Search Results (3,974)

In response to the demand for high-precision acoustic support under the condition of limited data, this study utilized high-resolution reanalysis data and in situ observation data to extract the Kuroshio Extension Front (KEF) section through front-line identification methods. By combining the parameterized oceanic front model and the statistical features of big data, the parameterized oceanic front was reconstructed. A proxy dataset was generated using the Latin hypercube sampling method, and the sound speed reconstruction model based on the PIX2PIX model was trained and validated using single sound speed profiles at different positions of the oceanic front, combined with the parameterized oceanic front model. The experimental results show that the proposed sound speed reconstruction model can significantly improve the reconstruction accuracy by introducing the parameterized front model as an additional input, especially in the shallow-water area. The mean absolute error (MAE) of the full-depth sound speed reconstruction for this model is 0.63~0.95 m·s⁻¹, and the structural similarity index (SSIM) is 0.76~0.78. The MAE of the sound speed section within a 1000 m depth is reduced by 6.50~37.62%, reaching 1.95~3.31 m·s⁻¹. In addition, the acoustic support capabilities and generalization of the model were verified through ray tracing models and in situ data. This study contributes to advancing high-precision acoustic support in data-limited oceanic environments, laying a solid groundwork for future innovations in marine acoustics. Full article

The objective of this study was to evaluate the antimicrobial effect of direct cold atmospheric plasma (CAPP) treatment for pre-harvest application using four different crop species: Hordeum vulgare L. (barley), Triticum aestivum L. (wheat), Brassica napus L. (rapeseed) and Lupinus angustifolius L. (lupine). The model bacterium Bacillus atrophaeus served as a proxy for spore-forming plant pathogens on the seed surface. After semi-dry inoculation of spores onto the seeds, treatment with two different plasma sources, a volume-dielectric barrier discharge and a corona discharge, and different exposure times was carried out. Subsequently, recovery of viable spores from the seeds’ surfaces was performed. Moreover, seed viability was determined based on maximum germination, as well as water contact angle as a measure for seed surface hydrophilicity. Direct CAPP treatment was efficient in reducing viable spores of B. atrophaeus with no significant differences between the plasma sources, reaching a mean inactivation of 1 log₁₀ CFU/mL across all treatment times and crops species. Maximum germination of seeds was not negatively affected under any treatment condition. Seed hydrophilicity was increased for both plasma sources tested. Overall, this study provides valuable information on the efficiency of direct CAPP treatment of seeds with the purpose of seed hygienization with the premise of unaltered seed vitality and evaluates the potential application in comparison with previous investigated CAPP methods. Full article

Being located in the middle of Southern Europe, and thus likely representing a particularly dynamic member of Mediterranean Europe, Italy has experienced a sudden increase in early desertification risk because of multiple factors of change. Long-term research initiatives have provided relatively well-known examples of the continuous assessment of the desertification risk carried out via multiple exercises from different academic and practitioner stakeholders, frequently using the Environmentally Sensitive Area Index (ESAI). This composite index based on a large number of elementary variables and individual indicators—spanning from the climate to soil quality and from vegetation cover to land-use intensity—facilitated the comprehensive, long-term monitoring of the early desertification risk at disaggregated spatial scales, being of some relevance for policy implementation. The present study summarizes the main evidence of environmental monitoring in Italy by analyzing a relatively long time series of ESAI scores using administrative boundaries for a better representation of the biophysical and socioeconomic trends of interest for early desertification monitoring. The descriptive analysis of the ESAI scores offers a refined representation of economic spaces in the country during past (1960–2010 on a decadal basis), present (2020), and future (2030, exploring four different scenarios, S1–S4) times. Taken as a proxy of the early desertification risk in advanced economies, the ESAI scores increased over time as a result of worse climate regimes (namely, drier and warmer conditions), landscape change, and rising human pressure that exacerbated related processes, such as soil erosion, salinization, compaction, sealing, water scarcity, wildfires, and overgrazing. Full article

Stellar evolution models serve as tools to derive stellar parameters from elemental and isotopic abundance ratios. For low-to-intermediate mass evolved stars, C/O, ¹²C/¹³C, and ¹⁷O/¹⁸O ratios are proxies of the initial mass, a largely unknown parameter in post-AGB sources, yet fundamental to establish correlations with the main properties of their post-AGB envelopes, progressing in understanding their formation and evolution. In these sources, the C/O ratio can be constrained from the detection of C- or O-bearing species in addition to CO, while the ¹⁷O/¹⁸O ratio is straightforwardly determined from the C¹⁷O-to-C¹⁸O intensity ratio of rotational lines. However, the theory is at odds with the observations. We review the status of the question, including new accurate ¹⁷O/¹⁸O ratios for 11 targets (totaling 29). Comparing the results for the ¹⁷O/^$18$O ratios and C-rich/O-rich chemical composition, we find that ∼45% of the cases are canonical, i.e., the observations align with standard model predictions. O-rich non-canonical sources, with ^$17$O/^$18$O ratios above the expected, can be explained by a premature interruption of their AGB evolution as a consequence of a quasi-explosive ejection of a large fraction of the initial mass. For non-canonical C-rich sources, with ^$17$O/^$18$O ratios below predictions, we suggest the possibility they are extrinsic C-rich stars. Full article

The COVID-19 pandemic has caused major disruptions to workplace safety and productivity. A browser-based interactive disease transmission simulation was developed to enable managers and individuals (agents) to optimize safe office work activities during pandemic conditions. The application provides a user interface to evaluate the impact of non-pharmaceutical interventions (NPIs) policies on airborne disease exposure based on agents’ meeting patterns and room properties. Exposure is empirically calibrated using CO₂ as a proxy for viral aerosol dispersion. For the building studied, the major findings are that the cubicles during low occupancy produce unexpectedly high exposure, upgrading meetings to larger rooms reduces total average exposure by 44%, and when all meetings are conducted in large rooms, a 79% exposure reduction is realized. Full article

Pollarding has historically been used in broadleaf tree species across European woodlands. However, despite pollarding enhances vigor growth in the short term, it is still unclear how long this effect lasts and whether it can alleviate drought stress in seasonally dry regions. We compared the radial growth and wood δ¹³C (¹³C/¹²C), a proxy of intrinsic water-use efficiency (iWUE), of trees pollarded 10 and 20 years ago in two black poplar (Populus nigra L.) riparian stands located in North Eastern Spain and subjected to different ecohydrological conditions. We also assessed if pollarded trees showed different leaf phenology as compared with uncut trees of coexisting white poplar (Populus alba L.) trees. The relationships between growth, climate variables, drought severity and river flow were quantified. Pollarded and uncut trees showed a similar leaf phenology with a trend towards earlier leaf unfolding as springs become warmer. Pollarding increased growth rates by 54% (ratio between trees pollarded 10 and 20 years ago, respectively), but this enhancement was transitory and lasted ca. 10 years, whereas wood δ¹³C decreased −5%. The growth of black poplar increased in response to high precipitation in the previous winter, cool wet conditions, and a higher river flow in summer. Pollarding improves growth and relieves drought stress. Full article

Soil aggregation results from the rearrangement, flocculation and cementation of primary soil particles. Furthermore, the aggregates undergo transformation under no-tillage (NT) overtime. Soil organic carbon (OC) is the major component of soil organic matter and is protected within aggregates and can serve as a proxy for soil structural stability. Organic matter contributes significantly to the formation of soil aggregates and the carbon within them is protected against degradation. This study assessed the impact of tillage systems, soil depth and no-till duration on soil aggregate size distribution, stability and aggregate associated carbon. It was carried out in Thohoyandou (Tshivhilwi and Dzingahe), Vhembe district, Limpopo province, South Africa. The soil samples were collected from NT, conventional tillage (CT) and virgin (VG) fields in the topsoil (0–30 cm) and subsoil (30–60 cm) at each location. The duration of NT for fields in Tshivhilwi and Dzingahe were 8 years (short-term) and >40 years (long-term), respectively. The results showed that macro-aggregates constituted the largest proportion of aggregates, with a percentage contribution of >60% during the short-term and long-term. The mean weight diameter (MWD) varied significantly between NT and VG in the subsoil for the short-term NT. The aggregates were more stable in the short-term NT than long-term NT. Organic carbon in all aggregate fractions between the tillage systems in the topsoil was not significantly affected after more than 40 years. The MWD was higher in the subsoil than topsoil in NT and CT during both periods. Micro-aggregates contained greater OC than other fractions. The study showed that the impact of NT on aggregation, structural stability and the capacity to store carbon vary overtime. It is recommended that the aggregation and/or structural stability of different soil textures under NT with different cropping systems and management practices should be studied periodically. Full article

Soil multifunctionality is closely tied to soil health, yet a comprehensive understanding of this link in agricultural soils is lacking. The aim of this study was to understand how long-term fertilization practices affect the provision of multiple services by comparing the multifunctionality of soils. The three objectives were to (i) determine whether the effect of fertilization is consistent across soil types, (ii) describe the effect of the different fertilizers on soil multifunctionality, and (iii) identify soil chemical properties that can be easily used proxies of soil multifunctionality. The descriptors belong to three functioning indexes associated with nutrient availability, carbon transformation, and soil structure maintenance. This study is the first to investigate the effect of a variety of organic fertilizers on the health of three soil types by combining physical, chemical, and biological indicators in sugarcane agroecosystems. An increase in soil multifunctionality was obtained, with no effect on yield. The effect of fertilizers was consistent across soil types. Filter mud and green waste compost significantly increased the multifunctionality and functioning indexes compared to mineral fertilizer. Modifications in soil properties did not fully explain the observed variations. Our results confirm the high potential of organic fertilization to improve multifunctionality and provide ecosystem services. Full article

Warm water temperature is a risk factor for recurrent mass mortality in farmed Pacific oysters Crassostrea gigas caused by Ostreid herpesvirus-1, but there is little information on environmental conditions when the disease first appears in a region—the index case. Environmental conditions between four index cases in Australia (2010, 2013, 2016 and 2024) were compared to provide insight into possible origins of the virus. Each index case was preceded by unusually low rainfall and higher rates of temperature change that could increase oyster susceptibility through thermal flux stress. Water temperature alone did not explain the index cases, there being no consistency in sea surface, estuary or air temperatures between them. Tidal cycles and chlorophyll-a levels were unremarkable, harmful algae were present in all index cases and anthropogenic environmental contamination was unlikely. The lack of an interpretable change in the estuarine environment suggests the recent introduction of OsHV-1; however, viral emergence from a local reservoir cannot be excluded. Future events will be difficult to predict. Temperature flux and rainfall are likely important, but they are proxies for a range of undetermined factors and to identify these, it will be necessary to develop comprehensive protocols for data acquisition during future index cases. Full article

The estimation of space-varying geological parameters is often not computationally affordable for high-dimensional subsurface reservoir modeling systems. The adjoint method is generally regarded as an efficient approach for obtaining analytical gradient and, thus, proceeding with the gradient-based iteration algorithm; however, the infeasible memory requirement and computational demands strictly prohibit its generic implementation, especially for high-dimensional problems. The autoregressive neural network (aNN) model, as a nonlinear surrogate approximation, has gradually received increasing popularity due to significant reduction of computational cost, but one prominent limitation is that the generic application of aNN to large-scale reservoir models inevitably poses challenges in the training procedure, which remains unresolved. To address this issue, model-order reduction could be a promising strategy, which enables us to train the neural network in a very efficient manner. A very popular projection-based linear reduction method, i.e., propel orthogonal decomposition (POD), is adopted to achieve dimensionality reduction. This paper presents an architecture of a projection-based autoregressive neural network that efficiently derives an easy-to-use adjoint model by the use of an auto-differentiation module inside the popular deep learning frameworks. This hybrid neural network proxy, referred to as POD-aNN, is capable of speeding up derivation of reduced-order adjoint models. The performance of POD-aNN is validated through a synthetic 2D subsurface transport model. The use of POD-aNN significantly reduces the computation cost while the accuracy remains. In addition, our proposed POD-aNN can easily obtain multiple posterior realizations for uncertainty evaluation. The developed POD-aNN emulator is a data-driven approach for reduced-order modeling of nonlinear dynamic systems and, thus, should be a very efficient modeling tool to address many engineering applications related to intensive simulation-based optimization. Full article

Daylight plays a crucial role in human health, and as research into its effects expands, it is essential for designers to estimate the non-image-forming impacts of various daylighting and lighting strategies. This allows them to create indoor environments that are both pleasant and comfortable. To support this, daylight measurements were taken in five Chinese cities, focusing on spectral power distribution, correlated color temperature, and illuminance. The study calculated the non-image-forming effects of daylight exposure using metrics like melanopic Equivalent Daylight Illuminance and Circadian Light. A key finding was the development of the action factor S_AI, which estimates the potential non-image-forming effects of light in built environments. This factor serves as a proxy for understanding how non-image-forming effects relate to correlated color temperatures. Additionally, the research suggests the possibility of creating a time-variational daylighting and lighting strategy with four distinct periods of non-image-forming effects throughout a 24 h day. These insights could be valuable for architects and designers in optimizing indoor lighting systems. Full article

Low-molecular-mass organic chemicals are widely discussed as potential indicators of life in extraterrestrial habitats. However, demarcation lines between biotic chemicals and abiotic chemicals have been difficult to define. Here, we have analyzed the potential utility of the quantum chemical property, HOMO-LUMO gap (HLG), as a novel proxy variable of life, since a significant trend towards incrementally smaller HLGs has been described in the genetically encoded amino acids. The HLG is a zeroth-order predictor of chemical reactivity. Comparing a set of 134 abiotic organic molecules recovered from meteorites, with 570 microbial and plant secondary metabolites thought to be exclusively biotic, we found that the average HLG of biotic molecules was significantly narrower (−10.4 ± 0.9 eV versus −12.4 ± 1.6 eV), with an effect size of g = 1.87. Limitation to hydrophilic molecules (XlogP < 2) improved the separation of biotic from abiotic compounds (g = 2.52). The “hydrophilic reactivity” quadrant defined by |HLG| < 11.25 eV and XlogP < 2 was populated exclusively by 183 biotic compounds and 6 abiotic compounds, 5 of which were nucleobases. We conclude that hydrophilic molecules with small HLGs represent valuable indicators of biotic activity, and we discuss the evolutionary plausibility of this inference. Full article

The escalating human pressures on natural ecosystems necessitate urgent and effective conservation strategies to safeguard biodiversity and ecosystem functions. This review explored current techniques for mapping human pressure, with a particular focus on their application in nature conservation, especially within protected areas (PAs). Specifically, we analyzed the impacts of seven major types of human pressures on nature conservation within PAs. Additionally, we discussed four key methods for mapping human pressure, including land use intensity, human footprint, digital human footprint, and other proxies, examining their distinct characteristics and respective advantages and disadvantages. Additionally, our research explored the application of human pressure mapping for nature conservation, assessing its suitability for conservation applications and delineating directions for future work. These insights contributed to better support nature conservation and the management of PAs. Full article

This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. An approach leveraging a machine learning workflow for reservoir characterization, history matching, sensitivity analysis, field development and optimization was proposed to accomplish the above goal. A 3D subsurface model representing studied sand-shale sequences was constructed based on geophysical and petrophysical logs, core measurements, and advanced machine learning techniques. After that, a robust sensitivity analysis and history matching process were conducted using a machine learning workflow. The most sensitive control variables were the aquifer properties, permeability heterogeneity in different directions, and water–oil contacts. The history matching results from the constructed geological model showed that the oil rate, water rate, bottom hole pressure, and average reservoir pressure were matched within a 10% deviation from the observed data. Several field development scenarios were generated using the validated model to optimize cumulative oil recovery. Different injection well placement locations, well patterns, and the possibility of converting existing oil-producing wells to water injection wells were investigated. A machine learning-based proxy model was built for the prediction of cumulative oil production and then optimized with hybrid machine learning techniques. The Artificial Neural Network (ANN) algorithm was found to provide higher field cumulative oil production compared with the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) of 3.5% and 26.5%, respectively. Following the detailed proposed machine learning-based workflow, one can effectively decide on the development strategy and apply the findings from this research to their field. Full article

Background: Due to the relatively advanced age and high mortality rate of patients with high-grade chondrosarcoma (CS), it is important to holistically assess patient- and tumor characteristics in multidisciplinary team and shared decision-making with regard to treatment options. While current prognostic models include multiple tumor and treatment characteristics, the only patient characteristics that are commonly included are age and gender. Based on clinical experience, we believe that factors related to patient preoperative systemic health status such as the American Society of Anesthesiologists (ASA) score may be equally important prognostic factors for overall survival (OS). Methods: A retrospective nationwide cohort study was identified from four specialized bone sarcoma centers in The Netherlands. Patients with a primary CS grade II, III, and dedifferentiated CS were eligible. Prognostic factors including age at presentation, gender, ASA score, CVD, tobacco use, BMI, histological tumor grade, tumor size, pathological fracture, presentation after unplanned excision, type of surgery and surgical margin were evaluated. The outcome measure was OS at the time of surgery. The Kaplan–Meier methodology was employed to estimate OS; a log-rank test was used to assess the difference in survival. To study the impact of prognostic factors on OS, a multivariate Cox proportional hazard regression model was estimated. Results: In total, 249 patients were eligible for this study, and 89 were deceased at the end of follow-up. In multivariate analysis, histological grade (HR 2.247, 95% CI 1.334–3.783), ASA score III (HR 2.615, 95% CI 1.145–5.976, vs. ASA I), and age per year (HR: 1.025, 95% CI 1.004–1.045) were negatively associated with OS. No association was found between tobacco use, BMI, gender or cardiovascular disease and OS in this cohort. Pathological fracture and tumor size were only associated with OS in univariate analysis. Conclusions: This multicenter study is the first on sarcomas to include ASA in a prognostic model. Results show that ASA score as a proxy for patients’ systemic health status should be included when providing a prognosis for patients with a high-grade primary CS, besides the conventional risk factors such as tumor grade and age. Specifically, severe systemic disease (ASA score III) is a strong negative predictor. Conversely, we found no difference in OS between ASA scores I and II. These findings aid multidisciplinary team and shared decision-making with regard to these complex sarcoma patients that often require life-changing surgeries. Level of Evidence: Prognostic level III. See the instructions for authors for the complete description of levels of evidence. Full article