Il linguaggio politico dell’Eliseo dopo il gollismo

Protagonista della vita politica nazionale e detentore di ampi poteri politici e simbolici, il presidente della Quinta Repubblica francese è una figura di grande interesse sia per gli studiosi di politica che per gli esperti di comunicazione. Le circostanze storiche degli ultimi decenni hanno contribuito, infatti, a consegnare al presidente francese uno status del tutto peculiare, difficilmente paragonabile a quello di altri capi di Stato europei. Attraverso l’analisi (tematica, retorica e argomentativa) dei principali discorsi ufficiali pronunciati da Giscard d’Estaing, Mitterrand e Chirac, viene descritta l’evoluzione della funzione presidenziale nella fase di consolidamento della Quinta repubblica, nel tentativo di analizzare le trasformazioni delle culture politiche nella Francia degli ultimi trent’anni. La tesi sostenuta in questo lavoro è che la progressiva deritualizzazione della comunicazione presidenziale va di pari passo con un sensibile slittamento della retorica politica dal polo razionale del logos a quelli, più affettivi, dell'ethos e del pathos

Association Rule Mining Meets Regression Analysis: An Automated Approach to Unveil Systematic Biases in Decision-Making Processes

Decisional processes are at the basis of most businesses in several application domains. However, they are often not fully transparent and can be affected by human or algorithmic biases that may lead to systematically incorrect or unfair outcomes. In this work, we propose an approach for unveiling biases in decisional processes, which leverages association rule mining for systematic hypothesis generation and regression analysis for model selection and recommendation extraction. In particular, we use rule mining to elicit candidate hypotheses of bias from the observational data of the process. From these hypotheses, we build regression models to determine the impact of variables on the process outcome. We show how the coefficient of the (selected) model can be used to extract recommendation, upon which the decision maker can operate. We evaluated our approach using both synthetic and real-life datasets in the context of discrimination discovery. The results show that our approach provides more reliable evidence compared to the one obtained using rule mining alone, and how the obtained recommendations can be used to guide analysts in the investigation of biases affecting the decisional process at hand.</p

Understanding the stumbling blocks of Italian higher education system:A process mining approach

Nowadays universities strive to continuously enhance their educational programs to improve both the quality and quantity of their graduates. This is a sensitive problem, especially for Italian universities where only 30% of the students enrolled at the university succeed in graduating within a year after the normal duration of the study plan. Over the last few years, the Italian Ministry of University and Education has introduced several indicators to assess students’ careers and help universities identify possible criticality in their study programs. However, these indicators only provide a high-level overview of the graduation process without providing insights into students’ failure. To address this issue, in this work, we propose to model a study program as a process and exploit process analysis techniques to assess students’ performance. These techniques allow delving into students’ careers, thus enabling the investigation of their failures and delays. The findings obtained by applying our approach to the Bachelor program of an Italian university allowed us to determine common bottlenecks that seem to have an impact on students’ graduation time. Moreover, we were able to determine and compare the career paths of successful and late students. The insights gathered by our analysis can be used to support university personnel in delving into factors causing some exams to be a bottleneck, as well as to determine potential improvements in the overall curricula.</p

Isolation of Methicillin-Resistant Coagulase-Negative Staphylococcus (MRCoNS) from a fecal-contaminated stream in the Shenandoah Valley of Virginia

Staphylococcus is comprised of 41 known species, of which 18 can colonize humans. Despite the prevalence of infectious Staphylococcus within hospital settings and agriculture, there are few reports of Staphylococcus in natural bodies of water. A recent study by the US Food and Drug Administration found substantial contamination of poultry and other meats with Staphylococcus. We hypothesized that intensive farming of poultry adjacent to streams would result in contaminated runoff, resulting in at least transient occurrence of Staphylococcus spp. in stream waters and sediments. In this study, we sought to determine whether Staphylococcus occurs and persists within Muddy Creek, a stream located in Hinton, Virginia that originates at the Appalachian Mountains of Virginia and runs through various agricultural fields and adjacent to a poultry processing plant in the central Shenandoah Valley. Five different Staphylococcus spp. were detected in water and sediment from Muddy Creek. Mannitol Salt Agar (MSA) was used to isolate eleven Staphylococcus from both water and sediment. These isolates were Gram-positive, catalase-positive, and oxidase-negative cocci that were capable of fermenting mannitol. In addition, a method for screening putative staphylococci species from stream water and sediment was developed. Ten out of the eleven tested isolates were oxacillin resistant (now used to identify phenotypic methicillin-resistance) using a Kirby Bauer disc diffusion test. Furthermore, the isolates were susceptible to trimethoprim/sulfamethoxazole, tetracycline, and gentamicin while two of the isolates were resistant to erythromycin. Additionally, the BOX-PCR repetitive sequence fingerprinting method verified the presence of nine different strains among the isolates. Sequencing of the 16S rRNA gene identified five of the isolates as Staphylococcus equorum. The Biolog identification protocol further identified the remaining isolates as Staphylococcus xylosus, Staphylococcus lentus, Staphylococcus succinus, and Staphylococcus sciuri. Finally, polymerase chain reaction amplification (PCR) confirmed that ten of the eleven isolates harbored the mecA gene known to confer methicillin-resistance. Overall, the occurrence of coagulase-negative staphylococci (MRCoNS) in stream water and sediment represents a potential environmental and human health concern

Understanding the stumbling blocks of Italian higher education system:A process mining approach

Nowadays universities strive to continuously enhance their educational programs to improve both the quality and quantity of their graduates. This is a sensitive problem, especially for Italian universities where only 30% of the students enrolled at the university succeed in graduating within a year after the normal duration of the study plan. Over the last few years, the Italian Ministry of University and Education has introduced several indicators to assess students’ careers and help universities identify possible criticality in their study programs. However, these indicators only provide a high-level overview of the graduation process without providing insights into students’ failure. To address this issue, in this work, we propose to model a study program as a process and exploit process analysis techniques to assess students’ performance. These techniques allow delving into students’ careers, thus enabling the investigation of their failures and delays. The findings obtained by applying our approach to the Bachelor program of an Italian university allowed us to determine common bottlenecks that seem to have an impact on students’ graduation time. Moreover, we were able to determine and compare the career paths of successful and late students. The insights gathered by our analysis can be used to support university personnel in delving into factors causing some exams to be a bottleneck, as well as to determine potential improvements in the overall curricula.</p

Personalizzazione della politica e campagne elettorali: il caso delle regionali 2010 nel Lazio

Il saggio analizza la campagna elettorale per le elezioni regionali nel Lazio del 2010, che hanno viste contrapposte due donne: Renata Polverini e Emma Bonino. Sono messi a confronto i due stili comunicativi e le differenti strategia adottate

Towards a systematic process-aware behavioral analysis for security

\u3cp\u3eNowadays, security is a key concern for organizations. An increasingly popular solution to enhance security in organizational settings is the adoption of anomaly detection systems. These systems raise an alert when an abnormal behavior is detected, upon which proper measures have to be taken. A well-known drawback of these solutions is that the underlying detection engine is a black box, i.e., the behavioral profiles used for detections are encoded in some mathematical model that is challenging to understand for human analysts or, in some cases, is not even accessible. Therefore, anomaly detection systems often fail in supporting analysts in understanding what is happening in the system and how to respond to detected security threats. In this work, we investigate the use of process analysis techniques to build behavioral models understandable by human analysts. We also delineate a systematic methodology for process-aware behaviors analysis and discuss the findings obtained by applying such a methodology to a real-world event log.\u3c/p\u3

Unveiling systematic biases in decisional processes: an application to discrimination discovery

Decisional processes are at the basis of several security and privacy applications. However, they are often not transparent and can be affected by human or algorithmic biases that may lead to systematically misleading or unfair outcomes. To unveil these biases, one has to identify which information was used to make the decision and to quantify to what extent such information has influenced the process outcome. Two classes of techniques are widely used to determine possible correlation between variables within decisional processes from observational data: (i) econometric techniques, in particular regression analysis, and (ii) knowledge discovery techniques, in particular association rules mining. However, these techniques, taken individually, have intrinsic drawbacks that limit their applicability. In thiswork, we propose an approach for unveiling biases in decisional processes, which leverages association rule mining for systematic hypothesis generation and regression analysis for model selection and recommendation extraction. We demonstrate the proposed approach in the context of discrimination detection, showing that not only it provides 'statistically significant' evidence of discrimination but it also allows for a more efficient operationalization of the recommendations extracted, upon which the decision maker can operate

A cosa serve una bella campagna?

il volume analizza le ragioni che hanno portato alla sconfitta delle sinistre nelle elezioni del 2008. In particolare, il contributo analizza la campagna elettorale di Veltroni e della Sinistra Arcobalen