239700 research outputs found
Sort by
Contro-femminismo femminile. Marthe Borély e l'appello alle francesi (1919)
No full textPrima traduzione italiana di L'appel aux françaises di Marthe Borély (1919
Mandarin essential oil-flavoured bio-based active packaging for quality preservation and fungal control in fresh produce
No full textFatigue and adherence can challenge the prevailing wisdom on the response to severe epidemic outbreaks
No full textAfter COVID-19, identifying robust epidemic control principles is a priority of preparedness. We challenge the public health wisdom that responses must be 'early, rapid and aggressive' by focusing on the roles of adherence and associated fatigue for the response's success. Using a model coupling infection transmission and human behaviour, we seek social distancing policies that optimally balance the direct epidemiological costs of an outbreak with its indirect costs. We show that adherence, fatigue and the speed at which they spread critically shape both the type (elimination, suppression and mitigation) and timing of responses depending on their interplay with policymaking priorities. Specifically, when adherence is driven solely by private perceptions, fatigue rules out elimination, limiting feasible interventions to suppression or mitigation. Suppression, prevailing at high-to-moderate health prioritization and fast individuals' responses, needs restriction-relaxation cycles to mitigate fatigue. However, different suppression regimes emerge: while high health prioritization yields overly aggressive measures exacerbating fatigue and undermining adherence, moderate prioritization achieves similar control outcomes while sustaining adherence. Additionally, slow individual responses hinder coordination between public and individual actions, compromising response effectiveness. Effective public communication then becomes essential to realign private behaviour with collective goals. Therefore, behavioural factors should be carefully considered in future response planning
The mite, the bug, and the nematode: Assessing the efficacy of three biological control agents against Echinothrips americanus (Thysanoptera: Thripidae)
No full text
Data Augmentation for Neuroaesthetics Analysis
No full textNeuroaesthetics investigates the neural activities during aesthetic experiences, using EEG recordings or fMRI images to decode the perception of visual art. However, studies in this domain are hindered by the limited and imbalanced nature of datasets, which is due to the subjective and resource-intensive nature of data collection. This study examines the effectiveness of various data augmentation strategies in enhancing EEG classification performance for neuroaesthetic analysis. We experiment three different EEG augmentation techniques, namely Signal Segmentation and Recombination, Temporal and Spatial Reconstruction Data Augmentation, and Gaussian Noise Addition. Furthermore, once extracted the features from the signals, we applied an instance-level data augmentation algorithm, namely SMOTE. We tested the four augmentation techniques individually, as well as SMOTE applied in cascade with the three EEG-specific augmentation methods, using stratified ten-fold cross-validation and leave-one-subject-out validation strategies. Results show that Gaussian Noise Addition, particularly when combined with SMOTE for generalization, yields consistent performance improvements in both accuracy and F-score. Conversely, Temporal and Spatial Reconstruction Data Augmentation often degrades classification performance (up to −9.95% of accuracy). Finally, Signal Segmentation and Recombination achieved the best improvement in the leave-one-subject-out analysis (+2.2% accuracy). Our findings present that appropriate data augmentation can enhance model generalization for aesthetic experience classification
Approved anti- and pro-angiogenic drugs in the two last decades: A historical landscape of the therapeutic opportunities
No full textThe imaginary patient. Fantastic health data and where to find them
No full textIn nome di un’imminente “rivoluzione dell'intelligenza artificiale” nell’ambito dell’assistenza sanitaria e in nome di chatbot e “IA agentica”, che sarebbero in grado di fornire consulenze sanitarie, gli Stati Uniti, le istituzioni internazionali e la Commissione europea stanno promuovendo insistentemente la digitalizzazione e l’integrazione totale dei dati clinici e sanitari.
Sfortunatamente, “digitalizzazione” è solo il nuovo nome della sorveglianza di massa, non esiste alcuna “IA agentica” e chi ci sorveglia non è interessato a rendere l'assistenza sanitaria più accessibile o personalizzata (obiettivo che richiederebbe anzitutto maggiori assunzioni di personale medico qualificato).
Nella migliore delle ipotesi, un sistema di apprendimento automatico in grado di tracciare correlazioni può essere uno strumento ausiliario, in medicina. Un estrusore di stringhe di testo probabili può solo farci immaginare di essere in una relazione medico-paziente, dato che l’attività di un medico non consiste certo nel completamento automatico, su basi probabilistiche, delle frasi del paziente. Un chatbot è dunque inutile e pericoloso, se l'obiettivo è l'assistenza sanitaria. Un'azienda sanitaria privata il cui obiettivo sia l’aumento dei dividendi trimestrali può comunque considerare utili i chatbot, per ridurre i costi. Entro una razionalità strumentale, un'azienda sanitaria può ritenere razionale sostituire i medici con i chatbot, così come riterrebbe razionale, se gestisse una prigione, servire ai detenuti cibo per cani. Dopo tutto, gli analisti finanziari che ragionano entro una logica aziendale si chiedono seriamente se curare i pazienti sia un modello di business sostenibile.
Gli annunci di una rivoluzione sanitaria basata sull'intelligenza artificiale non hanno alcun fondamento scientifico. Sono tuttavia saldamente radicati in settori finanziati dall'industria farmaceutica e dalle aziende tecnologiche. Qui, l'interesse per le promesse di automazione, per la disumanizzazione dei pazienti, per la mercificazione della salute e per la distruzione dei sistemi sanitari pubblici converge con gli obiettivi di sorveglianza, controllo, manipolazione e dominio del complesso militare-industriale statunitense.
Anche se non può curarci, l'IA generativa è perfetta per tutti questi scopi.In the name of an upcoming AI revolution in healthcare and of chatbots and ‘agentic AI’ allegedly capable of providing health advice, the US, international institutions, and the European Commission are pushing for the digitisation of clinical and health data.
Unfortunately, ‘digitisation’ is just a new name for mass surveillance, there is no such a thing as ‘agentic AI’ and those surveilling us are not interested in making healthcare more accessible or personalised, which would simply require hiring more healthcare personnel.
At best, a machine learning system capable of tracking correlations can be an auxiliary tool in medicine. An extruder of probable text strings can only make us imagine that we are in a doctor–patient relationship, since a doctor's job certainly does not consist of auto-completing their patients' sentences. A chatbot is therefore both useless and dangerous, if the objective is healthcare. However, a private healthcare company whose goal is to increase quarterly dividends may consider a chatbot to be a useful cost-reduction tool. Within an instrumental rationality, a healthcare company may find it rational to replace doctors with chatbots, just as it would find it rational to feed prisoners dog food if it ran a prison. After all, financial analysts who think in terms of business logic are seriously asking themselves whether treating patients is a sustainable business model.
Announcements of an AI-based healthcare revolution have no scientific basis. They are deeply rooted in sectors that are heavily funded by the pharmaceutical industry and technology companies. Here, the interest in promises of automation, in dehumanising patients, in commodifying health and in destroying public healthcare systems converge with the surveillance, control, manipulation and domination goals of the US military–industrial complex.
Even if it cannot cure us, generative AI is perfect for all these purposes
Restitution of the Sensory Urban Ambiences of a French Colonial Urban Fabric in Algeria: A Case Study of Didouche Mourad Street, Skikda
No full textThe ambiance-based approach to old urban fabrics has emerged as a response to the evolution of heritage, focusing on the spirit of place and the relationship between people and their environment. It aims to preserve the identity of architectural and urban spaces, incorporating intangible elements beyond their physical character. In Algeria, colonial-era urban fabrics continue to structure cities. Skikda, a city in eastern Algeria was created ex-nihilo during this era. In this context, Didouche Mourad Street—the main thoroughfare and structuring element of the city—constitutes the core of the analysis. This study focuses on the French colonial period (1838–1962), considered a foundational phase in the spatial and sensory formation of the street. It aims to restitute the sensory urban ambiences of this period and to analyse their evolution in order to identify sensory permanences contributing to the heritage identity of the place. A thematic content analysis was used to identify sensory ambiences, supported by NVivo software to quantify their recurrences and analyse their spatio-temporal dynamics. The findings show that some ambiences have persisted, others have disappeared, and new ones have emerged through successive transformations. By documenting the sensory history of the street, this research proposes a conceptual and methodological framework for the interpretation of heritage urban ambiences and for informing contemporary rehabilitation approaches, considering permanent ambiences as interpretative tools and reference points for understanding heritage dynamics
