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We propose to explore the potential of physics-informed neural networks (PINNs) in solving a class of partial differential equations (PDEs) used to model the propagation of chronic inflammatory bowel diseases, such as Crohn's disease and ulcerative colitis. An unsupervised approach was privileged during the deep neural network training. Given the complexity of the underlying biological system, characterized by intricate feedback loops and limited availability of high-quality data, the aim of this study is to explore the potential of PINNs in solving PDEs. In addition to providing this exploratory assessment, we also aim to emphasize the principles of reproducibility and transparency in our approach, with a specific focus on ensuring the robustness and generalizability through the use of artificial intelligence. We will quantify the relevance of the PINN method with several linear and non-linear PDEs in relation to biology. However, it is important to note that the final solution is dependent on the initial conditions, chosen boundary conditions, and neural network architectures.

Since the first reports of a coronavirus (CoV) disease 2019 (COVID-19) caused by severe acute respiratory syndrome virus (SARS-CoV-2) in Wuhan, Hubei province, China, scientists are working around the clock to find sound answers to the issue of its origin. While the number of scientific articles on SARS-CoV-2 is increasing, there are still many gaps as to its origin. All studies failed to find a coronavirus in other animals that is more similar to human SARS-COV2 than the bat virus, considered to be the primary reservoir. In this paper we address a new hypothesis, based on a possible recombination between a DNA and SARS-CoV viruses, to explain the rise of SRAS-CoV-2. By comparing SARS-CoV-2 and related CoVs with circoviruses (CVs), we found strong sequence similarity of the genomic region at the 3-end of Bat-CoV ORF1a and the origin of replication (Ori) of porcine CV type 2 (PCV2), as well as similar RNA secondary structures of the region encompassing the cleavage site of CoV S gene with the PCV2 Ori. This constitutes a primary evidence that supports a possible recombination, which occurrence might explain the origin of SARS-CoV-2., Comment: 18 pages, 4 figures

Codalema is one of the experiments devoted to the detection of ultra high energy cosmic rays by the radio method. The main objective is to study the features of the radio signal induced by the development in the atmosphere of extensive air showers (EAS) generated by cosmic rays in the energy range of 10 PeV-1 EeV . After a brief presentation of the detector features, the main results obtained are reported (emission mechanism, lateral distribution of the electric field, energy calibration, etc.). The first studies of the radio wave front curvature are discussed as new preliminary results., Comment: Proc. of the annual meeting of the French Society of Astronomy & Astrophysics SF2A, Paris, June 2011, G. Alecian, K. Belkacem, R. Samadi and D. Valls-Gabaud (eds)

A study of the response in energy of the radio-detection method of air showers initiated by ultra-high-energy cosmic rays is presented. Data analysis of the CODALEMA experiment shows that a strong correlation can be demonstrated between the primary energy of the cosmic ray and the electric field amplitude estimated at the heart of the radio signal. Its sensitivity to the characteristics of shower suggests that energy resolution of less than 20% can be achieved. It suggests also that, not only the Lorentz force, but also another contribution proportional to all charged particles generated in the development of the shower, could play a significant role in the amplitude of the electric field peak measured by the antennas (as coherence or the charge excess)., Comment: 21 pages, 13 figures, 2 tables

Reconstruction of the curvatures of radio wavefronts of air showers initiated by ultra high energy cosmic rays is discussed based on minimization algorithms commonly used. We emphasize the importance of the convergence process induced by the minimization of a non-linear least squares function that affects the results in terms of degeneration of the solutions and bias. We derive a simple method to obtain a satisfactory estimate of the location of the main point of emission source, which mitigates the problems previously encountered.

In this paper we expose a dynamic traffic-classification scheme to support multimedia applications such as voice and broadband video transmissions over IEEE 802.11 Wireless Local Area Networks (WLANs). Obviously, over a Wi-Fi link and to better serve these applications - which normally have strict bounded transmission delay or minimum link rate requirement - a service differentiation technique can be applied to the media traffic transmitted by the same mobile node using the well-known 802.11e Enhanced Distributed Channel Access (EDCA) protocol. However, the given EDCA mode does not offer user differentiation, which can be viewed as a deficiency in multi-access wireless networks. Accordingly, we propose a new inter-node priority access scheme for IEEE 802.11e networks which is compatible with the EDCA scheme. The proposed scheme joins a dynamic user-weight to each mobile station depending on its outgoing data, and therefore deploys inter-node priority for the channel access to complement the existing EDCA inter-frame priority. This provides efficient quality of service control across multiple users within the same coverage area of an access point. We provide performance evaluations to compare the proposed access model with the basic EDCA 802.11 MAC protocol mode to elucidate the quality improvement achieved for multimedia communication over 802.11 WLANs., Comment: 15 pages, 8 figures, 3 tables, International Journal of Computer Networks & Communications (IJCNC)

Previous studies have shown that the actual handoff schemes employed in the IEEE 802.11 Wireless LANs (WLANs) do not meet the strict delay constraints placed by many multimedia applications like Voice over IP. Both the active and the passive supported scan modes in the standard handoff procedure have important delay that affects the Quality of Service (QoS) required by the real-time communications over 802.11 networks. In addition, the problem is further compounded by the fact that limited coverage areas of Access Points (APs) occupied in 802.11 infrastructure WLANs create frequent handoffs. We propose a new optimized and fast handoff scheme that decrease both handoff latency and occurrence by performing a seamless prevent scan process and an effective next-AP selection. Through simulations and performance evaluation, we show the effectiveness of the new adaptive handoff that reduces the process latency and adds new context-based parameters. The Results illustrate a QoS delay-respect required by applications and an optimized AP-choice that eliminates handoff events that are not beneficial., Comment: 20 pages, 14 figures, 4 tables