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1. Pressure drop measurements over anisotropic porous substrates in channel flow

   https://doi.org/10.1007/s00348-024-03873-2  

   Vijay, Shilpa; Luhar, Mitul (September 2024, Experiments in Fluids)

   AbstractPrevious theoretical and simulation results indicate that anisotropic porous materials have the potential to reduce turbulent skin friction in wall-bounded flows. This study experimentally investigates the influence of anisotropy on the drag response of porous substrates. A family of anisotropic periodic lattices was manufactured using 3D printing. Rod spacing in different directions was varied systematically to achieve different ratios of streamwise, wall-normal, and spanwise bulk permeabilities ($$\kappa _{xx}$$ ${\kappa }_{\mathrm{xx}}$,$$\kappa _{yy}$$ ${\kappa }_{\mathrm{yy}}$, and$$\kappa _{zz}$$ ${\kappa }_{\mathrm{zz}}$). The 3D printed materials were flush-mounted in a benchtop water channel. Pressure drop measurements were taken in the fully developed region of the flow to systematically characterize drag for materials with anisotropy ratios$$\frac{\kappa _{xx}}{\kappa _{yy}} \in [0.035,28.6]$$ $\frac{{\kappa }_{\mathrm{xx}}}{{\kappa }_{\mathrm{yy}}}\in [0.035,28.6]$. Results show that all materials lead to an increase in drag compared to the reference smooth wall case over the range of bulk Reynolds numbers tested ($$\hbox {Re}_b \in [500,4000]$$ ${\text{Re}}_b\in [500,4000]$). However, the relative increase in drag is lower for streamwise-preferential materials. We estimate that the wall-normal permeability for all tested cases exceeded the threshold identified in previous literature ($$\sqrt{\kappa _{yy}}^+> 0.4$$ ${\sqrt{{\kappa }_{\mathrm{yy}}}}^{+}>0.4$) for the emergence of energetic spanwise rollers similar to Kelvin–Helmholtz vortices, which can increase drag. The results also indicate that porous walls exhibit a departure from laminar behavior at different values for bulk Reynolds numbers depending on the geometry. Graphical abstract 

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2. Connection probabilities of multiple FK-Ising interfaces

   https://doi.org/10.1007/s00440-024-01269-1  

   Feng, Yu; Peltola, Eveliina; Wu, Hao (June 2024, Probability Theory and Related Fields)

   Abstract We find the scaling limits of a general class of boundary-to-boundary connection probabilities and multiple interfaces in the critical planar FK-Ising model, thus verifying predictions from the physics literature. We also discuss conjectural formulas using Coulomb gas integrals for the corresponding quantities in general critical planar random-cluster models with cluster-weight$${q \in [1,4)}$$ $q\in [1,4)$. Thus far, proofs for convergence, including ours, rely on discrete complex analysis techniques and are beyond reach for other values ofqthan the FK-Ising model ($$q=2$$ $q=2$). Given the convergence of interfaces, the conjectural formulas for other values ofqcould be verified similarly with relatively minor technical work. The limit interfaces are variants of$$\text {SLE}_\kappa $$ ${\text{SLE}}_{\kappa }$curves (with$$\kappa = 16/3$$ $\kappa =16/3$for$$q=2$$ $q=2$). Their partition functions, that give the connection probabilities, also satisfy properties predicted for correlation functions in conformal field theory (CFT), expected to describe scaling limits of critical random-cluster models. We verify these properties for all$$q \in [1,4)$$ $q\in [1,4)$, thus providing further evidence of the expected CFT description of these models. 

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3. Search for CP violation in t$$ \overline{\textrm{t}} $$H and tH production in multilepton channels in proton-proton collisions at $$ \sqrt{s} $$ = 13 TeV

   https://doi.org/10.1007/JHEP07(2023)092  

   Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Escalante Del Valle, A.; Hussain, P. S.; Jeitler, M.; et al (July 2023, Journal of High Energy Physics)

   A<sc>bstract</sc> The charge-parity (CP) structure of the Yukawa interaction between the Higgs (H) boson and the top quark is measured in a data sample enriched in the t$$ \overline{\textrm{t}} $$ $\overline{t}$H and tH associated production, using 138 fb⁻¹of data collected in proton-proton collisions at$$ \sqrt{s} $$ $\sqrt{s}$= 13 TeV by the CMS experiment at the CERN LHC. The study targets events where the H boson decays via H → WW or H →ττand the top quarks decay via t → Wb: the W bosons decay either leptonically or hadronically, and final states characterized by the presence of at least two leptons are studied. Machine learning techniques are applied to these final states to enhance the separation ofCP-even fromCP-odd scenarios. Two-dimensional confidence regions are set onκ_tand$$ \overset{\sim }{\kappa } $$ $\tilde{\kappa }$_t, which are respectively defined as theCP-even andCP-odd top-Higgs Yukawa coupling modifiers. No significant fractionalCP-odd contributions, parameterized by the quantity|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$|are observed; the parameter is determined to be|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$|= 0.59 with an interval of (0.24,0.81) at 68% confidence level. The results are combined with previous results covering the H→ZZ and H→ γγdecay modes, yielding two- and one-dimensional confidence regions onκ_tand$$ \overset{\sim }{\kappa } $$ $\tilde{\kappa }$_t, while|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$|is determined to be|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$|= 0.28 with an interval of|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$| <0.55 at 68% confidence level, in agreement with the standard modelCP-even prediction of|$$ {f}_{CP}^{\textrm{Htt}} $$ $f_{\mathrm{CP}}^{\mathrm{Htt}}$|= 0. 

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4. eGHWT: The Extended Generalized Haar–Walsh Transform

   https://doi.org/10.1007/s10851-021-01064-w  

   Saito, Naoki; Shao, Yiqun (January 2022, Journal of Mathematical Imaging and Vision)

   Abstract Extending computational harmonic analysis tools from the classical setting of regular lattices to the more general setting of graphs and networks is very important, and much research has been done recently. The generalized Haar–Walsh transform (GHWT) developed by Irion and Saito (2014) is a multiscale transform for signals on graphs, which is a generalization of the classical Haar and Walsh–Hadamard transforms. We propose theextendedgeneralized Haar–Walsh transform (eGHWT), which is a generalization of the adapted time–frequency tilings of Thiele and Villemoes (1996). The eGHWT examines not only the efficiency of graph-domain partitions but also that of “sequency-domain” partitionssimultaneously. Consequently, the eGHWT and its associated best-basis selection algorithm for graph signals significantly improve the performance of the previous GHWT with the similar computational cost,$$O(N \log N)$$ $O(NlogN)$, whereNis the number of nodes of an input graph. While the GHWT best-basis algorithm seeks the most suitable orthonormal basis for a given task among more than$$(1.5)^N$$ ${\left(1.5\right)}^N$possible orthonormal bases in$$\mathbb {R}^N$$ $R^N$, the eGHWT best-basis algorithm can find a better one by searching through more than$$0.618\cdot (1.84)^N$$ $0.618·{\left(1.84\right)}^N$possible orthonormal bases in$$\mathbb {R}^N$$ $R^N$. This article describes the details of the eGHWT best-basis algorithm and demonstrates its superiority using several examples including genuine graph signals as well as conventional digital images viewed as graph signals. Furthermore, we also show how the eGHWT can be extended to 2D signals and matrix-form data by viewing them as a tensor product of graphs generated from their columns and rows and demonstrate its effectiveness on applications such as image approximation. 

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5. Differentiating Contact with Symptomatic and Asymptomatic Infectious Individuals in a SEIR Epidemic Model

   https://doi.org/10.1007/s11538-025-01416-2  

   Chebotaeva, Victoria; Srinivasan, Anish; Vasquez, Paula A (March 2025, Bulletin of Mathematical Biology)

   Abstract This manuscript introduces a new Erlang-distributed SEIR model. The model incorporates asymptomatic spread through a subdivided exposed class, distinguishing between asymptomatic ($$\hbox {E}_a$$ ${\text{E}}_a$) and symptomatic ($$\hbox {E}_s$$ ${\text{E}}_s$) cases. The model identifies two key parameters: relative infectiousness,$$\beta _{{SA}}$$ ${\beta }_{\mathrm{SA}}$, and the percentage of people who become asymptomatic after being infected by a symptomatic individual,$$\kappa $$ $\kappa$. Lower values of these parameters reduce the peak magnitude and duration of the infectious period, highlighting the importance of isolation measures. Additionally, the model underscores the need for strategies addressing both symptomatic and asymptomatic transmissions. 

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