12,081 research outputs found
Embryonic and neonatal mortality from salmonellosis in captive bred raptors
No full textIn a captive breeding center near Rome (Italy), cases of embryonic and neonatal death were recorded during the breeding seasons in the European eagle owl (Bubo bubo), peregrine falcon (Falco peregrinus), buzzard (Buteo buteo), and lanner falcon. (Falco biarmicus). Salmonella havana and S. virchow were isolated. Three pulli, clinically infected with S. havana, were successfully treated with enrofloxacin. From two groups of healthy 3- to 4-wk-old eagle owls, Salmonella sp. group 61 (61:r:-) and S. havana were collected. A strain of S. paratyphi B was detected in a pharyngeal swab and a fecal sample from an adult female goshawk (Accipiter gentilis), affected with pharyngeal trichomoniasis. A S. hadar strain was collected from a healthy 1-yr-old female eagle owl and S. livingstone was isolated from a 1-mo-old female peregrine, dead of an acute respiratory syndrome. Lesions of fibrinous polyserositis and multivisceral congestion were observed. From frozen 1-day-old chicks, on which adult and young raptors were fed, S. havana and S. livingstone isolates with similar biochemical and drug susceptibility patterns to those isolated from raptors were identified. A surveillance program on infectious diseases reduced embryonic and neonatal death rates in the following breeding seasons.[...
Human-AI Collaboration in Academic Writing: towards a Synergy Model and A Case to Include AI as a Co-Author
No full textAs generative AI systems such as ChatGPT and Gemini 2.5 become increasingly integrated into academic workflows, the question of their legitimacy, limitations, and potential in scholarly writing has become urgent. This paper presents a reflexive case study of a sustained collaboration between a domain expert in consciousness studies and Gemini 2.5, culminating in the co-authorship of a peer-reviewed research article. By analyzing exactly 37,440 words of recorded interactions, we identify patterns of synergy, including recursive refinement, conceptual amplification, and accelerated manuscript development. We argue that when guided by a knowledgeable human author, AI can act as a cognitive partner rather than a passive tool—amplifying scholarly creativity and improving efficiency without compromising academic rigor. The case supports a '1+1=3' synergy model for co-authorship, in which human steering and AI fluency converge to produce novel insights and polished output faster and more effectively than either could achieve alone. The findings advocate for a paradigm shift from prohibitive policies to the responsible, expert-guided integration of AI in academic research and writing, grounded in transparency and accountability, and present arguments for why the AI tool should be listed as a co-author despite current injunctions against such practice
Meaningful human control: actionable properties for AI system development
No full textHow can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control.Interactive IntelligenceDesign AestheticsCyber SecurityHuman-Robot InteractionEthics & Philosophy of TechnologyHuman Information Communication DesignWeb Information System
A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable
No full textBecause of recent and rapid developments in Artificial Intelligence (AI), humans and AI-systems increasingly work together in human-agent teams. However, in order to effectively leverage the capabilities of both, AI-systems need to be understandable to their human teammates. The branch of eXplainable AI (XAI) aspires to make AI-systems more understandable to humans, potentially improving human-agent teamwork. Unfortunately, XAI literature suffers from a lack of agreement regarding the definitions of and relations between the four key XAI-concepts: transparency, interpretability, explainability, and understandability. Inspired by both XAI and social sciences literature, we present a two-dimensional framework that defines and relates these concepts in a concise and coherent way, yielding a classification of three types of AI-systems: incomprehensible, interpretable, and understandable. We also discuss how the established relationships can be used to guide future research into XAI, and how the framework could be used during the development of AI-systems as part of human-AI teams.Accepted author manuscriptInteractive Intelligenc
Using Generative AI in Research
No full textThe slides accompany a workshop that is intended for graduate students to learn more about generative AI in the context of the research lifecycle. This work is licensed under a Creative Commons license so that others may share and adapt the content for other purposes as long as appropriate credit is provided to the author of the work. To access the Google slides, click here: https://bit.ly/Library_AI_Research
Learning Objectives
At the end of the session participants will be able to:
Demonstrate a basic understanding of how AI tools work
Differentiate between grounded and ungrounded AI tools
Identify key considerations for grad students/researchers
Identify ways AI tools can be used to support the phases of the research lifecycle
Identify main areas of concern with using AI tools
Outline the steps and potential resources for evaluating and citing AI outpu
Occurrence of Salmonella in pigs from herds of the province of Rome over a 15-year-period (1980-1994)
No full textAntimicrobial agents and Clostridium difficile colitis: Pathological studies in guinea pigs with clindamycin-associated pseudomembranous colitis
No full textThe AI Author in Litigation
No full textMany scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity.
However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on another’s. A cause of action is meaningless if a copyright owner cannot enforce it by suing the infringer or if the infringer is judgement-proof. Thus, when contemplating whether an emancipated AI—or any non-human—can be an author under the Copyright Act, part of that examination should be whether the AI which created the work can sue or be sued for infringement.
This article considers issues from the theoretical, like civil procedure and remedies, to the practical, such as legal representation and discovery. How is an AI served with a lawsuit? What would be an adequate, enforceable remedy for an AI’s infringement? Is an AI even bound by our laws? Additional questions—and procedural barriers—are raised when considering other roles an AI might play in an infringement action: as a witness, a co-party, or even a plaintiff seeking to protect its own creative expression.
This morass of legal headaches goes beyond any doctrinal issues regarding authorship, and provide ample reason to keep legal authorship in the hands of humans or entities controlled by humans—at least until legal procedure catches up to technological realities and possibilities for litigation that AI parties present
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The AI Author in Litigation
No full textMany scholars have posited whether a computer possessing Artificial Intelligence (AI) could be considered an author as defined per the Copyright Act of 1976. What was once a thought experiment is now becoming reality. To date, scholarship has focused primarily been on whether an AI meets the requirements of authorship from a purely objective legal framework or whether an AI could be an author based on the doctrines of incentives, independent creation, and creativity.
However, a burden inherent in the rights and liabilities of authorship is the ability to be held liable if that author’s expressive work is infringing on another’s. A cause of action is meaningless if a copyright owner cannot enforce it by suing the infringer or if the infringer is judgement-proof. Thus, when contemplating whether an emancipated AI—or any non-human—can be an author under the Copyright Act, part of that examination should be whether the AI which created the work can sue or be sued for infringement.
This article considers issues from the theoretical, like civil procedure and remedies, to the practical, such as legal representation and discovery. How is an AI served with a lawsuit? What would be an adequate, enforceable remedy for an AI’s infringement? Is an AI even bound by our laws? Additional questions—and procedural barriers—are raised when considering other roles an AI might play in an infringement action: as a witness, a co-party, or even a plaintiff seeking to protect its own creative expression.
This morass of legal headaches goes beyond any doctrinal issues regarding authorship, and provide ample reason to keep legal authorship in the hands of humans or entities controlled by humans—at least until legal procedure catches up to technological realities and possibilities for litigation that AI parties present
Infezione da TSWV in Alstroemeria spp. in Liguria Maria Grazia Bellardi, Lisa Cavicchi, Giorgio Bozzano, Mario Mattone, Giuseppe Parrella
No full textI Tospovirus (famiglia Bunyaviridae) costituiscono un gruppo di virus estremamente pericolosi in tutto il mondo, il cui capostipite (TSWV: virus dell’avvizzimento maculato del pomodoro) è purtroppo assai noto ai coltivatori liguri (e non solo) di orticole, aromatiche ed ornamentali.
Di TSWV (e di INSV, virus della maculatura necrotica dell’impatiens) ci siamo ampiamente occupati in questi ultimi anni; basti citare le recenti segnalazioni su specie ornamentali (Iberis semperflorens, Lupinus spp., Stephanotis floribunda, Arctotis x hybrida, ciclamino, calla bianca, ecc.) caratterizzate da gravi sintomatologie che hanno compromesso la produttività degli impianti.
TSWV e INSV non rappresentano però le uniche specie di Tospovirus note: fino ad oggi nel mondo ne sono state descritte almeno 19, fra cui IYSV (virus della maculatura gialla dell’iris) presente in Italia su cipolla da seme.
In questa breve nota ci occupiamo di una rizomatosa, Alstroemeria spp., segnalata nel 1992 in Italia ospite naturale di TSWV: le piante, cresciute in una serra ligure, manifestavano anulature e maculature gialle sulle foglie, e producevano un numero limitato di fiori. Da allora non si sono registrate ulteriori segnalazioni su questa ornamentale, fino al mese di aprile del 2015 quando, in una serra della Piana di Albenga (Savona) su due piante di una varietà “nana” (proveniente dall’Olanda) sono stati osservati sintomi attribuibili a TSWV.
Prendiamo spunto da questo recente caso per parlare degli altri Tospovirus presenti in Europa e del costante pericolo di una loro introduzione nel nostro Paese mediante materiale di propagazione già infetto o contaminato da tripidi viruliferi.
Le due piante oggetto di studio, cresciute in vaso, sono state inviate al DipSA (Università di Bologna) nel febbraio del 2015. I sintomi consistevano in anulature più o meno ampie, bianche o giallastre, sulle foglie e/o “variegatura” del lembo fogliare. Nel mese di marzo, si è assistito alla produzione dei boccioli: i fiori, di colore rosso porpora, sono apparsi nomali come forma e dimensione.
Questa breve indagine conferma Alstroemeria spp. ospite naturale di TSWV in Italia. Nel 1992 (anno del primo ritrovamento) l’identificazione era stata ottenuta unicamente grazie all’applicazione di tecniche sierologiche (immunodiffusione in gel di agar), mentre oggi sono state utilizzate quelle ben più sensibili di biologia molecolare.
La sintomatologia di allora solo in parte è simile a quella osservata sulle due piante oggetto di studio; un “punto” in comune è il non coinvolgimento dei fiori.
Una volta esclusa fortunatamente l’introduzione nel nostro Paese del “nuovo” Tospovirus ANSV, resta il dubbio se TSWV fosse già presente nel materiale di propagazione importato o se l’infezione sia stata contratta durante la crescita nella serra ligure, trasmessa da tripidi vettori. Considerando che non si sono notati altri esemplari infetti, si è più propensi verso la prima ipotesi. Ciò significa che, quando si tratta di Tospovirus non bisogna mai abbassare la guardia e che, anche quando gli effetti negativi dell’infezione sulla produzione appaiono molti contenuti (come nel nostro caso), occorre comunque rivolgersi a Laboratori di analisi specializzati nella diagnosi di fitovirus
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