1,030 research outputs found
Come rimanere rimasti. La trasmigrazione di Timothy Archer
No full textUn’analisi ravvicinata dell’ultimo romanzo di Philip. K. Dick
Characterization of Neoparamoeba pemaquidensis strains: PCR-RFLP of the internal transcribed spacer region from the amoeba and endosymbiont
No full textNeoparamoeba pemaquidensis continues to be an ongoing problem for commercial finfish aquaculture and has also sporadically been associated with mass mortalities of commercially relevant marine invertebrates. Despite the ubiquity and importance of this amphizoic amoeba, our understanding of the biology as it applies to host range, pathogenicity, tissue tropism, and geographic distribution is severely lacking. This may stem from the inability of current diagnostic tests based on morphology, immunology, and molecular biology to differentiate strains at the subspecies level. In the present study, we developed a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method based on the internal transcribed spacer (ITS) region that can accurately differentiate amoeba strains of N. pemaquidensis. The investigation focused on the complications of the amoeba ITS microheterogeneity in the development of a subspecies marker and the use of the endosymbiont, Ichthyobodo necator related organism (IRO), ITS region as an alternative marker. The combination of host amoeba and endosymbiont ITS PCR-RFLP analyses was successfully used to correctly identify and characterize an N. pemaquidensis isolate from an outbreak of amoebic gill disease in Atlantic salmon Salmo salar from the west coast of North America (Washington State, USA).Charles G. B. Caraguel, Nathanaëlle Donay, Salvatore Frasca Jr., Charles J. O’Kelly, Richard J. Cawthorn Spencer J. Greenwoo
A conservative numerical method for a time fractional diffusion equation
No full textGeometric numerical integration, the branch of numerical analysis with the goal of finding approximate solutions of differential equations that preserve some structure of the continuous problem, is a well established field of research [5]. In particular, requiring that invariants or conservation laws are preserved, on one hand, applies on the approximations some constraints that are satisfied also by the exact solutions. On the other hand, it guarantees a better propagation of the error over long integration times [3].
In the last two decades, new techniques for finding conservation laws of fractional differential equations have been derived by suitably generalising methods for PDEs [4, 6]. However, the numerical preservation of conservation laws of time fractional differential
equations is a research topic still at an embryonic state. This talk deals with the numerical solution of diffusion equations in the form
D^α_t u = D^2_x K(u), α ∈ R,
where D_x is the partial derivative in space, K is an arbitrary regular function, and D^α_t
denotes the Riemann-Liouville fractional derivative of order α.
The proposed numerical method combines a finite difference scheme in space with a spectral time integrator and preserves discrete versions of the conservation laws of the original differential equation [1, 2].
The conservative and convergence properties of the proposed method are verified by the computational solution of some numerical experiments.
References
[1] K. Burrage, A. Cardone, R. D’Ambrosio, B. Paternoster. Numerical solution of time fractional diffusion systems. Appl. Numer. Math., 116 (2017), 82–94.
[2] A. Cardone, G. Frasca-Caccia. Numerical conservation laws of time fractional diffusion PDEs. arXiv.2203.01966, (2022).
[3] A. Dur ́an, J. M. Sanz-Serna. The numerical integration of relative equilibrium solutions. Geometric theory. Nonlinearity, 11, 1547–1567, (1998).
[4] G. S. F. Frederico, D. F. M. Torres. Fractional conservation laws in optimal control theory. Nonlinear Dyn., 53 (2008), 215–222.
[5] E. Hairer, C. Lubich, G. Wanner. Geometric Numerical Integration. Structure Preserving Algorithms for Ordinary Differential Equations, volume 31 of Springer Series in Computational Mathematics. Springer, Berlin, second edition, 2006.
[6] S. Y. Lukashchuk. Conservation laws for time-fractional subdiffusion and diffusionwave equations. Nonlinear Dyn., 80 (2015), 791–80
Lavoro a termine e contrattazione collettiva
No full textNel ripercorrere l’evoluzione della disciplina del lavoro a tempo determinato, considerato come emblema della flessibilità e, al contempo, quale strumento per favorire l’incremento dell’occupazione, l’A. analizza in particolare il ruolo svolto dalla contrattazione collettiva, che talvolta è destinataria di un ampio rinvio legale, talaltra si ritrova ad operare entro ristretti limiti.Analysing the evolution and the regulation of fixed-term contract, considered as a symbol of flexibility and, at the same time, as a means to increase employment, the Author particularly examines the role played by collective bargaining, that sometimes is connected to a large legal referral, sometimes has to operate within stricts limit
[ABO-incompatible kidney transplantion]
No full textThe widespread worldwide implementation of ABO-incompatible kidney transplantation (ABOi KT) programs have increased the chances of gaining access to kidney transplantation. In Italy the practice of ABOi KT has somewhat lagged behind that practiced in many other European Countries. Even though some Italian Transplant Centers have recently started ABOi KT programs, most of them appear still reluctant in adopting this procedure. In this paper, nephrologists from two different Italian Transplant Centers express their contrasting point of view concerning specific issues related to ABOi KT. The first issue concerns the safety and efficacy of ABOi KT and how it compares with HLA-incompatible kidney transplantation. The second concerns to what extent does ABOi KT be adopted, whenever a paired kidney exchange program is available. The third issue regards the indications or contraindications of ABOi KT in specific patient categories. The last issue is about the economical sustainability of ABOi KT programs nowadays. The different point of views of the discussants are summarized in the context of the most recent available evidence
Precision in Dermatology: Combining U-Net and Quantum Neural Networks for Melanoma Diagnosis
No full textMelanoma is one of the most severe types of skin cancer, and early diagnosis is crucial to improving the chances of successful treatment. Deep learning models, in particular, have proven to be a highly promising application of artificial intelligence in helping dermatologists diagnose melanoma early. By using these models, dermatological images can be analyzed with greater precision, making it easier to identify suspicious lesions and differentiate between benign and malignant ones. This study shows that more accurate segmentation and classification of skin lesions can be achieved by combining models like U-Net with preprocessing methods such as Autoencoder. This can lead to better melanoma detection and treatment. Additionally, we employed a hybrid CNN-quantum neural network model for classification, which achieved an accuracy of 99.67%, a precision of 99.35%, and a recall of 99.67%
Multitask Hopfield Networks
No full textMultitask algorithms typically use task similarity information as a bias to speed up and improve the performance of learning processes. Tasks are learned jointly, sharing information across them, in order to construct models more accurate than those learned separately over single tasks. In this contribution, we present the first multitask model, to our knowledge, based on Hopfield Networks (HNs), named HoMTask. We show that by appropriately building a unique HN embedding all tasks, amore robust and effective classification model can be learned. HoMTask is a transductive semi-supervised parametric HN, that minimizes an energy function extended to all nodes and to all tasks under study. We provide theoretical evidence that the optimal parameters automatically estimated by HoMTask make coherent the model itself with the prior knowledge (connection weights and node labels). The convergence properties of HNs are preserved, and the fixed point reached by the network dynamics gives rise to the prediction of unlabeled nodes. The proposed model improves the classification abilities of singletask HNs on a preliminary benchmark comparison, and achieves competitive performance with state-of-the-art semi-supervised graph-based algorithms
Comparing Forward-Forward and Backpropagation in U-Net for Melanoma Image Classification
No full textIn recent years, deep neural networks have become essential in medical imaging, especially for precise diagnostic applications. This paper compares two main learning methods for neural networks—Forward-Forward and Backpropagation—focused on the U-Net architecture for classifying dermatological images, specifcally melanomas. The Forward-Forward approach, which sidesteps traditional gradient-based Backpropagation in favor of a simpler, unidirectional process, offers a more computationally effcient alternative. In contrast, Backpropagation is a well-established method for optimizing network weights, especially for complex tasks where high accuracy is crucial. We trained U-Net models on a dataset of melanoma images, evaluating both their computational and diagnostic performance. The fndings show that while Backpropagation achieves higher accuracy and precision, the Forward-Forward method stands out in computational effciency, making it valuable in resourcelimited settings. This study highlights the balance between computational speed and diagnostic accuracy, suggesting potential ways to optimize neural networks for medical diagnostics
A proposito di laicità. Una lunga e complessa storia semantica
No full textThe author, in her essay, describes the place occupied in the distant past of Western culture by the concept of secularism, and uses that are made. The author discovers the concept of secularism in ancient societies to bring it into modernity. He links it to issues related to youth education opportunities, training and multicultural issues. and it focuses on the concept of Citizenship and transmission of knowledge
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