An important step towards improving performance while reducing weight and maintenance needs is the integration of composite materials into mechanical and aerospace engineering. This subject explores the many aspects of composite application, from basic material characterization to state-of-the-art advances in manufacturing and design processes. The major goal is to present the most recent developments in composite science and technology while highlighting their critical significance in the industrial sector—most notably in the wind energy, automotive, aerospace, and marine domains. The foundation of this investigation is material characterization, which offers insights into the mechanical, chemical, and physical characteristics that determine composite performance. The papers in this collection discuss the difficulties of gaining an in-depth understanding of composites, which is necessary to maximize their overall performance and design. The collection of articles within this topic addresses the challenges of achieving a profound understanding of composites, which is essential for optimizing design and overall functionality. This includes the application of complicated material modeling together with cutting-edge simulation tools that integrate multiscale methods and multiphysics, the creation of novel characterization techniques, and the integration of nanotechnology and additive manufacturing. This topic offers a detailed overview of the current state and future directions of composite research, covering experimental studies, theoretical evaluations, and numerical simulations. This subject provides a platform for interdisciplinary cooperation and creativity in everything from the processing and testing of innovative composite structures to the inspection and repair procedures. In order to support the development of more effective, durable, and sustainable materials for the mechanical and aerospace engineering industries, we seek to promote a greater understanding of composites.
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Saliva diagnostics have become increasingly popular due to their non-invasive nature and patient-friendly collection process. Various collection methods are available, yet these are not always well standardized for either quantitative or qualitative analysis. In line, the objective of this study was to evaluate if measured levels of various biomarkers in the saliva of healthy individuals were affected by three distinct saliva collection methods: 1) unstimulated saliva, 2) chew stimulated saliva, and 3) oral rinse. Saliva samples from 30 healthy individuals were obtained by the three collection methods. Then, the levels of various salivary biomarkers such as proteins and ions were determined. It was found that levels of various biomarkers obtained from unstimulated saliva were comparable to those in chew stimulated saliva. The levels of potassium, sodium, and amylase activity differed significantly among the three collection methods. Levels of all biomarkers measured using the oral rinse method significantly differed from those obtained from unstimulated and chew-stimulated saliva. In conclusion, both unstimulated and chew-stimulated saliva provided comparable levels for a diverse group of biomarkers. However, the results obtained from the oral rinse method significantly differed from those of unstimulated and chew-stimulated saliva, due to the diluted nature of the saliva extract.
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This study introduces a detailed method for analyzing the buckling behavior of laminated composite structures strengthened with multi-walled carbon nanotubes (MWCNTs). We propose a multi-scale analysis that combines analytical and computational techniques to assess the mechanical performance of MWCNT-reinforced composites under combined moisture, temperature, and mechanical stress conditions. The Halpin-Tsai equations are used to calculate the overall stiffness properties of the nano-enhanced matrix, considering factors like MWCNT clustering, alignment, and curvature. Additionally, we incorporate the nanoscopic, size-dependent features of MWCNTs into our model. The Chamis micromechanical formulas are applied to determine the individual elastic properties of the nanocomposite layers, considering the impacts of temperature and moisture. We then explore how variables such as MWCNT content and size, along with temperature and moisture levels, influence the critical buckling load of MWCNT-based laminated composite beams and plates using our multi-scale model. Our results are successfully compared with existing experimental and theoretical data to validate our approach. The developed method offers significant insights for the design and optimization of MWCNT-reinforced composites, potentially benefiting various engineering fields, including aerospace and automotive industries.
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This study presents a detailed buckling analysis of laminated composites reinforced by multi-walled carbon nanotube (MWCNT) inclusions using a multiscale computational framework. It combines multiple analytical and computational techniques to assess the performance of these composites under varying hygro-thermo-mechanical conditions. The model incorporates nanoscopic MWCNT characteristics, estimates orthotropic constants, and investigates the impact of various factors on the critical buckling load of MWCNT-based laminates. Comparison with existing data validates our approach, marking the first usage of the multiscale finite element method for predicting the buckling behaviour of MWCNT-reinforced laminates. This research offers valuable design insights for various industries including aerospace and automotive.
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The paper introduced an automatic score detection model using object detection techniques. The performance of sevenmodels belonging to two different architectural setups was compared. Models like YOLOv8n, YOLOv8s, YOLOv8m, RetinaNet-50, and RetinaNet-101 are single-shot detectors, while Faster RCNN-50 and Faster RCNN-101 belong to the two-shot detectors category. The dataset was manually captured from the shooting range and expanded by generating more versatile data using Python code. Before the dataset was trained to develop models, it was resized (640x640) and augmented using Roboflow API. The trained models were then assessed on the test dataset, and their performance was compared using matrices like mAP50, mAP50-90, precision, and recall. The results showed that YOLOv8 models can detect multiple objects with good confidence scores.
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This study presents an automated method for detecting and measuring the apex head thickness of tomato plants, a critical phenotypic trait associated with plant health, fruit development, and yield forecasting. Due to the apex's sensitivity to physical contact, non-invasive monitoring is essential. This paper addresses the demand for automated, contactless systems among Dutch growers. Our approach integrates deep learning models (YOLO and Faster RCNN) with RGB-D camera imaging to enable accurate, scalable, and non-invasive measurement in greenhouse environments. A dataset of 600 RGB-D images captured in a controlled greenhouse, was fully preprocessed, annotated, and augmented for optimal training. Experimental results show that YOLOv8n achieved superior performance with a precision of 91.2 %, recall of 86.7 %, and an Intersection over Union (IoU) score of 89.4 %. Other models, such as YOLOv9t, YOLOv10n, YOLOv11n, and Faster RCNN, demonstrated lower precision scores of 83.6 %, 74.6 %, 75.4 %, and 78 %, respectively. Their IoU scores were also lower, indicating less reliable detection. This research establishes a robust, real-time method for precision agriculture through automated apex head thickness measurement.
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As an active member of the Global Network for Age-Friendly Cities and Communities, The Hague has been monitoring the progress over the years. In 2022, a second cross-sectional survey based on the Age Friendly Cities and Communities Questionnaire (AFCCQ) was conducted among 396 community-dwelling older citizens in the municipality. During times of the pandemic, scores for Social Participation went notably down, and scores for Respect and Social Inclusion increased. For the first time, based on survey data, four personas were found through cluster analysis. These personas ranged from the precariat and people with personal health issues with lower scores, to the silent majority without the limitations of health problems, and the upper echelon who score positively in all domains. Age-friendly policies in The Hague should focus particularly on the first two clusters through dedicated action plans, which would help steer efforts towards those most in need for support. This would help The Hague to become an age-friendly city for all, and not only for those living in good health and with sufficient financial means.
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The evolution of emerging technologies that use Radio Frequency Electromagnetic Field (RF-EMF) has increased the interest of the scientific community and society regarding the possible adverse effects on human health and the environment. This article provides NextGEM’s vision to assure safety for EU citizens when employing existing and future EMF-based telecommunication technologies. This is accomplished by generating relevant knowledge that ascertains appropriate prevention and control/actuation actions regarding RF-EMF exposure in residential, public, and occupational settings. Fulfilling this vision, NextGEM commits to the need for a healthy living and working environment under safe RF-EMF exposure conditions that can be trusted by people and be in line with the regulations and laws developed by public authorities. NextGEM provides a framework for generating health-relevant scientific knowledge and data on new scenarios of exposure to RF-EMF in multiple frequency bands and developing and validating tools for evidence-based risk assessment. Finally, NextGEM’s Innovation and Knowledge Hub (NIKH) will offer a standardized way for European regulatory authorities and the scientific community to store and assess project outcomes and provide access to findable, accessible, interoperable, and reusable (FAIR) data.
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There are over 1400 age-friendly cities and communities worldwide, and the efforts to create a better quality of life for older people progressively intersect with sustainability goals. The intentions and behaviours concerning sustainability among older are, however, not yet well understood. Therefore, there is a need for assessing these intentions and behaviours through the use of a transparently constructed and validated instrument which can be used to measures the construct of environmental sustainability among older people. The aim of this study is to develop a questionnaire measuring how older people view the theme of environmental sustainability in their daily lives, with a focus on the built environment, providing full transparency and reproducibility. The process of development and validation of the SustainABLE-16 Questionnaire followed the COSMIN protocol, and has been conducted in five phases. This rigorous process has resulted in a valid, psychometrically sound, comprehensive 16-item questionnaire. This instrument can be applied to assess older people's beliefs, behaviours and financial aspects regarding environmental sustainability in their lives. The SustainABLE-16 Questionnaire was created in Dutch and in British English.
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While the optimal mean annual temperature for people and nations is said to be between 13 °C and 18 °C, many people live productive lives in regions or countries that commonly exceed this temperature range. One such country is Australia. We carried out an Australia-wide online survey using a structured questionnaire to investigate what temperature people in Australia prefer, both in terms of the local climate and within their homes. More than half of the 1665 respondents (58%) lived in their preferred climatic zone with 60% of respondents preferring a warm climate. Those living in Australia's cool climate zones least preferred that climate. A large majority (83%) were able to reach a comfortable temperature at home with 85% using air-conditioning for cooling. The preferred temperature setting for the air-conditioning devices was 21.7 °C (SD: 2.6 °C). Higher temperature set-points were associated with age, heat tolerance and location. The frequency of air-conditioning use did not depend on the location but rather on a range of other socio-economic factors including having children in the household, the building type, heat stress and heat tolerance. We discuss the role of heat acclimatisation and impacts of increasing air-conditioning use on energy consumption.
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