Continuous Process Research Articles

How higher education teachers see their professional identity

An important dimension to understand the student learning process is the professional identity of teachers, which is conceptualized as a continuous process of construction and reconstruction. In this process, teachers define and assume their roles in a specific educational context that is characterized by tensions, adjustments, and transformations. This study focuses on understanding the professional identity of higher education teachers, a field characterized by constant evolution and demands. The personal characteristics of this identity are explored, including experiences and biographical representations, as well as its interrelationship with the institutional environment. Using a qualitative interpretive approach, six teachers recognized for their pedagogical innovation and educational commitment were interviewed. The results reveal outstanding motivation and responsibility in educational work, but also tensions between personal identity and the work context, reflected in the perception of low recognition and the importance of institutional leadership. The teachers show a critical and reflective view of their work, influenced by childhood experiences that impact their conceptions of educational justice and equity. To conclude, the common characteristics of professional identity in higher education highlight the need to integrate them into professional development. The article advocates for the design of more personalized training programs and the promotion of continuous learning among peers as key elements to strengthen this identity and improve pedagogical practice.

Optimization Study on Hardness of Cold Rolled Strip Steel Based on a Data-Driven Approach

As a key index to measure product quality and processability, the hardness of cold-rolled strip steel has an important influence on the production efficiency of iron and steel enterprises. However, due to the coupling between the process parameters at each stage of the continuous annealing process, and the setting of traditional process parameters depending on the experience of the operator, the lack of scientific and systematic optimization methods, which easily leads to the problem of high hardness fluctuation and low resource utilization. In this study, the data-driven method is used to conduct a preliminary correlation analysis to further clarify the optimal combination of process parameters for achieving the target hardness. The Pearson correlation coefficient is used to determine that carbon content, quenching furnace temperature, and strip speed significantly affect strip hardness. To further clarify the optimal combination of process parameters to achieve the target hardness, a Genetic Algorithm (GA) was tried in this study. The results show that the optimized process parameter combination can effectively improve the stability and consistency of strip hardness, and provide a scientific basis for the process parameter setting in the cold rolled strip production process, which is helpful for enterprises to improve product quality, reduce cost, and enhance market competitiveness.

Generalized Itô’s lemma and the stochastic thermodynamics of diffusion with resetting

Abstract Methods from the theory of stochastic processes are increasingly being used to extend classical thermodynamics to mesoscopic non-equilibrium systems. One characteristic feature of these systems is that averaging the stochastic entropy with respect to an ensemble of stochastic trajectories leads to a second law of thermodynamics that quantifies the degree of departure from thermodynamic equilibrium. A well known mechanism for maintaining a diffusing particle out of thermodynamic equilibrium is stochastic resetting. In its simplest form, the position of the particle instantaneously resets to a fixed position x 0 at a sequence of times generated from a Poisson process of constant rate r. Within the context of stochastic thermodynamics, instantaneous resetting to a single point is a unidirectional process that has no time-reversed equivalent. Hence, the average rate of entropy production calculated using the Gibbs–Shannon entropy cannot be related to the degree of time-reversal symmetry breaking. The problem of unidirectionality can be avoided by considering resetting to a random position or diffusion in an intermittent confining potential. In this paper we show how stochastic entropy production along sample paths of diffusion processes with resetting can be analyzed in terms of extensions of Itô’s formula for stochastic differential equations (SDEs) that include both continuous and discrete processes. First, we use the stochastic calculus of jump-diffusion processes to calculate the rate of stochastic entropy production for instantaneous resetting, and show how previous results are recovered upon averaging over sample trajectories. Second, we formulate single-particle diffusion in a switching potential as a hybrid SDE and develop a hybrid extension of Itô’s stochastic calculus to derive a general expression for the rate of stochastic entropy production. We illustrate the theory by considering overdamped Brownian motion in an intermittent harmonic potential. Finally, we calculate the average rate of entropy production for a population of non-interacting Brownian particles moving in a common switching potential. In particular, we show that the latter induces statistical correlations between the particles, which means that the total entropy is not given by the sum of the 1-particle entropies.

Comparative Evaluation of Methane Yield from Continuous and Batch Fermentative Processing of Selected Agrowaste

This study investigated the influence of different agrowaste compositions on methane yield in batch and continuous operational modes, highlighting the significance of substrate characteristics in determining the efficiency of methane production. It comparatively assessed the methane yield derived from continuous and batch fermentative processing of the following agrowaste; Cassava peels (A), Maize husks (B), Pig Slurry (C), and composite (D) that represents the co-digestion of the aforementioned A, B & C. Eight digesters were used in all, two anaerobic systems for each substrate, [I.e one operating in a batch mode (1) and the other in a continuous mode (2)]. The proximate properties of the substrates were determined and gas production rates were monitored over the experimental period of 45 days. Gas analysis of the generated gas revealed mainly methane and CO2, with concomitant organic compounds like; Ethanol, Methanol, Acetic Acid, Acetone, etc. Minute quantities of Phenol and Lactic Acid were mainly found in the gas generated from Cassava peels. The average percentage value of Co-digested substrates (D) yielded higher gas volume of 78.263±4.54, followed by C (74.263±4.65), B (70.240±4.38), and A (56.090±3.50). The results also revealed that the continuous fermentative process demonstrated a more stable and consistent methane production rate compared to the batch system, attributed to its steady-state operational mode and continuous substrate feed input. However, modeled graphical results showed that batch fermentation system produced higher gas yield (for all the substrates) between days 29-39 before it recorded a sharp decline curve, attributed to the reduction in substrate availability.

Evaluation of Integrated Anaerobic/Aerobic Conditions for Treating Dye-Rich Synthetic and Real Textile Wastewater Using a Soda Lake Derived Alkaliphilic Microbial Consortia

Textile industry wastewater (WW) has intense color, high chemical oxygen demand (COD), pH, and salinity, making it challenging for conventional treatment. Soda lakes, with high alkalinity and salinity, host diverse microbes capable of textile dye degradation. This study evaluated anaerobic/aerobic reactors using alkaliphilic microbial consortia from Lake Chitu, an Ethiopian soda lake, for treating synthetic and real textile WW. The experimental setup consisted of a first-stage anaerobic reactor followed by a second-stage aerobic reactor, operating continuously with a predetermined flow rate and hydraulic residence time. After evaluating synthetic WW, real textile WW was collected in two batches (rounds I and II). The treatment setup removed 99% of the dye color for synthetic WW, 98% for round I, and 96% for round II. COD removal was 87% for synthetic WW, 86% for round I, and 93.37% for round II. TKN removal reached 90% for synthetic WW, 91% for round I, and 96% for round II at a steady state. Residual COD and TKN values met the final effluent discharge standards. GC–MS and IR analyses revealed that dyes were broken down into intermediate organic compounds under anaerobic conditions and further degraded into smaller molecules under aerobic conditions. This integrated reactor approach effectively removes dyes and enhances COD and TKN removal. The study’s novelty lies in evaluating both synthetic and real textile WW using integrated reactors under alkaline conditions in a continuous process, inoculating alkaliphilic consortia, without pre-enrichment or external nutrient addition to real WW. The study provides insights into the effectiveness of alkaliphilic microbial consortia derived from soda lakes for treating textile WW using integrated reactor conditions. Reactor microbiome characterization is needed to further explore microbial diversity and community structure.

Successful Aging and Preventative Health: A Business Owner's Perspective

Successful aging can be viewed as a continuous and ongoing holistic process or as a goal-oriented approach. Both views provide sufficient exploration and definition toward development continuing through adulthood into the latter. However, the investigation of successful aging and how its definition can become affected by technological-based health innovation is an under-researched topic. Using literature and qualitative interview findings, successful aging may be considered to also incorporate the use of health-related innovation assets under the umbrella of preventative health, which contributes as an important factor toward how older individuals perceive the success of themselves and the various areas of their life as they continue to develop in late adulthood.

Highly efficient synthesis of the chiral ACE inhibitor intermediate (R)-2-hydroxy-4-phenylbutyrate ethyl ester via engineered bi-enzyme coupled systems

(R)-2-Hydroxy-4-phenylbutyric acid ethyl ester ((R)-HPBE) is an essential chiral intermediate in the synthesis of angiotensin-converting enzyme (ACE) inhibitors. Its production involves the highly selective asymmetric reduction of ethyl 2-oxo-4-phenylbutyrate (OPBE), catalyzed by carbonyl reductase (CpCR), with efficient cofactor regeneration playing a crucial role. In this study, an in-situ coenzyme regeneration system was developed by coupling carbonyl reductase (CpCR) with glucose dehydrogenase (GDH), resulting in the construction of five recombinant strains capable of NADPH regeneration. Among these, the recombinant strain E. coli BL21-pETDuet-1-GDH-L-CpCR, where CpCR is fused to the C-terminus of GDH, demonstrated the highest catalytic activity. This strain exhibited an enzyme activity of 69.78 U/mg and achieved a conversion rate of 98.3%, with an enantiomeric excess (ee) of 99.9% during the conversion of 30 mM OPBE to (R)-HPBE. High-density fermentation further enhanced enzyme yield, achieving an enzyme activity of 1960 U/mL in the fermentation broth, which is 16.2 times higher than the volumetric activity obtained from shake flask fermentation. Additionally, the implementation of a substrate feeding strategy enabled continuous processing, allowing the strain to efficiently convert a final OPBE concentration of 920 mM, producing 912 mM of (R)-HPBE. These findings highlight the system’s improved catalytic efficiency, stability, and scalability, making it highly suitable for industrial-scale biocatalytic production.

Sustainable fluoride removal with scrap aluminum: Co-producing cryolite and hydrogen

This study presents a novel continuous process for fluoride removal and re- source recovery as cryolite, using a scrap aluminum-packed column. Efficient aluminum dissolution in hydrofluoric acid (HF) generates hydrogen gas and provides cost-saving alkalinity. The process achieves high efficiency (Al/F molar ratio of 2/6) within short Empty Bed Contact Times (15 min) and at low HF concentrations (500 mg/L). Solution pH plays a crucial role, with Al/F ratios above 1 achievable at pH below 4. The exothermic reaction requires temperature control, with a strong correlation (R²=0.99) between HF concentration and heat generation. Hydrogen production matches theoretical predictions. Cryolite synthesis was confirmed at optimized pH (5–5.5) with a 1:1 bypass ratio, achieving 98 % fluoride removal. XRD and SEM- EDS analyses verified cryolite formation. This approach offers a promising solution for industrial fluoride management, resource recovery, and clean hydrogen production.

Optimizing the Pore Structure of Lotus-Type Porous Copper Fabricated by Continuous Casting.

Lotus-type porous copper was fabricated using a continuous casting method in pressurized hydrogen and nitrogen gas atmospheres. This study evaluates the effects of process parameters, such as the hydrogen ratio, total pressure, and transference velocity, on the resulting pore structure. A continuous casting process was developed to facilitate the mass production of lotus-type porous copper. To achieve the desired porosity and pore diameter for large-scale manufacturing, a systematic evaluation of the influence of each process parameter was conducted. Lotus-type porous copper was produced within a hydrogen ratio range of 25-50%, a transference velocity range of 30-90 mm∙min-1, and a total pressure range of 0.2-0.4 MPa. As a result, the porosity ranged from 36% to 55% and the pore size varied from 300 to 1500 µm, demonstrating a wide range of porosities and pore sizes. Through process optimization, it is possible to control the porosity and pore size. The hydrogen ratio and total pressure were found to primarily affect porosity, whereas the hydrogen ratio, transference velocity, and total pressure significantly influenced pore diameter. When considering these parameters together, porosity was most influenced by the hydrogen ratio, whereas the total pressure and transference velocity had a greater influence on pore diameter. Reducing the hydrogen ratio and increasing the transference velocity and total pressure reduced the pore diameter and porosity. This optimization of the continuous casting process enables the control of porosity and pore diameter, facilitating the production of lotus-type porous copper with the desired pore structures.

Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI’s applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI’s transformative impact on the pharmaceutical industry and its broader implications for healthcare.

A Combined Experimental and Computational Study on the Effect of the Reactor Configuration and Operational Procedures on the Formation, Growth and Dissociation of Carbon Dioxide Hydrate

Clathrate hydrate-based technologies are considered promising and sustainable alternatives for the effective management of the climate change risks related to emissions of carbon dioxide produced by human activities. This work presents a combined experimental and computational investigation of the effects of the operational procedures and characteristics of the experimental configuration, on the phase diagrams of CO2-H2O systems and CO2 hydrates’ formation, growth and dissociation conditions. The operational modes involved (i) the incremental (step-wise) temperature cycling and (ii) the continuous temperature cycling processes, in the framework of an isochoric pressure search method. Also, two different high-pressure PVT configurations were used, of which one encompassed a stirred tank reactor and the other incorporated an autoclave of constant volume with magnetic agitation. The experimental results implied a dependence of the subcooling degree, (P, T) conditions for hydrate formation and dissociation, and thermal stability of the hydrate phase on the applied temperature cycling mode and the technical features of the utilized PVT configuration. The experimental findings were complemented by a thermodynamic simulation model and other calculation approaches, with the aim to resolve the phase diagrams including the CO2 dissolution over the entire range of the applied (P, T) conditions.

Operational Excellence: Process optimization for competitive edge

This study explores the concept of operational excellence and the role of process optimization in gaining a competitive edge for organizations. Operational excellence involves the continuous improvement of business processes to increase efficiency, reduce waste, enhance quality, and improve overall performance. The study reviews established methodologies such as Lean, Six Sigma, and Total Quality Management (TQM) that provide structured approaches to achieving operational efficiency. It also examines the impact of emerging technologies, including artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), in driving data-driven decision-making and enhancing process optimization. Additionally, the study highlights the importance of leadership in fostering a culture of continuous improvement and collaboration across departments, ensuring alignment with strategic objectives. The integration of sustainability into operational strategies is discussed as a means to not only improve efficiency but also meet corporate social responsibility goals. The relationship between process optimization and innovation is also explored, showing how operational excellence can free up resources for research and development (R&D) and foster a culture of innovation. Despite the focus on these established practices and technologies, the study acknowledges limitations, particularly the challenges faced by small and medium-sized enterprises (SMEs) and service oriented sectors in implementing these strategies. The study concludes that operational excellence, supported by technological advancements and a strong organizational culture, is essential for organizations to navigate competitive markets, improve customer satisfaction, and achieve long-term success. This research offers valuable insights for businesses aiming to enhance operational performance and sustain their competitive advantage through continuous process optimization and innovation.

Massive Education in Prison Health in Brazil: A Look Beyond the Walls

Equal access to health initiatives and services under the principles of universal and comprehensive care remains a challenge in Brazil. The realization of public health policies is further intricate when one examines the health situation of people deprived of liberty. This study showcases the “Prison System: Beyond the Walls” educational pathway, available on the Virtual Learning Environment of the Brazilian National Health System (AVASUS). The action research methodological strategy guided the pathway development, emphasizing dialogic learning. The goal was to address the need for massive training on the topic of prison health, with the model focusing on engagement through spontaneous, non-mandatory participation in the pathway courses. The pathway comprised four modules, whose educational offerings were based on the self-learning model. Students were free to choose which courses to take and in what order, as there was no prerequisite for participating in modules. Hence, students could either take all the courses or only those with which they identify their learning needs, regardless of work demands or personal interests. Structuring the pathway through action research facilitated a massive, cohesive, and continuous training process. This approach expanded knowledge and established meaningful relationships among the related topics and the key players involved: health professionals, prison officers, and people deprived of liberty. Notably, the pathway courses have surpassed the 50,000-enrollment mark, spanning all five regions of Brazil. In this context, this article presents and discusses the development of the “Prison System: Beyond the Walls” pathway, emphasizing the massive improvement of health within Brazil’s prison system and highlighting the results achieved.

Results of the Mycological Investigation of the Shoot System of "Irinovsky Oak" Tree (Leningrad Oblast, Russia).

The wild nature monument "184-year-old oak tree in the village of Irinovka" (Leningrad oblast, Russia), better known in local historical literature as "Irinovsky Oak," was officially opened in 2013. It is represented by a separate pedunculate oak tree (Quercus robur), planted in 1829 and preserved in satisfactory condition at 194 years of age. This paper presents data from a survey of the shoot system of the tree investigated. A total of 12 fungal species were registered (Cladosporium herbarum, Colpoma quercinum, Coryneum depressum, Diatrypella quercina, Erysiphe alphitoides, Hyphoderma setigerum, Laetiporus sulphureus, Mar-chandiomyces corallinus, Peniophora quercina, Trichoderma viride, Sphaerulina quercicola, Vuilleminia comedens). The lichenicolous species Marchandiomyces corallinus was reported as a new find to the Leningrad oblast. It was shown that the shoot system of the tree investigated is associated with a complex of Quercus robur-adapted and coadapted species, among which such necrotrophs as Sphaerulina quercicola and Coryneum depressum and such pathogenic saprotrophs as Vuilleminia comedens and Colpoma quercinum, as well as saprotrophs (Diatrypella quercina, Peniophora quercina), dominated. This species complex ensures a continuous process of the crown's thinning.

Manajemen Strategi Peningkatan Mutu Pendidikan Di Smp Al Bayan Kota Makassar

The purpose of this study is to describe the strategic management approach used to improve teaching standards at Al Bayan Junior High School Makassar City. This type of research is descriptive qualitative. The data collection techniques used include notes, interviews, and observations. This research uses three activity streams for qualitative data analysis, namely data reduction, data presentation, and verification/conclusion drawing. The data triangulation technique was used in assessing the validity of the data. The findings show that: (1) Al Bayan Junior High School Makassar City conducts integrated, methodical, and comprehensive planning through the following stages in order to realize the quality of education: a) Examining the school's internal environment both material, technical, and human resources. b) Examining the geographical, social, and economic context outside the school. c) Careful observation and in-depth analysis. (2) In implementing initiatives aimed at raising educational standards, Al Irsyad leaders use the following policies: a) Continuous process improvement. b) Creating standards for school improvement and quality assurance. c) Establishing a school culture. d) Modifying the organizational structure. e) Maintaining positive interactions with customers. (3) To verify that a high-quality education program has been achieved, evaluation is also conducted in the following ways: a) by tracking all results from planning and implementing strategic management activities. b) evaluating student and individual performance. c) providing reports on how all actions were carried out; and d) making necessary corrections.

Implementation of Machine Learning in the Categorization of Improvement Areas for Kaizen Submissions

This paper explores the synergy between Kaizen methodologies and Machine Learning, with the goal of improving the efficiency of categorizing areas of improvement. The implementation of Machine Learning algorithms, utilizing the ML.NET tool, has proven to be highly advantageous. These algorithms automate the categorization of Kaizen proposals based on structured data and predefined labels. This automation significantly reduces manual workload, expedites the classification process, and ultimately accelerates decision-making within the realm of continuous improvement. Furthermore, the application of machine learning has improved the categorization accuracy, reduced the risk of human errors, and ensured a more precise assignment to the relevant categories. This, in turn, enhances the quality of the collected information, facilitating well-informed decision-making. Additionally, the automated categorization has streamlined the process for users submitting Kaizen proposals, eliminating the need for manual category selection. This reduces cognitive load and promotes active engagement in the continuous improvement process. Furthermore, the system has introduced a category-based incentive structure, where users accrue points corresponding to the category assigned to their Kaizen proposals. These points can be exchanged for items provided by the company, acting as an additional incentive for active employee participation in the continuous improvement process. In conclusion, the integration of Machine Learning with the ML.NET tool has become a valuable tool for optimizing the management of improvement proposals, resulting in a marked enhancement in efficiency, accuracy, and user engagement in the categorization process.

Low-Contact Impedance Textile Electrode for Real-Time Detection of ECG Signals.

The quality of the electrocardiography (ECG) signals depends on the effectiveness of the electrode-skin connection. However, current electrocardiogram electrodes (ECGE) often face challenges such as high contact impedance and unstable conductive networks, which hinder accurate measurement during movement and long-term wearability. Herein, in this work, a bionic 3D pile textile as an ECGE with high electrical conductivity and flexibility is prepared by a facile, continuous, and high-efficiency electrostatic self-assembly process. Integrating pile textiles with conductive materials creates a full textile electrode for bioelectrical signal detection that can retain both the inherent characteristics of textiles and high conductivity. Moreover, the dense piles on the textile surface make full contact with the skin, mitigating motion artifacts caused by the sliding between the textile and the skin. The continuous conductive network formed by the interconnected piles allows the pile textile ECGE (PT-ECGE) to function effectively under both static and dynamic conditions. Leveraging the unique pile structure, the PT-ECGE achieves superior flexibility, improved conductivity, low contact impedance, and high adaptivity, washability, and durability. The textile electrode, as a promising candidate for wearable devices, offers enormous application possibilities for the unconscious and comfortable detection of physiological signals.

Continuous recovery of tellurium and cadmium from simulated CdTe leachates using a fixed-bed-column adsorption system

Rare element resource (Te) loss and heavy metal (Cd) pollution, derived from waste photovoltaic CdTe cells, have attracted considerable attention in the cleaner production and environmental protection field. However, there are several technical barriers in conventional adsorption strategies for the continuous recovery Te(Ⅳ) and Cd(Ⅱ) due to single-component recovery, inefficient adsorbent utilization and less automation. Herein, this work presented a fixed-bed-column adsorption system for the continuous adsorption recovery of tellurium and cadmium from a simulated CdTe leachate using functional sludge-based adsorption fillers (LDO/SF and EDTA@LDH/SF) that prepared from water-processing sludge via hydrothermal synthesis, thermal activation and surface modification technologies. Breakthrough curves were analyzed for adsorption columns, considering initial concentration, flow rate, and filler height, with parameters evaluated using the Thomas and BDST models to determine the optimal separation parameters. During the continuous adsorption process, the column adsorption system with the filler layer height of 4 cm and liquid delivery rate of 1 mL/min can be used for continuous separation of more than 1000 mL of a simulated CdTe leachate and exhibits adsorption efficiencies of more than 96% and 82% for Te(Ⅳ) and Cd(Ⅱ), respectively. More importantly, the elution procedure was used to treat the column adsorption system with ion adsorption acceptances of 83% and 90% for Te(Ⅳ) and Cd(Ⅱ), respectively. Meanwhile, the functional sludge-based fillers demonstrated great regeneration and recycling capabilities, thus maximizing the utilization of adsorbents and saving treatment costs. This study has established a robust technical solution for the continuous recovery of tellurium and cadmium from simulated leachates, providing a practical framework for evaluating the efficiency of adsorption filler columns in actual applications.

A participatory research to assess how a student citizens’ assembly can facilitate the co-creation of nutrition interventions in higher education settings

BackgroundThe transition period from adolescence to early adulthood is critical for developing new nutritional behaviors, making higher education students an important target group for public health nutrition interventions. Given the complexity of nutrition-related behaviors and their various determinants, involving the student population (the future beneficiaries of interventions) and the partners engaged in their implementation when designing campus nutrition interventions is essential. Citizens’ assemblies are deliberative processes which are more and more frequently organized to co-create solutions to complex problems. This study aims 1) to design and implement a student citizens’ assembly using participatory research methods, 2) to describe its process and evaluate its transferability, 3) to evaluate changes in dietary habits, knowledge and citizen practices among students participating in this assembly.MethodsThis study will take place at a French university (University Sorbonne Paris Nord, USPN) located in socio-economically disadvantaged suburbs of Paris. The student citizens’ assembly will gather a mini-public of 30 students enrolled at the time of the study and a co-creation team of academic and non-academic partners involved in student life, nutrition, physical activity, or public policies. The aim of the assembly is to co-create a set of concrete proposals that would enhance USPN students’ access to sustainable diets and physical activity. The protocol is based on a continuous process evaluation and a pre-post design among the mini-public. A mixed-method framework combining quantitative and qualitative approaches will be developed. This study will make use of (i) field observations of the intervention process and transferability, (ii) data collected by questionnaires on pre- and post- dietary habits, knowledge and citizen practices of the mini-public, and (iii) pre-post interviews with a subsample of the same mini-public.DiscussionRelying on participatory research methods, this study will provide new insights into involving higher education students and diverse partners in co-creating campus nutrition interventions. Through the collaborative work of researchers, higher education students, university representatives, public institutions, and local and community actors, this study will provide evidence-based guidance for designing innovative and contextually-relevant nutrition interventions in the higher education setting.Trial registrationThis research was registered at the ClinicalTrial.gov (NCT06580795; registration date: 2024–08-30; https://www.clinicaltrials.gov/study/NCT06580795).

Reduction and structural modification of MoOx/γ-Al2O3 catalysts through acetic acid treatment for green diesel production from corn distiller’s oil

Enabling new environmentally-friendly resources for fuels and platform chemicals is crucial to fulfill our future energy demands while enhancing circularity. Corn distiller’s Oil (CDO) − as a coproduct of the ethanol industry, serves as a sustainable supply of carbon that may be converted into energy, fuels and specialty chemicals. A current challenge in using renewable oxygenated feedstocks is the high amount of coking and catalyst fouling that occurs. This study examined the hydrothermal deoxygenation of CDO into green diesel using molybdenum oxide (MoOx) catalysts in a continuous process without using any external hydrogen. The possibility of reduction and developing oxygen-deficient surfaces on molybdenum oxide (MoOx) catalysts through acetic acid treatment or adding ceria (CeO2) was investigated in order to enhance the acidity of catalysts as well as catalytic activity and stability required for the production of green diesel from CDO. Results showed that the acidity of these catalysts as measured by NH3 temperature programmed desorption (NH3-TPD) had a strong correlation between the degree of deoxygenation and catalyst stability. Acetic acid treatment of the 7.5 wt% MoO3/γ-Al2O3 catalyst reduced MoO3 to MoO3-x, increased the Mo5+ species from 8.7 % to 22 %, created Mo4+ species and increased the catalyst surface acidity in the range of low to moderate strength by approximately 17 %. The use of acetic acid-treated molybdenum oxide (Hac-7.5 wt% MoO3/γ-Al2O3) catalyst enabled nearly complete (99.9 %) deoxygenation of CDO and heavy hydrocarbons cracking to produce diesel-like fuels. A moderate increase in catalyst surface acidity by acetic acid treatment also increased the selectivity of diesel-like fuel through hydrocracking of long-chain hydrocarbons. This low-cost modification step of catalyst improvement is promising for industrial application. However, cracking of hydrocarbons generated amorphous coke (no graphitic coke was observed) on the catalyst surface, which required periodic removal by controlled calcination of the catalyst in presence of air for further use.