Search Results (847)

Handwriting impairment is a cardinal symptom of Parkinson’s. However, treatment options are limited. Here we evaluate the utility and estimate effects of a novel low-resource handwriting intervention (Clinicaltrials. gov NCT03369587). Forty-eight people with Parkinsons with self-reported handwriting problems were recruited to an exploratory, assessor-blind two-arm parallel randomized trial to either diverging (n = 24, n = 19 analysed) or parallel (n = 24, n = 20 analysed) groups. Both received a six-week, five times a week, handwriting program: writing a daily diary on lined paper (diverging: 10 mm increasing to 13 mm apart, parallel: 10 mm apart). Outcomes were measures of impairment (cursive ‘el’, single and dual-task), handwriting function (sentence and free writing) and self-reported difficulties. Median diary entries (31, IRQ: 17.5–39) were greater than requested (30) with no differences between groups, p = 0.302. No adverse events were reported. Regardless of group, improvements were found in writing ‘el’ speed (single task: d = −0.90, 95% CI: −1.41: −0.38, p = 0.001; dual task: d = −0.72, 95% CI: −1.24: −0.21, p = 0.09) and amplitude (single task: d = 1.07, 95% CI: 0.49: 1.66, p < 0.001; dual task: d = 0.86, 95% CI: 0.35: 1.37, p = 0.002). Sentence amplitude (d = 0.80, 95% CI: 0.30: 1.29, p = 0.003) and perceived difficulties also improved (OR = −3.6, 95% CI: −12.6: −1.0, p = 0.047). Between-group effects were small (d = 0.11 to 0.48). Large improvements to handwriting, which required less attention, were found after self-directed well-adhered-to practice. Potential additional benefits of exaggerated cueing were small. Full article

This paper investigates how architectural theories from the Bauhaus in the 1920s have the opportunity to influence approaches to wellbeing through the built environment today. Through a literature review, the study examines work and writings by primarily Hungarian artist László Moholy-Nagy and German architect Siegfried Ebeling, as well as their contemporaries and predecessors at the Bauhaus. The research identifies a gap in architectural history where past architectural theories and practices have been underexplored in relation to wellbeing, particularly in early modernist discourse. By analyzing Moholy-Nagy and Ebeling writings, this paper reveals how their work prefigures and expands contemporary concerns in wellness design. The key finding is: in the examined works there are clear links between metaphysical thinking, environmental conditions, construction innovation and wellbeing. This study contributes to architectural discourses by: firstly proposing that metaphysically informed design thinking can offer valuable insights for architectural practices aiming to enhance occupant wellbeing; secondly, recontextualizing historical ideas within present-day design challenges, and thirdly offering future research directions for developing understandings of wellbeing in relation to architecture. Full article

Additive manufacturing methods can constitute a valuable alternative to conventional production techniques for components used in the heavy industry, particularly in foundry applications. This innovative manufacturing approach enables an expanded product portfolio as well as higher precision and geometrical complexity of ceramic components. One additive technology applicable to ceramic processing is robocasting, classified within the direct ink writing (DIW) family. In this method, a semi-fluid ceramic paste is extruded to build the part layer by layer; the shaped green body is subsequently fired (sintered) to attain its final functional properties. This study presents the results of materials characterization of printed ceramic filters, encompassing phase composition analysis, density measurements, three-point bending strength testing, hardness, and microstructural examination. The investigations demonstrated that the oxide ceramic Al₂O₃ processed by the modern robocasting method exhibits mechanical performance at a comparably high level relative to classical manufacturing routes (slip casting, ceramic injection molding, dry pressing). Moreover, the porosity results indicate that 3D printing technology enables lower post-sintering porosity. Full article

Azimuth sensing plays a vital role in numerous industrial applications where tilt angle serves as a key parameter. To address the demand for accurate and reliable measurements, we propose an all-fiber two-dimensional inclinometer based on the Vernier effect in a multi-core fiber Fabry–Perot interferometer. The sensor is capable of simultaneously measuring both inclination and azimuth angles with high accuracy. A cascaded Fabry–Perot interferometer was inscribed in a seven-core fiber using a femtosecond laser plane-by-plane direct writing technique. By monitoring the wavelength shifts in two peripheral cores, we demonstrated the feasibility and performance of the proposed sensor. The experimental results showed that the inclinometer exhibited high sensitivity, with maximum values of −0.5272 nm/° for azimuth measurement (maximum measurement error: 7.33°) and −0.5557 nm/° for inclination measurement (maximum measurement error: 5.97°). The measurement ranges extended from 0° to 360° for azimuth and from –90° to 90° for inclination. Owing to its wide measurement range, compact structure, and high sensitivity, the proposed all-fiber two-dimensional inclinometer holds significant potential for practical applications. Full article

Hydrogel scaffolds have emerged as pivotal materials in regenerative medicine due to their biocompatibility, tunable mechanical properties, and ability to mimic the extracellular matrix. However, conventional fabrication techniques often lack the precision required to create complex architectures, limiting their effectiveness in tissue engineering. This review explores advanced laser-based fabrication methods, such as two-photon polymerization, laser-induced forward transfer, selective laser sintering/melting, and laser direct writing, which offer unparalleled resolution and control over scaffold geometry. These techniques enable the production of intricate 3D structures tailored to specific clinical needs, from vascular networks to patient-specific implants. We analyze the principles, advantages, and limitations of each method, highlighting their biomedical applications and the challenges of scalability, material compatibility, and cost. By bridging the gap between laboratory research and clinical implementation, laser-based technologies hold significant promise for advancing personalized medicine and tissue regeneration. Full article

Yield stress and thixotropy are critical rheological properties for enabling successful 3D printing of magnetic colloidal systems. However, conventional magnetic colloids, typically composed of a single dispersed phase, exhibit insufficient rheological tunability for reliable 3D printing. In this study, we developed a novel magnetic colloidal system comprising a carrier liquid, magnetic nanoparticles, and organic modified bentonite. A direct-ink-writing 3D-printing platform was specifically designed and optimized for thixotropic materials, incorporating three distinct extruder head configurations. Through an in-depth rheological investigation and printing trials, quantitative analysis revealed that the printability of magnetic colloids is significantly affected by multiple factors, including magnetic field strength, pre-shear conditions, and printing speed. Furthermore, we successfully fabricated 3D architectures through the precise coordination of deposition paths and magnetic field modulation. This work offers initial support for the material’s future applications in soft robotics, in vivo therapeutic systems, and targeted drug delivery platforms. Full article

In order to optimize the preparation process of microlens arrays, improve preparation efficiency, and reduce preparation costs, 248 nm KrF excimer laser direct writing is combined with a motion mask to prepare microlens arrays on PMMA substrates. Firstly, a specific exposure mask based on the contour characteristics of the microlens unit was designed, and the preparation principle was analyzed. Using COMSOL Multiphysics 6.3 simulation software, a microlens preparation model was built to intuitively describe the process of preparing microlenses by the motion mask method. Secondly, a preparation system was built, and the laser processing technology was optimized. Finally, microlens arrays were prepared based on the optimized process, and an optical microscope and white-light interferometer were used to observe their morphology. The experimental results show that this method can effectively prepare cylindrical and circular microlens arrays. The width of the cylindrical microlens array unit exceeded 90 μm, the height was 7.08 μm, and the roughness was 0.09 μm. The diameter of the circular microlens array unit was φ100 μm, the height was 4 μm, and the curvature radius was 230 μm. The geometric dimensions of the mask can be adjusted to obtain microlens units of the desired size, achieving personalized preparation of microlens arrays. The excimer laser motion mask method can prepare various types of microlens arrays, and the array units have a high consistency and high surface quality, which helps to improve the efficiency, flexibility, stability, and specificity of microlens array preparation. Full article

Titanium (Ti)-based implants are widely used for bone injuries but suffer from poor bioactivity. To address this, we propose an innovative synergistic approach that combines laser melting deposition (LMD) for the fabrication of titanium-based supports with laser direct writing via two-photon polymerization (LDW via TPP) for their functionalization with 3D polymeric microstructures. We functionalized Ti surfaces fabricated by LMD using Ti (99.85 wt.%) and TiC powders (79.95 wt.% Ti, 20.05 wt.% C), with 3D microstructures obtained by LDW via TPP. The 3D microstructures were made of IP-Dip photopolymer and comprised 64 vertical microtubes arranged in five layers (10 to 170 μm tall, >94% porosity). When seeded with MG-63 osteoblast-like cells, the Ti-based surfaces functionalized with 3D polymeric microstructures promoted 3D cells’ spatial organization. Moreover, the cells seeded on functionalized Ti-based surfaces showed earlier organic matrix synthesis (day 7 vs. day 14) and mineralization (higher deposits of calcium and phosphorus, starting from day 7), as compared with the cells from non-functionalized Ti. In addition, the traction forces exerted by the cells on the 3D microstructures, determined using FEBio Studio software, were of the order of hundreds of µN, whereas if the cells would have been seeded on extracellular matrix-like materials, the traction forces would have been of only few nN. These results point towards the major role played by 3D polymeric microarchitectures in the interaction between osteoblast-like cells and Ti-based surfaces. Overall, the functionalization of Ti-based constructs fabricated by LMD with 3D polymeric microstructures made by LDW via TPP significantly improved Ti bioactivity. Full article

Background: Pre-retrofit auditing and pre-demolition auditing (PRA/PDA) are important in material reuse, waste reduction, and regulatory compliance in the building sector. An emphasis on sustainable construction practices has led to a higher requirement for PRA/PDA. However, traditional auditing processes demand substantial time and manual effort and are more easily to create human errors. As a developing technology, artificial intelligence (AI) can potentially assist PRA/PDA processes. Objectives: This scoping review aims to review the potential of AI in assisting each sub-stage of PRA/PDA processes. Eligibility Criteria and Sources of Evidence: Included sources were English-language articles, books, and conference papers published before 31 March 2025, available electronically, and focused on AI applications in PRA/PDA or related sub-processes involving structured elements of buildings. Databases searched included ScienceDirect, IEEE Xplorer, Google Scholar, Scopus, Elsevier, and Springer. Results: The review indicates that although AI has the potential to be applied across multiple PRA/PDA sub-stages, actual application is still limited. AI integration has been most prevalent in floor plan recognition and material detection, where deep learning and computer vision models achieved notable accuracies. However, other sub-stages—such as operation and maintenance document analysis, object detection, volume estimation, and automated report generation—remain underexplored, with no PRA/PDA specific AI models identified. These gaps highlight the uneven distribution of AI adoption, with performance varying greatly depending on data quality, available domain-specific datasets, and the complexity of integration into existing workflows. Conclusions: Out of multiple PRA/PDA sub-stages, AI integration was focused on floor plan recognition and material detection, with deep learning and computer vision models achieving over 90% accuracy. Other stages such as operation and maintenance document analysis, object detection, volume estimation, and report writing, had little to no dedicated AI research. Therefore, although AI demonstrates strong potential in PRA/PDA, particularly for floor plan and material analysis, broader adoption is limited. Future research should target multimodal AI development, real-time deployment, and standardized benchmarking to improve automation and accuracy across all PRA/PDA stages. Full article

The increasing demand for novel tissue engineering (TE) applications in bone tissue regeneration underscores the importance of exploring advanced manufacturing techniques and biomaterials for personalised treatment approaches. Three-dimensional printing (3DP) technology facilitates the development of implantable devices with intricate geometries, enabling patient-specific therapeutic solutions. Although Fused Filament Fabrication (FFF) and Direct Ink Writing (DIW) are widely utilised for fabricating bone-like implants, the need for multiple processing steps often prolongs the overall production time. In this study, a single-step melt-extrusion 3DP technique was performed to develop multi-material scaffolds including bioceramics, hydroxyapatite (HA), and β-tricalcium phosphate (TCP) in both their bioactive and calcined forms at 10% and 20% w/w, within polycaprolactone (PCL) matrices. Printing parameters were optimised, and physicochemical properties of all biomaterials and final forms were evaluated. Thermal degradation and surface morphology analyses assessed the consistency and distribution of the ceramics across the different formulations. The tensile testing of the scaffolds defined the impact of each ceramic type and wt% on scaffold flexibility performance, while in vitro cell studies determined the cytocompatibility efficiency. Hence, all 3D-printed PCL–ceramic composite scaffolds achieved structural integrity and physicochemical and thermal stability. The mechanical profile of extruded samples was relevant to the ceramic consistency, providing valuable insights for further mechanotransduction investigations. Notably, all materials showed high cell viability and proliferation, indicating strong biocompatibility. Therefore, this additive manufacturing (AM) process is a precise and fast approach for developing biomaterial-based scaffolds, with potential applications in surgical restoration and support of segmental bone defects. Full article

Three-dimensional printing technology is fundamentally reshaping the design and fabrication of health monitoring sensors. While it holds great promise for achieving miniaturization, multi-material integration, and personalized customization, the lack of a clear selection framework hinders the optimal matching of printing technologies to specific sensor requirements. This review presents a classification framework based on existing standards and specifically designed to address sensor-related requirements, categorizing 3D printing technologies into point-based, line-based, and area-based modalities according to their fundamental fabrication unit. This framework directly bridges the capabilities of each modality, such as nanoscale resolution, multi-material versatility, and high-throughput production, with the critical demands of modern health monitoring sensors. We systematically demonstrate how this approach guides technology selection: Point-based methods (e.g., stereolithography, inkjet) enable micron-scale features for ultra-sensitive detection; line-based techniques (e.g., Direct Ink Writing, Fused Filament Fabrication) excel in multi-material integration for creating complex functional devices such as sweat-sensing patches; and area-based approaches (e.g., Digital Light Processing) facilitate rapid production of sensor arrays and intricate structures for applications like continuous glucose monitoring. The point–line–area paradigm offers a powerful heuristic for designing and manufacturing next-generation health monitoring sensors. We also discuss strategies to overcome existing challenges, including material biocompatibility and cross-scale manufacturing, through the integration of AI-driven design and stimuli-responsive materials. This framework not only clarifies the current research landscape but also accelerates the development of intelligent, personalized, and sustainable health monitoring systems. Full article

The assimilation–accommodation theory provides a crucial theoretical framework for understanding the neural mechanisms of second language (L2) processing. Chinese characters, as logographic scripts, contain diverse strokes and components with high visual complexity, and their grapheme–phoneme conversion differs fundamentally from alphabetic writing systems. Existing studies have identified unique neural patterns in Chinese language processing, yet a systematic synthesis of L2 Chinese processing remains limited. This review focuses on the brain mechanisms underlying Chinese language processing among L2 learners with diverse native language backgrounds. On the one hand, Chinese language processing relies on neural networks of the native language (assimilation); on the other hand, it recruits additional right-hemisphere regions to adapt to Chinese characters’ visuospatial complexity and grapheme–phoneme conversion strategies (accommodation). Accordingly, this review first synthesizes current brain imaging studies on L2 Chinese processing within this theoretical framework, noting that prevailing paradigms—limited to lexical and sentence-level processing—fail to capture the complexity, hierarchy, and dynamics of natural language. Next, this review examines the application and implications of naturalistic stimuli paradigms in neuroimaging research of L2 Chinese processing. Finally, future directions for this field are proposed. Collectively, these findings reveal neuroplasticity in processing complex ideographic scripts. Full article

The rapid growth of artificial intelligence (AI), data centers, and high-performance computing (HPC) has increased the demand for large bandwidth, high energy efficiency, and high-density optical interconnects. Co-packaged optics (CPO) technology offers a promising solution by integrating photonic integrated circuits (PICs) directly within or close to electronic integrated circuit (EIC) packages. This paper explores the evolution of CPO performance from various perspectives, including fan-out wafer level packaging (FOWLP), through-silicon via (TSV)-based packaging, through-glass via (TGV)-based packaging, femtosecond laser direct writing waveguides, ion-exchange glass waveguides, and optical coupling. Micro ring resonators (MRRs) are a high-density integration solution due to their compact size, excellent energy efficiency, and compatibility with CMOS processes. However, traditional thermal tuning methods face limitations such as high static power consumption and severe thermal crosstalk. To address these issues, non-volatile neuromorphic photonics has made breakthroughs using phase-change materials (PCMs). By combining the integrated storage and computing capabilities of photonic memory with the efficient optoelectronic interconnects of CPO, this deep integration is expected to work synergistically to overcome material, integration, and architectural challenges, driving the development of a new generation of computing hardware with high energy efficiency, low latency, and large bandwidth. Full article

Artificial Intelligence (AI) tools have transformed academic writing and literacy development in higher education. Students can now receive instant feedback on grammar, coherence, style, and argumentation using AI-powered writing assistants, like Grammarly, ChatGPT, and QuillBot. Moreover, these writing assistants can quickly produce completed essays and papers, leaving little else for the student to do aside from reading and perhaps editing the content. Many teachers are concerned that this erodes critical thinking skills and undermines ethical considerations since students are not performing the work themselves. This study addresses this concern by synthesizing and evaluating peer-reviewed literature on the effectiveness of AI in supporting writing pedagogy. Studies were selected based on their relevance and scholarly merit, following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines to ensure methodological rigor and quality. The findings reveal that although AI tools can be detrimental to the development of writing skills, they can foster self-directed learning and improvement when carefully integrated into coursework. They can facilitate enhanced writing fluency, offer personalized tutoring, and reduce the cognitive load of drafting and revising. This study also compares AI-assisted and traditional writing approaches and discusses best practices for integrating AI tools into curricula while preserving academic integrity and creativity in student writing. Full article