Explore the vast range of titles available.

The significant interest in actinide bonding has recently focused on novel compounds with exotic oxidation states. However, the difficulty in obtaining relevant high-quality experimental data, particularly for low-valent actinide compounds, prevents a deeper understanding of 5f systems. Here we show X-ray absorption near-edge structure (XANES) measurements in the high-energy resolution fluorescence detection (HERFD) mode at the uranium M 4 edge for the U III and U IV halides, namely UX 3 and UX 4 (X = F, Cl, Br, I). The spectral shapes of these two series exhibit clear differences, which we explain using electronic structure calculations of the 3d-4f resonant inelastic X-ray scattering (RIXS) process. To understand the changes observed, we implemented crystal field models with ab initio derived parameters and investigated the effect of reducing different contributions to the electron-electron interactions involved in the RIXS process. Our analysis shows that the electron-electron interactions weaken as the ligand changes from I to F, indicative of a decrease in ionicity both along and between the UX 3 and UX 4 halide series. The authors investigate fundamental interactions in low-valent uranium compounds using resonant inelastic X-ray scattering, providing insights into their complex electronic structures and contributing to our understanding of actinide chemistry.

The vertical plane transverse emittance of accelerated electron bunches at the AWAKE experiment at CERN has been determined, using three different methods of data analysis. This is a proof-of-principle measurement using the existing AWAKE electron spectrometer to validate the measurement technique. Large values of the geometric emittance, compared to that of the injection beam, are observed (\\(\\sim \\SI{0.5}{\\milli\\metre\\milli\\radian}\\) compared with \\(\\sim \\SI{0.08}{\\milli\\metre\\milli\\radian}\\)), which is in line with expectations of emittance growth arising from plasma density ramps and large injection beam bunch size. Future iterations of AWAKE are anticipated to operate in conditions where emittance growth is better controlled, and the effects of the imaging systems of the existing and future spectrometer designs on the ability to measure the emittance are discussed. Good performance of the instrument down to geometric emittances of approximately \\(\\SI{1e-4}{\\milli\\metre\\milli\\radian}\\) is required, which may be possible with improved electron optics and imaging.

The firm’s price policy decision is a central issue in spatial economics. Previous results show, e.g., that the specification of consumers’ demand functions is pivotal but mostly mill and uniform pricing are compared in a monopoly setting with constant marginal costs. The results in this paper highlight that some conclusions of prior work do not hold if the monopolist operates under non-constant marginal production costs. For instance, the optimal price is no longer independent of transport costs, and the welfare ranking of mill and uniform pricing also depends on the shape of the cost function.

Much of the land economics literature has largely ignored the spatial nature of competition and related differences between farmland rental and sales markets when assessing return rates from farming, the capitalization of agricultural, environmental and energy policy into land values, and climate change impacts. We propose a model for price formation in both markets under a spatial competition framework. We demonstrate that price formation differs, particularly under policy-induced output price shocks.We suggest that using the rent-price ratio as an approximation for expectations in the net returns of farming, based on the net present value model, may produce biased results. In consequence, studies relying on land prices need to control for local land competition, farming structure, and policies.

Background Fecal water syndrome (FWS) is long‐standing and common in horses, particularly in central Europe. No large epidemiological data sets exist, and the cause remains elusive. Dysbiosis could play a role in pathogenesis. Objectives To evaluate whether dysbiosis is present in horses with FWS when compared to stable‐matched control horses in spring and autumn. Animals Fecal samples were collected from horses with FWS (n = 16; 9 mares, 7 geldings) and controls (n = 15; 8 mares, 7 geldings). Methods The bacterial microbiome of samples collected in spring and autumn of 2016 was analyzed using high‐throughput sequencing. Differences in relative abundance of bacterial taxa, alpha diversity, and beta diversity indices were assessed between horses with FWS and controls based on season. Results Differences in microbial community composition based on time point and health status were not observed on any taxonomic level. Limited differences were seen on linear discriminant analysis effect size analysis. No difference in alpha diversity indices was observed including richness, diversity based on health status, or time point. No effect of health status on microbial community membership structure was observed. Conclusions and Clinical Importance Limited differences were found in the bacterial microbiota of horses with and without FWS, regardless of season. Further research is needed to elucidate the role of microbiota in the development of FWS.

SlyD is a widely-occurring prokaryotic FKBP-family prolyl isomerase with an additional chaperone domain. Often, such as in Escherichia coli , a third domain is found at its C-terminus that binds nickel and provides it for nickel-enzyme biogenesis. SlyD has been found to bind signal peptides of proteins that are translocated by the Tat pathway, a system for the transport of folded proteins across membranes. Using peptide arrays to analyze these signal peptide interactions, we found that SlyD interacted only with positively charged peptides, with a preference for arginines over lysines, and large hydrophobic residues enhanced binding. Especially a twin-arginine motif was recognized, a pair of highly conserved arginines adjacent to a stretch of hydrophobic residues. Using isothermal titration calorimetry (ITC) with purified SlyD and a signal peptide-containing model Tat substrate, we could show that the wild type twin-arginine signal peptide was bound with higher affinity than an RR>KK mutated variant, confirming that positive charges are recognized by SlyD, with a preference of arginines over lysines. The specific role of negative charges of the chaperone domain surface and of hydrophobic residues in the chaperone active site was further analyzed by ITC of mutated SlyD variants. Our data show that the supposed key hydrophobic residues of the active site are indeed crucial for binding, and that binding is influenced by negative charges on the chaperone domain. Recognition of positive charges is likely achieved by a large negatively charged surface region of the chaperone domain, which is highly conserved although individual positions are variable.

Much of the land economics literature has largely ignored the spatial nature of competition and related differences between farmland rental and sales markets when assessing return rates from farming, the capitalization of agricultural, environmental and energy policy into land values, and climate change impacts. We propose a model for price formation in both markets under a spatial competition framework. We demonstrate that price formation differs, particularly under policy-induced output price shocks.We suggest that using the rent-price ratio as an approximation for expectations in the net returns of farming, based on the net present value model, may produce biased results. In consequence, studies relying on land prices need to control for local land competition, farming structure, and policies.

Purpose Through activism, brands participate in the sociopolitical controversies that shape society today. Based on social identity theory, this study aims to examine the moderating effects of consumer–brand identification (CBI) and political ideology in explaining consumer responses to brand activism. Furthermore, the role of perceived marginalization that can arise in the case of consumer–brand disagreement is explored. Design/methodology/approach The hypothesized effects were tested in three experiments. Study 1 (n = 262) and Study 2 (n = 322) used a moderation analysis, which was supplemented by a mixed design analysis with repeated measures in Study 1. In Study 3 (n = 383), the mediating effect of perceived marginalization by the brand was tested using a moderated mediation model. Findings The results show that strong CBI as well as a conservative ideology buffer the negative effects of consumer–brand disagreement on brand attitude and word-of-mouth intentions. In the case of agreement with a brand’s stance, no direct or interactive effects of brand activism on consumer responses occur. Perceived marginalization by a brand mediates the effects of brand activism. Originality/value This study extends the “love is blind” versus “love becomes hate” debate to the realm of brand activism and finds evidence for the former effect. It also contributes to the research on political consumption by highlighting the role of political ideology as an important boundary condition for brand activism. Perceived marginalization is identified as a relevant risk for activist brands.

Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce.We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet.ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

In the dog, there is no luteolysis in the absence of pregnancy. Thus, this species lacks any antiluteolytic endocrine signal as found in other species that modulate uterine function during the critical period of pregnancy establishment. Nevertheless, in the dog an embryo-maternal communication must occur in order to prevent rejection of embryos. Based on this hypothesis, we performed microarray analysis of canine uterine samples collected during pre-attachment phase (days 10-12) and in corresponding non-pregnant controls, in order to elucidate the embryo attachment signal. An additional goal was to identify differences in uterine responses to pre-attachment embryos between dogs and other mammalian species exhibiting different reproductive patterns with regard to luteolysis, implantation, and preparation for placentation. Therefore, the canine microarray data were compared with gene sets from pigs, cattle, horses, and humans. We found 412 genes differentially regulated between the two experimental groups. The functional terms most strongly enriched in response to pre-attachment embryos related to extracellular matrix function and remodeling, and to immune and inflammatory responses. Several candidate genes were validated by semi-quantitative PCR. When compared with other species, best matches were found with human and equine counterparts. Especially for the pig, the majority of overlapping genes showed opposite expression patterns. Interestingly, 1926 genes did not pair with any of the other gene sets. Using a microarray approach, we report the uterine changes in the dog driven by the presence of embryos and compare these results with datasets from other mammalian species, finding common-, contrary-, and exclusively canine-regulated genes. Summary Sentence Pre-implantation embryos invoke functional changes in the canine uterus related to ongoing structural remodeling and immunological modulation; comparisons with different mammals reveal similarities and differences in maternal pregnancy recognition.