Search Results (7,341)

Telemetric systems are particularly valuable in applications where remote data acquisition and automatic transmission allow effective monitoring of local characteristics. Among the different telemetric approaches, passive wireless systems based on inductive coupling are particularly attractive because they enable sensor interrogation without onboard power storage. Printed electronics (PE) offer several advantages in the realization of such systems, including a wide selection of functional materials, reduced production costs, possibility of rapid prototyping and complete customization. This allows for the development of smart products by embedding sensors and electronics directly into existing objects without significantly altering their geometry or weight. In light of this, the aim of this scoping review is to explore key factors in implementing chipless passive inductively coupled LC telemetric systems via PE. Given the growing interest in smart products, this scoping review serves as a starting point for the design and implementation of smart products specifically on printed passive inductively coupled LC telemetric systems, addressing their development. To better understand the identified solutions, we first outlined the requirements and characteristics of ideal chipless passive LC-based inductively coupled telemetric systems. Then, we provided a comprehensive analysis of conductive materials and substrates, manufacturing technologies, and the design and performance of printed inductors and associated readout architectures. Full article

Identifying similarities in data is fundamental to discovery in science. Measuring or ranking similarity is a key way of reducing the dimensionality of data, is at the heart of many data intensive algorithms and can also be used directly for some applications. This paper extends our understanding of a relatively simple similarity problem. Our primary application is spectral-based fault localisation (SBFL), in which a computer program is run with a large number of test cases and data is collected on which statements are executed in each test case. For each statement, the set of test cases in which it is executed is compared to the set of test cases that failed, and this is used to rank the statements to help locate bugs, an instance of what we call the similarity to a single set (STASS) problem. This paper is primarily theoretical but some contributions are validated with SBFL experiments. Set similarity is equivalent to similarity of binary vectors or two-by-two contingency tables. The problem is also equivalent to converting two-dimensional data with a “partial order”, such as points on a rectangular grid, to a one-dimensional total order. Even when the raw data is not binary, we are often interested in comparing binary classifiers for the data, such as diagnostic tests, and comparing binary classifiers is an instance of the STASS problem. More than a hundred set similarity measures have been proposed in the literature and hundreds of thousands have been evaluated for SBFL, but there is very little understanding of how best to choose a similarity measure for a given domain. This work discusses numerous properties and forms of symmetry that similarity measures can have. It refines previously identified properties so they are no longer incompatible, identifies new forms of symmetry, defines ordering relations over similarity measures, and proposes a new statistic that can be used to help choose a good similarity measure for a given domain. Full article

Growing environmental pressures have increased interest in zero-waste practices within the hospitality industry, while digital platforms have become key spaces where such practices are interpreted and debated. However, limited research has examined how zero-waste hospitality is represented in digital public discourse. This study addresses this gap by analyzing 10,944 posts from X (Twitter) collected globally in English using an integrated approach combining text mining, sentiment analysis, and topic modeling implemented in Python (v3.14.5). The findings indicate that online discussions are predominantly neutral and positive, suggesting a normalization of zero-waste practices, while critical narratives point to concerns about greenwashing, pricing, and implementation consistency. Topic modeling further shows that zero-waste hotels are framed within broader themes, such as circular economy and carbon reduction, rather than solely operational practices. Building on these insights, the study proposes a three-layer conceptualization of digital sustainability discourse—informational, normative, and critical dimensions. By offering a conceptual perspective grounded in large-scale user-generated data, the study contributes to sustainable tourism literature and advances our understanding of how sustainability practices are socially constructed in digital contexts. Full article

Background: The increased detection of small peripheral non-small-cell lung cancers through screening programs has renewed interest in parenchyma-sparing sublobar resection as an alternative to lobectomy. While oncologic non-inferiority has been established, the functional impact of sublobar resection remains a key consideration. Methods: We reviewed evidence from landmark randomized controlled trials, recent meta-analyses, observational studies, and updated clinical practice guidelines. Results: In the CALGB 140503 trial, sublobar resection demonstrated only a modest 2-percentage-point advantage in preserved FEV1 and FVC at 6 months compared with lobectomy, a difference considered clinically marginal in patients with normal baseline pulmonary function. A meta-analysis of five randomized controlled trials confirmed that sublobar resection was associated with significantly less reduction in postoperative lung function. A retrospective study demonstrated that segmentectomy preserved FEV1 at 84.2% of preoperative values versus 69.9% after lobectomy at one year, with particular benefit observed in elderly patients and those with COPD. Volumetric analyses showed greater contralateral compensatory lung expansion after lobectomy, partially offsetting functional differences. Notably, patient-reported outcomes, including physical function, dyspnea, and cough scores, showed no significant differences between groups up to two years postoperatively. The ERS/ESTS 2025 guideline noted that segmentectomy is associated with reduced long-term dyspnea deterioration and may improve patients’ ability to tolerate subsequent treatments. Conclusions: Sublobar resection offers a statistically significant but modest advantage in spirometric lung function preservation over lobectomy for early-stage NSCLC. This benefit may be most clinically relevant in patients with compromised baseline pulmonary function, COPD, or a potential need for future treatments. Full article

As a non-pathogenic oomycete, Pythium oligandrum possesses unique advantages, particularly in the context of being a biological control agent. With the increasing awareness of consumer consciousness, people are paying more attention to the use of environmentally friendly strategies in plant disease prevention and control. Pythium oligandrum is a type of biocontrol oomycete that can be developed as a biological control agent, and it does not have adverse effects on humans in the prevention and control of plant diseases. Consequently, there is increasing scientific interest in the beneficial plant–microbe interactions mediated by P. oligandrum. Currently, the main points of focus regarding the beneficial role of P. oligandrum in plant interactions are as follows: (i) P. oligandrum can activate plant defense responses and cause plants to produce resistance, thus protecting them from disease attacks; (ii) it is a strong mycoparasite that can coil around various oomycetes and fungi, directly killing pathogenic microorganisms; (iii) in addition, it can also promote plant growth. In this paper, we will discuss the aforementioned three main features in detail. Full article

Ultra-high-temperature ceramics (UHTCs) in the Ta–Hf–C ternary system are of significant interest for extreme aerospace and energy applications due to their melting points near 4000 °C. However, their synthesis typically requires extreme temperatures and pressures. This study reports a pectin-assisted low-temperature route for Ta-rich Ta_xHf_1−xC powder synthesis via carbothermal reduction at 1500 °C. The effect of Ta/Hf molar ratios (2.7/1, 0.9/1, and 0.3/1) on phase evolution, crystallinity, and morphology was systematically investigated. FTIR confirmed the successful formation of homogeneous hybrid organic–inorganic precursors through the chelation of metal ions with pectin functional groups. XRD results demonstrated that the Ta-rich composition (Ta/Hf = 2.7/1) promotes the formation of a high-purity (95.87%) cubic solid solution (lattice parameter a = 4.453 Å) with sharp reflections and improved crystallinity. In contrast, Hf-rich samples exhibited incomplete conversion, leaving unreacted HfO₂ and Ta₂Hf₆O₁₇ oxide phases due to the high thermodynamic stability of hafnia. Microstructural analysis revealed quasi-spherical Ta_xHf_1−xC particles with an average size of approximately 123 nm, together with finer residual oxide particles of about 50 nm. Overall, these results demonstrate that pectin-assisted precursor chemistry is an effective strategy for promoting low-temperature carbide formation in Ta-rich Ta_xHf_1−xC compositions. Full article

The powder metallurgy route (PM route) for producing aluminum closed-cell foams has recently attracted significant scientific and industrial interest. The process involves mixing a blowing agent powder (e.g., TiH₂) with aluminum powder, then compacting the mixture to produce a high-density bulk foamable precursor (BFP). The BFP is then heated above the melting point of aluminum, where the hydrogen released from TiH₂ particles forms bubbles in the molten aluminum, which become closed pores (cells) upon solidification. Despite metal powder agglomeration being an important factor in powder metallurgy research that can significantly influence processing, it has surprisingly received little to no attention in the powder-based foaming of metals. To the best of our knowledge, this paper is the first to address aluminum powder agglomeration within the context of powder-based metallic foams. Results show that significant aluminum powder agglomeration not only leads to an inhomogeneous distribution of the TiH₂ particles within the BFP, but also to the formation of locally higher than nominal concentrations of TiH₂ particle-rich regions, which greatly influence foaming characteristics. The work, for the first time, highlights the need to seriously consider metal-powder agglomeration (even partial agglomeration) in future foaming research via the PM route, and its effect on foaming characteristics. Full article

The rapid expansion of ski tourism in Northeast China has triggered extensive land use and land cover change (LULCC), yet the micro-scale spatial mechanisms linking historical land conversion to the accessibility of tourist services remain largely unquantified. This study addresses this gap by integrating annual 30 m CLCD land cover data with GIS network analysis of Points of Interest (POIs) around 30 major ski resorts (2018–2023). Specifically, it makes a novel distinction between the accessibility outcomes of construction-oriented and agriculture-oriented land transitions. Results indicate that while forest-to-construction conversion significantly predicts reduced travel distances to services (e.g., hotels: r = −0.532, p < 0.01), a distinct and previously unreported agri-tourism synergy emerges: forest-to-cropland conversion is positively associated with higher per capita tourist spending (r = 0.366, p < 0.05). This finding challenges the conventional zero-sum view of land use competition and suggests that cultivated landscapes can function as complementary tourism assets. These empirical patterns provide an evidence-based framework for integrated land-transport planning in emerging winter sports destinations. Full article

Purpose: This study explores how older adults with chronic back pain (CBP) evaluate different user interface (UI) designs and gamification elements for an ultrasound-based wearable providing real-time biofeedback during segmental stabilization exercises (SSE). The aim is to identify design preferences and motivational factors to enhance usability, engagement, and adherence in this specific population. Methods: We conducted a mixed-methods study with 15 older adults (aged ≥ 65) experiencing CBP. Participants interacted with three UI mockups (simple, anatomical, and playful) via a Wizard-of-Oz simulation and evaluated additional motivational elements (e.g., points, badges, progress charts). Semi-structured interviews and the Technology Usage Inventory (TUI) subscales were used to assess usability, acceptance, and intention to use. Results: Participants preferred the simple and anatomical UI designs, citing clarity, professionalism, and ease of interpretation. The playful design was viewed as less appropriate due to perceived infantilization. Game elements such as progress tracking, points, and levels were positively received, while competitive features like leaderboards were viewed critically. Most participants expressed interest in integrating pain education, favoring multimedia formats. Conclusions: Digital health tools for older adults must prioritize intuitive, medically reliable interfaces and allow personalization of motivational and educational components. The findings highlight the need for age-appropriate UI design and suggest that well-balanced gamification and educational features may enhance perceived acceptance and have the potential to support long-term use, which should be evaluated in longitudinal studies. Full article

(1) The growing interest in the use of natural and sustainable ingredients highlights the investigation of vegetable oils in dermato-cosmetic applications. In this context, the vegetable oil obtained from walnut (Juglans regia L.) is of actual interest due to its composition rich in unsaturated fatty acids. The aim of the present study was to investigate and characterize walnut oil from a physicochemical, structural, and rheological point of view. (2) The oil was obtained by a cold pressing process from walnut seeds, with a yield of about 51.03 ± 1.41%, and subsequently analyzed by complementary methods. (3) The results show an acceptable physicochemical profile, characterized by appropriate values of density, pH, and spreadability. The oxidative stability indicated a moderate resistance to degradation, specific to oils rich in polyunsaturated fatty acids. Fourier infrared transform spectrometry (FTIR) analysis confirmed the presence of functional groups characteristic of triglycerides, without indications of advanced oxidation, and atomic force microscopy (AFM) investigations revealed a heterogeneous morphology. The rheological properties indicated a pseudoplastic behavior, favorable for topical application. The determination of heavy metals confirmed the safety of the raw material for the intended dermato-cosmetic use. While arsenic levels were slightly above the strict Codex Alimentarius limits for foodstuffs, all values remained within the safety ranges established for cosmetic ingredients. A total of six fatty acids were found in cold-pressed walnut oil, determined using GC-MS methods. The number of compounds identified in the silylated sample was found to be 17. The antioxidant activity determined using DPPH and ABTS methods was generally considered good and relatively stable over time. The measured sun protection value (SPF) demonstrates a favorable capacity to act as a photoprotective ingredient against ultraviolet (UV) radiation. (4) Overall, the results demonstrate that walnut oil presents adequate physicochemical and structural properties, supporting its further use as a potential cosmetic raw material. Full article

This paper presents analytical approximations for the inverse error function, its complementary inverse, and the cumulative distribution function using the Power Series Extender Method (PSEM). The proposed expressions exhibit high accuracy over a wide portion of the domain, particularly in the central region, while maintaining a compact structure based on elementary functions. This formulation ensures practical implementation and computational efficiency without the need for specialized numerical algorithms. The use of strategically selected cancellation points further enhances the accuracy of the approximations, especially in regions of interest. As expected for this class of elementary approximations, a gradual loss of accuracy is observed near the boundaries of the domain due to the asymptotic behavior of the inverse functions. To demonstrate the effectiveness and practical relevance of the proposed expressions, two case studies are presented, involving applications in statistical analysis and engineering contexts. Full article

Background/Objectives: High liver fat content is closely associated with hepatic disease and multiple comorbidities including cancer, diabetes and cardiovascular accidents. Therefore, accurate quantification of hepatic steatosis, especially of borderline cases, is essential for clinical management. Although MRI non-invasively assesses hepatic steatosis, current approaches remain limited by the data variability introduced through use of region-of-interest measurements or classification models that predict discrete fat grades without providing uncertainty estimates. This study proposes a probabilistic approach for hepatic steatosis quantification based on combining a neural network and beta distribution, enabling prediction of hepatic fat percentage with corresponding confidence intervals. Methods: Single in-phase Dixon MRI liver images from a cohort of prepubertal males (n = 84) were used as input to a probabilistic neural network combined with a beta distribution framework to estimate hepatic fat content along with associated confidence intervals. The predicted fat fractions were then compared against reference MRI-derived measurements (ground truth). Results: The methodology achieved a low prediction error and demonstrated good performance for the test set, with predicted values in good agreement with the ground truth measurements. This was reflected by the mean absolute error (MAE = 0.44 percentage points) and the coefficient of determination (R² = 0.98). The empirical standard deviation of the prediction errors on a logarithmic scale was σ = 0.0609. Conclusions: By incorporating uncertainty quantification into hepatic steatosis estimation, this probabilistic framework provides an interpretable measure of variability alongside point estimates. The approach is demonstrated in a specific cohort and requires further validation in broader populations. Full article

Xylitol is a five-carbon sugar alcohol of industrial interest due to its applications as a food sweetener and sugar substitute. In this study, artificial neural networks combined with a genetic algorithm were evaluated as a data-driven approach for modeling and exploring xylitol production by Spathaspora boniae and Spathaspora brasiliensis during fermentation of sugarcane bagasse hemicellulosic hydrolysate. The dataset comprised 20 experimental points obtained from a face-centered central composite design, using urea, yeast extract, peptone, and ammonium sulfate as input variables. The neural network models showed high goodness-of-fit, with R² values of 0.9952 for S. boniae and 0.9930 for S. brasiliensis. Experimental validation of the optimized conditions resulted in xylitol production of 11.54 ± 0.52 g L⁻¹ for S. boniae and 9.29 ± 0.24 g L⁻¹ for S. brasiliensis. Comparison with response surface methodology showed that both approaches provided strong predictive performance, although the statistical model predicted the optimum conditions more accurately. For S. boniae, however, the ANN-GA approach identified an alternative condition associated with lower nitrogen supplementation and higher experimental xylitol production. Given the limited dataset, this study should be regarded as a proof-of-concept for the application of data-driven optimization tools to xylitol fermentation. The results indicate that ANN-GA can complement classical statistical methods by helping to identify alternative operating conditions in bioprocess optimization. Full article

Background: The expanding interest in chatbots within the medical domain underscores the imperative for a comprehensive understanding of their capabilities and limitations, particularly in the context of anatomical education. Chatbots possess the potential to comprehend intricate anatomical concepts, deliver both advanced and contextually relevant information, and serve as a valuable resource for medical students and educators. This study aimed to evaluate the proficiency and constraints of chatbots in the domain of neuroanatomy. Methods: We developed 30 questions and administered them to ChatGPT-4, Google Gemini, Microsoft Copilot, and Perplexity.ai in their open versions. Questions were collaboratively constructed by the research team, selected through a semi-randomized process within the domain of neuroanatomy. Chatbots’ responses were evaluated in a blinded manner for validity and appropriateness, utilizing a 5-point Likert scale. Results: The highest observed performance among the evaluated chatbots was exhibited by ChatGPT-4 and Perplexity.ai, which achieved scores of 4.6 ± 0.5 and 4.5 ± 0.5, respectively. Microsoft Copilot (4.4 ± 0.5) and Google Gemini (4.1 ± 1.0) followed. The least successful performance was observed in the task of generating a neuroanatomical structure: only Microsoft Copilot attempted to fulfil the request, albeit with a dramatically flawed outcome. Conversely, Google Gemini and Perplexity.ai provided web links to anatomical illustrations. Conclusions: Despite technological advancements, AI models have not yet reached a level of sophistication sufficient to entirely supplant the role of educators or facilitators in a neuroanatomy course; however, they can serve as valuable adjunct tools for medical educators and students when utilized with careful consideration. Full article

Background/Objectives: Adolescent mental health problems emerge early, remain undertreated, and are shaped by diverse contextual stressors. In response to calls for more youth-centered prevention, school-based health promotion, and participatory intervention design, this study explored which mental health-related problems internationally mobile adolescents prioritize and which solution ideas they generate in a structured co-creation setting, including where movement- and sport-related elements are embedded. Methods: A qualitative, participatory study was conducted during a 24 h social hackathon embedded in the Youth Empowerment Seminar for exchange students. Hackathon materials from 43 projects were analyzed using content-structuring qualitative content analysis following Kuckartz. Results: Adolescents most frequently framed problems in terms of self-image, stress and anxiety, belonging, and harassment. Solutions clustered around low-threshold group formats, while implementation segments focused strongly on staffing, funding, barriers, and feasibility. Cross-domain analyses suggested recurring problem-solution matches, such as loneliness with hobby or interest groups. Conclusions: Social hackathons can surface adolescent-prioritized mental health concerns and translate them into context-sensitive prevention ideas. The findings mainly point to social and psychosocial solution pathways, while some proposals additionally positioned shared activity or movement contexts as potentially supportive for well-being. These results provide a starting point for subsequent school-based prototyping and feasibility work. Full article