Antisymmetric tensor gauge theory

We analyze to all perturbative orders the properties of two possible quantum extensions of classically on-shell equivalent antisymmetric tensor gauge models in four dimensions. The first case, related to the soft breaking of a topological theory wants a gauge field of canonical dimension one. The other possibility, which assigns canonical dimension two to the gauge field, leads to the $\sigma$ model interpretation of the theory. In both instances we find that the models are anomaly free.Comment: 28 ,Latex,GEF-TH 10/9

Effects of political-economic integration and trade liberalization on exports of Italian Quality Wines Produced in Determined Regions (QWPDR)

The aim of this work is to explain the magnitude of the trade flows for high quality wine from Italy to its main importing countries. This objective has been reached by establishing an appropriate econometric model derived from an extended form of the “Gravity Model”. This model has been broadly applied to the analysis of international trade because it provides robust estimates. The results obtained and the model itself are useful in forecasting potential trends in the exportation of high quality Italian wines. In particular, these estimates give a quantitative evaluation of the export gains that could result from the enlargement of the EU and from an increasing liberalization in international trade. Moreover, it is possible to identify the growing markets where Italian ventures could exploit certain promotional and communication strategies.Italy, Exports, QWPDR, Integration, Gravity Model

New challenges and opportunities for Italian exports of table wines and high quality wines

Competition in international wine market has recently become more intense because of several factors and, in particular, the progressive reduction in world-wide consumption, the addition of new producing countries such as Australia, Chile, the USA and South Africa (the so called New World wine producers) and the increasing trade liberalization. In order to achieve a competitive advantage in the international marketplace, it is very important to identify which markets are characterized by bigger attractiveness. In particular, the ability of a producer, a region or a country to provide effective communication and promotion actions towards more profitable local markets is strategic in international trade. Italy, one of the first wine producing country in the world, exports its wines to almost all countries of the five continents. However, the five greater importing countries account for 70 percent of Italy’s total wine exports (the USA, Germany, the United Kingdom, Switzerland, and Canada) and so Italy shows only a moderate market diversification. In this paper, an econometric model able to explain the size of wine export flows from Italy to its main importing countries was elaborated and estimated. This model provides useful information that can help to identify the main growing markets where all participants in the wine supply-chain, such as private wineries, joint-ventures, regional and national agencies, and producers’ associations, can unite to concentrate product communication and promotional efforts. The model is an extended version of the “gravity model” that many economists believe a very powerful tool for international trade analysis. In fact, at the empirical level, the gravity model gives very robust estimates and provides a good fit to the observed data. The basic concept of the gravity model for trade analysis borrows the gravity equation from physics: the volume of trade between two countries is proportional to their economic “mass” and inversely proportional to their respective distance. In this work, the investigation about the features of Italian wine export flows is conducted through the estimation of two different econometric models; the first one is related to QWPDR and second one is related to table wine category. Both models derive from an extended version of the basic gravity model where dummies for groups of countries have been added. An important result is that Italy should increase the production of high quality wine because there are favorable conditions in place which would increase exportation. At the same time, Italy should decrease the production of table wine because its international demand is declining. Moreover, estimation results show that both QWPDR and table wine exportations are income elastic. Hence, if Italian wine producers intend to expand their exportations, it is natural to look at those countries where income growth is high but also constant and solid. It is interesting to highlight that, among countries with the highest income growth rates, there are three very big countries, China, Russia and India, where expansion possibilities for Italian wine exports are very attractive. Currently, these countries import less than 1% of total exports of Italian wine. At the same time, it is important to highlight that the main countries importing Italian wine (the United States, Germany, the United Kingdom, Switzerland, Canada, Japan and almost all western European countries) show a moderate but stable income growth and therefore it would be strategic to defend and consolidate Italian market shares against any possible aggressions by the new wine producing countries. The recent enlargement of the EU could represent a great opportunity for the exporters of Italian wine. In particular, it is interesting to note that all new EU members and, in particular, the Baltic Republics (Latvia, Estonia, Lithuania) show high income growth rates. In addition, as widely known, there are no customs barriers within the European Union but instead there is a common external tariff applied to imports from non-EU countries. Therefore, these countries represent very interesting, and as yet untapped, markets even if, in the next years, there are real possibilities to expand mainly table wine exports because the income, although rapidly increasing, remains still moderate.Italian Wine; Trade; Gravity model; Exports

Agritourism flows to Italy: an analysis of determinants using the gravity model approach

Tourism represents one of the most important income sources for Italy. In recent years, apart from “traditional” destinations, tourism supply is widely changing in order to satisfy the customers “love for variety” and valorise marginal resources, then new formulas are emerging (e.g. agritourism). This work aims to elaborate and estimate an econometric model able to adequately explain the size of agritourists flows to Italy from main partner countries using the gravity model approach that has been broadly applied to the analysis of international flows. In this work, the “basic” model has been enlarged and improved with the introduction of other explicative variables. The results has allowed to confirm empirical validity of the gravity model in studying international flows of any nature. Furthermore, the estimated econometric model represents a useful analytical instrument to describe, and, eventually, predict demand of foreign visitors for agritourist vacations in Italy.Gravity Model, Agritourism, Rural tourism, Tourism flows, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

Synthesis of Poly(acrylic acid) Nanogels and Application in Loading and Release of an Oligothiophene Fluorophore and Its Bovine Serum Albumin Conjugate

Nanometer-sized poly(acrylic acid) (PAA) hydrogels were synthesized by emulsion polymerization of methyl acrylate and subsequent acid hydrolysis, and their pH-dependent swelling behaviour was studied by dynamic light scattering. To determine the suitability of PAA nanogels as pH-sensitive carriers for biomedical applications, loading and release of an oligothiophene fluorophore and its albumin conjugate onto the PAA nanogels were investigated as a function of pH by absorption and photoluminescence measurements. it was observed that loading and release processes of both the oligothiophene and its conjugate could be controlled by changing pH of their solutions

A dynamic Bayesian network model for predicting organ failure associations without predefining outcomes

Critical care medicine has been a field for Bayesian networks (BNs) application for investigating relationships among failing organs. Criticisms have been raised on using mortality as the only outcome to determine the treatment efficacy. We aimed to develop a dynamic BN model for detecting interrelationships among failing organs and their progression, not predefining outcomes and omitting hierarchization of organ interactions. We collected data from 850 critically ill patients from the national database used in many intensive care units. We considered as nodes the organ failure assessed by a score as recorded daily. We tested several possible DBNs and used the best bootstrapping results for calculating the strength of arcs and directions. The network structure was learned using a hill climbing method. The parameters of the local distributions were fitted with a maximum of the likelihood algorithm. The network that best satisfied the accuracy requirements included 15 nodes, corresponding to 5 variables measured at three times: ICU admission, second and seventh day of ICU stay. From our findings some organ associations had probabilities higher than 50% to arise at ICU admittance or in the following days persisting over time. Our study provided a network model predicting organ failure associations and their evolution over time. This approach has the potential advantage of detecting and comparing the effects of treatments on organ function

Smart surfaces for pH controlled cell staining

In this work, novel smart surfaces for in situ cell staining were realized by covalent attachment of pH-responsive microgels on platforms dedicated to microfluidics for lab-on-chip. The poly(methacrylic acid) microgels were firstly synthesized in solution and then covalently immobilized on a glass surface. As they preserve their pH-sensitive nature after the covalent immobilization, microgels were loaded with an oligothiophene-conjugated anti-human CD4 monoclonal antibody, and finally incubated with a Jurkat T-cell suspension. The physiological pH of the extracellular environment induced the pH-triggered release of the labeled anti-CD4 antibodies and the selective staining of the CD4-positive subpopulations within the Jurkat cell suspension. The realization of this type of smart surface for the encapsulation of specific monoclonal antibodies and their release in an on-demand way should have an enormous potential in developing fully integrated platforms for cell analysis

Clinical efficacy of nab-paclitaxel in patients with metastatic pancreatic cancer

Purpose: Pancreatic carcinoma is the neoplasia with the major mortality, and main standard treatments in this cancer increase survival but do not lead to complete recovery of the patient. The aim of this study was to evaluate the efficacy of Abraxane® (nab-paclitaxel) in Italian patients with metastatic pancreatic cancer (MPC). Patients and methods: We conducted a retrospective analysis of 80 patients. Overall survival (OS) was the primary end point for evaluating the efficacy of nab-paclitaxel in combination with gemcitabine treatment, while carbohydrate antigen 19-9 (CA 19-9) reduction, safety, progression-free survival (PFS), overall response rate and reduction in pain were secondary end points. Results: The median OS was 8 months, and the median PFS was 5 months. A considerable difference in CA 19-9 before and after treatment was observed. Descriptive and correlation analyses were done to examine the relationship between CA 19-9 response and OS. Linear regression analysis between OS and CA 19-9 response revealed that CA 19-9 is an important predictor of OS, showing a positive correlation. Conclusion: Nab-paclitaxel is a well-tolerated and effective treatment for patients affected by MPC. The drug showed an improved tolerability profile, significant pain relief and an increase in survival rate

Surface-based integration approach for fNIRS-fMRI reliability assessment

Introduction: Studies integrating functional near-infrared spectroscopy (fNIRS) with functional MRI (fMRI) employ heterogeneous methods in defining common regions of interest in which similarities are assessed. Therefore, spatial agreement and temporal correlation may not be reproducible across studies. In the present work, we address this issue by proposing a novel method for integration and analysis of fNIRS and fMRI over the cortical surface. Materials and methods: Eighteen healthy volunteers (age mean±SD 30.55 ± 4.7, 7 males) performed a motor task during non-simultaneous fMRI and fNIRS acquisitions. First, fNIRS and fMRI data were integrated by projecting subject- and group-level source maps over the cortical surface mesh to define anatomically constrained functional ROIs (acfROI). Next, spatial agreement and temporal correlation were quantified as Dice Coefficient (DC) and Pearson's correlation coefficient between fNIRS-fMRI in the acfROIs. Results: Subject-level results revealed moderate to substantial spatial agreement (DC range 0.43 - 0.64), confirmed at the group-level only for blood oxygenation level-dependent (BOLD) signal vs. HbO2 (0.44 - 0.69), while lack of agreement was found for BOLD vs. HbR in some instances (0.05 - 0.49). Subject-level temporal correlation was moderate to strong (0.79 - 0.85 for BOLD vs. HbO2 and -0.62 to -0.72 for BOLD vs. HbR), while an overall strong correlation was found for group-level results (0.95 - 0.98 for BOLD vs. HbO2 and -0.91 to -0.94 for BOLD vs. HbR). Conclusion: The proposed method directly compares fNIRS and fMRI by projecting individual source maps to the cortical surface. Our results indicate spatial and temporal correspondence between fNIRS and fMRI, and promotes the use of fNIRS when more ecological acquision settings are required, such as longitudinal monitoring of brain activity before and after rehabilitation