Miracle-dz/UniFAR-FTUs huggingface dataset:
Surface soil water content estimation based on thermal inertia and Bayesian smoothing

Soil water content plays a critical role in agro-hydrology since it regulates the rainfall partition between surface runoff and infiltration and, the energy partition between sensible and latent heat fluxes. Current thermal inertia models characterize the spatial and temporal variability of water content by assuming a sinusoidal behavior of the land surface temperature between subsequent acquisitions. Such behavior implicitly supposes clear sky during the whole interval between the thermal acquisitions; but, since this assumption is not necessarily verified even if sky is clear at the exact epoch of acquisition, , the accuracy of the model may be questioned due to spatial and temporal variability of cloud coverage. During the irrigation season, cloud coverage exhibits a quite regular daily behavior, which, when rendered in probabilistic terms, allows for an a-priory evaluation of the most likely suitable pair of images to estimate thermal inertia, given the results of the satellite passes. In turn, the water content of soil is estimated through thermal inertia by coupling diurnal optical and nighttime thermal images, e.g. as acquired by MODIS sensor on board polar orbiting satellites AQUA and TERRA, which have spatial resolution high enough to cope with typical agricultural applications. The method relies on the availability of the shortwave albedo and, at least, two daily thermographs preferably acquired in specific epochs of the day: the first at sunset when latent and heat fluxes are negligible; the second just before sunrise, when surface soil temperature reaches its minimum. Unfortunately, high resolution thermal images are often not available in those specific epochs, so that the accuracy of estimate accuracy decays even severely. In this perspective the paper, following previous contributions by some of the authors of the present paper [1-4], proposes exploiting SEVIRI data, characterized by higher acquisition rate but coarser spatial resolution as available from geostationary platform, to supplement MODIS data in a twofold way: i) by allowing to verify, by means of cloud detection algorithms, the hypothesis of clear sky throughout the time; ii) by synthesizing a high spatial/high temporal resolution sequence of images, through fusion of MODIS and SEVIRI data via Bayesian smoothing. A first validation of the latter method is achieved by comparing the results with in situ micro-meteorological measurements.
Detecting Soil Salinity in Alfalfa Fields using Spatial Modeling and Remote Sensing

A new methodology, which integrates field data, geographic information systems, remote sensing, and spatial modeling, was developed to accurately model soil salinity using statistical tools. Ground data from four alfalfa (Medicago sativa L.) fields in the lower Arkansas River basin in Colorado were compared with data derived from Ikonos satellite images with a 4-m resolution and Landsat satellite images with a 30-m resolution. For each image, the combination of satellite image bands that had the best correlation with soil salinity was used. Three statistical models were applied to estimate soil salinity from remote sensing: the ordinary least squares (OLS) model, the spatial autoregressive (spatial AR) model, and a modified residual kriging model. A number of criteria were evaluated to select the best model. The results show that both the Ikonos and Landsat satellite images can be used to estimate soil salinity, and regardless of the source of the satellite image used, the modified kriging model provided the best estimates of soil salinity. Although the OLS model met most of the model selection criteria, in most cases it involved some autocorrelation among the residuals. When the same data were tested using the spatial AR model, most of the autocorrelation among the residuals was removed, but the R 2 was reduced. In the modified kriging model, where the kriged residuals were combined with the results of the OLS model, there were significant improvements in the R 2 for all cases tested in this study. Thus, this study shows that combining field data, geographic information systems, and remote sensing with strong statistical measures can significantly enhance the development of high-quality soil salinity maps.
Lucidophyllous Forest Development since the Last Glacial Age in Southern Kyushu, Japan, Clarified by Phytolith Studies

鬼界アカホヤ火山灰(K-Ah)などの広域テフラを時間の指標として,植物珪酸体分析の結果から九州南部における最終氷期以降の照葉樹林の発達史について検討を行った. その結果,種子島では約65,000年前以降の最終氷期に,シイ属Castanopsisなどの照葉樹林が継続して存在していたことが確かめられた. その後,約11,000年前には薩摩半島でクスノキ科Lauraceaeが拡大を開始し,約6,300年前までにはシイ属やクスノキ科を主体とした照葉樹林が南九州の沿岸部をはじめ九州の内陸部にまで拡大していたと推定される. ただし,黒ボク土が広く分布する南九州の内陸部などでは,ネザサ節やススキ属などのイネ科主体の草原植生が継続されており,九州南部全域に照葉樹林が拡大したのは約4,200年前以降と推定される. 約6,300年前に鬼界カルデラから噴出した幸屋火砕流(K-Ky)が及んだ大隅半島南部や薩摩半島南部では,照葉樹林が絶えてススキ属Miscanthusなどが繁茂する草原植生に移行したことが確かめられた. これらの地域では,少なくとも600年間は照葉樹林が回復しなかったと推定されるが,幸屋火砕流が及ばなかった地域では照葉樹林が絶えるほどの影響を受けなかった可能性が考えられる.
A model of the seasonal cycle in the tropical Atlantic Ocean

In the western tropical Atlantic, seasonal variations in the surface winds and in the ocean are dominated by an annual harmonic. A simulation with a general circulation model indicates that the response in the western side of the basin is an equilibrium one practically in phase with the local winds. It includes the following: large vertical excursions of the thermocline that have a 180° change in phase across 8°N approximately; a change in the direction of the North Brazilian Coastal Current, which flows continuously along the coast between December and May but which veers offshore near 5°N to feed the North Equatorial Countercurrent during the other months; and a seasonal reversal of the countercurrent. To the east of 30°W, seasonal changes in the model have a prominent semiannual harmonic in phase with the local winds but only partially attributable to forcing at that frequency. The transients excited by the abrupt intensification of the southeast tradewinds in May happen to have a phase essentially the same as that of the semiannual forcing. These transients decay by the end of the calendar year, so that the seasonal cycle that starts with the intensification of the winds in May can be treated as an initial value problem as far as the upper ocean, above the thermocline, is concerned. The winds along the equator determine the response of the surface equatorial layer in the Gulf of Guinea but play a minor role in the seasonal upwelling along the coast near 5°N. That upwelling is strongly influenced by changes in both components of the wind, and in the curl of the wind, over the Gulf of Guinea.
Hydrographic and hydrochemical conditions in the Gotland Deep area between 1992 and 2003

The paper describes the hydrographic-hydrochemical development in the eastern Gotland Basin between the major saltwater inflows into the Baltic Sea in 1993 and 2003. This period is characterised by only low inflow activity. The most important hydrographic events were the effects of the very strong inflow in 1993 and the weak inflows in 1993/1994 and 1997. The 1993/1994 inflows led to deep-water renewal, a steep fall in deep-water temperatures, and increasing salinity. The effects of the inflow of very warm, saline and oxygen-rich water in autumn 1997 were observed in the deep water in 1998, resulting in temperatures rising to 7◦C. The recent renewal in spring 2003 is reflected in the decreasing temperature, higher salinity and improved ventilation of the bottom water. * This paper was presented at the Baltic Sea Science Congress (BSSC) in August 2003 in Helsinki. The complete text of the paper is available at http://www.iopan. gda.pl/oceanologia/ 558 G. Nausch, W. Matthäus, R. Feistel Changes in the redox conditions exert a considerable influence on the nutrient distribution. During stagnation periods, there is enrichment of phosphate and ammonium, while nitrate is absent. Thus, around 31 μmol l−1 ammonium and 7 μmol l−1 phosphate were measured prior to the water renewal in 2003. Deepwater ventilation results in lower phosphate concentrations of around 2 μmol l−1, the nitrification of ammonium and the occurrence of nitrate. For the observation period, an estimate of nutrients stored in the deep water was done for the eastern Gotland Basin. During the recent stagnation period, there was an increase of up to 150% in the phosphate pool below the halocline, whereas the pool of inorganic nitrogen compounds decreased to 80% compared with 1992 when the previous stagnation period had ended. Under specific circumstances, these unbalanced nutrients can be made available to the upper water layers and can induce large-scale blooms of algae, especially of cyanobacteria.
A NEW COELUROSAURIAN DINOSAUR FROM THE EARLY CRETACEOUS OF SOUTH AFRICA

Abstract We report the well preserved skeleton of a small theropod dinosaur, Nqwebasaurus thwazi, gen. et sp. nov., from the Lower Cretaceous Kirkwood Formation of South Africa. Nqwebasaurus has an elongate three-digit manus with a partially opposable first digit, a long and slender pes with a highly reduced metatarsal IV, and preserves gastroliths (stomach stones) in its abdominal region. As a basal coelurosaurian, Nqwebasaurus pushes back the Gondwanan record of this derived group of tetanuran theropods approximately 50 million years. This confirms that coelurosaurians were present on the Gondwana supercontinent well before its main phase of fragmentation and supports the hypothesis that this clade could have achieved a global distribution early in their evolution. Nqwebasaurus is one of the most complete and best preserved Cretaceous theropods described thus far from Africa.
Vertical crustal motions from the DORIS Space‐Geodesy System

Five years (1993–1997) of DORIS data on the SPOT and Topex‐Poseidon satellites have been analyzed to estimate vertical motions at 33 sites of the permanent DORIS network. Rates have been determined assuming constant velocity over the 5‐year time span. Except for a few stations, vertical rates are lower than 5 mm/yr. Comparison with solutions provided by GPS, SLR or VLBI at colocated sites shows good agreement for most stations. Some space‐geodesy vertical rates however disagree significantly. This may result from interannual to decadal fluctuations affecting the vertical motions, giving rise to different apparent linear trends if estimated over different time spans. Except for six high‐latitude stations, post‐glacial rebound produces negligible signal and cannot explain the observed motions. Other local or regional phenomena from geophysical or anthropogenic origin may be responsible for the estimated vertical motions.
A test of heterogeneous mixing as a mechanism for ecological persistence in a disturbed environment

Persistence is a central issue in population ecology with important implications for population management. Most theoretical studies have focused on continually interacting populations, even though many systems are subject to ecological disturbances which confound analysis of persistence. In this paper, we use a combination of a simple parasite–hyperparasite model with disturbances and field data to investigate the factors contributing to the observed persistence of the parasite population. The field data are taken from a two–year experiment (including five growing seasons) investigating the use of the mycoparasite Sporidesmium sclerotivorum as a persistent biological control agent of Sclerotinia minor, an economically important fungal parasite of lettuce. We show that the standard assumption of homogeneous mixing fails to predict the observed persistence of the parasite population. We demonstrate that allowing for heterogeneous mixing prevents the fade–out predicted in the homogeneous mixing case. The implications of the results for broad classes of host–parasite systems are discussed.
Post-transcriptional repression of mRNA enhances competence to transit from mitosis to meiosis in mouse spermatogenic cells

The special cell cycle known as meiosis transforms diploid germ cells into haploid gametes. In mammalian testes, diploid spermatogenic cells become competent to transition from mitosis to meiosis in response to retinoic acid. In mice, previous studies revealed that MEIOC, alongside binding partners YTHDC2 and RBM46, represses mitotic genes and promotes robust meiotic gene expression in spermatogenic cells that have already initiated meiosis. Here, we molecularly dissect MEIOC-dependent regulation in mouse spermatogenic cells and find that MEIOC actually shapes the transcriptome much earlier, even before meiotic initiation. MEIOC, acting with YTHDC2 and RBM46, destabilizes mRNA targets, including transcriptional repressors E2f6 and Mga, in mitotic spermatogonia. MEIOC thereby derepresses E2F6- and MGA-repressed genes, including Meiosin and other meiosis-associated genes. This confers on spermatogenic cells the molecular competence to, in response to retinoic acid, fully activate the STRA8-MEIOSIN transcriptional regulator, which is required for the meiotic G1/S cell cycle transition and meiotic gene expression. We conclude that in mice, mRNA decay mediated by MEIOC-YTHDC2-RBM46 enhances the competence of mitotic spermatogonia to transit from mitosis to meiosis.
An accurate probabilistic step finder for time-series analysis

Noisy time-series data is commonly collected from sources including Förster Resonance Energy Transfer experiments, patch clamp and force spectroscopy setups, among many others. Two of the most common paradigms for the detection of discrete transitions in such time-series data include: hidden Markov models (HMMs) and step-finding algorithms. HMMs, including their extensions to infinite state-spaces, inherently assume in analysis that holding times in discrete states visited are geometrically–or, loosely speaking in common language, exponentially–distributed. Thus the determination of step locations, especially in sparse and noisy data, is biased by HMMs toward identifying steps resulting in geometric holding times. In contrast, existing step-finding algorithms, while free of this restraint, often rely on ad hoc metrics to penalize steps recovered in time traces (by using various information criteria) and otherwise rely on approximate greedy algorithms to identify putative global optima. Here, instead, we devise a robust and general probabilistic (Bayesian) step-finding tool that neither relies on ad hoc metrics to penalize step numbers nor assumes geometric holding times in each state. As the number of steps themselves in a time-series are, a priori unknown, we treat these within a Bayesian nonparametric (BNP) paradigm. We find that the method developed, Bayesian Nonparametric Step (BNP-Step), accurately determines the number and location of transitions between discrete states without any assumed kinetic model and learns the emission distribution characteristic of each state. In doing so, we verify that BNP-Step can analyze sparser data sets containing higher noise and more closely-spaced states than otherwise resolved by current state-of-the-art methods. What is more, BNP-Step rigorously propagates measurement uncertainty into uncertainty over state transition locations, numbers, and emission levels as characterized by the posterior. We demonstrate the performance of BNP-Step on both synthetic data as well as data drawn from force spectroscopy experiments. SIGNIFICANCE Many time-series data sets exist which are challenging to analyze with current state-of-the-art methods, either because they contain excessive noise or because they violate one or more assumptions inherent to the chosen analysis method. To our knowledge, BNP-Step is the first time-series analysis algorithm which leverages Bayesian nonparametrics to learn the number and location of transitions between states and the emission levels associated to each state, while providing rigorous estimates of uncertainty for the learned quantities. We anticipate our algorithm will allow analysis of data sets at levels of noise or sparsity beyond what current state-of-the-art methods allow, and could potentially reveal previously unknown features in data sets analyzed using existing methods.
Autophagy contributes to homeostasis in esophageal epithelium where high autophagic vesicle content marks basal cells with limited proliferation and enhanced self-renewal potential

Background & Aims Autophagy has been demonstrated to play roles in esophageal pathologies both benign and malignant. Here, we aim to define the role of autophagy in esophageal epithelium under homeostatic conditions. Methods We generated tamoxifen-inducible, squamous epithelial-specific Atg7 (autophagy related 7) conditional knockout mice to evaluate effects on esophageal homeostasis and response to the carcinogen 4-nitroquinoline 1-oxide (4NQO) using histological and biochemical analyses. We FACS sorted esophageal basal cells based upon fluorescence of the autophagic vesicle (AV)-identifying dye Cyto-ID, then subjected these cells to transmission electron microscopy, image flow cytometry, 3D organoid assays, RNA-Sequencing (RNA-Seq), and cell cycle analysis. 3D organoids were subjected to passaging, single cell (sc) RNA-Seq, cell cycle analysis, and immunostaining. Results Genetic autophagy inhibition in squamous epithelium resulted in increased proliferation of esophageal basal cells. Esophageal basal cells with high AV level (Cyto-IDHigh) displayed limited organoid formation capability upon initial plating but passaged more efficiently than their counterparts with low AV level (Cyto-IDLow). RNA-Seq suggested increased autophagy in Cyto- IDHigh esophageal basal cells along with decreased cell cycle progression, the latter of which was confirmed by cell cycle analysis. scRNA-Seq of 3D organoids generated by Cyto-IDLow and Cyto- IDHigh cells identified expansion of 3 cell populations, enrichment of G2/M-associated genes, and aberrant localization of cell cycle-associated genes beyond basal cell populations in the Cyto- IDHigh group. Ki67 expression was also increased in organoids generated by Cyto-IDHigh cells, including in cells beyond the basal cell layer. Squamous epithelial-specific autophagy inhibition induced significant weight loss in mice treated with 4NQO that further displayed perturbed epithelial tissue architecture. Conclusions High AV level identifies esophageal epithelium with limited proliferation and enhanced self-renewal capacity that contributes to maintenance of the esophageal proliferation- differentiation gradient in vivo.
Preconfigured cortico-thalamic neural dynamics constrain movement-associated thalamic activity

Neural preconfigured activity patterns (nPAPs) have been proposed as building blocks for cognitive and sensory processing. However, their existence and function in motor networks have not been explicitly studied. Here, we explore the possibility that nPAPs are present in the motor thalamus (VL/VM) and their potential contribution to motor-related activity. To this end, we developed a preparation where VL/VM multiunitary activity could be robustly recorded in mouse behavior evoked by primary motor cortex (M1) optogenetic stimulation and forelimb movements. VL/VM-evoked activity was organized as rigid stereotypical activity patterns at the single and population levels. These activity patterns were unable to dynamically adapt to different temporal architectures of M1 stimulation. Moreover, they were experience-independent and present in virtually all animals, confirming their preconfigured nature. Finally, subpopulations expressing specific M1-evoked patterns also displayed specific movement-related patterns. Our data demonstrate that the behaviorally related identity of specific neural subpopulations is tightly linked to nPAPs.
A phage nucleus-associated RNA-binding protein is required for jumbo phage infection

Large-genome bacteriophages (jumbo phages) of the Chimalliviridae family assemble a nucleus-like compartment bounded by a protein shell that protects the replicating phage genome from host-encoded restriction enzymes and CRISPR/Cas nucleases. While the nuclear shell provides broad protection against host nucleases, it necessitates transport of mRNA out of the nucleus-like compartment for translation by host ribosomes, and transport of specific proteins into the nucleus-like compartment to support DNA replication and mRNA transcription. Here we identify a conserved phage nuclear shell-associated protein that we term Chimallin C (ChmC), which adopts a nucleic acid-binding fold, binds RNA with high affinity in vitro, and binds phage mRNAs in infected cells. ChmC also forms phase-separated condensates with RNA in vitro. Targeted knockdown of ChmC using mRNA-targeting dCas13d halts infections at an early stage. Taken together, our data suggest that the conserved ChmC protein acts as a chaperone for phage mRNAs, potentially stabilizing these mRNAs and driving their translocation through the nuclear shell to promote translation and infection progression.
A whole-brain model of auditory discrimination

Whole-brain simulations have been proposed previously to simulate global properties such as brain states or functional connectivity. Here, our aim is to build a whole-brain model to simulate a simple cognitive paradigm involving multiple brain areas. We focus on auditory discrimination, using a paradigm designed for the macaque cortex. To model at the whole-brain scale, we use The Virtual Brain (TVB) [18] simulation environment. TVB is a computational framework which simulates the brain as a network of small brain regions, where each node models neuronal populations and the connectivity between nodes determines the pathway of information flow over the brain. We use Adaptive Exponential (AdEx) neuronal population models [4, 11] to describe each node. For the connectivity, we use the open-access CoCoMac connectivity dataset [2], which is a matrix containing the connection weights between the nodes. We focus on a cognitive task that mainly involves the prefrontal cortex (PFC). In the auditory discrimination task, our pipeline starts from the primary auditory cortex stimulated by the auditory signals, it is then modulated in the PFC so that the stimulus discrimination occurs, after competition. Finally, it ends in the primary motor cortex which outputs the neuronal activity determining the motor action. Because the AdEx mean-fields can provide access to neuronal activity or local field potentials, we think that the present model constitutes a useful tool to promote interactions between theory and experiments for simple cognitive tasks in macaque monkey.