Search Results (536)

A conceptual design study is presented for a hemispherical, two-chamber water Cherenkov detector instrumented with bladder-embedded light traps. The detector consists of a rigid aluminium vessel enclosing a water volume that is divided into an outer, optically black chamber and a inner, reflective chamber lined by a flexible bladder. Arrays of light-trap modules, based on plastic scintillators with wavelength-shifting elements and thin silicon photomultipliers, are integrated into the bladder and selected inner surfaces. This geometry is intended to enhance muon tagging, increase acceptance for inclined air showers, and enable improved discrimination between electromagnetic and hadronic components. The study describes the mechanical and optical layout of the detector, the baseline aluminium housing, and the use of 3D-printed hexagonal prototypes to validate integration of the bladder and readout electronics. A first-order structural assessment based on thin-shell and plate theory is presented, indicating large safety margins for the hemispherical shells and identifying the flat base as the mechanically most loaded component. While GEANT4 simulations for detector response to extensive air showers in the atmosphere and performance measurements are left to future work, the present study establishes a mechanically validated, costed baseline design and outlines the steps needed to assess its impact in air-shower arrays. Full article

Despite the increased interest in neuromorphic materials—a physical implementation of neural networks that could overcome the so-called von Neumann architecture’s limitations—most studies have been performed on the basis of systems specially constructed for this purpose. It has previously been shown that analogues of neural networks can spontaneously arise in solutions of hydrophilic polymers, but these systems involved molecules of different natures or required direct interaction between macromolecular clusters. The present paper proposes a theory that indicates the possibility of an analogue of neural network formation even in a single-component solution of a relatively weak polyacid. A model is suggested based on the account of heterogeneous distribution of polymer ionogenic groups within the volume leading to the fluctuations of electric fields and, as a result, to the local changes in the degree of ionisation of functional groups. Theoretical description of the system shows how it was reduced to a solution of the analogue based on the Poisson–Boltzmann equation. The results obtained showed that it is just fluctuations in the distribution of charges that provide the collective response of the system to external influences and serve as an argument in favour of analogy of such a solution within a neural network. The results are discussed in the context of a potential simple hydrophilic polymer system as a prototypical neuromorphic and evolving material that is relevant for organic electronics, metamaterials, and studies on prebiological evolution. Full article

Targeted coverage of crushed grass segments under the fruit tree canopy synergistically achieves the agronomic goals of soil moisture conservation, weed suppression, and soil fertility improvement. To address issues like incomplete grass cutting and high risk of damaging fruit trees in complex orchard environments with traditional mowing devices, a lateral grass discharge blade for orchard mowers was designed. Based on airflow field theory, the dynamic basis of the airflow field, critical conditions for carrying crushed grass segments, and their movement laws on the blade and in the air were analyzed to identify key factors affecting discharge. CFD simulations were conducted using the Flow Simulation module of SolidWorks 2021 to explore the effects of the blade airfoil’s long side, short side lengths, and horizontal included angle on the outlet velocity and outlet volumetric flow rate of crushed grass segments, determining the reasonable parameter range. With these three as test factors and the two indicators above, orthogonal tests and parameter optimization were performed via Design-Expert 13.0 software, yielding optimal parameters: long side 125 mm, short side 35 mm, horizontal included angle 60°, corresponding to 9.105 m/s outlet velocity and 0.045 m³/s volume flow rate. A prototype mowing device with these parameters was fabricated for orchard field tests. Results show an average stubble stability coefficient of 94.2%, average over-stubble loss rate of 0.39%, and crushed grass segment distribution variation coefficient of 23.8%, meeting orchard mower operation requirements and providing technical support for orchard weed mowing, coverage, and utilization. Full article

Driven by global initiatives to mitigate climate change, the offshore wind power industry is experiencing rapid growth. Personnel transfer between service operation vessels (SOVs) and offshore wind turbines under complex sea conditions remains a critical factor governing the safety and efficiency of operation and maintenance (O&M) activities. This study establishes a fully coupled dynamic response and control simulation framework for an SOV equipped with an active motion-compensated gangway. A numerical model of the SOV is first developed using potential flow theory and frequency-domain multi-body hydrodynamics to predict realistic vessel motions, which serve as excitation inputs to a co-simulation environment (MATLAB/Simulink coupled with MSC Adams) representing the Stewart platform-based gangway. To address system nonlinearity and coupling, a composite control strategy integrating velocity and dynamic feedforward with three-loop PID feedback is proposed. Simulation results demonstrate that the composite strategy achieves an average disturbance isolation degree of 21.81 dB, significantly outperforming traditional PID control. Validation is conducted using a ship motion simulation platform and a combined wind–wave basin with a 1:10 scaled prototype. Experimental results confirm high compensation accuracy, with heave variation maintained within 1.6 cm and a relative error between simulation and experiment of approximately 18.2%. These findings demonstrate the framework’s capability to ensure safe personnel transfer by effectively isolating complex vessel motions and validate the reliability of the coupled dynamic model for offshore operational forecasting. Full article

Multi-use of sea space is increasingly seen as a tool for efficient marine resource management, renewable energy utilisation, and sustainable food production. Multi-use Offshore Installations combine two or more production technologies on a single platform at sea. However, achieving commercial viability faces several challenges: social, technical, environmental, and economic. This research focuses on the social aspect, investigating community perceptions of a multi-use offshore installations over three years from 2019 to 2021. Our research was conducted in Reggio Calabria, Italy, where a prototype was deployed in 2021, and Islay, Scotland, suitable for a full-scale multi-use offshore installation but with no deployment, using community surveys. We used the theories of Social License to Operate and Institutional Analysis and Development to frame our analysis. Our findings indicate that coastal communities prefer wind turbines over fish farming, have low trust in public officials to regulate environmental impacts of a multi-use offshore installation, and that short-term deployment of a prototype does not significantly change opinions. We reflect on the challenges of understanding societal opinions of a multi-use offshore installation, given complex boundary conditions, and that multi-use offshore installations combine familiar technologies into a new and unknown form. We suggest that future research should explore the scale of deployment needed to crystallise community opinions, and the role of regulators in developing social license to operate for multi-use offshore installations. Full article

Engineering programmes have been giving more weight to experiential learning, largely because many students still find it difficult to see how classroom theory connects to the work that engineers handle on the ground. With this in mind, a robotics-centred Project-based Learning (PBL) module was introduced to first-year general engineering students as part of the faculty’s engineering spine. The module asks students to design, build, and program small autonomous robots capable of navigating and competing in a set arena. Even a simple task of this kind draws together multiple strands of engineering. Students shift between sketching mechanical layouts, wiring basic circuits, writing code, testing prototypes, and negotiating the usual challenges that arise when several people share responsibility for the same piece of hardware. To explore how students learned through the module, a mixed-methods evaluation was carried out using survey responses alongside reflective pieces written by the students themselves. Certain patterns appeared repeatedly. Many students felt that their technical skills had grown, particularly in breaking down a messy problem into smaller, more workable components. Teamwork also surfaced as a prominent theme. Groups often had to sort out issues such as a robot veering off course due to a misaligned sensor or a block of code producing unpredictable behaviour. These issues were undoubtedly challenging for the students, but they also had a certain pedagogical flavour, with many students describing them as a source of frustration as well as a learning opportunity. Later iterations of the module may benefit from more targeted support at key stages. Despite the many challenges, robotics has been shown to be an attractive way for students to step into engineering practice. The project helped them build technical capability, but it also encouraged habits that matter just as much in real work, such as planning, communicating clearly, and returning to a problem until it behaves as expected. Taken together, the experience offers useful guidance for curriculum designers seeking to create early learning environments that feel authentic and manageable and for motivating students who are just beginning their engineering journey. Full article

This study examines how undergraduate design students imagined and critiqued biotechnological futures through speculative work with generative AI in a semester-long biodesign course. Using inductive qualitative coding and visual discourse analyses, we traced how students’ prompts, images, and reflections reveal an evolving grammar of speculation. Students shifted from crisis description to design-oriented possibility and socio-political reasoning about ecological, cultural, and ethical implications. Generative AI supported this shift by offering visual feedback that enabled students to recognize assumptions and critically examine speculative designs. Through repeated cycles of prompting and refinement, students advanced biodesign prototypes and developed a nuanced understanding of AI’s affordances and limits. Extending constructionism learning theories into speculative design with generative AI, this study examines how learners externalize discursive and imaginative thought through prompt-crafting. These findings articulate a grammar of speculation, showing how generative AI mediates critical AI literacy as a discursive and constructionist learning process. Full article

Numerous attempts to define art have been made from antiquity to the present, yet historical overviews often adopt a Eurocentric (and American-centric) perspective focused mainly on culturally dependent aesthetic approaches. As a universal social and cultural phenomenon, art resists center-periphery models. The cognitive turn reshaped art theory by reconsidering art as a cognitive dimension of humanity. Art has no limits on who can create or enjoy it. The ability to use and understand metaphor, for instance, demonstrates everyday human artistic cognition. The analysis relies on both field research (case studies) and academic literature; it argues for a revised theoretical frame for defining art and organizes it into a dynamic model of three main vectors: (1) art as communication (including art as agency); (2) art as creation; and (3) art as experience (involving both audience and artist). The model can incorporate the study of emotions into the third criterion while remaining open to both materialist and non-materialist approaches. Rather than offering a new definition, the study integrates the perspective of cognitive anthropology, cognitive semantics, and the anthropology of art in order to broaden understanding. Instead of searching for special aesthetic or economic values, these three dimensions of art appear more universal. A pragmatic analysis of how art “works” in individuals and groups provides a useful model for cognitive sciences. Instead of binary codes, it is a vectorial model, a 3D space for expressing family resemblance, since there is no common denominator (prototype) for all kinds of art. Full article

Five-axis precision dispensing machines are employed for semiconductor packaging. The dispensing accuracy is significantly affected by multiple geometric errors among the five axes. This paper proposes a vision-based measurement (VBM) system for identifying geometric errors and calibrating kinematics. The VBM system is also employed to complete the detection of the workpiece. A kinematic model of the machine was established using a local product-of-exponential formulation of screw theory. A geometric error identification algorithm was designed. Eight position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs) were involved. The system of overdetermined equations was solved. Combining the singular value decomposition and regularization, eight PIGEs in the A and C axes were identified. Comprehensive error measurement results verified the proposed approach. The VBM system measured a mean spatial position error of approximately 59.9 μm and a mean orientation error of about 160 arcsec for the end-effector, reflecting the geometric error level of the prototype machine. The proposed approach provides a feasible and automated calibration solution for five-axis precision dispensing machines. Full article

A window-embedded broadband vehicle-mounted antenna for frequency modulation (FM) broadcast application is proposed. Antenna miniaturization at sub-gigahertz frequencies remains challenging due to the inherently long wavelengths, which impose strict constraints on compactness, bandwidth, and structural weight. A promising strategy to alleviate this problem is to use the vehicle itself as an effective radiator to enhance the bandwidth and maintain good radiation performance. In this work, the potentialities of the radiation patterns offered by the vehicle are analyzed by using the characteristic mode theory (CMT). A compact T-shape coupling element, with dimensions of 0.2λ₀ × 0.08λ₀ × 0.01λ₀, is employed to simultaneously excite multiple significant characteristic modes, thereby broadening the operating band. Both simulated and measured results validate that the proposed antenna can cover the FM broadcast operating band from 87 MHz to 108 MHz, with the 1:10 scaled prototype achieving a maximum measured gain of 7.4 dBi at 950 MHz. The proposed antenna and design strategy have advantages in radio broadcasting, radio navigation, and military and law enforcement communication systems for its low-cost, compact, and easy conformal structure. Full article

To address the issues of imprecise user segmentation, inadequate handling of fuzzy evaluation information, and low recommendation accuracy in current electricity retail package recommendations, a novel recommendation method based on K-prototypes clustering and interval-valued intuitionistic fuzzy theory is proposed. First, a multi-dimensional user profile is constructed, incorporating five numerical tags—such as monthly average electricity consumption and monthly load factor—and two categorical tags: industry characteristics and value-added service demand. The K-prototypes algorithm is employed to cluster users, effectively resolving the profile distortion problem caused by the neglect of categorical features in traditional K-means clustering. Second, interval-valued intuitionistic fuzzy numbers are introduced to transform user linguistic evaluations into quantitative indicators. A projection measure-based model is established to objectively determine attribute weights, thereby eliminating subjective weighting bias. Finally, a comprehensive ranking of electricity retail packages is generated by integrating satisfaction levels of similar users and similar measures of new users. The recommendation performance is validated using Root Mean Square Error (RMSE), Kendall’s τ, Normalized Discounted Cumulative Gain (NDCG@5), and Discrimination Index (S). A case study involving users from a region in China demonstrates that the proposed method reduces the Root Mean Square Error (RMSE) to 0.32, which is 31.25% lower than the next best traditional method (K-prototypes + equal weight clustering with RMSE = 0.48), accurately addresses the core demands of diverse user groups, significantly improves recommendation precision and user satisfaction, and exhibits substantial practical application value. Full article

Limited workspace and singularities are major challenges for parallel mechanisms. This article addresses these issues for a 4-DOF 1-SPS/3-RRRRR parallel mechanism with a circular rail, proposed in our prior work. The mechanism has a 3R1T motion type with a movable center of spherical motion. The paper begins with a detailed description of the mechanism design. A closed-form solution of the inverse kinematics follows next, which computes the active joint coordinates and determines the spatial positions of all joints and links. Based on this solution, an iterative approach is applied to analyze the workspace for three different heights of the spherical motion center. The analysis reveals the regions of a full twist about the platform symmetry axis, bounded by maximum tilt angles of 51°, 38°, and 23°, respectively. Introducing joint constraints significantly reduces the workspace, limiting the tilt angles to 21°, 26°, and 0° at the same heights. Subsequently, screw theory is applied to identify serial, parallel, and constraint singularities, and an iterative approach is used to find the boundary of the singularity-free workspace. The analysis shows that the full-twist tilt angles are limited to 33°, a value determined solely on the platform geometry and independent of the spherical motion center height. These results establish a foundation for the design optimization and prototyping of the mechanism. Full article

This study presents a systematic literature review of 58 peer-reviewed publications on blockchain-based project management to examine the dominant research methods and theoretical approaches in the field. Using an established Information Systems theory classification framework, the review classifies existing studies into four categories: Explicit Theory-Driven, Conceptual/Framework-Oriented, Design Science/Artifact-Oriented, and Descriptive/Empirical without Theory. Findings reveal that current research is largely technology-centric, with nearly 70% of studies adopting design-science or artifact-oriented methods and fewer than 10% engaging explicit theoretical foundations. This indicates that blockchain-project management scholarship remains in a pre-theoretical stage, focusing primarily on prototype development rather than explanatory or predictive theorizing. A clear method–theory coupling also emerges, where design-science methods align with artifact creation, quantitative surveys with theory-driven studies, and qualitative cases with descriptive work. Temporal patterns show gradual movement toward theory-informed and mixed-method research, signaling early maturation of the field. The review concludes by outlining three priorities for future research: translating design insights into theoretical constructs, developing hybrid frameworks that integrate behavioral and institutional perspectives, and adopting multi-level approaches to examine blockchain’s impact across project ecosystems. These insights provide a structured foundation for advancing both scholarly theory and practical applications in blockchain-enabled project management. Full article

Taking a large single-phase generator transformer product as the research object, this paper applied the finite element simulation method to analyze the vibration characteristics of its core. Firstly, through the analysis of vibration theory, the vibration laws and characteristics of the core are clarified, and a three-dimensional equivalent model of the transformer is constructed. The B-H curve of the silicon steel sheet is measured through experiments and used for the assignment of the core material when calculating the electromagnetic field later. Then, based on the simulation calculation of multi-physical field coupling, the no-load current on the primary side, the distribution and variation characteristics of the magnetic field inside the core are solved and analyzed. On this basis, the sequential coupling method was adopted to solve the displacement distribution of the core vibration and the displacement changes at different position points and conduct a comparative analysis. Subsequently, the accuracy of the simulation calculation method was verified through the test of a small prototype. Finally, based on the comparison of the dry and wet modal simulation results, the impact of transformer oil on the vibration characteristics of the core was evaluated and analyzed. It can be seen from the analysis that the core vibration is generally more intense at the upper part and corners; the impact of the internal oil flow on the vibration of the body of large transformers is relatively complex and thus cannot be ignored. Full article

The transition to sustainable food systems requires communication strategies that resonate with consumers’ values, not only technological innovation. This study examines how values-centric communication can shape German consumers’ responses to alternative proteins, focusing on insect-based snacks. A desk-based synthesis of recent studies, guided by Schwartz’s value theory, identified Tradition and Security as dominant drivers of food choice and yielded five communication requirements: Cultural familiarity, Emotional safety, Simplicity and clarity, Trust and credibility, and Routine integration. These were operationalised into communication guidelines and short on-pack claims, which were applied to a refined packaging prototype. An exploratory focus group (N = 7) then compared reactions to the original versus the refined packaging, analysed using McGuire’s communication–persuasion stages. Within this small exploratory group, participants reported that familiar formats, a reassuring tone, clear visual hierarchy, and salient trust cues made them more willing to consider trying the product, whereas information overload, claim–image incongruence, value-incongruent brand naming, and delayed recognition of insect content appeared to impede acceptance. The study contributes an integrative analytic lens combining Schwartz’s value theory with McGuire’s model and a set of testable guidelines for value-aligned food communication. Because the empirical evidence is based on a single small student focus group with fixed presentation order, bundled manipulations, and hypothetical intentions, these results are exploratory and self-reported and should be interpreted cautiously; future research should employ counterbalanced factorial designs with behavioural outcomes. Full article