In this work we analyze the anaphoric devices employed in topic continuity and topic shift in the semi-spontaneous narrations of three groups of speakers: Italian Natives, Greek Natives and ...near-native second language speakers (L2ers) of Italian with Greek as a first language (L1). According to some recent literature, near-native speakers of a null subject language over-use overt pronouns even when their L1 is also a null subject language. It is still unclear whether this over-use is tied to differences in the languages involved (e.g. Italian and Spanish, Filiaci et al. 2014) and hence might be the result of cross-linguistic influence. Our data reveal that in Italian pro has a more specific function than in Greek in signaling topic continuity. The characteristic of pro in Italian is preserved in the L2ers productions. We also found that L2ers over-use overt pronouns, particularly in topic continuity, despite the similarity of their two languages in this respect. Finally, we single out an additional factor that influences speakers’ choice of anaphoric devices, i.e. the number and kind of active referents, proving evidence that all speakers’ groups employ overt pronouns particularly when there are two active animate referents that differ for gender and/or number, and L2ers significantly more than the other two groups. Our findings thus show that micro-variation in the use of anaphoric devices is attested among null subject languages, while the over-use of overt pronouns by L2ers stems from their difficulty in establishing topicality under higher degrees of cognitive load.
Partial conditional probability assessments are having renewed attention and the merging of several sources of information is one of the more compelling needs associated with them. We focus here on ...the consequent task of correcting inconsistent probabilistic databases.
We propose an efficient method for correcting incoherent (i.e. inconsistent) conditional probability assessments, that has a polynomial space complexity, differently from methods based on probabilistic satisfiability problems (PSAT) which require an exponential amount of memory space.
This method uses Mixed Integer Programming (MIP) procedure to minimize the L1 distance between probability assessments and exploits the presence of the so-called “zero layers”. Through a simple prototypical example, we illustrate the feasibility and the peculiarities of the proposed procedure.
Finally, we show some experimental results obtained through randomly generated incoherent assessments.
A recently proposed procedure for correcting inconsistent (i.e. incoherent) probability assessments is specifically tailored for the statistical matching problem with misclassification component. ...Such procedure is based on
distance minimization encoded in mixed integer programming (MIP) problems and it results particularly apt to deal with assessments stemming from different sources of information. The statistical matching problem is one of those cases. The statistical matching problem has been recently studied also inside a misclassification setting. To proceed with a correction in such a framework, if marginal assessments on the conditioning event are wanted to remain fixed, the only possible solutions are the closest Fréchet-Hoeffding bounds for the misclassification probabilities. On the contrary, if also the marginal probabilities are allowed to be modified, the
-based procedure can be applied by a straightforward translation in an MIP problem. Such procedure is applied to a healthcare expenditures and health conditions data example.
Surgical site infections (SSIs) are the most common healthcare-associated infections. The appropriate use of Surgical Antibiotic Prophylaxis (SAP) is a key component to reduce SSIs, while its ...inappropriate application is a major cause of some emerging infections and selects for antibiotic resistance. We describe an Antimicrobial Stewardship (AMS) intervention on SAP appropriateness. The prospective study was conducted in an Italian hospital, in 12 main surgical units, and was organized in three subsequent phases, as follows. Phase 0: Definition of hospital evidence-based guidelines and a new workflow to optimize the process of ordering, dispensing, administering and documenting the SAP. Phase 1: We analysed 2059 elective surgical cases from January to June 2018 for three SAP parameters of appropriateness: indication, choice and dose. Phase 2: In July 2018, an audit was performed to analyse the results; we reviewed 1781 elective surgical procedures from July to December 2018 looking for the same three SAP appropriateness parameters. The comparative analysis between phases 1 and 2 demonstrated that the correct indication, the correct dose and the overall compliance significantly improved (
-value 0.00128,
-value < 2.2·10
and
-value < 5.6·10
respectively). Our prospective study demonstrates a model of successful antimicrobial stewardship intervention that improves appropriateness on SAP.
In the last two decades, studies of lymphoscintigraphy imaging in lymphatic mapping reported an extreme heterogeneity of skin lymphatic drainage of some skin area, in contrast with the previous ...scientific literature. The aim of this study was to investigate the presence of any correlations between the topographical location of cutaneous melanoma and the topographical location of sentinel lymph nodes. Data from 165 patients undergoing sentinel lymph node biopsy between January 2013 and May 2021 were analyzed, demonstrating that melanomas in the Lumbar region presented a significant more heterogeneous drainage by site than those in the Scapular region (p < 0.01) and that melanomas in the Subscapular region were significantly more heterogeneous by laterality (unilateral vs. bilateral) than those in the Scapular region (p < 0.05). Results of this study supported the evidence of multiple lymphatic drainage as regards the sentinel node biopsy performed in skin melanoma located on the dorsal subscapular region and lumbar region. For this reason, the association of preoperative lymphoscintigraphy with another imaging evaluation is needed in these critical cutaneous areas. Recent technical developments enabling fluorescence lymphography together with indocyanine green have significantly improved the visualization of lymphatic drainage patterns at a microscopic level. In the preoperative phase, any doubt can be resolved by associating the SPET-CT scan to lymphoscintigraphy, while during the intraoperative phase, an additional evaluation with indocyanine green can be performed in doubtful cases. The aim of the duplex lymphatic mapping (pre and/or intraoperative) is an accurate search of sentinel nodes, in order to reduce the rate of false negatives.
We propose to use a recently introduced merging procedure for jointly inconsistent probabilistic assessments to the statistical matching problem. The merging procedure is based on an efficient
L
1 ...distance minimization through mixed-integer linear programming. Significance of the method can be appreciated whenever among quantities (events) there are logical (structural) constraints and there are different sources of information. Statistical matching problem has these features and is characterized by a set of random (discrete) variables that cannot be jointly observed. Separate observations share anyhow some common variable, and this, together with structural constraints, make sometimes inconsistent the estimates of probability occurrences. Even though estimates on statistical matching are mainly conditional probabilities, inconsistencies appear only on events with the same conditioning, hence the correction procedure can be easily reduced to unconditional cases and the aforementioned procedure applied.
Credit scoring analysis is an important activity, especially nowadays after a huge number of defaults has been one of the main causes of the financial crisis. Among the many different tools used to ...model credit risk, the recent development of rough set models has proved effective. The original development of rough set theory has been widely generalized and combined with other approaches to uncertain reasoning, especially probability and fuzzy set theories. Since coherent conditional probability assessments cope well with the problem of unifying these different approaches, a merging of fuzzy rough set theory with this subjectivist approach is proposed. Specifically, expert partial probabilistic evaluations are encompassed inside a gradual decision rule structure, with coherence of the conclusion as a guideline. In line with Bayesian rough set models, credibility degrees of multiple premises are introduced through conditional probability assessments. Nonetheless, discernibility with this method remains too fine. Therefore, the basic partition is coarsened by equivalence classes based on the arity of positively, negatively and neutrally related criteria. A membership function, which grades the likelihood of default, is introduced by a peculiar choice of t-norms and t-conorms. To build and test the model, real data related to a sample of firms are used.
► We combine rough set theory with other uncertain reasoning approaches. ► This thanks to the generality of conditional coherent probability assessments. ► We soundly incorporate expert opinions in a procedure mainly based on data analysis. ► By a gradual coarsening of information we improve standard classification abilities. ► The study is led through a prototypical credit risk analysis example.
Special issue on Reasoning under Partial Knowledge Capotorti, Andrea; Vantaggi, Barbara; Petturiti, Davide
International journal of approximate reasoning,
September 2021, 2021-09-00, Letnik:
136
Journal Article
In this paper we introduce new average operators for merging any number of fuzzy numbers, without any exogenous components. The proposed n-ary operators are based on a specific adaptation of ...Marzullo's algorithm, and depart from the usual fuzzy arithmetic mean according to the degree of agreement or disagreement among the memberships of input fuzzy numbers. Such merging operators are suitable to be applied in any model where the same quantity (usually a parameter) can be measured (estimated) through different fuzzy memberships stemming by different sources of information. The special case of two fuzzy memberships was the focus of our previous contributions that were elicited in order to estimate the fuzzy volatility parameter in an hybrid fuzzy-stochastic model for option pricing. In this paper we generalize the setting to the case of n fuzzy inputs to be merged and also remove exogenous factors from the definition of the operators. In order to have an application at hand we consider the same example treated in the quoted paper and we compare the outcomes obtained via the new operators, named SMART, with the fuzzy arithmetic mean as a canonical benchmark.
Incoherence correction strategies in statistical matching Brozzi, Alessandro; Capotorti, Andrea; Vantaggi, Barbara
International journal of approximate reasoning,
11/2012, Letnik:
53, Številka:
8
Journal Article, Conference Proceeding
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Several economic applications require to consider different data sources and to integrate the information coming from them. This paper focuses on statistical matching, in particular we deal with ...incoherences. In fact, when logical constraints among the variables are present incoherencies on the probability evaluations can arise. The aim of this paper is to remove such incoherences by using different methods based on distances minimization or least commitment imprecise probabilities extensions. An illustrative example shows peculiarities of the different correction methods. Finally, limited to pseudo distance minimization, we performed a systematic comparison through a simulation study.
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