More on Codes Over Finite Quotients of Polynomial Rings by Emad Kadhim Al-Lami, Reza Sobhani, Alireza Abdollahi, Javad Bagherian

“…El Amrani) of <inline-formula> <tex-math notation="LaTeX">$\mathbb {A}$ </tex-math></inline-formula>-codes of length l over <inline-formula> <tex-math notation="LaTeX">$\mathbb {A}$ </tex-math></inline-formula>, i.e. <inline-formula> <tex-math notation="LaTeX">$\mathbb {A}$ </tex-math></inline-formula>-submodules of <inline-formula> <tex-math notation="LaTeX">${\mathbb {A}}^{l}$ </tex-math></inline-formula>. …”
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Growth response of <i>Emiliania huxleyi</i> to ocean alkalinity enhancement by G. Faucher, M. Haunost, A. J. Paul, A. U. C. Tietz, U. Riebesell

“…They contribute <span class="inline-formula"><i>&lt;</i></span> 10 % to the global marine primary production but are responsible for a large proportion of the marine calcite deposition. …”
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Assessment of the southern polar and subpolar warming in the PMIP4 last interglacial simulations using paleoclimate data syntheses by Q. Gao, Q. Gao, Q. Gao, E. Capron, L. C. Sime, R. H. Rhodes, R. Sivankutty, X. Zhang, B. L. Otto-Bliesner, M. Werner

“…The hosed 128 ka HadCM3 simulation captures much of the warming and sea ice loss shown in the four data syntheses at 127 ka relative to preindustrial: south of 40° S, modeled annual sea surface temperature (SST) rises by 1.3 <span class="inline-formula">±</span> 0.6 °C, while reconstructed average anomalies range from 2.2 to 2.7 °C; modeled summer SST increases by 1.1 <span class="inline-formula">±</span> 0.7 °C, close to the 1.2–2.2 °C reconstructed average anomalies; September sea ice area (SIA) is reduced by 40 <span class="inline-formula"><i>%</i></span>, similar to the reconstructed 40 <span class="inline-formula">%</span> reduction of sea ice concentration (SIC); over the Antarctic Ice Sheet, modeled annual surface air temperature (SAT) increases by 2.6 <span class="inline-formula">±</span> 0.4 °C, even larger than reconstructed average anomalies of 2.2 °C. …”
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Ensemble estimates of global wetland methane emissions over 2000–2020 by Z. Zhang, B. Poulter, J. R. Melton, W. J. Riley, G. H. Allen, D. J. Beerling, P. Bousquet, J. G. Canadell, E. Fluet-Chouinard, P. Ciais, N. Gedney, P. O. Hopcroft, A. Ito, R. B. Jackson, A. K. Jain, K. Jensen, F. Joos, T. Kleinen, S. H. Knox, S. H. Knox, T. Li, X. Li, X. Liu, K. McDonald, G. McNicol, P. A. Miller, J. Müller, P. K. Patra, P. K. Patra, C. Peng, S. Peng, Z. Qin, R. M. Riggs, M. Saunois, Q. Sun, H. Tian, X. Xu, Y. Yao, Y. Xi, W. Zhang, W. Zhang, Q. Zhu, Q. Zhu, Q. Zhuang

“…Our results estimated global average wetland CH<span class="inline-formula">₄</span> emissions at 158 <span class="inline-formula">±</span> 24 (mean <span class="inline-formula">±</span> 1<span class="inline-formula"><i>σ</i></span>) Tg CH<span class="inline-formula">₄</span> yr<span class="inline-formula">⁻¹</span> over a total annual average wetland area of 8.0 <span class="inline-formula">±</span> <span class="inline-formula">2.0×10⁶</span> km<span class="inline-formula">²</span> for the period 2010–2020, with an average increase of 6–7 Tg CH<span class="inline-formula">₄</span> yr<span class="inline-formula">⁻¹</span> in 2010–2019 compared to the average for 2000–2009. …”
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Fixed-Point Grover Adaptive Search for Quadratic Binary Optimization Problems by Akos Nagy, Jaime Park, Cindy Zhang, Atithi Acharya, Alex Khan

“…Finally, we give a heuristic argument that, with high probability and in <inline-formula><tex-math notation="LaTeX">$O (\frac{\log _{2} (n)}{\sqrt{\epsilon }})$</tex-math></inline-formula> time, this adaptive method finds a configuration that is among the best <inline-formula><tex-math notation="LaTeX">$\epsilon 2^{n}$</tex-math></inline-formula> ones.…”
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The effect of groundwater depth on topsoil organic matter mineralization during a simulated dry summer in northwestern Europe by A. Françoys, A. Françoys, O. Mendoza, J. Hu, P. Boeckx, W. Cornelis, S. De Neve, S. Sleutel

“…Additionally, a model fitted to cumulative ryegrass mineralization showed a lower mineralization rate for the stable <span class="inline-formula"><i>C</i>_ryegrass</span> pool in the silt loam soil with the shallowest GWT, where capillary rise contributed most significantly to topsoil moisture, compared with other combinations of soil texture and GWT depth. …”
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Analytical treatment of proton double-quantum NMR intensity buildup: multi-spin couplings and the flip-flop term by N. Fatkullin, I. Brekotkin, K. Saalwächter

“…<p>A modified Anderson–Weiss approximation for describing double-quantum (DQ) NMR experiments in systems with many <span class="inline-formula"><i>I</i></span> <span class="inline-formula">=</span> <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M3" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">2</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="caca869f2f384264fc5bcd3ae2b8aeff"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="mr-6-1-2025-ie00001.svg" width="20pt" height="14pt" src="mr-6-1-2025-ie00001.png"/></svg:svg></span></span> spins is proposed, taking inter-spin flip-flop processes into special consideration. …”
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Power calculation of novel single-piece aspheric diffractive trifocal intraocular lens by K.B. Pershin, N.F. Pashinova, M.M. Konovalova, A.Yu. Tsygankov, M.E. Konovalov

“…IOL power was calculated using six formulas, i.e., SRK/T (35%), Holladay 2 (18%), Hoffer Q (9%), Haigis (22%), and Barrett Universal II (16%). …”
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