Search Results (62)

Climate change has intensified extreme weather events and accelerated soil salinization, posing serious threats to crop yield and quality. Salinity stress, now affecting about 20% of irrigated lands, is expected to worsen due to rising temperatures and sea levels. At the same time, the global population is projected to exceed 9 billion by 2050, demanding a 70% increase in food production (UN, 2019; FAO). Agriculture, responsible for 34% of global greenhouse gas emissions, urgently needs sustainable solutions. Microbial inoculants, known as “plant probiotics,” offer a promising eco-friendly alternative by enhancing crop resilience and reducing environmental impact. In this study, we evaluated the plant growth-promoting (PGP) traits and melatonin-producing capacity of Bacillus aerius EH2-5. To assess its efficacy under salt stress, soybean seedlings at the VC stage were inoculated with EH2-5 and subsequently subjected to salinity stress using 150 mM and 100 mM NaCl treatments. Plant growth parameters, the expression levels of salinity-related genes, and the activities of antioxidant enzymes were measured to determine the microbe’s role in promoting plant growth and mitigating salt-induced oxidative stress. Here, our study shows that the melatonin-synthesizing Bacillus aerius EH2-5 (7.48 ng/mL at 24 h after inoculation in Trp spiked LB media) significantly improved host plant (Glycine max L.) growth, biomass, and photosynthesis and reduced oxidative stress during salinity stress conditions than the non-inculcated control. Whole genome sequencing of Bacillus aerius EH2-5 identified key plant growth-promoting and salinity stress-related genes, including znuA, znuB, znuC, and zur (zinc uptake); ptsN, aspA, and nrgB (nitrogen metabolism); and phoH and pstS (phosphate transport). Genes involved in tryptophan biosynthesis and transport, such as trpA, trpB, trpP, and tspO, along with siderophore-related genes yusV, yfhA, and yfiY, were also detected. The presence of multiple stress-responsive genes, including dnaK, dps, treA, cspB, srkA, and copZ, suggests EH2-5′s genomic potential to enhance plant tolerance to salinity and other abiotic stresses. Inoculation with Bacillus aerius EH2-5 significantly enhanced soybean growth and reduced salt-induced damage, as evidenced by increased shoot biomass (29%, 41%), leaf numbers (12% and 13%), and chlorophyll content (40%, 21%) under 100 mM and 150 mM NaCl compared to non-inoculated plants. These results indicate EH2-5′s strong potential as a plant growth-promoting and salinity stress-alleviating rhizobacterium. The EH2-5 symbiosis significantly enhanced a key ABA biosynthesis enzyme-related gene NCED3, dehydration responsive transcription factors DREB2A and NAC29 salinity stresses (100 mM and 150 mM). Moreover, the reduced expression of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT) by 16%, 29%, and 24%, respectively, and decreased levels of malondialdehyde (MDA) and hydroxy peroxidase (H₂O₂) by 12% and 23% were observed under 100 mM NaCl compared to non-inoculated plants. This study demonstrated that Bacillus aerius EH2-5, a melatonin-producing strain, not only functions effectively as a biofertilizer but also alleviates plant stress in a manner comparable to the application of exogenous melatonin. These findings highlight the potential of utilizing melatonin-producing microbes as a viable alternative to chemical treatments. Therefore, further research should focus on enhancing the melatonin biosynthetic capacity of EH2-5, improving its colonization efficiency in plants, and developing synergistic microbial consortia (SynComs) with melatonin-producing capabilities. Such efforts will contribute to the development and field application of EH2-5 as a promising plant biostimulant for sustainable agriculture. Full article

Accurate prediction of ship fuel consumption is essential for improving energy efficiency, optimizing mission planning, and ensuring operational integrity at sea. However, during complex tasks such as high-speed maneuvers, fuel consumption exhibits complex dynamics characterized by the coexistence of baseline drift and transient peaks that conventional models often fail to capture accurately, particularly the abrupt peaks. In this study, a hybrid prediction model, DGM-SVR, is presented, combining a rolling dynamic grey model (DGM (1,1)) with support vector regression (SVR). The DGM (1,1) adapts to the dynamic fuel consumption baseline and trends via a rolling window mechanism, while the SVR learns and predicts the residual sequence generated by the DGM, specifically addressing the high-amplitude fuel spikes triggered by maneuvers. Validated on a simulated dataset reflecting typical fuel spike characteristics during high-speed maneuvers, the DGM-SVR model demonstrated superior overall prediction accuracy (MAPE and RMSE) compared to standalone DGM (1,1), moving average (MA), and SVR models. Notably, DGM-SVR reduced the test set’s MAPE and RMSE by approximately 21% and 34%, respectively, relative to the next-best DGM model, and significantly improved the predictive accuracy, magnitude, and responsiveness in predicting fuel consumption spikes. The findings indicate that the DGM-SVR hybrid strategy effectively fuses DGM’s trend-fitting strength with SVR’s proficiency in capturing spikes from the residual sequence, offering a more reliable and precise method for dynamic ship fuel consumption forecasting, with considerable potential for ship energy efficiency management and intelligent operational support. This study lays a foundation for future validation on real-world operational data. Full article

Articles have recently been circulating in the media around the world, claiming that natural ${\mathrm{CO}}_2$ sinks have “suddenly and unexpectedly” ceased to function. It turned out that these articles were based on a single preprint of a meanwhile published article. Its reasoning is essentially based on the large spike of ${\mathrm{CO}}_2$ concentration growth in 2023 despite constant anthropogenic emissions. However, there are no obvious indications that photosynthesis or oceanic sinks have decreased. In this paper, it is shown that besides the natural sink systems of the land plants and oceans, the variability of natural emissions has to be considered. Based on a previous publication, it is made evident that natural emissions are temperature-dependent. Therefore, the careful analysis of monthly sea surface temperature and ${\mathrm{CO}}_2$-concentration data for 2023 and 2024 gives a consistent explanation for the rise in atmospheric carbon concentration growth without referring to the implausible hypothesis of failing carbon sinks. The temperature dependence of natural ${\mathrm{CO}}_2$ emissions indicates a clear causality from temperature to ${\mathrm{CO}}_2$ concentration. This is confirmed by the time shift between temperature and the subsequent concentration change. This suggests a new component in climate models with implications for climate policies. Full article

Maintaining a Constant False Alarm Rate (CFAR) in the presence of K-distributed sea clutter is vital due to the dynamic and unpredictable nature of maritime environments. However, conventional CFAR detectors suffer significant performance degradation in multi-target scenarios, primarily due to the masking effect caused by interfering targets. To address this challenge, this paper introduces an advanced detection scheme that integrates Linear Density-Based Spatial Clustering for Applications with Noise (Lin-DBSCAN) with CFAR processing. Lin-DBSCAN is specifically tailored to efficiently identify and isolate interfering targets and sea spikes, which typically manifest as outliers in the symmetric reference windows surrounding the Cell Under Test (CUT). By leveraging Lin-DBSCAN, the proposed Lin-DBSCAN-CFAR method effectively filters out anomalous signals from the background clutter, resulting in enhanced detection accuracy and robustness, especially under complex sea clutter conditions. Extensive simulations under varying conditions, including multiple target environments, varying false alarm rates, and different clutter shape parameters, demonstrate that Lin-DBSCAN-CFAR significantly outperforms conventional CFAR approaches. It is noteworthy that the proposed method achieves detection performance comparable to the more computationally intensive DBSCAN-CFAR while significantly reducing computational complexity. Simulation results reveal that Lin-DBSCAN-CFAR requires a 1 to 2 dB lower SNR to reach a detection probability of 0.8 compared with the nearest traditional CFAR techniques, confirming its superiority in both accuracy and efficiency. Full article

Sulfur dioxide (SO₂) can be of natural and anthropogenic origin and is one of the sulfur compounds present in the atmosphere. Among natural sources, volcanoes contribute with relevant annual outputs, and major eruptions lead to spikes in these outputs. In the case of anthropogenic pollution, SO₂ emissions are mostly correlated with the sulfur content of fuels, which has been the focus of specific emission mitigation policies for decades. Following other examples of cyclic and multi-year evaluations, an analysis of SO₂ at the Lamezia Terme (code: LMT) WMO/GAW (World Meteorological Organization—Global Atmosphere Watch) station in Calabria, Southern Italy, was performed. The coastal site is characterized by wind circulation patterns that result in the detection of air masses with low or enhanced anthropic influences. The presence of the Aeolian Arc of active, quiescent, and extinct volcanoes, as well as Mount Etna in Sicily, may influence LMT observations with diffused SO₂ emissions. For the first time in the history of the LMT, a multi-year analysis of a parameter has been integrated with TROPOMI data gathered by Sentinel-5P and used to test total tropospheric column densities at the LMT itself and select coordinates in the Tyrrhenian and Ionian seas. Surface and satellite data indicate that SO₂ peaks at the LMT are generally linked to winds from the western–seaside wind corridor, a pattern that is compatible with active volcanism in the Tyrrhenian Sea and maritime shipping to and from the Gioia Tauro port located in the same region. The findings of this research provide the basis for enhanced source apportionment, which could further differentiate anthropogenic sources in the area from natural outputs. Full article

This work aims to improve the characterization of petrophysical properties by accurately estimating subsurface porosity using seismic and well data. The study includes Bayesian Linearized Inversion to obtain elastic parameters (e.g., compressional e shear wave velocities and densities). This reduces processing uncertainty and provides a reliable substitute for the standard Amplitude versus Offset inversion method. Furthermore, incorporating sparse spike wavelets with Bayesian Linearized Inversion refines the inversion output, facilitating the extraction of petrophysical properties. Combined with log data from seventeen wells, these inverted parameters serve as inputs for two porosity prediction models: the empirical Han’s equation and a more adaptable Support Vector Regression model, the latter demonstrating superior precision in most cases due to its flexible fitting and calibration capabilities. Results from the Norne field in the North Sea confirm the approach’s viability, with the Support Vector Regression model achieving a significant Pearson correlation coefficient of 90% in porosity prediction, underscoring the potential of machine learning techniques in improving subsurface exploration results. Full article

Food poisoning outbreaks frequently involve staphylococcal enterotoxins (SEs). SEs include 33 distinct types and multiple sequence variants per SE type. Various mass spectrometry methods have been reported for the detection of SEs using a conventional bottom-up approach. However, the bottom-up approach cannot differentiate between all sequence variants due to partial sequence coverage, and it requires a long trypsin digestion time. While the alternative top-down approach can theoretically identify any sequence modifications, it generally provides lower sensitivity. In this study, we optimized top-down mass spectrometry conditions and incorporated a fully ¹⁵N-labeled SEA spiked early in the protocol to achieve sensitivity and repeatability comparable to bottom-up approaches. After robust immunoaffinity purification of the SEA, mass spectrometry signals were acquired on a Q-Orbitrap instrument operated in full-scan mode and targeted acquisition by parallel reaction monitoring (PRM), enabling the identification of sequence variants and precise quantification of SEA. The protocol was evaluated in liquid and solid dairy products and demonstrated detection limits of 0.5 ng/mL or ng/g in PRM and 1 ng/mL or ng/g in full-scan mode for milk and Roquefort cheese. The top-down method was successfully applied to various dairy products, allowing discrimination of contaminated versus non-contaminated food, quantification of SEA level and identification of the variant involved. Full article

This study investigated the influence of sea–land breezes on nocturnal spatial and temporal distribution of ozone (O₃) and its potential effects on particulate nitrate formation in Qingdao, a coastal city in northern China. Observation campaigns were conducted to measure surface air pollutants and meteorological factors during a typical sea–land breezes event from 22 to 23 July 2022. A coherent Doppler lidar (CDL) system was employed to continuously detect three-dimensional wind fields. The results revealed that nocturnal ozone levels were enhanced by a conversion of sea–land breezes. Initially, the prevailing northerly land breeze transported high concentrations of O₃ and other air pollutants from downtown to the Yellow Sea. As the sea breeze developed in the afternoon, the sea breeze front advanced northward, resulting in a flow of high O₃ concentrations back into inland areas. This penetration of the sea breeze front led to a notable spike in O₃ concentrations between 16:00 on 22 July and 02:00 on 23 July across downtown areas, with an average increase of over 70 μg/m³ within 10 min. Notably, a time lag in peak O₃ concentration was observed with southern downtown areas peaking before northern rural areas. During this period, combined pollution of O₃ and PM_2.5 was also observed. These findings indicated that the nighttime increase in O₃ concentrations, coupled with enhanced atmospheric oxidation, would likely promote the secondary conversion of gaseous precursors into PM_2.5. Full article

To analyze the impact of volcanic rocks in the Offshore Indus Basin on hydrocarbon reservoir formation, seismic data interpretation, seismic data inversion, and sea–land correlation analysis were carried out. The results show that, longitudinally, volcanic rocks are mainly distributed at the top of the Cretaceous system or at the bottom of the Paleocene, and carbonate rock platforms or reefs of the Paleocene–Eocene are usually developed on them. On the plane, volcanic rocks are mainly distributed on the Saurashtra High in the southeastern part of the basin. In terms of thickness, the volcanic rocks revealed by drilling in Karachi nearshore are about 70 m thick. We conducted sparse spike inversion for acoustic impedance in the volcanic rock area. The results show that the thickness of the Deccan volcanic rocks in the study area is between 250 and 750 m which is thinning from southeast to northwest. Based on sea–land comparison and comprehensive research, the distribution of volcanic rocks in the Indian Fan Offshore Basin played a constructive role in the Mesozoic oil and gas accumulation in the Indus offshore. Therefore, in the Indian Fan Offshore Basin, attention should be paid to finding Mesozoic self-generated and self-stored hydrocarbon reservoirs and Cenozoic lower-generated and upper-stored hydrocarbon reservoirs. Full article

Human observation of the ocean has gradually evolved from the sea surface to systematic monitoring and sampling through seafloor observation networks, and constant current power supply has become the main power supply method for seafloor observation networks due to its high reliability. There are some studies on current source to voltage source converters, but there are few studies on current source to current source (CS/CS) converters, which affects the expansion of power supply networks for seafloor observation networks. In this paper, by employing input current sharing and output voltage doubling circuits, an active clamp dual-inductor isolated CS/CS converter which uses a single-stage conversion circuit to realize constant current source conversion with a wide output voltage range is proposed. Active clamp technology at the primary side of the proposed circuit is employed to recover energy stored in leakage inductance, suppress voltage spikes of the primary side switches, and achieve zero-voltage switching of the primary side switches. The secondary side’s output voltage doubling circuit resonates with transformer leakage inductance to achieve zero-current switching of the secondary side diodes, which can reduce losses and enhance efficiency. The operating principles of the proposed circuit are analyzed in detail, and the characteristic and parameter design analysis, including current conversion ratio, transformer turn ratio, power inductors, and resonant capacitors and inductor, are presented. Finally, the experimental results based on a 100 W experimental prototype validate the feasibility of the proposed converter. Full article

Since 2017, there has been a considerable increase in the recorded sea salt aerosol (SSA) levels across the United States, particularly the economically critical Baltimore–Washington Corridor (BWC). This unexpected escalation, as reported in the Environmental Protection Agency’s (EPA) annual air quality report, has generated worries about the potential effects on air quality, public health, and regional climate dynamics. However, this technical note demonstrates that the apparent rise in SSA levels is mostly due to a change in the EPA’s Chemical Speciation Network’s (CSN) approach to measuring these aerosols. In 2017, the CSN switched from utilizing chlorine to chloride as a tracer for SSAs. Speciation data for this region show that chloride concentrations are often an order of magnitude greater than chlorine concentrations, explaining the significant increase in SSA levels following the methodological modification. The absence of a similar spike in SSA levels at the nearby IMPROVE site, which has been consistent with its methodology, provides more evidence to corroborate this conclusion. These findings demonstrate the importance of methodological consistency and openness in environmental monitoring networks. Clear documentation of such changes is critical to avoiding data misunderstanding, which might lead to the development of incorrect public health and environmental policies. We advocate for continued collaboration among researchers to establish standardized measuring procedures and data analysis tools to accommodate and clarify methodological changes, resulting in accurate environmental evaluations and informed decision-making. Full article

Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human–robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing. Full article

The Han River Estuary (HRE), Yellow Sea, forms part of the border between South Korea and North Korea, and these two countries are militarily hostile. Since the HRE has quite excellent ecological integrity, the task of preserving it well is emerging as important. Thus, the South Korean Government is attempting to preserve the ecological integrity of the HRE through interstate cooperation. By employing contingent valuation, this study delves into South Korean households’ willingness to pay (WTP) for this preservation. One thousand households nationwide were sampled and surveyed through face-to-face individual interviews. Annual household income tax was selected as the payment vehicle. Dichotomous choice questioning was chosen as the WTP induction method. A spike model was selected as a method for modelling a WTP of zero. The main results showed statistical significance. Annual WTP per household and national WTP were obtained as KRW 4487 (USD 3.92) and KRW 125.75 billion (USD 109.83 million), respectively. When a 10-year payment period and a 4.5% discount rate were adopted, the value was KRW 766.14 billion (USD 669.12 million). South Korean households placed considerable value on the preservation of the ecological integrity of the HRE through interstate cooperation. Full article

Feature capture and recognition of sea wave components in radar systems especially in global navigation satellite system reflectometry (GNSS-R) using signal processing approaches or computer simulative methods has become a research hotspot in recent years. At the same time, parameter inversion of marine phenomena from the discovered characteristics plays a significant role in monitoring and forewarning the different components of sea waves. This paper aims to investigate the impact of multiple parameters, such as the wind speed, directionality variable, wave amplitude, wave length, and directions of sea wave components, on the delay waveform of the delay–Doppler map (DDM). Two types of wind waves and the 2-D sinusoidal sea surface are chosen to be analyzed. By comparing and analyzing the discrepancy of delay waveforms under different conditions, it can be concluded that the increased MSS which arises from the increase in the roughness of the sea surface can lead to the difference in the peak value or trial edges exhibited in delay waveforms. The values of delay waveforms at zero chip along the increasing direction of long-crest wind waves exhibit the periodic spikes shape, which is the opposite of the short-crest wind waves, and the fluctuation of the periodic profiles decreases with the increase in the amplitude of waves. The results and conclusions can provide a foundation for the parameter inversion, tracking, and early warning of anomalous formations of waves in bistatic radar configuration. Full article

This five-year study (2016–2021) across diverse Moroccan agro-climatic zones investigated genotype by environment (G × E) interactions in wheat, focusing on variations in agronomic traits and quality attributes such as protein and gluten content. Significant environmental effects were observed on key traits, like yield, thousand kernel weight (TKW), and spikes per square meter (Spk/m²), highlighting environmental factors’ role in wheat yield variability. In the Tassaout (TST) location, notable genotypic effects emerged for traits like biomass, underscoring genetic factors’ importance in specific contexts, while in Sidi El Aidi (SEA) and Marchouch (MCH), genotypic effects on yield and its components were predominantly absent, indicating a more substantial environmental influence. These findings illustrate the complexity of G × E interactions and the need for breeding strategies considering genetic potential and environmental adaptability, especially given the trade-offs between yield enhancement and quality maintenance. Insights from the biplot and heatmap analyses enhanced the understanding of genotypes’ dynamic interactions with environmental factors, establishing a basis for strategic genotype selection and management to optimize wheat yield and quality. This research contributes to sustainable wheat breeding in Morocco, aligning with global efforts to adapt wheat breeding strategies to changing climatic conditions. Full article