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Background/Objectives: Deep brain stimulation (DBS) is an effective surgical treatment for Parkinson’s Disease (PD) and other movement disorders. Despite its benefits, DBS explantation occurs in 5.6% of cases, with costs exceeding USD 22,000 per implant. Traditional statistical methods have struggled to identify reliable risk factors for explantation. We hypothesized that supervised machine learning would more effectively capture complex interactions among perioperative factors, enabling the identification of novel risk factors. Methods: The Medical Informatics Operating Room Vitals and Events Repository was queried for patients with DBS, adequate clinical data, and at least two years of follow-up (n = 38). Fisher’s exact test assessed demographic and medical history variables. Data were analyzed using Anaconda Version 2.3.1. with pandas, numpy, sklearn, sklearn-extra, matplotlin. pyplot, and seaborn. Recursive feature elimination with cross-validation (RFECV) optimized factor selection was used. A multivariate logistic regression model was trained and evaluated using precision, recall, F1-score, and area under the curve (AUC). Results: Fisher’s exact test identified chronic pain (p = 0.0108) and tobacco use (p = 0.0026) as risk factors. RFECV selected 24 optimal features. The logistic regression model demonstrated strong performance (precision: 0.89, recall: 0.86, F1-score: 0.86, AUC: 1.0). Significant risk factors included tobacco use (OR: 3.64; CI: 3.60–3.68), primary PD (OR: 2.01; CI: 1.99–2.02), ASA score (OR: 1.91; CI: 1.90–1.92), chronic pain (OR: 1.82; CI: 1.80–1.85), and diabetes (OR: 1.63; CI: 1.62–1.65). Conclusions: Our study suggests that supervised machine learning can identify risk factors for early DBS explantation. Larger studies are needed to validate our findings. Full article

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17 pages, 3902 KiB

Open AccessArticle

Electrical Potential-Induced Lubricity Changes in an Ionic Liquid-Lubricated Friction Pair

by Raimondas Kreivaitis, Audrius Žunda and Albinas Andriušis

Lubricants 2025, 13(7), 311; https://doi.org/10.3390/lubricants13070311 (registering DOI) - 17 Jul 2025

Abstract

The control of lubricity induced by electric potential is appealing for numerous applications. On the other hand, the high polarity of ionic liquids facilitates the adsorption of equally charged molecules onto polar surfaces. This phenomenon and its consequences are well understood at the nanoscale; however, they have recently garnered significant attention at the macroscale. This study investigates the lubricity of trihexyltetradecylphosphonium dicyanamide, a phosphonium ionic liquid, when used as a neat lubricant in reciprocating sliding under electrically charged conditions. Two different polarities with the same potential were applied to the friction pair of bearing steel against bearing steel while monitoring electrical contact resistance. The lubricity was evaluated through measurements of friction, wear, surface morphology, and composition. It was found that the application of electric potential significantly alters the lubricity of the investigated ionic liquid where a positive potential applied to the ball resulted in the least damaging situation. The recorded electrical contact resistance enabled the monitoring of tribofilm formation during reciprocation. It was found that there was minimal to no separation between interacting surfaces when the ball was changing direction. Full article

(This article belongs to the Special Issue Recent Advances in Eco-Friendly Ionic Liquids as Lubricants and Additives)

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14 pages, 704 KiB

Open AccessReview

From Rare Genetic Variants to Polygenic Risk: Understanding the Genetic Basis of Cardiomyopathies

by Ana Belen Garcia-Ruano, Elena Sola-Garcia, Maria Martin-Istillarty and Jose Angel Urbano-Moral

J. Cardiovasc. Dev. Dis. 2025, 12(7), 274; https://doi.org/10.3390/jcdd12070274 (registering DOI) - 17 Jul 2025

Abstract

Cardiomyopathies represent a heterogeneous group of myocardial disorders, traditionally classified by phenotype into hypertrophic, dilated, and arrhythmogenic. Historically, these conditions have been attributed to high-penetrance rare variants in key structural genes, consistent with a classical Mendelian pattern of inheritance. However, emerging evidence suggests that this model does not fully capture the full spectrum and complexity of disease expression. Many patients do not harbor identifiable pathogenic variants, while others carrying well-known disease-causing variants remain unaffected. This highlights the role of incomplete penetrance, likely modulated by additional genetic modifiers. Recent advances in genomics have revealed a broader view of the genetic basis of cardiomyopathies, introducing new players such as common genetic variants identified as risk alleles, as well as intermediate-effect variants. This continuum of genetic risk, reflecting an overall genetic influence, interacts further with environmental and lifestyle factors, likely contributing together to the observed variability in clinical presentation. This model offers a more realistic framework for understanding genetic inheritance and helps provide a clearer picture of disease expression and penetrance. This review explores the evolving genetic architecture of cardiomyopathies, spanning from a monogenic foundation to intermediate-risk variants and complex polygenic contribution. Recognizing this continuum is essential for enhancing diagnostic accuracy, guiding family screening strategies, and enabling personalized patient management. Full article

(This article belongs to the Section Genetics)

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15 pages, 1034 KiB

Open AccessArticle

In Vitro Oral Cavity Permeability Assessment to Enable Simulation of Drug Absorption

by Pankaj Dwivedi, Priyata Kalra, Haiying Zhou, Khondoker Alam, Eleftheria Tsakalozou, Manar Al-Ghabeish, Megan Kelchen and Giovanni M. Pauletti

Pharmaceutics 2025, 17(7), 924; https://doi.org/10.3390/pharmaceutics17070924 (registering DOI) - 17 Jul 2025

Abstract

Background/Objectives: The oral cavity represents a convenient route of administration for drugs that exhibit significant hepatic first-pass extraction. In this study, the mucosal permeation properties of selected active pharmaceutical ingredients (APIs) incorporated into oral cavity drug products that are approved by the U.S. Food and Drug Administration were quantified using the human-derived sublingual HO-1-u-1 and buccal EpiOral™ in vitro tissue models. Methods: Epithelial barrier properties were monitored using propranolol and Lucifer Yellow as prototypic transcellular and paracellular markers. APIs were dissolved in artificial saliva, pH 6.7, and transepithelial flux from the apical to the basolateral compartment was quantified using HPLC. Results: Apparent permeability coefficients (Papp) calculated for these APIs in the sublingual HO-1-u-1 tissue model varied from Papp = 2.72 ± 0.06 × 10⁻⁵ cm/s for asenapine to Papp = 6.21 ± 2.60 × 10⁻⁵ cm/s for naloxone. In contrast, the buccal EpiOral™ tissue model demonstrated greater discrimination power in terms of permeation properties for the same APIs, with values ranging from Papp = 3.31 ± 0.83 × 10⁻⁷ cm/s for acyclovir to Papp = 2.56 ± 0.68 × 10⁻⁵ cm/s for sufentanil. The tissue-associated dose fraction recovered at the end of the transport experiment was significantly increased in the buccal EpiOral™ tissue model, reaching up to 8.5% for sufentanil. Conclusions: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. Following a robust in vitro–in vivo correlation analysis, it is expected that such innovative in silico modeling strategies will the accelerate development of generic oral cavity products by facilitating the utility of model-integrated evidence to support decision making in generic drug development and regulatory approval. Full article

(This article belongs to the Special Issue Next-Generation Biomaterials for Oral Healthcare: Focus on Regenerative and Delivery Functions)

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Graphical abstract

11 pages, 1461 KiB

Open AccessArticle

Global–Local Cooperative Optimization in Photonic Inverse Design Algorithms

by Mingzhe Li, Tong Wang, Yi Zhang, Yulin Shen, Jie Yang, Ke Zhang, Dehui Pan and Ming Xin

Photonics 2025, 12(7), 725; https://doi.org/10.3390/photonics12070725 (registering DOI) - 17 Jul 2025

Abstract

We developed the Global–Local Integrated Topology inverse design algorithm (denoted as the GLINT algorithm), which employs a trajectory-based optimization strategy with waveguide–substrate material-flipping structural modifications, enabling the direct optimization of discrete waveguide–substrate binary structures. Compared to the conventional Direct Binary Search (DBS), the GLINT algorithm not only significantly enhances computational efficiency through its global search–local refinement framework but also achieves a superior 20 nm × 20 nm optimization resolution while maintaining its optimization speed—substantially advancing the design capability. Utilizing this algorithm, we designed and experimentally demonstrated a 3.5 µm × 3.5 µm dual-port wavelength division multiplexer (WDM), achieving a minimum crosstalk of −11.3 dB and a 2 µm × 2 µm 90-degree bending waveguide exhibiting a 0.31–0.52 dB insertion loss over the 1528–1600 nm wavelength range, both fabricated on silicon-on-insulator (SOI) wafers. Additionally, a 4.5 µm × 4.5 µm three-port WDM structure was also designed and simulated, demonstrating crosstalk as low as −36.5 dB. Full article

(This article belongs to the Special Issue Recent Progress in Integrated Photonics)

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10 pages, 2022 KiB

Open AccessArticle

Geometric Effect of the Photo Responsivity of Organic Phototransistors

by Chengtai Li and Xiaochen Ren

Materials 2025, 18(14), 3349; https://doi.org/10.3390/ma18143349 (registering DOI) - 17 Jul 2025

Abstract

Organic phototransistors exhibit considerably higher photoresponsivity than diode-like photodetectors owing to gate-field-effect amplification. However, the conventional definition of photoresponsivity (R) fails to accurately capture the photoresponsivity trends of transistor-based photodetectors. This study systematically investigates the impact of device geometry—specifically the width-to-length (W/L) ratio and photosensitive area—on the responsivity and photocurrent of organic phototransistors. The experimental results reveal that increasing the W/L ratio or decreasing the device area substantially enhances responsivity. A detailed analysis based on the definition of responsivity is presented herein. Finally, we introduce a channel-width-normalized responsivity to compensate for geometric effects, enabling a more accurate evaluation of device performance across different device structures. Overall, our results indicate the potential for optimizing organic phototransistors by tuning their geometric parameters. Full article

(This article belongs to the Section Electronic Materials)

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27 pages, 481 KiB

Open AccessArticle

Advancing Sustainable Urban Mobility in Oman: Unveiling the Predictors of Electric Vehicle Adoption Intentions

by Wafa Said Al-Maamari, Emad Farouk Saleh and Suliman Zakaria Suliman Abdalla

World Electr. Veh. J. 2025, 16(7), 402; https://doi.org/10.3390/wevj16070402 (registering DOI) - 17 Jul 2025

Abstract

The global shift toward sustainable transportation has gained increasing interest, promoting the use of electric vehicles (EVs) as an environmentally friendly alternative to conventional vehicles as a result of a complex interaction between economic incentives, social dynamics, and environmental imperatives. This study is based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) to understand the key factors influencing consumers’ intentions in the Sultanate of Oman toward adopting electric vehicles. It is based on a mixed methodology combining quantitative data from a questionnaire of 448 participants, analyzed using ordinal logistic regression, with qualitative thematic analysis of in-depth interviews with 18 EV owners. Its results reveal that performance expectations, trust in EV technology, and social influence are the strongest predictors of EV adoption intentions in Oman. These findings suggest that some issues related to charging infrastructure, access to maintenance services, and cost-benefit ratio are key considerations that influence consumers’ intention to accept and use EVs. Conversely, recreational motivation is not a statistically significant factor, which suggests that consumers focus on practical and economic motivations when deciding to adopt EVs rather than on their enjoyment of driving the vehicle. The findings of this study provide valuable insights for decision-makers and practitioners to understand public perceptions of electric vehicles, enabling them to design effective strategies to promote the adoption of these vehicles in the emerging sustainable transportation market of the future. Full article

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23 pages, 3885 KiB

Open AccessFeature PaperArticle

Sustainable Urban Branding: The Nexus Between Digital Marketing and Smart Cities

by Maria Briana, Roido Mitoula and Eleni Sardianou

Urban Sci. 2025, 9(7), 278; https://doi.org/10.3390/urbansci9070278 (registering DOI) - 17 Jul 2025

Abstract

Smart cities leverage digital marketing to promote sustainability and build a distinctive global branding. Despite its growing significance, the role digital marketing in smart city development remains underexplored. This study aims to fill this gap by employing bibliometric analysis of 1908 articles indexed in the Scopus database (2000–2024), using the Bibliometrix R-Studio (version 1.4.1743) and VOSviewer (version 1.6.20). The analysis reveals two thematic clusters: (1) “Digital Innovation and Sustainability”, which emphasizes technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data for energy efficiency and green urban development; and (2) “Governance and Policy”, which highlights digital marketing’s role in enabling participatory governance, citizen engagement, and inclusive urban policies. Findings underscore that digital marketing is not only a strategic communication channel but also a driver of sustainable urban transformation. By synthesizing insights from urban planning, technology, and sustainability, this paper provides a novel perspective on the intersection of digital marketing and smart cities. The results provide valuable guidance for policymakers, city planners, and researchers to harness digital marketing in promoting sustainability and further develop the smart city concept. Full article

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22 pages, 435 KiB

Open AccessArticle

Sustainable Entrepreneurship in Emerging Economies: The Role of Financial Planning, Environmental Consciousness, and Artificial Intelligence in Ecuador—A Cross-Sectional Study

by Martha Cecilia Aguirre Benalcázar, Marcia Fabiola Jaramillo Paredes and Oscar Mauricio Romero Hidalgo

Sustainability 2025, 17(14), 6533; https://doi.org/10.3390/su17146533 (registering DOI) - 17 Jul 2025

Abstract

This study investigates the interconnected roles of financial planning, environmental consciousness, and artificial intelligence (AI) in fostering sustainable entrepreneurship among merchants in Machala, Ecuador. Through structural equation modeling analysis of data from 300 entrepreneurs, we found that financial planning positively influences both sustainable entrepreneurship (β = 0.508, p < 0.001) and environmental consciousness (β = 0.421, p < 0.001). Environmental consciousness demonstrates a significant impact on sustainable business development (β = 0.504, p < 0.001), while AI integration emerges as a powerful enabler of both financial planning (β = 0.345, p < 0.001) and sustainable entrepreneurship (β = 0.664, p < 0.001). The findings reveal how AI technologies can democratize access to sophisticated sustainability planning tools in resource-constrained environments, potentially transforming how emerging market entrepreneurs approach environmental challenges. This research advances our understanding of sustainable entrepreneurship by demonstrating that successful environmental business practices in developing economies require an integrated approach combining financial literacy, ecological awareness, and technological adoption. The results suggest that policy interventions supporting sustainable entrepreneurship should simultaneously address financial capabilities, environmental education, and technological accessibility to maximize their impact on sustainable development. Full article

(This article belongs to the Special Issue AI-Driven Entrepreneurship and Sustainable Business Innovation)

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22 pages, 4581 KiB

Open AccessArticle

Strategies to Mitigate Risks in Building Information Modelling Implementation: A Techno-Organizational Perspective

by Ibrahim Dogonyaro and Amira Elnokaly

Intell. Infrastruct. Constr. 2025, 1(2), 5; https://doi.org/10.3390/iic1020005 (registering DOI) - 17 Jul 2025

Abstract

The construction industry is moving towards the era of industry 4.0; 5.0 with Building Information Modelling (BIM) as the tool gaining significant traction owing to its inherent advantages such as enhancing construction design, process and data management. However, the integration of BIM presents risks that are often overlooked in project implementation. This study aims to develop a novel amalgamated dimensional factor (Techno-organizational Aspect) that is set out to identify and align appropriate management strategies to these risks. Firstly, it encompasses an in-depth analysis of BIM and risk management, through an integrative review approach. The study utilizes an exploratory-based review centered around journal articles and conference papers sourced from Scopus and Google Scholar. Then processed using NVivo 12 Pro software to categorise risks through thematic analysis, resulting in a comprehensive Risk Breakdown Structure (RBS). Then qualitative content analysis was employed to identify and develop management strategies. Further data collection via online survey was crucial for closing the research gap identified. The analysis by mixed method research enabled to determine the risk severity via the quantitative approach using SPSS (version 29), while the qualitative approach linked management strategies to the risk factors. The findings accentuate the crucial linkages of key strategies such as version control system that controls BIM data repository transactions to mitigate challenges controlling transactions in multi-model collaborative environment. The study extends into underexplored amalgamated domains (techno-organisational spectrum). Therefore, a significant contribution to bridging the existing research gap in understanding the intricate relationship between BIM implementation risks and effective management strategies. Full article

(This article belongs to the Special Issue From Concept to Reality: Digital Innovations Driving the Future of Intelligent Infrastructure and Construction)

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19 pages, 5755 KiB

Open AccessArticle

A Context-Aware Doorway Alignment and Depth Estimation Algorithm for Assistive Wheelchairs

by Shanelle Tennekoon, Nushara Wedasingha, Anuradhi Welhenge, Nimsiri Abhayasinghe and Iain Murray

Computers 2025, 14(7), 284; https://doi.org/10.3390/computers14070284 (registering DOI) - 17 Jul 2025

Abstract

Navigating through doorways remains a daily challenge for wheelchair users, often leading to frustration, collisions, or dependence on assistance. These challenges highlight a pressing need for intelligent doorway detection algorithm for assistive wheelchairs that go beyond traditional object detection. This study presents the algorithmic development of a lightweight, vision-based doorway detection and alignment module with contextual awareness. It integrates channel and spatial attention, semantic feature fusion, unsupervised depth estimation, and doorway alignment that offers real-time navigational guidance to the wheelchairs control system. The model achieved a mean average precision of 95.8% and a F1 score of 93%, while maintaining low computational demands suitable for future deployment on embedded systems. By eliminating the need for depth sensors and enabling contextual awareness, this study offers a robust solution to improve indoor mobility and deliver actionable feedback to support safe and independent doorway traversal for wheelchair users. Full article

(This article belongs to the Special Issue AI for Humans and Humans for AI (AI4HnH4AI))

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35 pages, 1464 KiB

Open AccessSystematic Review

Assessing Transparency of Robots, Exoskeletons, and Assistive Devices: A Systematic Review

by Nicol Moscatelli, Cristina Brambilla, Valentina Lanzani, Lorenzo Molinari Tosatti and Alessandro Scano

Sensors 2025, 25(14), 4444; https://doi.org/10.3390/s25144444 (registering DOI) - 17 Jul 2025

Abstract

Transparency is a key requirement for some classes of robots, exoskeletons, and assistive devices (READs), where safe and efficient human–robot interaction is crucial. Typical fields that require transparency are rehabilitation and industrial contexts. However, the definitions of transparency adopted in the literature are heterogeneous. It follows that there is a need to clarify, summarize, and assess how transparency is commonly defined and measured. Thus, the goal of this review is to systematically examine how transparency is conceptualized and evaluated across studies. To this end, we performed a structured search across three major scientific databases. After a thorough screening process, 20 out of 400 identified articles were further examined and included in this review. Despite being recognized as a desirable and essential characteristic of READs in many domains of application, our findings reveal that transparency is still inconsistently defined and evaluated, which limits comparability across studies and hinders the development of standardized evaluation frameworks. Indeed, our screening found significant heterogeneity in both terminology and evaluation methods. The majority of the studies used either a mechanical or a kinematic definition, mostly focusing on the intrinsic behavior of the device and frequently giving little attention to the device impact of the user and on the user’s perception. Furthermore, user-centered or physiological assessments could be examined further, since evaluation metrics are usually based on kinematic and robot mechanical metrics. Only a few studies have examined the underlying motor control strategies, using more in-depth methods such as muscle synergy analysis. These findings highlight the need for a shared taxonomy and a standardized framework for transparency evaluation. Such efforts would enable more reliable comparisons between studies and support the development of more effective and user-centered READs. Full article

(This article belongs to the Special Issue Wearable Sensors, Robotic Systems and Assistive Devices)

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10 pages, 367 KiB

Open AccessReview

Graphenes for Corrosion Protection in Electrochemical Energy Technology

by Dan Liu, Xuan Xie, Xuecheng Chen and Rudolf Holze

Corros. Mater. Degrad. 2025, 6(3), 33; https://doi.org/10.3390/cmd6030033 (registering DOI) - 17 Jul 2025

Abstract

Graphene, graphene oxide, reduced graphene oxide, and few-layer graphene as functional coating materials for corrosion protection in devices for electrochemical energy conversion and storage are reviewed. Reported applications are briefly described, enabling the reader to make an informed decision about the protective options [...] Read more.

(This article belongs to the Special Issue Corrosion in Electrochemical Energy Technology: Causes and Effects, Investigations and Remediation)

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21 pages, 1186 KiB

Open AccessArticle

How Digital Technology and Business Innovation Enhance Economic–Environmental Sustainability in Legal Organizations

by Linhua Xia, Zhen Cao and Muhammad Bilawal Khaskheli

Sustainability 2025, 17(14), 6532; https://doi.org/10.3390/su17146532 (registering DOI) - 17 Jul 2025

Abstract

This study discusses the role of organizational pro-environmental behavior in driving sustainable development. Studies of green practices highlight their capacity to achieve ecological goals while delivering economic sustainability with business strategies for sustainable businesses and advancing environmental sustainability law. It also considers how the development of artificial intelligence, resource management, big data analysis, blockchain, and the Internet of Things enables companies to maximize supply efficiency and address evolving environmental regulations and sustainable decision-making. Through digital technology, businesses can facilitate supply chain transparency, adopt circular economy practices, and produce in an equitable and environmentally friendly manner. Additionally, intelligent business management practices, such as effective decision-making and sustainability reporting, enhance compliance with authorities while ensuring long-term profitability from a legal perspective. Integrating business innovation and digital technology within legal entities enhances economic efficiency, reduces operational costs, improves environmental sustainability, reduces paper usage, and lowers the carbon footprint, creating a double-benefit model of long-term resilience. The policymakers’ role in formulating policy structures that lead to green digital innovation is also to ensure that economic development worldwide is harmonized with environmental protection and international governance. Using example studies and empirical research raises awareness about best practices in technology-based sustainability initiatives across industries and nations, aligning with the United Nations Sustainable Development Goals. Full article

(This article belongs to the Special Issue Pro-Environmental Behavior and Sustainable Development in Organizations)

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15 pages, 4749 KiB

Open AccessArticle

Selective Laser Melting of a Ti-6Al-4V Lattice-Structure Gear: Design, Topology Optimization, and Experimental Validation

by Riad Ramadani, Snehashis Pal, Aleš Belšak and Jožef Predan

Appl. Sci. 2025, 15(14), 7949; https://doi.org/10.3390/app15147949 (registering DOI) - 17 Jul 2025

Abstract

The manufacture of lightweight components is one of the most important requirements in the automotive and aerospace industries. Gears, on the other hand, are among the heaviest parts in terms of their total weight. Accordingly, a spur gear was considered, the body of which was configured as a lattice structure to make it lightweight. In addition, the structure was optimized by topology optimization using ProTOP software. Subsequently, the gear was manufactured by a selective laser melting process by using a strong and lightweight material, namely Ti-6Al-4V. This study defeated the problems of manufacturing orientation, surface roughness, support structure, and bending due to the high thermal gradient in the selective laser melting process. To experimentally investigate the benefits of such a lightweight gear body structure, a new test rig with a closed loop was developed. This rig enabled measurements of strains in the gear ring, hub, and tooth root. The experimental results confirmed that a specifically designed and selectively laser-melted, lightweight cellular lattice structure in the gear body can significantly influence strain. This is especially significant with respect to strain levels and their time-dependent variations in the hub section of the gear body. Full article

(This article belongs to the Section Additive Manufacturing Technologies)

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