The marine sediments of the area of Verde Peninsula - Jabali Island （39°28＇S/62°19%V-40°28＇ S/62°11＇W） Holocene in age （3-2 ky）, and modern beaches contain a significant amount of bioeroded ...The marine sediments of the area of Verde Peninsula - Jabali Island （39°28＇S/62°19%V-40°28＇ S/62°11＇W） Holocene in age （3-2 ky）, and modern beaches contain a significant amount of bioeroded mollusc shells. Fifteen sites were analyzed, in which 20.11% of the mollusc shells （2168 valves） presented bioerosion traces, in 54 species （30 bivalves and 24 gastropods）. Fourteen ichnogenera were reported： Entobia, Maeandropolydora, Iramena, Caulostrepsis, Pennatichnus, Pinaceocladichnus, Trypanites, and Gastrochaenolites （Domichnia）, Gnathichnus and Radulichnus （Pascichnia）, Finichnus and Centrichnus （Fixichnia）, Oichnus （Praedicnia） （macrobioerosion）, y Semidendrina （microbioerosion）, the latter is first reported in mollusc shells in Argentina. Eleven ichnospecies were identified Finichnus peristroma, Maeandropolydora sulcans, Gnathichnus pentax, Pinaceocladichnus onubensis, Caulostrepsis taeniola, Centrichnus eccentricus, Radulichnus inopinatus, Oichnus simplex, Oichnus paraboloides, Oichnus gradatus, and Gastrochaenolites torpedo （lithic remains）. The dominant ichnogenera in the Holocene deposits are Iramena, Entobia and Oichnus. The same ichnogenera are constant with different abundance in the modern beaches, and increasing representation of Pinaceocladichnus and Pennatichnus. The dominant ichnofacies in the Holocene deposits is Trypanites, revealing a benthonic marine community composed of cheilostome bryzoans, clionaid sponges, predator gastropods, regular echinoids, polychaete annelids, bivalves, thallophytas and fungi. Generally, the area was described as a sublittoral, low-energy, stable environment with high rate of oxygenation, and sandy bottoms, with rocky bottoms at Villalonga locality.展开更多
From the Global Historical Climate Network (GHCN-V3), monthly mean summer (DJF) temperature (1856-2012) and total precipitation (1861-2012) are analyzed in correlation with four climate modes and sunspot number to bet...From the Global Historical Climate Network (GHCN-V3), monthly mean summer (DJF) temperature (1856-2012) and total precipitation (1861-2012) are analyzed in correlation with four climate modes and sunspot number to better understand the role of teleconnections on Buenos Aires’ (Argentina) climate. A general increase in temperature and precipitation was observed. Temperature has increased by about 1.8°C and precipitation has increased by about 300 mm in the past century and a half. Indices of Arctic Oscillation (AO), Pacific North American (PNA), Antarctic Oscillation (AAO), and El Nino-Southern Oscillation (ENSO) are evaluated to study their effects on wheat and corn production and export. AO and PNA show strong relationships with precipitation and temperature received. AAO and ENSO show strong negative correlations with precipitation patterns and weak correlations with temperature. Sunspot Number shows a positive correlation with temperature. ENSO phases are strongly linked with the wheat and corn production and export;during El Nino Buenos Aires tends to experience extremely wet summer weather, causing soggy fields and extremely dry summer weather during La Nina causing drought. Both of these conditions result in reducing wheat and corn production and export.展开更多
Introduction: Mechanical or physical restraint is an exceptional therapeutic resource to immobilize a subject and thus guarantee the safety of the patient and/or third parties in the face of high-risk behaviors, but i...Introduction: Mechanical or physical restraint is an exceptional therapeutic resource to immobilize a subject and thus guarantee the safety of the patient and/or third parties in the face of high-risk behaviors, but it entails multiple crossings (bioethical, philosophical, medical, psychological, legal). Framed in the so-called “safety culture” developed by the WHO, based on the Protocol for its implementation of the CABA and attentive to its frequent use in CABA by different hospital services (medical clinic, geriatrics, intensive care and medical guards) we consider it necessary its study in terms of compliance with the risks it entails and its management. Objectives: Identify regulatory compliance with the GCABA Mechanical restraint (MR) Protocol from a patient safety perspective, as well as describe the clinical and medicolegal aspects, and propose the usefulness of a tool for its management and control. Methodology: Observational, descriptive, transversal and prospective work through the analysis of Clinical Records with indication of MR using a rubric-type form. 177 cases were analyzed between September-November 2023 from three hospitals of the Government of the City of Buenos Aires, statistical parameters were applied and graphs were made. Results: Only 12.99% complied with the Protocol. In the mental health specialized hospital compliance was almost 5 times greater than in the general one, and in the emergency services compliance was 12 times greater than in Inpatient services. We found that the start or end time of MR was not recorded and only 43% described the causes/justifications for the indication (mostly in Emergency and Specialized hospitals), with the MR average time being shorter in Emergency. Conclusions: Only 1.3 out of 10 patients reliably completed the Protocol and it was mostly in the mental health specialized hospital and the emergency services. The results show non-compliance behavior in the application and management of the risk that the use of mechanical restraints entails, being causes for criminal litigation. We consider that the checklists are useful to complete the Protocol and thus provide security to patients and professionals.展开更多
Background: The impact of urban air pollution and temperature changes over health is a growing concern for epidemiologists all over the world and particularly for developing countries where fewer studies have been per...Background: The impact of urban air pollution and temperature changes over health is a growing concern for epidemiologists all over the world and particularly for developing countries where fewer studies have been performed. Aim: The main goal of this paper is to analyze the short term effects of changes in temperature and atmospheric carbon monoxide on daily mortality in Buenos Aires, Argentina. Methods: We conducted a time series study focused on three age groups, gender, and cardiovascular and respiratory mortality, with lags up to four days and temporal variables as modifiers. Results: Temperature correlates positively with total mortality for summer months, with a RR = 1.0184 (95%, CI 1.0139, 1.0229) on the same day for each 1℃ increase. In winter this relationship reverses, as 1?C temperature increase exhibit a protective effect with a RR = 0.9894 (95%, CI 0.9864, 0.9924) at the 3 day lag. Carbon monoxide correlates always positively with mortality, with a RR = 1.0369 (95%, CI 1.0206, 1.0534) for each 1 ppm increase, on the previous day. Conclusions: Climate and pollution parameters measured in Buenos Aires City exhibit a correlation with health outcomes. The impacts of temperature and carbon monoxide vary with age and gender, being elderly the most susceptible subgroup. One day after an increase in CO of 1 ppm, about 4% extra deaths can be expected. The correlation found between increases in CO and mortality for greater lags may be ascribed to the role of CO as a chemical marker of urban air pollution, indicating the co-presence of other pollutants.展开更多
Chinese strontium optical clocks help keep the world on time The new mandatory national standard GB 3095-2026,Ambient air quality standards,was jointly released by the Ministry of Ecology and Environment(MEE)and the S...Chinese strontium optical clocks help keep the world on time The new mandatory national standard GB 3095-2026,Ambient air quality standards,was jointly released by the Ministry of Ecology and Environment(MEE)and the State Administration for Market Regulation(SAMR).Two corresponding technical regulations,HJ 633-2026,Technical specifications on ambient air quality index,and HJ 663-2026,Technical specifications for ambient air quality assessment,were released as well.展开更多
Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Exp...Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Expanded operation envelopes of tropical data centers is assessed to analyze the potential for the building energy savings and carbon emission reduction through collaborative analysis of operation modes(OMs),supply air temperature(SAT),and outdoor air temperature(OAT).The OMs of compression vary with the setpoints of SAT,in which the average exergy efficiency of compressors at alternate operation mode is 6.8%and 8.0%lower than that of double and single compression operations.As SAT rises from 20℃to 32℃,the system exergoeconomic factor increases from 5.4%to 8.0%,and the average carbon cost decreases by 36.5%.Additionally,with just an 8.5%increase in exergy cost(i.e.,Case 8)at OAT rising from 30 to 34℃,the high SAT and low refrigerant charges provide considerable exergy cost advantages versus resisting the OAT fluctuations.Dynamic operation strategies are also proposed and compared to cope with the impacts of tropical environments.Compared to the 26℃SAT baseline,the average energy savings are 9.1-14.7%,indicating the ability to fully utilize outdoor and indoor conditions.展开更多
The Mechanism for Air pollution compleX version 1.0(MAX1),describing detailed tropospheric chemical processes,has been developed based on the latest knowledge.MAX1 contains 940 reactions,including photolysis,gaseous r...The Mechanism for Air pollution compleX version 1.0(MAX1),describing detailed tropospheric chemical processes,has been developed based on the latest knowledge.MAX1 contains 940 reactions,including photolysis,gaseous reactions,and heterogeneous reactions of 300 species,which is adequate for both box model and climate transport model(CTM)applications.Detailed chemical processes of chlorine chemistry,chemistry of Criegee intermediates,and heterogeneous uptake of HO_(2) and N_(2)O_(5) have been implemented and updated.With this level of explicitness,MAX1 can support investigations into the quantification of secondary pollutant productions and the chemical behavior of the crucial intermediates,such as organic peroxy radicals.Box model and CTM tests were conducted to evaluate the performance of MAX1 from different perspectives.Simulations of MAX1 successfully captured the variation of ozone in all cases tested.Meanwhile,significant improvement was made on predictions of radicals compared to other mechanisms,especially under the low NO_(x) environment,with good similarity to simulations of a nearly explicit chemical mechanism(i.e.,Master Chemical Mechanism)that contains over 17000 reactions.The computational expense of MAX1 is acceptable and it can be applied in atmospheric scientific research and air quality prediction.MAX1 introduces new dimensions in atmospheric chemistry modeling,and its potential application in policymaking is a promising yet exploratory step.It offers improved insights into air quality dynamics,which could assist policymakers in making more informed decisions.However,the translation of its detailed chemical understanding into practical strategies remains an area for further investigation.This model suggests a path towards more nuanced air pollution control methods,contributing to ongoing efforts in environmental management.展开更多
Exposure to urban air pollution during early pregnancy is associated with increased risk for adverse pregnancy outcomes,such as preeclampsia(PE),and there is an urgent need to understand how air pollution affects biol...Exposure to urban air pollution during early pregnancy is associated with increased risk for adverse pregnancy outcomes,such as preeclampsia(PE),and there is an urgent need to understand how air pollution affects biological mechanisms in the placenta.Hofbauer cells(HBCs)are fetal placental macrophages that regulate immune tolerance in the placenta.They are normally polarized towards an anti-inflammatory M2 phenotype but display a more pro-inflammatory M1 phenotype in PE.The ex vivo dual placental perfusion approach uses full term human placentas to study physiological aspects of the placenta.In this study,effects of urban traffic-derived particles of size<2.5μm(PM_(2.5))on placental tissue and HBC polarization was deciphered.To study changes in placental microarchitecture and cell morphology,transmission electron microscopy was applied.In addition,changes in cell surface markers on HBCs were determined by immunohistochemistry.Exposure to PM_(2.5) caused disrupted collagen structures and affected cell organelles in multiple cell types inside placental villi.The resident HBC marker CD163 was not affected by PM_(2.5) exposure,while CD206 was reduced by 60%and CD209 remained unchanged,indicating altered M2 polarization.Additionally,the expression of pro-inflammatory M1 markers CD40(p=0.02)and CD80(p=0.03)in HBCs increased due to urban PM_(2.5) exposure.Urban PM_(2.5) showed detrimental effects on the placenta by disrupting tissue morphology and affecting HBC polarization specifically.These results extend the currently accepted view on properties of HBCs,by demonstrating their ability to react plastically and specifically to different exogenous stimuli.展开更多
Anthropogenic ammonia emissions primarily originate from agriculture,especially field fertilization.These emissions represent nitrogen loss for farmers and contribute to air pollution,posing risks to human health and ...Anthropogenic ammonia emissions primarily originate from agriculture,especially field fertilization.These emissions represent nitrogen loss for farmers and contribute to air pollution,posing risks to human health and the environment.Estimating ammonia emissions is crucial for national inventories and policy-making.Various models exist for predicting emissions,including mechanistic,empirical,and semi-empirical approaches.While machine learning(ML)is widely used in environmental science,its application to ammonia emissions remains limited.In this study,we used 5939 ammonia emission data from 538 trials,extracted from the ALFAM2 database,to train three machine learning methods-random forest,gradient boosting,and lasso-for predicting cumulative ammonia emissions 72 h after manure application.These methods were compared to the semi-empirical ALFAM2 model using an independent test dataset.Random forest(RMSE=4.51,r=0.94,MAE=3.28,Bias=0.92)and gradient boosting(RMSE=6.19,r=0.89,MAE=4.10,Bias=0.51)showed the best performance,while the lasso log-linear model(RMSE=7.30,r=0.84,MAE=5.57,Bias=-1.38)performed worst.Both random forest and gradient boosting outperformed the semi-empirical ALFAM2 model,which showed performance comparable to the lasso model.We then used these models and the ALFAM2 model to compare five slurry management techniques,varying in application method(trailing hoses,trailing shoes,and open slot)and post-application incorporation,across 128 scenarios with different manure types and weather conditions.Compared to broadcast application,alternative techniques reduced emissions by a median of-13.6%to-61.7%.This study highlights the promise of ML models in assessing ammonia emission reduction methods,while emphasizing the importance of evaluating model sensitivity to algorithm choice.展开更多
Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and ...Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and systemic inflammation,as well as whether this association is modified by indoor particulate matter and the underlying mechanisms.In this prospective repeated-measure study among 66 participants,indoor airborne mi-crobiome was characterized using amplicon sequencing and qPCR.Indoor fine particulate matter(PM_(2.5))and inhalable particulate matter(PM10)were measured.Systemic inflammatory biomarkers were assessed,including white blood cell(WBC),neutrophil(NEUT),monocyte,eosinophil counts,and their proportions.Targeted serum amino acid metabolomics were conducted to explore the underlying mechanisms.Linear mixed-effect models re-vealed that bacterial and fungal Simpson diversity were significantly associated with decreased WBC and NEUT.For example,for each interquartile range increase in the bacterial Simpson diversity,WBC and NEUT changed by-4.53%(95%CI:-8.25%,-0.66%)and-5.95%(95%CI:-11.3%,-0.27%),respectively.Notably,increased inflammatory risks of airborne microbial exposure were observed when indoor PM_(2.5) and PM10 levels were below the WHO air quality guidelines.Mediation analyses indicated that dopamine metabolism partially mediated the anti-inflammatory effects of fungal diversity exposure.Overall,our study indicated protection from a diverse indoor microbial environment on cardiovascular health and proposed an underlying mechanism through amino acid metabolism.Additionally,health risks associated with microbial exposure deserve more attention in con-texts of low indoor particulate matter pollution.Further research is necessary to fully disentangle the complex relationships between indoor microbiome,air pollutants,and human health.展开更多
Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,...Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,its feasibility has not been fully explored.This study uses data envelopment analysis and the analytic hierarchy process to establish a development potential index,covering technical efficiency,economic cost,application sce-narios,and charging time and range,with an empirical analysis conducted in Beijing.The findings indicated the high feasibility of replacing OCM with electric alternatives,especially within the low-power range.Based on 2023 registered coding dat1,it is projected that by 2030,electrification could reduce regional average con-centrations of CO,NO_(x),PM_(2.5) and VOCs by 12.2%to 56.4%and reduce CO_(2) by 11.7%to 56.9%.Owing to economic considerations,small-and medium-sized machinery are particularly feasible for electrification.Key recommendations include prioritizing the electrification of forklifts,lifting platforms,and small-sized machinery in high-emission areas,particularly in central urban districts.Policies such as carbon taxes,carbon markets,and performance grading systems are suggested to incentivize electrification,along with expanding high-emission restriction zones and improving energy infrastructure to support widespread electrification.展开更多
The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing ...The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing hull.The original hull was modified by introducing a step to allow air ventilation.Following an assessment of the hull performance,a simulation campaign in calm water was conducted to characterize the hull at various forward speeds and air insufflation rates for a defined single step geometry.Geometric analysis of the air layer thickness beneath the hull for each simulated condition was performed using a novel method for visualizing local air thickness.Additionally,two new parameters were introduced to understand the influence of spray rails on the air volume beneath the hull and to indicate the primary direction of ventilated air escape.A validation campaign and an assessment of uncertainty of the simulation has been conducted.The features offered by the CFD methodology include the evaluation of the air layer thickness as a function of hull velocity and injection flow rate and the air volume distribution beneath the hull.The air injection velocity can be adjusted across various operating conditions,thereby preventing performance or efficiency loss during navigation.Based on these findings,the study highlights the benefits of air insufflation in reducing hull resistance for high-speed planing vessels.This work lays a robust foundation for future research and new promising topics,as the exploration of air insufflation continues to be a topic of contemporary interest within naval architecture and hydrodynamics.展开更多
The rise in noise and air pollution poses severe risks to human health and the environment.Industrial and vehicular emissions release harmful pollutants such as CO_(2),SO_(2),CO,CH_(4),and noise,leading to significant...The rise in noise and air pollution poses severe risks to human health and the environment.Industrial and vehicular emissions release harmful pollutants such as CO_(2),SO_(2),CO,CH_(4),and noise,leading to significant environmental degradation.Monitoring and analyzing pollutant concentrations in real-time is crucial for mitigating these risks.However,existing systems often lack the capacity to monitor both indoor and outdoor environments effectively.This study presents a low-cost,Io'T-based pollution detection system that integrates gas sensors(MQ-135and M(Q-4),a noise sensor(LM393),and a humidity sensor(DHT-22),all connected to a Node MCU(ESP8266)microcontroller.The system leverages cloud-based storage and real-time analytics to monitor harmful gas levels and sound pollution.Sensor data is processed using decision tree algorithms for classification,enabling threshold-based detection with environmental context.A Progressive Web Application(PWA)interface provides tusers with accessible,cross-platform visualizations.Experimental validation demonstrated the system’s ability to detect pollutant concentration variations across both indoor and outdoor settings,with real-time alerts triggered when thresholds were exceeded.The collected data showed consistent classification of normal,warning,and critical states for methane,CO_(2),temperature,humidity,and noise levels.These results confirm the system's reliability in dynamic environmental conditions.The proposed framework offers ascalable,energy-efficient,and user-friendly solution for pollution detectionand public awareness.Future enhancements will focus on extending the sensor suite,improving machine learning accuracy,and integrating meteorological data for predictive pollution modeling.展开更多
Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popul...Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popularly also known as “global dimming and brightening”. These variations have been particularly evident in China, where the SSR substantially declined from the 1960s to the 1990s(dimming), with indications for a trend reversal in the 2000s and a slight recovery(brightening) in recent years. This perspective/review paper will discuss recent updates and remaining challenges regarding our knowledge of the magnitudes, causes, and implications of these variations in SSR worldwide, with a particular emphasis on the developments in China.展开更多
Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead ...Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead to uncertainties or inaccuracies in assessing their impacts.Further investigation of differences between fixed and transient LULCC simulations is needed.Here,we employ the Community Earth System Model(CESM)to analyze contrasting responses of mean and extreme near-surface air temperature to historical land cover change.Our results show that forest cover in Europe generally follows a linear upward trend,while East Asia experiences deforestation processes during the historical period.It is found that temperature changes do not exhibit similar seasonal variation and have regional dependence,with Europe showing more pronounced seasonal variability.It is also demonstrated that using fixed land cover simulations exaggerates the temperature responses,leading to an overestimation of temperatures.In Europe,the overestimation of mean and extreme near-surface air temperature is approximately 0.2℃ and 0.3℃,respectively.However,the overestimation is about 0.1℃ in East Asia.Besides,we further disentangle the local and nonlocal effects in the temperature changes and show that nonlocal atmospheric feedbacks dominate the temperature responses in Europe,while local and nonlocal effects exhibit similar temperature variations in East Asia.Further efforts to explore the nonlocal effects of realistic land cover change could help enhance our understanding of climatic effects of land cover change at midlatitudes.展开更多
Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-netwo...Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.展开更多
The algorithm is designed to solve the global problem of multi-objective optimization with constraints in the context of greenhouse gas assessment and mitigation.Artificial intelligence provides unique opportunities f...The algorithm is designed to solve the global problem of multi-objective optimization with constraints in the context of greenhouse gas assessment and mitigation.Artificial intelligence provides unique opportunities for analyzing large amounts of data and identifying hidden relationships between various factors affecting emissions.The use of AI makes it possible to develop effective emission reduction strategies,predict the consequences of various scenarios,and evaluate the effectiveness of decisions made.Machine learning algorithms are capable of modeling complex systems such as energy infrastructure,transportation,and industry to determine the best ways to minimize emissions.The greenhouse effect and related climate change pose one of the most serious threats to our future.Innovative approaches and modern technologies are needed to effectively combat these problems.Government intelligence,in particular,Giga Chat,offers a variety of services for analysts,forecasting,and user support.Their use can significantly accelerate the transition to sustainable development and achieve the goals of the Paris Agreement to limit global temperature growth to 1.5℃.However,realizing the potential of AI requires careful preparation and consideration of many factors,including data quality,ethics,and technical aspects.Only through the joint efforts of scientists,politicians,and society will we be able to overcome the challenge of climate change and build a future that is safe for future generations.展开更多
With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,exist...With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.展开更多
The optimized Grok algorithm can significantly improve the accuracy of time series analysis and understanding the dynamics of climate change.Fine-tuned Grok architecture can be used to monitor and analyze climate proc...The optimized Grok algorithm can significantly improve the accuracy of time series analysis and understanding the dynamics of climate change.Fine-tuned Grok architecture can be used to monitor and analyze climate processes.The main aim is to analyze the Fine-tuned Grok architecture for research on climate change,world ecology,carbon dioxide growth,and carbon funds.The global challenges of climate change and ecological degradation demand innovative analytical approaches capable of processing vast,multivariate,and non-linear datasets.Concurrently,the global financial system,deeply intertwined with energy transitions and sustainable development,requires sophisticated tools for risk assessment and investment strategy in a changing world.Fine-tuned Grok architecture model helps to plan strategies for adaptation to climate change by calculating the optimal allocation of resources,taking into account risks and reducing losses.Due to its ability to respond quickly to new conditions,the system will be able to quickly adjust evacuation plans,deploy protective structures,and distribute assistance to affected regions.The use of artificial intelligence significantly expands the capabilities of the scientific community and authorities in monitoring,assessing,and managing climate change.The optimized Fine-tuned Grok architecture opens the way to a new level of informed decision-making about climate change and ensuring the safety of our future generations.展开更多
基金CONICETPICT 468(ANPCYT) for providing financial support to this research project
文摘The marine sediments of the area of Verde Peninsula - Jabali Island （39°28＇S/62°19%V-40°28＇ S/62°11＇W） Holocene in age （3-2 ky）, and modern beaches contain a significant amount of bioeroded mollusc shells. Fifteen sites were analyzed, in which 20.11% of the mollusc shells （2168 valves） presented bioerosion traces, in 54 species （30 bivalves and 24 gastropods）. Fourteen ichnogenera were reported： Entobia, Maeandropolydora, Iramena, Caulostrepsis, Pennatichnus, Pinaceocladichnus, Trypanites, and Gastrochaenolites （Domichnia）, Gnathichnus and Radulichnus （Pascichnia）, Finichnus and Centrichnus （Fixichnia）, Oichnus （Praedicnia） （macrobioerosion）, y Semidendrina （microbioerosion）, the latter is first reported in mollusc shells in Argentina. Eleven ichnospecies were identified Finichnus peristroma, Maeandropolydora sulcans, Gnathichnus pentax, Pinaceocladichnus onubensis, Caulostrepsis taeniola, Centrichnus eccentricus, Radulichnus inopinatus, Oichnus simplex, Oichnus paraboloides, Oichnus gradatus, and Gastrochaenolites torpedo （lithic remains）. The dominant ichnogenera in the Holocene deposits are Iramena, Entobia and Oichnus. The same ichnogenera are constant with different abundance in the modern beaches, and increasing representation of Pinaceocladichnus and Pennatichnus. The dominant ichnofacies in the Holocene deposits is Trypanites, revealing a benthonic marine community composed of cheilostome bryzoans, clionaid sponges, predator gastropods, regular echinoids, polychaete annelids, bivalves, thallophytas and fungi. Generally, the area was described as a sublittoral, low-energy, stable environment with high rate of oxygenation, and sandy bottoms, with rocky bottoms at Villalonga locality.
文摘From the Global Historical Climate Network (GHCN-V3), monthly mean summer (DJF) temperature (1856-2012) and total precipitation (1861-2012) are analyzed in correlation with four climate modes and sunspot number to better understand the role of teleconnections on Buenos Aires’ (Argentina) climate. A general increase in temperature and precipitation was observed. Temperature has increased by about 1.8°C and precipitation has increased by about 300 mm in the past century and a half. Indices of Arctic Oscillation (AO), Pacific North American (PNA), Antarctic Oscillation (AAO), and El Nino-Southern Oscillation (ENSO) are evaluated to study their effects on wheat and corn production and export. AO and PNA show strong relationships with precipitation and temperature received. AAO and ENSO show strong negative correlations with precipitation patterns and weak correlations with temperature. Sunspot Number shows a positive correlation with temperature. ENSO phases are strongly linked with the wheat and corn production and export;during El Nino Buenos Aires tends to experience extremely wet summer weather, causing soggy fields and extremely dry summer weather during La Nina causing drought. Both of these conditions result in reducing wheat and corn production and export.
文摘Introduction: Mechanical or physical restraint is an exceptional therapeutic resource to immobilize a subject and thus guarantee the safety of the patient and/or third parties in the face of high-risk behaviors, but it entails multiple crossings (bioethical, philosophical, medical, psychological, legal). Framed in the so-called “safety culture” developed by the WHO, based on the Protocol for its implementation of the CABA and attentive to its frequent use in CABA by different hospital services (medical clinic, geriatrics, intensive care and medical guards) we consider it necessary its study in terms of compliance with the risks it entails and its management. Objectives: Identify regulatory compliance with the GCABA Mechanical restraint (MR) Protocol from a patient safety perspective, as well as describe the clinical and medicolegal aspects, and propose the usefulness of a tool for its management and control. Methodology: Observational, descriptive, transversal and prospective work through the analysis of Clinical Records with indication of MR using a rubric-type form. 177 cases were analyzed between September-November 2023 from three hospitals of the Government of the City of Buenos Aires, statistical parameters were applied and graphs were made. Results: Only 12.99% complied with the Protocol. In the mental health specialized hospital compliance was almost 5 times greater than in the general one, and in the emergency services compliance was 12 times greater than in Inpatient services. We found that the start or end time of MR was not recorded and only 43% described the causes/justifications for the indication (mostly in Emergency and Specialized hospitals), with the MR average time being shorter in Emergency. Conclusions: Only 1.3 out of 10 patients reliably completed the Protocol and it was mostly in the mental health specialized hospital and the emergency services. The results show non-compliance behavior in the application and management of the risk that the use of mechanical restraints entails, being causes for criminal litigation. We consider that the checklists are useful to complete the Protocol and thus provide security to patients and professionals.
文摘Background: The impact of urban air pollution and temperature changes over health is a growing concern for epidemiologists all over the world and particularly for developing countries where fewer studies have been performed. Aim: The main goal of this paper is to analyze the short term effects of changes in temperature and atmospheric carbon monoxide on daily mortality in Buenos Aires, Argentina. Methods: We conducted a time series study focused on three age groups, gender, and cardiovascular and respiratory mortality, with lags up to four days and temporal variables as modifiers. Results: Temperature correlates positively with total mortality for summer months, with a RR = 1.0184 (95%, CI 1.0139, 1.0229) on the same day for each 1℃ increase. In winter this relationship reverses, as 1?C temperature increase exhibit a protective effect with a RR = 0.9894 (95%, CI 0.9864, 0.9924) at the 3 day lag. Carbon monoxide correlates always positively with mortality, with a RR = 1.0369 (95%, CI 1.0206, 1.0534) for each 1 ppm increase, on the previous day. Conclusions: Climate and pollution parameters measured in Buenos Aires City exhibit a correlation with health outcomes. The impacts of temperature and carbon monoxide vary with age and gender, being elderly the most susceptible subgroup. One day after an increase in CO of 1 ppm, about 4% extra deaths can be expected. The correlation found between increases in CO and mortality for greater lags may be ascribed to the role of CO as a chemical marker of urban air pollution, indicating the co-presence of other pollutants.
文摘Chinese strontium optical clocks help keep the world on time The new mandatory national standard GB 3095-2026,Ambient air quality standards,was jointly released by the Ministry of Ecology and Environment(MEE)and the State Administration for Market Regulation(SAMR).Two corresponding technical regulations,HJ 633-2026,Technical specifications on ambient air quality index,and HJ 663-2026,Technical specifications for ambient air quality assessment,were released as well.
基金supported by the National Research Foundation,Singapore,funded under Energy Research Testbed and Industry Partnership Funding Initiative,part of the Energy Grid(EG)2.0 programme.
文摘Rapid developments in the electronic information industry drive the increased energy usage and carbon emission of data center buildings,prompting the focus on the energy efficiency and environmental sustainability.Expanded operation envelopes of tropical data centers is assessed to analyze the potential for the building energy savings and carbon emission reduction through collaborative analysis of operation modes(OMs),supply air temperature(SAT),and outdoor air temperature(OAT).The OMs of compression vary with the setpoints of SAT,in which the average exergy efficiency of compressors at alternate operation mode is 6.8%and 8.0%lower than that of double and single compression operations.As SAT rises from 20℃to 32℃,the system exergoeconomic factor increases from 5.4%to 8.0%,and the average carbon cost decreases by 36.5%.Additionally,with just an 8.5%increase in exergy cost(i.e.,Case 8)at OAT rising from 30 to 34℃,the high SAT and low refrigerant charges provide considerable exergy cost advantages versus resisting the OAT fluctuations.Dynamic operation strategies are also proposed and compared to cope with the impacts of tropical environments.Compared to the 26℃SAT baseline,the average energy savings are 9.1-14.7%,indicating the ability to fully utilize outdoor and indoor conditions.
基金supported by the National Natural Science Foundation of China(Grant Nos.22325601,92044302,42377105)the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”.
文摘The Mechanism for Air pollution compleX version 1.0(MAX1),describing detailed tropospheric chemical processes,has been developed based on the latest knowledge.MAX1 contains 940 reactions,including photolysis,gaseous reactions,and heterogeneous reactions of 300 species,which is adequate for both box model and climate transport model(CTM)applications.Detailed chemical processes of chlorine chemistry,chemistry of Criegee intermediates,and heterogeneous uptake of HO_(2) and N_(2)O_(5) have been implemented and updated.With this level of explicitness,MAX1 can support investigations into the quantification of secondary pollutant productions and the chemical behavior of the crucial intermediates,such as organic peroxy radicals.Box model and CTM tests were conducted to evaluate the performance of MAX1 from different perspectives.Simulations of MAX1 successfully captured the variation of ozone in all cases tested.Meanwhile,significant improvement was made on predictions of radicals compared to other mechanisms,especially under the low NO_(x) environment,with good similarity to simulations of a nearly explicit chemical mechanism(i.e.,Master Chemical Mechanism)that contains over 17000 reactions.The computational expense of MAX1 is acceptable and it can be applied in atmospheric scientific research and air quality prediction.MAX1 introduces new dimensions in atmospheric chemistry modeling,and its potential application in policymaking is a promising yet exploratory step.It offers improved insights into air quality dynamics,which could assist policymakers in making more informed decisions.However,the translation of its detailed chemical understanding into practical strategies remains an area for further investigation.This model suggests a path towards more nuanced air pollution control methods,contributing to ongoing efforts in environmental management.
基金supported by The Swedish Research Council(Vetenskapsrådet,No.314373.35.135949)ALF+3 种基金SUS FoundationRegion Skånes Foundations in Swedensupported through the PhD program Inflammatory Disorders in Pregnancy(DP-iDP)by the Austrian Science Fund FWF(No.Doc 31-B26)the Medical University of Graz,Austria.
文摘Exposure to urban air pollution during early pregnancy is associated with increased risk for adverse pregnancy outcomes,such as preeclampsia(PE),and there is an urgent need to understand how air pollution affects biological mechanisms in the placenta.Hofbauer cells(HBCs)are fetal placental macrophages that regulate immune tolerance in the placenta.They are normally polarized towards an anti-inflammatory M2 phenotype but display a more pro-inflammatory M1 phenotype in PE.The ex vivo dual placental perfusion approach uses full term human placentas to study physiological aspects of the placenta.In this study,effects of urban traffic-derived particles of size<2.5μm(PM_(2.5))on placental tissue and HBC polarization was deciphered.To study changes in placental microarchitecture and cell morphology,transmission electron microscopy was applied.In addition,changes in cell surface markers on HBCs were determined by immunohistochemistry.Exposure to PM_(2.5) caused disrupted collagen structures and affected cell organelles in multiple cell types inside placental villi.The resident HBC marker CD163 was not affected by PM_(2.5) exposure,while CD206 was reduced by 60%and CD209 remained unchanged,indicating altered M2 polarization.Additionally,the expression of pro-inflammatory M1 markers CD40(p=0.02)and CD80(p=0.03)in HBCs increased due to urban PM_(2.5) exposure.Urban PM_(2.5) showed detrimental effects on the placenta by disrupting tissue morphology and affecting HBC polarization specifically.These results extend the currently accepted view on properties of HBCs,by demonstrating their ability to react plastically and specifically to different exogenous stimuli.
基金the French state aid managed by the ANR under the“Investissements d’avenir”programme with the reference ANR-16-CONV-0003from the AgroEcoSystem department of INRAE.We are grateful to the INRAE MIGALE bioinformatics facility(MIGALE,INRAE,2020.Migale bioinformatics Facility,doi:10.15454/1.5572390655343293E12)for providing help and/or computing and/or storage resources.We are also grateful to Sasha Hafner for his help in reproducing some of the results of Hafner et al.(2019).
文摘Anthropogenic ammonia emissions primarily originate from agriculture,especially field fertilization.These emissions represent nitrogen loss for farmers and contribute to air pollution,posing risks to human health and the environment.Estimating ammonia emissions is crucial for national inventories and policy-making.Various models exist for predicting emissions,including mechanistic,empirical,and semi-empirical approaches.While machine learning(ML)is widely used in environmental science,its application to ammonia emissions remains limited.In this study,we used 5939 ammonia emission data from 538 trials,extracted from the ALFAM2 database,to train three machine learning methods-random forest,gradient boosting,and lasso-for predicting cumulative ammonia emissions 72 h after manure application.These methods were compared to the semi-empirical ALFAM2 model using an independent test dataset.Random forest(RMSE=4.51,r=0.94,MAE=3.28,Bias=0.92)and gradient boosting(RMSE=6.19,r=0.89,MAE=4.10,Bias=0.51)showed the best performance,while the lasso log-linear model(RMSE=7.30,r=0.84,MAE=5.57,Bias=-1.38)performed worst.Both random forest and gradient boosting outperformed the semi-empirical ALFAM2 model,which showed performance comparable to the lasso model.We then used these models and the ALFAM2 model to compare five slurry management techniques,varying in application method(trailing hoses,trailing shoes,and open slot)and post-application incorporation,across 128 scenarios with different manure types and weather conditions.Compared to broadcast application,alternative techniques reduced emissions by a median of-13.6%to-61.7%.This study highlights the promise of ML models in assessing ammonia emission reduction methods,while emphasizing the importance of evaluating model sensitivity to algorithm choice.
基金supported by the National Key Research and Development Program of China(No.2022YFC3702704)the National Natural Science Foundation of China(Nos.22376005,22076006 and 82073506).
文摘Microorganisms constitute an essential component in the indoor environment,which is closely related to hu-man health.However,there is limited evidence regarding the associations between indoor airborne microbiome and systemic inflammation,as well as whether this association is modified by indoor particulate matter and the underlying mechanisms.In this prospective repeated-measure study among 66 participants,indoor airborne mi-crobiome was characterized using amplicon sequencing and qPCR.Indoor fine particulate matter(PM_(2.5))and inhalable particulate matter(PM10)were measured.Systemic inflammatory biomarkers were assessed,including white blood cell(WBC),neutrophil(NEUT),monocyte,eosinophil counts,and their proportions.Targeted serum amino acid metabolomics were conducted to explore the underlying mechanisms.Linear mixed-effect models re-vealed that bacterial and fungal Simpson diversity were significantly associated with decreased WBC and NEUT.For example,for each interquartile range increase in the bacterial Simpson diversity,WBC and NEUT changed by-4.53%(95%CI:-8.25%,-0.66%)and-5.95%(95%CI:-11.3%,-0.27%),respectively.Notably,increased inflammatory risks of airborne microbial exposure were observed when indoor PM_(2.5) and PM10 levels were below the WHO air quality guidelines.Mediation analyses indicated that dopamine metabolism partially mediated the anti-inflammatory effects of fungal diversity exposure.Overall,our study indicated protection from a diverse indoor microbial environment on cardiovascular health and proposed an underlying mechanism through amino acid metabolism.Additionally,health risks associated with microbial exposure deserve more attention in con-texts of low indoor particulate matter pollution.Further research is necessary to fully disentangle the complex relationships between indoor microbiome,air pollutants,and human health.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2024ZD1200200).
文摘Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,its feasibility has not been fully explored.This study uses data envelopment analysis and the analytic hierarchy process to establish a development potential index,covering technical efficiency,economic cost,application sce-narios,and charging time and range,with an empirical analysis conducted in Beijing.The findings indicated the high feasibility of replacing OCM with electric alternatives,especially within the low-power range.Based on 2023 registered coding dat1,it is projected that by 2030,electrification could reduce regional average con-centrations of CO,NO_(x),PM_(2.5) and VOCs by 12.2%to 56.4%and reduce CO_(2) by 11.7%to 56.9%.Owing to economic considerations,small-and medium-sized machinery are particularly feasible for electrification.Key recommendations include prioritizing the electrification of forklifts,lifting platforms,and small-sized machinery in high-emission areas,particularly in central urban districts.Policies such as carbon taxes,carbon markets,and performance grading systems are suggested to incentivize electrification,along with expanding high-emission restriction zones and improving energy infrastructure to support widespread electrification.
基金supported by European Union funding(PON“Ricerca e Innovazione”2014‒2020).
文摘The issue of resistance reduction through hull ventilation is of particular interest in contemporary research.This paper presents multiphase computational fluid dynamics(CFD)simulations with 2-DOF motion of a planing hull.The original hull was modified by introducing a step to allow air ventilation.Following an assessment of the hull performance,a simulation campaign in calm water was conducted to characterize the hull at various forward speeds and air insufflation rates for a defined single step geometry.Geometric analysis of the air layer thickness beneath the hull for each simulated condition was performed using a novel method for visualizing local air thickness.Additionally,two new parameters were introduced to understand the influence of spray rails on the air volume beneath the hull and to indicate the primary direction of ventilated air escape.A validation campaign and an assessment of uncertainty of the simulation has been conducted.The features offered by the CFD methodology include the evaluation of the air layer thickness as a function of hull velocity and injection flow rate and the air volume distribution beneath the hull.The air injection velocity can be adjusted across various operating conditions,thereby preventing performance or efficiency loss during navigation.Based on these findings,the study highlights the benefits of air insufflation in reducing hull resistance for high-speed planing vessels.This work lays a robust foundation for future research and new promising topics,as the exploration of air insufflation continues to be a topic of contemporary interest within naval architecture and hydrodynamics.
文摘The rise in noise and air pollution poses severe risks to human health and the environment.Industrial and vehicular emissions release harmful pollutants such as CO_(2),SO_(2),CO,CH_(4),and noise,leading to significant environmental degradation.Monitoring and analyzing pollutant concentrations in real-time is crucial for mitigating these risks.However,existing systems often lack the capacity to monitor both indoor and outdoor environments effectively.This study presents a low-cost,Io'T-based pollution detection system that integrates gas sensors(MQ-135and M(Q-4),a noise sensor(LM393),and a humidity sensor(DHT-22),all connected to a Node MCU(ESP8266)microcontroller.The system leverages cloud-based storage and real-time analytics to monitor harmful gas levels and sound pollution.Sensor data is processed using decision tree algorithms for classification,enabling threshold-based detection with environmental context.A Progressive Web Application(PWA)interface provides tusers with accessible,cross-platform visualizations.Experimental validation demonstrated the system’s ability to detect pollutant concentration variations across both indoor and outdoor settings,with real-time alerts triggered when thresholds were exceeded.The collected data showed consistent classification of normal,warning,and critical states for methane,CO_(2),temperature,humidity,and noise levels.These results confirm the system's reliability in dynamic environmental conditions.The proposed framework offers ascalable,energy-efficient,and user-friendly solution for pollution detectionand public awareness.Future enhancements will focus on extending the sensor suite,improving machine learning accuracy,and integrating meteorological data for predictive pollution modeling.
基金supported by a sequence of Swiss National Science Foundation Grants (Grant Nos.200021_135395,200020_159938,200020_188601)funding from the Federal Office of Meteorology and Climatology Meteo Swiss within the framework of GCOS Switzerland in support of the Global Energy Balance Archive (GEBA) hosted at ETH Zurich。
文摘Worldwide radiation records suggest that the amount of sunlight received at the Earth's surface(surface solar radiation, SSR) has not been stable over the years, but underwent significant decadal variations, popularly also known as “global dimming and brightening”. These variations have been particularly evident in China, where the SSR substantially declined from the 1960s to the 1990s(dimming), with indications for a trend reversal in the 2000s and a slight recovery(brightening) in recent years. This perspective/review paper will discuss recent updates and remaining challenges regarding our knowledge of the magnitudes, causes, and implications of these variations in SSR worldwide, with a particular emphasis on the developments in China.
基金supported by the National Key R&D Program of China(Grant No.2022YFF0801601).
文摘Previous modeling studies have made significant contributions to understanding the climatic effects of historical land use and land cover change(LULCC).However,the absence of transient land cover simulations may lead to uncertainties or inaccuracies in assessing their impacts.Further investigation of differences between fixed and transient LULCC simulations is needed.Here,we employ the Community Earth System Model(CESM)to analyze contrasting responses of mean and extreme near-surface air temperature to historical land cover change.Our results show that forest cover in Europe generally follows a linear upward trend,while East Asia experiences deforestation processes during the historical period.It is found that temperature changes do not exhibit similar seasonal variation and have regional dependence,with Europe showing more pronounced seasonal variability.It is also demonstrated that using fixed land cover simulations exaggerates the temperature responses,leading to an overestimation of temperatures.In Europe,the overestimation of mean and extreme near-surface air temperature is approximately 0.2℃ and 0.3℃,respectively.However,the overestimation is about 0.1℃ in East Asia.Besides,we further disentangle the local and nonlocal effects in the temperature changes and show that nonlocal atmospheric feedbacks dominate the temperature responses in Europe,while local and nonlocal effects exhibit similar temperature variations in East Asia.Further efforts to explore the nonlocal effects of realistic land cover change could help enhance our understanding of climatic effects of land cover change at midlatitudes.
文摘Transit managers can use Intelligent Transportation System technologies to access large amounts of data to monitor network status.However,the presentation of the data lacks structural information.Existing single-network description technologies are ineffective in representing the temporal and spatial characteristics simultaneously.Therefore,there is a need for complementary methods to address these deficiencies.To address these limitations,this paper proposes an approach that combines Network Snapshots and Temporal Paths for the scheduled system.A dual information network is constructed to assess the degree of operational deviation considering the planning tasks.To validate the effectiveness,discussions are conducted through a modified cosine similarity calculation on theoretical analysis,delay level description,and the ability to identify abnormal dates.Compared to some state-of-the-art methods,the proposed method achieves an average Spearman delay correlation of 0.847 and a relative distance of 3.477.Furthermore,case analyses are invested in regions of China's Mainland,Europe,and the United States,investigating both the overall and sub-regional network fluctuations.To represent the impact of network fluctuations in sub-regions,a response loss value was developed.The times that are prone to fluctuations are also discussed through the classification of time series data.The research can offer a novel approach to system monitoring,providing a research direction that utilizes individual data combined to represent macroscopic states.Our code will be released at https://github.com/daozhong/STPN.git.
基金financed as part of the project“Development of a methodology for instrumental base formation for analysis and modeling of the spatial socio-economic development of systems based on internal reserves in the context of digitalization”(FSEG-2023-0008).
文摘The algorithm is designed to solve the global problem of multi-objective optimization with constraints in the context of greenhouse gas assessment and mitigation.Artificial intelligence provides unique opportunities for analyzing large amounts of data and identifying hidden relationships between various factors affecting emissions.The use of AI makes it possible to develop effective emission reduction strategies,predict the consequences of various scenarios,and evaluate the effectiveness of decisions made.Machine learning algorithms are capable of modeling complex systems such as energy infrastructure,transportation,and industry to determine the best ways to minimize emissions.The greenhouse effect and related climate change pose one of the most serious threats to our future.Innovative approaches and modern technologies are needed to effectively combat these problems.Government intelligence,in particular,Giga Chat,offers a variety of services for analysts,forecasting,and user support.Their use can significantly accelerate the transition to sustainable development and achieve the goals of the Paris Agreement to limit global temperature growth to 1.5℃.However,realizing the potential of AI requires careful preparation and consideration of many factors,including data quality,ethics,and technical aspects.Only through the joint efforts of scientists,politicians,and society will we be able to overcome the challenge of climate change and build a future that is safe for future generations.
基金support of the National Key Research and Development Plan(No.2021YFB3302501)the financial support of the National Science Foundation of China(No.12161076)the financial support of the Fundamental Research Funds for the Central Universities(No.DUT25GF207).
文摘With the rapid development of artificial intelligence,intelligent air combat maneuver decision-making(ACMD)has garnered global attention.Although deep reinforcement learning provides a promising approach to ACMD,existing methods often suffer from rigid reward functions and limited adaptability to evolving adversarial strategies.Moreover,most research assumes open airspace,overlooking the influence of potential obstacles.In this paper,we address one-on-one within-visual-range ACMD in obstructed environments,and propose an improved Soft Actor-Critic(SAC)algorithm trained under a curriculum self-play framework.A maneuver strategy mirroring inference module is integrated to estimate each other's likely positions when visual obstruction occurs.By leveraging curriculum learning to guide progressive experience accumulation and self-play for adversarial evolution,our method enhances both training efficiency and tactical diversity.We further integrate an attention mechanism that dynamically adjusts the weights of sub-rewards,enabling the learned policy to adapt to rapidly changing air combat situations.Numerical simulations demonstrate that our enhanced SAC converges more quickly and achieves higher win rates than other baseline methods.An animation is available at bilibili.com/video/BV1BHVszHE98 for better illustration.
基金financed as part of the project“Development of a methodology for instrumental base formation for analysis and modeling of the spatial socio-economic development of systems based on internal reserves in the context of digitalization”(FSEG-2023-0008).
文摘The optimized Grok algorithm can significantly improve the accuracy of time series analysis and understanding the dynamics of climate change.Fine-tuned Grok architecture can be used to monitor and analyze climate processes.The main aim is to analyze the Fine-tuned Grok architecture for research on climate change,world ecology,carbon dioxide growth,and carbon funds.The global challenges of climate change and ecological degradation demand innovative analytical approaches capable of processing vast,multivariate,and non-linear datasets.Concurrently,the global financial system,deeply intertwined with energy transitions and sustainable development,requires sophisticated tools for risk assessment and investment strategy in a changing world.Fine-tuned Grok architecture model helps to plan strategies for adaptation to climate change by calculating the optimal allocation of resources,taking into account risks and reducing losses.Due to its ability to respond quickly to new conditions,the system will be able to quickly adjust evacuation plans,deploy protective structures,and distribute assistance to affected regions.The use of artificial intelligence significantly expands the capabilities of the scientific community and authorities in monitoring,assessing,and managing climate change.The optimized Fine-tuned Grok architecture opens the way to a new level of informed decision-making about climate change and ensuring the safety of our future generations.
