Near optimal solutions to least-squares problems with stochastic uncertainty

In this paper, we consider least-squares (LS) problems where the regression data is affected by parametric stochastic uncertainty. In this setting, we study the problem of minimizing the expected value with respect to the uncertainty of the LS residual. For general nonlinear dependence of the data on the uncertain parameters, determining an exact solution to this problem is known to be computationally prohibitive. Here, we follow a probabilistic approach, and determine a probable near optimal solution by minimizing the empirical mean of the residual. Finite sample convergence of the proposed method is assessed using statistical learning methods. In particular, we prove that if one constructs the empirical approximation of the mean using a finite number N of samples, then the minimizer of this empirical approximation is, with high probability, an ε-suboptimal solution for the original problem. Moreover, this approximate solution can be efficiently determined numerically by a standard recursive algorithm. Comparisons with gradient algorithms for stochastic optimization are also discussed in the paper and several numerical examples illustrate the proposed methodology.     

A distributed simplex algorithm for degenerate linear programs and multi-agent assignments

In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous peer-to-peer networks with distributed information structures. We propose a distributed version of the well-known simplex algorithm for general degenerate linear programs. A network of agents, running our algorithm, will agree on a common optimal solution, even if the optimal solution is not unique, or will determine infeasibility or unboundedness of the problem. We establish how the multi-agent assignment problem can be efficiently solved by means of our distributed simplex algorithm. We provide simulations supporting the conjecture that the completion time scales linearly with the diameter of the communication graph.     

Enhancing augmented reality with cognitive and knowledge perspectives: a case study in museum exhibitions

ABSTRACT

In this paper, we present our results related to the definition of a methodology that combines augmented reality (AR) with semantic techniques for the creation of digital stories associated with museum exhibitions. In contrast to traditional AR approaches, we augment real-world elements by supplementing contents of a museum exhibition with additional inputs that provide new and different meanings. In this way we augment a cultural resource with respect to both its presentation and meaning. The methodology is framed in the cultural re-mediation theory and is grounded on a set of ontologies aimed at modelling a cultural resource and correlating it with external multimedia objects and resources. To provide an easy tool for the creation of museum narratives, the methodology makes use of a set of recognised practices widely adopted by museum curators that have been formalised through inference rules. The defined methodology has been experimented in a scenario related to Flemish paintings to validate the augmentation of cultural objects with two different approaches, the first basing on similarities and the second on dissimilarities.     

Epigenetic and Genetic Factors Related to Curve Progression in Adolescent Idiopathic Scoliosis: A Systematic Scoping Review of the Current Literature

Adolescent idiopathic scoliosis (AIS) is a progressive deformity of the spine. Scoliotic curves progress until skeletal maturity leading, in rare cases, to a severe deformity. While the Cobb angle is a straightforward tool in initial curve magnitude measurement, assessing the risk of curve progression at the time of diagnosis may be more challenging. Epigenetic and genetic markers are potential prognostic tools to predict curve progression. The aim of this study is to review the available literature regarding the epigenetic and genetic factors associated with the risk of AIS curve progression. This review was carried out in accordance with Preferential Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The search was carried out in January 2022. Only peer-reviewed articles were considered for inclusion. Forty studies were included; fifteen genes were reported as having SNPs with significant association with progressive AIS, but none showed sufficient power to sustain clinical applications. In contrast, nine studies reporting epigenetic modifications showed promising results in terms of reliable markers. Prognostic testing for AIS has the potential to significantly modify disease management. Most recent evidence suggests epigenetics as a more promising field for the identification of factors associated with AIS progression, offering a rationale for further investigation in this field.     

Engineering the Thermoelectrical Properties of PEDOT:PSS by Alkali Metal Ion Effect

Engineering the electrical properties of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS)holds great potential for various applications such a...     

Adipose Tissue Dysfunction and Obesity-Related Male Hypogonadism

Obesity is a chronic illness associated with several metabolic derangements and comorbidities (i.e., insulin resistance, leptin resistance, diabetes, etc.) and often leads to impaired testicular function and male subfertility. Several mechanisms may indeed negatively affect the hypothalamic–pituitary–gonadal health, such as higher testosterone conversion to estradiol by aromatase activity in the adipose tissue, increased ROS production, and the release of several endocrine molecules affecting the hypothalamus–pituitary–testis axis by both direct and indirect mechanisms. In addition, androgen deficiency could further accelerate adipose tissue expansion and therefore exacerbate obesity, which in turn enhances hypogonadism, thus inducing a vicious cycle. Based on these considerations, we propose an overview on the relationship of adipose tissue dysfunction and male hypogonadism, highlighting the main biological pathways involved and the current therapeutic options to counteract this condition.     

Training,research, and technical assistance to improve the water resources management in Southern Italy — The experience of CSEI Catania

Water resources management may be improved through the activities of organizations devoted to practice-oriented research, continuing education, and technical assistance. The experience carried out in southern Italy by CSEI Catania during 13 years of activity is presented. Two main activities are discussed: the research and training program on regional pollution control plans and the development of a water data bank.     

Morphological and Biological Evaluations of Human Periodontal Ligament Fibroblasts in Contact with Different Bovine Bone Grafts Treated with Low-Temperature Deproteinisation Protocol

Several types of deproteinised bovine bone mineral (DBBM) are available on the market, and each one is obtained with a thermic and chemical process that can differ, achieving different results. Currently, several protocols using low temperature are suggested to reduce the possible particle crystallisation during the production process. This study aimed to evaluate the biomorphological reaction of periodontal fibroblast cultures in contact with different DBBM particles treated with a low-temperature protocol (Thermagen^®) and without exposure to sodium hydroxide (NaOH). Morphological evaluation was performed using light, confocal laser, and scanning electron microscopy, and the biological reaction in terms of proliferation was performed using an XTT proliferation assay at 24 h (T1), 72 h (T2), and 7 days (T3). The morphological analysis highlighted how the presence of the materials stimulated a change in the morphology of the cells into a polygonal shape, surface reactions with the thickening of the membrane, and expression of actin. In particular, the morphological changes were appreciable from T1, with a progressive increase in the considered morphological characteristics at T2 and T3 follow-ups. The proliferation assay showed a statistical significance between the different experimental materials and the negative control in T2 and T3 follow-ups. The post hoc analysis did not reveal any differences between the materials. In conclusion, the grafts obtained with the low-temperature extractions protocol and not exposed to NaOH solution showed positive morphological reactions with no differences in the sizes of particles.     

Challenges in Metabolomics-Based Tests,Biomarkers Revealed by Metabolomic Analysis,and the Promise of the Application of Metabolomics in Precision Medicine

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene–environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.     

Probabilistic topic models for sequence data

Probabilistic topic models are widely used in different contexts to uncover the hidden structure in large text corpora. One of the main (and perhaps strong) assumption of these models is that generative process follows a bag-of-words assumption, i.e. each token is independent from the previous one. We extend the popular Latent Dirichlet Allocation model by exploiting three different conditional Markovian assumptions: (i) the token generation depends on the current topic and on the previous token; (ii) the topic associated with each observation depends on topic associated with the previous one; (iii) the token generation depends on the current and previous topic. For each of these modeling assumptions we present a Gibbs Sampling procedure for parameter estimation. Experimental evaluation over real-word data shows the performance advantages, in terms of recall and precision, of the sequence-modeling approaches.