On the Atkin Polynomials

We identify the Atkin polynomials in terms of associated Jacobi polynomials. Our identificationthen takes advantage of the theory of orthogonal polynomials and their asymptotics to establish many new properties of the Atkin polynomials. This shows that co-recursive polynomials may lead to interesting sets of orthogonal polynomials.Comment: 18 pages. Accepted for publication at the Pacific Journal of Mathematic

MoVAL: Towards a Multi-views/Multi-hierarchy Software Architecture

This paper was published in the 20th LAAS International Science Conference Advanced Research for Better TomorrowIn order to manage software systems' life cycle and complexities, software development communities has recognized the needs to invest in software architectures. Despite numerous research and industrial works established in software engineering domain, there are always many significant limitations in current software architecture approaches, like the lack of relations definition among different architectural components on the one hand, and the lack of multi-hierarchy definition for each architectural component on the other hand. This paper presents MoVAL, a multi-views/multi-hierarchy software architecture which complies with the IEEE recommended practice for architectural description (ISO/IEC/IEEE standard 42010-2011)

Changement climatique, vulnérabilité des systèmes de production agricoles et impact sur la pauvreté au Maroc : Cas du Saïss

La perception de la pauvreté à la vulnérabilité des systèmes de production et le comportement des agriculteurs est en mesure d’enrichir la réflexion sur les indicateurs de mesure de la pauvreté en milieu rural. En fait, les objectifs fondamentaux de ce travail consistent en les questions suivantes: (i) quelles sont les caractéristiques géographiques des systèmes de production dans chaque site étudié? (ii) quels sont les pauvres ruraux vulnérables au changement climatiqueet qui sont affrontés à l’insécurité alimentaire ? et, enfin (iii) quelles sont les caractéristiques de distinction entre les ménages vulnérables et exposés à la pauvreté et ceux qui ne le sont pas dans les trois sites d’étude de la région de Saïss-Meknès ? Il est nécessaire de placer cette analyse dans son contexte national et aussi les tendances nationales et régionales en ce qui concerne la pauvreté compte tenu des documentations et données disponibles sur la région. La hiérarchisation des systèmes de production sur la base de données de structure et de fonctionnement pourra renseigner sur le comportement des agriculteurs, le niveau d’efficience et aussi permettre d’expliquer des phénomènes socioéconomiques comme la pauvreté et l’adaptation ou non au changement climatique. Les trois communautés étudiées ont montré des différences quant à la diversité des systèmes de production, le recours à l’irrigation, le capital humain, le capital financier et le capital foncier. Tous ces éléments sont à la base de différenciation des systèmes de production, des capacités d’adaptation ou de résilience, d’exposition à la pauvreté et à l’insécurité alimentaire. A partir des résultats de l’enquête, les évènements climatiques les plus fréquents dans cette région, sont la sécheresse, la perte de récolte, lestempêtes et les inondations. Ainsi, les agriculteurs ont développé des formes d’adaptation pour faire face aux effets de ces évènements. Dans ce sens, il a été constaté que la majorité des enquêtés (55% à 70%) ont affirmé qu’ils n’ont rien fait devant lesmajeurs chocs climatiques rencontrés. L’analyse de la sécurité alimentaire a montré une tendance à une insécurité alimentaire des trois communes avec une légère vulnérabilité de la commune de Sidi Slimane. Il faut noter que ce constat se confirme par l’estimation des indicateurs d’insécurité alimentaire. Combinés au changement climatique et à la vulnérabilité de l’activité, les ménages de ces trois localités sont exposés à l’insécurité alimentaire et par conséquence à la pauvreté. On ne peut se prononcer àce niveau d’analyse à une exposition à la famine mais on est plus à un niveau d’accessibilité aux aliments d’une manière régulière

Thymoquinone inhibits growth of human medulloblastoma cells by inducing oxidative stress and caspase-dependent apoptosis while suppressing NF-jB signaling and IL-8 expression

Medulloblastoma (MB) is the most common malignant brain tumor of childhood. The transcription factor NF-κB is overexpressed in human MB and is a critical factor for MB tumor growth. NF-κB is known to regulate the expression of interleukin-8 (IL-8), the chemokine that enhances cancer cell growth and resistance to chemotherapy. We have recently shown that thymoquinone (TQ) suppresses growth of hepatocellular carcinoma cells in part by inhibiting NF-κB signaling. Here we sought to extend these studies in MB cells and show that TQ suppresses growth of MB cells in a dose- and time-dependent manner, causes G2M cell cycle arrest, and induces apoptosis. TQ significantly increased generation of reactive oxygen species (ROS), while pretreatment of MB cells with the ROS scavenger N-acetylcysteine (NAC) abrogated TQ-induced cell death and apoptosis, suggesting that TQ-induced cell death and apoptosis are oxidative stress-mediated. TQ inhibitory effects were associated with inhibition of NF-κB and altered expression of its downstream effectors IL-8 and its receptors, the anti-apoptotic Bcl-2, Bcl-xL, X-IAP, and FLIP, as well as the pro-apoptotic TRAIL-R1, caspase-8, caspase-9, Bcl-xS, and cytochrome c. TQ-triggered apoptosis was substantiated by up-regulation of the executioner caspase-3 and caspase-7, as well as cleavage of the death substrate poly(ADP-ribose)polymerase. Interestingly, pretreatment of MB cells with NAC or the pan-caspase inhibitor zVAD-fmk abrogated TQ-induced apoptosis, loss of cyclin B1 and NF-κB activity, suggesting that these TQ-mediated effects are oxidative stress- and caspase-dependent. These findings reveal that TQ induces both extrinsic and intrinsic pathways of apoptosis in MB cells, and suggest its potential usefulness in the treatment of MB

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

Is Metaverse in education a blessing or a curse: a combined content and bibliometric analysis

The Metaverse has been the centre of attraction for educationists for quite some time. This field got renewed interest with the announcement of social media giant Facebook as it rebranding and positioning it as Meta. While several studies conducted literature reviews to summarize the findings related to the Metaverse in general, no study to the best of our knowledge focused on systematically summarizing the finding related to the Metaverse in education. To cover this gap, this study conducts a systematic literature review of the Metaverse in education. It then applies both content and bibliometric analysis to reveal the research trends, focus, and limitations of this research topic. The obtained findings reveal the research gap in lifelogging applications in educational Metaverse. The findings also show that the design of Metaverse in education has evolved over generations, where generation Z is more targeted with artificial intelligence technologies compared to generation X or Y. In terms of learning scenarios, there have been very few studies focusing on mobile learning, hybrid learning, and micro learning. Additionally, no study focused on using the Metaverse in education for students with disabilities. The findings of this study provide a roadmap of future research directions to be taken into consideration and investigated to enhance the adoption of the Metaverse in education worldwide, as well as to enhance the learning and teaching experiences in the Metaverse

Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts

<p>Abstract</p> <p>Background</p> <p>Public health surveillance is the monitoring of data to detect and quantify unusual health events. Monitoring pre-diagnostic data, such as emergency department (ED) patient chief complaints, enables rapid detection of disease outbreaks. There are many sources of variation in such data; statistical methods need to accurately model them as a basis for timely and accurate disease outbreak methods.</p> <p>Methods</p> <p>Our new methods for modeling daily chief complaint counts are based on a seasonal-trend decomposition procedure based on loess (STL) and were developed using data from the 76 EDs of the Indiana surveillance program from 2004 to 2008. Square root counts are decomposed into inter-annual, yearly-seasonal, day-of-the-week, and random-error components. Using this decomposition method, we develop a new synoptic-scale (days to weeks) outbreak detection method and carry out a simulation study to compare detection performance to four well-known methods for nine outbreak scenarios.</p> <p>Result</p> <p>The components of the STL decomposition reveal insights into the variability of the Indiana ED data. Day-of-the-week components tend to peak Sunday or Monday, fall steadily to a minimum Thursday or Friday, and then rise to the peak. Yearly-seasonal components show seasonal influenza, some with bimodal peaks.</p> <p>Some inter-annual components increase slightly due to increasing patient populations. A new outbreak detection method based on the decomposition modeling performs well with 90 days or more of data. Control limits were set empirically so that all methods had a specificity of 97%. STL had the largest sensitivity in all nine outbreak scenarios. The STL method also exhibited a well-behaved false positive rate when run on the data with no outbreaks injected.</p> <p>Conclusion</p> <p>The STL decomposition method for chief complaint counts leads to a rapid and accurate detection method for disease outbreaks, and requires only 90 days of historical data to be put into operation. The visualization tools that accompany the decomposition and outbreak methods provide much insight into patterns in the data, which is useful for surveillance operations.</p