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Making mistakes and receiving feedback are crucial elements of learning. Reading picturebooks with young children can help shape their perceptions of mistakes and model adaptive responses they can emulate, both in the short term and for years to come. This content analysis identified and analyzed the story characteristics of 25 recently published and widely available picturebooks with mistake-related narratives. Findings include frequencies and descriptions of characters, plot, setting, and a host of other story attributes. Overall, messaging in these books was optimistic--emphasizing responsibility, growth, and acceptance--and making mistakes ultimately led to positive outcomes. Such stories are promising resources for the development of growth mindsets in young children. Teachers and caregivers can use these picturebooks to help children develop positive perceptions of mistakes and learn healthy ways to navigate them in their day-to-day lives.

Nadia Al Wachami,1 Karima Boumendil,1 Maryem Arraji,1 Younes Iderdar,1 Yassmine Mourajid,1 Nadia Ghosne,2 Ali Benmoussa,3 Mohamed Khalis,4– 6 Amal Korrida,7,8 Fatima Zahra Laamiri,1 Halima Lajane,2 Mohamed Lahbib Louerdi,9 Saad El Madani,1 Mohamed Chahboune1 1Hassan First University of Settat, Higher Institute of Health Sciences, Laboratory of Sciences and Health Technologies, Settat, 26000, Morocco; 2Higher Institute of Nursing Professions and Health Techniques (ISPITS), Casablanca, Morocco; 3Higher Institute of Nursing Professions and Health Techniques (ISPITS), Meknès, Morocco; 4Mohammed VI Center of Research and Innovation, Rabat, Morocco; 5International School of Public Health, Mohammed VI University of Health Sciences, Casablanca, Morocco; 6Higher Institute of Nursing Professions and Technical Health, Rabat, Morocco; 7Higher Institute of Nursing Professions and Health Techniques (ISPITS), Agadir, Morocco; 8Research Laboratory of Innovation in Health Sciences (LARISS), Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco; 9Provincial Delegation of health, Settat, 26000, MoroccoCorrespondence: Nadia Al Wachami, Hassan First University of Settat, Higher Institute of Health Sciences, Laboratory of Sciences and Health Technologies, Settat, 26000, Morocco, Tel +212622536000, Email n.alwachami@uhp.ac.maBackground: Chronic obstructive pulmonary disease (COPD) is a major public health problem that remains largely under-diagnosed, mainly due to the under-use of spirometry to establish the diagnosis. The aim of this study is to evaluate the effectiveness of the Moroccan Arabic dialect version of the COPD Assessment Test (CAT) in screening for COPD.Methods: This was a cross-sectional study carried out in primary care facilities in Morocco, involving participants aged 40 and over. The performance of CAT in detecting cases of COPD was measured with reference to the results of spirometry, considered to be the gold Standard.Results: A total of 477 participants were included in the study. The prevalence of COPD was 6.7%. Internal consistency of the Moroccan Arabic dialect version of the CAT was high, with a Cronbach’s alpha of 0.89. The total score of the CAT and of each item was significantly higher in subjects with COPD than in those without (P=0.000). Significantly negative correlations were found between CAT total score and FEV1 (r = − 0.33, p=0.000), CAT and FVC (r = − 0.22, p=0.000), CAT and FEV1/FVC ratio (r = − 0.22, p=0.000). The receiver operating characteristic curve showed an area under the curve of 0.93. A CAT score of 10 was the optimal cut-off value for COPD screening, with a sensitivity, specificity, positive predictive value, and negative predictive value of 78.1%, 93.9%, 48.1% and 98.4%, respectively.Conclusion: The results of the present study showed that the CAT could be used as a screening tool for COPD. The use of this tool by healthcare professionals in primary care settings will improve and promote early diagnosis of this chronic disease.Keywords: chronic obstructive pulmonary disease, COPD assessment test, screening, primary care

In industrial mixing processes, impeller design, rotational speed, and mixing conditions play a crucial role in determining process efficiency, product quality, and energy consumption. Optimizing the performance of stirring systems for non-Newtonian fluids is essential for achieving better results. This study examines the hydrodynamic and thermal performance of stirring systems for viscoplastic fluids, utilizing close-clearance anchor impellers with chamfered angles of 22.5°, 45°, and 67.5° in cylindrical, flat-bottom and unbaffled vessels. Through a comprehensive comparative analysis between standard and chamfered impeller designs, the study evaluates their efficacy in overcoming yield stress, enhancing flow dynamics, and improving thermal homogeneity. The effects of Reynolds number and yield stress on the hydrodynamic and thermal states are analyzed. The results indicate that the 67.5° chamfered impeller significantly improves flow distribution and minimizes dead zones, particularly in critical areas between the anchor blades and vessel walls, where mixing stagnation typically occurs. It also enhances vertical mixing by promoting a broader shear spread along the vessel height and a more uniform temperature distribution. These insights contribute to the development of more efficient agitation systems, applicable across various industries handling complex fluids.

Recent financial crises have highlighted the utmost importance of implementing risk management practices, as exemplified by the profound repercussions of the COVID-19 pandemic. Moreover, we witnessed the rise of various initiatives within the medical sector, specifically in the fields of biomedicine, hospitals, and pharmaceuticals, across Africa, with a notable emphasis on Morocco. The government in Morocco has implemented measures to foster investment and encourage participation from companies and stakeholders. Taking into account an indeterminate and volatile future, it becomes imperative for organizations to establish robust risk management strategies to navigate successfully through these uncertainties. This research paper concentrates on the convergence of complexity, project categorization, and risks. We propose a novel approach to the implementation of the Risk Management Process, utilizing the Enterprise Risk Management framework. By establishing Risk Management rules within the context of a “complex” project, we observed enhanced performance and improved risk management through the holistic consideration of interdependencies rather than treating them as separate entities. Additionally, to substantiate this interdependency, we conducted a comparative analysis of the project's risk and complexity between 2020 and 2022.

This paper presents a comprehensive review of machine learning (ML) and deep learning (DL) models used for demand forecasting in supply chain management. By analyzing 119 papers from the Scopus database covering the period from 2015 to 2024, this study provides both macro- and micro-level insights into the effectiveness of AI-based methodologies. The macro-level analysis illustrates the overall trajectory and trends in ML and DL applications, while the micro-level analysis explores the specific distinctions and advantages of these models. This review aims to serve as a valuable resource for improving demand forecasting in supply chain management using ML and DL techniques.

Technological advancements have continued to progress in all fields, achieving remarkable feats. Additionally, productivity is increasing across the board as a result of strong economic expansion, which has encouraged changes in people’s way of life, such as the increasing use of pharmaceutical products, cosmetics, detergents, and food products. A hydrothermal study is required in these areas to optimize the design of the stirring system. The aim of the current work is to investigate the hydrodynamics and thermodynamics of a mechanical agitation system with a non-Newtonian fluid of the Bingham–Bercovier type in a cylindrical vessel with three blade configurations. Our research is specifically directed towards mechanically agitated systems utilizing close clearance stirrers, particularly focusing on the anchor, gate and two-bladed impellers, within cylindrical tanks that possess flat bottoms without baffles. The results show that the anchor impeller, with its broad blades and low-shear characteristics, is more suited for breaking down yield stress and inducing flow in these fluids, which creates a wide flow pattern that effectively overcomes yield stress. However, the addition of vertical arms to transform it into a gate impeller promotes mixing, heat transfer and thermal efficiency with a small energy cost compared to an anchor impeller against the two-bladed impeller.

This paper presents an optimization approach for supply chain management that incorporates goal programming (GP), dependent chance constraints (DCC), and the hunger games search algorithm (HGSA). The model acknowledges uncertainty by embedding uncertain parameters that promote resilience and efficiency. It focuses on minimizing costs while maximizing on-time deliveries and optimizing key decision variables such as production setups, quantities, inventory levels, and backorders. Extensive simulations and numerical results confirm the model’s effectiveness in providing robust solutions to dynamically changing supply chain problems when compared to conventional models. However, the integrated model introduces substantial computational complexity, which may pose challenges in large-scale real-world applications. Additionally, the model’s reliance on precise probabilistic and fuzzy parameters may limit its applicability in environments with insufficient or imprecise data. Despite these limitations, the proposed approach has the potential to significantly enhance supply chain resilience and efficiency, offering valuable insights for both academia and industry.

Blockchain technology is expected to have a radical impact on most industries by boosting security, transparency, and efficiency. This work considers the potential benefits of blockchain-focused applications in industrial process monitoring. The research design facilitates a detailed bibliometric analysis and delivers insights into the intellectual structure of blockchain technology’s application in industry via scientometric approaches. The work also approaches numerous sources in various industrial sectors to identify the transformative role of blockchain in industrial processes. Aspects such as blockchain technology’s impact on industrial processes’ transparency are discussed, while the paper does not ignore that success stories in applying blockchain to industrial sectors are often exaggerated due to a highly competitive environment that the cryptocurrency domain has become. Finally, the work presents major research avenues and decision-making areas that should be tackled to maximize the disruptive potential of blockchain and create a secure, transparent, and inclusive future.

This research aims to assess faculty members' attitudes at Djelfa University's Faculty of Economic Sciences in Algeria toward organizational trust's influence on improving organizational citizenship behaviors. Moreover, the research used a descriptive approach and case study methodology to achieve this goal. Furthermore, the research included a sample of 98 permanent professors. The results indicated that faculty members had a medium level of perception regarding organizational trust and citizenship behaviors. The research also demonstrated that trust in an organization's management significantly and positively promotes organizational citizenship behaviors within the studied college. In contrast, neither trust in co-workers nor direct supervisors affect organizational citizenship behaviors among faculty members.

The objective of this study is to investigate the planting density, nitrogen and potassium influencing on the pod characteristics of bean. The experiment is made in a Split Randomized Complete Block Design, replicated three times. Two plant densities and seven doses of nitrogen and potassium fertilizers were examined. The results reflected that density had no effect on pod attributes, except pod length in the second season, whereas significantly increased by the lower density. The plant received lower nitrogen lacking potassium increased length in the both seasons however, the higher individual potassium dose and control increased length in first and second seasons, respectively. The widest and narrowest pod diameters shown by the lower dose of nitrogen and higher dose of both fertilizers, subsequently. The separately maximum and minimum dose of potassium in the first and second season subsequently, in addition to the individual lower dose of nitrogen in the second season have a heaviest dry weight. The interaction significantly affected overall parameters, except pod diameter and dry matter in the first season. Pod dry matter is commonly constant, except with the higher density received the greatest dose of both fertilizers, whereas record significant decline. Pod length and diameter are good indicator of quality, it can be given by the lower density and lower dose of nitrogen without potassium. The combination between lower density with higher potassium dose or neutral dose of both fertilizers is a preferable for length while, the higher density with both doses of potassium or with lower nitrogen, is an appropriate for diameter. The best treatment for both, dry weight and dry matter are wobbly.