An information-theoretic perspective of physical adversarial patches.

Real-world adversarial patches were shown to be successful in compromising state-of-the-art models in various computer vision applications. Most existing defenses rely on analyzing input or feature level gradients to detect the patch. However, these methods have been compromised by recent GAN-based attacks that generate naturalistic patches.

Graph Neural Networks in Network Neuroscience.

Noninvasive medical neuroimaging has yielded many discoveries about the brain connectivity. Several substantial techniques mapping morphological, structural and functional brain connectivities were developed to create a comprehensive road map of neuronal activities in the human brain -namely brain graph. Relying on its non-euclidean data type, graph neural network (GNN) provides a clever way of learning the deep graph structure and it is rapidly becoming the state-of-the-art leading to enhanced performance in various network neuroscience tasks.

A New Collaborative Classification Process for Microcalcification Detection Based on Graphs and Knowledge Propagation.

In this paper, we propose a new collaborative process that aims to detect macrocalcifications from mammographic images while minimizing false negative detections. This process is made up of three main phases: suspicious area detection, candidate object identification, and collaborative classification. The main concept is to operate on the entire image divided into homogenous regions called superpixels which are used to identify both suspicious areas and candidate objects.

Toward new multi-wavelets: associated filters and algorithms. Part I: theoretical framework and investigation of biomedical signals, ECG, and coronavirus cases.

Biosignals are nowadays important subjects for scientific researches from both theory, and applications, especially, with the appearance of new pandemics threatening the humanity such as the new coronavirus. One aim in the present work is to prove that wavelets may be a successful machinery to understand such phenomena by applying a step forward extension of wavelets to multi-wavelets. We proposed in a first step to improve multi-wavelet notion by constructing more general families using independent components for multi-scaling and multi-wavelet mother functions.

A new conditional region growing approach for microcalcification delineation in mammograms.

Microcalcifications (MCs) are considered as the first indicator of breast cancer development. Their morphology, in terms of shape and size, is considered as the most important criterion that determines their malignity degrees. Therefore, the accurate delineation of MC is a cornerstone step in their automatic diagnosis process.

Brain multigraph prediction using topology-aware adversarial graph neural network.

Brain graphs (i.e, connectomes) constructed from medical scans such as magnetic resonance imaging (MRI) have become increasingly important tools to characterize the abnormal changes in the human brain. Due to the high acquisition cost and processing time of multimodal MRI, existing deep learning frameworks based on Generative Adversarial Network (GAN) focused on predicting the missing multimodal medical images from a few existing modalities.

Brain graph synthesis by dual adversarial domain alignment and target graph prediction from a source graph.

Developing predictive intelligence in neuroscience for learning how to generate multimodal medical data from a single modality can improve neurological disorder diagnosis with minimal data acquisition resources. Existing deep learning frameworks are mainly tailored for images, which might fail in handling geometric data (e.g.

Brain graph super-resolution for boosting neurological disorder diagnosis using unsupervised multi-topology connectional brain template learning.

Existing graph analysis techniques generally focus on decreasing the dimensionality of graph data (i.e., removing nodes, edges, or both) in diverse predictive learning tasks in pattern recognition, computer vision, and medical data analysis such as dimensionality reduction, filtering and embedding techniques.

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states.

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer's disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, 'shape connections' between brain regions are rarely investigated -e.

Polyphenolic contents, antioxidant activities and UPLC-ESI-MS analysis of Haplophyllum tuberculatum A. Juss leaves extracts.

The aim of this study is to determine the phytochemical profile, the total polyphenolic contents and the antioxidant activities of Haplophyllum tuberculatum leaves extracts. The most active extracts were analyzed by ultra-high performance liquid chromatography coupled to electrospray ionization mass spectrometry. Antioxidant activities were screened by the 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) test and measured by the 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2-azinobis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and β-carotene bleaching inhibition assays.

Biological properties of Hertia cheirifolia L. flower extracts and effect of the nopol on α-glucosidase.

In screening for antioxidant and α-glucosidase inhibitors from the extracts of Hertia cheirifolia L. flowers, the petroleum ether extract showed interesting antioxidant activity and inhibitory effect on the activity of α-glucosidase. The fractionation of this extract resulted in the isolation of a compound which is characterized by NMR and ESI-MS as a nopol.

Antibacterial, antifungal and cytotoxic activities of two flavonoids from Retama raetam flowers.

We have investigated the antibacterial, antifungal and cytotoxic activities of two flavonoids isolated from Retama raetam flowers using the disc diffusion and micro-dilution broth methods. The cytotoxic activity was tested against Hep-2 cells using the MTT assay. The compounds licoflavone C (1) and derrone (2) were active against Pseudomonas aeruginosa and Escherichia coli (7.

Spasmolytic and anti-inflammatory effects of constituents from Hertia cheirifolia.

A sesquiterpenoid Bakkenolide (1), and two steroids, (3beta, 22E)-Stigmasta-5, 22-diène-3-ol (Stigmasterol) (2) and stigmasterol 3beta-glucoside (3), isolated from the Hertia cheirifolia (L.) chloroform extract, were evaluated respectively for their spasmolytic and anti-inflammatory activities. We note that these natural products were isolated and purified for the first time from the specie Hertia cheirifolia.

Mutagenic, antimutagenic and antioxidant activities of a new polyphenolic and a flavonoid substances isolated from Anagallis monelli.

A new polyphenolic natural substance: 2,5-dihydroxy-benzoic acid 3'-formyl-5'-hydroxy-phenyl ester (1), Anamighrinal and 3-(O-alpha-L-rhamnosyl) quercetin (2) have been isolated from the methanolic aerial part extract of the plant Anagallis monelli by chromatographic separation. Their structures have been deduced essentially by one and two NMR spectroscopic procedures and mass spectrometry. Antioxidant, mutagenic, antimutagenic activities, of the natural products were realised and positive results were recorded.

Antimicrobial and cytotoxic activity of Marrubium alysson and Retama raetam grown in Tunisia.

Antibacterial and antifungal activities of extracts obtained from M. alysson, R. raetam were tested using a solid medium technique.

Mutagenic, antimutagenic and antioxidant activities of a new class of beta-glucoside hydroxyhydroquinone from Anagallis monelli growing in Tunisia.

A new skeleton of an O-heteroside natural substance named zinolol, the first representative of a new class of aminated hydroxyhydroquinone, has been isolated from the whole plant Anagallis monelli. Its structure has been established by one and two dimensional NMR spectroscopic procedures. Antioxidant, mutagenic, antimutagenic activities were realised and positive results were recorded.

A new biflavonoid and an isobiflavonoid from Rhus tripartitum.

A new biflavonoid masazinoflavanone (1) and the isobiflavonoid calodenone (2) have been isolated and characterized from the methanolic aerial part extract of the plant Rhus tripartitum. Their structures have been deduced from extensive spectral analysis (NMR and MS). Interpretation of the nuclear overhauser effects (NOESY) permitted us to establish relative stereochemistry of these natural products.