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Applied Sciences

Applied Sciences is an international, peer-reviewed, open access journal on all aspects of applied natural sciences published semimonthly online by MDPI.

Quartile Ranking JCR - Q2 (Engineering, Multidisciplinary)

All Articles (81,143)

The rapid growth of the semiconductor industry has created a bottleneck in which traditional manual methods for designing fabrication plants (fabs) cannot keep pace with their high complexity and short technological lifecycles. This problem stems from the critical mismatch between a fab’s multiyear construction timeline and the rapidly shrinking lifecycle of the advanced chips it is built to produce. To address this challenge, the present study proposes a methodological framework that uses dynamic generative design within a Building Information Modelling (BIM) environment. This approach applies algorithms to generalized models to generate and evaluate numerous potential design solutions automatically. For facility layouts, the framework produces plans that balance spatial efficiency, material flow, and stringent cleanroom protocols. For complex utility systems, it moves beyond simple clash detection to proactively generate resource-efficient, clash-free routing paths that consider both constructability and long-term maintainability. The primary contribution of this study is a standardized, data-agnostic design process that enhances design quality without requiring sensitive project data, establishing a robust foundation for future Digital Twin integration.

14 October 2025

GD: Data, Rules, and Optimization.

Recent studies have identified the hip joint as a central component of the human kinetic chain, playing a pivotal role in optimizing force transmission during movement. Enhancing its functional capacity represents an effective strategy for enhancing overall physical well-being and preventing injuries. This study investigates the effects of an eight-week hip joint functional training program on the health-related physical fitness, hip joint function, and factors associated with injury risk in university students from a track and field elective class. A total of 56 participants were randomly assigned to an experimental group (n = 28) or a control group (n = 28). The experimental group incorporated hip joint functional training, which comprising dynamic stretching and activation exercises, into their standard physical education (PE) class activities, while the control group continued with the regular physical education curriculum. Pre-intervention and post-intervention assessments included hip joint range of motion (ROM), functional movement screening (FMS), a 50 m sprint, standing long jump, sit-and-reach test, and spinal health evaluations. Results indicated that the experimental group demonstrated significant improvements in multi-directional hip range of motion (ROM), with examples including flexion increasing by 10° and external rotation by 9°. These improvements were accompanied by significant gains in functional movement screen (FMS) scores, with significant improvements in the Hurdle Step, whose median score increased to 3.0, Active Straight Leg Raise, and Rotary Stability components (all p < 0.05) compared to the control group. Furthermore, the training significantly reduced spinal asymmetry (axial trunk rotation reduced from 3.86°to 3.43°) and enhanced performance in the 50 m sprint (−0.26 s) and standing long jump (+0.08 m) (all p < 0.05). These objective improvements in functional movement patterns, postural alignment, and physical performance are associated with key biomechanical factors known to influence injury risk, such as the demonstrated gains in joint mobility and movement efficiency. Therefore, incorporating hip joint functional training into college physical education programs may effectively enhance students’ fundamental movement quality, improve joint stability, and promote postural health, thereby mitigating key biomechanical risk factors. This approach offers a practical strategy for educators to improve student physical health in general PE settings.

14 October 2025

Two essential oils: cinnamon and clove were used to aromatize rapeseed honey for the first time. For comparison self-distilled and commercially purchased essential oils were used. All essential oils and obtained flavored honeys were assessed for antioxidant activity, volatile fraction composition (GC-MS) and polyphenolic profiles (HPTLC). The results indicated that while in the case of clove oils the differences in the enrichment of the honey composition were not dependent on the origin of essential oil, the effect of the self-distilled cinnamon oil addition was completely different than for its market equivalent. The commercial cinnamon oil contained a larger amount (59.58%) of eugenol than the self-produced oil, probably as a result of the admixture of cinnamon leaf oil or different raw material used for commercial essential oil production. The described studies may constitute a basis for introducing to the market a new type of product based on honey and phytoadditives. The essential oil flavored honey is characterized not only by new desirable organoleptic features but also by highly enhanced antioxidant and probably antibacterial properties, which, however, requires further research.

14 October 2025

There have been significant breakthroughs in developing models for segmenting 3D medical images, with many promising results attributed to the incorporation of Vision Transformers (ViT). However, the fundamental mechanism of transformers, known as self-attention, has quadratic complexity, which significantly increases computational requirements, especially in the case of 3D medical images. In this paper, we investigate the UNETR++ model and propose a voxel-focused attention mechanism inspired by TransNeXt pixel-focused attention. The core component of UNETR++ is the Efficient Paired Attention (EPA) block, which learns from two interdependent branches: spatial and channel attention. For spatial attention, we incorporated the voxel-focused attention mechanism, which has linear complexity with respect to input sequence length, rather than projecting the keys and values into lower dimensions. The deficiency of UNETR++ lies in its reliance on dimensionality reduction for spatial attention, which reduces efficiency but risks information loss. Our contribution is to replace this with a voxel-focused attention design that achieves linear complexity without low-dimensional projection, thereby reducing parameters while preserving representational power. This effectively reduces the model’s parameter count while maintaining competitive performance and inference speed. On the Synapse dataset, the enhanced UNETR++ model contains 21.42 M parameters, a 50% reduction from the original 42.96 M, while achieving a competitive Dice score of 86.72%.

14 October 2025

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Structural Seismic Design and Evaluation
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Editors: Alfredo Reyes-Salazar, Federico Valenzuela-Beltran, Mario D. Llanes-Tizoc
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Applied Sciences - ISSN 2076-3417Creative Common CC BY license