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Abstract Analgesia and sedation are often provided during mechanical ventilation in extremely preterm neonates. Opioids and benzodiazepines are the most frequently used agents but can have adverse effects. Dexmedetomidine, an alpha‐2 agonist, might be interesting to spare opioid and benzodiazepine use. The objective of this study was to describe a cohort of mechanically ventilated extremely, preterm infants treated with morphine with or without dexmedetomidine. This was a retrospective, observational, single‐center study in the neonatal intensive care unit of Creteil. We included preterm neonates born before 28 weeks of gestation and/or weighting less than 1000 g hospitalized between July 2017 and June 2020, on mechanical ventilation for at least 72 h and who received morphine with or without dexmedetomidine as a second‐ or third‐line treatment. We described morphine and midazolam exposure, respiratory, and digestive outcomes for patients who received dexmedetomidine and those who did not. Twenty nine preterm infants received morphine and dexmedetomidine, and 44 received morphine without dexmedetomidine. Dexmedetomidine was used in patients of 25.7 [25.1–26.7] weeks, 680 [600–750] g and significantly more often in patients with vascular complications during pregnancy (p = 0.008), intrauterine growth restriction (p = 0.01) and in patients who received higher cumulative doses of morphine (p = 0.01). Morphine and midazolam doses tended to decrease after the introduction of dexmedetomidine. Dexmedetomidine was never discontinued because of side effects. In this study, dexmedetomidine, used as a second or third‐line treatment during mechanical ventilation, was associated with a decrease in morphine and midazolam doses after introduction. Dexmedetomidine was used in a specific population of extremely preterm infants, with severe respiratory disease, who required prolonged mechanical ventilation and high morphine doses. This study highlights the need for pharmacokinetic/pharmacodynamic studies in this population, followed by randomized controlled trials and studies on the long‐term effects of dexmedetomidine to determine its place in analgosedation of ventilated preterm infants.

Résumé : La situation linguistique et culturelle en Algérie est à la fois riche et complexe. L'Algérie est marquée par ses différentes langues et cultures à travers son histoire. Elle est considérée ainsi comme un pays plurilingue et pluriculturel. Cette pluralité est due au contact des langues au sein de la société, des foyers et même à l'école, cela engendre d'autres questions sur l'identité, la diversité et les conflits linguistiques. Pour autant, ces questions sont au cœur des recherches sur le plurilinguisme et l'interculturalisme au sein de la société Algérienne. Mots-clés: Plurilinguisme; Interculturalisme; Identité; Langues ; Cultures.

Furfural is potentially produced from lignocellulose waste of biorefinery processes and is widely used as a value-added in various chemical industries. However, the purification of furfural should be conducted to obtain high purity. This work aims to synthesize, design, and optimize the furfural production using some alternative distillation processes by simulation using Super Pro and ASPEN software. The pretreatment process of producing crude furfural from empty fruit bunch waste is also evaluated. The production cost of $0.23/kg of crude furfural (5 %) was obtained in the preliminary process. In the purification process, the sequenced distillation process was less prospective than the extractive distillation based on the simulation basis and economic evaluation. The extractive distillation using n‑butyl chloride performed better than toluene and benzene as the furfural recovery, and the purity was 98.60 % and 99.94 %, respectively. The payback period (PBP), internal rate return (IRR), and net present value (NPV) also indicated the great performance of the extractive distillation process with values of 1.24 years, 36.04 %, and $14,591,500, respectively. Therefore, the simulation, design, and economic evaluation presented promising results that are feasible for plant establishment.

The production of food-grade salt from crude solar salt has been examined through a techno-economic evaluation. This study aimed to investigate a salt factory to analyze its technical and economic aspects to determine the precise parameters for improving the quality of food-grade salt. The primary process of this factory involves grinding, washing, draining, drying, and fortification, supported by equipment like brine management, conveyors, sieves, and packaging. The proposed salt plant, designed for a 3-ton daily output over 15 years, requires 30 months for construction and a 4-month startup. The total capital outlay is USD 1,921,000, with USD 310,000 for technology and equipment. Economic indicators, including a Net Present Value (NPV) of USD 7,862,000, an Internal Rate of Return (IRR) of 46.48%, payback in 1.56 years, and a Return on Investment (ROI) of 64.28%, demonstrate feasibility. Establishing a salt plant in Indonesia supports food-grade salt production, stabilizes solar salt prices and enhances the welfare of traditional salt farmers. Ultimately, the results of this study can provide valuable insights for evaluating the feasibility of establishing a food-grade salt production plant in Indonesia.

Abstract In order to enhance the tribological and corrosion properties of AISI 316 substrate, rf plasma carbonitriding was involved to form a carbonitrided layer on AISI 316 base substrate. The deposition of TiN top layer was executed engaging titanium nitride target in argon plasma atmosphere. All the deposition working parameters were reserved to be constant excepting the deposition period that was altered from 4 to 20 min. The effect of TiN top layer thickness on the structure, tribological and electrochemical characteristics of TiN@AISI 316 CN duplex treatment was explored. It was demonstrated, that the duplex coating enhanced the hardness (max: 1740 HV0.025 for TiN (1325nm)@AISI 316 CN sample) and improved the wear and corrosion resistance. Besides, the coefficient of friction is reduced to 0.12–0.2 for TiN@AISI 316 CN duplex treated samples compared with untreated AISI 316 which recorded a value of 0.47.

Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the learner's preferences. We propose to address the issue of student's dissatisfaction and lack of interaction, by integrating learning style theory into the analysis of the learner's online behavior. Our work differentiates itself from the rest of researches that employed learning style theory by its two step process. First, we classify the learning activities into learning categories based on learning style theory. Second, we define behavioral features that quantify the learner's behavior across the learning categories. The analysis of the learner's online behavior based on the behavioral features revealed new aspects of the learner's preferences. We consider these findings to be best useful for developing learning style-sensitive adaptive learning environments. Nevertheless, the behavioral features could be beneficial in different contexts. In fact, when applied to course outcome prediction, the behavioral features enhanced the results by 10%. The latter indicates that behavioral features reflected the correlation between behavior and academic performance.

Résumé : La psycholinguistique est une discipline qui étudie la relation entre les phénomènes linguistiques et les processus psychologiques lors des activités de la perception, la compréhension et la production du langage. Cette discipline s'intéresse également aux processus liés à l'acquisition/apprentissage de sa langue maternelle et par la suite, des langues étrangères. Elle fait appel à plusieurs disciplines telles que : la psychologie et les sciences cognitives. Elle s'intéresse également à d'autres domaines comme la sémantique afin de donner sens à ses propos, de bien communiquer avec autrui, de comprendre et se faire comprendre. Mots-clés : la psycholinguistique, l'acquisition/apprentissage de(s) langue(s), processus psychologiques, compréhension et production du langage, phénomènes linguistiques.

The burgeoning food waste problem is driving environmental pollution and climate change due to landfilling of waste. It is imperative to reduce greenhouse gas emissions and lower carbon footprint through food waste management. In the culinary setting, a vast amount of food waste is generated from food preparation. However, there is no module to educate staff on this. In this study, a culinary waste management (CWM) module was introduced to train culinary arts students to reduce culinary waste in the food preparation process, from cleaning to assembling. It is essential to assess the user-friendliness of the module during practical implementation. This study aimed to explore participants’ awareness and understanding of CWM before and after implementing of a CWM module in teaching kitchens and identify the motivators and barriers to its implementation. A total of 35 participants, consisting of students, teaching chefs and cleaning staff’s were recruited at Sunway University, Malaysia. Themes derived in the pre-module interview revealed a varying degree of engagement among participants, with low literacy, alongside barriers like labor-intensiveness and concern over hygiene. The post-module interview highlighted positive psychological and cognitive impacts on participants with motivators that drive them to practice CWM. Nevertheless, barriers such as resistance to novelty impeded the implementation. Therefore, CWM is the way forward to reduce the significant amount of waste generated in culinary settings. Integrating this CWM module into the education-industrial system will equip future culinary professionals with the knowledge and skills needed for.g a sustainable culinary career.

This study delves into the intricate electronic and photophysical properties of copper (II) complexes and their ligands, shedding light on their behavior under varying conditions. UV–Vis absorption spectroscopy unveils significant insights, revealing absorption peaks attributed to ligand–metal charge transfer transitions (LMCT) and π → π* transitions of C = N bonds. The solvent’s polarity dictates the absorption peak positions, indicating a pronounced solvatochromic effect. Molar extinction coefficients underscore the complexes’ high absorption efficiency across different solvents. Density Functional Theory (DFT) calculations provide a theoretical framework, elucidating electronic transitions observed experimentally. While HL1 exhibits a single peak, HL2 displays two peaks, findings supported by calculated transition energies and oscillator strengths.Moreover, the oxidation processes of copper complexes with iodide salt and triethylamine unveil favorable electron transfer mechanisms, as corroborated by cyclic voltammograms and free energy change values. Photolysis experiments underpin the complexes’ behavior under light irradiation, revealing reversible photoreduction processes and the formation of novel photoproducts. Notably, the addition of triethylamine influences photolysis kinetics, elucidating complex interactions. Furthermore, fluorescence experiments unveil the fluorescent behavior of bidentate copper (II) complexes and their ligands. Fluorescence emission peaks, observed around 475–550 nm for complexes and 400–550 nm for ligands, are influenced by solvent polarity, indicating solvent effects on fluorescence deactivation pathways. Overall, this comprehensive investigation provides valuable insights into the electronic and photophysical characteristics of copper (II) complexes, paving the way for their potential applications in diverse fields, including materials science, catalysis, and photochemistry.

Objectives: This study examines the potential of International Medical Graduates (IMG) in contributing to the health and wellness of a community, particularly through transdisciplinary knowledge engagement or mobilization in diverse settings. We aimed to gather IMGs’ perspectives on potential non-physician roles to enhance community health and wellness using a qualitative descriptive approach. Methods: Eight focus groups were conducted among IMGs in Canada between June and August 2020 (n = 42), followed by a thematic analysis of the verbatim transcripts. Two independent reviewers carried out inductive coding of the data. Emergent themes and sub-themes were identified. Through an iterative process incorporating insights from community partners, themes were refined to capture the lived experiences of IMGs in this context. Results: We sought to engage this population in discussions to capture their perspectives on contributions to health and wellness. Participants suggested various alternative contribution pathways such as knowledge mobilization, research generation, and supportive community roles. They also identified individual and systemic challenges. Finally, strategies for change were proposed on personal, professional, and organizational levels. Conclusion: The IMGs put forward various ideas and insights regarding their potential contributions to community health and wellness. They can be valuable assets in promoting health and improving health literacy. It is important to recognize that IMGs are eager to take on significant roles in the community and that they are currently an underused resource for enhancing community health and wellness.

This paper presents a new optimization technique based on the hybridization of two meta-heuristic methods, Jellyfish Search (JS) and Moth Flame Optimizer (MFO), to solve the Optimal Power Flow (OPF) problem. The JS algorithm offers good exploration capacity but lacks performance in its exploitation mechanism. To improve its efficiency, we combined it with the Moth Flame Optimizer, which has proven its ability to exploit good solutions in the search area. This hybrid algorithm combines the advantages of both algorithms. The performance and precision of the hybrid optimization approach (JS-MFO) were investigated by minimizing well-known mathematical benchmark functions and by solving the complex OPF problem. The OPF problem was solved by optimizing non-convex objective functions such as total fuel cost, total active transmission losses, total gas emission, total voltage deviation, and the voltage stability index. Two test systems, the IEEE 30-bus network and the Mauritanian RIM 27-bus transmission network, were considered for implementing the JS-MFO approach. Experimental tests of the JS, MFO, and JS-MFO algorithms on eight well-known benchmark functions, the IEEE 30-bus, and the Mauritanian RIM 27-bus system were conducted. For the IEEE 30-bus test system, the proposed hybrid approach provides a percent cost saving of 11.4028%, a percent gas emission reduction of 14.38%, and a percent loss saving of 50.60% with respect to the base case. For the RIM 27-bus system, JS-MFO achieved a loss percent saving of 50.67% and percent voltage reduction of 62.44% with reference to the base case. The simulation results using JS-MFO and obtained with the MATLAB 2009b software were compared with those of JS, MFO, and other well-known meta-heuristics cited in the literature. The comparison report proves the superiority of the JS-MFO method over JS, MFO, and other competing meta-heuristics in solving difficult OPF problems.

Food waste around the world has emerged as a pressing issue that calls for attention and intervention. Analysing the food waste problem without understanding wasteful behaviour antecedents may oversimplify this multi-faceted issue, which will then compromise the development of interventions. This paper provides an overview of the theoretical approaches to food waste behaviour antecedents, followed by evidence-based interventions, using the Theory of Planned Behaviour (TPB), the Norm Activation Model (NAM), and the Social Practice Theory (SPT). These theories encompass the psychological, behavioural, societal, material, and structural factors that influence food waste practices. Our aim is to provide a holistic understanding on the antecedents of food waste behaviours and theory-based interventions.

Due to the industrial revolution the emission of CO2 in the air reached to a noticeable degree (∼ 419.51 ppm) and continuous increase leading to effects effect adversely in the global climate. The utilization of captured CO2 through its electrochemical reduction into valuable fuels or chemicals has emerged as a promising technology to address climate change. Thus, among the various approaches electrochemical CO2 reduction is being progressively implemented for the conversion of CO2 into valuable fuels or chemicals. Unfortunately, the current state-of-the-art of such processes is lacking with respect to performance targets for scaling-up these technologies to industrial levels such as high current density (>200 mA/cm2) as well as stability for ∼30000 hours. Unluckily, in most of reported research these criteria found much lower. Distinctive properties of the electrocatalyst materials determine the selective, effective, and stable electrocatalysts of CO2 reduction to industrial scale. The gap between the reported and targeted performance stems from the available electrocatalyst materials that dictate the selectivity, efficiency, and stability of the electrochemical reduction of CO2. In this review, we summarize recent progress made on the modification of low dimensional (LD) nanomaterials and their nanohybrids for the electrochemical reduction of CO2. Particular focus is placed on highlighting common challenges faced by these electrocatalysts, spanning recent advances on modified LD nanomaterials of CNTs, Graphene and MXenes. We further highlight areas that require additional attention in order for such catalyst materials to meet the required targets to enable the scale-up of CO2 electroreduction to the industrial scale.

This work is a case study intended to explore the capability of three forecasting techniques to predict emergency department (ED) visits based on Major Diagnostic Categories. It is a part of a larger work aimed to improve ED patients’ throughput time. The ED in this case is considered as a part of the health chain and the process of arrival and departure of patients are included. The prediction models presented in this work are initially established and validated from the historical 3-year emergency room visits at Sherbrook University Hospitals and uses the week as the period unit. Given that resources are consumed differently for each disease, a group of patients has been considered according to the major diagnostic categories (MDC). Three predictive models of the number of visits are considered and compared: linear regression model, SARIMA and multivariate SARIMA. The accuracy of the prediction models is evaluated by calculating the mean percentage error (MAPE) and the mean absolute error (MAE) between forecast and observed data. The medium term forecasting model for the number of admissions is determined according to the estimated admission ratio for each patient group, while the short term model is established according to a regression model based on age groups. SARIMAX offers the most accurate model with a MAPE ranging from 6% to 49% (group of a small number of visits). Twelve of the twenty-seven groups of patients account for nearly 90% of the total of emergency room visits and the weighted mean average percentage error (WMAPE) stands at 8%. The admission rates for each group of patients is based on Gauss’ distribution and is different from one group to another. For many MDCs, strong correlations can be demonstrated between the admission rates and the patient age groups by using a quadratic regression. The prediction models explored in this paper aims to help managers to plan more efficiently the emergency department resources. The models can also be used to plan resources of other hospital departments since they give information about the number of admitted patients for each MDC.

The aim of this study was to evaluate the use of horse and donkey meat in the production of kaddid—a traditional dish typically not made with these meats—from a physical and chemical perspective. The results showed that both meats exhibit similar water retention during cooking, contributing to comparable tenderness and juiciness, with no significant differences in pH values, indicating similar quality (p > 0.05). However, their amino acid profiles differ: horse meat contains lower levels of glutamate (p < 0.05), methionine (p < 0.01), isoleucine (p < 0.05), and leucine (p < 0.05), but higher levels of proline (p < 0.05), histidine (p < 0.01), and lysine (p < 0.001) compared to donkey meat. Both meats provide essential amino acids. Horse meat is richer in saturated and monounsaturated fatty acids (32.44% and 39.58%, respectively), while donkey meat has a higher content of polyunsaturated fatty acids (31.51%), with a more favorable PUFA/SFA ratio, suggesting better cardiovascular health benefits. In terms of dried meat, donkey kaddid has a higher protein (17.45 g/100 g) and lower fat content (2.1 g/100 g) compared to horse kaddid (16.7 g/100 g, and 3.5 g/100 g, respectively) (p < 0.05). These findings inform consumer choices and production practices, promoting the use of horse and donkey meat for kaddid production.