Search Results (20,094)

A stripline-type circulator is essential for the initial low-power characterization of vacuum electron devices such as magnetrons, enabling accurate measurements of startup behavior, oscillation frequency, and mode structure while minimizing reflections and protecting diagnostic equipment. In this study, two broadband S-band stripline circulator prototypes operating in the 2–4 GHz and 3–4 GHz bands were designed, fabricated, and experimentally characterized. A unified design methodology was implemented by using the same ferrite material and coupling angle in both structures, providing procurement simplicity, cost reduction, and technological standardization. This approach also enabled a direct assessment of how bandwidth variations influence circulator behavior. The design goals targeted a transmission efficiency above 90%, isolation exceeding 15 dB, and a voltage standing-wave ratio (VSWR) of 1.2:1. Experimental evaluations, including magnetic field mapping, low-power S-parameter measurements, and high-power tests, confirmed that both prototypes satisfy these specifications, consistently achieving at least 90% transmission across their respective operating bands. Additionally, a comparative analysis between a locally fabricated ferrite and a commercial ferrite sample was conducted, revealing the influence of material properties on transmission stability and high-power behavior. The results demonstrate that broadband stripline circulators employing a common ferrite material can be adapted to different S-band applications, offering a practical, cost-effective, and reliable solution for RF systems. Full article

Urban and population densification have resulted in deteriorating living conditions for populations and the loss of UGSs. The COVID-19 pandemic has exposed the social, economic and environmental vulnerabilities of our societies, but it has also demonstrated the importance of UGSs as intrinsic elements for maintaining the quality of life of the population and making urban spaces sustainable. Due to its considerable area of UGS, the district of Benfica in Lisbon, Portugal, is the object of study. The study focuses on understanding how the proximity of UGS influences the practice of leisure activities for different publics, and how they are reflected in the populations’ lives, exploring the context during the COVID-19 pandemic. It develops a methodology with a mixed-methods approach: (1) literature review, policies, and urban planning; (2) observation methods, mapping and spatial analysis of UGS types; and (3) surveys. The empirical results indicate the importance of proximity to improve the frequency, namely for the elderly and children. The results also demonstrate that the quality (infrastructure and equipment) of UGS, despite having less walking proximity, is an important element to attract people to use the UGS. A general conclusion is that the proximity and accessibility (walking or public transport) are interlinked in both profiles of UGS, demonstrating a relationship between the place of residence, easy access and frequency of UGS in the practice of activities and the self-assessed physical and mental health benefits. Full article

This study re-examines generational differences in media literacy and news consumption within the evolving digital landscape. It expands on the well-known dichotomy of Digital Natives and Digital Immigrants by proposing a new conceptual framework that introduces the terms Analog Anchors and Digital Floaters. These terms aim to reflect the heterogeneity and fluidity more accurately, the adaptive nature of users’ engagement with digital media. A quantitative survey was conducted using an online questionnaire distributed to Greek participants (N = 1020) through a non-probability convenience sampling method. The analysis revealed significant variations in digital literacy, news consumption habits, and skepticism toward the media across generations. Findings indicate that the relationships with technology and information are not linear or age-bound but are shaped by cultural, cognitive, and social parameters. High levels of media skepticism observed across all age groups further challenge traditional divides. As a result, this study argues for a paradigm shift that captures the complexity of media literacy in the platform era, moving from static generational labels towards a more dynamic understanding of users as Analog Anchors and Digital Floaters. Full article

The calmodulin-binding protein 60 (CBP60) family comprises essential Ca²⁺-responsive transcription factors that orchestrate salicylic acid (SA)-mediated immunity and broader stress responses. Despite being extensively characterized in model species, the CBP60 family remains poorly understood in watermelon (Citrullus lanatus), a globally significant cucurbit crop highly susceptible to aphid infestation and fusarium wilt. In this study, we performed a comprehensive genome-wide identification and characterization of the CBP60 gene family in watermelon, identifying 16 putative ClaCBP60 members, all of which harbor the conserved calmodulin-binding domain. These genes are non-randomly distributed across chromosomes, featuring a prominent cluster of 10 members on chromosome 3. Phylogenetic analysis across seven cucurbit species categorized the CBP60 proteins into four distinct subfamilies, revealing both evolutionary conservation and lineage-specific diversification. Gene structure and conserved motif analyses revealed shared core domains with subfamily-specific variations, indicative of functional divergence. Furthermore, synteny analysis showed strong collinearity with cucumber and melon, reflecting the evolutionary stability of key CBP60 loci. Transcriptional profiling under F. oxysporum infection and aphid infestation revealed dynamic expression patterns, with ClaCBP60_01 and ClaCBP60_16 exhibiting rapid and robust induction during the early stages of both stresses. These findings indicated that ClaCBP60 genes operate in a coordinated yet diversified manner to modulate defense signaling against F. oxysporum and aphid attack. This study provides a systematic insight into CBP60 family members in watermelon, establishing a foundation for validation and molecular breeding aimed at enhancing biotic tolerance. Full article

This study identifies key determinants shaping countries’ Sustainable Development Goals performance and develops classification models for predicting country group membership based on the SDG Index. The research addresses the urgent need to optimize development policies amid limited resources and the approaching 2030 Agenda deadline. Using data from 154 countries (2024), the analysis reveals that key SDG determinants are fundamentally method-dependent: discriminant analysis identified Goals 10, 6, 15, and 5 as most influential for differentiating countries by SDGI level, while Random Forest identified Goals 4, 9, and 2 as the most important predictors. This divergence reflects fundamentally different analytical perspectives—linear contributions to group separation versus complex nonlinear interactions and synergies between goals—with critical policy implications for prioritization strategies. Correlation analysis demonstrates that sustainable development dynamics operate differently across development stages: high-development countries show strongest associations with technological advancement and institutional capacity, while low-development countries exhibit compensation effects where basic infrastructure provision occurs alongside lagging human capital development. The discriminant model achieved 94.08% overall accuracy with perfect classification for extreme SDGI categories, while the Random Forest model provides complementary insights into interactive pathways. The scientific contribution lies in demonstrating that perceived variable importance depends on analytical framework rather than representing objective reality, and in providing validated classification tools for rapid assessment in data-limited contexts. These findings offer actionable guidance for evidence-based resource allocation and policy prioritization in the critical final years of SDG implementation. Full article

Background: Colorectal cancer (CRC) remains a leading cause of cancer mortality worldwide, with epidermal growth factor receptor (EGFR) inhibitors improving outcomes in patients with metastatic CRC (mCRC) harboring KRAS wild-type tumors. Inflammation has emerged as a potential determinant of treatment efficacy, and the neutrophil-to-lymphocyte ratio (NLR) represents an accessible biomarker reflecting the balance between protumoral neutrophils and antitumor lymphocytes. Methods: We conducted a retrospective study of 44 patients with left-sided, KRAS wild-type mCRC treated at the Institute of Oncology “Prof. Dr. Ion Chiricuta” between 2015 and 2024 with first-line FOLFOX/FOLFIRI plus panitumumab. Baseline NLR (bNLR) and NLR after four treatment cycles were assessed, with progression-free survival (PFS) as the primary endpoint. Results: Receiver operating characteristic analysis identified an optimal bNLR cutoff of 3.06 (AUC = 0.78, p = 0.004). Patients with low bNLR (≤3.06) had significantly longer PFS than those with high bNLR (>3.06) (14 vs. 7 months, HR = 2.7, p = 0.002). Notably, patients with a positive ΔNLR (increase during therapy) also demonstrated superior PFS compared to those with a negative ΔNLR (18 vs. 11 months, HR = 0.47, p = 0.022). In multivariate analysis, only bNLR remained independently associated with PFS. Conclusions: These results suggest that both baseline and dynamic NLR may serve as low-cost prognostic biomarkers in mCRC patients treated with anti-EGFR therapy. Full article

Soil salinization, characterized by complex ionic compositions, threatens global wheat production. Current research often focuses on single salts, leaving a gap in systematic comparisons of specific salt effects. This study comprehensively evaluated six prevalent salts (NaCl, Na₂SO₄, KCl, NaHCO₃, MgSO₄, and MgCl₂) across concentrations (10–200 mmol/L) during wheat (Triticum aestivum L.) germination. By integrating ten physiological indicators with principal component analysis (PCA), membership function evaluation, and median lethal concentration (LC₅₀) calculation, we identified distinct salt-specific toxicities. Results established a clear toxicity hierarchy: MgCl₂ was consistently most toxic (LC₅₀ = 32.92 mmol/L), indicating Mg²⁺/Cl⁻ synergy, while KCl was least inhibitory (LC₅₀ = 159.66 mmol/L). PCA simplified the 10-trait dataset, extracting 1 principal component (PC, 89.29–92.35% contribution) for most salts (fresh weight as key loading, reflecting growth) and 2 PCs (95.65% cumulative contribution) for MgSO₄ (separating root-growth and germination-vigor responses), thus identifying salt-specific key evaluation traits. Building on this PCA-derived trait screening, this analysis further revealed fresh weight (FW), germination rate (GR), shoot length (SL), and simple vigor index (SVI) as core evaluation indicators, and identified distinct mechanistic pathways: while most salts caused a generalized growth inhibition reflected in biomass reduction, MgCl₂ exerted a more specific and severe inhibitory effect on shoot elongation. MgSO₄ uniquely employed dual pathways, separately affecting root and germination traits. An innovative aspect of this work is the synergistic application of three synergistic evaluation methodologies with multi-physiological parameters, which allows for the rigorous quantitative characterization of distinct salt-specific effects on both early germination and seedling growth in wheat. This laboratory-based study provides a theoretical framework and practical indicators for salt damage risk assessment and preliminary screening of salt-tolerant wheat germplasm and lays a foundation for field validation and targeted management strategies for specific saline–alkali soils. Full article

This paper showcases how electric scooter data can be used to visually explore and interpret urban dynamics, offering a perspective on city structure and mobility patterns. The goal of the study is to investigate how visual analysis of micromobility data can reveal spatial and temporal patterns that support urban planning and operational decision-making. Through a series of visual analyses, the article identifies high-demand areas and popular travel routes, with areas of particularly strong traffic—insights valuable for infrastructure planning and operational optimization. Temporal visualizations reveal distinct peaks in e-scooter activity during lunch hours and late evenings, highlighting behavior patterns that may inform service adjustments. Clustering techniques are used to delineate functional zones within the city, which are then visualized to reflect how users interact with urban space. These visuals help uncover mobility-based boundaries and support a deeper understanding of the city’s layout. Additionally, the approach highlights key locations that may be attractive for business development, such as new commercial spots, based on user behavior. By focusing on visual storytelling rather than predictive modeling, this work proposes analyses suitable for urban planners, mobility providers, and other stakeholders with actionable insights into urban movement and structure. Full article

The aim of this article is to determine the extent to which (directly or indirectly) the papal teachings apply to cooperatives as tools for solving social, economic and environmental problems, which were defined by Sustainable Development Goals (SDGs), in accordance with CST by implementing the principles of solidarity, cooperation, justice and respect for human dignity. The analysis of various papal documents covers the period from the pontificate of Pope Leo XIII up to Francis. The popes appreciate the work of cooperatives. They serve their members by implementing Christian values, including in the cooperative movement known as Christian solidarity. Cooperatives had been developing since the 19th century, often thanks to the priests involved in their founding and management. Popes are interested in socio-economic issues, economic activity and its form as cooperatives. Their reflections encompass various issues related to cooperatives, ranging from the right of people to associate, the principles of cooperative activity, the tasks of cooperative members, the role of production, agricultural, banking, consumer, social, labour, and energy cooperatives, to the necessity of state support for this form of management. They also emphasize the achievement of universal personal, spiritual, and community values, as well as the need to promote the common good. Full article

Coastal sandbars play a crucial role in shoreline protection, yet monitoring their dynamics remains challenging due to the cost and limited temporal coverage of traditional surveys. This study assesses the feasibility of using Sentinel-2 multispectral imagery combined with the logarithmic band ratio method to automatically detect submerged sandbar crests along three morphologically distinct beaches on the northwestern Mediterranean coast. Pseudo-bathymetry was derived from log-transformed band ratios of blue-green and blue-red reflectance used to extract the sandbar crest and validated against high-resolution in situ bathymetry. The blue-green band ratio achieved higher accuracy than the blue-red band ratio, which performed slightly better in very shallow waters. Its application across single, single/double, and double shore-parallel bar systems demonstrated the robustness and transferability of the approach. However, the method requires relatively clear or calm water conditions, and breaking-wave foam, sunglint, or cloud cover conditions limit the number of usable satellite images. A temporal analysis at a dissipative beach further revealed coherent bar migration patterns associated with storm events, consistent with observed hydrodynamic forcing. The proposed method is cost-free, computationally efficient, and broadly applicable for large-scale and long-term sandbar monitoring where optical water clarity permits. Its simplicity enables integration into coastal management frameworks, supporting sediment-budget assessment and resilience evaluation in data-limited regions. Full article

Edible mushrooms are often regarded as a sustainable source of proteins, and several studies have sought to further improve the sustainability of this production. The vertical farming (VF) system could help to reduce the environmental impact during the cultivation of this crop. This study aimed to evaluate whether a VF cultivation system could increase the production and sustainability of Pleurotus species. In this study, P. cornucopiae (PC) and P. ostreatus (PO) were cultivated in a VF system using four-layer iron shelves arranged both individually and in combined configurations in the mushrooms greenhouse; a randomized block design with three replicates for each treatment was used. The impact of shelf layers on the productive traits of these crops was also evaluated, comparing upper layers to the ground layer (Control). In addition, a Life Cycle Assessment (LCA) analysis was carried out to compare the environmental impact of VF and a conventional cultivation system for PO. The results demonstrated that the shelf layer influenced primordia formation, yield, and morphological characteristics. PC exhibited optimal growth in the upper layers, whereas PO performed better in the lower layers, reflecting their respective temperature preferences. The shelf configuration affected light exposure and primordia induction but did not significantly influence overall yield or morphology. The VF system had a lower overall environmental burden, in particular, considering the climate change impact (−27%) and fossil fuel consumption (−37%) compared to conventional cultivation. Among the phases, substrate production had the highest impact due to the higher substrate needed. In conclusion, VF for Pleurotus production enhanced both the productivity and the sustainability of this crop, but further study regarding the economic analysis of this system is needed to assess the industrial application of this system. Full article

Background/Objectives: Longitudinal metabolomics analysis offers valuable insights into how metabolic pathways change according to age and health status. However, metabolite levels can fluctuate due to biological factors (e.g., age, diet, and health status) and technical factors (e.g., sample handling, storage times, and instrument performance), with some metabolites exhibiting greater sensitivity to these sources of variability than others. This study aimed to characterize the longitudinal and technical stability of untargeted plasma and cerebrospinal fluid (CSF) metabolites and to identify a subset that remains reliable over the extended time scales required for epidemiological research. Methods: Untargeted ultrahigh-performance liquid chromatography–mass spectrometry (LC-MS) metabolomic profiles were available from multiple visits in the Wisconsin Registry for Alzheimer’s Prevention (WRAP) and Wisconsin Alzheimer’s Disease Research Center (ADRC) studies. For this analysis, we constructed a subset of generally healthy participants with samples drawn at four time points (~2.5 years apart): two visits analyzed in 2017 and two visits analyzed in 2023, corresponding to two distinct analytical waves. We computed Rothery’s intraclass correlation coefficients (ICCs) to quantify intra-wave and inter-wave stability, evaluated pooled quality-control (QC) variation, classified metabolite stability by established thresholds, and developed a composite score integrating longitudinal stability and susceptibility to technical variance. Results: Across all metabolites, median stability was classified as ‘fair’ (Rothery’s ρ > 0.40 to ≤0.75) for both plasma and CSF. Although analytical batches were bridged using pooled QC samples, inter-wave stability was significantly lower than intra-wave stability, reflecting increased technical variability across waves. Using the composite score, we identified subsets of metabolites with ‘excellent’ stability and low susceptibility to batch effects in plasma and CSF. Stability patterns varied across biochemical super pathways. Conclusions: This work highlights metabolites suitable for long-term epidemiological studies and informs experimental design and analytical strategies for combining data across cohorts and analytical batches. Full article

Recent policy reports and state briefs continue to highlight the trend of out-migration from California. This outflow has been pronounced over the last three years, revealing a substantial net loss (i.e., net migration) of approximately 740,000 residents. However, there has been comparatively less emphasis on new residents moving to California. Over the past decade, California has attracted substantial in-migration from both domestic and international sources with annual inflows often exceeding 300,000 individuals. As such, studying in-migration is noteworthy as it shapes economic, political, and social landscapes. In-migration can alter the demographic profiles of regions, thereby impacting community dynamics, cultural diversity, and the provision of social services. Using pooled data from the American Community Survey (ACS) from 2021 to 2023 and employing a two-way fixed effects regression framework, I study how temporal changes in racial and ethnic composition, age structure, educational attainment, and economic indicators influence in-migration rates per 1000 residents at the public use microdata level (PUMA). The analysis reveals that higher proportions of Asian and Hispanic populations, as well as an increased share of college-educated residents, are positively associated with in-migration. Notably, higher supplemental poverty rates are also associated with greater in-migration, a counterintuitive finding that may reflect mobility toward affordable housing markets. These findings emphasize the importance of recognizing demographic and intra-regional variability, which can aid policymakers and planners in assessing and delivering public services. Full article

The precise determination of material type and thickness is of major significance in non-destructive testing, quality assurance, and materials science, as it influences the functionality, reliability, and performance of materials in engineering applications. This study proposes a methodology for the classification of material thickness and type through the analysis of scattering parameters within the 8–12 GHz frequency range. A database was created, encompassing real, imaginary, and dB values of reflection and transmission parameters for nine real-world materials with thicknesses ranging from 1 to 10 mm. This study addressed two main classification tasks, namely material thickness and material type. A variety of training–testing splits were employed in conjunction with 10-fold cross-validation to facilitate a comparison of classifier performance. In the material type classification, incorporating multiple thickness levels of each material enabled the model to distinguish materials with similar reflection characteristics more accurately, thereby enhancing discrimination performance. The results showed that Fine KNN consistently achieved 100% accuracy in thickness classification, while Quadratic SVM achieved 100% accuracy in material type classification, even when utilising only three thickness levels. Furthermore, the 90% training–10% testing split yielded the highest performance in thickness classification, whereas the optimal data split for material type classification differed across classifiers. Overall, this study demonstrates that the combination of scattering parameters and machine learning serves as a reliable and efficient approach for non-destructive material characterization. Full article

This systematic review examined how the Travel Cost Method (TCM) works together with other valuation methods, such as stated and declared preferences, to improve estimates of total economic value (TEV). Despite the widespread use of TCM, no systematic synthesis has examined how its integration with complementary methods enhances TEV estimation across different ecosystems and geographical contexts. Following PRISMA guidelines, we conducted searches in Scopus and Web of Science, identifying 245 records. After the screening process, 57 studies remained for analysis. Results show that 74% of the studies combined TCM with Contingent Valuation Method (CVM), and 12.3% with Choice Experiment (CEM). Three chronological phases were identified: early domination by the United States (1985–2000), international expansion and diversification (2001–2015), and recent methodological innovation led by China (2016–2024). Forest and recreational ecosystems accounted for 25% of applications, followed by marine-coastal (21%). Within cultural ecosystem services, the subcategory of physical and experiential interactions predominates with 63.1%. Comparative analysis indicates that TCM systematically produces higher and more variable monetary estimates than CVM, reflecting its sensitivity to travel behavior and spatial scale, while stated preference methods provide more stable estimates of non-use values. Persistent methodological limitations include non-probabilistic sampling and uneven ecosystem coverage. This review advances the literature by providing the first comprehensive synthesis of integrated TCM applications, demonstrating how methodological combinations strengthen TEV estimation beyond single-method approaches. The findings offer practical guidance for policymakers designing environmental impact assessments, environmental managers selecting valuation tools tailored to ecosystem and management objectives, and researchers seeking standardized and robust frameworks for integrated ecosystem service valuation. Full article