Search Results (14,996)

Background/Objectives: The laser beam absorption and thermal relaxation time (TRT) in oral tissues are key to optimizing treatment parameters. The aim of this study is to (1) evaluate, in an ex vivo study, the percentage of attenuation and transmittance of each wavelength as a function of tissue thickness; (2) determine the global absorption coefficient, α, of pig gingival tissue for the most commonly used wavelengths in dentistry; (3) calculate the thermal relaxation time (TRT) of oral tissue for these wavelengths; and (4) determine their corresponding penetration depths. Methods: We measured the transmission of different laser wavelengths through pig oral gingival tissues (Mandibular labial gingiva). We placed each tissue sample between two glass slides with minimal light attenuation. The input and output powers were measured after irradiating the tissue at different specific wavelengths: 450 nm, 480 nm, 532 nm, 632 nm, 810 nm, 940 and 980 nm, 1064 nm, 1341, 2780 nm and 2940 nm. After calculating the transmittance values, we plotted transmittance curves for each wavelength. Using the Beer–Lambert law, we then calculated the absorption coefficient (α) of each wavelength in the oral gingival tissue. Absorption coefficients were then used to calculate the TRT and penetration depth for each wavelength. Results: Among the tested wavelengths, 810 nm exhibited the lowest absorption in ex vivo porcine gingival tissue (α = 9.60 cm⁻¹). The 450 nm blue laser showed moderate absorption (α = 26.8 cm⁻¹), while the Er:YAG laser at 2940 nm demonstrated the highest absorption (α = 144.8 cm⁻¹). We ranked the wavelengths from most absorbed to least absorbed by porcine oral gingival mucosa as follows: 2940 nm > 2780 nm > 450 nm > 480 nm > 532 nm > 1341 nm > 632 nm > 940 nm > 980 nm > 1064 nm > 810 nm. Conclusions: Absorption and the TRT vary significantly across wavelengths. Erbium lasers are characterized by the highest absorption and minimal light penetration. Infrared diodes, particularly the 810 nm wavelength, showed the lowest absorption and deepest tissue penetration and exhibited the highest thermal relaxation time. The 480 nm laser demonstrated greater absorption by porcine gingival tissue compared to the 532 nm laser. These findings provide evidence-based guidance for wavelength selection in dental treatments and photobiomodulation, enabling improved precision, safety, and therapeutic efficacy in clinical practice. Full article

Sacha inchi (Plukenetia volubilis) is a high-value crop due to its high content of omega-3 fatty acids and its outstanding nutritional, pharmaceutical, and cosmetic properties. However, this species faces challenges from diseases, particularly root rot. In this study, we identified one of the causal agents of root rot in sacha inchi using morphological observations, molecular methods, and pathogenicity tests. The pathogen was isolated from root tissues showing symptoms of Fusarium infection, observed in a plot in the Picota province. Morphological identification, DNA sequencing, and phylogenetic analysis using the ITS and TEF-1α markers revealed that the isolate causing root rot was Fusarium suttonianum (FSSC 20). Analysis of the PQ636870 (ITS) and PQ639345 (TEF-1α) sequences in the NCBI database, together with phylogenetic analysis, revealed 99.58% and 99.51% similarity with the ITS and TEF sequences, respectively, corresponding to F. suttonianum. Pathogenicity tests confirmed that this species induced the same symptoms observed in the field, fulfilling Koch’s postulates. This study represents the first report of F. suttonianum as a pathogen causing root rot in sacha inchi in Peru. This finding is critical for developing effective strategies for disease management and control, contributing to the sustainability and improvement of sacha inchi production in the region. Full article

Land disputes pose a severe challenge for many developing countries worldwide. Understanding the driving factors of land disputes is crucial for social stability and sustainable development. China is one of the countries with the most severe situations of land disputes. This paper evaluates the land dispute intensity (LDI) across 30 provinces in China from 2011 to 2022. Using the GBDT model and interpretability methods, this study reexamines the importance of multidimensional variables in LDI, while also uncovering their nonlinear and interaction effects. The results show that LDI across 30 provinces generally and continuously increased after 2014, with this trend being notably curbed after 2019. In terms of the driving factors of LDI, the number of specialized farmers’ cooperatives plays the most critical role (mean |SHAP value| = 0.4). Variables such as share of primary industry, coverage of land transfer service centers, and agricultural product price index also exert a stronger influence on LDI. Clear nonlinear effects on LDI are observed for the agricultural product price index, the number of specialized farmers’ cooperatives, and the mediation rate of non-litigation disputes. In terms of interaction effects, when the mediation rate of non-litigation disputes is lower than 0.9, increases in the number of specialized farmers’ cooperatives and coverage of land transfer service centers tend to enhance their influence on raising LDI. When the ratio of cultivated land transfer is below 0.3, an increase in coverage of land transfer service centers is associated with a stronger effect in reducing LDI. Overall, this study uses the GBDT model, Shapley additive explanation (SHAP), and partial dependency plots (PDPs) to identify the main driving factors of land disputes. This paper can provide valuable references for developing countries and regions worldwide in addressing land disputes and conflicts. Full article

Background/Objectives: Gout, a complex metabolic disorder of increasing global incidence, remains incompletely understood in its pathogenesis. Current diagnostic approaches exhibit significant limitations, including insufficient specificity and the requirement for invasive joint aspiration, highlighting the need for non-invasive, sensitive biomarkers for early detection. Methods: Urine metabolites were extracted from 28 healthy controls, 13 asymptomatic hyperuricemia (HUA) patients, and 29 acute gouty arthritis (AGA) patients. The extracted metabolites were analyzed by UHPLC-MS/MS for untargeted metabolomics. Differential metabolites were screened by partial least squares discriminant analysis (PLS-DA) and volcano plot analysis. Pathway analysis determined the core disorder pathway of gout progression. Results: A total of 278 differential metabolites associated with gout progression were identified. The most pronounced metabolic alterations were observed between the AGA and control groups, indicative of substantial metabolic reprogramming during disease transition. Metabolic pathway analysis revealed four significantly dysregulated pathways: histidine metabolism, nicotinate and nicotinamide metabolism, phenylalanine metabolism, and tyrosine metabolism. Receiver operating characteristic (ROC) curve analysis revealed that three urine markers with high diagnostic efficacy—oxoamide, 3-methylindole, and palmitic acid—exhibited progressive alterations across the disease continuum. Conclusions: This metabolomics study identified core regulatory metabolites and newly discovered metabolic pathways underlying gout pathogenesis, along with novel urinary biomarkers capable of predicting HUA-to-AGA progression. The aberrant levels of key metabolites in the disordered pathway implicate neuroimmune dysregulation, energy metabolism disruption, and oxidative stress in gout pathogenesis. These findings provide new foundations and strategies for the daily monitoring and prevention of gout. Full article

To study the adsorption of lanthanide (Ln) atoms on graphene containing a Stone–Wales defect, we used a cluster model (SWG) and performed calculations at the PBE-D2/DNP level of the density functional theory. Our previous study, where the above combination was complemented with the ECP pseudopotentials, was only partially successful due to the impossibility of calculating terbium-containing systems and a serious error found for the SWG complex with dysprosium. In the present study we employed the DSPP pseudopotentials and completely eliminated the latter two failures. We analyzed the optimized geometries of the full series of fifteen SWG + Ln complexes, along with their formation energies and electronic parameters, such as frontier orbital energies, atomic charges, and spins. In many regards, the two series of calculations show qualitatively similar features, such as roughly M-shaped curves of the adsorption energies and trends in the changes in charge and spin of the adsorbed Ln atoms, as well as the spin density plots. However, the quantitative results can differ significantly. For most characteristics we found no evident correlation with the lanthanide contraction. The only dataset where this phenomenon apparently manifests itself (albeit to a limited and irregular degree) is the changes in the closest Ln^…C approaches. Full article

Background: Chemokines play a pivotal role in the progression of osteoarthritis (OA), but their exact mechanisms remain unclear. This study aimed to identify potential chemokine-associated biomarkers and investigate their causal relationships with OA. Methods: Transcriptome and genome-wide association study (GWAS) data were obtained from public databases, while chemokine-related genes (CRGs) were sourced from the literature. Initially, CRGs were expanded, followed by Mendelian randomization (MR) analysis, differential expression analysis, machine learning, and receiver operating characteristic (ROC) curve plotting to identify potential biomarkers. The causal relationships between these biomarkers and OA, as well as their biological functions, were further explored. Results: Fourteen candidate genes were identified for machine learning analysis, with DDIT3, CEBPB, CX3CR1, and ARHGAP25 emerging as feature genes. CEBPB and CX3CR1, which exhibited AUCs > 0.7 in the GSE55235 and GSE55457 datasets, were selected as potential biomarkers. Notably, CEBPB expression was lower, while CX3CR1 expression was elevated in the case group. Furthermore, both genes were co-enriched in spliceosome, lysosome, and cell adhesion molecule pathways. MR analysis confirmed that CEBPB and CX3CR1 were causally linked to OA and acted as protective factors (IVW model for CEBPB: OR = 0.9051, p = 0.0001; IVW model for CX3CR1: OR = 0.8141, p = 0.0282). Conclusions: CEBPB and CX3CR1 were identified as potential chemokine-related biomarkers, offering insights into OA and suggesting new avenues for further investigation. Full article

Effective nutrient management in grassland ecosystems is essential for maintaining soil nutrient balance and ensuring high forage productivity. A field experiment was conducted between 2022 and 2024 on a permanent dry meadow at the Experimental Station in Poznań-Strzeszyn, western Poland. The trial, established in autumn 2021, was carried out under production conditions on large plots (140 m² each). Plots were assigned to different fertilisation regimes, varying in both type and dosage. The treatments included an unfertilised control, three levels of annual mineral NPK fertilisation (NPK1, NPK2, NPK3), three levels of annually applied farmyard manure (FYM1, FYM2, FYM3), and three levels of mineral and organic fertilisers applied every two years (NPK1/FYM1, NPK2/FYM2, NPK3/FYM3). Throughout the study, botanical composition, annual dry matter yield (DMY), nitrogen (N), phosphorus (P), and potassium (K) content in the plant biomass were assessed. A simplified nutrient balance was calculated based on nutrient input from fertilisers and nutrient output with harvested yield. The average N balance across three years ranged from −12.17 kg N ha⁻¹ in control to +20.6 kg N ha⁻¹ in FYM3. For phosphorus, average balances ranged from −7.2 kg P ha⁻¹ in the control to +9.8 kg P ha⁻¹ in FYM3. In contrast, potassium balances were mostly negative: from −51.7 kg K ha⁻¹ in FYM1 to −7.4 kg K ha⁻¹ in NPK1. The most balanced nutrient budgets were observed under alternate NPK/FYM fertilisation, with moderate surpluses of N and P and a smaller K deficit compared to FYM applied alone. In contrast, inorganic and organic fertilisation applied separately resulted in greater nutrient surpluses or a pronounced potassium deficit. This study emphasises the importance of balanced nutrient management in permanent meadows, showing that moderate fertilisation strategies, such as alternating FYM and mineral NPK, can maintain productivity, and reduce environmental impacts. These findings provide a practical basis for developing sustainable grassland management practices under variable climatic conditions. Full article

China aims to reduce carbon emissions but faces challenges from small-scale farmer operations. Previous studies have predominantly examined carbon density using macro-level data. This study employs a primary field survey involving 916 rice farmers, along with input–output data from their typical paddy plots, to calculate micro-level carbon emissions and assess the impact of land operation scale. The results indicate that operational scale enhances carbon emission productivity and has a nonlinear relationship with carbon emission intensity. From survey data, the carbon emission intensity of late rice is 4648.77 kg CO_2eq·ha⁻¹ in Guangdong province China, which differs by a mere 1.14% from the figure derived from yearbook macro data. The yield carbon emission productivity and yield value carbon emission productivity of rice production are 1.347 kg·kg CO_2eq⁻¹ and 2.166 CNY·kg CO_2eq⁻¹, respectively. The operational scale significantly positively enhances indirect carbon emission productivity, a key indicator of economic growth and environmental sustainability. However, it exhibits a U-shaped effect on carbon emission intensity. Our results underscore the critical role of expanding the operational scale among individual farmers to boost carbon emission productivity, facilitating the simultaneous development of grain crops and a reduction in carbon emissions. Full article

Most ash trees (Fraxinus excelsior) in Germany are infected with Hymenoscyphus fraxineus, the causative agent of ash dieback (ADB). This study investigates the phenolic content of ash leaves to evaluate their potential as indicators for monitoring ADB and to assess how this potential is affected by site and year. Fresh leaf samples were collected and immediately frozen from 14 forest plots across Germany over a period of up to four years. Phenolic compounds were quantified using both photometric assays and HPLC. The results reveal strong site-specific differences in both total phenolic content and individual phenolic profiles. Temporal differences between sampling years were less pronounced, but were frequently significant. In contrast, crown condition—a key indicator of ADB damage—had only a weak effect on phenolic content. This suggests that mature ash trees do not exhibit a clear phenol-based defence response to H. fraxineus under field conditions. Our findings underscore the complexity of phenolic dynamics in natural stands and demonstrate that no robust of phenolic biomarker for ADB could be identified in mature trees. Full article

Maize (Zea mays L.) is a key global cereal crop with significant relevance to food security. Maize yield prediction is challenged by cultivar diversity and varying management practices. This preliminary study was conducted at Youyi Farm, Heilongjiang Province, China. Three maize cultivars (Songyu 438, Dika 1220, Dika 2188), two fertilization rates (700 and 800 kg·ha⁻¹), and three planting densities (70,000, 75,000, and 80,000 plants·ha⁻¹) were evaluated across 18 distinct cropping treatments. During the V6 (Vegetative 6-leaf stage), VT (Tasseling stage), R3 (Milk stage), and R6 (Physiological maturity) growth stages of maize, multi-temporal canopy spectral images were acquired using an unmanned aerial vehicle (UAV) equipped with a multispectral sensor. In situ measurements of key agronomic traits, including plant height (PH), stem diameter (SD), leaf area index (LAI), and relative chlorophyll content (SPAD), were conducted. The optimal vegetation indices (VIs) and agronomic traits were selected for developing a maize yield prediction model using the random forest (RF) algorithm. Results showed the following: (1) Vegetation indices derived from the red-edge band, particularly the normalized difference red-edge index (NDRE), exhibited a strong correlation with maize yield (R = 0.664), especially during the tasseling to milk ripening stage; (2) The integration of LAI and SPAD with NDRE improved model performance, achieving an R² of 0.69—an increase of 23.2% compared to models based solely on VIs; (3) Incorporating SPAD values from middle-canopy leaves during the milk ripening stage further enhanced prediction accuracy (R² = 0.74, RMSE = 0.88 t·ha⁻¹), highlighting the value of vertical-scale physiological parameters in yield modeling. This study not only furnishes critical technical support for the application of UAV-based remote sensing in precision agriculture at the field-plot scale, but also charts a clear direction for the synergistic optimization of multi-dimensional agronomic traits and spectral features. Full article

In this study, a new approach was developed for the estimation of optimum parameters (ODP), in terms of materials and design in livestock barns, and for optimal design. For this purpose, two thousand simulations were run using Monte Carlo (MC) techniques and Latin hypercube methods using the Energy Plus program on a 50-head closed dairy farm. In this study, the heat balance in the barn was adapted to Energy Plus using an innovative approach, using heat balance equations according to the ASHRAE Standard. First, data normality was determined using the Shapiro–Wilk (SW) and Kolmogorov–Smirnov (KS) tests. Data on thermal stress duration and energy consumption for dairy cattle welfare were estimated directly from the simulations, and sensitivity (SA) and uncertainty (UA) analyses were conducted. Furthermore, the statistical relationship between thermal comfort and energy consumption was determined using Pearson correlation. The predicted values obtained from the simulations were validated with barn values, and time-series overlay plots and histograms were generated. Furthermore, interpretations of the validation processes were made based on MBE, RSME, and R² statistical values. The study estimated an indoor thermal comfort temperature of 12 °C, and this value was taken into account in the innovatively developed simulations. The estimated optimum design parameters in the study resulted in energy reductions of 25% and 41% for walls and roofs, 48% and 19% for cooling and heating setpoint temperatures, 43% and 37% for window areas, and 75% and 40% for natural and mechanical ventilation, respectively. When the design parameters were evaluated holistically and analyzed in terms of average values, the new simulation model achieved approximately 50% energy savings. We believe that the newly developed approach will guide future planning for countries, the public, and private sectors to ensure animal welfare and reduce energy consumption. Full article

The harmonized multi-sensor satellite data assists users by providing seamless analysis-ready data with enhanced temporal resolution. The Harmonized Landsat Sentinel (HLS) product has gained popularity due to the seamless integration of Landsat OLI and Sentinel-2 MSI, achieving a temporal resolution of 2.8 to 3.5 days. However, applications that require monitoring intervals of less than three days or cloudy data can limit the usage of HLS data. Gaofen-1 (GF-1) Wide Field of View (WFV) data provides the capacity further to enhance the data availability by harmonization with HLS. In this study, GF-1/WFV data is harmonized with HLS by employing deep learning-based conditional Generative Adversarial Networks (cGANs). The harmonized WFV data with HLS provides an average temporal resolution of 1.5 days (ranging from 1.2 to 1.7 days), whereas the temporal resolution of HLS varies from 2.8 to 3.5 days. This enhanced temporal resolution will benefit applications that require frequent monitoring. Various processes are employed in HLS to achieve seamless products from the Operational Land Imager (OLI) and Multispectral Imager (MSI). This study applies 6S atmospheric correction to obtain GF-1/WFV surface reflectance data, employs MFC cloud masking, resamples the data to 30 m, and performs geographical correction using AROP relative to HLS data, to align preprocessing with HLS workflows. Harmonization is achieved without using BRDF normalization and bandpass adjustment like in the HLS workflows; instead, cGAN learns cross-sensor reflectance mapping by utilizing a U-Net generator and a patchGAN discriminator. The harmonized GF-1/WFV data were compared to the reference HLS data using various quality indices, including SSIM, MBE, and RMSD, across 126 cloud-free validation tiles covering various land covers and seasons. Band-wise scatter plots, histograms, and visual image color quality were compared. All these indices, including the Sobel filter, histograms, and visual comparisons, indicated that the proposed method has effectively reduced the spectral discrepancies between the GF-1/WFV and HLS data. Full article

Seed-sown wildflower meadows are becoming increasingly important in our cities. One of the best methods is to design low-maintenance green spaces with an ecological approach. They can be used either to create perennial beds or to enrich and replace larger areas of regularly mown grass. Seeded surfaces are closer to a functioning ecosystem. The seed mixtures available in Hungary include seeds of native and non-native species, but due to a lack of time or resources, they have not been tested and have been in the field almost immediately. With our research, launched in autumn 2023, we tried to fill this gap and established seed-sown perennial beds in Budapest (Hungary), in ten plots in different media, using a seed mix of native species (96 taxa). Our experiment is an attempt to answer the question of what makes a seed-sown herbaceous plantation successful in the long term in an urban environment. Which species will emerge first, in which medium and which will persist in the long term? What will be the cover, diversity of the plots, the phenology of each species at different times of the year and to what extent does this depend on the medium and the frequency of irrigation? Which taxa will appear in each growing medium, and will there be taxa that can only develop in certain media? The study reports on the first experiences of the long-term study, according to which there were dynamically developing stands, but we observed a basically negative correlation between rapidly developing media and diversity. The most diverse species set was provided by the andesite aggregate medium, followed by green roof substrate, then demolition rubble with sand and sand. Full article

This study investigates the effects of Bisphenol A (BPA)—a ubiquitous endocrine disruptor—on the swimming behavior of the rotifer Brachionus plicatilis. Across a 0–40 ppm gradient, a biphasic response was observed, with swimming speed peaking at 20 ppm (100.42 ± 12.17 µm/s) and then significantly declining by 43% to 57.58 ± 30.59 µm/s at 40 ppm (Tukey, p < 0.05). Speed–frequency plots revealed co-existing hyper- and hypoactive sub-populations at 10–30 ppm, whereas severe inhibition dominated at 40 ppm. Additionally, temporal analysis confirmed that BPA effects were both concentration- and time-dependent, with the mean speed at 10 ppm declining only slightly over time (slope ≈ −0.8), whereas at 40 ppm, the decrease was an order of magnitude steeper (slope ≈ −16.9). Additionally, BPA exposure also triggered a sharp rise in abrupt turns (582.53 ± 477.55 events) and greater path sinuosity, consistent with neuromuscular disturbance. These findings demonstrate that rotifer locomotion provides an early and sensitive indicator of environmental BPA exposure. Full article

This work investigates the effect of interface traps on the impedance spectra of dopant-free silicon solar cells. The studied device consists of a crystalline silicon absorber with an a-Si:H/MoOx/ITO stack as the front passivating hole-collecting contact and an a-Si:H/LiF/Al stack as the rear passivating electron-collecting contact. Experimental measurements, including illuminated current–voltage (I–V) characteristics and impedance spectroscopy, were performed on the fabricated devices and after a soft annealing treatment. The annealed cells exhibit an increased open-circuit voltage and a larger Nyquist plot radius. To interpret these results, a numerical model was developed in a TCAD environment. Simulations reveal that traps located at the p/i interface (MoOx/i-a-Si:H) significantly affect the impedance spectra, with higher trap concentrations leading to smaller Nyquist plot circumferences. The numerical impedance curves were aligned to the experimental data, enabling extraction of the interfacial traps concentration. The results highlight the sensitivity of impedance spectroscopy to interfacial quality and confirm that the performance improvement after soft annealing is primarily due to reduced defect density at the MoOx/i-a-Si:H interface. Full article