Considering the Impacts of Metal Depletion on the European Electricity System

The transformation of the European electricity system could generate unintended environment-related trade-offs, e.g., between greenhouse gas emissions and metal depletion. The question thus emerges, how to shape policy packages considering climate change, but without neglecting other environmental and resource-related impacts. In this context, this study analyzes the impacts of different settings of potential policy targets using a multi-criteria analysis in the frame of a coupled energy system and life cycle assessment model. The focus is on the interrelationship between climate change and metal depletion in the future European decarbonized electricity system in 2050, also taking into account total system expenditures of transforming the energy system. The study shows, firstly, that highly ambitious climate policy targets will not allow for any specific resource policy targets. Secondly, smoothing the trade-off is only possible to the extent of one of the policy targets, whereas, thirdly, the potential of recycling as a techno-economic option is limited.</p

Effects of Litchi chinensis fruit isolates on prostaglandin E2 and nitric oxide production in J774 murine macrophage cells

<p>Abstract</p> <p>Background</p> <p><it>Litchi chinensis </it>is regarded as one of the 'heating' fruits in China, which causes serious inflammation symptoms to people.</p> <p>Methods</p> <p>In the current study, the effects of isolates of litchi on prostaglandin E₂(PGE₂) and nitric oxide (NO) production in J774 murine macrophage cells were investigated.</p> <p>Results</p> <p>The AcOEt extract (EAE) of litchi was found effective on stimulating PGE₂production, and three compounds, benzyl alcohol, hydrobenzoin and 5-hydroxymethyl-2-furfurolaldehyde (5-HMF), were isolated and identified from the EAE. Benzyl alcohol caused markedly increase in PGE₂and NO production, compared with lipopolysaccharide (LPS) as positive control, and in a dose-dependent manner. Hydrobenzoin and 5-HMF were found in litchi for the first time, and both of them stimulated PGE₂and NO production moderately in a dose-dependent manner. Besides, regulation of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) mRNA expression and NF-κB (p50) activation might be involved in mechanism of the stimulative process.</p> <p>Conclusion</p> <p>The study showed, some short molecular compounds in litchi play inflammatory effects on human.</p

Crop Phenology Estimation in Rice Fields Using Sentinel-1 GRD SAR Data and Machine Learning-Aided Particle Filtering Approach

Monitoring crop phenology is essential for managing field disasters, protecting the environment, and making decisions about agricultural productivity. Because of its high timeliness, high resolution, great penetration, and sensitivity to specific structural elements, synthetic aperture radar (SAR) is a valuable technique for crop phenology estimation. Particle filtering (PF) belongs to the family of dynamical approach and has the ability to predict crop phenology with SAR data in real time. The observation equation is a key factor affecting the accuracy of particle filtering estimation and depends on fitting. Compared to the common polynomial fitting (POLY), machine learning methods can automatically learn features and handle complex data structures, offering greater flexibility and generalization capabilities. Therefore, incorporating two ensemble learning algorithms consisting of support vector machine regression (SVR), random forest regression (RFR), respectively, we proposed two machine learning-aided particle filtering approaches (PF-SVR, PF-RFR) to estimate crop phenology. One year of time-series Sentinel-1 GRD SAR data in 2017 covering rice fields in Sevilla region in Spain was used for establishing the observation and prediction equations, and the other year of data in 2018 was used for validating the prediction accuracy of PF methods. Four polarization features (VV, VH, VH/VV and Radar Vegetation Index (RVI)) were exploited as the observations in modeling. Experimental results reveals that the machine learning-aided methods are superior than the PF-POLY method. The PF-SVR exhibited better performance than the PF-RFR and PF-POLY methods. The optimal outcome from PF-SVR yielded a root-mean-square error (RMSE) of 7.79, compared to 7.94 for PF-RFR and 9.1 for PF-POLY. Moreover, the results suggest that the RVI is generally more sensitive than other features to crop phenology and the performance of polarization features presented consistent among all methods, i.e., RVI＞VV＞VH＞VH/VV. Our findings offer valuable references for real-time crop phenology monitoring with SAR data

MomentDiff: Generative Video Moment Retrieval from Random to Real

Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language description. To achieve this goal, we provide a generative diffusion-based framework called MomentDiff, which simulates a typical human retrieval process from random browsing to gradual localization. Specifically, we first diffuse the real span to random noise, and learn to denoise the random noise to the original span with the guidance of similarity between text and video. This allows the model to learn a mapping from arbitrary random locations to real moments, enabling the ability to locate segments from random initialization. Once trained, MomentDiff could sample random temporal segments as initial guesses and iteratively refine them to generate an accurate temporal boundary. Different from discriminative works (e.g., based on learnable proposals or queries), MomentDiff with random initialized spans could resist the temporal location biases from datasets. To evaluate the influence of the temporal location biases, we propose two anti-bias datasets with location distribution shifts, named Charades-STA-Len and Charades-STA-Mom. The experimental results demonstrate that our efficient framework consistently outperforms state-of-the-art methods on three public benchmarks, and exhibits better generalization and robustness on the proposed anti-bias datasets. The code, model, and anti-bias evaluation datasets are available at https://github.com/IMCCretrieval/MomentDiff.Comment: 12 pages, 5 figure

Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques

Surface soil moisture (SM) retrieval over agricultural areas from polarimetric synthetic aperture radar (PolSAR) has long been restricted by vegetation attenuation, simplified polarimetric scattering modelling, and limited SAR measurements. This study proposes a modified polarimetric decomposition framework to retrieve SM from multi-incidence and multitemporal PolSAR observations. The framework is constructed by combining the X-Bragg model, the extended double Fresnel scattering model and the generalised volume scattering model (GVSM). Compared with traditional decomposition models, the proposed framework considers the depolarisation of dihedral scattering and the diverse vegetation contribution. Under the assumption that SM is invariant for the PolSAR observations at two different incidence angles and that vegetation scattering does not change between two consecutive measurements, analytical parameter solutions, including the dielectric constant of soil and crop stem, can be obtained by solving multivariable nonlinear equations. The proposed framework is applied to the time series of L-band uninhabited aerial vehicle synthetic aperture radar data acquired during the Soil Moisture Active Passive Validation Experiment in 2012. In this study, we assess retrieval performance by comparing the inversion results with in-situ measurements over bean, canola, corn, soybean, wheat and winter wheat areas and comparing the different performance of SM retrieval between the GVSM and Yamaguchi volume scattering models. Given that SM estimation is inherently influenced by crop phenology and empirical parameters which are introduced in the scattering models, we also investigate the influence of surface depolarisation angle and co-pol phase difference on SM estimation. Results show that the proposed retrieval framework provides an inversion accuracy of RMSE<6.0% and a correlation of R≥0.6 with an inversion rate larger than 90%. Over wheat and winter wheat fields, a correlation of 0.8 between SM estimates and measurements is observed when the surface scattering is dominant. Specifically, stem permittivity, which is retrieved synchronously with SM also shows a linear relationship with crop biomass and plant water content over bean, corn, soybean and wheat fields. We also find that a priori knowledge of surface depolarisation angle, co-pol phase difference and adaptive volume scattering could help to improve the performance of the proposed SM retrieval framework. However, the GVSM model is still not fully adaptive because the co-pol power ratio of volume scattering is potentially influenced by ground scattering.This work was supported by the National Natural Science Foundation of China [grant numbers 61971318, 41771377, 41901286, 42071295, 41901284, U2033216]; the China Postdoctoral Science Foundation [grant number 2018M642914]. This work was supported in part by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI), and the European Funds for Regional Development (EFRD) under Project TEC2017-85244-C2-1-P

Quantum geometric-induced third-order nonlinear transport in antiferromagnetic topological insulator MnBi2Te4

Discovering the nonlinear transport features in antiferromagnets is of fundamental interest in condensed matter physics as it offers a new frontier of the understanding deep connections between multiple degrees of freedom, including magnetic orders, symmetries, and band geometric properties. Antiferromagnetic topological insulator MnBi${_2}$Te${_4}$ has provided a highly tunable platform for experimental explorations due to its rich magnetic structures and striking topological band structures. Here, we experimentally investigate the third-order nonlinear transport properties in bulk MnBi${_2}$Te${_4}$ flakes. The measured third-harmonic longitudinal ($V_{xx}^{3{\omega}}$) and transverse ($V_{xy}^{3{\omega}}$) voltages show intimate connection with magnetic transitions of MnBi${_2}$Te${_4}$ flakes and their magnitudes change abruptly as MnBi${_2}$Te${_4}$ flakes go through magnetic transitions with varying temperature and magnetic fields. In addition, the measured $V_{xx}^{3{\omega}}$ exhibits an even-symmetric feature with changing magnetic field direction and the $V_{xy}^{3{\omega}}$ shows an odd-symmetric property, which are believed to be related to the quantum metric and the emergency of non-zero Berry curvature quadrupole with broken ${PT}$ symmetry and non-degenerate band structures under external magnetic fields, respectively. Our work shows great advances in the understanding of the underlying interactions between multiple geometric quantities

Spinal infection caused by Aspergillus flavus in a diabetic: a case report and literature review

Spinal infections, notably those induced by Aspergillus flavus (A. flavus), represent a complex and uncommon clinical challenge. In individuals with diabetes mellitus, the risk is exacerbated due to a compromised immune response and a heightened vulnerability to non-standard pathogens. This case report chronicles the intricate diagnostic and treatment journey of a 59-year-old diabetic patient grappling with a spinal infection attributed to A. flavus. The diagnosis was delayed due to non-specific symptoms and unclear radiological signs. The administration of voriconazole, a targeted antifungal treatment, resulted in a significant clinical and radiological improvement, underscoring its effectiveness in treating such unusual fungal spinal infections; meanwhile, we found that terbinafine hydrochloride also has a similar effect in treating fungal spinal infections. This case underscores the importance of considering fungal causes in spinal infections among diabetic patients and highlights prompt diagnosis and individualized targeted antifungal therapy

Polysaccharides Derived From the Brown Algae Lessonia nigrescens Enhance Salt Stress Tolerance to Wheat Seedlings by Enhancing the Antioxidant System and Modulating Intracellular Ion Concentration

Soil salinity reduces plant growth and is a major factor that causes decreased agricultural productivity worldwide. Seaweed polysaccharides promote crop growth and improve plant resistance to abiotic stress. In this study, polysaccharides from brown seaweed Lessonia nigrescens polysaccharides (LNP) were extracted and further separated and fractionated. Two acidic polysaccharides (LNP-1 and LNP-2) from crude LNP were obtained and characterized. The latter had a lower molecular weight (MW) (40.2 kDa) than the former (63.9 kDa), but had higher uronic acid and sulfate content. Crude LNP and LNP-2 were composed of mannose, glucuronic acid, fucose, and xylose, whereas LNP-1 has little mannose. Moreover, the effects of the three polysaccharides on plant salt tolerance were investigated. The results showed that crude LNP, LNP-1, and LNP-2 promoted the growth of plants, decreased membrane lipid peroxidation, increased the chlorophyll content, improved antioxidant activities, and coordinated the efflux and compartmentation of intracellular ion. All three polysaccharides could induce plant resistance to salt stress, but LNP-2 was more effective than the other two. The present study allowed to conclude that both MW and sulfate degree contribute to salt resistance capability of polysaccharides derived from L. nigrescens

All-Inorganic Perovskite Solar Cells With Both High Open-Circuit Voltage and Stability

Metal halide perovskite solar cells based on all-inorganic CsPbBr3 have attracted considerable attentions recently, due to their high open-circuit voltage and good stability. However, the fabrication of CsPbBr3 film is limited by the poor solubility of cesium precursors in organic solvents by the one-step method. Here, we successfully fabricated CsPbBr3 film solar cells by employing colloid nanocrystal. The effects of technique parameters, including purification times, anneal temperatures, and spin-coating times on film morphology, optical spectra, and device performance are investigated in detail. The highest power conversion efficiency of 4.57% has been achieved based on a large open-circuit voltage of 1.45 V and a large short-circuit current of 9.41 mA cm−2. A large open-circuit voltage results from the reduced non-radiative energy loss channels and defect states while a large short-circuit current is related to the high conductivity induced by the removal of organic ligands with the increased nanocrystal electronic coupling. Furthermore, excellent stability in air is disclosed on the unencapsulated device suggesting the enormous potential for developing high open-circuit photovoltaic devices with high stability in future