Entrepreneurial Inclination in Morocco: Perspectives on Drivers and Challenges.

Abstract: Entrepreneurship among youth represents a crucial challenge for the economic and social development of Morocco. Despite the initiatives deployed to encourage this dynamism, numerous challenges persist. Understanding these obstacles is of paramount importance to develop effective policies and programs aimed at promoting entrepreneurship among young people and stimulating economic growth. This study aims to identify and understand the main motivations of young entrepreneurs as well as the obstacles they face in Morocco. Our objective is to provide precise data to better understand the determining factors of entrepreneurship and to foster entrepreneurial spirit among young people. The sample consists of 157 young Moroccans with higher education levels. Data were collected using a self-administered questionnaire completed by the participants. For data analysis, we used principal component analysis as well as Cronbach's alpha to evaluate the reliability of items, and descriptive statistics to highlight the main obstacles and motivations. The results reveal that the primary motivation for entrepreneurship is employment, closely followed by the desire for autonomy, then income improvement, and finally the need for creativity. Regarding obstacles, lack of capital tops the list, followed by lack of skills, lack of family support, and finally fear of taking risks.Abstract: Entrepreneurship among youth represents a crucial challenge for the economic and social development of Morocco. Despite the initiatives deployed to encourage this dynamism, numerous challenges persist. Understanding these obstacles is of paramount importance to develop effective policies and programs aimed at promoting entrepreneurship among young people and stimulating economic growth. This study aims to identify and understand the main motivations of young entrepreneurs as well as the obstacles they face in Morocco. Our objective is to provide precise data to better understand the determining factors of entrepreneurship and to foster entrepreneurial spirit among young people. The sample consists of 157 young Moroccans with higher education levels. Data were collected using a self-administered questionnaire completed by the participants. For data analysis, we used principal component analysis as well as Cronbach's alpha to evaluate the reliability of items, and descriptive statistics to highlight the main obstacles and motivations. The results reveal that the primary motivation for entrepreneurship is employment, closely followed by the desire for autonomy, then income improvement, and finally the need for creativity. Regarding obstacles, lack of capital tops the list, followed by lack of skills, lack of family support, and finally fear of taking risks

Human resources practices as a mechanism for improving performance within public institutions and state-owned enterprises in Morocco

In an economic environment marked by rapid change, characterized by factors such as globalization and increasing demands from stakeholders and clients, public institutions and state-owned enterprises have become significant players through their multiple interventions in providing public services to citizens and businesses, in implementing structuring projects for economic and social development, and in promoting investment. This paper aims to examine the correlation between human resource management and employee performance within Moroccan public institutions and state-owned enterprises to understand how these organizations should manage their human capital to enhance their performance. The sample consists of 67 top executives of Moroccan entities operating in various sectors. Data were collected through a self-administered questionnaire completed by the participants. Partial least squares (PLS) was used to estimate structural equation models and analyze causal relationships between variables. SmartPLS 4 software was employed for model analysis. The findings reveal a positive and significant impact of training, selective recruitment, digital transformation, and performance-based compensation on employee performance improvement. The results indicate that the T-values are 3.126, 2.870, 2.178, and 2.406, respectively. Regarding the Q² value, it stands at 0.899, confirming the model’s predictive capability. The GoF coefficient is 0.851, affirming the overall validity of the model. However, it was observed that there is no significant link between job security and performance, as the T-values did not exceed the threshold of 1.64. This study suggests adopting changes in HRM practices to enhance the organizational performance of public institutions and state-owned enterprises

Caractérisation du début de l'atrésie folliculaire et de la hiérarchie des follicules dans l'ovaire de bovin

Le projet de recherche visait à améliorer nos connaissances sur le développement folliculaire par vagues chez le bovin et à mieux comprendre le phénomène de la sélection du follicule dominant. Pour cela, la première partie de nos travaux de recherche était consacrée à caractériser de façon rigoureuse le début de l'atrésie folliculaire. Ainsi, nous avons réalisé une première étude chez les follicules de moyenne (5 a 7,9 mm) et de grande taille ([plus grand ou égal à] 8mm) provenant d'ovaires recueillis à l'abattoir. En effet, parmi les follicules de grande taille, la proportion des follicules ayant un rapport molaire E\sb2/A $>$ 1 subit une chute brutale dès le début de l'atrésie. D'autre part, nous avons effectué une deuxième expérience où nous avons mis les follicules (individuellement) en culture stationnaire pendant une courte durée (4 heures). La relâche d'estradiol-17\bêta dans le milieu d'incubation, est un excellent indicateur du début de l'atrésie pour les deux classes folliculaires. En effet, la relâche in vitro de ce stéroïde subit une chute draconienne dès le début de l'atrésie. Cette baisse est d'environ 50% pour les moyens follicules et 90% pour les gros follicules. La deuxième partie de nos travaux de recherche était consacrée à la caractérisation de la hiérarchie folliculaire au sein de la paire d'ovaires. Enfin, le follicule subordonné (FS) non atrésique de stade I ou III le plus riche en estradiol-17\bêta du liquide folliculaire, et non le plus gros de la paire d'ovaires, relâche significativement près de trois fois plus d'estradiol-17\bêta dans le milieu d'incubation que les autres FS non atrésiques de la cohorte. Ce FS pourrait être le futur follicule dominant (FD ). [[symboles non conformes]] [Résumé abrégé par UMI]

Analytical and experimental study of electrical conductivity in the lithium tantalate nonstoichiometric structure

We have been interested to experimental and analytical studies of ionic conductivity of nonstoichiometric LiTaO3 solid solutions. Theoretical approach combined with lithium and tantalate vacancy models has been performed. A comparative study between the calculated and measured values is presented taking into account the temperature and composition effects on the conductivity.We have been interested to experimental and analytical studies of ionic conductivity of nonstoichiometric LiTaO3 solid solutions. Theoretical approach combined with lithium and tantalate vacancy models has been performed. A comparative study between the calculated and measured values is presented taking into account the temperature and composition effects on the conductivity

Enhancing learner performance prediction on online platforms using machine learning algorithms

E-learning has emerged as a prominent educational method, providing accessible and flexible learning opportunities to students worldwide. This study aims to comprehensively understand and categorize learner performance on e-learning platforms, facilitating timely support and interventions for improved academic outcomes. The proposed model utilizes various classifiers (random forest (RF), neural network (NN), decision tree (DT), support vector machine (SVM), and K-nearest neighbors (KNN)) to predict learner performance and classify students into three groups: fail, pass, and withdrawn. Commencing with an analysis of two distinct learning periods based on days elapsed (≤120 days and another exceeding 220 days), the study evaluates the classifiers’ efficacy in predicting learner performance. NN (82% to 96%) and DT (81%-99.5%) consistently demonstrate robust performance across all metrics. The classifiers exhibit significant performance improvement with increased data size, suggesting the benefits of sustained engagement in the learning platform. The results highlight the importance of selecting suitable algorithms, such as DT, to accurately assess learner performance. This enables educational platforms to proactively identify at-risk students and offer personalized support. Additionally, the study highlights the significance of prolonged platform usage in enhancing learner outcomes. These insights contribute to advancing our understanding of e-learning effectiveness and inform strategies for personalized educational interventions

A novel hybrid model for sentiment analysis in MOOC forums with hybrid word and character-level neural networks

Sentiment analysis is crucial, in the field of natural language processing (NLP). Has applications in different areas. This study focuses on analyzing sentiments in massive open online course (MOOC) forums highlighting its importance in understanding how users interact and shaping educational strategies. The study presents a novel hybrid neural network model specifically tailored for sentiment analysis in MOOC forums. This innovative model combines word level and character level embeddings to handle the linguistic expressions commonly found in this context. The model architecture integrates bidirectional long short-term memory (BiLSTM) layers for word level embeddings and convolutional neural networks (CNNs) for character level embeddings aiming to harness the strengths of both types of embeddings for a view of the linguistic used in MOOC forum posts. Notably this model achieves an accuracy rate of 93.11% showcasing its effectiveness, in sentiment analysis within MOOC forums. This research contributes to sentiment analysis within the context of online education

Objective quality assessment of medical images and videos : review and challenges

Quality assessment is a key element for the evaluation of hardware and software involved inimage and video acquisition, processing, and visualization. In the medical field, user-basedquality assessment is still considered more reliable than objective methods, which allow theimplementation of automated and more efficient solutions. Regardless of increasing researchon this topic in the last decade, defining quality standards for medical content remains a nontrivial task, as the focus should be on the diagnostic value assessed by expert viewers ratherthan the perceived quality from naïve viewers, and objective quality metrics should aim atestimating the first rather than the latter. In this paper, we present a survey of methodologiesused for the objective quality assessment of medical images and videos, dividing them intovisual quality-based and task-based approaches. Visual quality-based methods compute aquality index directly from visual attributes, while task-based methods, being increasinglyexplored, measure the impact of quality impairments on the performance of a specific task. Adiscussion on the limitations of state-of-the-art research on this topic is also provided, alongwith future challenges to be addressed

Infective endocarditis following COVID-19 pneumonia: about two cases

Coronavirus disease 2019 (COVID-19) has emerged as a pandemic and public health crisis across the world. The severity of this situation is escalating in certain populations, particularly when the COVID-19 diagnosis may delay the recognition of more dramatic illnesses such as infective endocarditis, which is a dreaded complication in patients with cardiac disease. We report the case of two patients who presented with infective endocarditis initially mistaken for COVID-19 pneumonia, which was responsible for a delay in diagnosis. We discuss the diagnostic difficulties as well as the management of this complication in the COVID-19 era. As a physician, one must remain alert to this dreaded complication, especially in patients with a cardiac history, in order to prevent it, detect it early, and manage it in time