Search Results (2,492)

The increasing demand for rapid, sensitive, and eco-friendly methods for the detection of trace heavy metals in environmental samples, attributed to their serious threats to health and the environment, has spurred considerable interest in the development of sustainable sensor materials. Toxic metal ions, namely, lead (Pb²⁺), cadmium (Cd²⁺), mercury (Hg²⁺), arsenic (As³⁺), and chromium, are potential hazards due to their non-biodegradable nature with high toxicity, even at trace levels. Acute health complications, including neurological, renal, and developmental disorders, arise upon exposure to such metal ions. To monitor and mitigate these toxic exposures, sensitive detection techniques are essential. Pre-existing conventional detection methods, such as atomic absorption spectroscopy (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS), involve expensive instrumentation, skilled operators, and complex sample preparation. Electrochemical sensing, which is simple, portable, and eco-friendly, is foreseen as a potential alternative to the above conventional methods. Carbon-based nanomaterials play a crucial role in electrochemical sensors due to their high conductivity, stability, and the presence of surface functional groups. Biochar (BC), a carbon-rich product, has emerged as a promising electrode material for electrochemical sensing due to its high surface area, sustainability, tunable porosity, surface rich in functional groups, eco-friendliness, and negligible environmental footprint. Nevertheless, broad-spectrum studies on the use of biochar in electrochemical sensors remain narrow. This review focuses on the recent advancements in the development of biochar-based electrochemical sensors for the detection of toxic heavy metals such as Pb²⁺, Cd²⁺, and Hg²⁺ and the simultaneous detection of multiple ions, with special emphasis on BC synthesis routes, surface modification methodologies, electrode fabrication techniques, and electroanalytical performance. Finally, current challenges and future perspectives for integrating BC into next-generation sensor platforms are outlined. Full article

Stevia rebaudiana Bertoni, a semi-perennial herb from the Asteraceae family, is native to the Paraguay–Brazil border region. The growing industrial interest in this species is due to its natural sweetening properties, such as steviol and its derivatives, which offer sweetness without adding calories. Morphological traits are crucial for assessing genetic variability and ensuring distinctness, homogeneity, and stability (DHS) for cultivar protection. This study characterized 19 elite Stevia genotypes from Embrapa Cerrados’ Active Germplasm Bank (BAG) using 21 morphological descriptors from Brazil’s Ministry of Agriculture, Livestock, and Supply (MAPA). Genetic distances were calculated using the simple coincidence index complement method, and clustering was performed via the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA). The results showed that 17 of the 21 descriptors (>80%) effectively differentiated the genotypes, revealing significant genetic variability. Dendrogram analysis identified at least four major similarity groups, highlighting the potential of these genotypes for Stevia breeding programs. These findings underscore the suitability of these elite genotypes for developing superior varieties adapted to Cerrado conditions, supporting future cultivation and genetic improvement efforts. Full article

Background/Objectives: Cardiorespiratory fitness (CRF) is of great interest in children and adolescents. Due to the limited availability of cardiopulmonary exercise testing, simple and reliable alternatives are needed. A stair climbing test (SCT) for the assessment of CRF developed at the Department of Pediatric Cardiology of the LMU University Hospital in Munich showed a strong correlation with VO₂max. The aim of this study is to prove its feasibility in a non-clinical setting and to analyse its results in a larger study population. Methods: During the “Hand aufs Herz” study, a comprehensive cardiovascular examination was carried out on 922 pupils and siblings (13.2 ± 7.8 years) at a high school in Bavaria. The SCT was performed to evaluate CRF: participants had to run up and down a total of four floors (14.8 m) as quickly as possible without skipping steps or holding on to the banister. Absolute time has been normalized over the standard height of 12 m to allow comparisons with different settings. An SCT Index was calculated to adjust results to the different weights of participants and the exact height of the staircase. Results: The SCT proved to be easily feasible and safe in non-clinical contexts. Out of 922 participants, 13 (1.4%) were not able to perform the test, and 3 (0.3%) had to interrupt it following fatigue or stumbling. A total of 827 participants aged from 9 to 17 years (13.1 ± 2.1 years, 45.8% girls) had a mean absolute SCT time of 53.4 ± 6.2 s and 43.3 ± 5.1 s when normalized over 12 m. Conclusions: The SCT represents a simple, cost- and time-saving test that allows a rapid and solid assessment of cardiorespiratory fitness in children and adolescents. We could demonstrate that it is safe and feasible in non-clinical contexts. Its short duration and universal applicability are valuable advantages that could facilitate the establishment of a repetitive cardiovascular screening in the pediatric population, particularly in outpatient departments or settings with low-resource systems. Full article

During the last few years, the requirements for highly efficient, sustainable, and versatile materials in modern biomedicine, aircraft and aerospace industries, automotive production, and electronic and electrical engineering applications have increased. This has led to the development of new and innovative methods for material modification and optimization. This can be achieved in many different ways, but one such approach is the application of surface thin films. They can be conductive (metallic), semi-conductive (metal-ceramic), or isolating (polymeric). Special emphasis is placed on applying semi-conductive thin films due to their unique properties, be it electrical, chemical, mechanical, or other. The particular thin films of interest are composite ones of the type of transition metal oxide (TMO) and transition metal nitride (TMN), due to their widespread configurations and applications. Regardless of the countless number of studies regarding the application of such films in the aforementioned industrial fields, some further possible investigations are necessary to find optimal solutions for modern problems in this topic. One such problem is the possibility of characterization of the applied thin films, not via textbook approaches, but through a simple, modern solution using their electrical properties. This can be achieved on the basis of measuring the films’ electrical impedance, since all different semi-conductive materials have different impedance values. However, this is a huge practical work that necessitates the collection of a large pool of data and needs to be based on well-established methods for both characterization and formation of the films. A thorough review on the topic of applying thin films using physical vapor deposition techniques (PVD) in the field of different modern applications, and the current results of such investigations are presented. Furthermore, current research regarding the possible methods for applying such films, and the specifics behind them, need to be summarized. Due to this, in the present work, the specifics of applying thin films using PVD methods and their expected structure and properties were evaluated. Special emphasis was paid to the electrical impedance spectroscopy (EIS) method, which is typically used for the investigation and characterization of electrical systems. This method has increased in popularity over the last few years, and its applicability in the characterization of electrical systems that include thin films formed using PVD methods was proven many times over. However, a still lingering question is the applicability of this method for backwards engineering of thin films. Currently, the EIS method is used in combination with traditional techniques such as X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), energy-dispersive X-ray spectroscopy (EDX), and others. There is, however, a potential to predict the structure and properties of thin films using purely a combination of EIS measurements and complex theoretical models. The current progress in the development of the EIS measurement method was described in the present work, and the trend is such that new theoretical models and new practical testing knowledge was obtained that help implement the method in the field of thin films characterization. Regardless of this progress, much more future work was found to be necessary, in particular, practical measurements (real data) of a large variety of films, in order to build the composition–structure–properties relationship. Full article

The escalating consumption of fossil fuels and the rapid development of portable electronics have increased interest in alternative energy solutions that can sustainably self-power wearable devices. Triboelectric nanogenerators (TENGs), which convert mechanical energy into electricity through contact electrification and electrostatic induction, have emerged as a promising technology due to their high voltage output, lightweight design, and simple fabrication. However, the performance of TENGs is often limited by a low surface charge density, inadequate dielectric properties, and poor charge retention of triboelectric materials. To address these challenges, recent research has focused on the use of polymer composites that incorporate various functional fillers. The filler materials play roles in improving dielectric performance and enhancing mechanical durability, thereby boosting triboelectric output even in harsh environments, while also diminishing charge loss. This review comprehensively examines the role of polymer composite design in TENG performance, with particular emphasis on materials categorized by their triboelectric polarity. Tribo-negative polymers, such as PDMS and PVDF, benefit from filler incorporation and phase engineering to enhance surface charge density and charge retention. By contrast, tribo-positive materials like nylon and cellulose have demonstrated notable improvements in mechanical robustness and environmental stability through composite strategies. The interplay between material selection, surface engineering, and filler design is highlighted as a critical path toward developing high-performance, self-powered TENG systems. Finally, this review discusses the current challenges and future opportunities for advancing TENG technology toward practical and scalable applications. Full article

Axis definition plays a key role in the establishment of animal body plans, both in normal development and regeneration. The cnidarian Hydra can re-establish its simple body plan when regenerating from a random cell aggregate or a sufficiently small tissue fragment. At the beginning of regeneration, a hollow cellular spheroid forms, which then undergoes symmetry breaking and de novo body axis definition. In the past, we have published related work in a physics journal, which is difficult to read for scientists from other disciplines. Here, we review our work for readers not so familiar with this type of approach at a level that requires very little knowledge in mathematics. At the same time, we present a few aspects of Hydra biology that we believe to be linked to our work. These biological aspects may be of interest to physicists or members of related disciplines to better understand our approach. The proposed theoretical model is based on fluctuations of gene expression that are triggered by mechanical signaling, leading to increasingly large groups of cells acting in sync. With a single free parameter, the model quantitatively reproduces the experimentally observed expression pattern of the gene ks1, a marker for ‘head forming potential’. We observed that Hydra positions its axis as a function of a weak temperature gradient, but in a non-intuitive way. Supposing that a large fluctuation including ks1 expression is locked to define the head position, the model reproduces this behavior as well—without further changes. We explain why we believe that the proposed fluctuation-based symmetry breaking process agrees well with recent experimental findings where actin filament organization or anisotropic mechanical stimulation act as axis-positioning events. The model suggests that the Hydra spheroid exhibits huge sensitivity to external perturbations that will eventually position the axis. Full article

Using graphs as a data structure is a simple way to represent relationships between objects. Consequently, it has raised the need for algorithms to process, analyze, and extract meaningful information from graphs. Therefore, frequent subgraph mining (FSM) algorithms have been reported in the literature to discover interesting, unexpected, and useful patterns in graph databases. Frequent subgraph mining involves discovering subgraphs that appear no less than a user-specified threshold; this can be performed exactly or approximately. Although several algorithms for mining frequent approximate subgraphs exist, mining this type of subgraph in graph collections has scarcely been addressed. Thus, we propose AGCM-SLV, an algorithm for mining frequent approximate subgraphs within a graph collection that allows structural and label variations. Unlike other FSM approaches, our proposed algorithm tracks subgraph occurrences and their structural dissimilarities, allowing user-defined partial similarities between node and edge labels, and captures frequent approximate subgraphs (patterns) that would otherwise be overlooked. Experiments on real-world datasets demonstrate that our algorithm identifies more patterns than the most similar state-of-the-art algorithm with a shorter runtime. We also present experiments in which we add white noise to the graph collection at different levels, revealing that over 99% of the patterns extracted without noise are preserved under noisy conditions, making the proposed algorithm noise-tolerant. Full article

Breast cancer is a leading cause of mortality among women worldwide. Early detection is crucial for increasing patient survival rates. Artificial intelligence, particularly convolutional neural networks (CNNs), has enabled the development of effective diagnostic systems by digitally processing mammograms. CNNs have been widely used for the classification of breast cancer in images, obtaining accurate results similar in many cases to those of medical specialists. This work presents a hybrid feature extraction approach for breast cancer detection that employs variants of EfficientNetV2 network and convenient image representation based on phase features. First, a region of interest (ROI) is extracted from the mammogram. Next, a three-channel image is created using the local phase, amplitude, and orientation features of the ROI. A feature vector is constructed for the processed mammogram using the developed CNN model. The size of the feature vector is reduced using simple statistics, achieving a redundancy suppression of $99.65\%$. The reduced feature vector is classified as either malignant or benign using a classifier ensemble. Experimental results using a training/testing ratio of 70/30 on 15,506 mammography images from three datasets produced an accuracy of $86.28\%$, a precision of $78.75\%$, a recall of $86.14\%$, and an F1-score of $80.09\%$ with the modified EfficientNetV2 model and stacking classifier. However, an accuracy of $93.47\%$, a precision of $87.61\%$, a recall of $93.19\%$, and an F1-score of $90.32\%$ were obtained using only CSAW-M dataset images. Full article

In this work, we study n-agent Bayesian games with m-dimensional vector types and linear payoffs, also called linear multidimensional Bayesian games. This class of games is equivalent with n-agent, m-game uniform multigames. We distinguish between games that have a discrete type space and those with a continuous type space. More specifically, we are interested in the existence of pure Bayesian Nash equilibriums for such games and efficient algorithms to find them. For continuous priors, we suggest a methodology to perform Nash equilibrium searches in simple cases. For discrete priors, we present algorithms that can handle two-action and two-player games efficiently. We introduce the core concept of threshold strategy and, under some mild conditions, we show that these games have at least one pure Bayesian Nash equilibrium. We illustrate our results with several examples like the double-game prisoner’s dilemma (DGPD), the game of chicken, and the sustainable adoption decision problem (SADP). Full article

In recent times, blades that have the ability to change shape passively or actively have garnered interest due to their ability to optimize blade performance for varying flow conditions. Various versions of morphing exist, from simple chord length changes to full blade morphing with multiple degrees of freedom. These blades can incorporate smart materials or mechanical actuators to modify the blade shape to suit the wind conditions. Morphing blades have shown an ability to improve performance in simulations. These simulations show increased performance in Region 2 (partial load) operating conditions. This study focuses on the effects of the wake for a flexible wind turbine with actively variable twist angle distribution (TAD) to improve the energy production capabilities of morphing structures. These wake effects influence wind farm performance for locally clustered turbines by extracting energy from the free stream. Hence, the development of better wake models is critical for better turbine design and controls. This paper provides an outline of some approaches available for wake modeling. FLORIS (FLow Redirection and Induction Steady-State) is a program used to predict steady-state wake characteristics. Alongside that, the Materials and Methods section shows different modeling environments and their possible integration into FLORIS. The Results and Discussion section analyzes the 20 kW wind turbine with previously acquired data from the National Renewable Energy Laboratory’s (NREL) AeroDyn v13 software. The study employs FLORIS to simulate steady-state non-linear wake interactions for the nine TAD shapes. These TAD shapes are evaluated across Region 2 operating conditions. The previous study used a genetic algorithm to obtain nine TAD shapes that maximized aerodynamic efficiency in Region 2. The Results and Discussion section compares these TAD shapes to the original blade design regarding the wake characteristics. The project aims to enhance the understanding of FLORIS for studying wake characteristics for morphing blades. Full article

The growing interest in alternative fuels stems from the need to reduce greenhouse gas emissions and promote sustainable development. Despite the dominance of fossil fuels in aviation, pulsejet engines offer a promising platform for testing new fuels due to their simple design and fuel versatility. This study presents a multi-criteria analysis of alternative fuels for use in pulsejet engines, emphasizing environmental impacts. Both gaseous (biogas, ethyne, LPG, and natural gas) and liquid fuels (methanol, ethanol, biodiesel, Jet A-1, and SAF) were examined. Exhaust emissions (CO₂, H₂O, CO) were simulated in Ansys 2025 based on literature data and chemical calculations. Additional factors analyzed included calorific value, production cost, thermal expansion, density, life cycle emissions (LCA), CO₂ emissions per fuel mass, and renewable energy content. Using the zero-unitization method, results were normalized into a single aggregate variable for each fuel. The highest values were recorded for biogas and methanol, respectively, indicating their potential as alternative fuels. The findings support further development of sustainable fuels for pulsejet engines. Future research should address combustion optimization and noise reduction, enhancing viability in aviation and other transport sectors. Integration with the current fuel infrastructure is also recommended to facilitate broader implementation. Full article

The growing concern for environmental sustainability has led to an increased interest in biodegradable materials derived from renewable resources. This study explores the innovative use of residual biomass from the green photosynthetic microalga Chlamydomonas reinhardtii, left over after polysaccharide extraction, as a natural filler in the development of the compostable protein-based material SP-Milk^®. The microalgal biomass was characterized using Fourier transform infrared spectroscopy (FTIR) and UV-Visible Spectroscopy to assess its chemical and structural composition. Subsequently, it was incorporated into a biodegradable protein matrix, and the resulting biocomposites were evaluated for mechanical and thermal properties. The results demonstrate that the incorporation of algal filler improves the mechanical strength and elasticity of the material while reducing its glass transition temperature, highlighting its potential for use in sustainable applications as a possible substitute for conventional plastics. The biocomposite materials developed, based on the protein-based material SP-Milk^® and residual microalgal biomass, are environmentally friendly, contributing to the reduction in pollution and the risks associated with plastic accumulation. Thus, this study offers a simple, effective, and sustainable strategy for the valorization of microalgal biomass, enabling the production of biodegradable materials with enhanced mechanical performance, suitable for applications such as sustainable packaging within a circular economy framework. Full article

The Italian market for non-alcoholic beer is very small, with a volume per capita of around 0.7 L. However, there are interesting prospects for future growth for reasons ranging from strict traffic code rules on the quantity of alcohol ingested to simple curiosity. This research aimed to investigate the willingness of Italian consumers/potential consumers to pay for non-alcoholic beer. To accomplish this, a questionnaire was administered using the Google Forms application. Three hundred and ninety-two people participated in this survey voluntarily and without monetary compensation. A probit regression model was used to estimate the impact of certain sociodemographic characteristics (number of inhabitants of the place of residence, region of residence, age group, gender, education level, employment situation, and annual net income), participants’ consumption habits with respect to alcoholic beer, and participants’ knowledge of and preference for non-alcoholic beers with respect to willingness to pay for non-alcoholic beers. The prices respondents were willing to pay ranged from EUR 1.51 to 2.00 for a 33 cL glass bottle. Only two factors significantly affected (p < 0.1) non-alcoholic beer WTP, namely, “Age” and “Non-alcoholic beer color”. WTP decreased as the age of the respondents increased and was higher for the darker beer. Full article

The trade-off between resolution and contrast is a transcendental problem in optical imaging, spanning from artistic photography to technoscientific applications. To the latter, Fourier-optics-based filters, such as the 4f system, are well-known for their image-enhancement properties, removing high spatial frequencies from an optically Fourier-transformed light signal through simple aperture adjustment. Nonetheless, assessing the contrast–resolution balance in optical imaging remains a challenging task, often requiring complex mathematical treatment and controlled laboratory conditions to match theoretical predictions. With that in mind, we propose a simple yet robust analytical technique to determine the optimal aperture in a 4f imaging system for static and quasi-static objects. Our technique employs the mathematical formalism of the H-theorem, enabling us to directly access the information of an imaged object. By varying the aperture at the Fourier plane of the 4f system, we have empirically found an optimal aperture region where the imaging entropy is maximum, given that the object is fitted to the imaged area. At that region, the image is lit and well-resolved, and no further aperture decrease improves that, as information of the whole assembly (object plus imaging system) is maximum. With that analysis, we have also been able to investigate how the imperfections in an object affect the entropy during its imaging. Despite its simplicity, our technique is generally applicable and passable for automation, making it interesting for many imaging-based optical devices. Full article

Highly scattering media have garnered significant interest in recent years, ranging from potential applications in solar cells, photocatalysis, and other novel photonic devices to research on fundamental topics such as topological photonics, enhanced light–matter coupling and light confinement. Here, we report measurements of spectrally and time-resolved delayed luminescence (DL) in highly scattering rutile TiO₂ films. The complex emission kinetics manifests in the non-exponential decay of photon density and the temporal evolution of the spectral composition. We found that while the energy levels of TiO₂ nanoparticles broadly set the spectral regions of excitation and emission, our results demonstrate that the DL intensity and duration are strongly influenced by the inherent multiple elastic and inelastic processes determined by the mesoscale inhomogeneous structure of random media. We show that the lifetime of DL increases up to 6 s for the largest redshift detected, which is associated with multiple reabsorption processes. We outline a simple model for spectrally resolved DL emission from dense scattering media that can guide the design and characterization of composite materials with specific spectral and temporal properties. Full article