Search Results (601)

Manganese (Mn) is an essential micronutrient required for plant growth, photosynthesis and metabolic regulation. Its importance is related to the involvement in several metabolic processes that ensure proper cellular function and balanced plant development throughout the production cycle. In plants, Mn is absorbed predominantly as Mn²⁺, and its availability is strongly influenced by soil pH, aeration, and other mineral nutrients in the soil solution. After uptake by roots, Mn is translocated to the shoot, accumulating primarily in metabolically active organs such as stems, young leaves and flowers. Although Mn exhibits limited mobility in the phloem, adequate concentrations are necessary to sustain both vegetative development and reproductive growth. Adequate Mn concentration is directly reflected in fruit development, as well-nourished plants show improved flowering, greater assimilate translocation capacity, and better fruit filling, thereby positively influencing yield and quality. However, Mn deficiency is common in alkaline soils or soils with high organic matter, causing interveinal chlorosis in young leaves, reduced growth, and lower biomass production. Under prolonged conditions, deficiency leads to less vigorous plants with reduced metabolic efficiency. Conversely, Mn toxicity, typically associated with acidic and poorly drained soils, restricts root development and induces nutritional imbalances with other elements, such as calcium, magnesium, and iron. Therefore, proper Mn management is essential to ensure nutritional balance and optimal performance of agricultural crops. Overall, this review synthesizes advances in Mn transport, cellular compartmentalization, and metabolic regulation, emphasizing how Mn interacts with other mineral nutrients to influence plant physiology. Attention is given to the integration of Mn with redox networks, photosynthetic regulation, and reproductive development. By linking transport mechanisms with physiological outcomes, this review identifies key patterns governing Mn homeostasis and highlights implications for crop nutrition and sustainable nutrient management. Full article

While early ideal consolidation theories for vertical drains focused primarily on radial flow, numerous coupled radial–vertical seepage models have since been developed to better capture complex flow behavior in practice. To overcome this limitation, a nonlinear large-strain consolidation model for vertical drains with coupled radial-vertical flow is proposed, explicitly incorporating Hansbo’s non-Darcy flow, smear effects, and soil nonlinearity. The finite difference method is then employed to obtain numerical solutions, and the reliability of the proposed numerical scheme is verified by degenerating the model to the radial consolidation case and comparing the results with the corresponding analytical solution. The results indicate that consolidation develops fastest when the permeability coefficient within the smear zone follows a parabolic distribution. Increasing the Hansbo’s flow parameter m and threshold hydraulic gradient parameter I₁ markedly slows down the consolidation process, while the contribution of vertical flow is primarily confined to the early stage. In addition, larger soil nonlinearity parameters I_c and α amplify the influence of radial–vertical coupled flow. Parametric analysis further shows that when the ratio of soil layer thickness to the radius of the influence zone (H/r_e) exceeds 10, the effect of vertical flow becomes negligible, and the consolidation behavior can be reasonably approximated using a radial-flow-only model. Full article

European peatlands have been extensively drained for agriculture, resulting in substantial carbon losses and widespread soil degradation. Peatland restoration is therefore a global priority, with rewetting recognised as a key strategy for mitigating greenhouse gas emissions and climate change. This review synthesizes current knowledge on soil transformations following the rewetting of agriculturally drained peatlands in Europe. We describe major degradation processes induced by drainage, including land subsidence, organic matter oxidation, and microbial community shifts from anaerobic to aerobic conditions. We then examine key rewetting approaches—ditch blocking, controlled flooding, and paludiculture—and their intended restoration outcomes. Rewetting fundamentally alters soil physical, chemical, and biological properties by raising and stabilizing water tables, restoring anoxic conditions, and modifying nutrient cycling and microbial processes. Findings indicate long-term stabilization of organic carbon in peat soils under anaerobic conditions, but also reveal trade-offs between reduced CO₂ emissions and increased CH₄ and N₂O fluxes. Vegetation–soil interactions strongly influence recovery trajectories, and paludiculture offers potential to align agricultural land use with climate mitigation objectives. Finally, we evaluate current research methodologies and identify major knowledge gaps, including limited long-term data and insufficient integration of hydrological, chemical, and biological processes. We highlight priorities for future research to support evidence-based rewetting strategies that deliver climate benefits while maintaining ecological and economic sustainability in European peatlands. Full article

The Prespa Lakes system, shared between Greece, the Republic of North Macedonia, and Albania, forms a significant transboundary, large-scale integrated freshwater ecosystem subject to multiple anthropogenic and natural pressures. This study focuses on the Greek part of the Prespa Lakes system with particular emphasis on the identification of the ecological and hydrological impacts of the contributing stream inflows on the lakes by examining the spatial variability in physicochemical and biological conditions and conducting water balance and isotopic analyses. Based on our results, streams draining into Lesser Prespa Lake exhibited more pronounced hydrological and physicochemical fluctuations than the Agios Germanos River connected to Great Prespa Lake, while ecological status classifications of all studied streams ranged from high to moderate. Furthermore, moderate ecological status conditions (mainly observed at the downstream stations) were closely associated with adjacent anthropogenic pressures, including agricultural drainage, livestock activities, irrigated croplands, and wastewater discharges. In addition, although both lakes were classified as mesotrophic, field data indicated greater transparency loss in Lesser Prespa than in Great Prespa Lake. Regarding the stream influences on Lesser Prespa Lake’s water quality, nutrient loads induced changes in lake concentrations by roughly one month. Total nitrogen showed moderate stream–lake correlations (R = 0.61) and a strong negative correlation for total phosphorus (R = −0.94), suggesting substantial nutrient retention and processes within the lake. Water balance analysis revealed an annual water deficit for both Lesser and Great Prespa, with the latter exhibiting a markedly stronger and systematic long-term decline in water level. In the Lesser Prespa, seasonal fluctuations in water volume were primarily driven by excess rainfall, while stream inflows contributed minimally. Conversely, correlation analysis for Great Prespa identified surface inflow from the Ag. Germanos catchment as the dominant driver of water storage variability, surpassing direct rainfall, with strong correlations in both wet (R = 0.79) and dry (R = 0.88) periods. Isotopic compositions (δ¹⁸O, δ²H) did not differ significantly between the two lakes, indicating common recharge sources and strong evaporative imprints, while stream isotopic signatures highlighted spatial and seasonal variability in hydrological inputs. Seasonal and spatial variations were proved to be strongly influenced by both natural hydrological dynamics and anthropogenic pressures within the basin, while these findings reinforce the importance and the necessity of adopting holistic, cross-border management strategies that maintain the ecological integrity and the long-term sustainability of the Prespa Lakes ecosystem. Full article

Phages, the most abundant entities on Earth, exhibit a complex interplay with bacteria, especially within environmental biofilms, resulting in an ecological arms race. This study investigates the interaction between phages and bacteria in the drains of beef-processing plants using high-throughput sequencing and metagenomic analysis. Metagenomic data collected from 75 drain samples from beef-processing plants were analyzed to investigate phage–bacterial interactions. First, assembled contigs were screened to identify viral sequences, which were then taxonomically annotated to determine the viral composition, including phages. Functional annotation of these viral sequences provided information about the viral genes and their roles in bacterial interactions specifically associated with attack and counterattack of bacteria. In parallel, bacterial contigs were examined to identify genes associated with antiphage defense systems, providing insights into the strategies adapted by bacteria to resist phage infection. Taxonomic annotation of viral sequences from the bulk metagenomic data revealed the presence of phages targeting Pseudomonas, Klebsiella, and Enterococcus. The higher abundance of Pseudomonas phages aligns with our previous study, where Pseudomonas was identified as the dominant bacterial genus, suggesting potential copersistence of phages and their hosts. Functional annotation of phage contigs revealed infective and lysis-related genes, highlighting their potential role in bacterial attack. Conversely, bacterial contigs encoded antiphage defense systems, including CRISPR-Cas, restriction–modification, and other defense-related genes. The study also uncovered the presence of anti-CRISPR proteins in phages, suggesting a counterattack on the bacterial defense. These findings provide evidence for phage attack, bacterial defense, and phage counterattack and may showcase the ongoing coevolutionary arms race between phages and bacteria. While this evidence looks promising, these results remain preliminary and further studies are needed to validate these findings. Still, this study provides a foundational understanding of bacteria–phage coexistence in beef-processing plant drains and paves the way for further explorations of these intricate interactions and their possible applications in controlling pathogenic microorganisms within biofilms. Full article

This paper presents a novel Double Buried-Window Junctionless Field-Effect Transistor (DBW-FET) designed for high-sensitivity, label-free biosensing applications. The proposed device integrates two buried windows, one N-type and one P-type, beneath the active channel within the buried oxide layer, along with two nanocavities serving as biomolecular recognition sites. The dual buried windows form two depletion regions that enhance electrostatic coupling, suppress short-channel effects, and improve biomolecular sensitivity. Numerical simulations using Silvaco TCAD Atlas were performed to investigate device performance under various biomolecular binding conditions. Results show that the DBW-FET exhibits higher drain current, lower subthreshold swing, and improved sensitivity compared with a conventional junctionless FET (C-FET). Furthermore, a machine-learning-assisted optimization framework employing Gaussian Process Regression (GPR) and Bayesian Optimization (BO) was implemented to identify optimal buried window parameters. The optimized design achieved a 20–25% improvement in current sensitivity while maintaining low leakage. These findings demonstrate that the proposed DBW-FET offers a promising and Complementary Metal-Oxide-Semiconductor (CMOS)-compatible architecture for next-generation nanoscale biosensors. Full article

Bacterial sourcing in urban watersheds is a critical water quality concern because elevated index bacteria concentrations routinely trigger beach advisories and closures in coastal Southern California and elsewhere. This study evaluates diurnal controls on dry-weather bacterial loading in a groundwater-fed storm drain within the Malibu Creek watershed using a 24 h monitoring campaign. Discharge, nutrients, major ions, stable water isotopes, and index bacteria (total coliforms and Escherichia coli) were measured at six time intervals. Storm drain discharge varied by more than an order of magnitude, with rapid nighttime increases of up to +91 L/min during irrigation periods. Total Dissolved Solids ranged from 1276 to 2175 mg/L, peaking during groundwater-dominated low-flow conditions. Nitrate–N ranged from 1.08 to 2.96 mg/L, and orthophosphate from 0.44 to 2.16 mg/L, with nutrient concentrations increasing as irrigation inputs increased. Total coliform concentrations ranged from 13,000 to 670,000 MPN/100 mL, and E. coli ranged from 300 to 120,000 MPN/100 mL, exceeding concentrations in tap water and recycled water runoff by up to two orders of magnitude. End member mixing analysis showed that storm drain flow consisted of approximately 45% groundwater, 23–26% tap water, and 30–33% recycled water during early morning peak flow, shifting to ~56% groundwater and <12% recycled water by mid-morning. The lowest bacterial concentrations occurred during groundwater-only flow, while the largest bacterial increases coincided with the greatest positive changes in discharge rather than with maximum absolute flow. These results support an irrigation-driven biofilm stripping mechanism as the dominant control on dry-weather bacterial loading, with groundwater seepage sustaining biofilm persistence but not peak bacterial release. The findings highlight the importance of internal storm drain processes for managing coastal bacterial exceedances and protecting beach health. Full article

Artificial intelligence transforms lubricant research by linking molecular modeling, diagnostics, and industrial operations into predictive systems. In this regard, machine learning methods such as Bayesian optimization and neural-based Quantitative Structure–Property/Tribological Relationship (QSPR/QSTR) modeling help to accelerate additive design and formulation development. Moreover, deep learning and hybrid physics–AI frameworks are now capable to predict key lubricant properties such as viscosity, oxidation stability, and wear resistance directly from molecular or spectral data, reducing the need for long-duration field trials like fleet or engine endurance tests. With respect to condition monitoring, convolutional neural networks automate wear debris classification, multimodal sensor fusion enables real-time oil health tracking, and digital twins provide predictive maintenance by forecasting lubricant degradation and optimizing drain intervals. AI-assisted blending and process control platforms extend these advantages into manufacturing, reducing waste and improving reproducibility. This article sheds light on recent progress in AI-driven formulation, monitoring, and maintenance, thus identifying major barriers to adoption such as fragmented datasets, limited model transferability, and low explainability. Moreover, it discusses how standardized data infrastructures, physics-informed learning, and secure federated approaches can advance the industry toward adaptive, sustainable lubricant development under the principles of Industry 5.0. Full article

Selenium contamination in arid agricultural basins remains a key ecological concern, yet the Wister Unit of the Imperial Wildlife Area has received comparatively little hydrochemical study. This investigation provides the most integrated assessment to date of selenium, salinity, nitrate, stable water isotopes (δ²H and δ¹⁸O), and selected redox-sensitive trace elements within the Wister Unit and its contributing open agricultural drains, with the goal of identifying controls on selenium concentrations and mobility. Water samples from open agricultural drains, shallow groundwater tile drains, canal project water, and tailwater return flow were analyzed for Total Dissolved Solids (TDS), major ions, nutrients, selenium, and stable water isotopes. A subset of samples was anlayzed for iron, manganese, and vanadium. Overall, 71% of open drain and tile drain samples collected in this study exceeded the U.S. Environmental Protection Agency aquatic-life criterion of 5 µg/L, indicating persistent ecological risk. All waters plotted along an evaporation trajectory originating from imported Colorado River irrigation water; however, isotopic enrichment did not scale directly with salinity. Pure evaporation models predicted much lower TDS values than observed, and the most evaporated samples were not the most saline or selenium-rich. These results demonstrate that simple soil water evaporation alone cannot explain the data. Instead, the broad isotopic range at similar salinities reflects a secondary process in which salts that accumulated in soils during dry or average years are later mobilized and flushed during periods of surplus water and heavy irrigation. Low dissolved iron, manganese, and vanadium concentrations in a subset of water samples indicate predominantly oxidizing conditions, under which selenium behaves conservatively during salt leaching, producing a strong correlation with TDS. Selenium levels measured in Wister Unit are generally lower than those reported in nearby areas during the 1990s–2000s, implying changes in salt accumulation, hydrologic routing, or agricultural practices. These results refine the conceptual model for the Wister Unit and motivate future work on selenium speciation, nitrate isotope tracing, time series monitoring, and soil-salt interactions. Full article

Channel length modulation (CLM) in indium gallium zinc oxide (IGZO) thin film transistors (TFTs) reduces the output resistance (r_o) in the saturation regime. It also degrades current driving accuracy for active matrix organic light emitting diode (AMOLED) backplanes. For top gate, self-aligned devices with nominal channel lengths of 5–15 μm, transmission line method (TLM) analysis yields an effective channel length reduction (ΔL) of about 1.8 μm. This result is consistent with lateral hydrogen redistribution from the self-aligned source/drain (S/D) process. At L = 5 μm, the conventional TFT exhibits r_o = 13.5 ± 2.5 MΩ and an Early voltage (V_A) = 56.1 ± 10.4 V (n = 5). We propose a source connected bottom gate (SCBG) structure that electrostatically stabilizes the pinch-off region and suppresses CLM. The SCBG TFT increases r_o to 475 ± 52 MΩ and V_A to 1159 ± 173 V at L = 5 μm (n = 5), while maintaining normal transfer characteristics. Two-dimensional device simulations reproduce the trend and show that the drain-bias-induced pinch-off shift is reduced, with d(ΔL)/dV_DS decreasing from 0.027 to 0.012 μm/V (about 55%). These results indicate that the SCBG approach is effective for enhancing current saturation in short channel IGZO TFTs for high-resolution AMOLED applications. Full article

During liquid drainage from intermediate vessels in various industrial processes such as continuous steel casting, aircraft fuel supply, and chemical separation, free-surface vortices commonly occur. The formation and evolution of these vortices not only entrain surface slag and gas, but also lead to deterioration of downstream product quality and abnormal equipment operation. The vortex evolution process exhibits notable three-dimensional unsteadiness, multi-scale turbulence, and dynamic gas–liquid interfacial changes, accompanied by strong coupling effects between temperature gradients and flow field structures. Traditional macroscopic numerical models show clear limitations in accurately capturing these complex physical mechanisms. To address these challenges, this study developed a mesoscopic numerical model for gas-liquid two-phase vortex flow based on the lattice Boltzmann method. The model systematically reveals the dynamic behavior during vortex evolution and the multi-field coupling mechanism with the temperature field while providing an in-depth analysis of how initial perturbation velocity regulates vortex intensity and stability. The results indicate that vortex evolution begins near the bottom drain outlet, with the tangential velocity distribution conforming to the theoretical Rankine vortex model. The vortex core velocity during the critical penetration stage is significantly higher than that during the initial depression stage. An increase in the initial perturbation velocity not only enhances vortex intensity and induces low-frequency oscillations of the vortex core but also markedly promotes the global convective heat transfer process. With regard to the temperature field, an increase in fluid temperature reduces the viscosity coefficient, thereby weakening viscous dissipation effects, which accelerates vortex development and prolongs drainage time. Meanwhile, the vortex structure—through the induction of Taylor vortices and a spiral pumping effect—drives shear mixing and radial thermal diffusion between fluid regions at different temperatures, leading to dynamic reconstruction and homogenization of the temperature field. The outcomes of this study not only provide a solid theoretical foundation for understanding the generation, evolution, and heat transfer mechanisms of vortices under industrial thermal conditions, but also offer clear engineering guidance for practical production-enabling optimized operational parameters to suppress vortices and enhance drainage efficiency. Full article

We present a methodology that enhances the analytical performance of organic electrochemical transistors (OECTs) by continuously cycling the devices through gate potential sweeps during sensing experiments. This continuous cycling methodology (CCM) enables real-time acquisition of full transfer curves, allowing simultaneous monitoring of multiple characteristic parameters. We show that the simultaneous temporal evolution of several OECT response parameters (threshold voltage (V_TH), maximum transconductance (g_max), and maximum transconductance potential (V_G,gmax)) provides highly sensitive descriptors for detecting pH changes and macromolecule adsorption on OECTs based on polyaniline (PANI) and poly(3,4-ethylenedioxythiophene) (PEDOT) channels. Moreover, the method allows reconstruction of I_DS–t (drain–source current vs. time) profiles at any selected gate potential, enabling the identification of optimal gate voltage (V_G) values for maximizing sensitivity. This represents a substantial improvement over traditional measurements at fixed V_G, which may suffer from reduced sensitivity and parasitic reactions associated with gate polarization. Moreover, the expanded set of parameters obtained with the CCM provides deeper insight into the physicochemical processes occurring at both gate and channel electrodes. We demonstrate its applicability in monitoring polyelectrolyte and enzyme adsorption, and detecting urea and glucose through enzyme-mediated reactions. Owing to its versatility and the richness of the information it provides, the CCM constitutes a significant advance for the development and optimization of OECT-based sensing platforms. Full article

Nitrogen (N) deposition poses a multi-pronged threat to the carbon (C)-regulating services of moss understories. For forest C-cycle modeling under increasing N deposition, failure to mechanistically incorporate the moss-mediated processes risks severely overestimating the C sink potential of global forests. To explore whether and how N input affects the moss-mediated CH₄ and carbon dioxide (CO₂) fluxes, a five-year field measurement was performed in the N manipulation experimental plots treated with 22.5 and 45 kg N ha⁻¹ yr⁻¹ as ammonium chloride for nine years under a well-drained temperate forest in northeastern China. In the presence of mosses, the average annual CH₄ uptake and CO₂ emission in all N-treated plots ranged from 0.96 to 1.48 kg C-CH₄ ha⁻¹ yr⁻¹ and from 4.04 to 4.41 Mg C-CO₂ ha⁻¹ yr⁻¹, respectively, with a minimum in the high-N-treated plots, which were smaller than those in the control (1.29–1.83 kg C-CH₄ ha⁻¹ yr⁻¹ and 4.82–6.51 Mg C-CO₂ ha⁻¹ yr⁻¹). However, no significant differences in annual cumulative CO₂ and CH₄ fluxes across all treatments occurred without moss cover. Based on the differences in C fluxes with and without mosses, the average annual moss-mediated CH₄ uptake and CO₂ emission in the control were 0.77 kg C-CH₄ ha⁻¹ yr⁻¹ and 2.40 Mg C-CO₂ ha⁻¹ yr⁻¹, respectively, which were larger than those in the two N treatments. The N effects on annual moss-mediated C fluxes varied with annual meteorological conditions. Soil pH, available N and C contents, and microbial activity inferred from δ¹³C shifts in respired CO₂ were identified as the main driving factors controlling the moss-mediated CH₄ and CO₂ fluxes. The results highlighted that this inhibitory effect of increasing N deposition on moss-mediated C fluxes in the context of climate change should be reasonably taken into account in model studies to accurately predict C fluxes under well-drained forest ecosystems. Full article

Background: Pediatric craniocervical junction (CCJ) anomalies consist of a unique subset of anatomically complex spine conditions. The aims of intervention are to achieve long-term stability, correct existing deformity, and prevent neurological compromise. However, surgery is challenging due to critical neurovascular and musculoskeletal structures in the limited operative space of a young child. Recently, the use of three-dimensional (3D) printed models has been demonstrated to be valuable neurosurgical adjuncts. We therein report the application of a 3D-printed model for a pediatric case with a complex CCJ condition. A systematic review of the related literature is concurrently performed. Case description: A 10-year-old male presented with torticollis associated with neck pain and progressive thoracic kyphosis. Neuroimaging reported an unfused os odontoideum inferior to the basion and anterior half of the C2 vertebral body and anteriorly angulated with the C1 anterior arch. Of note, there was a large vertebral vein coursing over the left C2 lamina that was predominantly draining into the CCJ venous plexus. A radiologically derived 3D model of the patient’s CCJ was printed and used for pre-operative planning, multi-disciplinary team discussion, and detailed counseling with the patient and caregivers. The patient underwent an uneventful C1–C2 posterior screw fixation and has recovered well since. Separately, we observed there is a paucity of publications specific to this topic. Conclusions: As demonstrated, a custom-made 3D model was useful for clinicians work through technical difficulties and improve the perioperative discussion process in an otherwise difficult case. Full article

Long-range, high-resolution distance measurement with high ambient-light tolerance has been achieved using a 720 × 488-resolution short-pulse indirect time-of-flight (SP-iToF) image sensor featuring six-tap, one-drain pixels fabricated by a front-side illumination (FSI) process. The sensor performs 30-phase demodulation through six-tap pixels in each subframe, combined with five range-shifted subframe (SF) readouts. The six-tap demodulation pixel, designed with a lateral drift-field pinned photodiode, demonstrates over 90% demodulation contrast for a 20 ns light-pulse width. High-speed column-parallel 12-bit cyclic ADCs enable all six-tap subframe signals to be read within 4.38 ms. This high-speed subframe readout, together with efficient exposure-time allocation across the five subframes, enables a depth-image frame rate of 10 fps. The multi-phase demodulation in SP-iToF measurements, operating with an extremely small duty ratio of 0.2%, effectively suppresses ambient-light charge accumulation and the associated shot noise in the pixel. As a result, distance measurements up to 100 m under 100 klux illumination are achieved, with depth noise maintained below 1%. Full article