Concentration-dependent effects of spinetoram on nontarget freshwater microalgae: A comparative study on Chlorella vulgaris and Microcystis aeruginosa.

The rising global demand for agricultural products is leading to the widespread application of pesticides, such as spinetoram, resulting in environmental pollution and ecotoxicity to nontarget organisms in aquatic ecosystems. This research focused on assessing the toxicity of spinetoram at various concentrations (0, 0.01, 0.1, 0.5, 1.0, and 3.0 mg L-1) on two common freshwater microalgae, Chlorella vulgaris and Microcystis aeruginosa, to shed light on the ecotoxicological effects of insecticides. Our findings demonstrate that M. aeruginosa is more sensitive to spinetoram than is C. vulgaris, with a concentration-dependent reduction in the growth rate observed for M. aeruginosa, whereas only the highest concentration of spinetoram adversely affected C. vulgaris. At a concentration of 0.01 mg L-1, the growth rate of M. aeruginosa unexpectedly increased beginning on day 7, indicating a potential hormetic effect. Although initial exposure to spinetoram improved the photosynthetic efficiency of both microalgae strains at all concentrations, detrimental effects became apparent at higher concentrations and with prolonged exposure. The photosynthetic efficiency of C. vulgaris recovered, in contrast to that of M. aeruginosa, which exhibited limited recovery. Spinetoram more significantly inhibited the effective quantum yield of PSII (EQY) in M. aeruginosa than in C. vulgaris. Although spinetoram is not designed to target phytoplankton, its toxicity can disrupt primary productivity and modify phytoplankton-consumer interactions via bottom-up control mechanisms. This study enhances our understanding of spinetoram's ecotoxicity and potential effects on aquatic ecosystems.

Utility of the Python package Geoweaver_cwl for improving workflow reusability: an illustration with multidisciplinary use cases.

Computational workflows are widely used in data analysis, enabling automated tracking of steps and storage of provenance information, leading to innovation and decision-making in the scientific community. However, the growing popularity of workflows has raised concerns about reproducibility and reusability which can hinder collaboration between institutions and users. In order to address these concerns, it is important to standardize workflows or provide tools that offer a framework for describing workflows and enabling computational reusability. One such set of standards that has recently emerged is the Common Workflow Language (CWL), which offers a robust and flexible framework for data analysis tools and workflows. To promote portability, reproducibility, and interoperability of AI/ML workflows, we developed geoweaver_cwl, a Python package that automatically describes AI/ML workflows from a workflow management system (WfMS) named Geoweaver into CWL. In this paper, we test our Python package on multiple use cases from different domains. Our objective is to demonstrate and verify the utility of this package. We make all the code and dataset open online and briefly describe the experimental implementation of the package in this paper, confirming that geoweaver_cwl can lead to a well-versed AI process while disclosing opportunities for further extensions. The geoweaver_cwl package is publicly released online at https://pypi.org/project/geoweaver-cwl/0.0.1/ and exemplar results are accessible at: https://github.com/amrutakale08/geoweaver_cwl-usecases.

Analysis of Structural Parameters of Steel-NC-UHPC Composite Beams.

The cracking of the negative moment area of steel-normal concrete (NC) composite bridges is common owning to the low tensile strength of concrete. In order to solve the problem, Ultra High Performance Concrete (UHPC) is used to enhance the tensile performance of the negative moment area. This paper conducted interface experiments to study the bonding behaviour of the UHPC-NC interface. The design parametric analysis of steel-NC-UHPC composite bridges was carried out based on the interface experimental results. Firstly, slant shear tests and flexural shear tests were carried out to study the rationality of the interface handling methods. Then, the finite element model was used to analyze the state of every component in the composite beams based on experimental results, such as the stress of UHPC, concrete and steel plate. Finally, the calculation results of finite analysis were compared and summarized. It is concluded that (1) the chiseling interface can meet the utilization requirements of physical bridges. The average shear stress and flexural tensile strength of the chiseling interface are 10.29 MPa and 1.93 MPa, respectively. In the failure state, a slight interface damage occurs for specimens with a chiseling interface. (2) The influence on overall performance is different for changes in different design parameters. The thickness of concrete has a significant influence on the stress distribution of composite slabs. (3) Reliable interface simulation is conducted in the finite element models based on interface test results. The stress variation patterns are reflected in the change of design parameters.

Salinity-dependent mitigation of naphthalene toxicity in migratory Takifugu obscurus juveniles: Implications for survival, oxidative stress, and osmoregulation.

Naphthalene, an environmental pollutant classified as a polycyclic aromatic hydrocarbon (PAH), can induce toxicity in fish and other aquatic organisms. Through our investigation, we determined how Takifugu obscurus juveniles were affected by naphthalene (0, 2 mg L-1) exposure in terms of oxidative stress biomarkers and Na+/K+-ATPase activity in various tissues (gill, liver, kidney and muscle) under dissimilar salinities (0, 10 psu). Results suggest that naphthalene exposure significantly affects the survival of T. obscurus juveniles and leads to significant changes in the levels of malondialdehyde, superoxide dismutase, catalase, glutathione, and Na+/K+-ATPase activity, which are indicative of oxidative stress and emphasized the risks associated with osmoregulatory function. The higher salinity affected on the noxious effects of naphthalene can be observed, resulting in decreased biomarker levels and increased Na+/K+-ATPase activity. Salinity levels affected the uptake of naphthalene and its impact on different tissues, with high salinity conditions having mitigating effects on oxidative stress and naphthalene uptake in the liver and kidney tissues. Increased Na+/K+-ATPase activity was observed in all tissues treated with 10 psu and 2 mg L-1 naphthalene. Our findings deepen the understanding of T. obscurus juveniles' physiological responses to naphthalene exposure, and highlight the potential mitigating effects of salinity. These insights can inform the development of appropriate conservation and management practices to protect aquatic organisms from susceptibility.

Preparation of Melatonin-Loaded Nanoparticles with Targeting and Sustained Release Function and Their Application in Osteoarthritis.

(1) The vicious cycle of innate immune response and reactive oxygen species (ROS) generation is an important pathological process of osteoarthritis (OA). Melatonin may be a new hope for the treatment of OA because of its antioxidant capacity. However, the mechanism of melatonin in the treatment of OA is still not completely clear, and the physiological characteristics of articular cartilage make melatonin unable to play a long-term role in OA. (2) The effects of melatonin on ROS and the innate immune response system in OA chondrocytes and the therapeutic effect in vivo were evaluated. Then, a melatonin-loaded nano-delivery system (MT@PLGA-COLBP) was prepared and characterized. Finally, the behavior of MT@PLGA-COLPB in cartilage and the therapeutic effect in OA mice were evaluated. (3) Melatonin can inhibit the activation of the innate immune system by inhibiting the TLR2/4-MyD88-NFκB signal pathway and scavenging ROS, thus improving cartilage matrix metabolism and delaying the progression of OA in vivo. MT@PLGA-COLBP can reach the interior of cartilage and complete the accumulation in OA knee joints. At the same time, it can reduce the number of intra-articular injections and improve the utilization rate of melatonin in vivo. (4) This work provides a new idea for the treatment of osteoarthritis, updates the mechanism of melatonin in the treatment of osteoarthritis, and highlights the application prospect of PLGA@MT-COLBP nanoparticles in preventing OA.

How does lake water clarity affect lake thermal processes?

The objective of this study was to determine the effects of water clarity changes on thermal processes in Lake Poyang, the largest freshwater lake in China, using a physically based lake model embedded in the Community Land Model. A water extinction coefficient (K d ) describing water clarity and controlling radiation penetration in the lake model was used to conduct controlled simulations. Three sets of simulations were conducted for Lake Poyang over the period from 2000 to 2015: DEFAULT with the K d = 0.45 m-1; CTL with the K d = 1.68 m-1 based on a water clarity of 0.85 m; and DARK with the K d = 1.68 m-1 from 2000 to 2005 and K d = 3.44 m-1 based on a water clarity of 0.41 m observed from 2005 to 2015. The simulation results showed that compared with the DEFAULT simulation, the temperature simulations were closer to the observations using the more accurate K d values for the CTL and DARK simulations. Due to decreased water clarity, radiation absorbed in the top 1 m of the water body was larger for the DARK simulation and lower at greater depths than that observed for the CTL simulation. Such changes in radiation penetration in the DARK simulation generated a higher lake water surface temperature (LWST) and thus stronger lake-air interactions from February to July and lower LWST and turbulent fluxes from August to the following January than in the CTL simulation. The temperature inside the lake water body declined markedly, with a significant reduction from June to August that exceeded 5 °C. The results of this study provide an additional reference regarding lake water clarity effects on inland freshwater systems and theoretical support for lake water system management.

An improved typhoon simulation method based on Latin hypercube sampling method.

In order to further improve the prediction accuracy of typhoon simulation method for extreme wind speed in typhoon prone areas, an improved typhoon simulation method is proposed by introducing the Latin hypercube sampling method into the traditional typhoon simulation method. In this paper, the improved typhoon simulation method is first given a detailed introduction. Then, this method is applied to the prediction of extreme wind speeds under various return periods in Hong Kong. To validate this method, two aspects of analysis is carried out, including correlation analysis among typhoon key parameters and prediction of extreme wind speeds under various return periods. The results show that the correlation coefficients among typhoon key parameters can be maintained satisfactorily with this improved typhoon simulation method. The results show that the improved typhoon simulation method can generate the correlations among all typhoon key parameters satisfactorily. Compared with the traditional typhoon simulation method, the improved typhoon simulation method has higher accuracy in predicting the typhoon extreme wind speed in Hong Kong, increasing by about 8% and 11% respectively at 200 m height and gradient height.

The Deep-Time Digital Earth program: data-driven discovery in geosciences.

Current barriers hindering data-driven discoveries in deep-time Earth (DE) include: substantial volumes of DE data are not digitized; many DE databases do not adhere to FAIR (findable, accessible, interoperable and reusable) principles; we lack a systematic knowledge graph for DE; existing DE databases are geographically heterogeneous; a significant fraction of DE data is not in open-access formats; tailored tools are needed. These challenges motivate the Deep-Time Digital Earth (DDE) program initiated by the International Union of Geological Sciences and developed in cooperation with national geological surveys, professional associations, academic institutions and scientists around the world. DDE's mission is to build on previous research to develop a systematic DE knowledge graph, a FAIR data infrastructure that links existing databases and makes dark data visible, and tailored tools for DE data, which are universally accessible. DDE aims to harmonize DE data, share global geoscience knowledge and facilitate data-driven discovery in the understanding of Earth's evolution.

[Gaseous Nitrogen Emission from Soil After Application of NH4+-N Loaded Biochar].

To safely and effectively transfer NH4+-N from eutrophic water to soil, biochar was applied to adsorb NH4+-N from wastewater, and this NH4+-N loaded biochar (N-BC) was subsequently used as a soil amendment. Understanding the influence of N-BC on N2O-N emission and NH3-N volatilization is important for both decreasing the application of chemical fertilizers and reducing gaseous nitrogen loss from soil. In this study, experiments were conducted in soil columns with four treatments, namely CK (no fertilizer), NPK (chemical fertilizer), N-BC+PK (NH4+-N loaded biochar+chemical fertilizer), and BC+NPK (biochar+chemical fertilizer). Compared to both the NPK and BC+NPK treatments, N-BC+PK significantly reduced the cumulative N2O-N emissions and NH3-N volatilization, as well as the total gaseous nitrogen loss from the soil (P<0.05). Relative to NPK and BC+NPK, cumulative N2O-N emissions decreased by 33.62% and 24.64%, cumulative NH3-N volatilization decreased 70.64% and 79.29%, and the cumulative total gaseous nitrogen loss decreased by 64.97% and 73.75%. In particular, BC+NPK significantly enhanced the cumulative NH3-N volatilization. Furthermore, the N2O-N emission flux and NH3-N volatilization rate were significantly positively correlated with the NH4+-N concentration, NO3--N concentration, and pH of soil (P<0.01). Overall, using NH4+-N loaded biochar can significantly decrease N2O-N emissions and NH3-N volatilization, relative to the traditional application combining biochar and chemical fertilizer. This research provides solid theoretical support and data for the application of NH4+-N loaded biochar in soil, to reduce gaseous nitrogen loss.

Nitric acid-modified hydrochar enhance Cd2+ sorption capacity and reduce the Cd2+ accumulation in rice.

Remediating the agricultural soil polluted by cadmium (Cd) is a serious issue in China. Hydrochar showed its potential to purify Cd-contaminated water and improve Cd-contaminated soil due to its vast amounts of macro- and microporous structures. In this study, three concentration gradients of nitric acid (HNO3, mass fraction: 5%, 10%, 15%) were implemented to age pristine wheat straw hydrochar (N0-HC) aiming to improve surface physiochemical properties. Four HNO3-aging hydrochars named N0-HC, N5-HC, N10-HC, N15-HC were used to both remove Cd2+ from aqueous solution and improve soil properties. Results showed that HNO3-aging significantly improved the Cd2+ adsorption capacity by 1.9-9.9 folds compared to crude hydrochar due to the increased specific surface area (by 1.5-6.5 folds) and oxygen-containing functional group abundance (by 4.5-22.1%). Besides, initial solution pH of 8 or environmental temperature of 318.15 K performed the best Cd2+ adsorption capacity. Furthermore, the process of Cd2+ adsorption was fitted best to pseudo-second-order (R2 = 0.95) and Langmuir models (R2 = 0.98), respectively. Nanjing 46 (Oryza sativa L) and HNO3-aging hydrochars were furtherly applied into Cd-contaminated paddy soil to investigate the mitigation of Cd translation from soil to rice. N15-HC-1% (w/w) performed the best effect on reducing cadmium accumulation in various parts of rice plants. Overall, this research provided an approach to improve hydrochar capacity to remove Cd2+ from aqueous solution and mitigate Cd translation from soil to rice.

The role of intermediate products in the changes of China's energy use: index decomposition of the MRIO model.

From the perspective of supply chain, energy consumption is an aggregation of energy intensity, intermediate input ratio, and final demand. However, research on the role of intermediate input on energy consumption is rare. This paper disaggregates the complete demand model of China based on MRIO (multi-region input-output model) into final demands and intermediate demands, and applied a decomposition approach combining LMDI (logarithmic mean Divisia index) and SDA (structural decomposition analysis) to evaluate the contribution of intermediate intensity, integrating the respective advantages of SDA and LMDI. The results show that both domestic and international intermediated intensities promote China's energy consumption growth in most years. The reasons are as follows: (1) the intermediate efficiency enhanced; (2) the final consumption structure shifted toward the more complex pattern; (3) the market demanded more energy-intensive final goods. All effects are positive except the energy intensity effect. Based on the consistency in aggregation of LMDI, we found that the aggregation of international effects is bigger than the aggregation of domestic effects, illustrating that international factors are the main driving force of China's energy consumption. The research implies that the intermediate process deserves more attention for the mitigation of energy consumption and greenhouse gas emissions. Improvement of intermediate efficiency and structure will be effective.

Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau.

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0-10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.

Model-Driven Decision Making in Multiple Sclerosis Research: Existing Works and Latest Trends.

Multiple sclerosis (MS) is a neurological disorder that strikes the central nervous system. Due to the complexity of this disease, healthcare sectors are increasingly in need of shared clinical decision-making tools to provide practitioners with insightful knowledge and information about MS. These tools ought to be comprehensible by both technical and non-technical healthcare audiences. To aid this cause, this literature review analyzes the state-of-the-art decision support systems (DSSs) in MS research with a special focus on model-driven decision-making processes. The review clusters common methodologies used to support the decision-making process in classifying, diagnosing, predicting, and treating MS. This work observes that the majority of the investigated DSSs rely on knowledge-based and machine learning (ML) approaches, so the utilization of ontology and ML in the MS domain is observed to extend the scope of this review. Finally, this review summarizes the state-of-the-art DSSs, discusses the methods that have commonalities, and addresses the future work of applying DSS technologies in the MS field.

The Complexity and Entropy Analysis for Service Game Model Based on Different Expectations and Optimal Pricing.

The internet has provided a new means for manufacturers to reach consumers. On the background of the widespread multichannel sales in China, based on a literature review of the service game and multichannel supply chain, this paper builds a multichannel dynamic service game model where the retailer operates an offline channel and the manufacturer operates an online channel and offers customers the option to buy online and pick up from the retailer's store (BOPS). The manufacturer and the retailer take maximizing the channel profits as their business objectives and make channel service game under optimal pricing. We carry on theoretical analysis of the model and perform numerical simulations from the perspective of entropy theory, game theory, and chaotic dynamics. The results show that the stability of the system will weaken with the increase in service elasticity coefficient and that it is unaffected by the feedback parameter adjustment of the retailer. The BOPS channel strengthens the cooperation between the manufacturer and the retailer and moderates the conflict between the online and the offline channels. The system will go into chaotic state and cause the system's entropy to increase when the manufacturer adjusts his/her service decision quickly. In a chaotic state, the system is sensitive to initial conditions and service input is difficult to predict; the manufacturer and retailer need more additional information to make the system clear or use the method of feedback control to delay or eliminate the occurrence of chaos.