Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

The spaceborne imaging spectroscopy mission PRecursore IperSpettrale della Missione Applicativa (PRISMA), launched on 22 March 2019 by the Italian Space Agency, opens new opportunities in many scientific domains, including precision farming and sustainable agriculture. This new Earth Observation (EO) data stream requires new-generation approaches for the estimation of important biophysical crop variables (BVs). In this framework, this study evaluated a hybrid approach, combining the radiative transfer model PROSAIL-PRO and several machine learning (ML) regression algorithms, for the retrieval of canopy chlorophyll content (CCC) and canopy nitrogen content (CNC) from synthetic PRISMA data. PRISMA-like data were simulated from two images acquired by the airborne sensor HyPlant, during a campaign performed in Grosseto (Italy) in 2018. CCC and CNC estimations, assessed from the best performing ML algorithms, were used to define two relations with plant nitrogen uptake (PNU). CNC proved to be slightly more correlated to PNU than CCC (R-2 = 0.82 and R-2 = 0.80, respectively). The CNC-PNU model was then applied to actual PRISMA images acquired in 2020. The results showed that the estimated PNU values are within the expected ranges, and the temporal trends are compatible with plant phenology stages

miRNA-126 Orchestrates an Oncogenic Program in B Cell Precursor Acute Lymphoblastic Leukemia

MicroRNA (miRNA)-126 is a known regulator of hematopoietic stem cell quiescence. We engineered murine hematopoiesis to express miRNA-126 across all differentiation stages. Thirty percent of mice developed monoclonal B cell leukemia, which was prevented or regressed when a tetracycline-repressible miRNA-126 cassette was switched off. Regression was accompanied by upregulation of cell-cycle regulators and B cell differentiation genes, and downregulation of oncogenic signaling pathways. Expression of dominant-negative p53 delayed blast clearance upon miRNA-126 switch-off, highlighting the relevance of p53 inhibition in miRNA-126 addiction. Forced miRNA-126 expression in mouse and human progenitors reduced p53 transcriptional activity through regulation of multiple p53-related targets. miRNA-126 is highly expressed in a subset of human B-ALL, and antagonizing miRNA-126 in ALL xenograft models triggered apoptosis and reduced disease burden

MODIStsp: An R package for automatic preprocessing of MODIS Land Products time series

MODIStsp is a new R package allowing automating the creation of raster time series derived from MODIS Land Products. It allows performing several preprocessing steps (e.g. download, mosaicing, reprojection and resize) on MODIS products on a selected time period and area. All processing parameters can be set with a user-friendly GUI, allowing users to select which specific layers of the original MODIS HDF files have to be processed and which Quality Indicators have to be extracted from the aggregated MODIS Quality Assurance layers. Moreover, the tool allows on-the-fly computation of time series of Spectral Indexes (either standard or custom-specified by the user through the GUI) from surface reflectance bands. Outputs are saved as single-band rasters corresponding to each available acquisition date and output layer. Virtual files allowing easy access to the entire time series as a single file using common image processing/GIS software or R scripts can be also created. Non-interactive execution within an R script and stand-alone execution outside an R environment exploiting a previously created Options File are also possible, the latter allowing scheduling execution of MODIStsp to automatically update a time series when a new image is available. The proposed software constitutes a very useful tool for the Remote Sensing community, since it allows performing all the main preprocessing steps required for the creation of time series of MODIS data within a common framework, and without requiring any particular programming skills by its users

Risk and Protective Factors regarding Child Neglect: Differences among Immigrant and Italian Parents

Risk and protective factors regarding child neglect and maltreatment among immigrant families as well as families who live in their native country are widely studied. However, differences in risk and protective factors for child neglect among immigrant parents and Italian ones living in Italy have been less studied. The aim of this study is to investigate eventual differences, in cases of child neglect, between risk and protective factors in Italian and immigrant parents. This study uses retrospective data and included 141 mothers (70 immigrants and 71 Italians) and 130 fathers (61 immigrants and 69 Italians). The data for this study was attained through the submission of the Risk and Protective Factors Protocol. Italian and immigrant fathers and mothers had different combinations of these factors for child neglect. In particular immigrant mothers are more represented by risk factors such as chronic poverty, lack of social integration, distrust of social rules and institutions, approval of corporal punishments as educational practice and social deviance were the most common risk factors, whereas among Italian mothers, risk factors such as separation anxiety, and child physical disease, and disorder at birth were more common. Furthermore, immigrant fathers were more likely to approve of corporal punishment as educational practice, whereas Italian fathers were more likely to exhibit the proximal risk factor compensation syndrome

ropensci/MODIStsp: Version 2.0.5

MODIStsp 2.0.5 Main changes Edit documentation related to the change of maintainer (see https://docs.ropensci.org/MODIStsp/articles/lorenzo). Add the argument parallel to function MODIStsp() and MODSIStsp_process() to allow running the processing in single core modality. Minor changes Fix Travis tests Bug fix (#222) Previous versions Versions 2.0.0 to 2.0.4 were not referenced on GitHub; here below the news of those versions (the source code can be found on CRAN). MODIStsp 2.0.3 - Main changes This submission should fix errors on Debian CRAN builds, due to improper trigger of an internal function leading to writing in the user's lib folder. Fixes a bug leading to crash when using scale_val = TRUE and change_no_data = FALSE Fixes a bug leading to the GUI crashing rather than giving info messages in case not all input parameters are specified Implements redirection to MODIS products web pages when pressing the corresponding button Modifies slightly the Shiny GUI MODIStsp 2.0.0 - Main changes Replace the old gWidgets-based GUI with a new one based on Shiny; Enhances support for CLI usage. Now all parameters can be passed to the MODIStsp function. If also a opts_file is passed, values specified explicitly in the call override those in the options file; Fixes problems in retrieval of corners for MODIS products in 4008 projection (fixes #204); Fixes problems/improves support for datasets with multiple NoData values. Now, all NoData values are kept to original values if NoData change is set to FALSE. Also, Scale/Offset are no longer wrongly applied also to NoData values when scaleval = TRUE

A control-based observer approach for estimating energy intake during pregnancy

Gestational weight gain outside of Institute of Medicine guidelines poses a risk to both the mother and her unborn child. Behavioral interventions such as Healthy Mom Zone (HMZ) that aim to regulate gestational weight gain require self-monitoring of energy intake, which is often significantly under-reported by participants. This article describes the use of a control systems approach for energy intake estimation during pregnancy. It relies on an energy balance model that predicts gestational weight based on physical activity and energy intake, the latter treated as an unmeasured disturbance. Two control-based observer formulations relying on Internal Model Control and Model Predictive Control, respectively, are presented in this article, first for a hypothetical participant, then on data collected from four HMZ participants. Results demonstrate the effectiveness of the method, with generally best results obtained when estimating energy intake over a weekly time period