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Natural products-based Janus hydrophilic/hydrophobic membrane for efficient scaling-resistance and photothermal membrane distillation
No full textFreshwater scarcity has gradually become a serious global water crisis that needs to be solved urgently. Membrane distillation (MD) has been regarded as a promising desalination technology due to its merits compared with other desalination technologies, including high rejection of non-volatile components and superior feed water salinity tolerance. However, the conventional MD faces several challenges, including thermal loss and membrane scaling. Here, we develop a natural products-based Janus sodium alginate/melanin nanoparticles-composited polyvinylidene fluoride membrane (SA-M-PVDF membrane) with outstanding photothermal effect and high hydrophilicity, which can allow the SA-M-PVDF membrane to present excellent photothermal membrane distillation (PMD) performance and scaling-resistance property respectively, thus can solve the hard problems of thermal loss and frequent membrane scaling. Moreover, owing to the biomaterial characters of melanin nanoparticles and SA, the synthesis of SA-M-PVDF membrane circumvents risk of secondary pollution to product water. As expected, the SA-M-PVDF membrane showed excellent PMD performance with 96.5% solar energy utilization efficiency. The SA-M-PVDF membrane exhibited high scaling-resistance ability and robust structural stability, sustaining over 40 hours of continuous PMD operation with high-salinity feed, prospectively providing a facile and environmental approach for sustainably alleviating the freshwater and energy shortage.This work was supported by the Key R&D Plan of Shaanxi Province, China (No. 2022NY-006)
Integration of sentinel-2 data into the SIMETAW model for assessing irrigation water requirements and evapotranspiration
No full textWater management for crop irrigation has become a major consideration given the global scale implications of climate change and its impacts on water scarcity and security, with an increasing frequency of water restrictions in many locations during the summer months. As a consequence, decision-support tools are needed to evaluate scenarios of various agricultural practices in order to provide improved water management strategies. In this study, water requirements of orchards were assessed at the plot scale using the Simulation of Evapo-Transpiration of Applied Water (SIMETAW) model. This model was applied across a small Mediterranean watershed to evaluate and compare various water use scenarios. The standard version of SIMETAW integrates a simplified water balance model with a single uniform soil layer to calculate the crop water needs at the plot scale (Quantity of Irrigation QI). Evapotranspiration is computed using a crop coefficient specific to each crop type (Kc) and a water stress coefficient (Ks) derived from the water available in the soil (SWC). In this standard version, plots are categorized by crop type, with fixed Kc unchanged across years and between plots of the same crop type. To better capture the spatial variability of crops at the watershed scale, SIMETAW was modified to incorporate remote sensing data. Kc for each crop in the basin was estimated using the relationship between normalized difference vegetation index (NDVI) and fractional vegetation cover (FCOVER) derived from Sentinel-2 images. The modified SIMETAW model was then compared to the standard version in estimating irrigation water requirements, from the field level to the watershed scale. Model calibration was undertaken using distributed soil moisture measurements collected from 2021 to 2024. Data on water volumes used for irrigation together with farmer surveys were used to assess model performance in simulating QI both at the plot level, for thirteen distributed farms, and at the basin scale. Comparisons between the standard model version and the modified version (i.e. using Kc from remote sensing) are examined in relation to the accuracy of obtained water volumes. The model simulated soil water content (SWC) across the monitored orchards with good accuracy, providing R² values of 0.7 and 0.9 for simulation in 2022 and 2023 respectively. The simulation of the quantity of irrigation water in farms shows a strong correlation with reported data (R= 0.81). The application of the SIMETAW model to all the studied crop types offered an improved performance by incorporating the remote sensed Kc compared against the standard version, with an 17 % improvement of the water irrigation volume distributed against basin averaged irrigation volumes. Overall, the incorporation of Sentinel-2 data significantly enhanced the performance of the model by accounting for the variability in crop development across the catchment scale. By considering a typology of farms according to the irrigation practices (3 classes were defined according to observations and surveys, high, medium and low irrigation), the model was able to estimate water requirements with 10 % difference to the values provided by the manager of the water resources at regional scale (“Association Syndicale Autorisée” - ASA). Such information can prove particularly useful in helping to guide water managers in making informed decisions with regards to the dynamic management of water resources.This study was funded by several research projects, including the PACA region, a collaborative project with King Abdullah University of Science and Technology in Saudi Arabia and funds from INRAE. The authors thank the ASA president who has provided useful data for the validation of this work and the surveyed farmers, who kindly facilitated field access and measurements. The authors would also like to thank the colleagues who contributed their expertise to the processing and acquisition of the data, in particular Mr. Borgo Andrea (CMCC) for the presentation of the model
SymGraphAU: Prior knowledge based symbolic graph for action unit recognition
No full textThe prior and sample-aware semantic association between facial Action Units (AUs) and expressions, which could yield insightful cues for the recognition of AUs, remains underexplored within the existing body of literature. In this paper, we introduce a novel AU recognition method to explicitly explore both AUs and Expressions, incorporating existing knowledge about their relationships. Specifically, we novelly use the Conjunctive Normal Form (CNF) in propositional logic to express these knowledges. Thanks to the flexible and explainable logic proposition, our method can dynamically build a knowledge base specifically for each sample, which is not limited to fixed prior knowledge pattern. Furthermore, a new regularization mechanism is introduced to learn the predefined rules of logical knowledge based on embedding graph convolutional networks. Extensive experiments show that our approach can outperform current state-of-the-art AU recognition methods on the BP4D and DISFA datasets. Our codes will be made publicly available.The authors would like to thank the anonymous reviewers for their constructive suggestions. The work was supported by the National Natural Science Foundation of China under grants no. 62276170, 82261138629, 62306061, the Science and Technology Project of Guangdong Province, China under grants no. 2023A1515011549, 2023A1515010688, the Science and Technology Innovation Commission of Shenzhen, China under grant no. JCYJ20220531101412030, the Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), China under Grant No. GML-KF-24-11, Shenzhen Higher Education Stable Support Program General Project, China under Grant 20231120175215001, and Guangdong Provincial Key Laboratory, China under grant no. 2023B1212060076
Species differences in glycerol-3-phosphate metabolism reveals trade-offs between metabolic adaptations and cell proliferation.
No full textThe temperate climate-adapted brown hare (Lepus europaeus) and the cold-adapted mountain hare (Lepus timidus) are closely related and interfertile species. However, their skin fibroblasts display distinct gene expression profiles related to fundamental cellular processes. This indicates important metabolic divergence between the two species. Through targeted metabolomics and metabolite tracing, we identified species-specific variations in glycerol 3-phosphate (G3P) metabolism. G3P is a key metabolite of the G3P shuttle, which transfers reducing equivalents from cytosolic NADH to the mitochondrial electron transport chain (ETC), consequently regulating glycolysis, lipid metabolism, and mitochondrial bioenergetics. Alterations in G3P metabolism have been implicated in multiple human pathologies including cancer and diabetes. We observed that mountain hare mitochondria exhibit elevated G3P shuttle activity, alongside increased membrane potential and decreased mitochondrial temperature. Silencing mitochondrial G3P dehydrogenase (GPD2), which couples the conversion of G3P to the ETC, uncovered its species-specific role in controlling mitochondrial membrane potential and highlighted its involvement in skin fibroblast thermogenesis. Unexpectedly, GPD2 silencing enhanced wound healing and cell proliferation rates in a species-specific manner. Our study underscores the pivotal role of the G3P shuttle in mediating physiological, bioenergetic, and metabolic divergence between these hare species.S.S. was funded by AFM Telethon (23527), Alfred Kordelin Foundation (200340) and Tampere Institute of Advanced Studies. E.D. and J.P. were funded by the Academy of Finland (R'Life 329264). K.G. was funded by the Doctoral Programme at the Faculty of Medicine and Health Technology of Tampere University (Finland). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Authors acknowledge the support provided by Johanna ten Hoeve at UCLA Metabolomics center, US; Anni I. Nieminen at Biocenter Finland and HiLIFE-funded FIMM Metabolomics Unit, Helsinki, Finland; Young-Tae Chang at POSTECH, Republic of Korea, for providing MTY dye; Teemu O. Ihalainen at Tampere Imaging Facility (TIF), Tampere University, Finland for helping with the imaging; and Howy Jacobs for invaluable feedback and insightful discussions
Data-driven control of fluid flows
No full textData-based control of fluid systems aims at manipulating flows whose dynamics and receptivity to external forcing are known from measurements only. This type of control is particularly attractive for physical systems whose governing equations are elusive or too complex for a model-based approach. Data-based control critically relies on system identification, a discipline that recovers a model equation of a physical system from input-output data streams. In this chapter, we will touch on rudimentary, but fundamental concepts of control setup, system identification, and optimal control design. Identification based on impulse responses, subspace projections, and dynamic observers will be treated, together with model-predictive control algorithms. Applications to generic flow configurations will demonstrate the efficacy and usefulness of these techniques under realistic conditions
Mechanistic insight into the synergy between nickel single atoms and nanoparticles on N-doped carbon for electroreduction of CO2
No full textThe synergy of single atoms (SAs) and nanoparticles (NPs) has demonstrated great potential in promoting the electrocatalytic carbon dioxide reduction reaction (CO2RR); however, the rationalization of the SAs/NPs proportion remains one challenge for the catalyst design. Herein, a Ni2+-loaded porous poly(ionic liquids) (PIL) precursor synthesized through the free radical self-polymerization of the ionic liquid monomer, 1-allyl-3-vinylimidazolium chloride, was pyrolyzed to prepare the Ni, N co-doped carbon materials, in which the proportion of Ni SAs and NPs could be facilely modulated by controlling the annealing temperature. The catalyst Ni-NC-1000 with a moderate proportion of Ni SAs and NPs exhibited high efficiency in the electrocatalytic conversion of CO2 into CO. Operando Ni K-edge X-ray absorption near-edge structure (XANES) spectra and theoretical calculations were conducted to gain insight into the synergy of Ni SAs and NPs. The charge transfer from Ni NPs to the surrounding carbon layer and then to the Ni SAs resulted in the electron-enriched Ni SAs active sites. In the electroreduction of CO2, the co-existence of Ni SAs and NPs strengthened the CO2 activation and the affinity towards the key intermediate of *COOH, lowering the free energy for the potential-determining *CO2 → *COOH step, and therefore promoted the catalysis efficiency.This work was supported by the National Natural Science Foundation of China (grants 22072065, 22178162, and 22222806), the Distinguished Youth Foundation of Jiangsu Province (grant BK20220053), and the Six talent peaks project in Jiangsu Province (grant JNHB-035). The computational resources generously provided by the High Performance Computing Center of Nanjing Tech University are greatly appreciated
Stable <i>Q</i>-compensated viscoelastic reverse-time migration based on the modified fractional Laplacian wave equations
No full textThe attenuation property of earth media can lead to amplitude loss and phase dispersion effects on multicomponent elastic data. Ignoring their impacts during imaging process will result in blurred and dislocated imaging profiles. To accurately characterize the attenuation effect in viscoelastic media, we first derive a new viscoelastic wave equation with decoupled fractional Laplacians. Numerical tests show that the proposed wave equation can accurately capture the propagation characteristics of seismic waves in viscoelastic media. Furthermore, our new wave equation can be modified to yield a decomposition equation, which enables the separated propagation of vector P- and S-wavefields. Building on the derived viscoelastic forward propagator, we develop a stable Q-compensated viscoelastic reverse-time migration approach. Usually, the inner product imaging condition is used to obtain imaging results. However, the result of inner product is affected by the angle between vectors, making the resulting images contaminated with the angle information. In this article, we introduce the magnitude- and sign-based imaging condition for PS imaging and conduct a cross-correlation imaging condition based on the scalar P-wavefield for PP imaging. In contrast to the inner product imaging condition, our imaging scheme is capable of overcoming the contamination by the angle information. In addition, high-frequency noise is amplified exponentially during the attenuation compensation process, affecting imaging precision. To address this problem, we derive the stabilized Q-compensation wave equations explicitly for vector- and scalar wavefields. Numerical examples demonstrate that the proposed Q-compensated viscoelastic reverse-time migration method can effectively correct the viscoelastic effects, yielding high-quality PP- and PS-imaging profiles.Major project of the 14th 5-Year Plan,Grant/Award Number: 2021QNLM020001;Major Scientific and Technological Projectsof Shandong Energy Group, Grant/AwardNumber: SNKJ2022A06-R23; Funds ofCreative Research Groups of China,Grant/Award Number: 41821002; BasicTheoretical Research of Seismic WaveImaging Technology in Complex Oilfield ofChangqing Oilfield Company, Grant/AwardNumber: 2023-1050
Time-modulated phononic crystal of oscillating bimetallic rods
No full textMathematical treatment of space- and time-modulated structures is similar. However, the practical realization of time dependence on elastic properties is a much more difficult problem than the fabrication of a phononic crystal where elastic properties are space periodic. The most common method of temporal modulation is applying AC voltage to a piezoelectric constituent. This method allows high-frequency modulation, but the depth of modulation is relatively weak. Here, we propose a mechanical method of temporal modulation which requires a complicated engineering scheme but provides deep modulation. The scatterers of a phononic crystal are bimetallic rods driven by an external force to oscillate along their axes in a solid (or fluid) matrix. Due to mechanical oscillations, a propagating sound wave suffers time-dependent scattering. High elastic contrast between the components of the bimetallic rods provides deep time modulation and high contrast between the metals and the background matrix provides deep space modulation. The band structure of a mechanically time-modulated phononic crystal is calculated for aluminum-copper rods in an epoxy matrix. Mix band gaps with complex values of ω and k are predicted and analytical properties of the dispersion relation in complex ω-k plane are studied. [This work is supported by the NSF Grant No. 1741677 and by the AFOSR grant FA9550-23-1-0630.
Protecting Images From Manipulations With Deep Optical Signatures
No full textDue to the advancements in deep image generation models, ensuring digital image authenticity, integrity, and confidentiality becomes challenging. While many active image manipulation detection methods embed digital signatures post-image acquisition, the vulnerabilities persist if unauthorized access occurs before this embedding or the embedding software is compromised. This work introduces an optics-based active image manipulation detection approach that learns the structure of a color-coded aperture (CCA), which encodes the light within the camera and embeds a highly reliable and imperceptible optical signature before image acquisition. We optimize our camera model with our proposed image manipulation detection network via end-to-end training. We validate our approach with extensive simulations and a proof-of-concept optical system. The results show that our method outperforms the state-of-the-art active image manipulation detection techniques.This paper was supported by the Vicerrector´ıa de Investigacion y Extensi ´ on UIS ´ , under the project code VIE-3924
Development of High Performance Pyrolized Polyimide-based Carbon Molecular Sieves for Enhanced Selectivity of Propylene/Propane Gas Separation
No full textThe replacement or de-bottlenecking of the highly energy-intensive distillation unit operation process for propylene/propane separation has long posed a formidable challenge. Although membrane technology can potentially offer a more energy-efficient alternative, existing materials lack the requisite mixed-gas selectivity for industrial use. Achieving effective separation for propylene and propane with only 0.13Å difference in molecular size requires membranes with superb molecular sieving properties. Here, we report extremely selective carbon molecular sieve (CMS) materials fabricated by utilizing a triptycene-based intrinsically microporous 4,4′-(hexafluoroisopropylidene)diphthalic anhydride-2,6(7)-diamino triptycene (6FDA-DAT1) polyimide precursor and adjusting its microstructure through finely tuned high-temperature pyrolysis. A freshly prepared isotropic CMS membrane pyrolyzed at 800 °C for 2 h displayed a mixed-gas propylene permeability of 56 Barrer combined with a C3H6/C3H8 selectivity of 66. Notably, after an extended period of continuous mixed-gas testing and aging at 4 bar over 147 days, the CMS membrane exhibited a remarkable increase in mixed-gas propylene/propane selectivity to 152—an unmatched value to date for a CMS material—because of selective tightening of the CMS microstructure by physical aging.This research was supported by funding from King Abdullah University of Science and Technology (BAS/1/1323–01–01)