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Search Results (444)

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Keywords = behavioural flexibility

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28 pages, 503 KiB  
Article
An Examination of the Elements of Cultural Competence and Their Impact on Tourism Services: Case Study in Quintana Roo, Mexico
by María del Pilar Arjona-Granados, José Ángel Sevilla-Morales, Antonio Galván-Vera and Martín Alfredo Legarreta-González
Tour. Hosp. 2025, 6(2), 96; https://doi.org/10.3390/tourhosp6020096 - 22 May 2025
Viewed by 804
Abstract
Economic transformations in emerging countries have resulted in an increase in the volume of international travellers from diverse geographical regions. In the tourism sector, service providers must possess cultural competencies that foster a flexible and appropriate attitude, which in turn affects the perception [...] Read more.
Economic transformations in emerging countries have resulted in an increase in the volume of international travellers from diverse geographical regions. In the tourism sector, service providers must possess cultural competencies that foster a flexible and appropriate attitude, which in turn affects the perception of service. The present study aims to shed light on the motivational factors and cultural behaviours that influence intercultural empathy among staff working in the tourism sector in Quintana Roo. To this end, a comprehensive literature review has been conducted, during which the variables have been validated, and a quantitative study has been undertaken, employing multivariate analysis through a Multiple Correspondence Analysis and inferential statistics with an Ordinal Logistic Regression. The findings of this study demonstrate a positive correlation between motivation and cultural behaviour, which is contingent on experience and age, and its impact on empathy in understanding and meeting the diverse needs of tourists. Cultural motivation is defined as the interest in learning and interacting in multicultural situations, and its impact on behaviour is reflected in appropriate personal management for effective cultural interactions. The probabilities estimated by ordinal logistic regression models of consistently or predominantly exhibiting intercultural empathy increase with age and experience for the most significant variables obtained by the Multiple Correspondence Analysis. Full article
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21 pages, 18600 KiB  
Article
Predicting Clay Swelling Pressure: A Comparative Analysis of Advanced Symbolic Regression Techniques
by Esteban Díaz and Roberto Tomás
Appl. Sci. 2025, 15(10), 5603; https://doi.org/10.3390/app15105603 - 16 May 2025
Viewed by 172
Abstract
Swelling pressure is a key geotechnical property that influences the behaviour and stability of engineering structures built on expansive clayey soils. This pressure can be measured directly through laboratory tests or estimated using indirect methods. This paper analyses a dataset of undisturbed clay [...] Read more.
Swelling pressure is a key geotechnical property that influences the behaviour and stability of engineering structures built on expansive clayey soils. This pressure can be measured directly through laboratory tests or estimated using indirect methods. This paper analyses a dataset of undisturbed clay samples from southeastern Spain using advanced symbolic regression techniques, namely: deep symbolic regression (PhySO), high-performance symbolic regression (PySR), multi-objective symbolic regression (MOSR), and physics-guided symbolic regression (PGSR). These methods provide interpretable results as equations, unlike standard machine learning models. All generated equations showed high performance (R2 > 0.91 and MAE < 23 kPa) and simplicity, making them suitable for practical engineering applications. PySR yielded the best overall metrics (R2 = 0.933, MAE = 20.49 kPa), particularly excelling in high-pressure ranges, while PhySO demonstrated the most balanced performance, especially for low to medium pressures. MOSR minimized edge-case bias, and PGSR, despite lower overall performance, remained competitive. The plasticity index (PI) was identified as the most influential factor in all models, followed by the percentage of fines. The use of undisturbed samples enhanced the reliability of the findings, and the resulting equations enable a flexible estimation of swelling pressure based on commonly available geotechnical parameters. Full article
(This article belongs to the Special Issue Applications of Machine Learning in Geotechnical Engineering)
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20 pages, 7737 KiB  
Article
Battery Electric Vehicles: A Study on State of Charge and Cost-Effective Solutions for Addressing Range Anxiety
by Jason Pollock, Perk Lin Chong, Manu Ramegowda, Nashwan Dawood, Hossein Habibi, Zhonglan Hou, Foad Faraji and Pengyan Guo
Machines 2025, 13(5), 411; https://doi.org/10.3390/machines13050411 - 14 May 2025
Viewed by 286
Abstract
While Battery Electric Vehicles (BEVs) offer environmental benefits by reducing carbon emissions during use, their range remains limited compared to conventionally fuelled vehicles. This paper focuses on identifying factors that directly influence BEV range and explores strategies to mitigate range anxiety among potential [...] Read more.
While Battery Electric Vehicles (BEVs) offer environmental benefits by reducing carbon emissions during use, their range remains limited compared to conventionally fuelled vehicles. This paper focuses on identifying factors that directly influence BEV range and explores strategies to mitigate range anxiety among potential users. Specifically, it reviews the impact of battery cell characteristics and vehicle lightweighting. Using the WLTP Class 3B drive cycle, energy consumption and Depth of Discharge (DoD) were evaluated across various battery capacities. Multiple Lithium-Ion battery models were simulated to analyse discharge behaviour, while vehicle mass composition was examined to assess the effectiveness of lightweighting in extending driving range. A lower initial State of Charge (SoC) and a standard discharge rate were used to estimate the remaining range, highlighting an approximate gain of up to 6 km at lower DoD levels. This work aims to accurately demonstrate how battery technology and structural weight impact energy consumption and usable range in BEVs. Current modelling approaches often overlook the relationship between driver discomfort and battery performance metrics. The main contribution is to address the gap by integrating Li-ion discharge modelling with vehicle dynamics to estimate range and compare cell characteristics. The ultimate goal is to support cost-effective strategies for increasing BEV usability, aligning them more closely with conventional vehicle expectations and enhancing journey flexibility. Full article
(This article belongs to the Special Issue Advances in Vehicle Dynamics)
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15 pages, 270 KiB  
Article
Developing Elite Strength and Conditioning Coaches’ Practice Through Facilitated Reflection
by Chris Szedlak, Bettina Callary and Matthew Smith
Educ. Sci. 2025, 15(5), 603; https://doi.org/10.3390/educsci15050603 - 14 May 2025
Viewed by 223
Abstract
Recent research has suggested that strength and conditioning (S&C) coach development should consider constructivist learning theories to promote coach development and learning of psychosocial coaching competencies. Reflective practice can encourage holistic learning through promoting an internal dialogue of the meaningfulness of an individual’s [...] Read more.
Recent research has suggested that strength and conditioning (S&C) coach development should consider constructivist learning theories to promote coach development and learning of psychosocial coaching competencies. Reflective practice can encourage holistic learning through promoting an internal dialogue of the meaningfulness of an individual’s experiences. Our study aimed to examine the efficacy of a facilitated, guided, and longitudinal reflective process to promote coach learning of psychosocial coaching practice using Moon’s reflective framework. Over a four-week period, six elite S&C coaches engaged in a guided process reflection process with a facilitator. This included daily journaling in an e-diary with the facilitator providing feedback at the end of each week. At the end, each S&C coach participated in an exit interview. Data were analysed using interpretative phenomenological analysis. Findings revealed that there were potential benefits for the S&C coach’s process of reflection such as providing accountability through developing a close relationship with the facilitator, which enabled the S&C coaches to more critically link learning to behaviour change. Furthermore, S&C coaches’ learning resulted in developing awareness of self/athlete’s needs, increased flexibility, and enhanced confidence. This resulted in S&C coaches developing psychosocial coaching competencies that enabled them to change their practice to become more athlete centred. Full article
19 pages, 6692 KiB  
Article
Design and Hardware Implementation of a Highly Flexible PRNG System for NIST-Validated Pseudorandom Sequences
by María de Lourdes Rivas Becerra, Juan José Raygoza Panduro, Edwin Christian Becerra Alvarez, Susana Ortega Cisneros and José Luis González Vidal
Chips 2025, 4(2), 23; https://doi.org/10.3390/chips4020023 - 7 May 2025
Viewed by 109
Abstract
This work presents the design of a system of a highly flexible pseudorandom number generator system (PRNG) incorporating both conventional and neuro-generators. The system integrates four internal generators with different conditions to produce new output sequences with adequate bits distribution and complexity. Two [...] Read more.
This work presents the design of a system of a highly flexible pseudorandom number generator system (PRNG) incorporating both conventional and neuro-generators. The system integrates four internal generators with different conditions to produce new output sequences with adequate bits distribution and complexity. Two generators function at a frequency of 100 MHz with adjustable frequency settings, while two neuro-generators employ impulse neurons with distinct behaviours at 4 kHz, also modifiable. The proposed system meets 12 statistical randomness standards based on NIST’s (National Institute of Standards and Technology of U. S.) test suite, including the Frequency test, Binary Matrix Rank test, Linear Complexity test, and Random Excursion test, among others. Each resulted in a P-value greater than 0.01, confirming the pseudo-randomness of the generated sequences. The system is implemented on a reconfigurable device FPGA (Field Programmable Gate Array), with a low occupancy percentage, demonstrating its feasibility for various applications. Full article
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22 pages, 4631 KiB  
Article
ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering
by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif and Nasrin Shabani
Algorithms 2025, 18(4), 238; https://doi.org/10.3390/a18040238 - 21 Apr 2025
Viewed by 705
Abstract
Customers are the cornerstone of business success across industries. Companies invest significant resources in acquiring new customers and, more importantly, retaining existing ones. However, customer churn remains a major challenge, leading to substantial financial losses. Addressing this issue requires a deep understanding of [...] Read more.
Customers are the cornerstone of business success across industries. Companies invest significant resources in acquiring new customers and, more importantly, retaining existing ones. However, customer churn remains a major challenge, leading to substantial financial losses. Addressing this issue requires a deep understanding of customers’ cognitive status and behaviours, as well as early signs of churn. Predictive and Machine Learning (ML)-based analysis, when trained with appropriate features indicative of customer behaviour and cognitive status, can be highly effective in mitigating churn. A robust ML-driven churn analysis depends on a well-developed feature engineering process. Traditional churn analysis studies have primarily relied on demographic, product usage, and revenue-based features, overlooking the valuable insights embedded in customer–company interactions. Recognizing the importance of domain knowledge and human expertise in feature engineering and building on our previous work, we propose the Customer Churn-related Knowledge Base (ChurnKB) to enhance feature engineering for churn prediction. ChurnKB utilizes textual data mining techniques such as Term Frequency-Inverse Document Frequency (TF-IDF), cosine similarity, regular expressions, word tokenization, and stemming to identify churn-related features within customer-generated content, including emails. To further enrich the structure of ChurnKB, we integrate Generative AI, specifically large language models, which offer flexibility in handling unstructured text and uncovering latent features, to identify and refine features related to customer cognitive status, emotions, and behaviours. Additionally, feedback loops are incorporated to validate and enhance the effectiveness of ChurnKB.Integrating knowledge-based features into machine learning models (e.g., Random Forest, Logistic Regression, Multilayer Perceptron, and XGBoost) improves predictive performance of ML models compared to the baseline, with XGBoost’s F1 score increasing from 0.5752 to 0.7891. Beyond churn prediction, this approach potentially supports applications like personalized marketing, cyberbullying detection, hate speech identification, and mental health monitoring, demonstrating its broader impact on business intelligence and online safety. Full article
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42 pages, 3689 KiB  
Article
Gossip Coordination Mechanism for Decentralised Learning
by Philippe Glass and Giovanna Di Marzo Serugendo
Energies 2025, 18(8), 2116; https://doi.org/10.3390/en18082116 - 20 Apr 2025
Viewed by 151
Abstract
In smart grids, renewable energies play a predominant role, but they produce more and more data, which are volatile by nature. As a result, predicting electrical behaviours has become a real challenge and requires solutions that involve more all microgrid entities in learning [...] Read more.
In smart grids, renewable energies play a predominant role, but they produce more and more data, which are volatile by nature. As a result, predicting electrical behaviours has become a real challenge and requires solutions that involve more all microgrid entities in learning processes. This research proposes the design of a coordination model that integrates two decentralised approaches to distributed learning applied to a microgrid: the gossip federated learning approach, which consists of exchanging learning models between neighbouring nodes, and the gossip ensemble learning approach, which consists of exchanging prediction results between neighbouring nodes. The experimentations, based on real data collected in a living laboratory, show that the combination of a coordination model and intelligent digital twins makes it possible to implement and operate these two purely decentralised learning approaches. The results obtained on the predictions confirm that these two implemented approaches can improve the efficiency of learning on the scale of a microgrid, while reducing the congestion caused by data exchanges. In addition, the generic gossip mechanism offers the flexibility to easily define different variants of an aggregation operator, which can help to maximise the performance obtained. Full article
(This article belongs to the Section F5: Artificial Intelligence and Smart Energy)
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28 pages, 15740 KiB  
Article
Enhancing Mechanical Energy Absorption of Honeycomb and Triply Periodic Minimal Surface Lattice Structures Produced by Fused Deposition Modelling in Reusable Polymers
by Alin Bustihan, Ioan Botiz, Ricardo Branco and Rui F. Martins
Polymers 2025, 17(8), 1111; https://doi.org/10.3390/polym17081111 - 19 Apr 2025
Viewed by 329
Abstract
This study investigated the mechanical energy absorption properties of polymeric lattice structures fabricated using additive manufacturing. Existing studies have primarily focused on rigid or single-use materials, with limited attention given to flexible polymers and their behaviour under repeated compressive loading. Addressing this gap, [...] Read more.
This study investigated the mechanical energy absorption properties of polymeric lattice structures fabricated using additive manufacturing. Existing studies have primarily focused on rigid or single-use materials, with limited attention given to flexible polymers and their behaviour under repeated compressive loading. Addressing this gap, the structures investigated in this study are manufactured using three flexible polymers—polyether block amide, thermoplastic polyurethane, and thermoplastic copolyester elastomer—to enhance the reusability performance. Two high-performance designs were analysed, namely honeycomb structures (inspired by pomelo peel and simply hexagonal arrangements) and 3D triply periodic minimal surface structure of the type FRD. The primary objective was to evaluate their energy absorption capacity and reusability using three repeated compression tests. These tests revealed that thermoplastic copolyester elastomer exhibited the highest energy absorption in initial impact conditions, but lower values for the following compressions. However, polyether block amide demonstrated superior reusability, maintaining a consistent energy absorption efficiency of 56.1% over multiple compression cycles. The study confirms that modifying triply periodic minimal surface structures along the z-axis enhances their absorption efficiency, with even-numbered z-parameter structures outperforming odd-numbered ones due to their complete cell structure. These findings highlight the critical role of structural geometry and material selection to optimise polymeric lattice structures for lightweight reusable energy absorption applications, such as automotive safety and impact protection. Full article
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16 pages, 276 KiB  
Article
Teacher and School Mediation for Online Risk Prevention and Management: Fostering Sustainable Education in the Digital Age
by Esther Chiner, Marcos Gómez-Puerta, Santiago Mengual-Andrés and Gladys Merma-Molina
Sustainability 2025, 17(8), 3711; https://doi.org/10.3390/su17083711 - 19 Apr 2025
Viewed by 451
Abstract
(1) Background: The increasing use of information and communication technologies (ICT) in educational environments has introduced new challenges related to digital safety and sustainability. Teacher mediation and institutional initiatives are pivotal for preventing and managing Internet-related risks. This study investigates teacher and school [...] Read more.
(1) Background: The increasing use of information and communication technologies (ICT) in educational environments has introduced new challenges related to digital safety and sustainability. Teacher mediation and institutional initiatives are pivotal for preventing and managing Internet-related risks. This study investigates teacher and school mediation strategies for online risk prevention, analysing differences across educational settings and stages in Spain to inform inclusive digital safety practices. (2) Methodology: a quantitative study was conducted using a cross-sectional survey design involving 550 elementary and secondary school teachers from both mainstream and special education schools. (3) Results: Most schools implement intervention plans to mitigate risks associated with students’ Internet use, although the approach to these plans varies according to educational stage and school setting. Teachers employ strategies such as setting classroom rules and supporting students with online challenges, with secondary school teachers and those in mainstream schools tending to adopt more comprehensive or conversation-based prevention strategies. (4) Conclusions: Teachers and schools play a crucial role in ensuring digital safety and sustainability. Future efforts should strengthen digital skills, foster responsible online behaviour, and build inclusive, flexible learning environments according to the differing needs observed across stages and school settings. Full article
25 pages, 3353 KiB  
Article
Thermo-Physical Behaviour of Thermoplastic Composite Pipe for Oil and Gas Applications
by Obinna Okolie, Nadimul Haque Faisal, Harvey Jamieson, Arindam Mukherji and James Njuguna
Polymers 2025, 17(8), 1107; https://doi.org/10.3390/polym17081107 - 19 Apr 2025
Viewed by 369
Abstract
Thermoplastic composite pipes (TCP) consist of three distinct layers—liner, reinforcement, and coating—offering superior advantages over traditional industrial pipes, including flexibility, lightweight construction, and corrosion resistance. This study systematically characterises the thermal properties of TCP layers and their compositions using a multi-method approach. Thermal [...] Read more.
Thermoplastic composite pipes (TCP) consist of three distinct layers—liner, reinforcement, and coating—offering superior advantages over traditional industrial pipes, including flexibility, lightweight construction, and corrosion resistance. This study systematically characterises the thermal properties of TCP layers and their compositions using a multi-method approach. Thermal analysis was conducted through differential scanning calorimetry (DSC) for isothermal and non-isothermal crystallisation, thermogravimetric analysis (TGA) for thermal stability, and Fourier transform infrared spectroscopy (FTIR) for material identification. FTIR confirmed polyethylene as the primary component of TCP, with compositional variations across the layers. TGA results indicated that thermal degradation begins at approximately 200 °C, with complete decomposition at 500 °C. DSC analysis revealed a double melting peak, prompting further investigation into its mechanisms. On-isothermal crystallisation kinetics, analysed at cooling rates of 10 °C/min and 50 °C/min, revealed an anisotropic crystalline growth pattern. Although nucleation occurs uniformly, the subsequent three-dimensional crystalline growth is governed more by the degree of supercooling than by the crystallography of the glass fibres. This underscores the importance of precisely controlling the cooling rate during manufacturing to optimise the anisotropic properties of the reinforced layer. This study also demonstrates the value of FTIR, TGA, and DSC techniques in characterising the thermo-physical behaviour of TCP, offering critical insights into thermal expansion, shrinkage phenomena, and overall material stability. Given the limited body of research on this specific TCP formulation, the findings presented here lay a foundation for both quality enhancement and process optimisation. Moreover, the paper offers a distinctive perspective on the dynamic behaviour, thermal expansion, and long-term performance of TCP in demanding oil and gas environments. Full article
(This article belongs to the Section Polymer Applications)
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13 pages, 1259 KiB  
Article
Energy Production from Landfill Gas: Short-Term Management
by Nuno Soares Domingues
Energies 2025, 18(8), 1974; https://doi.org/10.3390/en18081974 - 11 Apr 2025
Viewed by 352
Abstract
An increasing lack of raw materials, resource depletion, environmental impacts and other concerns have changed the way the population faces garbage disposal and municipalities implement waste management strategies. The aggravated global rise in municipal solid waste (MSW) generation has led to a new [...] Read more.
An increasing lack of raw materials, resource depletion, environmental impacts and other concerns have changed the way the population faces garbage disposal and municipalities implement waste management strategies. The aggravated global rise in municipal solid waste (MSW) generation has led to a new stage in full development, with objectives and targets set by the European Union regarding reducing the production of MSW. The targets also include the increasing selective collection, reuse, recycling and recovery (organic and energetic) of the waste produced. At the same time, the European Union has also set caps for the greenhouse gas emissions and for increasing the use of alternative renewable energy sources. In this context, one of the sources of renewable energy that is beginning to be used to produce electricity in our country is biogas. Finally, AD promotes the development of a circular economy. The present study introduces the formalism for a computer application that simulates the technical–economic behaviour of the short-term management of biogas for the conversion of electricity, and the mathematical model is formulated as a mathematical programming problem with constraints. A simulation for a case study of short-term management is given using the real landfill data available. The case study proves the ability of the LandGEM, despite some authors’ support that the Tabasaran–Rettenberger model provided a more reliable estimate, especially when compared to actual landfill data. The present paper is a contribution to the optimisation of the management of electricity from the use of biogas, namely the second phase of the Strategic Plan for Urban Waste. In addition to complying with the legislation in force, the use of biogas to produce electricity is an added value for the concessionaires of waste treatment and final destination units, as this alternative energy source can provide not only self-sufficiency in electricity for these units but also the export of surplus energy to the National Electricity Grid, thus contributing to the self-sustaining management and energy flexibility that is intended for these infrastructures. Full article
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26 pages, 28205 KiB  
Article
Enhanced Mechanical Performance of Resin-Infused 3D-Printed Polymer Lattices
by Jakub J. Słowiński, Maciej Roszak, Mikołaj Kazimierczak, Grzegorz Skrzypczak and Maksymilian Stępczak
Polymers 2025, 17(8), 1028; https://doi.org/10.3390/polym17081028 - 10 Apr 2025
Viewed by 449
Abstract
Fused deposition modelling (FDM) technology provides a flexible and cost-effective solution for the manufacture of polymer components, enabling the precise design of structures and the incorporation of a variety of composite materials. Its development is confirmed by numerous studies on fibre reinforcements (e.g., [...] Read more.
Fused deposition modelling (FDM) technology provides a flexible and cost-effective solution for the manufacture of polymer components, enabling the precise design of structures and the incorporation of a variety of composite materials. Its development is confirmed by numerous studies on fibre reinforcements (e.g., GFRP and CF) and thermosetting resin modifications, resulting in improved impact strength and fracture toughness and increased thermal stability of products. The final mechanical properties are significantly influenced by processing parameters (e.g., fill density, layer height, and printing speed) and internal geometry (e.g., lattice structures), which can be further optimised by numerical analyses using constitutive models such as the Johnson–Cook model. The focus of the study presented here is on the fabrication of composites from FDM dies filled with F8 polyurethane resin. Filaments, including PETG carbon and PETG, were tested for potential applications with the resin. A static compression test, supported by numerical analysis using the Johnson–Cook model, was carried out to identify key mechanical characteristics and to predict the material’s behaviour under different loading conditions. The results indicate that these structures exhibit numerous potential delamination planes and voids between filament paths, leading to relatively low maximum stress values (σm ≈ 2.5–3 MPa). However, the impregnation with polyurethane resin significantly enhances these properties by bonding the layers and filling the pores, resulting in a more homogeneous and stronger composite. Additionally, numerical simulations effectively captured key aspects of structural behaviour, identifying critical stress concentration areas, particularly along the side walls and in regions forming triangular stress zones. These findings provide valuable insights into the potential of resin-filled FDM structures in engineering applications, demonstrating their improved performance over purely printed samples. Full article
(This article belongs to the Special Issue Polymers and Polymer Composite Structures for Energy Absorption)
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23 pages, 7985 KiB  
Article
Development and Characterization of PBS/EA Cellulose and PCL/EA Cellulose Biocomposites: Structural, Morphological, and Thermal Insights for Sustainable Applications
by Fisokuhle Innocentia Kumalo, Moipone Alice Malimabe, Mafereka Francis Tyson Mosoabisane and Thandi Patricia Gumede
Polymers 2025, 17(7), 971; https://doi.org/10.3390/polym17070971 - 2 Apr 2025
Viewed by 348
Abstract
This study investigates the effect of Eucomis autumnalis (EA) cellulose on the structural, thermal, and crystallization behaviour of polybutylene succinate (PBS) and polycaprolactone (PCL) composites. X-ray diffraction (XRD) results showed that in both matrices, EA cellulose promoted nucleation, as indicated by increased peak [...] Read more.
This study investigates the effect of Eucomis autumnalis (EA) cellulose on the structural, thermal, and crystallization behaviour of polybutylene succinate (PBS) and polycaprolactone (PCL) composites. X-ray diffraction (XRD) results showed that in both matrices, EA cellulose promoted nucleation, as indicated by increased peak intensity, while differential scanning calorimetry (DSC) showed reduced melting enthalpy, suggesting the formation of smaller, less perfect crystals. In PBS composites, EA cellulose acted as a crystallization disruptor, reducing crystallinity and enthalpy. Moreover, it slightly lowered the melting temperature. This is because EA cellulose contains β-(1→4) glycosidic bonds, which introduce –O– (ether) linkages along its polymer backbone. These linkages allow for a degree of rotational flexibility. When the cellulose is incorporated into PBS, this structural characteristic may contribute to a reduction in Tm, likely by disrupting the crystallization of PBS chains. At 1 wt.% EA cellulose, broader, more intense melting peaks indicated imperfect crystal formation, while higher loadings (3 and 5 wt.%) resulted in narrower, less intense peaks, reflecting reduced crystallinity. These results are consistent with cooling-curve results and SEM images showing structural irregularities. In PCL composites, EA cellulose similarly reduced crystallinity and enthalpy without significantly affecting melting or crystallization temperatures. The decrease in the melting enthalpy from 55.6 J/g to 47.6 J/g suggested the formation of thinner lamellae and less organized crystals, a conclusion supported by stable crystallization temperatures and declining peak intensities in cooling curves. The combination of XRD and DSC data highlighted the dual role of EA cellulose: it enhances nucleation while hindering crystal growth, leading to the formation of more amorphous structures in both PBS and PCL matrices. These findings offer valuable insights into the potential use of EA cellulose as a functional modifier to tailor the properties of biopolymer composites for environmentally friendly, biodegradable applications. Full article
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22 pages, 983 KiB  
Article
Assessment of Gaze Fixations and Shifts in Children with Cerebral Palsy: A Comparison of Computer- and Object-Based Approaches
by Tom Griffiths, Michael T. Clarke and John Swettenham
J. Clin. Med. 2025, 14(7), 2326; https://doi.org/10.3390/jcm14072326 - 28 Mar 2025
Viewed by 375
Abstract
Background/Objectives: Gaze behaviours, such as fixation on single objects, and switching gaze between two objects are important for signaling messages, making choices or controlling a computer for children with cerebral palsy (CP) and similar movement disabilities. Observing these behaviours can be challenging [...] Read more.
Background/Objectives: Gaze behaviours, such as fixation on single objects, and switching gaze between two objects are important for signaling messages, making choices or controlling a computer for children with cerebral palsy (CP) and similar movement disabilities. Observing these behaviours can be challenging for clinicians, with a lack of agreement on how they can be objectively quantified or rated. Methods: This study compares two methods of eliciting and observing gaze behaviours: a computer presentation using an eye tracker and an object presentation scored by two independent observers in order to explore the utility of each to clinicians working in this area. Children with CP (n = 39) attempted single-target fixation (STF) and target–target fixation shift (TTFS) tasks using both presentations and the results were compared. Results: Six children were unable to calibrate the eye tracker to the accuracy level required. Significantly higher scores for both STF (81.3% object presentation and 30.3% computer presentation, p < 0.01) and TTFS (70.1% and 26.9%, p < 0.01) were seen on the object presentation, with children’s performance not predicted by developmental age, severity of CP or presence or absence of strabismus. It is not possible to definitively state which method gives the “correct” result; however, the difference in reported success rate merits further discussion. Conclusions: Whilst eye tracking may present an “entry barrier” for some children in terms of its accuracy and calibration requirements, object presentation carries with it the risk of over-interpreting children as having fixated. Conversely, eye tracking may be better at recording fixations in children with strabismus, where object-based paradigms may offer more flexible administration for clinicians. The variability in children’s performance on both presentations underlines the risk of assuming these skills to be present and the importance of assessing gaze behaviours in individual children. Full article
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18 pages, 5121 KiB  
Article
Understanding the Design and Sensory Behaviour of Graphene-Impregnated Textile-Based Piezoresistive Pressure Sensors
by Md Faisal Mahmud, Md Raju Ahmed, Prasad Potluri and Anura Fernando
Sensors 2025, 25(7), 2000; https://doi.org/10.3390/s25072000 - 22 Mar 2025
Viewed by 497
Abstract
Graphene-based textile pressure sensors are emerging as promising candidates for wearable sensing applications due to their high sensitivity, mechanical flexibility, and low energy consumption. This study investigates the design, fabrication, and electromechanical behaviour of graphene-coated nonwoven textile-based piezoresistive pressure sensors, focusing on the [...] Read more.
Graphene-based textile pressure sensors are emerging as promising candidates for wearable sensing applications due to their high sensitivity, mechanical flexibility, and low energy consumption. This study investigates the design, fabrication, and electromechanical behaviour of graphene-coated nonwoven textile-based piezoresistive pressure sensors, focusing on the impact of different electrode materials and fabrication techniques. Three distinct sensor fabrication methods—drop casting, electrospinning, and electro-spraying—were employed to impregnate graphene onto nonwoven textile substrates, with silver-coated textile electrodes integrated to enhance conductivity. The fabricated sensors were characterised for their morphology (SEM), chemical composition (FTIR), and electromechanical response under cyclic compressive loading. The results indicate that the drop-cast sensors exhibited the lowest initial resistance (~0.15 kΩ) and highest sensitivity (10.5 kPa−1) due to their higher graphene content and superior electrical connectivity. Electro-spun and electro-sprayed sensors demonstrated increased porosity and greater resistance fluctuations, highlighting the role of fabrication methods in sensor performance. Additionally, the silver-coated knitted electrodes provided the most stable electrical response, while spun-bonded and powder-bonded nonwoven electrodes exhibited higher hysteresis and resistance drift. These findings offer valuable insights into the optimisation of graphene-based textile pressure sensors for wearable health monitoring and smart textile applications, paving the way for scalable, low-power sensing solutions. Full article
(This article belongs to the Section Chemical Sensors)
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