Pairwise Registration by Local Orientation Cues

Inspired by recent work on robust and fast computation of 3D Local Reference Frames (LRFs), we propose a novel pipeline for coarse registration of 3D point clouds. Key to the method are: (i) the observation that any two corresponding points endowed with an LRF provide a hypothesis on the rigid motion between two views, (ii) the intuition that feature points can be matched based solely on cues directly derived from the computation of the LRF, (iii) a feature detection approach relying on a saliency criterion which captures the ability to establish an LRF repeatably. Unlike related work in literature, we also propose a comprehensive experimental evaluation based on diverse kinds of data (such as those acquired by laser scanners, Kinect and stereo cameras) as well as on quantitative comparison with respect to other methods. We also address the issue of setting the many parameters that characterize coarse registration pipelines fairly and realistically. The experimental evaluation vouches that our method can handle effectively data acquired by different sensors and is remarkably fast.     

Feedforward networks in financial predictions: the future that modifies the present

The main goal of this paper is to show how relatively minor modifications of well-known algorithms (in particular, back propagation) can dramatically increase the performance of an artificial neural network (ANN) for time series prediction. We denote our proposed sets of modifications as the 'self-momentum', 'Freud' and 'Jung' rules. In our opinion, they provide an example of an alternative approach to the design of learning strategies for ANNs, one that focuses on basic mathematical conceptualization rather than on formalism and demonstration. The complexity of actual prediction problems makes it necessary to experiment with modelling possibilities whose inherent mathematical properties are often not well understood yet. The problem of time series prediction in stock markets is a case in point. It is well known that asset price dynamics in financial markets are difficult to trace, let alone to predict with an operationally interesting degree of accuracy. We therefore take financial prediction as a meaningful test bed for the validation of our techniques. We discuss in some detail both the theoretical underpinnings of the technique and our case study about financial prediction, finding encouraging evidence that supports the theoretical and operational viability of our new ANN specifications. Ours is clearly only a preliminary step. Further developments of ANN architectures with more and more sophisticated 'learning to learn' characteristics are now under study and test.     

Development and applications of surface-activated chemical ionization

This review regards the recently developed ionization source named surface-activated chemical ionization (SACI) that employs an interaction with a surface placed at low voltage for the activation of the ionization of sample molecules to increase the sensitivity in the analysis of various compounds of biological and clinical interest. These results are due to the strong chemical noise decrease and the increase of ionization efficiency. This ionization source has been employed for the analysis of various compounds of different molecular mass and polarity (addicted and pharmaceutical drugs, amino acids, steroids, peptides, and proteins). The SACI development theoretical mechanism, benefits, disadvantages, applications, and future developments are reported and discussed.     

Estimation of predictive accuracy in survival analysis using R and S-PLUS

When the purpose of a survival regression model is to predict future outcomes, the predictive accuracy of the model needs to be evaluated before practical application. Various measures of predictive accuracy have been proposed for survival data, none of which has been adopted as a standard, and their inclusion in statistical software is disregarded. We developed the surev library for R and S-PLUS, which includes functions for evaluating the predictive accuracy measures proposed by Schemper and Henderson. The library evaluates the predictive accuracy of parametric regression models and of Cox models. The predictive accuracy of the Cox model can be obtained also when time-dependent covariates are included because of non-proportional hazards or when using Bayesian model averaging. The use of the library is illustrated with examples based on a real data set.     

An Integrated Assessment of the Impacts of Changing Climate Variability on Agricultural Productivity and Profitability in an Irrigated Mediterranean Catchment

Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ET_N), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ET_N may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.     

Geometry and Stacking Sequence Effect on Composite Spinnaker Pole's Stiffness: Experimental and Numerical Analysis

Composite materials are widely employed in sailing sports, a possible application is for the mast pole or other sail poles. In the paper the attention is focused on the spinnaker poles mechanical performances; in particular the focus is on axial and ring compressive properties of three different carbon fibre/epoxy resin spinnaker poles, to investigate both the diameter and stacking sequence effect on the mechanical performance of the structure. Starting from the stacking sequence used in the production of a particular spinnaker pole, the effect of a lamina at 0° in the middle of wall thickness is investigated with the purpose to obtain a more stiff structure. Moreover to test the proposed stacking sequence on different size products, a prototype with lower diameter is realized. To properly evaluate axial and ring stiffness, axial compression test and ring stiffness one are performed. Then a numerical model is developed to support the design of the finished product: A simple and versatile numerical analysis (FEA with software ANSYS), by simulating ring stiffness and pull-direction compression tests, is carried out in elastic regime. Such model should be suitable for designing and/or verifying the mechanical performance of pole structures, even though differing from those above described, for materials, geometry and stacking sequence.     

Distinct Tomato Cultivars Are Characterized by a Differential Pattern of Biochemical Responses to Drought Stress

Future climate scenarios suggest that crop plants will experience environmental changes capable of affecting their productivity. Among the most harmful environmental stresses is drought, defined as a total or partial lack of water availability. It is essential to study and understand both the damage caused by drought on crop plants and the mechanisms implemented to tolerate the stress. In this study, we focused on four cultivars of tomato, an economically important crop in the Mediterranean basin. We investigated the biochemical mechanisms of plant defense against drought by focusing on proteins specifically involved in this stress, such as osmotin, dehydrin, and aquaporin, and on proteins involved in the general stress response, such as HSP70 and cyclophilins. Since sugars are also known to act as osmoprotectants in plant cells, proteins involved in sugar metabolism (such as RuBisCO and sucrose synthase) were also analyzed. The results show crucial differences in biochemical behavior among the selected cultivars and highlight that the most tolerant tomato cultivars adopt quite specific biochemical strategies such as different accumulations of aquaporins and osmotins. The data set also suggests that RuBisCO isoforms and aquaporins can be used as markers of tolerance/susceptibility to drought stress and be used to select tomato cultivars within breeding programs.     

Binding Properties of RNA Quadruplex of SARS-CoV-2 to Berberine Compared to Telomeric DNA Quadruplex

Previous studies suggest that berberine, an isoquinoline alkaloid, has antiviral potential and is a possible therapeutic candidate against SARS-CoV-2. The molecular underpinnings of its action are still unknown. Potential targets include quadruplexes (G4Q) in the viral genome as they play a key role in modulating the biological activity of viruses. While several DNA-G4Q structures and their binding properties have been elucidated, RNA-G4Qs such as RG-1 of the N-gene of SARS-CoV-2 are less explored. Using biophysical techniques, the berberine binding thermodynamics and the associated conformational and hydration changes of RG-1 could be characterized and compared with human telomeric DNA-G4Q 22AG. Berberine can interact with both quadruplexes. Substantial changes were observed in the interaction of berberine with 22AG and RG-1, which adopt different topologies that can also change upon ligand binding. The strength of interaction and the thermodynamic signatures were found to dependent not only on the initial conformation of the quadruplex, but also on the type of salt present in solution. Since berberine has shown promise as a G-quadruplex stabilizer that can modulate viral gene expression, this study may also contribute to the development of optimized ligands that can discriminate between binding to DNA and RNA G-quadruplexes.     

Order vs. Disorder: Cholesterol and Omega-3 Phospholipids Determine Biomembrane Organization

Lipid structural diversity strongly affects biomembrane chemico-physical and structural properties in addition to membrane-associated events. At high concentrations, cholesterol increases membrane order and rigidity, while polyunsaturated lipids are reported to increase disorder and flexibility. How these different tendencies balance in composite bilayers is still controversial. In this study, electron paramagnetic resonance spectroscopy, small angle neutron scattering, and neutron reflectivity were used to investigate the structural properties of cholesterol-containing lipid bilayers in the fluid state with increasing amounts of polyunsaturated omega-3 lipids. Either the hybrid 1-stearoyl-2-docosahexaenoyl-sn-glycero-3-phosphocholine or the symmetric 1,2-docosahexaenoyl-sn-glycero-3-phosphocholine were added to the mixture of the naturally abundant 1-palmitoyl-2-oleyl-sn-glycero-3-phosphocholine and cholesterol. Our results indicate that the hybrid and the symmetric omega-3 phospholipids affect the microscopic organization of lipid bilayers differently. Cholesterol does not segregate from polyunsaturated phospholipids and, through interactions with them, is able to suppress the formation of non-lamellar structures induced by the symmetric polyunsaturated lipid. However, this order/disorder balance leads to a bilayer whose structural organization cannot be ascribed to either a liquid ordered or to a canonical liquid disordered phase, in that it displays a very loose packing of the intermediate segments of lipid chains.     

Environmental Stress and Plants

Land plants are constantly subjected to multiple unfavorable or even adverse environmental conditions. Among them, abiotic stresses (such as salt, drought, heat, cold, heavy metals, ozone, UV radiation, and nutrient deficiencies) have detrimental effects on plant growth and productivity and are increasingly important considering the direct or indirect effects of climate change. Plants respond in many ways to abiotic stresses, from gene expression to physiology, from plant architecture to primary, and secondary metabolism. These complex changes allow plants to tolerate and/or adapt to adverse conditions. The complexity of plant response can be further influenced by the duration and intensity of stress, the plant genotype, the combination of different stresses, the exposed tissue and cell type, and the developmental stage at which plants perceive the stress. It is therefore important to understand more about how plants perceive stress conditions and how they respond and adapt (both in natural and anthropogenic environments). These concepts were the basis of the Special Issue that International Journal of Molecular Sciences expressly addressed to the relationship between environmental stresses and plants and that resulted in the publication of 5 reviews and 38 original research articles. The large participation of several authors and the good number of contributions testifies to the considerable interest that the topic currently receives in the plant science community, especially in the light of the foreseeable climate changes. Here, we briefly summarize the contributions included in the Special Issue, both original articles categorized by stress type and reviews that discuss more comprehensive responses to various stresses.