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Résumé : Depuis l'avènement de la pandémie de COVID-19 en 2019, l'Algérie a été confrontée à des défis sans précédent dans le domaine de l'éducation, entraînant la suspension temporaire des activités académiques, y compris la formation des doctorants. Cette situation a contraint les autorités algériennes à repenser les méthodes pédagogiques traditionnelles et à explorer de nouvelles approches pour assurer la continuité de l'apprentissage. Parmi ces approches, l'enseignement à distance hybride a émergé comme une solution viable pour permettre aux doctorants de poursuivre leurs études tout en respectant les mesures sanitaires en vigueur. Cette transition vers le numérique a été nécessaire pour répondre aux besoins des doctorants, en particulier ceux qui résident loin des centres universitaires ou qui ont des contraintes professionnelles. L'objectif de cette étude est d'analyser les implications de cette réforme sur le terrain, en examinant les avantages offerts par l'enseignement hybride ainsi que les défis potentiels associés à cette transition. Cette étude vise à fournir des recommandations pratiques pour améliorer l'efficacité de la formation des doctorants en Algérie dans le contexte de l'enseignement hybride, en identifiant les meilleures pratiques et en proposant des solutions innovantes pour garantir que cette transition vers le numérique réponde aux besoins des étudiants et contribue à l'amélioration de la qualité de l'enseignement supérieur en Algérie. Mots-clés : Réforme – enseignement Hybride – doctorants – e-learning – TICEs.

Summary: Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by a progressive loss of motor neurons. The limited efficacy of recent therapies in clinical development may be linked to lack of drug penetration to the affected motor neurons due to the blood-brain barrier (BBB) and blood-spinal cord barrier (BSCB). Methods: In this work, the safety and efficacy of repeated short transient opening of the BSCB by low intensity pulsed ultrasound (US, sonication) was studied in females of an ALS mouse model (B6.Cg-Tg(SOD1∗G93A)1Gur/J). The BSCB was disrupted using a 1 MHz ultrasound transducer coupled to the spinal cord, with and without injection of insulin-like growth factor 1 (IGF1), a neurotrophic factor that has previously shown efficacy in ALS models. Findings: Results in wild-type (WT) animals demonstrated that the BSCB can be safely disrupted and IGF1 concentrations significantly enhanced after a single session of transient BSCB disruption (176 ± 32 μg/g vs. 0.16 ± 0.008 μg/g, p

Tyll is a novel of the German-Austrian author Daniel Kehlmann that was published in 2017. The author deals through anachronistic as well as heterochronic moments with the medieval figure Tyll and their encounters with other historical and fictional figures in the context of the Thirty Years’ War. With an exciting story as an interplay between the tragedy of historical events and the humor of the mythical figure, Kehlmann succeeds in reconstructing the humorous characteristics of the fictional character Tyll and inscribing the facts of constructed history into his fictional text. In doing so, the character Tyll is ascribed a comic-carnivalesque status. In this way, Kehlmann reconstructs the historical events and thus transcends the boundaries between history and literature or fiction as a cultural-poetic demarcation. Here, the understanding of the reader’s present horizon overlaps with the historical horizon of the text. The present article aims to analyze Kehlmann’s historiographical writing as a textual demarcation and asks to what extent the contextualization of historical facts in Tyll can contribute to drawing cultural-poetic boundaries.

Machine learning (ML) represents one of the main pillars of the current digital era, specifically in modern real-world applications. The Internet of Things (IoT) technology is foundational in developing advanced intelligent systems. The convergence of ML and IoT drives significant advancements across various domains, such as making IoT-based security systems smarter and more efficient. However, ML-based IoT systems are vulnerable to lurking attacks during the training and testing phases. An adversarial attack aims to corrupt the ML model’s functionality by introducing perturbed inputs. Consequently, it can pose significant risks leading to devices’ malfunction, services’ interruption, and personal data misuse. This article examines the severity of adversarial attacks and accentuates the importance of designing secure and robust ML models in the IoT context. A comprehensive classification of adversarial machine learning (AML) is provided. Moreover, a systematic literature review of the latest research trends (from 2020 to 2024) of the intersection of AML and IoT-based security systems is presented. The results revealed the availability of various AML attack techniques, where the Fast Gradient Signed Method (FGSM) is the most employed. Several studies recommend the adversarial training technique to defend against such attacks. Finally, potential open issues and main research directions are highlighted for future consideration and enhancement.

Abstract Hematopoietic stem cells (HSCs) residing in specialized niches in the bone marrow are responsible for the balanced output of multiple short-lived blood cell lineages in steady-state and in response to different challenges. However, feedback mechanisms by which HSCs, through their niches, sense acute losses of specific blood cell lineages remain to be established. While all HSCs replenish platelets, previous studies have shown that a large fraction of HSCs are molecularly primed for the megakaryocyte-platelet lineage and are rapidly recruited into proliferation upon platelet depletion. Platelets normally turnover in an activation-dependent manner, herein mimicked by antibodies inducing platelet activation and depletion. Antibody-mediated platelet activation upregulates expression of Interleukin-1 (IL-1) in platelets, and in bone marrow extracellular fluid in vivo. Genetic experiments demonstrate that rather than IL-1 directly activating HSCs, activation of bone marrow Lepr+ perivascular niche cells expressing IL-1 receptor is critical for the optimal activation of quiescent HSCs upon platelet activation and depletion. These findings identify a feedback mechanism by which activation-induced depletion of a mature blood cell lineage leads to a niche-dependent activation of HSCs to reinstate its homeostasis.

Modern wireless communications advancements and miniaturization components in the field of electronics have led to the development of lower-cost, multi-functional microsensors. A very new useful type of network, called Wireless Sensor Networks (WSNs), has emerged in recent decades, acting as generators and relay data by controlling interesting physical phenomenon. However, some problems need to be improved in their mastery, particularly that of energy conservation. This valuable energy has to be sufficiently available until a WSN reaches its mission. In order to increase WSN lifetime, numerous protocols have been designed to address this problem of power consumption. The pioneer of these protocols was Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and other enhancement variants were subsequently created in this context. In this paper, a new protocol named Area Splitting for Clustering (ASC) that reduces energy consumption and increases network lifetime is proposed. The performance evaluation of ASC has been carried out and showed that it outperforms those of Leach and its variant protocols. [ABSTRACT FROM AUTHOR]