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The combination of nontrivial band topology and symmetry-breaking phases gives rise to novel quantum states and phenomena such as topological superconductivity, quantum anomalous Hall effect, and axion electrodynamics. Evidence of intertwined charge density wave (CDW) and superconducting order parameters has recently been observed in a novel kagome material AV_{3}Sb_{5} (A=K, Rb, Cs) that features a Z_{2} topological invariant in the electronic structure. However, the origin of the CDW and its intricate interplay with the topological state has yet to be determined. Here, using hard-x-ray scattering, we demonstrate a three-dimensional CDW with 2×2×2 superstructure in (Rb,Cs)V_{3}Sb_{5}. Unexpectedly, we find that the CDW fails to induce acoustic phonon anomalies at the CDW wave vector but yields a novel Raman mode that quickly damps into a broad continuum below the CDW transition temperature. Our observations exclude strong electron-phonon-coupling-driven CDW in AV_{3}Sb_{5} and support an unconventional CDW that was proposed in the kagome lattice at van Hove filling.

The recent and excellent edition of the most famous Ruzante’s comedy, curated by Luca D’Onghia, offers, among other things, a text restored and free of dense didactic remark with which it was always read to analyze it or to stage, since the sixties of last century and since the edition of Ludovico Zorzi. Written for four hands, the present work moves in two directions: on the one hand it reconstructs the history of this didactic interpolation, bearer not only of interpretation but of a real rewrite and secondly it wants to return to original text, coming to propose a conclusion of the play completely different from what was supposed to be and from what was view on stage.

Aim. Gestational diabetes mellitus (GDM) and celiac disease, if not diagnosed and properly treated, are associated with adverse outcomes of pregnancy. The aim of our study was to examine pregnancies complicated by GDM in celiac and nonceliac women in terms of their metabolic parameters and maternal and fetal outcomes. Methods. The study involved 60 women with GDM, 20 with and 40 without celiac disease. Maternal clinical and metabolic parameters (glucose and insulin levels in the oral glucose tolerance test (OGTT), fasting plasma glucose, HbA1c, lipid profile, prepregnancy BMI, gestational weight gain, and chronic diseases), pregnancy outcomes (gestational hypertension, pre-eclampsia, eclampsia, time, and mode of delivery), and fetal parameters (weight and length at birth, and neonatal complications) were recorded. Results. The two groups did not differ significantly in maternal parameters other than blood glucose levels at 120′ in the diagnostic OGTT (141.2 ± 35.2 vs 161.2 ± 35.4, mg/dl, p=0.047), prepartum cLDL (127.2 ± 43.5 vs 179.6 ± 31.7 mg/dl, p≤0.001), and total cholesterol (229.0 ± 45.9 vs 292.5 ± 42.1 mg/dl, p≤0.001), which were significantly lower in celiac women than in nonceliac controls. Children born from celiac women had a significantly higher birth weight (3458.1 ± 409.8 vs 3209.0 ± 432.7 g, p=0.044) and ponderal index (2.89 ± 0.32 vs 2.66 ± 0.25 g/cm3, p=0.006) and were more likely to be large for gestational age (27.8% vs 2.5%, p=0.012). Analyzing the composition of the celiac and nonceliac women’s diet showed that, for the same amount of kilocalories, the gluten-free diet was associated with a slight increase in the amount of carbohydrates (49.75% vs 48.54%) and a reduction in the amount of protein (21.10% vs 23.31%) and especially of fiber (9.84% vs 12.71%). Conclusions. Celiac women with GDM have much the same pregnancy outcomes as nonceliac women with GDM, except for fetal overgrowth. Gluten-free food, being richer in carbohydrates and less rich in fiber and protein, could have a role in fetal growth in celiac women.

Plant biodiversity is an important feature of grassland ecosystems, as it is related to the provision of many ecosystem services crucial for the human economy and well-being. Given the importance of grasslands, research has been carried out in recent years on the potential to monitor them with novel remote sensing techniques. In this study, the optical diversity (also called spectral diversity) approach was adopted to check the potential of using high-resolution hyperspectral images to estimate α-diversity in grassland ecosystems. In 2018 and 2019, grassland species composition was surveyed and canopy hyperspectral data were acquired at two grassland sites: Monte Bondone (IT-MBo; species-rich semi-natural grasslands) and an experimental farm of the University of Padova, Legnaro, Padua, Italy (IT-PD; artificially established grassland plots with a species-poor mixture). The relationship between biodiversity (species richness, Shannon’s, species evenness, and Simpson’s indices) and optical diversity metrics (coefficient of variation-CV and standard deviation-SD) was not consistent across the investigated grassland plant communities. Species richness could be estimated by optical diversity metrics with an R = 0.87 at the IT-PD species-poor site. In the more complex and species-rich grasslands at IT-MBo, the estimation of biodiversity indices was more difficult and the optical diversity metrics failed to estimate biodiversity as accurately as in IT-PD probably due to the higher number of species and the strong canopy spatial heterogeneity. Therefore, the results of the study confirmed the ability of spectral proxies to detect grassland α-diversity in man-made grassland ecosystems but highlighted the limitations of the spectral diversity approach to estimate biodiversity when natural grasslands are observed. Nevertheless, at IT-MBo, the optical diversity metric SD calculated from post-processed hyperspectral images and transformed spectra showed, in the red part of the spectrum, a significant correlation (up to R = 0.56, p = 0.004) with biodiversity indices. Spatial resampling highlighted that for the IT-PD sward the optimal optical pixel size was 1 cm, while for the IT-MBo natural grassland it was 1 mm. The random pixel extraction did not improve the performance of the optical diversity metrics at both study sites. Further research is needed to fully understand the links between α-diversity and spectral and biochemical heterogeneity in complex heterogeneous ecosystems, and to assess whether the optical diversity approach can be adopted at the spatial scale to detect β-diversity. Such insights will provide more robust information on the mechanisms linking grassland diversity and optical heterogeneity.

Armillaria genus represents one of the most common causes of chronic root rot disease in woody plants. Prompt recognition of diseased plants is crucial to control the pathogen. However, the current disease detection methods are limited at a field scale. Therefore, an alternative approach is needed. In this study, we investigated the potential of hyperspectral techniques to identify fungi-infected vs. healthy plants of Vitis vinifera. We used the hyperspectral imaging sensor Specim-IQ to acquire leaves’ reflectance data of the Teroldego Rotaliano grapevine cultivar. We analyzed three different groups of plants: healthy, asymptomatic, and diseased. Highly significant differences were found in the near-infrared (NIR) spectral region with a decreasing pattern from healthy to diseased plants attributable to the leaf mesophyll changes. Asymptomatic plants emerged from the other groups due to a lower reflectance in the red edge spectrum (around 705 nm), ascribable to an accumulation of secondary metabolites involved in plant defense strategies. Further significant differences were observed in the wavelengths close to 550 nm in diseased vs. asymptomatic plants. We evaluated several machine learning paradigms to differentiate the plant groups. The Naïve Bayes (NB) algorithm, combined with the most discriminant variables among vegetation indices and spectral narrow bands, provided the best results with an overall accuracy of 90% and 75% in healthy vs. diseased and healthy vs. asymptomatic plants, respectively. To our knowledge, this study represents the first report on the possibility of using hyperspectral data for root rot disease diagnosis in woody plants. Although further validation studies are required, it appears that the spectral reflectance technique, possibly implemented on unmanned aerial vehicles (UAVs), could be a promising tool for a cost-effective, non-invasive method of Armillaria disease diagnosis and mapping in-field, contributing to a significant step forward in precision viticulture.

Background: Several instruments have been proposed to investigate restricted, repetitive behaviors (RRBs) in individuals with Autism Spectrum Disorder (ASD). Systematic video observations may overcome questionnaire and interview limitations to investigate RRBs. This study aimed to analyze stereotypic patterns through video recordings and to determine the correlation between the number and appearance of RRBs to ASD severity. Methods: Twenty health professionals wearing a body cam recorded 780 specific RRBs during everyday activities of 67 individuals with ASD (mean age: 14.2 ± 3.72 years) for three months. Each stereotypy was classified according to its complexity pattern (i.e., simple or complex) based on body parts and sensory channels involved. Results: The RRBs spectrum for each subject ranged from one to 33 different patterns (mean: 11.6 ± 6.82). Individuals with a lower number of stereotypies shown a lower ASD severity compared to subjects with a higher number of stereotypies (p = 0.044). No significant differences were observed between individuals exhibiting simple (n = 40) and complex patterns (n = 27) of stereotypies on ASD severity, age, sex, and the number of stereotypes. Conclusions: This study represents the first attempt to systematically document expression patterns of RRBs with a data-driven approach. This may provide a better understanding of the pathophysiology and management of RRBs.

Electronic flat-band materials host quantum states characterized by a quenched kinetic energy. These flat bands are often conducive to enhanced electron correlation effects and emergent quantum phases of matter1. Long studied in theoretical models2–4, these systems have received renewed interest after their experimental realization in van der Waals heterostructures5,6 and quasi-two-dimensional (2D) crystalline materials7,8. An outstanding experimental question is if such flat bands can be realized in three-dimensional (3D) networks, potentially enabling new materials platforms9,10 and phenomena11–13. Here we investigate the C15 Laves phase metal CaNi2, which contains a nickel pyrochlore lattice predicted at a model network level to host a doubly-degenerate, topological flat band arising from 3D destructive interference of electronic hopping14,15. Using angle-resolved photoemission spectroscopy, we observe a band with vanishing dispersion across the full 3D Brillouin zone that we identify with the pyrochlore flat band as well as two additional flat bands that we show arise from multi-orbital interference of Ni d-electrons. Furthermore, we demonstrate chemical tuning of the flat-band manifold to the Fermi level that coincides with enhanced electronic correlations and the appearance of superconductivity. Extending the notion of intrinsic band flatness from 2D to 3D, this provides a potential pathway to correlated behaviour predicted for higher-dimensional flat-band systems ranging from tunable topological15 to fractionalized phases16.Angle-resolved photoemission spectroscopy of CaNi2 shows a band with vanishing dispersion across the full 3D Brillouin zone that is identified with the pyrochlore flat band as well as two additional flat bands that arise from multi-orbital interference of Ni d-electrons. [ABSTRACT FROM AUTHOR]

Red-edge (RE) spectral vegetation indices (SVIs)—combining bands on the sharp change region between near infrared (NIR) and visible (VIS) bands—alongside with SVIs solely based on NIR-shoulder bands (wavelengths 750–900 nm) have been shown to perform well in estimating leaf area index (LAI) from proximal and remote sensors. In this work, we used RE and NIR-shoulder SVIs to assess the full potential of bands provided by Sentinel-2 (S-2) and Sentinel-3 (S-3) sensors at both temporal and spatial scales for grassland LAI estimations. Ground temporal and spatial observations of hyperspectral reflectance and LAI were carried out at two grassland sites (Monte Bondone, Italy, and Neustift, Austria). A strong correlation (R2 > 0.8) was observed between grassland LAI and both RE and NIR-shoulder SVIs on a temporal basis, but not on a spatial basis. Using the PROSAIL Radiative Transfer Model (RTM), we demonstrated that grassland structural heterogeneity strongly affects the ability to retrieve LAI, with high uncertainties due to structural and biochemical PTs co-variation. The RENDVI783.740 SVI was the least affected by traits co-variation, and more studies are needed to confirm its potential for heterogeneous grasslands LAI monitoring using S-2, S-3, or Gaofen-5 (GF-5) and PRISMA bands.