO, and 2G3R giving the most stable values (less than 2.5 Å). Other parameters, including the SASA, Rg, and number of hydrogen bonds, all indicated the formation of fairly stable complexes. Our study indicates that overall, the interactions of 53BP1 with p53K370me2, p53K382me2, methylated K810 Rb, p53K381acK382me2, and tudor-interacting repair regulator protein indicated interactions that were not as strong as those with the histone protein. Thus, it could be that P53 may mediate its tumour suppressing effect via interactions with amino acids and histone., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The paper presents comparative laboratory investigations of tension fastener models that attach rails to concrete sleepers. The aim of the paper was to assess the influence of geometric nonconformity of the actual industrial product that meets the PKP Polskie Linie Kolejowe S.A. requirements on the operation of a tension-fastening clamp under stress. Due to the cost and limited possibility of research of the actual industrial product, an additional objective of the research was to validate the usefulness of it in the comparative assessment of the models. In the research, the authors used models of tension fastening clamps manufactured in incremental engineering technology (3D print) on scale 1:2. The properties of the fastening clamps (in their nominal shape) were compared (described in the PKP Polskie Linie Kolejowe S.A. documentation) with the fastening clamps of the actual shape. In the investigation, the authors have confirmed the negative influence of the non-conformance of the shape of the actual fastening clamps with the nominal ones., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Microplastic contamination of river sediments has been found to be pervasive at the global scale and responsive to plastic and sediment bed properties, the flow regime and the river morphology. The physical controls governing the storage, remobilization and pathways of transfer in sand bed rivers remain unquantified. This means it is not currently possible to determine the risks posed by microplastic contamination within these globally significant river systems. Using controlled flume experiments we show that sand bed rivers can store up to 40% of their microplastic load within the sediment bed indicating that these environments can act as resilient sinks of microplastics. By linking bedform dynamics with microplastic transport characteristics we show that similarities exist between granular transport phenomena and the behavior, and hence predictability, of microplastic flux. Specifically, we demonstrate the inverse relationship between bedform celerity and microplastic retention within the bed can be used to predict microplastic flux. Further, we show that, in these environments, microplastic shape is more important than previously thought in controlling the fate of microplastics. Together, these findings are significant since they have important implications for the prediction and hence management of microplastic contamination in sand bed environments., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

This paper presents an ultra-wideband (UWB) microstrip antenna with a simple structure operating at 2.2-6 GHz bandwidth. The proposed antenna has been demonstrated for its suitability in UWB and multi-band applications, such as wireless local area network (WLAN), Wi-Fi, 5G, Internet of Things (IoT), etc. The antenna is shown to use a simple folded dipole antenna structure demonstrating an omnidirectional radiation pattern of gain 0.8 to 6 dBi throughout the frequency band. The antenna has strong gain at 2.4, 3.5 and 5.5 GHz. The measured results are shown to have a good agreement with the simulated results., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Despite numerous surveys conducted across the world considering assisted death, content validity evaluations of the survey questionnaires are seldom published. Likewise, there is no previous research about the content validity of the survey "Finnish physicians´ attitudes and opinions on euthanasia and physician-assisted suicide" conducted by the Finnish Medical Association. The aim of this study was to assess the content validity of the survey questionnaire. To study this, a purposive sample of physicians was recruited. Firstly, the participants were interviewed to bring up their interpretations and assessments considering the relevance, comprehensibility, and measurement scale suitability of the questions. Secondly, the participants assessed the revised study questionnaire. Altogether 16 physicians participated in the study. Although the relevance and comprehensibility of the questions were assessed to be high-level, parallel interpretations of the contents were discovered. We suggest content validity research to be essential when developing a questionnaire on assisted death. Our results could be helpful when planning future surveys about this challenging topic., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethical approval and informed consent: This study was evaluated and approved by the Regional Ethics Committee of Human Sciences, Tampere, Finland (36/2023). The participants obtained written and oral information about the study and gave their informed consent to participate. This study was conducted according to national laws, regulations, and the Declaration of Helsinki., (© 2024. The Author(s).)