The labeled maximum matching problem

Given a graph G where a label is associated with each edge, we address the problem of looking for a maximum matching of G using the minimum number of different labels, namely the labeled maximum matching problem. It is a relatively new problem whose application is related to the timetabling problem. We prove it is NP-complete and present four different mathematical formulations. Moreover, we propose an exact algorithm based on a branch-and-bound approach to solve it. We evaluate the performance of our algorithm on a wide set of instances and compare our computational times with the ones required by CPLEX to solve the proposed mathematical formulations. Test results show the effectiveness of our procedure, that hugely outperforms the solver.     

Cubic B样条旋转曲面的自由绘制技术

随着基于样条曲线的模型逐渐成为CAGD的主要研究对象,进一步带动了高度自由曲面建模技术的发展.本文描述一个新颖、直观的旋转曲面绘制技术,它支持三次B样条的自由输入作为轮廓线,并通过提取的样点矢量以及最小方差逼近方法形成旋转轴,利用轴上测量点的切线方向确定各个圆平面,从而建立了平面上旋转坐标矩阵,最终插值空间球面样点生成双三次B样条曲面.实验结果有效地验证了此技术的高效性.     

A data fusion and spatial data analysis approach for the estimation of wheat grain nitrogen uptake from satellite data

The selection of the optimal band combination for the estimation of specific crop variables is a key aspect in order to obtain reliable estimation of in-field variability from multi- and hyperspectral remote-sensing data. The selection of the bands is strongly influenced by the phenological stage of the crop at the acquisition time. In this work, the influence of the growing stage on the combination of spectral bands related to grain nitrogen (N) uptake in wheat was evaluated using multispectral (Satellite Pour l’Observation de la Terre – SPOT) and hyperspectral (Compact High Resolution Imaging Spectrometer – CHRIS-PROBA) satellite images at different growth stages over two wheat growth seasons in central Italy. In order to identify the more appropriate covariates (spectral bands) for each phenological stage, stepwise regression with backward selection was combined with stepwise variance inflation factors (VIFs) analysis and linear mixed effect model (LMEM). The results obtained in this study suggest that the spectral region most related to N uptake varies over the growing season of the wheat crop. For SPOT data, near-infrared (NIR) region was selected at all the phenological stages in both growing seasons, except for the latest stage, with low chlorophyll content due to the onset of senescence, in which the red band was selected. At stem elongation, the shortwave infrared (SWIR) band of SPOT data was also selected. At this stage, the best N estimation accuracy was obtained using an LMEM (root mean square error, RMSE = 0.012 t ha^?1). The inclusion of a spatial component in the estimation model by means of LMEMs provided a more accurate estimation than ordinary least square (OLS) models at all growth stages. The test carried out with CHRIS-PROBA data at the fourth stage confirmed the importance of NIR and in particular of the red-edge region for N uptake prediction. A novel methodology is proposed, which involves two crucial aspects in the context of the use of remote-sensing data in precision agriculture: i) the standardization of the spatial resolution for in-field and satellite data by a geostatistical data technique (data fusion); and ii) the selection of the most appropriate spectral bands for each phenological stage, taking into account both correlation with the target variable and collinearity.     

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.     

Finite element shakedown analysis of two‐dimensional structures

In the present paper, the formulation proposed by Casciaro and Garcea (Comput. Meth. Appl. Mech. Eng., 2002; 191 :5761–5792) and applied to the shakedown analysis of plane frames, is extended to the analysis of two‐dimensional flat structures in both the cases of plane‐stress and plane‐strain. The discrete formulation is obtained using a mixed finite element in which both stress and displacement fields are interpolated. The material is assumed to be elasto‐plastic and a linearization of the elastic domain is performed. The result is a versatile iterative scheme well suited to implementation in general purpose FEM codes. An extensive series of numerical tests is presented showing the reliability of the proposed formulation. Copyright © 2005 John Wiley & Sons, Ltd.     

Ecological Neural Networks for Object Recognition and Generalization

Generalization is a critical capacity for organisms. Modeling the behavior of organisms with neural networks, some type of generalizations appear to be accessible to neural networks but other types do not. In this paper we present two simulations. In the first simulation we show that while neural networks can recognize where an object is located in the retina even if they have never experienced that object in that position ('where' generalization subtask), they have difficulty in recognizing the identity of a familiar object in a new position ('what' generalization subtask). In the second simulation we explore the hypothesis that organisms find another solution to the problem of recognizing objects in different positions on their retina: they move their eyes so that objects are always seen in the same position in the retina. This strategy emerges spontaneously in ecological neural networks that are allowed to move their 'eye' in order to bring different portions of the visible world in the central portion of their retina.     

Association of LTA and SOD Gene Polymorphisms with Cerebral White Matter Hyperintensities in Migraine Patients

White matter hyperintensities (WMHs) in migraine could be related to inflammatory and antioxidant events. The aim of this study is to verify whether migraine patients with WMHs carry a genetic pro-inflammatory/pro-oxidative status. To test this hypothesis, we analyzed lymphotoxin alpha (LTA; rs2071590T and rs2844482G) and superoxide dismutase 1 (SOD1; rs2234694C) and 2 (SOD2; rs4880T) gene polymorphisms (SNPs) in 370 consecutive patients affected by episodic (EM; n = 251) and chronic (CM; n = 119) migraine and in unrelated healthy controls (n = 100). Brain magnetic resonance was available in 183/370 patients. The results obtained show that genotypes and allele frequencies for all tested SNPs did not differ between patients and controls. No association was found between single SNPs or haplotypes and sex, migraine type, cardiovascular risk factors or disorders. Conversely, the LTA rs2071590T (OR = 2.2) and the SOD1 rs2234694C (OR = 4.9) alleles were both associated with WMHs. A four-loci haplotype (TGCT haplotype: rs2071590T/rs2844482G/rs2234694C/rs4880T) was significantly more frequent in migraineurs with WMHs (7 of 38) compared to those without WMHs (4 of 134; OR = 8.7). We may, therefore, conclude by suggesting that that an imbalance between pro-inflammatory/pro-oxidative and antioxidant events in genetically predisposed individuals may influence the development of WMHs.     

State-of-the-Art on Wound Vitality Evaluation: A Systematic Review

The vitality demonstration refers to determining if an injury has been caused ante- or post-mortem, while wound age means to evaluate how long a subject has survived after the infliction of an injury. Histology alone is not enough to prove the vitality of a lesion. Recently, immunohistochemistry, biochemistry, and molecular biology have been introduced in the field of lesions vitality and age demonstration. The study was conducted according to the preferred reporting items for systematic review (PRISMA) protocol. The search terms were “wound”, “lesion”, “vitality”, “evaluation”, “immunohistochemistry”, “proteins”, “electrolytes”, “mRNAs”, and “miRNAs” in the title, abstract, and keywords. This evaluation left 137 scientific papers. This review aimed to collect all the knowledge on vital wound demonstration and provide a temporal distribution of the methods currently available, in order to determine the age of lesions, thus helping forensic pathologists in finding a way through the tangled jungle of wound vitality evaluation.