Search Results (3,504)

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

A real-space renormalization group (RG) framework is formulated for classical SO(n) spin models defined on d-dimensional crystal lattices composed of corner-sharing hyper-tetrahedra, a class of geometrically frustrated crystal structures. This includes, as specific instances, the classical Heisenberg model on the kagome and pyrochlore crystals. The approach involves computing the partition function and corresponding order parameters for spin clusters embedded in the crystal, to leading order in symmetry-breaking fields generated by surrounding spins. The crystal geometry plays a central role in determining the scaling relations and the associated critical behavior. To illustrate the efficacy of the method, a reduced manifold of symmetry-allowed ordered states for isotropic nearest-neighbor interactions is analyzed. The RG flow systematically excludes the emergence of a $\overrightarrow{q}=\mathbf{0}$ ordered phase within the antiferromagnetic sector, independently of both the spatial dimensionality of the crystal and the number of spin components. Extensions to incorporate more elaborate crystal-symmetry-induced ordering patterns and fluctuation-driven phenomena—such as order-by-disorder—are also discussed. Full article

The a priori procedure (APP) is concerned with determining appropriate sample sizes to ensure that sample statistics to be obtained are likely to be good estimators of corresponding population parameters. Previous researchers have shown how to compute a priori confidence interval means or locations for normal and skew-normal distributions. However, two critical limitations persist in the literature: (1) While numerous skewed models have been proposed, the APP equations for location parameters have only been formally established for the basic skew-normal distributions. (2) Even within this fundamental framework, the APPs for sample size determinations in estimating locations are constructed on samples of specifically dependent observations having multivariate skew-normal distributions jointly. Our work addresses these limitations by extending a priori reasoning to the more comprehensive unified skew-normal (SUN) distribution. The SUN family not only encompasses multiple existing skew-normal models as special cases but also enables broader practical applications through its capacity to model mixed skewness patterns and diverse tail behaviors. In this paper, we establish APP equations for determining the required sample sizes and set up confidence intervals for the location parameter in the one-sample case, as well as for the difference in locations in matched pairs and two independent samples, assuming independent observations from the SUN family. This extension addresses a critical gap in the literature and offers a valuable contribution to the field. Simulation studies support the equations presented, and two applications involve real data sets for illustrations of our main results. Full article

This study presents a cross-cultural comparison of two fortified residences—Palazzo Farnese in Italy and Dong’s Fortified Compound in China—through a triadic analytical framework encompassing architectural form, symbolic ornamentation, and public perception. By combining field observation, iconographic interpretation, and digital ethnography, the research investigates how heritage meaning is constructed, encoded, and reinterpreted across distinct sociocultural contexts. Empirical materials include architectural documentation, decorative analysis, and a curated dataset of 4947 user-generated images and 1467 textual comments collected from Chinese and international platforms between 2020 and 2024. Methods such as CLIP-based visual clustering and BERTopic-enabled sentiment modelling were applied to extract patterns of perception and symbolic emphasis. The findings reveal contrasting representational logics: Palazzo Farnese encodes dynastic authority and Renaissance cosmology through geometric order and immersive frescoes, while Dong’s Compound conveys Confucian ethics and frontier identity via nested courtyards and traditional ornamentation. Digital responses diverge accordingly: international users highlight formal aesthetics and photogenic elements; Chinese users engage with symbolic motifs, family memory, and ritual significance. This study illustrates how historically fortified residences are reinterpreted through culturally specific digital practices, offering an interdisciplinary approach that bridges architectural history, symbolic analysis, and digital heritage studies. Full article

This study presents a novel method for controlling the position and orientation of the bioinspired I-SUPPORT soft robot, which represents a relevant advancement in the field of soft robotics. The approach is based on module actuation decoupling and fractional-order control, offering a more advanced and robust control solution. This innovation enhances the versatility of the robot and illustrates the efficacy of fractional-order controllers, which are comparable to current meta-learning-based controllers. The research involves experiments in both vertical and horizontal configurations, addressing tasks ranging from simple orientation to complex interactions, such as gentle rubbing during bathing activities with the robot. These experimental results exemplify the efficacy of the proposed control strategy and provide a foundation for future research in soft robotics control, underscoring its potential for broader applications and further technological advancement. Full article

The discharge of oily wastewater threatens the ecosystem and human health, and the efficient treatment of oily wastewater is confronted with problems of high mass transfer resistance at the oil-water-solid multiphase interface, significant light shielding effect, and easy deactivation of photocatalysts. Although traditional physical separation methods avoid secondary pollution by chemicals and can effectively separate floating oil and dispersed oil, they are ineffective in removing emulsified oil with small particle sizes. To address these complex challenges, photocatalytic technology and photocatalysis-based improved technologies have emerged, offering significant application prospects in degrading organic pollutants in oily wastewater as an environmentally friendly oxidation technology. In this paper, the degradation mechanism, kinetic mechanism, and limitations of conventional photocatalysis technology are briefly discussed. Subsequently, the surface interface modulation functions of metal doping and heterojunction energy band engineering, along with their applications in enhancing the light absorption range and carrier separation efficiency, are reviewed. Focus on typical studies on the separation and degradation of aqueous and oily phases using photocatalytic membrane technology, and illustrate the advantages and mechanisms of photocatalysts loaded on the membranes. Finally, other new approaches and converging technologies in the field are outlined, and the challenges and prospects for the future treatment of oily wastewater are presented. Full article

This study focuses on investigating the asymptotic and oscillatory behavior of a new class of fourth-order nonlinear neutral differential equations. This research aims to achieve a qualitative advancement in the analysis and understanding of the relationships between the corresponding function and its derivatives. By utilizing various techniques, innovative criteria have been developed to ensure the oscillation of all solutions of the studied equations without resorting to additional constraints. Effective analytical tools are provided, contributing to a deeper theoretical understanding and expanding their application scope. The paper concludes by presenting examples that illustrate the practical impact of the results, highlighting the theoretical value of the research in the field of functional differential equations. Full article

Plant microbiomes are vital for the growth and health of their host. Tree-associated microbiomes are shaped by multiple factors, of which the host is one of the key determinants. Whether different host genotypes affect the structure and diversity of the tissue-associated microbiome and how specific taxa enriched in different tree tissues are not yet well illustrated. Chinese fir (Cunninghamia lanceolata) is an important tree species for both economy and ecosystem in the subtropical regions of Asia. In this study, we investigated the tissue-specific fungal community structure and diversity of nine different Chinese fir genotypes (39 years) grown in the same field. With non-metric multidimensional scaling (NMDS) analysis, we revealed the divergence of the fungal community from rhizosphere soil (RS), fine roots (FRs), and thick roots (TRs). Through analysis with α-diversity metrics (Chao1, Shannon, Pielou, ACE, Good‘s coverage, PD-tree, Simpson, Sob), we confirmed the significant difference of the fungal community in RS, FR, and TR samples. Yet, the overall fungal community difference was not observed among nine genotypes for the same tissues (RS, FR, TR). The most abundant fungal genera were Russula in RS, Scytinostroma in FR, and Subulicystidium in TR. Functional prediction with FUNGuild analysis suggested that ectomycorrhizal fungi were commonly enriched in rhizosphere soil, while saprotroph–parasite and potentially pathogenic fungi were more abundant in root samples. Specifically, genotype N104 holds less ectomycorrhizal and pathogenic fungi in all tissues (RS, FR, TR) compared to other genotypes. Additionally, significant correlations of several endophytic fungal taxa (Scytinostroma, Neonothopanus, Lachnum) with the growth traits (tree height, diameter, stand volume) were observed. This addresses that the interaction between tree roots and the fungal community is a reflection of tree growth, supporting the “trade-off” hypothesis between growth and defense in forest trees. In summary, we revealed tissue-specific, as well as host genotype-specific and genotype-common characters of the structure and functions of their fungal communities. Full article

To address the issues of bulky structure and complex transmission systems in current transplanters, a compact, electric-driven automatic transplanter was designed. Using pepper plug seedlings as the test subject, this study investigated plug tray dimensions and planting patterns. According to the design requirement that the width of the single-row transplanter must be less than 62.5 cm, a three-dimensional transplanter model was constructed. The transplanter comprises a coaxially installed dual-layer seedling conveying device and a sector-expanding automatic seedling picking and depositing device. The structural dimensions, drive configurations, and driving forces of the transplanter were also determined. Finally, the circuit and pneumatic system were designed, and the transplanter was assembled. Both bench and field tests were conducted to select the optimal working parameters. The test results demonstrated that the seedling picking and depositing mechanism met the required operational efficiency. In static seedling picking and depositing tests, at three transplanting speeds of 120 plants/min, 160 plants/min, and 200 plants/min, the success rates of seedling picking and depositing were 100%, 100%, and 97.5%, respectively. In the field test, at three transplanting speeds of 80 plants/min, 100 plants/min, and 120 plants/min, the transplanting success rates were 94.17%, 90.83%, and 88.33%, respectively. These results illustrate that the compact, electric-driven seedling conveying and picking and depositing devices meet the operational demands of automatic transplanting, providing a reference for the miniaturization and electrification of transplanters. Full article

In this article, we investigate the fractional soliton solutions as well as the chaotic analysis of the fourth-order nonlinear Ablowitz–Kaup–Newell–Segur wave equation. This model is considered an intriguing high-order nonlinear partial differential equation that integrates additional spatial and dispersive effects to extend the concepts to more intricate wave dynamics, relevant in engineering and science for understanding complex phenomena. To examine the solitary wave solutions of the proposed model, we employ sophisticated analytical techniques, including the generalized projective Riccati equation method, the new improved generalized exponential rational function method, and the modified F-expansion method, along with mathematical simulations, to obtain a deeper insight into wave propagation. To explore desirable soliton solutions, the nonlinear partial differential equation is converted into its respective ordinary differential equations by wave transforms utilizing $\beta$-fractional derivatives. Further, the solutions in the forms of bright, dark, singular, combined, and complex solitons are secured. Various physical parameter values and arrangements are employed to investigate the soliton solutions of the system. Variations in parameter values result in specific behaviors of the solutions, which we illustrate via various types of visualizations. Additionally, a key aspect of this research involves analyzing the chaotic behavior of the governing model. A perturbed version of the system is derived and then analyzed using chaos detection techniques such as power spectrum analysis, Poincaré return maps, and basin attractor visualization. The study of nonlinear dynamics reveals the system’s sensitivity to initial conditions and its dependence on time-decay effects. This indicates that the system exhibits chaotic behavior under perturbations, where even minor variations in the starting conditions can lead to drastically different outcomes as time progresses. Such behavior underscores the complexity and unpredictability inherent in the system, highlighting the importance of understanding its chaotic dynamics. This study evaluates the effectiveness of currently employed methodologies and elucidates the specific behaviors of the system’s nonlinear dynamics, thus providing new insights into the field of high-dimensional nonlinear scientific wave phenomena. The results demonstrate the effectiveness and versatility of the approach used to address complex nonlinear partial differential equations. Full article

In this study, We explore for Minkowski 3-space ${\mathbb{E}}_1^3$ harmonic surfaces’ geometric features by employing a common tangent vector field along a curve situated on the surface. Our analysis is grounded in the rotation minimizing (RM) Darboux frame, which offers a robust alternative to the classical Frenet frame particularly valuable in the Lorentzian setting, where singularities frequently arise. The RM Darboux frame, tailored to curves lying on surfaces, enables the expression of fundamental invariants such as geodesic curvature, normal curvature, and geodesic torsion. We derive specific conditions that characterize harmonic surfaces based on these invariants. We also clarify the connection between the components of the RM Darboux frame and thesurface’s mean curvature vector. This formulation provides fresh perspectives on the classification and intrinsic structure of harmonic surfaces within Minkowski geometry. To support our findings, we present several illustrative examples that demonstrate the applicability and strength of the RM Darboux approach in Lorentzian differential geometry. Full article

Aerosol uniformity in the mixing chamber is one of the key factors in evaluating performance of aerosol samplers and accuracy of aerosol monitors which could output the direct reading of particle size or concentration. For obtaining high uniformity and a stable test aerosol sample during evaluation, a portable mixing chamber, where the sample and clean air were dual-vortex turbulent mixed, was designed. By using computational fluid dynamics (CFD), particle motion within the mixing chamber was illustrated or explained. By adjusting critical structure parameters of chamber such as height and diameter, the flow field structure was optimized to improve particle mixing characteristics. Accordingly, a novel portable aerosol mixing chamber with length and inner diameter of 0.7 m and 60 mm was developed. Through a combination of simulations and experiments, the operating conditions, including working flow rate, ratio of carrier/dilution clean air, and mixture duration, were studied. Finally, by using the optimized parameters, a mixing chamber with high spatial uniformity where variation is less than 4% was obtained for aerosol particles ranging from 0.3 μm to 10 μm. Based on this chamber, a standardized testing platform was established to verify the sampling efficiency of aerosol samplers with high flow rate (28.3 L·min⁻¹). The obtained results were consistent with the reference values in the sampler’s manual, confirming the reliability of the evaluation system. The testing platform developed in this study can provide test aerosol particles ranging from sub-micrometers to micrometers and has significant engineering applications, such as atmospheric pollution monitoring and occupational health assessment. Full article

We present an alternative to the classical SQUID magnetometric measurements for the First-Order Reversal Curve (FORC) diagram approach by employing differential scanning calorimetry (DSC) experiments. After discussing the main results, the advantages and limitations of the magnetometric FORCs, we introduce the calorimetric method. We argue that, while the results are comparable to those obtained via magnetometry, the calorimetric method not only significantly simplifies the required mathematical computations but also detects subtle or overlapping phase transitions that might be hard to distinguish magnetically. The methodology is illustrated through both experimental data and mean-field simulations. Full article

BeiDou navigation satellite system (BDS) precise point positioning (PPP)-B2b has significant potential for application in meteorological fields, such as standalone water vapor monitoring in depopulated area without Internet. In this study, the practical ability of water vapor monitoring using the BDS PPP-B2b service is illustrated through a continuously operated water vapor monitoring system in Wuhan, China, with a 25-day experiment in 2025. Original observations from the Global Positioning System (GPS) and BDS are collected and processed in the near real-time (NRT) mode using ephemeris from the PPP-B2b service. Precipitable water vapor PWV monitored with B2b ephemeris are evaluated with radiosonde and ERA5 reanalysis, respectively. Taking PWV from radiosonde observations as the reference, RMS of PWV based on B2b ephemeris varies from 3.71 to 4.66 mm for different satellite combinations. While those values are with a range from 3.95 to 4.55 mm when compared with ERA5 reanalysis. These values are similar to those processed with the real-time ephemeris from the China Academy of Science (CAS). In general, this study demonstrates that the practical accuracy of water vapor monitored based on the BDS PPP-B2b service can meet the basic demand for operational meteorology for the first time. This will provide a scientific reference for its wide promotion to meteorological applications in the near future. Full article

Background/Objectives: Recent breakthroughs in three-dimensional (3D) printing and high-resolution imaging have opened up new possibilities in personalized medicine, surgical planning, and forensic reconstruction. This study breaks new ground by evaluating the integration of high-resolution peripheral quantitative computed tomography (HR-pQCT) with multimodal imaging and additive manufacturing to assess a chronic, infected gunshot injury in the knee joint of a red deer. This unique approach serves as a translational model for complex skeletal trauma. Methods: Multimodal imaging—including clinical CT, MRI, and HR-pQCT—was used to characterise the extent of osseous and soft tissue damage. Histopathological and molecular analyses were performed to confirm the infectious agent. HR-pQCT datasets were segmented and processed for 3D printing using PolyJet, stereolithography (SLA), and fused deposition modelling (FDM). Printed models were quantitatively benchmarked through 3D surface deviation analysis. Results: Imaging revealed comminuted fractures, cortical and trabecular degradation, and soft tissue involvement, consistent with chronic osteomyelitis. Sphingomonas sp., a bacterium that forms biofilms, was identified as the pathogen. Among the printing methods, PolyJet and SLA demonstrated the highest anatomical accuracy, whereas FDM exhibited greater geometric deviation. Conclusions: HR-pQCT-guided 3D printing provides a powerful tool for the anatomical visualisation and quantitative assessment of complex bone pathology. This approach not only enhances diagnostic precision but also supports applications in surgical rehearsal and forensic analysis. It illustrates the potential of digital imaging and additive manufacturing to advance orthopaedic and trauma care, inspiring future research and applications in the field. Full article