Search Results (723)

Background/Objectives: This study investigated the use of artificial intelligence (AI) to identify and match barefoot prints belonging to the same individual on soft and sandy soil substrates. Recognizing footprints on soil is challenging due to low contrast and variability in impressions. Methods: We introduce Deep Learning Footprint Identification Technology (DeepFIT), based on a modified You Only Look Once (YOLOv11s) algorithm, using three methods, namely, Bounding Box (BBox), 16 anatomical landmarks, and automatically segmented outlines (Auto-Seg). An Extra Small Detection Head (XSDH) was added to improve feature extraction at smaller scales and enhance generalization through multi-scale supervision, reducing overfitting to specific spatial patterns. Results: Forty adults (20 males, 20 females) participated, with 600 images per individual. As the number of individuals in model training increased, the BBox model’s accuracy declined, resulting in misclassification on the test set. The average performance accuracy across both substrates was 77% for BBox, 90% for segmented outlines, and 96% for anatomical landmarks. Conclusions: The landmark method was the most reliable for identifying and matching barefoot prints on both soft and sandy soils. This approach can assist forensic practitioners in linking suspects to crime scenes and reconstructing events from footprint evidence, providing a valuable tool for forensic investigations. Full article

To address rising global food demand, improving phosphorus (P) use efficiency in agriculture is crucial. Organic fertilizers and biochar are recognized for their potential to improve soil phosphorus availability and reduce environmental losses. However, the synergistic effects of their combined application on phosphorus retention and transformation have received insufficient attention. This study investigated the synergy between cow dung-derived biochar (produced at 400 °C and 700 °C) and organic fertilizer using P fractionation, leaching, and extraction tests. Results indicated that the H₂O-P content in organic fertilizer as high as 42.17 mg·g⁻¹, resulting in a cumulative leaching loss of up to 11.62 mg·g⁻¹. In contrast, biochar exhibited lower leaching due to more stable C–P compounds, as confirmed by X-ray photoelectron spectroscopy (XPS). When biochar and organic fertilizer were co-applied, complexation with Ca²⁺ on their surfaces reduced phosphorus leaching from the mixture by 83.69%. The formation of Ca₂P₂O₇ crystals, detected through X-ray diffraction (XRD), indicates a strong synergistic effect between biochar and organic fertilizer. Additionally, the porous structure of biochar adsorbed phosphorus from organic fertilizer, further inhibiting leaching losses. This synergy enhances P retention, offering an effective strategy to improve P use efficiency and support sustainable soil management. Full article

The Ulan Buh Desert represents a quintessential desert ecosystem in the arid northwest of China. As the key factor to maintain the stability of ecosystem, the chemical characteristics of groundwater and its water relationship with vegetation need to be further studied. Through field sampling, hydrochemical analysis, hydrogen and oxygen isotope testing and the Bayesian mixing model (MixSIAR), this study systematically analyzed the chemical characteristics of groundwater, spatial distribution and vegetation water sources in the study area. The results show that the groundwater is predominantly of the Cl⁻–SO₄²⁻ type, with total dissolved solids (TDS) ranging from 0.34 to 9.56 g/L (mean: 2.03 g/L), indicating medium to high salinity and significant spatial heterogeneity. These characteristics are jointly controlled by rock weathering, evaporative concentration, and ion exchange. Soil water isotopes exhibited vertical differentiation: the surface layer (0–20 cm) was significantly affected by evaporative fractionation (δD: −72‰ to −45‰; δ¹⁸O: −9.3‰ to −6.2‰), while deep soil water (60–80 cm) showed isotopic enrichment (δD: −29‰ to −58‰; δ¹⁸O: −6.8‰ to 0.9‰), closely matching groundwater isotopic signatures. Vegetation water use strategies demonstrated depth stratification: shallow-rooted plants such as Reaumuria soongorica and Kalidium foliatum relied primarily on shallow soil water (0–20 cm, >30% contribution), whereas deep-rooted plants such as Nitraria tangutorum and Ammopiptanthus mongolicus predominantly extracted water from the 40–80 cm soil layer (>30% contribution), with no direct dependence on groundwater. Full article

Compaction quality is a critical factor in ensuring the long-term performance of subgrade structures; however, traditional testing methods are limited by their destructive nature and delayed feedback. To address these shortcomings, this study proposes a dynamic identification method for subgrade compaction based on embedded attitude sensors. A customized sensor unit integrated with an inertial measurement module was embedded in soil samples to record triaxial acceleration and attitude angles during the compaction process. Signal processing techniques, including an improved wavelet-based denoising strategy, were employed to separate long-term compaction trends from transient impact disturbances. Attitude features such as cumulative angular change, angular velocity, root mean square values, and a comprehensive inclination index were extracted as predictive variables. Ridge regression, random forest, and XGBoost models were constructed to establish the mapping relationship between attitude features and compaction degree. Experimental results on clay, loam, and sand samples indicate that the yaw angle is most sensitive to vertical settlement, while pitch and roll angles provide complementary information on lateral and rotational behaviors. Comparative analysis of filtering methods shows that the transient masking interpolation (TMI) approach outperforms the traditional asymmetric wavelet thresholding (AWT) method in effectively preserving baseline trends. Among the regression models, XGBoost demonstrated the best predictive performance, achieving an R² exceeding 0.995 at high compaction levels. The proposed method has been experimentally demonstrated as a laboratory-scale proof of concept, showing strong potential for future real-time field application, offering a novel technological pathway for intelligent quality control in road construction. Full article

Enhanced Rock Weathering (ERW) is a promising carbon dioxide removal (CDR) strategy that accelerates mineral dissolution, sequestering atmospheric CO₂ while improving soil health. This study builds on prior applications of soil calcimetry by investigating its ability to resolve short-term carbonate fluxes and rainfall-modulated weathering dynamics in wollastonite-amended croplands. Conducted over a single growing season (May–October 2024) in temperate row-crop fields near Port Colborne, Ontario—characterized by fibric mesisol soils (Histosols, FAO-WRB)—this study tests whether calcimetry can distinguish between dissolution and precipitation phases and serve as a proxy for weathering flux within the upper soil horizon, under the assumption that rapid pedogenic carbonate cycling dominates alkalinity retention in this soil–mineral system. Monthly measurements of soil pH (Milli-Q and CaCl₂) and calcium carbonate equivalent (CCE) were conducted across 10 plots, totaling 180 composite samples. Results show significant alkalinization (p < 0.001), with average pH increases of ~+1.0 unit in both Milli-Q and CaCl₂ extracts over the timeline. In contrast, CCE values showed high spatiotemporal variability (−2.5 to +6.4%) without consistent seasonal trends. The calcimetry-derived weathering proxy, log (Σ ΔCCE/Δt), correlated positively with pH (r = 0.652), capturing net carbonate accumulation, while the kinetic dissolution rate model correlated strongly and negatively with pH (r ≈ −1), reflecting acid-promoted dissolution. This divergence confirms that the two metrics capture complementary stages of the weathering–precipitation continuum. Rainfall strongly modulated short-term carbonate formation, with cumulative precipitation over the previous 7–10 days enhancing formation rates up to a saturation point (~30 mm), beyond which additional rainfall yielded diminishing returns. In contrast, dissolution fluxes remained largely independent of rainfall. These results highlight calcimetry as a direct, scalable, and dynamic tool not only for monitoring solid-phase carbonate formation, but also for inferring carbonate migration and dissolution dynamics. In systems dominated by rapid pedogenic carbonate cycling, this approach captures the majority of alkalinity fluxes, offering a conservative yet comprehensive proxy for CO₂ sequestration. Full article

The evaluation of bioavailable forms of heavy metals in zones of anthropogenic pollution is the basis of ecological risk assessment. The characterization of the consequences of the operation of the Pechenganikel smelting plant was carried out using AAS and two methods of soil bioavailable forms of heavy metal extraction (3% nitric acid and ammonium acetate buffer with pH 4.8) along three directions from the plant, corresponding to the wind prevalence. Buffer extraction provided more significant correlations between Ni, Co, Cu, Pb, and Zn, compared to nitric acid application, indicating a negative correlation between soil Cu, Co, and the distance from the plant, while no significant correlations were recorded for nitric acid extracts. A higher significant correlation number arose between soil elements in buffer extracts along the N-E direction than the S-W one. In the former direction, the number of the mentioned correlations decreased according to the following sequence: Zn (6) > Cu (5) > Se and Co (4) > Ni and Fe (3); in nitric acid extract, only significant correlations of Cu, Zn, and Se with Co and Ni were recorded. Biocrust formation was revealed only along the N-E direction, characterized by unexpected high Se concentrations and intensive correlation between Zn and all the elements extracted by the buffer. Biocrust accumulated high levels of all the elements tested and showed antioxidant activity and polyphenol content significantly correlated with soil organic matter. The biocrust mineral content demonstrated a complex relationship with soil Fe, Cu (buffer extract), and Se, as well as Co and Zn (nitric acid extract). Application of linear mixed-effects modelling and transfer factor analysis indicate that biocrusts may serve as effective bioindicators of both absolute metal contamination and its bioavailable fractions. The results indicate the expediency of using both methods of soil extraction for assessing the ecological risk and soil–biocrust relationships. Full article

Currently, the potential environmental concerns around the world for polycyclic aromatic hydrocarbon carcinogenic (PAHCs) contamination as carcinogenic compounds in industrial soils (automobile industry) are rising day by day. At present, the technology of treating contaminated soils using photocatalysts is commonly used; however, this study tested photolysis and photocatalysis through ultraviolet light (306 nm) due to its high treatment efficiency. FeCl₃ (0.3, 0.4 M) was used as an iron catalyst for each treatment in the presence of H₂O₂ (10%, 20%) as an oxidizing agent. The impact of light treatment on soils that contained various concentrations of PAHCs like naphthalene (NAP), chrysene (CRY), benzo(a) pyrene (BaP), indeno (1,2,3-cd) pyrene (IND) was investigated. The QuEChERS method was used to extract PAHCs, and a gas chromatograph mass spectrometer (GCMSMS) was used to determine concentration. The concentrations of PAHCs were measured for soils at intervals of every 2 h after exposure to ultraviolet rays. The results showed a decrease in PAHCs concentrations with increased exposure to UV irradiation, as the initial values were 26.8 ng/g (NAP), 97 ng/g (CRY), 9.1 ng/g (BaP) and 9.7 ng/g (IND), which decreased to 2.17 ng/g (NAP), 3.14 ng/g (CRY), 0.33 ng/g (BaP) and 0.46 ng/g (IND) at 20, 40, 30 and 40 h of UV exposure; moreover, with an increase in concentration of the catalyst (0.4 M FeCl₃ with 20% H₂O₂), NAP, CRY, BaP and IND became undetectable at 8, 26, 14 and 20 h, respectively. It was concluded that a significant effect of ultraviolet rays on the photolysis of PAHCs, along with Photovoltaic at 306 nm wavelength, was observed while using FeCl₃ (0.4 M) combined with H₂O₂ (20%) produced better results in a shorter time compared to FeCl₃ (0.3 M) with H₂O₂ (10%). Full article

This research provides a comprehensive evaluation of the phytochemical composition, antioxidant potential, and biological properties of four plant species with longstanding use in ethnobotanical traditions: Calendula officinalis, Mentha × piperita, Urtica dioica, and Juglans regia. Plant extracts were obtained using a range of solvent systems and subsequently analyzed for their content of total polyphenols, flavonoids, and phenolic acids. Ultra-high-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS) enabled the accurate identification and quantification of major polyphenolic constituents. The antioxidant capacity was assessed through a series of in vitro assays, and elemental analysis was conducted to determine microelement content. To evaluate potential ecological implications, acute toxicity was tested using Daphnia magna, while phytotoxic effects were also examined. The results demonstrate pronounced antioxidant activity along with notable biocidal and soil-enhancing properties. These findings underscore the potential of such plant-based formulations as sustainable alternatives to conventional agrochemicals and highlight the relevance of integrating traditional botanical knowledge with modern strategies for enhancing soil quality, crop performance, and environmental sustainability. Full article

Marine actinomycetes constitute a vigorous source of bioactive compounds with potential anti-tumor activity. This study investigates the antitumor activity and classification of actinomycetes isolated from 32 marine soil samples collected across four seasons from Tyr City Beach, Lebanon. A total of 80 morphologically diverse isolates were recovered and characterized, with dominant genera including Streptomyces, Kocuria, and Micrococcus. Among these, three promising strains—Kocuria rosea, Micrococcus luteus, and Streptomyces longisporoflavus—were selected for further analysis. Crude extracts were tested against human colorectal adenocarcinoma (Caco-2) and human hepatocellular carcinoma (HepG-2) cancer cell lines using MTT and Western blot assays. At the highest concentration (8 µg/µL), the extracts reduced cell viability to 24–37% in Caco-2 and 12–25% in HepG-2. The IC₅₀ values ranged from 1.72 to 3.53 µg/µL, depending on the extract and cell line. Western blot analysis showed dose-dependent increases in the Bax/Bcl-2 ratio, with fold changes reaching 4.35 (Kocuria), 11.39 (Micrococcus), and 14.25 (Streptomyces) in HepG-2 cells. The p53 protein expression also increased significantly, with fold changes up to 7.79 in Caco-2 and 3.0 in HepG-2 cells. These results indicate that marine actinomycetes from the Lebanese coastline hold strong potential as a source of antitumor agents targeting apoptosis pathways. Full article

In response to water scarcity and low agricultural water-use efficiency in arid regions in Northwest China, this study conducted field experiments in Wuwei, Gansu Province, from 2023 to 2024. It aimed to develop a water stress diagnosis model for spring maize to provide a scientific basis for precision irrigation and water management. In this work, two irrigation methods—plastic film-mulched drip irrigation (FD, where drip lines are laid on the soil surface and covered with film) and plastic film-mulched shallow-buried drip irrigation (MD, where drip lines are buried 3–7 cm below the surface under film)—were tested under five irrigation gradients. Multispectral UAV remote sensing data were collected from key growth stages (i.e., the jointing stage, the tasseling stage, and the grain filling stage). Then, vegetation indices were extracted, and the leaf water content (LWC) was retrieved. LWC inversion models were established using Partial Least Squares Regression (PLSR), Random Forest (RF), and Support Vector Regression (SVR). Different irrigation treatments significantly affected LWC in spring maize, with higher LWC under sufficient water supply. In the correlation analysis, plant height (hc) showed the strongest correlation with LWC under both MD and FD treatments, with R² values of −0.87 and −0.82, respectively. Among the models tested, the RF model under the MD treatment achieved the highest prediction accuracy (training set: R² = 0.98, RMSE = 0.01; test set: R² = 0.88, RMSE = 0.02), which can be attributed to its ability to capture complex nonlinear relationships and reduce multicollinearity. This study can provide theoretical support and practical pathways for precision irrigation and integrated water–fertilizer regulation in smart agriculture, boasting significant potential for broader application of such models. Full article

This study investigated the isolation and formulation of a bacterial conditioner as a biostimulant for Triticum durum (durum wheat) under salinity stress. An Algerian alkaline–saline soil was sampled, characterized for its physical and chemical characteristics and its culturable and total microbial community (16S rRNA gene metabarcoding). Three bacterial strains showing high 16S rRNA gene similarity to Pseudomonas putida, Bacillus proteolyticus, and Niallia nealsonii were selected for their plant growth-promoting (PGP) traits under different salinity levels, including phosphate solubilisation (194 µg mL⁻¹), hormone production (e.g., gibberellin up to 56 µg mL⁻¹), and good levels of hydrocyanic acid, ammonia, and siderophores. N. nealsonii maintained high indole production under saline conditions, while B. proteolyticus displayed enhanced indole synthesis at higher salt concentrations. Siderophore production remained stable for P. putida and N. nealsonii, whereas for B. proteolyticus a complete inhibition was registered in the presence of salt stress. The consortium density and application were tested under controlled conditions using Medicago sativa as a model plant. The effective biostimulant formulation was tested on Triticum durum under greenhouse experiments. Bacterial inoculation significantly improved plant growth in the presence of salt stress. Root length increased by 91% at 250 mM NaCl. Shoot length was enhanced by 112% at 500 mM NaCl. Total chlorophyll content increased by 208% at 250 mM NaCl. The chlorophyll a/b ratio increased by 117% at 500 mM. Also, reduced amounts of plant extracts were necessary to scavenge 50% of radicals (−22% at 250 mM compared to the 0 mM control). Proline content increased by 20% at both 250 mM and 500 mM NaCl. These results demonstrate the potential of beneficial bacteria as biostimulants to mitigate salt stress and enhance plant yield in saline soils. Full article

Dioscorea nipponica is an important medicinal and edible plant in northern China, and its extract dioscin is an important raw material for the modern pharmaceutical industry. To investigate the key environmental factors influencing diosgenin accumulation in the rhizomes of D. nipponica and their action mechanism, we collected wild D. nipponica plants from 60 plots on Zhongtiao Mountain and analyzed the effects of environmental conditions on both plant growth and diosgenin synthesis. Additionally, physiological parameters of D. nipponica were investigated under different intervals of watering treatments: control (CK, 3 days), mild drought (MID, 5 days), moderate drought (MD, 8 days) and severe drought (SD, 10 days). The results showed that the water content of rhizome was the main factor affecting the diosgenin content, and soil nutrients, especially nitrogen, played an important role in the growth of D. nipponica. The results of a drought stress gradient test showed that diosgenin increased significantly under mild drought compared to the control, reaching 103.19 ± 2.63%. SD inhibited the growth of plants, and the indexes decreased by 10.08 ± 0.03–34.94 ± 5.60% compared with MID but increased the proliferation rate of rhizomes (83.33%), which is the reproductive strategy of D. nipponica when faced with drought stress. It provides a scientific basis for imitation of wild cultivation of D. nipponica. Full article

Starch extracted from the domestically cultivated Scala potato variety was explored as a renewable resource for the formulation of biodegradable thermoplastic starch (TPS)/polylactic acid (PLA) blends intended for environmentally friendly food packaging applications. The isolated starch underwent comprehensive physicochemical and structural characterization to assess its suitability for polymer processing. TPS derived from Scala starch was compounded with PLA, both with and without citric acid (CA) as a green compatibilizer to enhance phase compatibility. The resulting polymer blends were systematically analyzed using Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR–ATR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) to evaluate thermal and structural properties. Mechanical performance, water vapor permeability (WVP), water absorption (WA), and biodegradability in soil over 56 days were also assessed. The incorporation of citric acid improved phase miscibility, leading to enhanced structural uniformity, thermal stability, mechanical strength, and barrier efficiency. Bio-degradation tests confirmed the environmental compatibility of the developed blends. Overall, the results demonstrate the potential of Scala-based TPS/PLA systems, particularly those modified with citric acid, as viable candidates for sustainable food packaging, while highlighting the importance of further formulation optimization to balance functional and biodegradative performance. Full article

Ground-penetrating radar surveys on structures have a wide range of applications, and they are very useful in solving engineering problems: from detecting reinforcement, studying concrete characteristics, unfilled joints, analyzing brick elements, detecting water content in building bodies, and evaluating structural deformation. They generally pursued small investigation areas with measurements made in direct contact with target structures and for small depths. Detecting deep piles presents specific challenges, and surveys conducted from the ground level may be unsuccessful. To reach great depths, medium-low frequencies must be used, but this choice results in lower resolution. Furthermore, the pile signals may be masked when they are located beneath massive reinforced foundations, which act as an electromagnetic shield. Finally, GPR equipment looks for differences in the dielectric of the material, and the signals recorded by the GPR will be very weak when the differences in the physical properties of the investigated media are modest. From these weak signals, it is difficult to identify information on the differences in the subsurface media. In this paper, we are illustrating an exploration on plinth foundations, supported by drilled piles, submerged in soil, extensive, deep and uninformed. Pulse GPR prospecting was performed in common-offset and single-fold, bistatic configuration, exploiting the exposed faces of an excavation around the foundation. In addition, three velocity tests were conducted, including two in common mid-point and one in zero-offset transillumination, in order to explore the range of variation in relative dielectric permittivity in the investigated media. Thanks to the innovative survey on the excavation faces, it is possible to perform profiles perpendicular to the strike direction of the interface. The electromagnetic backscattering analysis approach allowed us to extract the weighted average frequency attribute section. In it, anomalies emerge in the presence of drilled piles with four piles with an estimated diameter of 80 cm. Full article

Photovoltaic (PV) systems are increasingly integral to global energy solutions, but their long-term reliability is challenged by various operational faults. In this article, we propose an advanced hybrid diagnostic framework combining a Deep Belief Network (DBN) for feature pattern extraction and a Light Gradient Boosting Machine (LightGBM) for classification to detect and diagnose PV panel faults. The proposed model is trained and validated on the QASP PV Fault Detection Dataset, a real-time SCADA-based dataset collected from 255 W panels at the Quaid-e-Azam Solar 100 MW Power Plant (QASP), Pakistan’s largest solar facility. The dataset encompasses seven classes: Healthy, Open Circuit, Photovoltaic Ground (PVG), Partial Shading, Busbar, Soiling, and Hotspot Faults. The DBN captures complex non-linear relationships in SCADA parameters such as DC voltage, DC current, irradiance, inverter power, module temperature, and performance ratio, while LightGBM ensures high accuracy in classifying fault types. The proposed model is trained and evaluated on a real-world SCADA-based dataset comprising 139,295 samples, with a 70:30 split for training and testing, ensuring robust generalization across diverse PV fault conditions. Experimental results demonstrate the robustness and generalization capabilities of the proposed hybrid (DBN–LightGBM) model, outperforming conventional machine learning methods and showing an accuracy of 98.21% classification accuracy, 98.0% macro-F1 score, and significantly reduced training time compared to Transformer and CNN-LSTM baselines. This study contributes to a reliable and scalable AI-driven solution for real-time PV fault monitoring, offering practical implications for large-scale solar plant maintenance and operational efficiency. Full article