Hermitian matrices of three parameters: Perturbing coalescing eigenvalues and a numerical method

In this work we consider Hermitian matrix-valued functions of 3 (real) parameters, and are interested in generic coalescing points of eigenvalues, conical intersections. Unlike our previous works [L. Dieci, A. Papini and A. Pugliese, Approximating coalescing points for eigenvalues of Hermitian matrices of three parameters, SIAM J. Matrix Anal. Appl., 2013] and [L. Dieci and A. Pugliese, Hermitian matrices depending on three parameters: Coalescing eigenvalues, Linear Algebra Appl., 2012], where we worked directly with the Hermitian problem and monitored variation of the geometric phase to detect conical intersections inside a sphere-like region, here we consider the following construction: (i) Associate to the given problem a real symmetric problem, twice the size, all of whose eigenvalues are now (at least) double, (ii) perturb this enlarged problem so that, generically, each pair of consecutive eigenvalues coalesce along curves, and only there, (iii) analyze the structure of these curves, and show that there is a small curve, nearly planar, enclosing the original conical intersection point. We will rigorously justify all of the above steps. Furthermore, we propose and implement an algorithm following the above approach, and illustrate its performance in locating conical intersections

Blind-date conversation joining

In service-oriented applications, service providers and their clients can engage in conversations to exchange the data required to achieve their business goals. In this paper, we focus on a particular kind of conversation joining, which we call blind-date, where a client may join a conversation among multiple parties in an asynchronous and completely transparent way. Indeed, the client can join the conversation without knowing any information about it in advance. More specifically, we show that the correlation mechanism provided by orchestration languages enables the blind-date conversation joining strategy. To demonstrate the feasibility of the approach, we provide an implementation of this strategy by using the standard orchestration language WS-BPEL. Moreover, to clarify the run-time effects of the blind-date joining, we formally describe its behaviour by resorting to COWS, a process calculus specifically designed for modelling service-oriented applications. We illustrate our approach by means of a simple example and a more realistic case study from the online games domain

Decompositions and coalescing eigenvalues of symmetric definite pencils depending on parameters

In this work, we consider symmetric positive definite pencils depending on two parameters. That is, we are concerned with the generalized eigenvalue problem $A(x)-\lambda B(x)$, where $A$ and $B$ are symmetric matrix valued functions in ${\mathbb R}^{n\times n}$, smoothly depending on parameters $x\in \Omega\subset {\mathbb R}^2$; further, $B$ is also positive definite. In general, the eigenvalues of this multiparameter problem will not be smooth, the lack of smoothness resulting from eigenvalues being equal at some parameter values (conical intersections). We first give general theoretical results on the smoothness of eigenvalues and eigenvectors for the present generalized eigenvalue problem, and hence for the corresponding projections, and then perform a numerical study of the statistical properties of coalescing eigenvalues for pencils where $A$ and $B$ are either full or banded, for several bandwidths. Our numerical study will be performed with respect to a random matrix ensemble which respects the underlying engineering problems motivating our study.Comment: 34 pages, 4 figure

Correlates of calcaneal quantitative ultrasound parameters in patients with diabetes: the study on the assessment of determinants of muscle and bone strength abnormalities in diabetes

OBJECTIVE: Quantitative ultrasound (QUS) provides an estimate of bone mineral density (BMD) and also evaluates bone quality, which has been related to increased fracture risk in people with diabetes. This study aimed at assessing the correlates of calcaneal QUS parameters in diabetic subjects encompassing various degrees of micro and macrovascular complications and a wide-range of peripheral nerve function. METHODS: Four hundred consecutive diabetic patients were examined by QUS to obtain values of broadband ultrasound attenuation (BUA), the speed of sound (SOS), quantitative ultrasound index (QUI), and BMD. RESULTS: Among surrogate measures of complications, sensory and motor nerve amplitude and heart rate response to cough test and standing correlated with QUS parameters at univariate analysis, together with age, body mass index (BMI), waist circumference, lipid profile, and renal function. Multivariate analysis revealed that BUA, SOS, QUI, and BMD were independently associated with age, male gender, hemoglobin A1c, BMI (or fat, but not fat-free mass), and somatic and autonomic nerve function parameters. CONCLUSIONS: These data indicate that peripheral nerve dysfunction is associated with worse QUS parameters, possibly contributing to increased fracture risk in diabetes. The positive relation of QUS measures with adiposity needs further investigation. This trial is registered with ClinicalTrials.gov (NCT01600924)

Measuring Social Mood on Economy during Covid times: effects of retraining Supervised Deep Neural Networks

[EN] Supervised Machine learning approaches are popular techniques used for sentiment analysis tasks. However, such techniques have strong limitations due to their sensitivity to the quantity and quality of the training datasets and may fail when training data are biased or insufficient. In the present study we address the impact of Covid on a deep learning classifier based on long-short term memory neural network (LSTM).  This classifier is used to compute a daily sentiment index on Italian tweets with economic content, for the first five months of 2020 (more than 11 million of tweets are classified). We show how retraining the model with a set of annotated tweets containing reference to Covid increase the accuracy of the classifier. The accuracy is measured by analyzing the dynamics of the index. We will show that during pandemic the retrained index decreases coherently with most Italian economic indicators.In addition, we analyze how the training and tuning procedures (one-step, two-steps with fine-tuning) affect the daily dynamics of the index.IstatCatanese, E.; Bruno, M.; Stefanelli, L.; Pugliese, F. (2023). Measuring Social Mood on Economy during Covid times: effects of retraining Supervised Deep Neural Networks. Editorial Universitat Politècnica de València. 139-147. https://doi.org/10.4995/CARMA2023.2023.1647413914

Diabetic kidney disease. new clinical and therapeutic issues. Joint position statement of the Italian Diabetes Society and the Italian Society of Nephrology on "the natural history of diabetic kidney disease and treatment of hyperglycemia in patients with type 2 diabetes and impaired renal function"

Recent epidemiological studies have disclosed heterogeneity in diabetic kidney disease (DKD). In addition to the classical albuminuric phenotype, two new phenotypes have emerged, i.e., “nonalbuminuric renal impairment” and “progressive renal decline”, suggesting that DKD progression toward end-stage kidney disease in diabetic patients may occur through two distinct pathways heralded by a progressive increase in albuminuria and decline in renal function independent of albuminuria, respectively. Besides the natural history of DKD, also the management of hyperglycemia in patients with type 2 diabetes and reduced renal function has profoundly changed in the last two decades. New anti-hyperglycemic drugs have become available for treatment of these individuals and the lowest estimated glomerular filtration rate safety thresholds for some of the old agents have been reconsidered. This joint document of the Italian Diabetes Society (SID) and the Italian Society of Nephrology (SIN) reviews the natural history of DKD in the light of the recent epidemiological literature and provides updated recommendations on anti-hyperglycemic treatment with non-insulin agents in DKD patients

Uncertainty Analysis for the Classification of Multispectral Satellite Images Using SVMs and SOMs

Abstract: Classification of multispectral remotely sensed data with textural features is investigated with a special focus on uncertainty analysis in the produced land-cover maps. Much effort has already been directed into the research of satisfactory accuracy-assessment techniques in image classification, but a common approach is not yet universally adopted. We look at the relationship between hard accuracy and the uncertainty on the produced answers, introducing two measures based on maximum probability and a quadratic entropy. Their impact differs depending on the type of classifier. In this paper, we deal with two different classification strategies, based on support vector machines (SVMs) and Kohonen's self-organizingmaps (SOMs), both suitably modified to give soft answers. Once the multiclass probability answer vector is available for each pixel in the image, we studied the behavior of the overall classification accuracy as a function of the uncertainty associated with each vector, given a hard-labeled test set. The experimental results show that the SVM with one-versus-one architecture and linear kernel clearly outperforms the other supervised approaches in terms of overall accuracy. On the other hand, our analysis reveals that the proposed SOM-based classifier, despite its unsupervised learning procedure, is able to provide soft answers which are the best candidates for a fusion with supervised results

iga anticardiolipin in patients with gastroenteric tumor

Recently the presence of antiphospholipid antibodies in patients with cancer has been demonstrated, suggesting an involvement of autoimmune response in neoplastic conditions. The presence of antiphospholipid antibodies in tumor disease is highly correlated with the risk of developing thrombotic complications, which represents a significant cause of morbidity and mortality in cancer patients. Interestingly, it has been highlighted that high levels of IgM and IgG anticardiolipin antibodies are more often produced in patients with gastroenteric tumor than in patients with either ovarian or breast tumor. Thus far, there are no data looking into the role or measurements of IgA in patients with solid cancer. Our preliminary results, in this study, demonstrate that testing only for IgG and IgM anticardiolipin antibodies may increase the incidence of false positive because 44% who were IgA positive and IgG and IgM negative had high titres of CA19.9 and CEA. We suggest that taking into account the role of IgA could substantially improve the detection of antiphospholipids antibodies in subjects with solid cancer, and this detection may allow us for better prevention and management of thrombotic complications in these patients

Two behavioral tests allow a better correlation between cognitive function and expression of synaptic proteins

The molecular substrate of age-associated cognitive decline (AACD) is still elusive. Evidence indicates that AACD is related to synaptic impairment in hippocampus, but different hippocampal regions play different roles, with the dorsal hippocampus (DH) associated to spatial learning, and the ventral hippocampus (VH) crucial for emotionality. If changes in hippocampal function contributes to AACD, this contribution may be reflected in alterations of synaptic protein levels. A commonly used approach to investigate this issue is western blotting. When this technique is applied to the entire hippocampus and the cognitive impairment is evaluated by a single task, changes in expression of a protein might undergo a "dilution effect", as they may occur only in a given hippocampal region. We show that two behavioral tests yield more accurate results than one test in evaluating the function of the whole rat hippocampus by studying the expression of synaptotagmin 1 (SYT1), a vesicular protein whose expression in aged hippocampus is reportedly inconsistent. Analysis of SYT1 levels in the whole hippocampus of rats selected by the Morris water maze (MWM) test only failed to highlight a difference, whereas analysis of SYT1 levels in the whole hippocampus of rats categorized by both the MWM and the step-through passive avoidance (STPA) tests demonstrated a significant increase of SYT1 level in impaired rats. These findings, besides showing that SYT1 increases in impaired aged rats, suggest that using the whole hippocampus in blotting studies may prevent false negative results only if animals are categorized with tests exploring both DH and VH

Cinta Senese Pig

Cinta Senese is an Italian autochthonous pig breed, one of the local pig breeds investigated in the project TREASURE. The present chapter aims to present history and status of Cinta Senese pig breed, its phenotypic characteristics, geographical location, production system and the quality of its main products. Reproductive performance was estimated by several data: sow age at first parturition, litters/sow/year, piglets alive/litter, weaning weight, stillborn/litter, death rate percentage at weaning, duration of lactation, length of farrowing and sow age at culling. Growth performance was estimated by means of average daily gain in lactation and from birth to slaughter, growing at early, middle, late and overall fattening stage and average daily feed intake in late and overall fattening stage. Carcass traits were evaluated by means of age and weight at slaughtering, hot carcass weight, carcass yield, loin eye area and back fat thickness at the first thoracic vertebra, last rib and above gluteus medius muscle. Meat quality traits of the longissimus muscle were evaluated by means of the following: pH at 45 minutes and 24 hours after slaughtering, instrumental measurements of colour (CIE L*, a*, b*) and intramuscular fat content. Fatty acid composition was evaluated in back fat tissue