This study aims to design an expert system capable of providing early diagnosis of human psychological disorders using the Forward Chaining method. The research was conducted through a literature review, the development of a knowledge base, and the formulation of rule-based diagnostic structures derived from psychological references, including the DSM-5. The system is designed to identify eight common psychological disorders using twenty primary symptoms that are mapped into IF–THEN rules. The inference process operates by matching user-selected symptoms with the rules contained in the knowledge base. The results indicate that the Forward Chaining method can systematically and logically generate early diagnostic indications for disorders such as depression, anxiety, bipolar disorder, PTSD, and others. A case simulation demonstrates that the reasoning mechanism is able to produce accurate conclusions based on the combination of symptoms entered. Although the system has not yet been implemented as a software application, this study confirms that the conceptual design of an expert system using Forward Chaining can serve as an effective tool for early mental-health detection and has strong potential for further development.

Participatory Design is one of the traditional human-centred approaches commonly used during the early stages of the design process. Currently, Large Language Models and Generative Artificial Intelligence (GenAI) are increasingly being adopted in the early stage of design, particularly for requirements analysis and conceptual design. To harness the respective strengths of Participatory Design and GenAI, it is essential to approach the problem through the lens of multimodal human–machine perception. In this paper, we propose a new multimodal GenAI-Driven Participatory Design approach and develop the Multi-PDAI platform, which is validated in the context of wheeled humanoid robot design. A crossover experiment (N designers = 8, N users = 16) was conducted with evaluation data on the generated images from design industry experts (N = 10). Platform usability was assessed using the SUS scale. In addition, users’ UEQ data and designers’ IMI data were analyzed, with systematic comparisons of initial and final prompt templates, design completion criteria, and time–process metrics. The results show that the images generated by the Multi-PDAI platform are more innovative and aesthetically appealing, and the platform demonstrates better usability compared to Stable Diffusion (M = 72.5, Sig. = 0.043). These findings further support the hypothesis that participatory design and GenAI are mutually beneficial, and that multimodality in GenAI is essential.

Guided missiles are a key weapon in modern warfare, where designers aim to enhance their accuracy and lethality. In the conceptual design phase, the problem of missile trajectory tailoring to hit a specified target emerges. Nonetheless, focusing solely on this design goal may cause degradation in other design aspects such as structural integrity and flight control demands. Therefore, it is highly recommended to integrate flight, control, and structural aspects in the early phases of design. This study focuses on the conceptual phase of a guided surface-to-surface tactical missile trajectory toward a set of predefined targets with constraints. A comprehensive analysis is implemented to solve the trajectory optimization problem of a generic tactical missile. Based on a point-mass three-degree-of-freedom flight model, the optimal-control solver GPOPS is employed to solve this trajectory optimization problem. To ensure realistic and visible trajectory problem solutions, several physical constraints are considered, including minimum and maximum allowable dynamic pressure and maximum allowable rate for flight path angle. The control budget needed for each trajectory problem is discussed. Optimal trajectories ensuring maximum impact velocity via free and constrained flights are evaluated. Furthermore, trajectory problems that balance between minimum control budget and maximum lethality are analyzed.

ABSTRACT Digitally mediated design mediums have revolutionized product design, but their cognitive impact during early concept design stages remains unclear. This study employs cognitive load theory (CLT) and constraint-driven cognition to examine how traditional (TD) and digitally mediated (DM) mediums influence cognitive load, problem-solving, and design outcomes. A quasi-experimental study with 16 design students, divided into TD and DM groups, used two distinct design tasks. Results revealed three key findings. First, the DM medium imposed a significantly higher extraneous cognitive load due to attentional fragmentation and interface management, consuming working memory resources critical for creative synthesis. Second, a fundamental strategic divergence emerged: the TD group engaged in problem-driven cognition through material constraints, yielding higher conceptual novelty (63% vs. 25%) and five times more sustainability considerations. The DM group used solution-driven strategies, leading to more derived outcomes. Third, the cognitive impact was task-dependent; digital tools reduced intrinsic load for well-defined mechanical tasks but offered no advantage for open-ended aesthetic tasks. This study suggests design mediums function as active cognitive environments, not neutral tools. A reevaluation of design education and practice is essential, promoting digital metacognition, retaining tactile skills, and developing hybrid processes that leverage the distinct cognitive benefits of each medium.

The rapid growth of the culinary industry in Purwokerto has led to the emergence of numerous coffee shops with unique and competitive concepts. La Puerto Coffee & Eatery stands out as one of the leading businesses by implementing a green building concept and modern industrial design. This study aims to analyze the business processes of La Puerto using the SWOT and Value Chain methods to identify its strategic position and sustainable development opportunities. The research adopts a descriptive qualitative approach through direct observation, interviews with management and customers, and literature review. The results show that La Puerto’s main strengths lie in its eco-friendly concept, strategic location, and high-quality service, while its weaknesses include limited digitalization and underdeveloped marketing strategies. The Value Chain analysis reveals that most primary activities are effective; however, digital integration needs improvement to enhance efficiency and value creation. Overall, the combination of SWOT and Value Chain analyses provides a comprehensive understanding of business potential, suggesting that digital transformation, service innovation, and community-based marketing are key strategies for sustaining La Puerto Coffee & Eatery’s competitiveness in the dynamic culinary industry.

Abstract Hybrid electric aviation is a possible step towards sustainable flight. Several hybrid architectures and synergetic concepts have been investigated. However, environmental performance results seem to be inconsistent due to deviations in technology assumptions and a mismatch between the fidelity of methodologies used for simulation of different aircraft systems. A multidisciplinary framework is developed, consisting of detailed modelling approaches for thermal and turbomachinery components, electrical power system design, aircraft/mission and environmental analysis. The framework is employed for the investigation of an Entry-Into-Service 2035 30 passenger commuter aircraft with a design mission of 1000 nautical miles. The investigation of parallel hybrid electric, turboelectric and series/parallel partial architectures is performed through a systematic conceptual design approach. The analysis reveals a bare minimum battery technology of 0.75 kWh/kg and 0.8 kW/kg, needed to compete with the conventional aircraft?s performance. High degrees of hybridization (>20%) trigger the snowball effect of aircraft mass and thrust requirement, counteracting specific fuel and performance benefits generated by electrification. The turboelectric and series/parallel partial concepts are paired with an electrically driven boundary layer ingestion fan. For those concepts to result in any block fuel and emissions benefits compared to conventional counterparts, a drag reduction from wake ingestion of 7.5-10% is required, with power split ratios between the electrically driven fan and propellers being limited to 15% due to extensive mass increase.

Abstract We discuss the conceptual design of a spatially-resolved spectroscopy system of Thomson scattering with high wavelength resolution capable of measuring the shape of electron velocity distribution functions in magnetically confined plasmas. We design a spatially-resolved spectrometer with 2560 wavelength channels. The estimated number of scattered photons in a single spectrometer channel is much larger than unity under the experimental setup and plasma parameters of the Compact Helical Device (CHD), indicating sufficient photon statistics for single-shot measurements. Simulations of the scattered spectra show that the signal-to-noise ratio exceeds 5 even under the most unfavorable conditions expected in CHD at full spectral resolution, and further improves with post-processing pixel binning. Bayesian inference applied to the simulated spectra demonstrates that the inferred plasma parameters agree with the input values within the estimated uncertainties. Comparisons between spectra generated from non-Maxwellian electron velocity distribution functions and their Maxwellian fits indicate that deviations from Maxwellian distributions can be identified using the proposed system.

The early stages of structural design increasingly make use of computational tools that support rapid exploration, performance-informed decision-making, and closer interaction between design and engineering. This systematic mapping study examines how Algorithm-Aided Design (AAD) and the Finite Element Method (FEM) are applied and combined in conceptual design workflows. Based on a structured search across three academic databases and a coding scheme applied to 87 publications, the literature is mapped according to algorithmic strategies, FEM applications, element types, disciplinary domains, and levels of integration. The results show that algorithmic and predictive approaches are reported with increasing frequency after 2020, alongside growing use of surrogate models and optimisation routines. Linear-elastic analyses and shell- or beam-based models are frequently reported, particularly in civil engineering contexts, while nonlinear, dynamic, and solid-element analyses appear more prominently in mechanical domains. More tightly coupled AAD–FEM workflows become increasingly visible after 2021, reflecting a growing interest in real-time or near-real-time simulation feedback during early design exploration. At the same time, the literature highlights persistent challenges related to computational cost, fragmented toolchains, limited interoperability, and the relatively limited use of multiscale or advanced material models in conceptual design. Taken together, the findings suggest that continued progress toward more integrated AAD–FEM workflows is closely tied to advances in computational efficiency, improved data exchange and interoperability, and the development of more accessible design–analysis environments across disciplinary boundaries.

Purpose The purpose of this paper is to examine how agentic artificial intelligence may influence the future of library services. It discusses the nature of agentic systems, how they are evolving, what other sectors are learning from their use and what librarians should consider as these tools become more common. Design/methodology/approach This paper uses a conceptual and narrative design. It draws on current discussions to provide an informed reflection on the development of agentic artificial intelligence and its implications for library services. Findings This paper finds that agentic artificial intelligence is shifting from simple response-based technologies to systems that can interpret situations, initiate tasks and adjust their behaviour. Evidence from other sectors shows that agentic systems can support decision-making, reduce routine work and improve co-ordination when used with appropriate oversight. For libraries, these developments suggest opportunities for more responsive services, new forms of user support and enhanced workflow management. Originality/value To the best of the author’s knowledge, this paper is one of the early practice-focused reflections on agentic artificial intelligence within a library context. The discussion in this paper supports planning by providing opportunities and challenges associated with the integration of agentic systems in library environments.

The fast spread of artificial intelligence (AI) in the United States organizations has radically altered the managerial decision-making process, but on the other hand, it has augmented the complexity and uncertainty in decision, and the accountability stresses. Despite the high-level predictive and prescriptive potentials of AI-based analytics, most organizations have difficulties converting algorithmic results into sustainable managerial decisions. Low levels of trust, lack of explanation, and poor integration between AI systems and human judgment have been caused by over reliance on automation, weak explain ability, and poor organizational outcomes. Current literature has majorly focused on automation-based views of decision support, with a severe lack of insight into the coordinated manner in which human experience and AI intelligence can be systematically integrated with the assistance of analytics. This paper fills this gap by outlining a Human-AI Collaborative Decision Analytics Framework that could be beneficial to improve managerial decisions and organizational performance. Following a conceptual research design, the study integrates interdisciplinary literature in the field of managerial decision-making theory, business analytics, and governance of AI in its attempt to establish an integrative framework where analytics becomes the focal interpretive intercession between AI outputs and human decision-makers. The framework has five overlapping layers such as data, AI analytics, business analytics interpretation, human judgment, and feedback learning that combine to facilitate transparency, accountability, and contextual decision-making. The framework is depicted in the most important areas of the organization with the main focus on the strategic management and workforce decision-making and the secondary focus on the finance, operations, and marketing. The framework minimizes the effects of the algorithmic bias, automation bias, and enhances workforce confidence through embedding managerial control and ethical reasoning and contextual evaluation frameworks into the workflows of AI-assisted decision-making. The contribution of the study to the theory is that it develops human-grounded decision analytics and to practice by providing practical advice to executives and analytics leaders. The presented framework contributes to the responsible use of AI, productivity, and economic competitiveness in the United States in the long term.

Diabetes mellitus is a global health challenge requiring sustained self-management. Evidence highlights the role of families in supporting adults with diabetes mellitus, yet many interventions fail to adopt structured, theory-informed, and family-centred approaches. To address this gap, the psychoeducational intervention "Juntos com a Família + Capazes" (Together with Family + Capable) was developed within the Medical Research Council Framework for Complex Interventions, integrating empirical evidence, theoretical models, and stakeholder input. This study conducted a pre-intervention conceptual validation, exploring perspectives of healthcare professionals, adults with Type 1 and Type 2 diabetes mellitus, and family members on its structure, content, and feasibility. A qualitative descriptive design was applied. Focus groups interviews with healthcare professionals, adults with diabetes mellitus, and family members, were guided by a semi-structured interview guide. Sessions were audio-recorded, transcribed, and analysed using deductive qualitative content analysis with independent manual coding and consensus discussions. Three focus groups were held (n = 19): two with healthcare professionals and one with adults with diabetes and family members, separated due to participant availability and feasibility constraints. Participants critically reflected on the pre-implementation conceptual design of the programme, described as a six-month intervention with a six-month follow-up, structured into seven modules and delivered flexibly across 7-12 sessions. They endorsed the overall structure and content while suggesting refinements to module sequencing and module titles. Participatory strategies, tailored motivational phone calls, and strong family involvement were considered essential for engagement, sustained behavioural change, and feasibility. Analysis revealed both convergent themes and stakeholder-specific perspectives, integrating clinical expertise with lived experience. The "Juntos com a Família + Capazes" programme was conceptually validated, prior to implementation, as a family-centred, theory-informed, and adaptable intervention for adults with diabetes mellitus and their families. This pre-implementation phase enables refinements to content, sequencing, language, and delivery strategies, strengthening cultural relevance, acceptability, and feasibility. Conducting conceptual validation before piloting ensured that both clinical expertise and lived experiences shaped the intervention, highlighting the value of focus groups in identifying adjustments that enhance its real-world applicability. Future research should evaluate its effectiveness, sustainability, and scalability across healthcare contexts.

As consumer behaviours, cultures, and technologies evolve, restaurants must adapt, and fast casual formats represent innovative responses to these shifts. The present study aims to identify the key attributes defining Fast Casual 2.0 and evaluate their importance. Conjoint Analysis with 144 participants was used to assess 16 designed restaurant profile cards. Findings highlight six critical dimensions, with accessibility, atmosphere, service differentiation, and sustainability prioritized, while price promotions and standardized branding proved less influential. The study contributes to consumer behaviour literature by demonstrating how consumers balance hedonic, experiential, and sustainability expectations in hybrid dining formats, offering guidance for competitive concept design.

Background: The routine analysis of CD4+ T-lymphocyte percentages and absolute counts in HIV patients commonly employs the dual-platform method (blood cell analyzer and flow cytometer). However, variability related to equipment, methodology, or operator performance may affect accuracy. This study introduces the single-platform method, which relies solely on a flow cytometer to reduce variability, streamline workflow, and shorten turnaround times, in alignment with the Rational Laboratory Use guidelines of the Department of Medical Sciences, Ministry of Public Health. Objectives: To evaluate and compare the single-platform and dual-platform methods for determining CD4+ T-lymphocyte percentages and absolute counts. Materials and methods: The study was conducted from January 24 to November 29, 2024, encompassing the entire research process — from conceptual development, problem analysis, and study design to data collection, statistical analysis, interpretation, and application of findings. Routine diagnostic data were collected from HIV-infected patients in Trat Province, Thailand, between April 1 and July 31, 2024, as part of the data collection phase. Samples were analyzed using a semi-automated blood cell analyzer and a flow cytometer, and results were compared with those obtained using the single-platform method, which employed only the flow cytometer. Statistical analyses were performed to assess the accuracy, precision, and reliability of the singleplatform method compared with the conventional approach. Descriptive statistics, correlation, linear regression, and Bland–Altman analysis were applied to evaluate agreement and systematic bias. All statistical tests were conducted at a 95% confidence interval, with p-values <0.05 considered statistically significant. Results: Both methods produced data that followed a normal distribution (Kolmogorov–Smirnov test; p>0.05). Correlation coefficients demonstrated excellent agreement for CD4+ T-lymphocyte percentages (r=0.9914) and absolute counts (r=0.9697). Linear regression analysis showed a strong association, with r²=0.9403 for absolute counts. Bland–Altman analysis indicated a mean difference of 61.06 cells/μL (95% CI: -73.91 to 196.04), with most values falling within the confidence limits. Among patients with CD4+ T-lymphocyte percentages ≤ 20%, the mean difference was 28.56 cells/μL (95% CI: -61.98 to 119.09). Conclusion: The single-platform method is comparable to the dual-platform method for analyzing CD4+ T-lymphocytes in HIV patients. Both methods demonstrated normal data distribution, confirming statistical robustness. High correlations for percentages and absolute counts ensured consistent and reliable results, while regression analysis indicated strong predictive capability of the single-platform method for dual-platform results. Bland–Altman analysis further confirmed the equivalence of the two methods, supporting the reliability of the single-platform approach. Overall, the singleplatform method offers a reliable and efficient alternative, reducing variability, workload, and turnaround time in laboratory settings while maintaining analytical accuracy.

Food security in Indonesia is influenced by the dynamics of production, distribution, and availability between regions. However, many existing information systems still rely on conventional data structures without semantic integration, which limits interoperability and hinders interregional analysis. To address this gap, this study developed an ontology model based on the Web Ontology Language (OWL) that formally represents the relationships between food production, commodity characteristics, distribution flows, food insecurity conditions, and geographical context. The ontology was built using Protégé through stages of literature review, official data collection from BPS, FAO, and the Ministry of Agriculture, conceptual model design, implementation, and evaluation. Conceptual validation was conducted through Focus Group Discussions (FGD) with food supply chain experts to ensure the suitability of the ontology structure and the actual conditions of the national food system. The technical evaluation involved consistency testing using the Pellet reasoner and Competency Question (CQ) testing through SPARQL queries to assess the ontology's ability to respond to essential information needs. The resulting ontology consists of five core classes (FoodProduction, FoodItem, FoodDistribution, FoodSecurityStatus, and GeographicRegion) which collectively represent the semantic structure of Indonesia's food supply chain. The evaluation results show that the ontology is structurally consistent and capable of producing outputs that are in line with CQ, including the retrieval of production-distribution information and the initial identification of commodity surpluses and deficits based on instance data. These findings indicate that the developed ontology provides a coherent semantic foundation for modeling food systems and has strong potential to support the development of knowledge-based food security management applications.

Conceptual design and 4E analysis of an ammonia synthesis process integrating methane thermal decomposition and dual chemical looping

Conceptual design and analysis of a tube-launched fixed-Wing UAV with integrated folding wing systems

Lateral-directional trim for air and ground minimum control speeds evaluation in conceptual design

The impact of childhood emotional maltreatment on adulthood smoking behaviour: A systematic review and narrative synthesis.

Sustainability-oriented product conceptual innovation design method based on evolution potential prediction

Research on conceptual design process model based on function association