Search Results (6,411)

Bingdao ancient tree tea (BATT), a type of raw Pu-erh tea, is renowned for its brewing durability, characterized by a unique aroma and flavor. To explore the dynamic changes in infusion quality and the impact of multiple steeping process, BATT was brewed 14 times, and its sensory attributes, infusion color, and chemical composition were assessed across different brewing intervals. The color of the tea infusion remained relatively stable throughout the brewing process. Sensory evaluation indicated that BATT exhibited optimal sensory quality between the third and seventh infusions. While the leaching of polyphenols showed minimal variation across brews, the concentrations of ester-catechins, non-ester catechins, free amino acids, and caffeine after the seventh brewing decreased by 28.82%, 21.83%, 28.86%, and 40.37%, respectively. Our results indicated that higher concentrations of flavor compounds in the BATT infusion appeared between the fourth and seventh brews. This study provides a theoretical basis for understanding the brewing characteristics of BATT. Full article

The aim of this paper is to analyze how young people in Slovakia perceive individual attributes of quality of life and to highlight the positive correlation with ethical values acquired primarily through family upbringing and, significantly, through the national education system. Quality of life is understood as a multidimensional concept encompassing opportunities, fulfillment of human needs, and subjective well-being, including dimensions such as happiness and life satisfaction. These aspects are strongly influenced by ethical values, which are particularly shaped by compulsory ethics or religious education provided to children aged 6–15 within the Slovak national curriculum. To explore the link between ethically grounded education and perceived quality of life among youth, a questionnaire-based survey was conducted. The findings reveal significant correlations between ethical or religious education and various quality of life indicators, emphasizing the importance of ethical education in shaping socially responsible and value-oriented young citizens. This study contributes to understanding the cultural and educational context influencing youth perceptions of quality of life in Slovakia. Full article

Honey is prized for its nutritional and healing properties, but its quality can be affected by contamination with toxic elements. This study evaluates the nutritional value and health risks of fifteen honey samples from different agro-climatic regions of Pakistan. Physicochemical properties such as color, pH, electrical conductivity, moisture, ash, and solids content were within acceptable ranges. ICP-OES analysis was used to assess six essential minerals and ten toxic metals. Except for slightly elevated boron levels (up to 0.18 mg/kg), all elements were within safe limits, with potassium reaching up to 1018 mg/kg. Human health risk assessments—including Average Daily Dose of Ingestion, Total Hazard Quotient, and Carcinogenic Risk—indicated no carcinogenic threats for adults or children, despite some elevated metal levels. Antioxidant activity, measured through total phenolic content (TPC) and DPPH radical scavenging assays, showed that darker honeys had stronger antioxidant properties. While the overall quality of honey samples was satisfactory, significant variations (p ≤ 0.05) were observed across different regions. These differences are attributed to diverse agro-climatic conditions and production sources. The findings highlight the need for continued monitoring to ensure honey safety and nutritional quality. Full article

Aroma is an important indicator for evaluating the quality of baijiu. In this study, we determined the aroma-active compounds in four representative brands of strong-aroma baijiu from Sichuan and Jianghuai regions through GC-MS/O, and GC-TOF-MS quantification. In addition, the non-volatile composition of four baijiu samples was quantified by BSTFA derivatization and GC-MS. By constructing a full recombination model containing both volatile and non-volatile components, the effect of different groups of non-volatile compounds on the aroma of strong-aroma baijiu was evaluated through recombination-omission tests. A total of 72 aroma-active compounds and 59 non-volatile compounds were identified and quantified. The results indicated that pyrazines, furfural, and furan derivatives displayed higher aroma intensities in strong-aroma baijiu produced in Sichuan compared to that produced in Jianghuai. The recombination model that included both aroma-active and non-volatile compounds showed a closer resemblance to the original baijiu samples, underscoring the critical role these compounds play in shaping the dominant aroma profile of strong-aroma baijiu. Non-volatile compounds significantly influenced six aroma attributes: fruity, sweet, sauce, pit, acidic, and alcoholic notes. Omission tests revealed that among posorly volatile organic acids, monobasic acids had distinct effects on the aroma profile, while dibasic acids did not show any noticeable influence on the sensory characteristics. Full article

Arugula leaves (Diplotaxis tenuifolia L. and Eruca sativa L.) are a must-have ingredient in ready-to-eat salads, as they are prized for their appearance, taste, and flavor. The nutraceutical properties of this leafy vegetable are attributed to the presence of valuable secondary metabolites, such as phenolic acids and glucosinolates. Using UHPLC-Q-Orbitrap HRMS analysis and ion chromatography, we characterized the content of phenolic acids, glucosinolates, nitrates, and organic acids in organic arugula [Diplotaxis tenuifolia (L.) DC] and evaluated how the foliar application of three different non-microbial biostimulants (a seaweed extract, a vegetable protein hydrolysate, and a tropical plant extract) modulated the expression of these. Although the application of vegetable protein hydrolysate increased, compared to control plants, the nitrate content, the application of the same biostimulant increased the total content of glucosinolates and phenolic acid derivatives by 5.2 and 17.2%. Specifically, the foliar application of the plant-based biostimulant hydrolyzed protein significantly increased the content of glucoerucin (+22.9%), glucocheirolin (+76.8%), and ferulic acid (+94.1%). The highest values of flavonoid derivatives (173.03 μg g⁻¹ dw) were recorded from plants subjected to the exogenous application of seaweed extract. The results obtained underscore how biostimulants, depending on their origin and composition, can be exploited not only to improve agronomic performance but also to enhance the nutraceutical content of vegetables, guaranteeing end consumers a product with premium quality characteristics. Full article

Cropland is a critical resource for safeguarding food security. Ensuring both the quantity and quality of cropland is essential for achieving zero hunger and promoting sustainable agriculture. However, whether urbanization-induced cropland loss poses a substantial threat to regional food security remains a key concern. This study examines the central region of the Yangtze River Delta (YRD) in China, integrating CLCD (China Land Cover Dataset) land use/cover data (2001–2023), MOD17A2H net primary productivity (NPP) data, and statistical records to evaluate the impacts of urban expansion on grain yield. The analysis focuses on three components: (1) grain yield loss due to cropland conversion, (2) compensatory yield from newly added cropland under the requisition–compensation policy, (3) yield increases from stable cropland driven by agricultural enhancement strategies. Using Sen’s slope analysis, the Mann–Kendall trend test, and hot/coldspot analysis, we revealed that urban expansion converted approximately 14,598 km² of cropland, leading to a grain production loss of around 3.49 million tons, primarily in the economically developed cities of Yancheng, Nantong, Suzhou, and Shanghai. Meanwhile, 8278 km² of new cropland was added through land reclamation, contributing only 1.43 million tons of grain—offsetting just 41% of the loss. In contrast, stable cropland (102,188 km²) contributed an increase of approximately 9.84 million tons, largely attributed to policy-driven productivity gains in areas such as Chuzhou, Hefei, and Ma’anshan. These findings suggest that while compensatory cropland alone is insufficient to mitigate the food security risks from urbanization, the combined strategy of “Safeguarding Grain in the Land and in Technology” can more than compensate for production losses. This study underscores the importance of optimizing land use policy, strengthening technological interventions, and promoting high-efficiency land management. It provides both theoretical insight and policy guidance for balancing urban development with regional food security and sustainable land use governance. Full article

Mayfly nymphs are reliable indicators of aquatic habitat quality, and whilst their presence and relative abundance are often used in bioassessment schemes, it is important to recognise that these attributes are affected by the sampling method employed. To test these effects, we sampled stream habitats for mayflies using two commonly used techniques in a standardised setup: aquatic sweep nets and manual collection from stones. These methods resulted in different success rates in detecting certain taxa depending on their biological traits (preferred microhabitat and locomotion type). Whilst species lists generally overlapped between the two methods, they yielded different values of total abundance, taxon richness, Shannon–Wiener’s diversity index, assemblage saprobic index, and general community structure. These results suggest that reliance on a single collection method is prone to yield only partial information for ecological assessments and emphasises the importance of employing a sampling technique that is appropriate for the study question and goals or combining more than one method. Based on these findings, we outline the scientific justifications for using each sampling method. Full article

Broccoli stalks are considered an agro-industrial by-product that, in the context of fresh consumption, is undervalued, as only broccoli florets are typically marketed. This study evaluated the up-cycling of broccoli stalks into a value-added fresh-cut product through postharvest preservation strategies. Stalks were peeled, cut into sticks (8 × 8 mm × 50–100 mm), sanitised, packaged under modified atmosphere conditions, and stored at 5 °C. Treatments included (a) calcium ascorbate (CaAsc, 1% w/v), (b) trehalose (TREH, 5% w/v), (c) hot water treatment (HWT, 55 °C, 1 min), and several combinations of them. HWT alone was highly effective in reducing browning, a key factor for achieving an extended shelf-life, controlling microbial growth and respiration, and obtaining the highest sensory scores (appearance = 7.3 on day 11). However, it was less effective in preserving bioactive compounds. The HWT + CaAsc treatment proved to be the most effective at optimising quality and retaining health-promoting compounds. It increased vitamin C retention by 78%, antioxidant capacity by 68%, and total phenolic content by 65% compared to the control on day 11. This synergistic effect was attributed to the antioxidant action of ascorbic acid in CaAsc. TREH alone showed no preservative effect, inducing browning, elevated respiration, and microbial proliferation. Overall, combining mild thermal and antioxidant treatments offers a promising strategy to valorise broccoli stalks as fresh-cut snacks. An 11-day shelf-life at 5 °C was achieved, with increased content of health-promoting bioactive compounds, while supporting circular economy principles and contributing to food loss mitigation. Full article

Cardiovascular diseases (CVDs) are the leading cause of global mortality, with type 2 diabetes mellitus (T2DM) and obesity significantly increasing the risk of CVD. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and dipeptidyl peptidase-4 inhibitors (DPP-4is) have gained attention for their potential cardioprotective effects. Therefore, this review aims to explore the molecular mechanisms underlying the cardiovascular benefits of these agents. A literature review was conducted searching PubMed databases from 1990 to January 2025, including research on the effects of GLP-1 RA and DPP-4i on cardiovascular health, specifically concerning atherosclerosis, coronary artery disease, vascular health, cardiac arrhythmias, myocardial infarction (MI), and heart failure, with a focus on the biochemical and molecular effects of these drugs. We analyzed 131 scientific publications, which indicate that GLP-1 RA and DPP-4i significantly reduce cardiovascular risk and major adverse cardiovascular events (MACEs), including atherosclerosis, myocardial infarction, and cardiac arrhythmias. These clinical outcomes are attributed to the mitigation of oxidative stress, inflammation, and endothelial dysfunction as well as improvement in mitochondrial function and lipid metabolism. GLP-1 RAs offer substantial cardiovascular benefits, making them valuable in managing T2DM and reducing CVD risk. Their integration into treatment regimens for CVD can reduce hospitalization rates, improve quality of life, and extend life expectancy. DPP-4is, while beneficial, are less effective in cardiovascular protection. Further research is needed to optimize therapeutic strategies and broaden the clinical application of these agents in cardiometabolic care. Full article

Clustering algorithms help handle unlabeled datasets. In large datasets, density-based clustering algorithms effectively capture the intricate structures and varied distributions that these datasets often exhibit. However, while these algorithms can adapt to large datasets by building clusters with arbitrary shapes by identifying low-density regions, they usually struggle to identify density variations. This paper proposes a Variable DEnsity Clustering Algorithm for Large datasets (VDECAL) to address this limitation. VDECAL introduces a large-dataset partitioning strategy that allows working with manageable subsets and prevents workload imbalance. Within each partition, relevant objects subsets characterized by attributes such as density, position, and overlap ratio are computed to identify both low-density regions and density variations, thereby facilitating the building of the clusters. Extensive experiments on diverse datasets show that VDECAL effectively detects density variations, improving clustering quality and runtime performance compared to state-of-the-art DBSCAN-based algorithms developed for clustering large datasets. Full article

Vegetation is a fundamental component of terrestrial ecosystems. Understanding how vegetation changes and what drives these evolutions is crucial for developing a high-quality ecological environment and addressing global climate change. Extensive evidence has shown that China has undergone substantial vegetation changes, characterized primarily by greening. To quantify vegetation dynamics in China and assess the contributions of various drivers, we explored the spatiotemporal variations in the kernel Normalized Difference Vegetation Index (kNDVI) from 2001 to 2020, and quantitatively separated the influences of climate and human factors. The kNDVI time series were generated from the MCD19A1 v061 dataset based on the Google Earth Engine (GEE) platform. We employed the Theil-Sen trend analysis, the Mann-Kendall test, and the Hurst index to analyze the historical patterns and future trajectories of kNDVI. Residual analysis was then applied to determine the relative contributions of climate change and human activities to vegetation dynamics across China. The results show that from 2001 to 2020, vegetation in China showed a fluctuating but predominantly increasing trend, with a significant annual kNDVI growth rate of 0.002. The significant greening pattern was observed in over 48% of vegetated areas, exhibiting a clear spatial gradient with lower increases in the northwest and higher amplitudes in the southeast. Moreover, more than 60% of vegetation areas are projected to experience a sustained increase in the future. Residual analysis reveals that climate change contributed 21.89% to vegetation changes, while human activities accounted for 78.11%, being the dominant drivers of vegetation variation. This finding is further supported by partial correlation analysis between kNDVI and temperature, precipitation, and the human footprint. Vegetation dynamics were found to respond more strongly to human influences than to climate drivers, underscoring the leading role of human activities. Further analysis of tree cover fraction and cropping intensity data indicates that the greening in forests and croplands is primarily attributable to large-scale afforestation efforts and improved agricultural management. Full article

Topological insulators (TIs) hold considerable promise for the advancement of optoelectronic technologies, including spectroscopy, imaging, and communication, owing to their remarkable optical and electrical characteristics. This study proposes a novel combination of Bi${}_2$Se${}_3$ TIs and ReSe${}_2$ for self-powered broadband photodetectors with high sensitivity and fast response time. The Bi${}_2$Se${}_3$/ReSe${}_2$ heterojunction photodetector achieves broadband response spectra ranging for 375 nm to 1 $\mathsf{\mu }$m. It demonstrates a significant responsivity of 64 mA/W at a wavelength of 600 nm (1 mW/cm${}^2$), exhibits a rapid response speed of 345 $\mathsf{\mu }$s rise/336 $\mathsf{\mu }$s fall time, and has a 3 dB bandwidth of 1.4 kHz under zero-bias conditions. The high performance can be attributed to the suitable energy band structure of Bi${}_2$Se${}_3$/ReSe${}_2$ and high carrier mobility in surface states of Bi${}_2$Se${}_3$. Excitingly, self-powered TIs photodetectors allow for high-quality signal transmission. The TIs employed in photodetectors can stimulate the production of new optoelectronic features, but they could also be used for highly integrated photonic circuits in the future. Full article

The objective of this study was to analyze the impact of solar and hybrid dryers on the physicochemical characteristics, fingerprints, and cognitive-sensory perceptions of Mexican consumers of traditional tostadas made with corn of different races. Corn tostadas from different native races were evaluated with solar and hybrid (solar-photovoltaic solar panels) dehydration methods. Proximal chemical quantification, instrumental analysis (color, texture), fingerprint by Fourier transform infrared spectroscopy (FTIR), and sensory-cognitive profile (emotions and memories) and its relationship with the level of pleasure were carried out. The data were evaluated using analysis of variance models, Cochran Q, and an external preference map (PREFMAP). The results showed that the drying method and corn race significantly (p < 0.05) affected only moisture content, lipids, carbohydrates, and water activity. Instrumental color was influenced by the corn race effect, and the dehydration type influenced the fracturability effect. FTIR fingerprinting results revealed that hybrid samples exhibited higher intensities, particularly associated with higher lime concentrations, indicating a greater exposure of glycosidic or protein structures. Race and dehydration type effects impacted the intensity of sensory attributes, emotions, and memories. PREFMAP vector model results revealed that consumers preferred tostadas from the Solar-Chiquito, Hybrid-Pepitilla, Hybrid-Cónico, and Hybrid-Chiquito races for their higher protein content, moisture, high fracturability, crunchiness, porousness, sweetness, doughy flavor, corn flavor, and burnt flavor, while images of these tostadas evoked positive emotions (tame, adventurous, free). In contrast, the Solar-Pepitilla tostada had a lower preference because it was perceived as sour and lime-flavored, and its tostada images evoked more negative emotions and memories (worried, accident, hurt, pain, wild) and fewer positive cognitive aspects (joyful, warm, rainy weather, summer, and interested). However, the tostadas of the Solar-Cónico race were the ones that were most rejected due to their high hardness and yellow to blue tones and for evoking negative emotions (nostalgic and bored). Full article

This paper presents a methodology for extracting and simulating arterial pulse waveform signals from Fabry–Perot interferometric measurements, emphasizing a practical approach for noninvasive cardiovascular assessment. A key novelty of this work is the presentation of a complete Python-based processing pipeline, which is made publicly available as open-source code on GitHub (git version 2.39.5). To the authors’ knowledge, no such repository for demodulating these specific interferometric signals to obtain a raw arterial pulse waveform previously existed. The proposed system utilizes accessible Python-based preprocessing steps, including outlier removal, Butterworth high-pass filtering, and min–max normalization, designed for robust signal quality even in settings with common physiological artifacts. Key features such as the rate of change, the Hilbert transform of the rate of change (envelope), and detected extrema guide the signal reconstruction, offering a computationally efficient pathway to reveal its periodic and phase-dependent dynamics. Visual analyses highlight amplitude variations and residual noise sources, primarily attributed to sensor bandwidth limitations and interpolation methods, considerations critical for real-world deployment. Despite these practical challenges, the reconstructed arterial pulse waveform signals provide valuable insights into arterial motion, with the methodology’s performance validated on measurements from three subjects against synchronized ECG recordings. This demonstrates the viability of Fabry–Perot sensors as a potentially cost-effective and readily implementable tool for noninvasive cardiovascular diagnostics. The results underscore the importance of precise yet practical signal processing techniques and pave the way for further improvements in interferometric sensing, bio-signal analysis, and their translation into clinical practice. Full article

Air pollution source tracing is vital for effective pollution prevention and control, yet traditional methods often require large amounts of manual data, have limited cross-regional generalizability, and present challenges in capturing complex pollutant interactions. This study introduces AirTrace-SA (Air Pollution Tracing for Source Attribution), a novel hybrid deep learning model designed for the accurate identification and quantification of air pollution sources. AirTrace-SA comprises three main components: a hierarchical feature extractor (HFE) that extracts multi-scale features from chemical components, a source association bridge (SAB) that links chemical features to pollution sources through a multi-step decision mechanism, and a source contribution quantifier (SCQ) based on the TabNet regressor for the precise prediction of source contributions. Evaluated on real air quality datasets from five cities (Lanzhou, Luoyang, Haikou, Urumqi, and Hangzhou), AirTrace-SA achieves an average $R^2$ of 0.88 (ranging from 0.84 to 0.94 across 10-fold cross-validation), an average mean absolute error ($MAE$) of 0.60 (ranging from 0.46 to 0.78 across five cities), and an average root mean square error ($RMSE$) of 1.06 (ranging from 0.51 to 1.62 across ten pollution sources). The model outperforms baseline models such as 1D CNN and LightGBM in terms of stability, accuracy, and cross-city generalization. Feature importance analysis identifies the main contributions of source categories, further improving interpretability. By reducing the reliance on labor-intensive data collection and providing scalable, high-precision source tracing, AirTrace-SA offers a powerful tool for environmental management that supports targeted emission reduction strategies and sustainable development. Full article