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Abstract Eating less meat is associated with a healthier body and planet. Yet, we remain reluctant to switch to a plant-based diet, largely due to the sensory experience of plant-based meat. Food scientists characterize meat using a double compression test, which only probes one-dimensional behavior. Here we use tension, compression, and shear tests–combined with constitutive neural networks–to automatically discover the behavior of eight plant-based and animal meats across the entire three-dimensional spectrum. We find that plant-based sausage and hotdog, with stiffnesses of 95.9 ± 14.1 kPa and 38.7 ± 3.0 kPa, successfully mimic their animal counterparts, with 63.5 ± 45.7 kPa and 44.3 ± 13.2 kPa, while tofurky is twice as stiff, and tofu is twice as soft. Strikingly, a complementary food tasting survey produces in nearly identical stiffness rankings for all eight products (ρ= 0.833,p = 0.015). Probing the fully three-dimensional signature of meats is critical to understand subtle differences in texture that may result in a different perception of taste. Our data and code are freely available athttps://github.com/LivingMatterLab/CANN 

Abstract Polarimetric variables such as differential phase Φ_DPand its range derivative, specific differential phaseK_DP, contain useful information for improving quantitative precipitation estimation (QPE) and microphysics retrieval. However, the usefulness of the current operationally utilized estimation method ofK_DPis limited by measurement error and artifacts resulting from the differential backscattering phaseδ. The contribution ofδcan significantly influence the Φ_DPmeasurements and therefore negatively affect theK_DPestimates. Neglecting the presence ofδwithin non-Rayleigh scattering regimes has also led to the adoption of incorrect terminology regarding signatures seen within current operationalK_DPestimates implying associated regions of unrealistic liquid water content. A new processing method is proposed and developed to estimate bothK_DPandδusing classification and linear programming (LP) to reduce bias inK_DPestimates caused by theδcomponent. It is shown that by applying the LP technique specifically to the rain regions of Rayleigh scattering along a radial profile, accurate estimates of differential propagation phase, specific differential phase, and differential backscattering phase can be retrieved within regions of both Rayleigh and non-Rayleigh scattering. This new estimation method is applied to cases of reported hail and tornado debris, and the LP results are compared to the operationally utilized least squares fit (LSF) estimates. The results show the potential use of the differential backscattering phase signature in the detection of hail and tornado debris. 

Both trans and cis iron–CTMC complexes, namely, trans -dichlorido[(5 SR ,7 RS ,12 RS ,14 SR )-5,7,12,14-tetramethyl-1,4,8,11-tetraazacyclotetradecane]iron(III) tetrachloridoferrate, [Fe(C 14 H 32 N 4 )Cl 2 ][FeCl 4 ] ( 1a ), the analogous chloride methanol monosolvate, [Fe(C 14 H 32 N 4 )Cl 2 ]Cl·CH 3 OH ( 1b ), and cis -dichlorido[(5 SR ,7 RS ,12 SR ,14 RS )-5,7,12,14-tetramethyl-1,4,8,11-tetraazacyclotetradecane]iron(III) chloride, [Fe(C 14 H 32 N 4 )Cl 2 ]Cl ( 2 ), were successfully synthesized and structurally characterized using X-ray diffraction. The coordination geometry of the macrocycle is dependent on the stereoisomerism of CTMC. The packing of these complexes appears to be strongly influenced by extensive hydrogen-bonding interactions, which are in turn determined by the nature of the counter-anions ( 1a versus 1b ) and/or the coordination geometry of the macrocycle ( 1a/1b versus 2 ). These observations are extended to related ferric cis - and trans- dichloro macrocyclic complexes. 

Abstract Human gene research generates new biology insights with translational potential, yet few studies have considered the health of the human gene literature. The accessibility of human genes for targeted research, combined with unreasonable publication pressures and recent developments in scholarly publishing, may have created a market for low-quality or fraudulent human gene research articles, including articles produced by contract cheating organizations known as paper mills. This review summarises the evidence that paper mills contribute to the human gene research literature at scale and outlines why targeted gene research may be particularly vulnerable to systematic research fraud. To raise awareness of targeted gene research from paper mills, we highlight features of problematic manuscripts and publications that can be detected by gene researchers and/or journal staff. As improved awareness and detection could drive the further evolution of paper mill-supported publications, we also propose changes to academic publishing to more effectively deter and correct problematic publications at scale. In summary, the threat of paper mill-supported gene research highlights the need for all researchers to approach the literature with a more critical mindset, and demand publications that are underpinned by plausible research justifications, rigorous experiments and fully transparent reporting.