Three-stage Process Research Articles

The missing middle service gap: Obtaining a consensus definition of the 'Missing Middle' in youth mental health.

As highlighted in Australia's Productivity Commission Inquiry into mental health, subgroups of individuals are failing to have their needs met, or are 'falling through the cracks' in the current system - a phenomenon increasingly referred to as the 'missing middle'. A barrier to devising solutions is that the term 'missing middle' is not clearly defined. Using the Delphi method, we aimed to define the term and explore acceptability. Three expert groups were recruited: carers and young people with a lived experience of mental ill-health; clinicians and service providers; researchers, policymakers and commissioners of mental health services. Using a three-stage Delphi process, we elicited definitions, refined and developed a consensus definition. Ten subthemes describing the 'missing middle' were identified, with four endorsed across all expert groups from the outset: service gap, inflexibility, inadequate service quality and duration, and social disadvantage. Additional subthemes were later endorsed. Feedback was sought on a consensus-driven definition that encompassed the original four endorsed subthemes. Findings supported a shift to a systemic focus - framing the 'missing middle' as a care gap. A consensus definition was developed, repositioning the term to a systems lens, describing a 'missing middle service gap'. The definition represents the 'missing middle' as a term to describe a gap in care where existing mental health services are not meeting the needs of individuals in a meaningful way. Research was carried out in relation to youth mental health in Australia and the definition may need to be adapted for other contexts.

Audio-visual aesthetic teaching methods in college students’ vocal music teaching by deep learning

In recent times, characterized by the rapid advancement of science and technology, the educational system has continuously evolved. Within this modern educational landscape, Science, Technology, Engineering, Arts, and Mathematics (STEAM) education has emerged as a prominent pedagogical paradigm, gaining substantial popularity in college-level instruction and capturing widespread societal attention. Notably, the cultivation of audio-visual aesthetic proficiency occupies a central role within this educational approach, prioritizing the enhancement of aesthetic sensibilities. By ingeniously amalgamating scientific knowledge with emotional expression, this research assumes a crucial facet in the holistic development of individuals. The research aims to explore the cultivation of students’ audio-visual aesthetic abilities in university-level vocal music education by integrating deep learning and STEAM education principles. Drawing upon an extensive review of relevant literature, this research synthesizes the principles of STEAM education with those of deep learning, while considering the current cultural and societal context and the distinct realities faced by contemporary college students. Consequently, this research posits a novel conceptual framework for curriculum design and proposes a three-stage teaching process model. To substantiate the efficacy of this innovative educational model, an empirical investigation employing a questionnaire survey is conducted to assess its teaching effectiveness, confirming the marked superiority of this pioneering pedagogical approach. The results demonstrate that the new teaching model has led to notable enhancements in students’ audio-visual aesthetic abilities, self-confidence in learning, and learning efficiency. Additionally, compared to traditional educational methods, the curriculum primarily, which focused on STEAM education with the project as its core, emphasizes the logic of the learning process and its connection with other disciplines. In conclusion, the three-stage educational model combining STEAM education and deep learning fully considers students’ learning situations and utilizes the analytical capabilities of computers for educational purposes. This learner-centric approach significantly augments teaching efficiency and flexibility. Finally, the research concludes by summarizing its contributions and limitations, offering practical recommendations for the field. This research provides new insights and references for the practice and improvement of audio-visual aesthetic education in higher education institutions.

Practically High Performant Neural Adaptive Video Streaming

Despite offering early promise, Deep Reinforcement Learning (DRL) suffers from several challenges in adaptive bitrate streaming stemming from the uncertainty and noise in network conditions. However, in this paper, we find that although these challenges complicate the training process, in practice, we can substantially mitigate their effects by addressing a key overlooked factor: the skewed input trace distribution in DRL training datasets. We introduce a generalized framework, Plume , to automatically identify and balance the skew using a three-stage process. First, we identify the critical features that determine the behavior of the traces. Second, we classify the traces into clusters. Finally, we prioritize the salient clusters to improve the overall performance of the controller. We implement our ideas with a novel ABR controller, Gelato , and evaluate the performance against state-of-the-art controllers in the real world for more than a year, streaming 59 stream-years of television to over 280,000 users on the live streaming platform Puffer. Gelato trained with Plume outperforms all baseline solutions and becomes the first controller on the platform to deliver statistically significant improvements in both video quality and stalling, decreasing stalls by as much as 75%.

Life cycle assessment (LCA) of biodegradable linear low-density polyethylene (LLDPE) manufactured in India

The global plastic crisis requires urgent attention, as highlighted by a comprehensive review of LCA studies on plastics. Mismanagement of plastic waste has worsened this crisis, affecting all life forms and contaminating natural resources. Plastic production leads to Green House Gas (GHG) emissions. Plastic consumption has resulted in pollution across land, water, and even the air, with microplastics entering the human posing health risks like cancer and allergies. The article stresses the importance of LLDPE and explores the potential of bioplastics. Identifying research gaps led to the initiation of an innovative cradle-to-grave LCA investigation. NICHEM Solutions pioneered a three-stage process to manufacture three products: 1) a novel additive, 2) biodegradable LLDPE granules from the additive, and 3) biodegradable LLDPE film from these granules. Utilizing GaBi software and adhering to ISO 14040 guidelines, this study assessed the environmental and health impacts associated with all three products. Additive production had the highest environmental impact, followed by granule and film formation. Material production led to the overall environmental footprint, with LLDPE film production exhibiting notable effects. Transportation impacts were minimal but presented opportunities for optimization. Results revealed significant marine aquatic impacts across various processes, with global warming and human toxicity also identified as concerns. The study also evaluated alternative energy sources, finding natural gas to be the most favorable overall, followed by solar energy and biogas. Conversely, coal and grid-based electricity usage had the most detrimental effects on global warming and marine aquatic impact. Disposal methods such as landfilling and incineration were shown to exacerbate environmental impacts across multiple categories.

What’s in a name? Participants’ pseudonym choices as a practice of empowerment and epistemic justice

ABSTRACT In qualitative research, using pseudonyms for participants is a common practice. This paper examines how inviting participants to choose their pseudonyms contributes to epistemic justice in the research process. We highlight the transformative potential of participant agency in the research journey by exploring data derived from a large qualitative study of 40 participants from diverse cultural identities who shared their experiences of their doctoral journeys at Western universities (predominantly in Australia). Participants were invited to choose pseudonyms for themselves and their institutions. Employing a narrative inquiry research methodology, data were analyzed via a three-stage iterative process, focusing on participants’ pseudonym selection and the contextual explanations provided for their choices. Our findings reveal that when participants choose their pseudonyms, they are able to present their narratives with greater authenticity, capturing the richness of their lived experiences and cultural contexts, thereby advancing epistemic justice. This practice not only created a space of empowerment for participants but also fostered trust and collaboration between researchers and participants. Thus, we argue that recognizing and inviting the agency of participants in terms of naming can be considered a critical method, shifting traditional power dynamics in research by recognizing participants as experts on their own experiences.

Developing a high-fidelity reduced chemical kinetic mechanism for liquefied petroleum gas (LPG)

The current study aimed at developing an optimal and highly accurate reduced chemical kinetic mechanism for the Liquid Petroleum Gas (LPG). A three-stage reduction process including pre-processing, the main body reduction, and post-processing was utilized. In the main body reduction, a five-step reduction schematic was applied to the detailed mechanism including 980 species and 4972 reactions released by LLNL utilizing the Direct Relation Graph Error Propagation (DRGEP) method coupled with the isomer lumping and sensitivity analysis. Four different reduced mechanisms including 88, 73, 67, and 44 species were developed and compared with the experimental data. The laminar flame speed/equivalence ratio, ignition delay/temperature curves of the LPG combustion as well as 3D combustion parameters including in-cylinder pressure, mean temperature, heat release rate, and fuel consumption rate for an LPG-fueled opposed-piston engine were considered. It was seen that the 73 species mechanism results for the ignition delay/temperature and laminar flame speed/equivalence ratio matched with the experimental data with discrepancies of 3% and 5%, respectively. The 88 species and 73 species mechanisms showed good agreement in 3D modeling for all the considered parameters in comparison with the detailed mechanism with error values less than 2%. However, the 67 and 44 mechanisms results were not in accordance with the experimental data. Consequently, the developed 73-species mechanism was considered the optimal mechanism for LPG fuel.

Minoritizing identity: imposing racial & cultural illusions of ‘the Japanese’

Many identities are originally minoritized products of imposition by majoritized others. Contextualized through the identity of ‘Nihonjin’ (‘a Japanese person’) – one regularly informed by long deconstructed yet still prevalent myths of ‘the Japanese’ (i.e. ‘Nihonjinron’) – I conceptualize minoritization through a three-stage process of imposition, concession, and objectivization. To illustrate this ‘ICO process’ I draw on the experiences of ‘Japanese returnees’ and ‘Japanese biracials’ via in-depth semi-structured interviews. Further supplemented by ethnographic vignettes of those identified as ‘foreigners’ in Japan, I demonstrate how the ICO process can be synonymous with both racialization and culturalization independent from socio-genetics. Negotiable aspects and complex social hierarchies notwithstanding, I emphasize minoritized peoples’ forced concession with navigating lives through identities fabricated by majoritized others.

EXPRESS: From Social to Purchase: Customer Selection in Social Group Buying

Social scope group buying has emerged as an increasingly popular promotional strategy and has served as a new customer acquisition tool. In the service industry, companies use social group buying (SGB) to recruit new customers and promote full-price products. Through SGB activities, customers can trade their social capital to form buying groups, experience SGB-offered sample products, and further alleviate uncertainty regarding expensive full-price products before making a final purchase. We investigate this novel SGB phenomenon by examining customers’ decisions throughout the “experience-conversion” process. In collaboration with a leading online educational platform, we examine customers’ grouping behavior during SGB activities and analyze their subsequent purchases. Our analysis reveals an interesting pattern in which non-grouped customers have a higher proportion of full-price product purchases than grouped customers. We postulate that, in addition to observations from operational data, unobserved social information is important for gaining a deeper understanding of the customer behaviors underlying this pattern. Employing a Bayesian learning framework, we model customers’ three-stage discrete-choice decision-making processes and quantify two influential social information factors: social cost and social learning. By incorporating social information, our Bayesian learning model demonstrates improved effectiveness in assisting companies with accurately predicting final purchases in the conversion process. We provide actionable insights into how companies can employ our model to strategically tailor SGB designs by customer segments to increase overall purchase rates. Our study sheds light on the significance of social information in enhancing customer management and refining SGB design.

A Comprehensive Systematic Review of Depression and Anxiety in Adults with Pyoderma Gangrenosum

Background: Pyoderma gangrenosum (PG) is a rare, chronic inflammatory skin disease characterized by painful, necrotic ulcers that frequently lead to disfiguring scars and significantly impact patients’ quality of life. This interplay between PG and mental health issues like anxiety and depression underscores the need for holistic approaches to manage both the physical and psychological challenges faced by PG patients. Methods: This systematic review adhered to the PRISMA 2020 guidelines, focusing exclusively on full-text articles published in English between 2015 and 2024. Result: A total of over 600 publications were initially identified through the database search. Following a rigorous three-stage screening process, eight studies were selected for comprehensive analysis. These studies were critically examined to provide an in-depth evaluation of depression and anxiety among adults with pyoderma gangrenosum. Conclusion: Pyoderma gangrenosum, a chronic autoimmune disorder, significantly impacts patients' mental health due to painful ulcers, visible lesions, and social isolation. Untreated depression can exacerbate pain perceptions and reduce treatment satisfaction. Healthcare providers must screen for and address mental health conditions in PG patients, utilizing psychological support and counseling to address both physical and mental health issues.

Computational study with neural networks to double diffusion in Prandtl thermal nanofluid flow adjacent to a stretching surface design with numerical treatment

The study focuses on the implementation of neural networks in analyzing the behavior of Prandtl nanofluid near a extending surface in the existence of dual diffusion. The research investigates the merged consequence of thermal and concentration gradients on the fluid flow and heat transfer characteristics using advanced computational techniques. The investigation delves into the phenomenon of double diffusion in the flow of Prandtl nanofluid near a stretching surface (DD-PNSS), employing the Levenberg-Marquardt scheme with Artificial Neural Networks (LMS-ANNs). The application of similarity variables converts the non-linear partial differential equations into non-linear ordinary differential equations. Through the application of the Lobatto IIIa formula in a three-stage process, various data sets are generated for the LMS-ANNs by varying parameters such as the Prandtl fluid parameter ([Formula: see text]), Prandtl number (Pr), Brownian motion parameter (Nb), thermophoresis parameter (Nt), and Dufour-solutal Lewis number (Ld). The range of parameter α is from 2 to 3.5, parameter β from 0.1 to 0.9, Nb is from 0.1 to 0.4, Nt is from 0.1 to 0.7, Le is from 1 to 3 and Ld is from 0.1 to 0.5. The intrinsic behavior of embedded parameters on dimensionless velocity, temperature, solutal concentration, and nanoparticle concentration profiles is graphically evaluated. The proposed LMS-ANNs model is meticulously tested, validated, and trained using a multi-stage approach, and its performance is compared to established references to ensure its reliability. The effectiveness of the suggested LMS-ANNs model is further affirmed through regression analysis, Mean Squared Error (MSE) evaluation, and histogram studies, showcasing an exceptional accuracy level ranging from 10−08 to 10−10, setting it apart from alternative approaches and reference models.

2024 ACLP Recommendations for Training Residents in Consultation-Liaison Psychiatry

Despite rapid shifts in consultation-liaison psychiatry (CLP) training in residency, including increasing general residency training requirements from the Accreditation Council for Graduate Medical Education, greater utilization of advanced practice providers, and effects of the coronavirus-2019 pandemic, the Academy of Consultation-Liaison Psychiatry (ACLP) has not updated recommendations for residency training in CLP since 2014. A national survey of residency program directors in 2021 suggested many changes to the structure of CLP rotations at individual programs over the past decade. We convened a workgroup of 8 ACLP members holding leadership positions in residency and fellowship education on local and national levels. The project was approved by the ACLP Executive Council and conducted via a three-stage iterative process. Consensus was reached on 34 recommendations across four domains, including structural issues, faculty supervsion, formal curriculum and evaluations, and elective experiences. Residents must spend sufficient time on CLP rotations to achieve relevant milestones. Given that consultants are expected to offer unique insight, the ideal placement of core CLP rotations comes at a time in residency where residents are able to provide expert opinion and lead teams. Faculty expertise in CLP and availability to provide direct supervision and oversight to trainees is essential. A separate and formal CLP didactic curriculum should exist, and elective opportunities should be offered to supplement training. These recommendations are intended to guide residency program directors towards optimizing CLP training for all residents, including those who will eventually pursue CLP fellowship. Establishing a strong CLP foundation for all residents is essential for ensuring competency in providing psychiatric care for medically complex patients and collaborating with our colleagues in other specialties, as well as fostering trainee interest in pursuing a career in CLP.

Development and Validation of a Scale to Measure the Perception of Workplace Gender Discrimination for Women in Nursing.

Workplace gender discrimination as perceived by women in nursing, is currently under researched. The aim of this article is to outline the development and validation of a scale designed to measure the perception of workplace gender discrimination for women nurses. The instrument was developed following a three-stage process, consistent with recommendations for scale development. Twenty-nine items were derived from two comprehensive literature reviews and interviews with 10 women nurses. Exploratory factor analysis (principal axis factoring) with varimax rotation was conducted for identifying the dimensions underlying the data set. All 29 items loaded onto a factor. Each factor included at least four items and all item loadings were well above the acceptable minimum value (> 0.40). The four factors collectively account for 71.27% of the total variance. Cronbach's alpha of the 29 items (0.964) showed good internal consistency. It is our hope that this research tool will not only be used within nursing, but also with some modification, in other women dominated professions.

Pair formation in Enchenopa treehoppers (Hemiptera: Membracidae) involves complex male–female duetting, and three stages of female mate choice

Abstract We explore the complexity of the signal repertoire and sequences of behavioural interactions involved in pair formation in Enchenopa binotata treehoppers, which communicate via plant-borne vibrational signals, and whose pair formation involves prolonged male-female duetting interactions. We recorded these interactions using laser vibrometry and video assays. In males, we report two phases of signalling: a searching phase in which males use a basic repertoire to solicit engagement from females; and a more complex phase incorporating additional signal types and elements males used once engaged by females. In females, we report a novel three-stage process of selective cooperation with males, as well as a novel signal type that was necessary but not sufficient for copulation to occur. These three stages include active duetting with a male that was necessary for him to locate and mount females; the novel signal that females produce after continued mounted duetting that prompts the male to attempt genital coupling; and the female actively allowing coupling. We discuss implications of our observations for these insects’ cognitive abilities in terms of the memory and selective attention required to sustain signalling interactions and proceed along the decision-making stages of mate choice. Using attention to detail as an aid to discovery, we aim to promote research on how such animals express such capabilities.

Simulation of a system to simultaneously recover CO2 and sweet carbon-neutral natural gas from wet natural gas: A delve into process inputs and units performances

The growing need for carbon-neutral energy solutions necessitates the development of efficient systems for carbon dioxide (CO2) recovery and the production of sweet carbon-neutral natural gas (CNNG) from wet natural gas. Despite existing approaches, limitations in process optimization, solvent efficiency, and output purity persist. This study aims to address these gaps by simulating a system for simultaneous recovery of CO2 and CNNG using an integrated three-stage process, modeled in Aspen Plus V8.8. The unique aspect of this work lies in employing the ENRTL-RK base model, coupled with sensitivity analyses to optimize input parameters across 13 interconnected process units, including compressors, heat exchangers, and extraction columns. Key innovations include the novel configuration of units, yielding a recovery efficiency of 95.94% for CNNG and a CO2 purity of 93.185% at optimal conditions, surpassing conventional methods. The performance of the monoethanolamine (MEA) solvent was enhanced by careful adjustment of input parameters, improving its absorption efficiency by 12% compared to standard operational settings. Sensitivity analysis revealed critical parameters such as feed pressure and solvent flow rate as primary drivers for maximizing output efficiency. This study also provides a detailed quantitative assessment of power requirements, with a compressor brake horsepower (BHP) of 18,2605 watts at 110 bar discharge pressure. It addresses the existing research gap by introducing a systematic approach to process optimization, significantly improving the purity and recovery of CNNG and CO2 while minimizing energy consumption. The results not only demonstrate the viability of this process but also provide a foundation for further refinement in sustainable gas processing technologies.

Maximizing profitability in integrated energy markets: A novel framework for multi-faceted energy trading

The emergence of Integrated Energy Systems (IESs) has shifted energy management from traditional electricity paradigms to a more diverse approach involving electricity, thermal energy, and natural gas. This study introduces a framework for an Integrated Energy Network (IEN) that enables simultaneous trading across these interconnected markets. The objective is to maximize the profitability of integrated energy companies by optimizing energy trading strategies. The proposed business strategy incorporates integrated load response, addressing constraints within electric distribution systems, heating networks, and natural gas pipelines. A three-stage process is used: information sharing in the unified energy market, energy conversion in hubs, and flexible load planning in the retail market. Flexible loads are categorized as displaceable, reducible, or transformable. A Conditional Value-at-Risk (CVaR) mean-variance model addresses market price volatility. Simulations on a test system validate the model, demonstrating its effectiveness in improving profitability and operational efficiency for integrated energy companies.

Dynamics of microbial-induced oil degradation at the microscale.

Microbial-induced oil degradation (MIOD) has a wide range of applications, such as microbial enhanced oil recovery and bioremediation of oil pollution. However, our understanding of MIOD is still far from complete. Particularly, how is the dynamics of degradation process at the microscale level with a single-cell resolution remains to be disclosed. In this work, using hexadecane droplets in water as a model system, we have studied the dynamics of hexadecane degradation by different strains, including Pseudomonas aeruginosa PAO1, IMP68, O-2-2, and Dietzia sp. DQ12-45-1b, at the microscale. Based on visualization of MIOD, the dynamics of MIOD can be characterized by a three-stage process, including adhesion, adaptation, and degradation stages. Although different strains showed similar three-stage dynamics of MIOD, the effective degradation rate varied and followed an order of PAO1 > O-2-2 > IMP68 > DQ12-45-1b under aerobic conditions. Different oxygen conditions were also tested, and the dynamics of MIOD was slowed down under anaerobic conditions in comparison to under aerobic conditions. Further investigations at the degradation stage revealed that biofilms formed at the oil-water interface enhanced oil degradation, but a prerequisite for such enhanced degradation is proper stimulation of biofilm cells in the course of biofilm formation. The findings in this work provided a detailed picture on the dynamics of MIOD at the microscale and would be beneficial for better applications of MIOD.IMPORTANCEMicrobial-induced oil degradation is environmental friendly and economic and has become a promising technique in the fields of enhanced oil recovery and remediation of crude oil-polluted environments. For better applications of microbial-induced oil degradation, understanding the degradation dynamics particularly at the microscale is crucial. In this study, we investigated the degradation dynamics of hexadecane oil droplets incubated with different strains, including Pseudomonas aeruginosa PAO1, O-2-2, IMP68, and Dietzia sp. DQ12-45-1b at the microscale by employing microdroplet-based methods and bacterial tracking techniques. The findings in this study provided a detailed picture on the dynamics of microbial-induced oil degradation at the microscale, which will deepen our understandings on the biodegradation mechanisms of alkanes and shed insights for developing more effective biodegradation techniques.

A qualitative study revisiting the theoretical lens of brand image and developing the consumer brand image schema

Purpose Brand image remains a “nebulous” construct with very few frameworks dedicated to understanding the process of uncovering brand image. This is supported by explicit calls for greater clarity on how to examine brand image, particularly in different settings. Political branding is one setting that has received some attention, however, research has focused on “party” political brands and neglected “non-party” brands (independent candidates). Therefore, this study aims to examine how young citizens interpret independent non-party brands through the theoretical lens of brand image in the context of Guernsey and develop a systematic brand image framework that provides greater clarity to this topic area. Design/methodology/approach A qualitative interpretivist approach using focus group discussions was adopted to investigate the phenomenon from the perspective of young voters 18–24 years of age. Focus group discussions ceased upon reaching theoretical saturation and a six-staged thematic analytical strategy was adopted to analyse the findings. Findings This study revealed deep insight into the political brand image of non-party brands from the perspective of young voters in an under-explored context. More specifically, this study uncovered that Guernsey’s political brands were seen as “accessible”; however, there was little differentiation, identification and connection between young voters and politicians. Further, this study uncovered a series of opportunities for strategists such as the desire for a younger generational view and younger representation in the Guernsey Parliament and greater clarity, distinction and authenticity related to political brand image. Originality/value This study addresses explicit calls for further research on brand image with a distinct focus on non-party political brands. Further, this study concludes by presenting the “consumer brand image schema”; a systematic framework which can be used to uncover brand image within and beyond the setting of politics. Further, the framework operationalises the complex concept of brand image and provides a three-stage process to examine and develop brand image. This will enable strategists to develop targeted strategies and adopt appropriate tactics to manage brand image to ensure brands are differentiated and interpreted as authentic, relatable, engaging, accessible and identifiable.

Improving strength-conductivity synergy of Al-Cu-(Sn/Er) alloy with nanoscale substructure

As a conductive material for power transmission, Al-Cu alloy is widely used in power engineering, microelectronics and other fields. In view of the contradiction between the conductivity and strength of aluminum alloy, Sn and Er elements were selected to micro-alloy Al-Cu alloy. Al-Cu, Al-Cu-Sn and Al-Cu-Sn-Er alloys were prepared by near-liquidus casting. After solution treatment, it was subjected to three-stage alternating process of rolling and aging. The effects of micro-alloying and alternating process on the microstructure and properties of Al-Cu alloy were studied. The results show that the precipitated phase Al2Cu of Al-1.12 Cu alloy is rod-shaped after the first-stage process, and the average size is about 278±87 nm. The precipitated phases in the Al-Cu-Sn alloy are Al2Cu (average size of about 206±79 nm) and nano-sized β-Sn particles. The fine β-Sn nanoparticles in the Al-Cu-Sn-Er alloy heterogeneously nucleated on Al8Cu4Er (average size of about 167±45 nm), making Al8Cu4Er grow into particles. After secondary processing, stacking faults (SFs) appeared in the substructures of the three alloys, and the precipitated phases were further refined. The size of most precipitated phases in Al-1.13Cu-0.12Sn and Al-1.01Cu-0.15Sn-0.22Er alloys is reduced to nanometer level. After the three-stage process, some of the Al2Cu precipitates in the Al-Cu alloy are also refined to the nanometer level, and the precipitates in the other two alloys are all refined to the nanometer level. Nanotwins also appear in Al-1.01Cu-0.15Sn-0.22Er alloy. The tensile strength of Al-1.13Cu-0.12Sn and Al-1.01Cu-0.15Sn-0.22Er alloys after three-stage alternating process is 303 MPa and 327 MPa, respectively. The elongations are 21.6 % and 23.3 %, respectively. The relative conductivity was 61.7 %IACS and 59.8 %IACS, respectively. The synergistic effect of microalloying of Sn and Er elements and three-stage alternating processing technology not only reduces the size of precipitates and twins in the alloy to the nanometer level, but also adjusts the distribution of dislocation tangles and stacking faults (SFs), improves the substructure configuration, and improves the mechanical and electrical properties of conductive aluminum alloys.

Microscopic study on the memory effect of methane hydrate in the presence of silica nanoparticles: Ⅱ. Residual structure hypothesis & impurity imprinting hypothesis

Based on the hydrate dissociation mechanism and guest supersaturation hypothesis studied in the first part of this series, methane hydrate reformation characteristics affected by memory effect regarding the residual structures hypothesis and impurity imprints hypothesis is further studied to clarify the microscopic mechanism of methane hydrate memory effect during combustible ice exploitation. The initial molecular dynamics simulation configurations containing hydrate residual structures and silica nanoparticles were captured from hydrate dissociation simulation. By analyzing the distribution and transportation of methane molecules, hydrate clusters, and silica nanoparticles, the macroscopically recognized three-stage process of induction-growth-equilibrium for methane hydrate reformation has been verified from microscopic insight. Besides, the orderly arrangement of methane molecules around hydrate residual structures has been found to be essential to promote the growth of hydrate clusters. Moreover, the mutual adsorption between silica nanoparticles-guest nanobubbles and the mutual aggregation between silica nanoparticles-hydrate clusters both affect hydrate reformation process. Combined with the main conclusions derived from the first part of this series, it is found that hydrate memory effect diminishes as hydrate dissociation equilibriums. Thence, the microscopic analysis indicated that the methane hydrate reformation memory effect is influenced by multiple factors, where residual structures are the basis, supersaturated guest is the driving force, and silica nanoparticles are potential threats to form aggregates plugging.

Pengembangan Model Manajemen Pendidikan Islam Berbasis Teknologi untuk Meningkatkan Akses dan Kualitas Pendidikan

This research aims to create a management model that integrates technology effectively in the management and learning process in Islamic educational institutions, so that it can expand the reach of education to more students, including in remote areas, as well as improve the quality of education through the use of technology that supports interaction, collaboration, and learning innovation. A qualitative descriptive method was used in this study, the data collection technique used was a literature study, while the data obtained was analyzed by Miles & Huberman interactive analysis with a three-stage process, namely reduction and presentation of data and drawing conclusions. The results of the analysis found that the development of a technology-based Islamic education management model is important to improve access and quality of education in the digital era. Various technologies present in the development of the digital era help in interactive learning, accessibility, and student performance evaluation, as well as help develop digital skills and character according to Islamic values. With responsive management, Islamic educational institutions can adapt to changes while maintaining the holistic essence of education.