Search Results (573)

The Internet of Things (IoT) and Edge Computing (EC) play an essential role in today’s communication systems, supporting diverse applications in industry, healthcare, and environmental monitoring; however, these technologies face a major challenge in accurately determining the geographic origin of sensed data, as such data are meaningful only when their source location is known. The use of Global Positioning System (GPS) is often impractical or inefficient in many environments due to limited satellite coverage, high energy consumption, and environmental interference. This paper recruits the Distance Vector-Hop (DV-Hop), Jellyfish Search (JS), and Artificial Rabbits Optimization (ARO) algorithms and presents an innovative GPS-free positioning framework for three-dimensional (3D) EC environments. In the proposed framework, the basic DV-Hop and multi-angulation algorithms are generalized for three-dimensional environments. Next, both algorithms are structurally modified and integrated in a complementary manner to balance exploration and exploitation. Furthermore, a Lévy flight-based perturbation phase and a local search mechanism are incorporated to enhance convergence speed and solution precision. To evaluate performance, sixteen 3D IoT environments with different configurations were simulated, and the results were compared with nine state-of-the-art localization algorithms using MSE, NLE, ALE, and LEV metrics. The quantitative relative improvement ratio test demonstrates that the proposed method is, on average, 39% more accurate than its competitors. Full article

This study investigates the phylogenetic relationships, genetic diversity, and biogeographic structure of Pipistrellus species in Türkiye using mitochondrial cytochrome b (Cytb) sequences from 156 specimens collected across 26 localities. Our primary aim was to clarify taxonomic boundaries of morphologically cryptic species and elucidate the evolutionary role of Anatolia in the Western Palearctic. Analyses strongly confirmed that molecular data are mandatory for defining taxonomic boundaries. Crucially, all individuals morphologically identified as P. pygmaeus were genetically determined to be P. pipistrellus, highlighting the inadequacy of external traits for cryptic species. We resolved deep intraspecific divergence across the genus. In P. pipistrellus, two major lineages (Eastern and Western) were identified, partially separated by the Anatolian Diagonal. Their co-occurrence in multiple localities confirms Anatolia’s function as a secondary contact zone. Similarly, P. kuhlii populations represent a transition zone where two distinct lineages, one of Asiatic origin (P. k. lepidus) and one Mediterranean-Levantine (P. k. kuhlii), meet. Furthermore, while P. nathusii is largely associated with migratory European lineages; a genetically distinct, potentially resident lineage was revealed in southwestern Anatolia. Divergence time estimations indicate that this diversification was shaped by major climatic events from the Miocene to the Pleistocene. This study demonstrates that Anatolia is more than just a geographic bridge; it is a dynamic center of evolution, functioning critically as both a glacial refugium and a secondary contact zone for Palearctic bat fauna. Full article

The fritillary (Fritillaria meleagris) is a rare and endangered species that originated in forested habitats, but due to landscape changes, turned into a wet meadow plant. Currently, larger populations can be found in meadows than in forests. Nowadays, as hay production has become unnecessary, wet meadows are being slowly reforested. Little comparative evidence exists on the performance of populations in the two contrasting habitats. We examined Fritillaria meleagris populations in meadows and forests to investigate the impact of current land use changes on the demographic characteristics of this species. The study was carried out over three years in two geographical regions in Hungary, comparatively in two habitat types (forest and meadow). We used permanent quadrats to record the demographic status and morphometric traits of at least 100 fritillary plants in every population. Although some characteristics were different in each population, the results suggested that each population has a special demographic structure. There were larger variations between the different populations and only minor variations among populations across years in demographic composition. Trait variation across geographical regions exceeded the variation observed between habitat types as well. We conclude that regional differences override the role of habitat type in determining the demography and vulnerability of fritillaries. Full article

Organic acids shape the organoleptic properties of honey and are linked to its health-beneficial properties. Their composition is affected by botanical and geographical origin, and some acids have even been proposed as markers for authentication of varietal honeys. Organic-acid composition was determined using high-performance liquid chromatography with photodiode-array detection (HPLC-DAD) in 152 samples of monofloral (willow, acacia, rape, phacelia, linden, heather, buckwheat and goldenrod) and honeydew (deciduous and coniferous) honeys from Poland. The deciduous and coniferous honeydew honeys were distinguished by high content of L-(+)-lactic acid and the presence of succinic acid as well as high total content of acids. Buckwheat honey was the only variety for which the presence of D-(−)-tartaric acid was quantified. These three honey varieties were clearly separated from the others using principal component analysis (PCA). Samples from the other varieties formed one cluster. We conclude that while some promising results were obtained for distinguishing honeydew and buckwheat honeys from other varieties, further investigation is needed, including analysis of additional acids and possibly other physicochemical parameters. Full article

As tangible relics of modern colonial history, Manchurian regime (Manchukuo) architecture of Changchun possesses both historical commemorative value and tourism and cultural functions. Public perception and sentiment regarding this heritage in the contemporary social media context are key dimensions for evaluating the effectiveness of cultural regeneration. Existing research on Manchurian regime architecture has focused primarily on historical research and architectural form analysis, with limited research examining the diverse public interpretations of its cultural value through multi-platform social media data. This study aims to systematically explore the public’s cognitive characteristics, sentimental attitudes, and themes of interest regarding Changchun’s Manchurian regime architecture using online ethnographic data, providing empirical support for optimizing cultural regeneration pathways for Manchurian regime architectural heritage. The study collected data from 1 January 2020 to 20 September 2025, using the keyword “Changchun Manchurian regime architecture”. Using Python crawlers, the study extracted 334 original videos and 18,156 related comments from Douyin, Ctrip, and Dianping. The analysis was conducted using word frequency statistics, SnowNLP sentiment analysis, LDA topic modeling, and multidimensional visualization. The study found that (1) word frequency statistics show that the public has multiple concerns about the historical symbols, geographical positioning, cultural and tourism functions, and national emotions of Manchurian regime architecture; (2) SnowNLP analysis shows that positive comments account for 71%, neutral comments account for 11%, and negative comments account for 18%; (3) the optimal number of topics was determined to be five through perplexity and consistency indicators, namely “historical narrative and imperial power symbols”, “emotional experience and historical reflection”, “visit experience and service facilities”, “site distribution and regional space”, and “explanation and tour evaluation”; (4) the corpus can be divided into five time period stages, namely S1 (2020)–S5 (2024–2025), reflecting the shift in public attention from “space-facilities” to in-depth reflection on “emotion-history”. Full article

Background/Objectives: Houttuynia cordata Thunb., a widely consumed vegetable and traditional food in Asia, possesses significant nutritional value. However, the impact of geographical origin on its nutritional metabolite composition, crucial for food quality and functionality, remains unclear. Methods: Here, we conducted a comprehensive metabolomic analysis of H. cordata cultivated across six major Chinese regions (Yunnan, Guangxi, Guizhou, Sichuan, Chongqing, Hubei) using UPLC-MS/MS. Results and Conclusions: We identified 496 nutritional metabolites, predominantly amino acids and derivatives (53.23%). Key bioactive carbohydrates, maltotriose and maltitol, exhibited distinct geographical accumulation patterns: maltotriose was significantly enriched in Yunnan (YN), while maltitol accumulated predominantly in Sichuan (SC). Integrated transcriptomic analysis linked this variation to the differential expression of starch metabolism genes (GBE1/glgB, α-amylases, β-amylases). Bioinformatic evaluation suggested potential health-related functionalities associated with these metabolites. These findings provide critical insights into the geographical determinants of H. cordata nutritional quality and functional properties. They offer a scientific foundation for optimizing cultivation practices based on regional advantages and developing H. cordata as a region-specific, high-value vegetable and functional food ingredient targeting distinct nutraceutical applications. Full article

The accurate forecasting of surface air temperature (T2M) is crucial for climate analysis, agricultural planning, and energy management. This study proposes a novel forecasting framework grounded in structured temporal decomposition. Using the Kolmogorov–Zurbenko (KZ) filter, all predictor variables are decomposed into three physically interpretable components: long-term, seasonal, and short-term variations, forming an expanded multi-scale feature space. A central innovation of this framework lies in training a single unified model on the decomposed feature set to predict the original target variable, thereby enabling the direct learning of scale-specific driver–response relationships. We present the first comprehensive benchmarking of this architecture, demonstrating that it consistently enhances the performance of both regularized linear models (Ridge and Lasso) and tree-based ensemble methods (Random Forest and XGBoost). Under rigorous walk-forward validation, the framework substantially outperforms conventional, non-decomposed approaches—for example, XGBoost improves the coefficient of determination ($R^2$) from 0.80 to 0.91. Furthermore, temporal decomposition enhances interpretability by enabling Ridge and Lasso models to achieve performance levels comparable to complex ensembles. Despite these promising results, we acknowledge several limitations: the analysis is restricted to a single geographic location and time span, and short-term components remain challenging to predict due to their stochastic nature and the weaker relevance of predictors. Additionally, the framework’s effectiveness may depend on the optimal selection of KZ parameters and the availability of sufficiently long historical datasets for stable walk-forward validation. Future research could extend this approach to multiple geographic regions, longer time series, adaptive KZ tuning, and specialized short-term modeling strategies. Overall, the proposed framework demonstrates that temporal decomposition of predictors offers a powerful inductive bias, establishing a robust and interpretable paradigm for surface air temperature forecasting. Full article

Background/Objectives: Race-based cardiac screening criteria in sports cardiology, including the “Black athlete’s heart” concept, assume biological distinctions that may not reflect physiological reality. This systematic review evaluates whether geographic ancestry provides more clinically relevant predictors of cardiac adaptation than racial categorization. Methods: PubMed was searched (January 2005–July 2025) for studies examining cardiac adaptations in athletes by ethnicity. Data extraction captured demographics, geographic origin, cardiac assessments, and outcomes. Narrative synthesis was employed due to methodological heterogeneity. Results: Forty-seven studies (n = 66,130) revealed substantial within-race heterogeneity. The “Black athlete repolarization variant” prevalence ranged from 1.8% (Brazilian) to 30% (Ghanaian) Black athletes. Left ventricular wall thickness >12 mm (normal <11 mm) occurred in 7.1% of Black versus 0.4% of White athletes, yet varied significantly within Black populations—10.8 ± 1.2 mm in Sub-Saharan versus 9.4 ± 1.1 mm in African-American athletes (p < 0.001). Relative wall thickness ≥0.44 (normal ≤0.42) was presented in 43% of West/Middle African, 23% of East African, and 7% of White athletes. T-wave inversion showed four-fold variation within Black populations (3.6–8.5% West African versus 0.5–2.0% African-American/Caribbean). Current International Criteria demonstrated inequitable specificity: 3.3% false-positive rate in Black versus 1.4% in White athletes. Conclusions: Geographic ancestry explains more cardiac variation than racial categories, supporting contemporary understanding of race as a sociopolitical construct. The persistent diagnostic disparities in ECG screening specificity highlight the need for reform. Transitioning toward protocols incorporating continental origin, anthropometric factors, and social determinants of health—while eliminating terminology like “Black athlete’s heart”—represents an important step toward achieving equity in cardiovascular care for diverse athletic populations. Full article

Background: Health literacy (HL) is a key determinant of health outcomes and equity. The European Health Literacy Survey 2019 (HLS₁₉) introduced three domain-specific instruments—HLS₁₉-NAV, HLS₁₉-COM-P-Q11, and HLS₁₉-VAC. We present the translation, cultural adaptation, field testing, and descriptive pilot evaluation of their Greek versions (HLS₁₉-NAV-GR, HLS₁₉-COM-GR, HLS₁₉-VAC-GR). Methods: Dual forward/back-translation and expert review (11 health professionals/academics) produced the final versions. A purposive, quota-guided field test (N = 71) approximated population distributions by sex, age, education, and geographical region. Test–retest stability (n = 16; ~12 days) was summarized primarily with intraclass correlation ICC (2,1), with Pearson/Spearman correlations reported secondarily. Internal consistency was assessed using ordinal alpha computed from polychoric (polytomous) and tetrachoric (dichotomous) correlations. We report item- and scale-level descriptive statistics for both the original polytomous (four-category, 1–4) responses and a dichotomous difficulty–ease scheme (1–2 vs. 3–4). Given the non-probability sampling in this pilot, the results are descriptive, not statistically representative. Results: Instruments were well accepted, requiring only minor revisions. Scales demonstrated high short-term stability and good internal consistency; inter-scale correlations were moderate, interpreted as associations among related but distinct constructs. Item distributions skewed toward Easy/Very Easy; several HLS₁₉-VAC-GR items showed a clear ceiling, suggesting the need to consider harder items or a larger item pool in future validation. By scale, scores followed the descending order NAV, COM, and VAC. Distributions and ranking patterns broadly mirrored population-level findings from other countries. Conclusions: The adapted HLS₁₉-NAV/COM/VAC-GR instruments are linguistically and culturally appropriate and prepared for large-scale validation, while items NAV9, COM4, and the VAC ceiling are flagged for further assessment. Full article

Propolis is a valuable natural product whose chemical composition and bioactivity are strongly dependent on its geographical and botanical origin. This study presents a comprehensive comparative analysis of the volatile profiles and antibacterial properties of propolis from Romania, Australia, and Uruguay, benchmarked against previously published data from samples from Poland and Turkey. Volatile compounds were profiled using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The resulting data were interrogated using multivariate chemometric analyses (HCA, PCA), and antibacterial activity was assessed via the disk diffusion method against five bacterial strains. Chemometric analysis revealed a clear demarcation into two primary chemotypes: a European type (Poland, Romania, Turkey) dominated by aromatic compounds such as benzoic acid, and a non-European type (Australia, Uruguay) characterized by a high abundance of terpenes. The Australian propolis exhibited a complex terpene profile rich in α-copaene and pinenes, while the Uruguayan sample was distinguished by an exceptionally high concentration of α-pinene. All active extracts showed selective, concentration-dependent inhibition against Gram-positive Staphylococcus aureus and Streptococcus mutans. The terpene-rich Australian propolis displayed the highest antibacterial potency, particularly against S. mutans. Crucially, Pearson correlation analysis revealed a counter-intuitive relationship: the most abundant terpenes in the non-European samples (e.g., α-pinene, verbenone) were significantly negatively correlated with antibacterial activity (r ≈ −0.99). Conversely, less abundant compounds, including linalool and acetic acid, were identified as strong positive predictors of inhibition (r > 0.90). These findings underscore a complex geography-chemotype-bioactivity relationship, where the overall synergistic effect of a mixed chemical profile, rather than the dominance of a single compound, determines antibacterial potency. The initially proposed markers provide a basis for origin-based standardization and highlight Australian propolis as a promising source of natural antibacterial agents. Full article

This study proposes a rapid method for identifying the geographical origin of Poria by combining Raman spectroscopy with an improved PCA algorithm—multi-matrix projection discrimination analysis. Poria samples from four Chinese provinces—Yunnan, Anhui, Shaanxi, and Hubei—were analyzed. Four datasets were constructed, each containing 25 Raman spectra per origin, with an additional 10 spectra per origin reserved as independent test sets. PCA was then separately applied to the spectral dataset of each origin to derive its respective eigenvector matrix. For each test spectrum, four reconstructed spectra were generated by projecting it onto the eigenvector matrices of the four origins. The origin was determined by identifying the one with the minimum Euclidean distance between the test spectrum and its reconstructions. When the first six principal components were used for model construction, the test set accuracy reached 97.5%, significantly outperforming the optimized PCA–SVM model, which achieved an accuracy of 85%. These results demonstrate that Raman spectroscopy, combined with the multi-matrix projection discrimination method based on PCA, can effectively capture the fingerprint information of Poria and accurately determine its geographical origin. Full article

(1) Background: Medicinal plants are widely used in folk medicine. Hypericum perforatum L. (St. John’s wort) is a medicinal plant that is used domestically and exported to other countries. This study addresses the need to develop methods for determining the composition and content of St. John’s wort to determine its biological activity. (2) Methods: High-performance liquid chromatography (HPLC) equipped with an Electrochemical Detector (ECD) and a Photodiode Array Detector (PDA) was employed to identify and quantify major phenolic compounds—gallic acid, catechin, epicatechin, hyperoside, quercetin, and hyperforin—in extracted and lyophilized St. John’s wort flower; stem; and leaf samples. Key analytes exhibited linear responses across both detection systems, within a quantification range of 0.5–10 µg/mL. (3) Results: The PDA method, validated according to ICH Q2(R1) guidelines, demonstrated specificity, linearity, precision, and accuracy, with limits of detection (LOD) ranging from 0.24 to 0.61 µg/mL and limits of quantification (LOQ) between 0.26 and 0.62 µg/mL. PDA effectively identified gallic acid, epicatechin, hyperoside, quercetin, and hyperforin, although catechin was not detected. ECD yielded comparable compound levels across the samples. (4) Conclusions: The novelty of this study lies in identifying the influence of climatic factors associated with the altitude at which St. John’s wort is grown on the content and ratio of biologically active components. Overall, the chemometric approach demonstrates the utility of raw chromatographic data in distinguishing samples by plant part and geographic origin; even when traditional compound-based comparisons may be limited. Full article

Background/Objectives: The effects of geographical origin, alongside age, diet, and drug treatments, on the gut microbiota have not been thoroughly analyzed in African countries. Furthermore, eukaryotic components, including Blastocystis, the most common intestinal protozoan worldwide, require further investigation. This study compares the gut microbiota of Italian subjects with that of two African groups to examine the influence of dietary patterns and the effects of Blastocystis presence and subtypes. Methods: Three cohorts of healthy subjects (Italians residing in Rome, Africans residing in the Côte d’Ivoire, and Africans living in Italy) were compared by sequencing the V3-V4 hypervariable regions of the 16S rDNA gene. Taxa abundance and associations with typical West African and Italian foods were determined using DESeq2. Co-abundant genera were identified with a weighted correlation network analysis (WGCNA). Blastocystis subtypes were determined and correlated with the microbial composition in the three groups. Results: Distinct microbial taxa were associated with specific foods, including palm oil, Cube Maggi, sunflower oil, and olive oil. A Mediterranean diet consumed for over two years did not alter the abundance of Faecalibacterium and Dorea in the Africans living in Italy compared with Africans living in Côte d’Ivoire, whereas differences were observed in the abundance of some Prevotella-9, Bacteroides, and Lachnospiraceae OTUs. Significant associations were identified between palm oil and Subdoligranulum, Cube Maggi and Dorea, sunflower oil and the Ruminococcus torques group, and olive oil and Faecalibacterium. Concerning Blastocystis, alpha and beta diversity analysis showed a significant separation between carriers and non-carriers. Conclusions: This study provides the first comparative analysis of gut microbiota composition between individuals from Côte d’Ivoire and Italians focusing on the influence of distinct dietary patterns. Full article

Verifying the geographical origin of honey is crucial for its market value and for preventing fraudulent practices. This study aimed to characterize the chemical profiles of organic honeys from three distinct regions in Southeastern Türkiye—Şırnak Faraşin, Siirt Merkez, and Siirt Pervari—to establish a robust method for geographical authentication. A total of 51 multifloral honey samples were analyzed. The concentrations of 20 free amino acids (FAAs) and 16 phenolic compounds were quantified using (UPLC-ESI-MS/MS). The resulting data were subjected to both an unsupervised (PCA, CA) and supervised (PLS-DA, RF, SVM) chemometric analysis to identify biochemical markers for each region. The results revealed a distinct chemical fingerprint for each region. Based on the FAA profiles, the PLS-DA method provided the best overall classification, achieving an excellent discrimination with a total accuracy of 94.1% in the Şırnak Faraşin honeys. For the phenolic compound profiles, the RF method achieved the highest correct classification rate for Şırnak Faraşin honeys at 88.2%. This study demonstrates that an integrated approach, combining FAA and phenolic profiles with supervised chemometric methods, provides a successful and reliable model for determining the geographical origin of these multifloral honeys. Full article

Background: Asthma is the most prevalent chronic illness in children worldwide, contributing to significant morbidity, health care utilization, and economic burden. In the United States, approximately five million children are affected by asthma. This review explores the environmental contexts and lifestyle determinants of pediatric asthma, with a focus on the Inland Empire (IE) region of Southern California. The IE’s unique geographic landscape and importance as a major transportation hub highlights its critical role for understanding how both environmental and structural factors exacerbate asthma burden within the pediatric population. Variables such as household income, parental education levels, and lack of community-based asthma programs were explored. Despite significant burdens, the IE remains under-represented in asthma research, contributing to persistent disparity. Methods: A narrative literature review and regional data analysis were conducted via PubMed, Scopus, and Google Scholar (2000–2025), alongside data from the CDC, CDPH, and American Lung Association. Key words used included “pediatric asthma, Inland Empire, air pollution, asthma disparity, emergency department utilization, socioeconomic status.” Inclusion criteria were: (1) studies or reports focusing on pediatric asthma (ages 0–17), (2) articles addressing environmental, socioeconomic, or health care-related risk factors, and (3) research with either national, state-level, or IE-specific data. Exclusion criteria were: (1) articles not in English, adult-only asthma studies, and (3) publications without original data or reference to pediatric asthma burden, management, or outcomes. Titles and abstracts were screened for relevance, and full texts were reviewed when abstracts met inclusion criteria. A total of 61 studies, reports, and data sources met this criterion and were included into this review. Results: The IE—comprised of San Bernardino (SB) and Riverside Counties— is home to four of the top five most polluted cities in North America. Vehicle emissions and industrial waste are concentrated in the region due to limited air circulation from surrounding mountains that entrap pollutants. Pediatric asthma ED visit rates in SB and Riverside were 60.5% and 59.3%, compared to California’s average of 56.7%. Hospitalization rates for children aged 0–4 were also higher in SB (24.4%) compared to the state average (17.3%). The elevated rates among school-aged children underscore the crucial need for interventions aimed at improving air quality, enhancing asthma management, and increasing access to preventive health care. Conclusions: Pediatric asthma in the IE reflects heightened environmental risks, socioeconomic barriers, and gaps in health care access. Addressing these disparities requires targeted interventions, policies, and region-specific research to enhance long-term management strategies and outcomes for vulnerable pediatric populations. Full article