Process Integration Research Articles

Cyclooxygenase-2 (COX-2)-dependent mechanisms mediate sleep responses to microbial and thermal stimuli

Prostaglandins (PGs) play a crucial role in sleep regulation, yet the broader physiological context that leads to the activation of the prostaglandin-mediated sleep-promoting system remains elusive. In this study, we explored sleep-inducing mechanisms potentially involving PGs, including microbial, immune and thermal stimuli as well as homeostatic sleep responses induced by short-term sleep deprivation using cyclooxygenase-2 knockout (COX-2 KO) mice and their wild-type littermates (WT). Systemic administration of 0.4 µg lipopolysaccharide (LPS) induced increased non-rapid-eye movement sleep (NREMS) and fever in WT animals, these effects were completely absent in COX-2 KO mice. This finding underscores the essential role of COX-2-dependent prostaglandins in mediating sleep and febrile responses to LPS. In contrast, the sleep and fever responses induced by tumor necrosis factor α, a proinflammatory cytokine which activates COX-2, were preserved in COX-2 KO animals, indicating that these effects are independent of COX-2-related signaling. Additionally, we examined the impact of ambient temperature on sleep. The sleep-promoting effects of moderate warm ambient temperature were suppressed in COX-2 KO animals, resulting in significantly reduced NREMS at ambient temperatures of 30 °C and 35 °C compared to WT mice. However, rapid-eye-movement sleep responses to moderately cold or warm temperatures did not differ between the two genotypes. Furthermore, 6 h of sleep deprivation induced rebound increases in sleep with no significant differences observed between COX-2 KO and WT mice. This suggests that while COX-2-derived prostaglandins are crucial for the somnogenic effects of increased ambient temperature, the homeostatic responses to sleep loss are COX-2-independent. Overall, the results highlight the critical role of COX-2-derived prostaglandins as mediators of the sleep-wake and thermoregulatory responses to various physiological challenges, including microbial, immune, and thermal stimuli. These findings emphasize the interconnected regulation of body temperature and sleep, with peripheral mechanisms emerging as key players in these integrative processes.

Ultrasonic destruction of surfactants

This study investigates the effectiveness of ultrasonic (US) treatment in removing and mineralizing surfactants in wastewater. It examines the complex mechanisms and variables (acoustic conditions, solution temperature, initial dose, etc.) that affect sonolytic processes. The effect of water matrix components (such as salts and the presence of secondary pollutants) on process performance is thoroughly investigated. Various treatments are analyzed through a detailed comparison of synergistic hybridization processes. The study also provides a comprehensive review of current environmental applications and explores potential directions for surfactant degradation using ultrasound. Insightful information is presented to advance sustainable wastewater treatment techniques. The literature review clearly reveals the promising future of sonotreatment for degrading various surfactants under different conditions. The use of multifrequency mechanisms and the integration of other advanced oxidation processes (AOPs) with the US process have significantly enhanced the energy efficiency of the sonochemical system. Additionally, the results highlight the need to focus on developing new sonoreactor designs, identifying degradation intermediates, and hybridizing the sonochemical system under innovative operating conditions.

Applications of stochastic processes and reinforcement learning in strategic decision support and personalized ad recommendation: An AIGC study

This paper investigates the integration of stochastic processes and reinforcement learning (RL) in strategic decision support systems (SDSS) and personalized advertisement recommendations. Stochastic processes offer a robust framework for modeling uncertainties and predicting future states across various domains, while RL facilitates dynamic optimization through continuous interaction with the environment. The combination of these technologies significantly enhances decision-making accuracy and efficiency, yielding substantial benefits in industries such as financial services, healthcare, logistics, retail, and manufacturing. By leveraging these advanced AI techniques, businesses can develop adaptive strategies that respond to real-time changes and optimize outcomes. This paper delves into the theoretical foundations of stochastic processes and RL, explores their practical implementations, and presents case studies that demonstrate their effectiveness. Furthermore, it addresses the computational complexity and ethical considerations related to these technologies, providing comprehensive insights into their potential and challenges. The findings highlight the transformative impact of integrating stochastic processes and RL in contemporary decision-making frameworks.

Process integration and analysis of coupling solid oxide electrolysis cell (SOEC) and CO2 to methanol

The coupling of renewable energy electrolysis for hydrogen production and methanol synthesis can not only reduce CO2 emissions, but also achieve on-site consumption of renewable electricity. In this paper, an integrated system of solid oxide electrolysis cell (SOEC) with CO2 to methanol (SOEC-CO2tM) is studied: (1) The energy-intensive SOEC is combined with the intense exothermic CO2tM, (2) the heat of the system is redistributed to energy realize cascade utilization and electrification transformation of public works to further improve energy efficiency, (3) multi-dimensional techno-economic assessments are performed to reveal the development potential. The results show that the carbon utilization and carbon emissions of the new process are better controlled. The energy efficiency of the SOEC-CO2tM process after electrification transformation is also higher than that of traditional methanol synthesis processes. The production cost of methanol is currently higher than the market price, which does not give the SOEC-CO2tM process a competitive advantage. However, when considering carbon taxes and changes in raw material costs and renewable electricity prices, the future cost of the SOEC-CO2tM process can be comparable to or even more favorable than other processes. Through the research and analysis, we aim to explore the potential integration of SOEC and CO2tM process.

Explore the Teaching Design of English Reading based on the Alignment of Teaching, Learning and Evaluation

The “Alignment of Teaching, Learning and Evaluation” emphasizes the integration of teaching content, learning process and evaluation method in the whole teaching process, through which students’ comprehensive ability, teachers’ professional development and teaching reform can be facilitated. Taking Living Legends (Reading and Thinking) from Lesson 2, Unit 3, Book 1 by People’s Education Press as an example, this study explores how to guide students to complete the knowledge input, intake and creative output from text interpretation to practical application, then to innovation and transformation based on text and students analysis, aiming to sort out the specific methods and steps of integrated teaching, learning and assessment from macro planning to micro classroom teaching, and provide practical enlightenment for integrated reading teaching, learning and assessment in senior high school and useful data for theoretical research on teaching evaluation.

Integration of layer-by-layer hollow-fibre nanofiltration membranes and crystallization for water reclamation and resource recovery from acidic mine waters

Water pollution remains a critical issue in the global mining industry. Moreover, the access to a reliable source of raw materials such as Cu, Zn, Mg and Rare Earth Elements has become a challenge for the European Union. In this context, the treatment of Acidic Mine Waters (AMW) with a circular perspective can be a solution to both challenges. This study focused on the integration of crystallization processes and nanofiltration (NF) to selectively recover Mg(OH)2(s) and reclaim AMW for irrigation purposes from the Aznalcóllar open-pit (1629 mg/L Mg2+, 360 mg/L Ca2+ and 10,962 mg/L SO42−). The pre-treatment, involving selective precipitation, attained removals higher than 95 % of transitions elements. Different concentrations of NaOH (0.16 M, 0.25 M, 0.5 M) were used for the crystallization of Mg(OH)2(s), affecting the morphology and content of the final product. The removal of Ca2+ was performed by the addition of NaHCO3 at constant pH, achieving Ca removals of 99 %. The remaining salinity removal was achieved using a layer-by-layer hollow-fibre NF membrane, resulting to rejections higher than 80 % for Ca2+, SO42−, and Na+. The obtained results demonstrate that the combined crystallization and NF stages is a feasible approach for the efficient treatment and water reclamation of AMW.

IMPLEMENTATION OF SUPPLY CHAIN MANAGEMENT IN IMPROVING CUSTOMER SATISFACTION (CASE STUDY AT PT SIDO MUNCUL TBK)

The purpose of this research is to determine the implementation of Supply Chain Management (SCM) in improving customer satisfaction. Supply Chain Management is a management method that involves the integration of business processes among networks related to suppliers, manufacturers, distribution centers, and retailers. Customer satisfaction is the overall attitude shown by consumers towards goods and services after they have obtained and used them, and it represents the difference between what consumers expect and the situation provided by the company. The method used is a case study because the targeted company has already implemented Supply Chain Management in its operations. Data collection techniques include interviews and documentation. The results of this research prove that the proper implementation of Supply Chain Management by the company has an impact on customer satisfaction. Keywords: Supply Chain Management (SCM), Customer Satisfaction, Management Accounting, Production Management

Study of performance evaluation of various characteristics of a single phase full bridge inverter circuit using surrounded channel junctionless field effect transistor

This paper reports the characteristics study of a single phase full bridge power electronic inverter circuit with a new type of technology namely surrounded channel junctionless field effect transistor (SCJLFET) as a switch. The inverter circuit has been designed using mixed mode simulation platform of TCAD device simulator. The transient characteristics for various temperatures and work functions have been analysed. In the steady state analysis the output current and voltage variation with input voltage with various temperatures and work functions have been studied. The power factor variations with gate oxide thickness and dielectric constant of gate dielectric. The simulation and designing process along with pros and cons have been characterized. The SCJLFET would be one of the strongest participants for advanced power electronics technology as a switches, with various virtues of high-speed operation, low power consumption and low budget process integration. It has also been found that single phase full bridge inverter is giving best results when made using SCJLFET.

Reactive Carbon Capture: Cooperative and Bifunctional Adsorbent-Catalyst Materials and Process Integration for a New Carbon Economy.

ConspectusTo say the least, releasing CO2 into the atmosphere is reaping undue environmental consequences given the ever-present increase in severe global weather events over the past five years. However, it can be argued that-at least in the confines of current technological capabilities-the atmospheric release of CO2 is somewhat unavoidable given that even shifting toward clean energy sources-such as solar, nuclear, wind, battery, or H2 power-incurs an initial carbon requirement by way of manufacturing the very production abilities through which "clean" energy is generated. Even years from now, experts agree that energy production will be diversified and-as the global population continues to drive the growth of global energy consumption-thermal power derived from carbon combustion is likely to remain one intrinsic energetic source, of which CO2 will always be a byproduct. In this context, it is the responsibility of the scientific community to devise improved pathways of carbon management such that (i) the consequences of combustion on the global environment are reduced and (ii) carbon fuels can be leveraged in a sustainable fashion.In this Account, we discuss a pivotal perspective shift on CO2 emissions derived from a considerable breakthrough in material science from our work at Missouri University of Science and Technology. This account details the development of materials which no longer vilify CO2 emissions as a valueless combustion byproduct, instead providing a path for them to become a potential feedstock. In more specific terms, this work details the development of structured, cooperative "bifunctional" materials (BFMs) comprised of (i) a high-temperature adsorbent and (ii) a heterogeneous catalyst that enable single-bed CO2 capture and utilization in oxidative ethane dehydrogenation (ODHE), oxidative propane dehydrogenation (ODHP), and dry methane reforming (DMR) processes. This Account begins with the conceptual development of the BFMs in the powdered state, followed by detailing the first-ever reports of structuring the materials into facile honeycomb contactors by 3D printing. The Account then summarizes the impressive performance of the 3D-printed BFMs, specifically focusing on how their catalysts (metal oxides and perovskites) influence their reactive CO2 capture performances in ODHE, ODHP, and DMR processes. Such promise of CO2-as-fuel offers a glimpse into the future of a diversified energy economy, in which CO2/fuel looping can play an important role. A major factor in achieving this future is, of course, developing an appropriately active catalyst; an account of whose first breakthroughs in material science are detailed herein.

Energy consumption optimization of CO2 capture and compression in natural gas combined cycle power plant through configuration modification and process integration

Currently, natural gas combined cycle (NGCC) power plants account for a quarter of global electricity power supply and lead to greenhouse gas emissions. Carbon capture and storage (CCS) is one of the most effective technologies to reduce carbon emissions in the short term. However, the monoethanolamine (MEA)-based CO2 absorption and compression process is energy-intensive, which significantly reduces the power generation efficiency of NGCC. In addition, the waste hot and cold energy from NGCC and liquefied natural gas (LNG) regasification process, which are generally wasted, can be recovered for the CCS process. Therefore, this study aims to reduce the energy consumption of the carbon capture process and recover waste LNG cold energy and hot energy in the NGCC through configuration modification and process integration. The results show that the energy consumption of CO2 regeneration in the proposed CO2 capture process configuration is reduced by 18.03 %, and the net power efficiency of the NGCC plant increases from 48.88 % to 50.10 %. Furthermore, a cascade two-stage organic Rankine cycle is integrated into the system for waste heat recovery, which can generate 5.04 MW electric power and reduce the efficiency penalty of the plant from 13.72 % to 10.29 %. By contrast, the alternative application of LNG cold energy to the CO2 compression process reduces compression power by 3.95 MW with a lower footprint and utility requirement while the efficiency penalty is decreased by 3.15 %.

Exploring cleaner routes of Alumina Production: Thermodynamic Simulation of Pedersen Process and CO2 Capture Integration via Calcium Looping

Alumina industry stands out as a significant contributor to mineral scarcity because of the generation of bauxite residue during its production process. This study explores an alternative route to produce alumina: the Pedersen process. A thermodynamic simulation and an energy optimization are implemented to avoid bauxite residues and reach the goal of zero CO2 emissions.

Supply chain integration, competitive strategies and firm performance

Purpose This study aims to examine the interaction between different types of supply chain integration (SCI) and competitive strategies on firm performance. Design/methodology/approach The research method is quantitative. The study develops a structured model and a set of hypotheses based on the related theories. Empirical data is collected in a cross-sectional manner using an online survey to test the model and its hypotheses. The survey comprised standard scales to measure study variables. The scales had high reliability and validity and were commonly used in the literature. The study was conducted on Iranian firms working in steel and auto parts industries. Based on official reports, a total of 305 active companies were found in these two industries. Due to the small population size, all companies in the two industries were contacted for participation. Overall, 84 firms completed the survey. To test the research hypotheses, the authors used hierarchical regression analyses using SPSS 27 software. Findings Results showed that internal integration improves financial performance when firms follow a cost leadership strategy. Differentiation strategy and process integration interact positively and improve operational performance. Type of industry had no significant effect. The results add to the SCI literature by showing that a match between competitive strategy and integration type can influence both operational and financial performance. In total, firms should focus on the appropriate dimension of SCI based on their competitive strategy to improve the performance of the firm. Originality/value The impact of competitive strategy as a moderator on the SCI-performance relationship has not been widely addressed in the literature. In one study, Huo et al. (2014) investigated this relationship using data from 604 manufacturing companies in China. The results provided support for financial performance but not for operational performance. However, the influence of competitive strategies on the SCI performance may vary in different countries and contexts with dissimilar environmental, social and cultural characteristics. As several supply chain scholars have argued, understanding contextual conditions that influence the effect of best practices such as SCI on performance are critical

Analysis of the Design and Curricular Practices in an Educational Re-Engagement Program

<p style="text-align:justify">In this article, which is part of a broader investigation based on the study of the educational and socio-occupational re-engagement processes of young people in vulnerable situations, the curricular design of the vocational training programs (VTP) is described. Further, the curricular practices developed in the classrooms of these programs are analyzed, based, above all, on how the contents are selected, as well as the methodological approaches for their development. The research methodology that was followed responds to the conduct of multiple case studies with the integration of quantitative and qualitative processes. The data collection instruments used for this purpose were questionnaires, interviews, and discussion groups. The conclusions reveal the selection of contents that are relevant, interesting, and close to the reality of the students. The development of these contents is displayed through varied methodological strategies and diverse activities that enhance the students’ involvement and the practical sense of their learning.</p>

Should We Discourage AI Extension? Epistemic Responsibility and AI

We might worry that our seamless reliance on AI systems makes us prone to adopting the strange errors that these systems commit. One proposed solution is to design AI systems so that they are not phenomenally transparent to their users. This stops cognitive extension and the automatic uptake of errors. Although we acknowledge that some aspects of AI extension are concerning, we can address these concerns without discouraging transparent employment altogether. First, we believe that the potential danger should be put into perspective – many unreliable technologies are unlikely to be used transparently precisely because they are unreliable. Second, even an agent who transparently employs a resource may reflect on its reliability. Finally, agents can rely on a process transparently and be yanked out of their transparent use when it turns problematic. When an agent is responsive to the reliability of their process in this way, they have epistemically integrated it, and the beliefs they form with it are formed responsibly. This prevents the agent from automatically incorporating problematic beliefs. Responsible (and transparent) use of AI resources – and consequently responsible AI extension – is hence possible. We end the paper with several design and policy recommendations that encourage epistemic integration of AI-involving belief-forming processes. Keywords: phenomenal transparency, artificial intelligence, cognitive extension, adversarial attack, cognitive integration.

Dynamic Replacement of Soil Inorganic Carbon under Water Erosion

The dynamic replacement of soil organic carbon represents a pivotal mechanism through which water erosion modulates soil–atmosphere CO2 fluxes. However, the extent of this dynamic replacement of soil inorganic carbon within this process remains unclear. In our study, we focused on Yuanmou County, China, a prototypical region afflicted by water erosion, as our study area. We leveraged the WaTEM/SEDEM model to quantify the dynamic replacement of soil carbon, accounted for the average annual net change in soil carbon pools, and used isotope tracer techniques to track and measure the process of the coupled carbon–water cycling. This comprehensive approach enabled us to scrutinize the dynamic replacement of soil carbon under water erosion and delineate its ramifications for the carbon cycle. Our findings unveiled that the surface soil carbon reservoir in the Yuanmou area receives an annual replacement of 47,600 ± 12,600 tons following water erosion events. A substantial portion, amounting to 39,700 ± 10,500 tons, stems from the dynamic replacement of soil inorganic carbon facilitated by atmospheric carbon. These results underscore the critical role of the dynamic replacement of soil inorganic carbon in altering the soil–atmosphere CO2 fluxes under water erosion, thereby influencing the carbon cycle dynamics. Consequently, we advocate for the integration of water erosion processes into regional carbon sink assessments to attain a more comprehensive understanding of regional carbon dynamics.

Stress-induced nuclear translocation of ONAC023 improves drought and heat tolerance through multiple processes in rice

Drought and heat are major abiotic stresses frequently coinciding to threaten rice production. Despite hundreds of stress-related genes being identified, only a few have been confirmed to confer resistance to multiple stresses in crops. Here we report ONAC023, a hub stress regulator that integrates the regulations of both drought and heat tolerance in rice. ONAC023 positively regulates drought and heat tolerance at both seedling and reproductive stages. Notably, the functioning of ONAC023 is obliterated without stress treatment and can be triggered by drought and heat stresses at two layers. The expression of ONAC023 is induced in response to stress stimuli. We show that overexpressed ONAC23 is translocated to the nucleus under stress and evidence from protoplasts suggests that the dephosphorylation of the remorin protein OSREM1.5 can promote this translocation. Under drought or heat stress, the nuclear ONAC023 can target and promote the expression of diverse genes, such as OsPIP2;7, PGL3, OsFKBP20-1b, and OsSF3B1, which are involved in various processes including water transport, reactive oxygen species homeostasis, and alternative splicing. These results manifest that ONAC023 is fine-tuned to positively regulate drought and heat tolerance through the integration of multiple stress-responsive processes. Our findings provide not only an underlying connection between drought and heat responses, but also a promising candidate for engineering multi-stress-resilient rice.

Process Integration for the Production of Bioplastic Monomer: Techno-Economic Analysis and Life-Cycle Assessment

Process Integration for the Production of Bioplastic Monomer: Techno-Economic Analysis and Life-Cycle Assessment

Canonical variate residual analysis for industrial processes fault detection

AbstractWith the rapid development of intelligent integration in industrial processes, a challenge emerges. Early failures cannot be detected in a timely manner, potentially leading to significant financial losses. While traditional canonical variate analysis (CVA) methods are effective for dynamic process monitoring, they may lack the flexibility required for early fault detection. To address this challenge, a fault detection method based on canonical variate residual analysis (CVRA) is proposed. CVRA introduces a distinctive residual statistic that preserves critical information about the data. It places heightened focus on the primary components of the data, capturing core features of system changes and enhancing sensitivity to early anomalies. Additionally, by incorporating the geometric properties of the Manhattan distance, it mitigates statistical data errors, thereby improving detection accuracy. Simulation results validate the method's effectiveness in the Tennessee Eastman (TE) process. Furthermore, the successful application of the three‐phase flow facility provides a benchmark for evaluation using real process data.

The impact of premature birth on auditory-visual processes in very preterm schoolchildren

Interactions between stimuli from different sensory modalities and their integration are central to daily life, contributing to improved perception. Being born prematurely and the subsequent hospitalization can have an impact not only on sensory processes, but also on the manner in which information from different senses is combined—i.e., multisensory processes. Very preterm (VPT) children (<32 weeks gestational age) present impaired multisensory processes in early childhood persisting at least through the age of five. However, it remains largely unknown whether and how these consequences persist into later childhood. Here, we evaluated the integrity of auditory-visual multisensory processes in VPT schoolchildren. VPT children (N = 28; aged 8–10 years) received a standardized cognitive assessment and performed a simple detection task at their routine follow-up appointment. The simple detection task involved pressing a button as quickly as possible upon presentation of an auditory, visual, or simultaneous audio-visual stimulus. Compared to full-term (FT) children (N = 23; aged 6–11 years), reaction times of VPT children were generally slower and more variable, regardless of sensory modality. Nonetheless, both groups exhibited multisensory facilitation on mean reaction times and inter-quartile ranges. There was no evidence that standardized cognitive or clinical measures correlated with multisensory gains of VPT children. However, while gains in FT children exceeded predictions based on probability summation and thus forcibly invoked integrative processes, this was not the case for VPT children. Our findings provide evidence of atypical multisensory profiles in VPT children persisting into school-age. These results could help in targeting supportive interventions for this vulnerable population.

Leveraging Expert Knowledge for Mobile Livestock Care: Combining AHP and Naïve Bayes for Diagnosis, Treatment, and Management

This study successfully designed and developed a smartphone application for livestock disease diagnosis, treatment, and reporting. The agile development framework Extreme Programming (XP) ensured efficient iteration and adaptation based on user feedback. Additionally, the integration of the Analytical Hierarchy Process (AHP) with veterinary expert input facilitated the prioritization of disease possibilities within the app. Furthermore, the application of Naive Bayes probability allowed the system to rank diseases based on them likelihood, enhancing the accuracy of diagnoses. Workshops, field observations, group discussions, and interviews with senior veterinary experts were used as data collecting and final product assessment tools to ensure it met the original criteria. Purposive sampling was used to distribute the application to 90 smartphone users who work in veterinary clinics, including 49 senior veterinary medicine students. The proposed system offers benefits such as improved healthcare access, early disease detection, enhanced disease management, and strengthened livestock health surveillance. This multifaceted approach holds significant promise for improving livestock health management, particularly in resource-limited settings.