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In porous hollow fiber membrane (HFM) based anti-solvent crystallization (AsCr) technique, the anti-solvent is injected from HFM bore into the active pharmaceutical ingredient (API) containing solution flowing in the shell side. Conventionally, shell-side feed solution flows along the HFM. In our compact module design, the shell-side liquid flows perpendicular to the HFMs; the mean flow length is ~ 3 cm reducing considerably the residence time (tres) which strongly influences crystal growth. We investigated AsCr of griseofulvin (GF) from its acetone solution using anti-solvent water injected through HFM pores. The range of tres was 5–30 s; the volume flow rate ratio (FRR) of acetone/water ranged between 0.35 and 1.66; griseofulvin concentration was varied between saturation (3.73 g/100 g acetone) to 0.4 g GF in 100 g of solution having 50 wt% acetone in the total solution. Low tres yielded nanocrystals < 100 nm. The average API crystal size (Davg) remained around 230 nm in a three hour- long experiment. At a fixed mass FRR of 1.34 ±0.1, Davg increased linearly from 48 to 280 nm as tres increased from 5 to 28 s. For two HFM modules in series with the nanocrystal suspension from one module fed to the next module independently fed with anti-solvent water, GF crystallization yields as high as 98 % were achieved. AsCr of L-glutamic acid in water with anti-solvent acetone in the same device illustrated continuous nanocrystal production and similar behaviors vis-`a-vis variations of tres and FRR. The cross-flow HFM based continuous AsCr technique can continuously produce nanocrystals of APIs. 

Super-Kamiokande (SK) has observed ${}^8\mathrm{B}$solar neutrino elastic scattering at recoil electron kinetic energies ( $E_{\mathrm{kin}}$) as low as 3.49 MeV to study neutrino flavor conversion within the Sun. At SK-observable energies, these conversions are dominated by the Mikheyev-Smirnov-Wolfenstein effect. An upturn in the electron neutrino survival probability in which vacuum neutrino oscillations become dominant is predicted to occur at lower energies, but radioactive background increases exponentially with decreasing energy. New machine learning approaches provide substantial background reduction below 3.49 MeV such that statistical extraction of solar neutrino interactions becomes feasible. This article presents an analysis of the solar neutrino interaction rate at $E_{\mathrm{kin}}<3.49\mathrm{MeV}$with the full SK-IV period, using data from a wideband intelligent trigger when available and with a boosted decision tree for event selection. A solar neutrino signal is observed between $2.99\mathrm{MeV}<E_{\mathrm{kin}}<3.49\mathrm{MeV}$with $2.76\sigma$significance and a data to unoscillated Monte Carlo ratio of ${0.307}_{-0.111}^{+0.112}$. These additional low-energy data have a negligible effect on the $1\sigma$intervals of the fits to the solar neutrino energy spectrum but have a noticeable effect on the best fit when using the exponential parametrization. 

We introduce a new class of photonic resonators with resonant modes that feature hybrid standing-travelling waves. 

Abstract Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO₂in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO₂‐C yr⁻¹) and sources of CH₄(bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH₄‐C yr⁻¹) and N₂O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N₂O‐N yr⁻¹). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH₄dominates the total forcing. The net CO₂sink in Boreal forests and wetlands is largely offset by fires and inland water CO₂emissions as well as CH₄emissions from wetlands and inland waters, with a smaller contribution from N₂O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH₄and N₂O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques.