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Distance-based measures of incoherence for pairwise comparisons
No full textCoherence of preferences, and the measurement of its violation, has been a long standing issue in decision analysis. This paper focuses on preferences expressed by means of Pairwise Comparison Matrices. Whereas the consistency, that represents the full coherence, has been quantitatively measured by means of many indices proposed in literature, the same cannot be said for the other coherence conditions; as an example, thus far, the deviation of a set of preferences from transitivity condition has been represented by simple counts of how many times the transitivity condition is violated. As simple counts use only ordinal information discarding the information related with intensities of preferences, this manuscript introduces a cardinal approach where the deviation from the transitivity, and from further coherence levels, is seen as a matter of degree. This approach seems more suitable to cardinal preference relations where the decision makers’ preferences themselves are a matter of degree
Managing supply chain resilience to pursue business and environmental strategies
No full textResilience has become a crucial topic in the field of strategic management as it requires companies to design resilient business models to tackle managerial and environmental disruptions of individual firms and supply chains. However, extant research still lacks deep insights into how companies design and manage supply chains according to the resilience principles. With this premise, this paper aims at conducting a state of the art review on supply chain resilience (SCR) considering 125 relevant papers collected from Scopus and Web of Science academic search engine. Starting from the results of the literature review, this study proposes a systemic framework of SCR assessment and contributes to improve the understanding of the impact of different empirically tested constructs on the development of the resilience concept. Further, the findings are summarized in several areas including barriers in developing resilience, metrics to measure the resilience performance, and effective strategies to foster the SCR. Finally, this study outlines promising future research directions for scholars and practitioners
Relazione introduttiva al Convegno su "Diritti e nuove vulnerabilità in tempo di pandemia: re-immaginare gli spazi urbani"
No full textGli spazi urbani in tempi di pandemi
Centro Interdipartimentale Ricerca Peptidi Biattivi, Università degli Studi di Napoli “Federico II” (http://www.cirpeb.unina.it/) .
No full textComitato Scientifico della Collana del Dipartimento di Giurisprudenza dell'Università degli Studi Brescia, edita da Giappichelli, Torino
No full textDesigning for Confidence A concept for elevating the user’s confidence during a statistical study with artificial intelligence
Get PDFThe capabilities of Artificial Intelligence (AI) are utilized increasingly
in today‘s world. The autonomous and adaptive characteristics
allow applications to be more effective and efficient. A certain
subfield of Artificial Intelligence, Machine Learning, is enabling
services to be tailored to a user‘s specific needs. This could prove to
be useful in an information-heavy field such as Statistics. As design
research from SPSS Statistics, a legacy statistical application, has
indicated, statistics beginners struggle to tackle the challenge of
preparing a statistical research study. They turn to several sources
of information in an attempt to find help and answers but are not
always successful. This leads to them being unconfident before
they have even started to execute the statistical study. The adaptive
features of Artificial Intelligence could help support students
in this case, if designed according to established principles. This
thesis investigated the question whether an AI-powered solution
could elevate the users‘ confidence in statistical research studies.
In order to find the answer, a prototype with exemplary User Experience
was designed and implemented. Preceding research determined
the domain and market offer. User research was conducted
to ensure a human-centered outcome. The prototype was evaluated
with real test users and the results answered the question in
the affirmative.Die Fähigkeiten der künstlichen Intelligenz (KI) werden in der heutigen
Zeit zunehmend genutzt. Die autonomen und anpassungsfähigen
Eigenschaften erlauben es, Anwendungen effektiver und
effizienter zu gestalten. Ein bestimmtes Teilgebiet der Künstlichen
Intelligenz, das maschinelle Lernen, ermöglicht es, Dienstleistungen
auf die spezifischen Bedürfnisse eines Benutzers zuzuschneiden.
Dies könnte sich in einem informationsintensiven Bereich wie
der Statistik als nützlich erweisen. Wie die Designforschung von
SPSS Statistics, einer statistischen Anwendung, gezeigt hat, haben
Statistikanfänger Schwierigkeiten mit der Vorbereitung einer statistischen
Forschungsstudie. Sie wenden sich an mehrere Informationsquellen,
um Hilfe und Antworten zu finden, aber sind nicht
immer erfolgreich. Dies führt dazu, dass sie unzuversichtlich sind,
bevor sie überhaupt mit der Durchführung der statistischen Studie
begonnen haben. Die adaptiven Eigenschaften der künstlichen
Intelligenz könnten in diesem Fall helfen, die Studenten zu unterstützen,
wenn sie nach etablierten Prinzipien gestaltet werden. In
dieser Arbeit wurde der Frage nachgegangen, ob eine KI-gestützte
Lösung das Selbstbewusstsein der Nutzer vor und während
statistischen Forschungsstudien erhöhen kann. Um die Antwort
zu finden, wurde ein Prototyp mit vorbildhagter User Experience
entworfen und implementiert. Die vorangegangene Forschung
bestimmte die Domäne und das Marktangebot. Nutzerforschung
wurde durchgeführt, um ein auf den Menschen zentriertes Ergebnis
sicherzustellen. Der Prototyp wurde mit echten Testnutzern
evaluiert, und die Ergebnisse haben die Frage bejaht
Evaluation zur Wahrnehmung von Kryptowährungen innerhalb der Generation Z mit Prognose für die Akzeptanz in der Zukunft
Get PDFDiese Ausarbeitung beschäftigt sich mit der Wahrnehmung der Bevölkerungsgruppe Generation Z in Bezug auf Kryptowährungen und die dahinterliegende Technologie der Blockchain. Es wurde mittels einer empirischen quantitativen Umfrage erhoben, welche Medien, die die Jugendlichen konsumieren, wie über die Themen berichten, sowie welche Erfahrungen die Jugendlichen gemacht haben und welches Wissen sie sich dabei angeeignet haben. Im Anschluss wurde aus den erhobenen Informationen eine intuitive Prognose erstellt, wie die Generation Z zukünftig über Kryptowährungen und die Blockchain Technologie denken könnte. Die Teilnehmer der Umfrage zeigen ein breites Wissen über die Funktionsweise von Kryptowährungen, auch ohne den Begriff der Blockchain verinnerlicht zu haben. Es existieren Ängste, dass diese Technologie für illegale Zwecke missbraucht wird. Für die Prognose bewiesen die Teilnehmer Aufgeschlossenheit und Interesse am Thema Kryptowährungen. Sie sind auch bereit, gefestigte Meinungen zu hinterfragen.This thesis deals with the perception of the generation Z regarding cryptocurrencies and the underlying technology of the Blockchain. Using an empirical quantitative survey, it was determined which media the young people consume, how they report on the topics, as well as what experiences the young people had and what knowledge they acquired. Subsequently, the information collected will then be used for an intuitive prognosis of how Generation Z might think about cryptocurrencies and Blockchain technology in the future. The participants of the survey show a broad knowledge of how crypto currencies work, even without having internalized the word Blockchain. Fears that this technology will be misused for illegal purposes. For the prognosis, the participants showed open-mindedness and interest in the topic of crypto currencies. They are also willing to question established opinions
Spatial patterns and temporal variability of seagrass connectivity in the Mediterranean Sea
No full textAim: The endemic seagrass Posidonia oceanica is a key component of the coastal seascapes of the Mediterranean Sea, where it provides crucial ecosystem services and promotes the assembly of diverse ecological communities. Although protection policies exist, P. oceanica meadows have been steadily declining in the recent past because of human activities and climate change. Here, we quantitatively analyse basin-wide patterns of seagrass connectivity over a 30-year-long period and identify connectivity hotspots that may serve as priority targets for conservation actions. Location: Mediterranean Sea. Time period: 1987–2016. Major taxa studied: The seagrass P. oceanica. Methods: A biophysical Lagrangian approach is used to simulate dispersal of seagrass fruits operated by marine currents. Connectivity metrics (self-retention, indegree and outdegree) are evaluated on top of Lagrangian simulations to identify the most ecologically connected areas. Time series of local connectivity scores are analysed to study temporal variability and possibly detect trends at different spatial scales. Results: Spatio-temporal variability is an important component of seagrass connectivity in the Mediterranean. Connectivity hotspots are unevenly distributed in all of its four main sub-basins, and along both European and African coastlines. Although statistically significant local trends in connectivity are generally quite infrequent across the whole basin, they appear to be relatively more prevalent in connectivity hotspots. The interannual variability of average connectivity scores seems to be at least partially linked to meteorological fluctuations. Main conclusions: The present study represents a step forward in the application of a quantitative, scalable and replicable methodological framework for the prioritization of seagrass conservation actions in the Mediterranean large marine ecosystem, a challenging environment characterized by complex socio-economic boundary conditions and high sensitivity to the localized effects of global climate change
Breast cancer chemotherapeutic options: a general overview on the preclinical validation of a multi-target ruthenium(III) complex lodged in nucleolipid nanosystems
No full textIn this review we have showcased the preclinical development of original amphiphilic
nanomaterials designed for ruthenium‐based anticancer treatments, to be placed within the current
metallodrugs approach leading over the past decade to advanced multitarget agents endowed with
limited toxicity and resistance. This strategy could allow for new options for breast cancer (BC)
interventions, including the triple‐negative subtype (TNBC) with poor therapeutic alternatives. BC
is currently the second most widespread cancer and the primary cause of cancer death in women.
Hence, the availability of novel chemotherapeutic weapons is a basic requirement to fight BC
subtypes. Anticancer drugs based on ruthenium are among the most explored and advanced nextgeneration
metallotherapeutics, with NAMI‐A and KP1019 as two iconic ruthenium complexes
having undergone clinical trials. In addition, many nanomaterial Ru complexes have been recently
conceived and developed into anticancer drugs demonstrating attractive properties. In this field,
we focused on the evaluation of a Ru(III) complex—named AziRu—incorporated into a suite of both
zwitterionic and cationic nucleolipid nanosystems, which proved to be very effective for the in vivo
targeting of breast cancer cells (BBC). Mechanisms of action have been widely explored in the
context of preclinical evaluations in vitro, highlighting a multitarget action on cell death pathways
which are typically deregulated in neoplasms onset and progression. Moreover, being AziRu
inspired by the well‐known NAMI‐A complex, information on non‐nanostructured Ru‐based
anticancer agents have been included in a precise manner