Connecting the dots: a systematic review of corporate social responsibility, information asymmetry, and economic implications

This paper conducts a comprehensive review of the theoretical and empirical connections between Corporate Social Responsibility (CSR), Information Asymmetry (IA), and their economic consequences. It employs a bibliometric analysis on 73 Web of Science manuscripts using VOSviewer1.6.18 software, combining this analysis with a literature review. The results reveal four thematic areas categorized into three clusters: CSR and IA, the impact of CSR and IA on internal risk control and corporate performance, and the broader effects of CSR and IA. The systematic literature review finds a prevailing consensus that CSR can alleviate IA issues, leading to positive economic outcomes like increased stock liquidity, enhanced investment efficiency, and reduced cost of capital. This study's uniqueness lies in its integration of bibliometric analysis and systematic literature review to provide a holistic summary of both theoretical frameworks and the economic implications of the CSR-IA relationship. It offers valuable insights and recommendations for future research in this field

Cost-effectiveness analysis of dapagliflozin in addition to standard therapy in heart failure with reduced ejection fraction: A Qatari healthcare perspective

Background: Dapagliflozin has been shown to reduce the risk of heart failure hospitalization and cardiovascular mortality in patients with heart failure with reduced ejection fraction (HFrEF). 1,2 This work aims to determine the cost-effectiveness of dapagliflozin added to standard therapy versus standard therapy alone in patients with HFrEF, regardless of the presence or absence of type 2 diabetes mellitus (T2DM). Methods: A lifetime Markov model was constructed to compare the health outcomes and costs of dapagliflozin added to standard therapy versus standard therapy alone from a Qatari public healthcare perspective (Figure 1). 2 The cohort is comprised of HFrEF patients with left ventricular ejection fraction (LVEF) ? 40%, and New York Heart Association (NYHA) class II-IV with an average age of 65 years, based on Dapagliflozin and Prevention of Adverse-Outcomes in Heart Failure (DAPA-HF) trial (Table 1). 1,2 The model consisted of three health states: 'stable', 'hospitalization for heart failure', and 'dead'. Clinical inputs were derived from the results of DAPA-HF trial and costs, and utilities were estimated from published sources as well as publicly available sources in Qatar. 3 The main outcome was the incremental cost-effectiveness ratio (ICER) per quality-adjusted life-year gained (QALY). All outcomes and costs were discounted at a rate of 3% annually. Sensitivity analyses were conducted to confirm the robustness of the results. The study was based on published data; therefore ethics approval was not required. Results: Dapagliflozin added to standard care prevented 112 heart failure hospitalization and resulted in an additional cost of QAR 33,890 (USD 9,309). This equated to an ICER of QAR 101,763 (USD 27,951) per QALY gained, below the US willingness-to-pay threshold of USD 150,000 per QALY gained. Sensitivity analyses showed the findings to be robust. Conclusion: Dapagliflozin in addition to standard care appears to be a cost-effective strategy for patients with HFrEF, regardless of the presence or absence of T2DM.qscienc

Willingness to vaccinate against COVID-19 among healthcare workers: an online survey in 10 countries in the eastern Mediterranean region

BACKGROUND: Willingness of healthcare workers to be vaccinated is an important factor to be considered for a successful COVID-19 vaccination programme. This study aims to understand the willingness of health workers to receive a COVID-19 vaccine and its associated concerns across 10 countries in the Eastern Mediterranean Region (EMR). METHOD: A cross-sectional study was conducted in January 2021 among healthcare workers in EMR using an online survey. Data were analyzed using IBM SPSS software package version 20.0. RESULTS: A total of 2806 health workers (physicians, nurses and pharmacists) completed and returned the informed consent along with the questionnaire electronically. More than half of the respondents (58.0%) were willing to receive a COVID-19 vaccine, even if the vaccination is not mandatory for them. On the other hand, 25.7% of respondents were not willing to take COVID-19 vaccine while 16.3 % were undecided. The top three reasons for not willing to be vaccinated were unreliability of COVID-19 vaccine clinical trials (62.0%), fear of the side effects of the vaccine (45.3%), and that COVID-19 vaccine will not give immunity for a long period of time (23.1%). CONCLUSION: Overall, the study revealed suboptimal acceptance of COVID-19 vaccine among the respondents in the EMR. Significant refusal of COVID-19 vaccine among healthcare professionals can reverse hard-won progress in building public trust in vaccination program. The findings suggest the need to develop tailored strategies to address concerns identified in the study in order to ensure optimal vaccine acceptance among healthcare workers in the EMR

Une architecture croisée et sécurisée pour les véhicules connectés

Les réseaux ad hoc de véhicules (VANET), sont déployés pour minimiser le risque d'accidents de la route et améliorer le confort des passagers. Cette thèse traite le problème de l'abandon et du retard des paquets dans les VANET en réduisant le temps d'échange des données et en améliorant le taux de livraison des paquets. Elle traite également la problématique de protection de l’architecture véhiculaire. D’abord, nous proposons une méthode pour éviter la congestion sur le canal de contrôle afin de garantir le transfert en temps réel et la fiabilité des messages de sécurité urgents. En outre, nous utilisons un réseau de neurones pour réduire le temps d'échange des données de sécurité. Deuxièmement, nous proposons deux protocoles de routage basés sur le rapport Signal/Interférence (SIR). Dans les deux protocoles, notre objectif est de maximiser le SIR global entre la source et la destination afin de sélectionner le chemin optimal. Dans le premier protocole, nous évaluons le niveau de SIR, tandis que dans le second, nous utilisons une chaîne de Markov pour prédire le niveau de SIR. Enfin, nous protégeons ces protocoles contre diverses attaques grâce à trois algorithmes anti-attaque. Dans le premier algorithme, nous créons une variable clé-valeur pour détecter la fabrication de l'adresse source au niveau du nœud intermédiaire. Dans le deuxième, nous créons un tampon et le vérifions périodiquement afin d'attraper le nœud malveillant dans le champ de destination. Enfin, le but du dernier algorithme est de découvrir l’attaque au niveau du SIR.Vehicular Ad hoc NETworks, known as VANETs, are deployed to minimize the risk of road accidents as well as to improve passengers comfort. This thesis deals with the problem of dropping and delaying packets in VANETs by reducing the time of exchanging data, improving the packet delivery ratio, as well as securing the vehicular architecture. First, we propose a novel method to avoid the congestion on the control channel in order to guarantee the real time transfer and the reliability of urgent safety messages. In addition, we extend the proposed method by using a neural network with various parameters such as priority of the message, sensitivity of road, type of vehicle and buffer state to reduce the time of exchanging safety data. Second, we propose two routing protocols based on signal to interference ratio (SIR). Our target in both is to maximize the overall SIR between source and destination with the aim to select the optimal path. In the first one, we evaluate the SIR level, while in the second, we use a Markov chain model to predict the SIR level. Finally, we protect these protocols from various attacks through three anti-attack algorithms. In the first algorithm, we create a key-value variable to detect the fabrication of the source address at the intermediate node. In the second one, we create a buffer and check it periodically in order to catch out the malicious node occurring at the destination field. In the last one, we discover the attack at the SIR level

Determination of the cosmological parameters in the framework of the Friedmann-Lemaître model

Un siècle après le modèle d'univers de Friedmann-Lemaître, les observations le confortent avec une constante cosmologique Λ et une composante de matière sombre (noire) sans pression (poussière) et froide dominant celle baryonique, que l'on désigne par modèle ΛCDM. L'accélération de l'expansion de l'Univers confirmée par le diagramme de Hubble des supernovae en 1998 impose une valeur strictement positive à la constante cosmologique. Mes travaux de thèse se focalisent sur l'estimation des valeurs de paramètres cosmologiques du modèle standard en utilisant la technique de corrélation nulle. Cette approche présente l'avantage d'être plus robuste que les techniques usuelles. Ce travail a consisté aussi à modéliser des échantillons de l'événement quasar ainsi que l'événement supernova, une extrapolation adaptée du premier. Ce qui a permis de générer des échantillons conformes aux hypothèses des modèles, afin de valider les approches statistiques. Nous avons exploité les données du Sloan Digital Sky Survey (SDSS) pour les quasars, et celles du SuperNova Legacy Survey (SNLS) et du SDSS-II pour les supernovae. Les inférences statistiques ont conduit à un univers spatialement fermé et une présence de matière noire plus faible. Dans le cadre d'une prochaine application de cette technique, elle sera utilisée pour contraindre les modèles d'énergie noire. De même, l'utilisation des amas de galaxies observées grâce à l'effet de Sunyaev Zel'dovich, servira d'échantillon cosmologique. Une telle étude pourra contribuer à apporter un élément de réponse à la validité du rôle supposé des neutrinos massifs dans la formation des amas dans l'ère primordiale de l'Univers.A century after the Universe model of Friedmann-Lemaître, the observations comfort it with a cosmological constant Λ and a dark matter component without pressure (dust) and cold dominating the baryonic one, which is denoted by ΛCDM model. The acceleration of the expansion of the Universe confirmed by the Hubble diagram of the supernovae in 1998 imposes a strictly positive value on the cosmological constant. My thesis work focuses on the estimation of the cosmological parameters values of the standard model using the null correlation technique. This approach has the advantage of being more robust than the usual techniques. This work deals with modelling samples of the quasar event and the supernova event, which enables us to generate samples in order to validate the statistical approaches. We used data from the Sloan Digital Sky Survey (SDSS) for quasars, and the SuperNova Legacy Survey (SNLS) and SDSS-II for supernovae. The Statistical inferences suggest a Universe spatially Closed and a weaker presence of dark matter than that in the Standard model. Such a statistical analysis can be used to constrain dark energy models. Application of this technique might be useful for analyzing of clusters of galaxies observed through the effect of Sunyaev Zel'dovich, in view of deriving the cosmological model and provide an answer to the question of the contribution of massive neutrinos in the formation of clusters in the primordial era of the Universe

The politics of silence /

Silence has traditionally been analysed in linguistic terms as those moments of non-speech/non-sound interspersed between words and sounds. I will attempt to take this academic reasoning further to deconstruct established notions of silence and incorporate contemporary methods of investigation to arrive at a more viable and dynamic observation of the event. Silence goes beyond this simple dualistic and binary contrast and I believe may reveal itself as negotiator of language, wherein the impossibility of an absolute truth is translated into the imminent. This thesis will be an attempt at a discourse that redefines silence's fleeting site as an impending source for the political as such

Une architecture croisée et sécurisée pour les véhicules connectés

Vehicular Ad hoc NETworks, known as VANETs, are deployed to minimize the risk of road accidents as well as to improve passengers comfort. This thesis deals with the problem of dropping and delaying packets in VANETs by reducing the time of exchanging data, improving the packet delivery ratio, as well as securing the vehicular architecture. First, we propose a novel method to avoid the congestion on the control channel in order to guarantee the real time transfer and the reliability of urgent safety messages. In addition, we extend the proposed method by using a neural network with various parameters such as priority of the message, sensitivity of road, type of vehicle and buffer state to reduce the time of exchanging safety data. Second, we propose two routing protocols based on signal to interference ratio (SIR). Our target in both is to maximize the overall SIR between source and destination with the aim to select the optimal path. In the first one, we evaluate the SIR level, while in the second, we use a Markov chain model to predict the SIR level. Finally, we protect these protocols from various attacks through three anti-attack algorithms. In the first algorithm, we create a key-value variable to detect the fabrication of the source address at the intermediate node. In the second one, we create a buffer and check it periodically in order to catch out the malicious node occurring at the destination field. In the last one, we discover the attack at the SIR level.Les réseaux ad hoc de véhicules (VANET), sont déployés pour minimiser le risque d'accidents de la route et améliorer le confort des passagers. Cette thèse traite le problème de l'abandon et du retard des paquets dans les VANET en réduisant le temps d'échange des données et en améliorant le taux de livraison des paquets. Elle traite également la problématique de protection de l’architecture véhiculaire. D’abord, nous proposons une méthode pour éviter la congestion sur le canal de contrôle afin de garantir le transfert en temps réel et la fiabilité des messages de sécurité urgents. En outre, nous utilisons un réseau de neurones pour réduire le temps d'échange des données de sécurité. Deuxièmement, nous proposons deux protocoles de routage basés sur le rapport Signal/Interférence (SIR). Dans les deux protocoles, notre objectif est de maximiser le SIR global entre la source et la destination afin de sélectionner le chemin optimal. Dans le premier protocole, nous évaluons le niveau de SIR, tandis que dans le second, nous utilisons une chaîne de Markov pour prédire le niveau de SIR. Enfin, nous protégeons ces protocoles contre diverses attaques grâce à trois algorithmes anti-attaque. Dans le premier algorithme, nous créons une variable clé-valeur pour détecter la fabrication de l'adresse source au niveau du nœud intermédiaire. Dans le deuxième, nous créons un tampon et le vérifions périodiquement afin d'attraper le nœud malveillant dans le champ de destination. Enfin, le but du dernier algorithme est de découvrir l’attaque au niveau du SIR