Materials that exhibit yielding behavior are used in many applications, from spreadable foods and cosmetics to direct write three-dimensional printing inks and filled rubbers. Their key design feature is the ability to transition behaviorally from solid to fluid under sufficient load or deformation. Despite its widespread applications, little is known about the dynamics of yielding in real processes, as the nonequilibrium nature of the transition impedes understanding. We demonstrate an iteratively punctuated rheological protocol that combines strain-controlled oscillatory shear with stress-controlled recovery tests. This technique provides an experimental decomposition of recoverable and unrecoverable strains, allowing for solid-like and fluid-like contributions to a yield stress material's behavior to be separated in a time-resolved manner. Using this protocol, we investigate the overshoot in loss modulus seen in materials that yield. We show that this phenomenon is caused by the transition from primarily solid-like, viscoelastic dissipation in the linear regime to primarily fluid-like, plastic flow at larger amplitudes. We compare and contrast this with a viscoelastic liquid with no yielding behavior, where the contribution to energy dissipation from viscous flow dominates over the entire range of amplitudes tested.Soil erosion is a major global soil degradation threat to land, freshwater, and oceans. https://www.selleckchem.com/products/eflornithine-hydrochloride-hydrate.html Wind and water are the major drivers, with water erosion over land being the focus of this work; excluding gullying and river bank erosion. Improving knowledge of the probable future rates of soil erosion, accelerated by human activity, is important both for policy makers engaged in land use decision-making and for earth-system modelers seeking to reduce uncertainty on global predictions. Here we predict future rates of erosion by modeling change in potential global soil erosion by water using three alternative (2.6, 4.5, and 8.5) Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. Global predictions rely on a high spatial resolution Revised Universal Soil Loss Equation (RUSLE)-based semiempirical modeling approach (GloSEM). The baseline model (2015) predicts global potential soil erosion rates of [Formula see text] Pg yr-1, with current conservation agriculture (CA) practices estimated to reduce this by ∼5%. Our future scenarios suggest that socioeconomic developments impacting land use will either decrease (SSP1-RCP2.6-10%) or increase (SSP2-RCP4.5 +2%, SSP5-RCP8.5 +10%) water erosion by 2070. Climate projections, for all global dynamics scenarios, indicate a trend, moving toward a more vigorous hydrological cycle, which could increase global water erosion (+30 to +66%). Accepting some degrees of uncertainty, our findings provide insights into how possible future socioeconomic development will affect soil erosion by water using a globally consistent approach. This preliminary evidence seeks to inform efforts such as those of the United Nations to assess global soil erosion and inform decision makers developing national strategies for soil conservation.Honesty is one of the most valued traits in politicians. Yet, because lies often remain undiscovered, it is difficult to study if some politicians are more honest than others. This paper examines which individual characteristics are correlated with truth-telling in a controlled setting in a large sample of politicians. We designed and embedded a game that incentivizes lying with a nonmonetary method in a survey answered by 816 Spanish mayors. Mayors were first asked how interested they were in obtaining a detailed report about the survey results, and at the end of the survey, they had to flip a coin to find out whether they would be sent the report. Because the probability of heads is known, we can estimate the proportion of mayors who lied to obtain the report. We find that a large and statistically significant proportion of mayors lied. Mayors that are members of the two major political parties lied significantly more. We further find that women and men were equally likely to lie. Finally, we find a negative relationship between truth-telling and reelection in the next municipal elections, which suggests that dishonesty might help politicians survive in office.Multiple sclerosis (MS), an autoimmune disease of the central nervous system, generally starts as the relapsing remitting form (RRMS), but often shifts into secondary progressive MS (SPMS). SPMS represents a more advanced stage of MS, characterized by accumulating disabilities and refractoriness to medications. The aim of this study was to clarify the microbial and functional differences in gut microbiomes of the different stages of MS. Here, we compared gut microbiomes of patients with RRMS, SPMS, and two closely related disorders with healthy controls (HCs) by 16S rRNA gene and whole metagenomic sequencing data from fecal samples and by fecal metabolites. Each patient group had a number of species having significant changes in abundance in comparison with HCs, including short-chain fatty acid (SCFA)-producing bacteria reduced in MS. Changes in some species had close association with clinical severity of the patients. A marked reduction in butyrate and propionate biosynthesis and corresponding metabolic changes were confirmed in RRMS compared with HCs. Although bacterial composition analysis showed limited differences between the patient groups, metagenomic functional data disclosed an increase in microbial genes involved in DNA mismatch repair in SPMS as compared to RRMS. Together with an increased ratio of cysteine persulfide to cysteine in SPMS revealed by sulfur metabolomics, we postulate that excessive DNA oxidation could take place in the gut of SPMS. Thus, gut ecological and functional microenvironments were significantly altered in the different stages of MS. In particular, reduced SCFA biosynthesis in RRMS and elevated oxidative level in SPMS were characteristic.Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system.