Quasi-static and low-velocity impact behavior of intraply hybrid flax/basalt composites

In an attempt to increase the low-velocity impact response of natural fiber composites, a new hybrid intraply woven fabric based on flax and basalt fibers has been used to manufacture laminates with both thermoplastic and thermoset matrices. The matrix type (epoxy or polypropylene (PP) with or without a maleated coupling agent) significantly affected the absorbed energy and the damage mechanisms. The absorbed energy at perforation for PP-based composites was 90% and 50% higher than that of epoxy and compatibilized PP composites, respectively. The hybrid fiber architecture counteracted the influence of low transverse strength of flax fibers on impact response, irrespective of the matrix type. In thermoplastic laminates, the matrix plasticization delayed the onset of major damage during impact and allowed a better balance of quasi-static properties, energy absorption, peak force, and perforation energy compared to epoxy-based composites

Rubric-based Learner Modelling via Noisy Gates Bayesian Networks for Computational Thinking Skills Assessment

In modern and personalised education, there is a growing interest in developing learners’ competencies and accurately assessing them. In a previous work, we proposed a procedure for deriving a learner model for automatic skill assessment from a task-specific competence rubric, thus simplifying the implementation of automated assessment tools. The previous approach, however, suffered two main limitations: (i) the ordering between competencies defined by the assessment rubric was only indirectly modelled; (ii) supplementary skills, not under assessment but necessary for accomplishing the task, were not included in the model. In this work, we address issue (i) by introducing dummy observed nodes, strictly enforcing the skills ordering without changing the network’s structure. In contrast, for point (ii), we design a network with two layers of gates, one performing disjunctive operations by noisy-OR gates and the other conjunctive operations through logical ANDs. Such changes improve the model outcomes’ coherence and the modelling tool’s flexibility without compromising the model’s compact parametrisation, interpretability and simple experts’ elicitation. We used this approach to develop a learner model for Computational Thinking (CT) skills assessment. The CT-cube skills assessment framework and the Cross Array Task (CAT) are used to exemplify it and demonstrate its feasibility

Morphological variation on tomato leaves due to different nitrogen contents

Elliptic Fourier Analysis (EFA) is a method used to quantify shape differences.  It mathematically describes the entire shape of an object by transforming the contour into Fourier coefficients, used as variables for statistical analysis, and involving the fitting of some type of curve to the object outline.  Generally, the shape of agricultural products such as fruit, vegetables, grain and in addition other organs of plant is one of the most important factors for their classification and grading in relation to commercial quality and organoleptic properties.  The aim of this study is to quantify the morphological variation of the shape of tomato leaves in response to their different nitrogen (N) content using the EFA coefficients, the fractal geometry and the perimeter ratio in combination with the Partial Least Squares Discriminant Analysis (PLS-DA).  The analyses were realized on a tomato crop where each sample was chemically analyzed at the laboratory to establish the N content.  The leaves (168) were divided into 3 groups following different N concentrations.  Results suggest no relation between leaves lengths and N concentration is present following the Kruskal-Wallis performed with a p=0.735.  The PLS-DA performing on the EFA coefficients, fractal index and perimeter ratio shows a high sensitivity, sensibility, and reduced mean classification error (82.3%, 81.07% and 18.3% respectively).  The percentages of the correct classification in the model resulted to be 69.29% while the independent test equal to 56.1%.  This study demonstrated the relation between leaf shape and N content (expressed in 3 concentration groups).Keywords: Tomato leaf, elliptic Fourier analysis, fractal index, perimeter ratio, partial least squares discriminant analysis

Greenhouse application of light-drone imaging technology for assessing weeds severity occurring on baby-leaf red lettuce beds approaching fresh-cutting

Aim of study: For baby-leaf lettuces greenhouse cultivations the absence of weeds is a mandatory quality requirement. One of the most promising and innovative technologies in weed research, is the use of Unmanned Aerial Vehicles (or drones) equipped with acquisition systems. The aim of this study was to provide an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone equipped with an RGB microcamera.Area of study: Trials were performed at specialized organic farm site in Eboli (Salerno, Italy), under polyethylene multi-tunnel greenhouse.Material and methods: The RGB images acquired were processed with specific algorithms distinguishing weeds from crop yields, estimating the weeds covered surface and the severity of weed contamination in terms of biomass. A regression between the percentage of the surface covered by weed (with respect to the image total surface) and the weight of weed (with respect to the total harvested biomass) was calculated.Main results: The regression between the total cover values of the 25 calibration images and the total weight measured report a significant linear correlation. Digital monitoring was able to capture with accuracy the highly variable weed coverage that, among the different grids positioned under real cultivation conditions, was in the range 0-16.4% of the total cultivated one.Research highlights: In a precision weed management context, with the aim of improving management and decreasing the use of pesticides, this study provided an estimation of the exact weed amount on baby-sized red lettuce beds using a light drone

A quantitative multivariate methodology for unsupervised class identification in pistachio (Pistacia vera L.) plant leaves size

Aim of study: Genetic diversity of pistachio, can be evaluated by using different descriptors, as adopted in international certification systems. Mainly the descriptors are morphological traits as leaf, which represents an important organ for its sensibility to growth conditions during the expansion phase. This study adopted a rapid and quantitative non-hierarchic clustering classification (k-means), to extract size classes basing on the contemporary combination of different morphological traits (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) of a varietal collection composed by 21 pistachio cultivars.Area of study: Worldwide.Material and methods: The unsupervised non-hierarchic clustering technique was adopted to the entire samples of pistachio leaves from k=2 to k=15 for both four morphological variables (i.e., leaf stalk length, terminal leaf length, terminal leaf width and terminal leaf ratio) and three morphological variables (i.e., terminal leaf length, terminal leaf width and terminal leaf ratio).Main results: A classification model only on the three morphological variables (for results of statistical analysis in which the groups resulted to be more separated and different for all the variables), with k= 5 (five groups), was constructed using a non-linear artificial neural network approach. The percentages of bad prediction in both training and testing resulted equal to 0%. The “terminal leaf length” returned the higher impact (44.89%).Research highlights: The contemporary combination of different morphological leaf traits, allowed to create an automatic classification of size classes of great importance for cultivar identification and comparison

HST unveils a compact mildly relativistic Broad Line Region in the candidate true type 2 NGC 3147

NGC 3147 has been considered the best case of a true type 2 AGN: an unobscured AGN, based on the unabsorbed compact X-ray continuum, which lacks a broad line region (BLR). However, the very low luminosity of NGC 3147 implies a compact BLR, which produces very broad lines, hard to detect against the dominant background host galaxy. Narrow (0.1"x0.1") slit HST spectroscopy allowed us to exclude most of the host galaxy light, and revealed an H$\alpha$ line with an extremely broad base (FWZI$\sim27\,000$ km s$^{-1}$). The line profile shows a steep cutoff blue wing and an extended red wing, which match the signature of a mildly relativistic thin accretion disk line profile. It is indeed well fit with a nearly face on thin disk, at $i\sim23^\circ$, with an inner radius at $77\pm15$ r$_g$, which matches the prediction of $62^{+18}_{-14}$ r$_g$ from the $R_{\rm BLR} \sim L^{1/2}$ relation. This result questions the very existence of true type 2 AGN. Moreover, the detection of a thin disk, which extends below 100 r$_g$ in an $L/L_{\rm Edd}\sim10^{-4}$ system, contradicts the current view of the accretion flow configuration at extremely low accretion rates.Comment: 6 pages, 3 figures, accepted for publication in MNRAS Letter

Clasp2 ensures mitotic fidelity and prevents differentiation of epidermal keratinocytes

Epidermal homeostasis is tightly controlled by a balancing act of self-renewal or terminal differentiation of proliferating basal keratinocytes. An increase in DNA content as a consequence of a mitotic block is a recognized mechanism underlying keratinocyte differentiation, but the molecular mechanisms involved in this process are not yet fully understood. Using cultured primary keratinocytes, here we report that the expression of the mammalian microtubule and kinetochore-associated protein Clasp2 is intimately associated with the basal proliferative makeup of keratinocytes, and its deficiency leads to premature differentiation. Clasp2-deficient keratinocytes exhibit increased centrosomal numbers and numerous mitotic alterations, including multipolar spindles and chromosomal misalignments that overall result in mitotic stress and a high DNA content. Such mitotic block prompts premature keratinocyte differentiation in a p53-dependent manner in the absence of cell death. Our findings reveal a new role for Clasp2 in governing keratinocyte undifferentiated features and highlight the presence of surveillance mechanisms that prevent cell cycle entry in cells that have alterations in the DNA content.This work was supported by grants from the Spanish Ministerio de Economia y Competitividad (MINECO) [BFU2012-33910 and BFU2015-71376-R (MINECO/ European Regional Development Fund (ERDF), European Union) to M.P.-M.]. Deposited in PMC for immediate release.S