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  • Prediction of bearing capacity of ring footings on cohesive frictional soils using Terzaghi stability factors and Kolmogorov Arnold networks

  • Prasad, S. D. & Chakraborty, M. Bearing capacity of ring footing resting on two layered soil. Comput. Geotech. 134, 104088. https://doi.org/10.1016/j.compgeo.2021.104088 (2021).

    Google Scholar 

  • Seyedi Hosseininia, E. Bearing capacity factors of ring footings. Iran. J. Sci. Technol. Trans. Civil Eng. 40, 121–132. https://doi.org/10.1007/s40996-016-0003-6 (2016).

    Google Scholar 

  • Fisher, K. Zur berechnung der Setzung von fundamenten in der form einer kreisformigen ringflache. Der Bauingenieur. 32, 172–174 (1957).

    Google Scholar 

  • Egorov, K. in Proc. 6 th international conference of soil mechanics and foundation engineering. 41–45.

  • Egorov, K. & Nichiporovich, A. in Proceedings of the 5th international conference on soil mechanics and foundation engineering. 861–866.

  • Milovic, D. in Proc., 8th Int. Conf. on Soil Mechanics and Foundation Engineering. 167–171.

  • Al-Sanad, H. A., Ismael, N. F. & Brenner, R. P. Settlement of circular and ring plates in very dense calcareous sands. J. Geotech. Eng. 119, 622–638. https://doi.org/10.1061/(asce)0733-9410 (1993). (1993)119:4(622).

    Google Scholar 

  • Ismael, N. F. Loading tests on circular and ring plates in very dense cemented sands. J. Geotech. Eng. 122, 281–287. https://doi.org/10.1061/(asce)0733-9410(1996)122:4(281) (1996).

    Google Scholar 

  • Saha, M. Ultimate bearing capacity of ring footings on sand. M. Eng. thesis (1978).

  • Boushehrian, J. & Hataf, N. Experimental and numerical investigation of the bearing capacity of model circular and ring footings on reinforced sand. Geotext. Geomembr. 21, 241–256. https://doi.org/10.1016/s0266-1144(03)00029-3 (2003).

    Google Scholar 

  • Zhao, L. & Wang, J. H. Vertical bearing capacity for ring footings. Comput. Geotech. 35, 292–304. https://doi.org/10.1016/j.compgeo.2007.05.005 (2008).

    Google Scholar 

  • Kumar, J. & Chakraborty, M. Bearing Capacity Factors for Ring Foundations. J. Geotech. GeoEnviron. Eng. 141, https://doi.org/10.1061/(asce)gt.1943-5606.0001345 (2015).

  • Keshavarz, A. & Kumar, J. Bearing capacity computation for a ring foundation using the stress characteristics method. Comput. Geotech. 89, 33–42. https://doi.org/10.1016/j.compgeo.2017.04.006 (2017).

    Google Scholar 

  • Tang, C. & Phoon, K. K. Prediction of bearing capacity of ring foundation on dense sand with regard to stress level effect. Int. J. Geomech. 18 https://doi.org/10.1061/(asce)gm.1943-5622.0001312 (2018).

  • Bui-Ngoc, T., Nguyen, T., Nguyen-Quang, M. T. & Shiau, J. Predicting load-displacement of driven PHC pipe piles using stacking ensemble with Pareto optimization. Eng. Struct. 316 https://doi.org/10.1016/j.engstruct.2024.118574 (2024).

  • Nguyen, T., Ly, D. K., Shiau, J. & Nguyen-Dinh, P. Optimizing load-displacement prediction for bored piles with the 3mSOS algorithm and neural networks. Ocean Eng. 304, 117758. https://doi.org/10.1016/j.oceaneng.2024.117758 (2024).

    Google Scholar 

  • Nguyen-Minh, T., Bui-Ngoc, T., Shiau, J., Nguyen, T. & Nguyen-Thoi, T. Undrained sinkhole stability of circular cavity: a comprehensive approach based on isogeometric analysis coupled with machine learning. Acta Geotech. https://doi.org/10.1007/s11440-024-02266-3 (2024).

    Google Scholar 

  • Shiau, J., Nguyen, T. & Ly-Khuong, D. Unraveling seismic uplift behavior of plate anchors in frictional-cohesive soils: A comprehensive analysis through stability factors and machine learning. Ocean Eng. 297, 116987. https://doi.org/10.1016/j.oceaneng.2024.116987 (2024).

    Google Scholar 

  • Nguyen, D. K., Nguyen, T. P., Ngamkhanong, C., Keawsawasvong, S. & Lai, V. Q. Bearing capacity of ring footings in anisotropic clays: FELA and ANN. Neural Comput. Appl. 35, 10975–10996. https://doi.org/10.1007/s00521-023-08278-6 (2023).

    Google Scholar 

  • Vali, R. et al. Developing a novel big dataset and a deep neural network to predict the bearing capacity of a ring footing. Journal of Rock Mechanics and Geotechnical Engineering, (2024). https://doi.org/10.1016/j.jrmge.2024.02.016

  • Kolmogorov, A. N. On the representation of continuous functions of several variables by superpositions of continuous functions of a smaller number of variables (American Mathematical Society, 1961).

  • Kolmogorov, A. N. On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition. Translations Am. Math. Soc. 2, 55–59 (1963).

    Google Scholar 

  • Liu, Z. et al. Kan: Kolmogorov-arnold networks. arXiv preprint arXiv:2404.19756 (2024).

  • Bolton, M. D. & Lau, C. K. Vertical bearing capacity factors for circular and strip footings on Mohr–Coulomb soil. Can. Geotech. J. 30, 1024–1033. https://doi.org/10.1139/t93-099 (1993).

    Google Scholar 

  • Davis, E. & Booker, J. in Proc. 1st Australian-New Zealand Conf. on Geomechanics, Melbourne. 275–282.

  • Shiau, J., Keawsawasvong, S. & Yodsomjai, W. Determination of support pressure for the design of square box culverts. Int. J. Geomech. 23 https://doi.org/10.1061/(asce)gm.1943-5622.0002620 (2023).

  • Nguyen, T. & Shiau, J. Revisiting active and passive Earth pressure problems using three stability factors. Comput. Geotech. 163, 105759. https://doi.org/10.1016/j.compgeo.2023.105759 (2023).

    Google Scholar 

  • Krabbenhoft, K., Lyamin, A. & Krabbenhoft, J. Optum computational engineering (OptumG2). Computer software (2015).

  • Gholami, H. & Hosseininia, E. S. Bearing capacity factors of ring footings by using the method of characteristics. Geotech. Geol. Eng. 35, 2137–2146. https://doi.org/10.1007/s10706-017-0233-9 (2017).

    Google Scholar 

  • Chavda, J. T. & Dodagoudar, G. R. Finite element evaluation of vertical bearing capacity factors N′c, N′q, N′γ for ring footings. Geotech. Geol. Eng. 37, 741–754. https://doi.org/10.1007/s10706-018-0645-1 (2018).

    Google Scholar 

  • Benmebarek, S., Remadna, M. S., Benmebarek, N. & Belounar, L. Numerical evaluation of the bearing capacity factor of ring footings. Comput. Geotech. 44, 132–138. https://doi.org/10.1016/j.compgeo.2012.04.004 (2012).

    Google Scholar 

  • Mangalathu, S., Hwang, S. H. & Jeon, J. S. Failure mode and effects analysis of RC members based on machine-learning-based SHapley additive explanations (SHAP) approach. Eng. Struct. 219, 110927. https://doi.org/10.1016/j.engstruct.2020.110927 (2020).

    Google Scholar 

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  • Stanford Faces Oregon in San Francisco – Stanford Cardinal

    Stanford Faces Oregon in San Francisco – Stanford Cardinal

    THE GAME: Stanford (10-2) plays its penultimate nonconference contest against Oregon (12-1) in the Invisalign Bay Area Women’s Classic at Chase Center on Sunday, Dec. 21 at 3 p.m. Beth Mowins and Andraya Carter have the call on ESPN and Tim…

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  • What is WhatsApp ghost pairing? The new silent way scammers use to secretly access your messages and photos

    What is WhatsApp ghost pairing? The new silent way scammers use to secretly access your messages and photos

    A new WhatsApp threat, ‘ghost pairing,’ is silently compromising user privacy. Scammers trick individuals into linking their accounts via fake verification codes or QR scans. This allows attackers to view conversations in real-time without the victim’s knowledge. Users must remain vigilant, regularly check linked devices, and never share sensitive codes to prevent data misuse and privacy breaches.

    WhatsApp has become like our companion, next ‘click’ that helps us communicate in personal and professional settings. The green white interface integrated with various features and generative Meta AI is probably also one of the most recognised by children who use the app for chatting with friends and be connected in school groups.But with the platform’s growing popularity every day, the methods used by cybercriminals exploit trust and familiarity. One such emerging threat is WhatsApp ghost pairing. It is not something that becomes immediately obvious. Instead, it works quietly in the background, often going unnoticed until real damage is done.The problem has become pretty alarming as the victims may unknowingly continue using WhatsApp normally. They might remain unaware that someone else is watching their conversations in real time. Unlike traditional hacking, this does not always involve stealing passwords or breaking security systems directly.

    WhatsApp ghost pairing

    WhatsApp ghost pairing: What does this mean and how to protect yourself from the scam

    How WhatsApp ghost pairing works

    WhatsApp ghost pairing uses the “Linked Devices” feature. A scammer tricks a user into sharing a verification code or scanning a QR code, mostly through fake messages pretending to be support or known contacts. Once linked, the attacker’s device silently syncs with the victim’s WhatsApp. The victim continues chatting as usual, unaware that messages, media, and sometimes even contacts are being mirrored in some other unwanted device.

    Why is it hard to detect

    Ghost pairing is dangerous because it leaves very few visible signs. There is no sudden logout or app crash. Notifications and chats work normally, which never let’s theuser doubt what malicious is going on behind their suspicion. Many users rarely check their linked devices, allowing attackers prolonged access. Since the pairing uses a legitimate WhatsApp feature, victims often realise something is wrong only after data misuse, fraud, or leaked private conversations.

    Representative Image

    Representative Image

    What are some common tactics used by scammers

    Scammers depend mostly on human psychology, posting situations of utmost urgency. They create a necessity by claiming account verification issues, job offers, or urgent requests from “friends.” Some hackers might even impersonate WhatsApp officials or company HR teams. The goal is to make users act instantly without giving them much time for deliberation. Then, once the user trusts the scenario and scans the code, the devices get synced.

    How to stay safe from ghost pairing

    Prevention starts with just being aware. Never share WhatsApp verification codes or scan QR codes sent by others. Regularly check the “Linked Devices” section and remove devices that might look fishy and problematic. Enable two-step verification for increased protection. Most importantly, it is necessary to rethink when messages create panic or urgency. A few seconds of verification and cross-checking can prevent weeks of damage and loss of privacy.

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  • Late Surge Spurred by Neuendorf Pushes Men’s Basketball Past Valley City State on the Road

    Easton Neuendorf attempting a tough shot

    Photography by ThirDWheel Photo

    VALLEY CITY, N.D. — Dakota Wesleyan Men’s Basketball traveled to North Dakota to face the Valley City State Vikings in the second matchup of their home-and-home out-of-conference…

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  • Large gains in leaf scale photosynthetic rates of sparsely vegetated arid and semi-arid lands

  • Wang, H. et al. Towards a universal model for carbon dioxide uptake by plants. Nat. Plants 3, 734–741 (2017).

    Google Scholar 

  • Chen, C. et al. CO2 fertilization of terrestrial photosynthesis inferred from site to global scales. Proc. Natl Acad. Sci. USA 119, e2115627119 (2022).

    Google Scholar 

  • Ruehr, S. et al. Evidence and attribution of the enhanced land carbon sink. Nat. Rev. Earth Environ. 4, 518–534 (2023).

    Google Scholar 

  • Myneni, R. B. et al. Global products of vegetation leaf area and fraction absorbed PAR from one year of MODIS data. Remote Sens. Environ. 83, 214–231 (2002).

    Google Scholar 

  • Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).

    Google Scholar 

  • Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2020).

    Google Scholar 

  • Pu, J. et al. Sensor-independent LAI/FPAR CDR: reconstructing a global sensor-independent climate data record of MODIS and VIIRS LAI/FPAR from 2000 to 2022. Earth Syst. Sci. Data 16, 15–34 (2024).

    Google Scholar 

  • Keenan, T. F. et al. Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake. Nat Communications 7, 13428 (2016).

    Google Scholar 

  • Keenan, T. F. & Riley, W. J. Greening of the land surface in the world’s cold regions consistent with recent warming. Nat. Clim. Change 8, 825–828 (2018).

    Google Scholar 

  • Pugh, T. A. et al. Important role of forest disturbances in the global biomass turnover and carbon sinks. Nat. Geosci. 12, 730–735 (2019).

    Google Scholar 

  • Haverd, V. et al. Higher than expected CO2 fertilization inferred from leaf to global observations. Glob. Chang. Biol. 26, 2390–2402 (2020).

    Google Scholar 

  • Walker, A. P. et al. Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2. N. Phytol. 5, 2413–2445 (2020).

    Google Scholar 

  • Keenan, T. F. et al. A constraint on historic growth in global photosynthesis due to rising CO2. Nat. Clim. Chang. 13, 1376–1381 (2023).

    Google Scholar 

  • Winkler, A. J. et al. Carbon system state determines warming potential of emissions. PLoS ONE 19, e0306128 (2024).

    Google Scholar 

  • Zhu, Z. et al. Greening of the Earth and its drivers. Nat. Clim. Change 6, 791–795 (2016).

    Google Scholar 

  • Wang, S. et al. Drylands contribute disproportionately to observed global productivity Increases. Science Bulletin 68, 224–232 (2023).

    Google Scholar 

  • Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600 (2014).

    Google Scholar 

  • Xu, L. et al. Widespread decline in greenness of Amazonian vegetation due to the 2010 drought. Geophys. Res. Lett. 38, L07402 (2011).

    Google Scholar 

  • Doughty, C. E. et al. Drought impact on forest carbon dynamics and fluxes in Amazonia. Nature 519, 78–82 (2015).

    Google Scholar 

  • Yang, J. et al. Amazon drought and forest response: largely reduced forest photosynthesis but slightly increased canopy greenness during the extreme drought of 2015/2016. Glob. Change Biol. 24, 1919–1934 (2018).

    Google Scholar 

  • Thornley, J. H. Instantaneous canopy photosynthesis: analytical expressions for sun and shade leaves based on exponential light decay down the canopy and an acclimated non-rectangular hyperbola for leaf photosynthesis. Ann. Bot. 89, 451–458 (2002).

    Google Scholar 

  • Brodersen, C. R. & Vogelmann, T. C. Do changes in light direction affect absorption profiles in leaves? Funct. Plant Biol. 37, 403–412 (2010).

    Google Scholar 

  • Li, X. & Xiao, J. Mapping photosynthesis solely from solar-induced chlorophyll fluorescence: A global, fine-resolution dataset of gross primary production derived from OCO−2. Remote Sens 11, 2563 (2019).

    Google Scholar 

  • Stich, S. et al. Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project. Glob. Biogeochem. Cycles 38, e2024GB008102 (2024).

    Google Scholar 

  • Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).

    Google Scholar 

  • Chen, Y. et al. The direct and indirect effects of the environmental factors on global terrestrial gross primary productivity over the past four decades. Environ. Res. Lett. 19, 014052 (2023).

    Google Scholar 

  • Jung, M. et al. The FLUXCOM ensemble of global land-atmosphere energy fluxes. Sci Data 6, 74 (2019).

    Google Scholar 

  • Nelson, J. A. et al. X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X. Biogeosciences 21, 5079–5115 (2024).

    Google Scholar 

  • Cai, W. & Prentice, I. C. Recent trends in gross primary production and their drivers: analysis and modelling at flux-site and global scales. Environ. Res. Lett. 15, 124050 (2020).

    Google Scholar 

  • O’Sullivan, M. et al. Climate-driven variability and trends in plant productivity over recent decades based on three global products. Glob. Biogeochem. Cyc. 34, e2020GB006613 (2020).

    Google Scholar 

  • Myneni, R. B. et al. Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386, 698–702 (1997).

    Google Scholar 

  • Zhou, L. et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. J. Geophys. Res. Atmos. 106, 20069–20083 (2001).

    Google Scholar 

  • Park, T. et al. Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data. Environ. Res. Lett. 11, 084001 (2016).

    Google Scholar 

  • Winkler, A. J. et al. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2. Biogeosciences 18, 4985–5010 (2021).

    Google Scholar 

  • Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).

    Google Scholar 

  • Gutschick, V. P. Photosynthesis model for C3 leaves incorporating CO2 transport, propagation of radiation, and biochemistry. 1. Kinetics and their parameterization. Photosynthetica 18, 549–568 (1984).

    Google Scholar 

  • Collatz, G. J. et al. Physiological and environmental-regulation of stomatal conductance, photosynthesis and transpiration – a model that includes a laminar boundary-layer. Agric. For. Meteorol. 54, 107–136 (1991).

    Google Scholar 

  • Stocker, B. D. et al. P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production. Geosci. Model Dev. 13, 1545–1581 (2020).

    Google Scholar 

  • Liang, S. et al. The global land surface satellite (GLASS) product suite. Bull. Am. Meteorol. Soc. 102, E323–E337 (2021).

    Google Scholar 

  • Yan, K. et al. HiQ LAI: A high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2002. Earth Syst. Sci. Data 16, 1601–1622 (2024).

    Google Scholar 

  • Cao, S. et al. Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020. Earth Syst. Sci. Data 15, 4877–4899 (2023).

    Google Scholar 

  • Ma, H. & Liang, S. Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model. Remote Sens. Environ. 273, 112985 (2022).

    Google Scholar 

  • Wei, F. et al. Divergent trends of ecosystem-scale photosynthetic efficiency between arid and humid lands across the globe. Glob. Ecol. Biogeogr. 31, 1824–1837 (2022).

    Google Scholar 

  • Dardel, C. et al. Re-greening Sahel: 30 years of remote sensing data and field observations (Mali, Niger). Remote Sens. Environ. 140, 350–364 (2014).

    Google Scholar 

  • Brandt, M. et al. Ground- and satellite-based evidence of the biophysical mechanisms behind the greening Sahel. Glob. Change Biol. 21, 1610–1620 (2015).

    Google Scholar 

  • Yuan, W. et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth. Sci. Adv. 5, eaax1396 (2019).

    Google Scholar 

  • Fatichi, S. et al. Partitioning direct and indirect effects reveals the response of water-limited ecosystems to elevated CO2. Proc. Natl Acad. Sci. 113, 12757–12762 (2016).

    Google Scholar 

  • Knyazikhin, Y. et al. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. J. Geophys. Res. 103, 32257–32276 (1998).

    Google Scholar 

  • Norby, R. J. et al. Forest response to elevated CO2 is conserved across a broad range of productivity. Proc. Natl Acad. Sci. USA 102, 18052–18056 (2005).

    Google Scholar 

  • Kaptué, A. T., Prihodko, L. & Hanan, N. P. On regreening and degradation in Sahelian watersheds. Proc. Natl Acad. Sci. USA 112, 12133–12138 (2015).

    Google Scholar 

  • Min, J. et al. Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region. Big Earth Data 7, 298–317 (2023).

    Google Scholar 

  • Zhang, Y. et al. Multiple afforestation programs accelerate the greenness in the ‘Three North’ region of China from 1982 to 2013. Ecol. Indic. 61, 404–412 (2016).

    Google Scholar 

  • Lu, F. et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl Acad. Sci. USA 115, 4039–4044 (2018).

    Google Scholar 

  • Ray, D. K. & Foley, J. A. Increasing global crop harvest frequency: recent trends and future directions. Environ. Res. Lett. 8, 044041 (2013).

    Google Scholar 

  • Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).

    Google Scholar 

  • Running, S. W. & Zhao, M. Daily GPP and Annual NPP (MOD17A2/A3) Products NASA Earth Observing System MODIS Land Algorithm—User’s Guide V3. 28 (MODIS Land Team, 2015).

  • Yuan, W. et al. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes. Agric. For. Meteorol. 143, 189–207 (2007).

    Google Scholar 

  • Prentice, I. C. et al. Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology. Ecol. Lett. 17, 82–91 (2014).

    Google Scholar 

  • Korson, L., Drost-hansen, W. & Millero, F. J. Viscosity of water various temperatures. J. Phys. Chem. 73, 34–39 (1969).

    Google Scholar 

  • Bao, S. et al. Environment-sensitivity functions for gross primary productivity in light use efficiency models. Agric. For. Meteorol. 312, 108708 (2022).

    Google Scholar 

  • Kalliokoski, T. et al. Decomposing sources of uncertainty in climate change projections of boreal forest primary production. Agric. For. Meteorol. 262, 192–205 (2018).

    Google Scholar 

  • Sulla-Menashe, D. & Friedl, M. A. User Guide to Collection 6 MODIS Land Cover (MCD12Q1 and MCD12C1) Product (USGS, 2018).

  • Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data 7, 225 (2020).

    Google Scholar 

  • Zheng, Y. et al. Improved estimate of global gross primary production for reproducing its long-term variation, 1982–2017. Earth Syst. Sci. Data 12, 2725–2746 (2020).

    Google Scholar 

  • Wang, L. et al. Evaluation of the latest MODIS GPP products across multiple biomes using global eddy covariance flux data. Remote Sens 9, 418 (2017).

    Google Scholar 

  • Zhu, W., Zhao, C. & Xie, Z. An end-to-end satellite-based GPP estimation model devoid of meteorological and land cover data. Agric. For. Meteorol. 331, 109337 (2023).

    Google Scholar 

  • Bai, Y. et al. Different satellite products revealing variable trends in global gross primary production. J. Geophys. Res. 128, e2022JG006918 (2023).

    Google Scholar 

  • Baret, F. et al. Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: proposition of the CEOS-BELMANIP. IEEE Trans. Geosci. Remote Sens 44, 1794–1803 (2006).

    Google Scholar 

  • Gier, B. K. et al. Representation of the terrestrial carbon cycle in CMIP6. Biogeosciences 21, 5321–5360 (2024).

    Google Scholar 

  • Yan, K. et al. Evaluation of MODIS LAI/FPAR Product Collection 6. Part 1: Consistency and Improvements. Remote Sens 8, 350 (2016).

    Google Scholar 

  • Yan, K. et al. Evaluation of MODIS LAI/FPAR Product Collection 6. Part 2: Validation and Intercomparison. Remote Sens 8, 460 (2016).

    Google Scholar 

  • Jin, H. et al. Intercomparison and validation of MODIS and GLASS leaf area index (LAI) products over mountain areas: A case study in southwestern China. Int. J. Appl. Earth Obs. Geoinf. 55, 52–67 (2017).

    Google Scholar 

  • Zhang, X. et al. An insight into the internal consistency of MODIS global leaf area index products. IEEE Trans. Geosci. 62, 1–16 (2024).

  • Arneth, A. et al. Terrestrial biogeochemical feedbacks in the climate system. Nat. Geosci. 3, 525–532 (2010).

    Google Scholar 

  • Heinze, C. et al. ESD reviews: climate feedbacks in the Earth system and prospects for their evaluation. Earth Syst. Dyn. 10, 379–452 (2019).

    Google Scholar 

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  • Ohio Defeats Davidson; Bloomsburg Rolls to Pair of Dual Victories

    Ohio Defeats Davidson; Bloomsburg Rolls to Pair of Dual Victories

    …

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  • No. 5 Oregon Hands 51-34 Loss to No. 12 JMU and Advance to Playoff Quarterfinals

    No. 5 Oregon Hands 51-34 Loss to No. 12 JMU and Advance to Playoff Quarterfinals

    EUGENE, Ore. (AP) — Dante…

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  • Men’s Basketball Sunk by Buzzer Beater at Rutgers, Falls 70-69

    Men’s Basketball Sunk by Buzzer Beater at Rutgers, Falls 70-69

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  • Are Polynucleotides the Secret Solution to Hair Thinning?

    Are Polynucleotides the Secret Solution to Hair Thinning?

    Despite having voluminous, wavy-curly hair that often leads people to assume I have great density, there are days when I gather it into a ponytail and sense something is off – it feels thinner, lighter, and less substantial than it used to. For…

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  • Europe’s battery plants need local content rules to stay competitive, bosses say

    Europe’s battery plants need local content rules to stay competitive, bosses say

    Unlock the Editor’s Digest for free

    Two executives behind Europe’s newest battery plants have voiced support for a plan by Brussels to boost local content levels for car products as the continent seeks to weaken China’s grip on technologies critical to the electric transition.

    Some carmakers have panned the “made in Europe” proposal as “very dangerous” and said it could slow the shift to electric vehicles. But the chief executive of Seat-Cupra said such rules for car parts were necessary for Europe to remain competitive as the carmaker opened its battery assembly plant in Barcelona last week.

    “I think having a minimum amount of parts and also materials to be sourced from Europe for Europe is the natural answer,” said Markus Haupt, who heads the Spanish mass-market brand that is part of Volkswagen group. “It’s also the basis that we need to create to allow Europeans to stay competitive in Europe.” 

    Europe’s ambitions to build a homegrown battery industry took a hit with the collapse of Sweden’s Northvolt in March. Other battery projects have moved ahead elsewhere in Europe but face stiff competition from Asian competitors who lead the field.

    Proponents of the rules say having locally sourced materials will help to boost European competitiveness and jobs by reducing the continent’s reliance on China. European manufacturers remain particularly dependent on China for the manufacturing of battery cells as well as the battery metals supply chain.

    The opening of Seat-Cupra’s battery assembly plant in Barcelona is a key pillar of Volkswagen’s broader strategy to establish its independent supply chains for EVs © Ferran Nadeu

    The EU’s local sourcing targets for parts in products such as cars and solar panels are part of a set of proposals to be presented in late January aimed at strengthening the EU’s flagging industrial base.

    Echoing Seat-Cupra, which is part of the Volkswagen group, French battery maker Verkor also called for strict local content rules to boost the nascent European battery sector, as the company inaugurated its first gigafactory in Dunkirk last week.

    Benoit Lemaignan, chief executive and founder of the start-up Verkor, said that in order to protect the nascent battery sector, “made in Europe” rules were essential. Having a minimum capacity of European-made components would not only protect “industrial activity in Europe and France”, but also avoid Europe being excessively reliant on Chinese imports.

    The French government is leading calls for the content rules and at the Dunkirk event, industry minister Sébastien Martin said that Europe should follow the US and China in insisting on locally made content in vehicles. “In Europe, we need an extremely significant level of locally made content in our vehicles — 75 per cent — to save our industry.”

    Lemaignan is focusing the newly inaugurated Dunkirk facility on a single client and a single vehicle: the A390 SUV developed by Renault brand Alpine. He said this was a similar approach to that taken by China’s CATL and South Korea’s LG in earlier stages of development.

    In Spain, the opening of Seat-Cupra’s battery assembly plant in Barcelona is a key pillar of Volkswagen’s broader strategy to establish its independent supply chains for EVs. At maximum capacity, the facility will be able to assemble 300,000 battery systems per year and roughly half of its battery cells will be sourced from VW’s battery division. 

    An employee in protective gear operates machinery at Verkor's electric vehicle battery gigafactory during a press visit.
    French battery maker Verkor is focusing its new Dunkirk facility on a single vehicle © Francois Lo Presti/AFP via Getty Images

    Volkswagen earlier this month began the increase of production at its flagship battery plant in Salzgitter, close to its German headquarters.

    The new facility at the Martorell plant is also part of the German group’s €10bn investment into Spain’s electric transition. The VW group plans to take on Chinese rivals with a series of affordable electric vehicles produced in Spain and has spent about a third of its budget to transform Martorell into a production hub for EVs, hybrids and combustion engine vehicles.

    The battery systems will be used in Cupra’s sporty small EV Raval and Volkswagen’s ID. Polo, which will both go on sale next year starting at €25,000.

    “We think this segment could be the game changer for us,” Haupt said. “We strongly believe that we can be very competitive with this Cupra Raval.” 

    Jordi Hereu, Spain’s industry minister, welcomed the opening of the facility as “one step forward towards ensuring strategic autonomy starting here in Europe”.

    Europe’s local sourcing proposal has divided the industry and EU’s member states. It has faced opposition from carmakers who source many parts from outside the bloc. 

    Verkor has been backed by the French state to develop its gigafactory, with €650mn of French subsidies as part of a more than €2bn fundraise in 2023. 

    France has led efforts to develop the battery industry in Europe, with the Dunkirk region serving as a home not just to Verkor’s factory but also to Stellantis and Mercedes-Benz-backed battery maker ACC, Taiwanese developer Prologium and AESC, the Sino-Japanese battery maker whose cells are used in Renault’s R5 cars made at the nearby Douai plant. 

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