Search Results (7,650)

Background: Auricular defects resulting from congenital anomalies, trauma, or oncologic resection pose significant functional and psychosocial challenges. When autologous reconstruction is not feasible or not desired, implant-retained auricular prostheses represent a reliable alternative with high patient satisfaction. This study aimed to systematically evaluate the clinical performance of craniofacial implants used for auricular prosthetic rehabilitation, focusing on implant survival, prosthetic outcomes, workflow typologies, and complications. A secondary objective was to illustrate the long-term validity of a minimally invasive navigation technique through a clinical case with 6-year follow-up. Methods: A systematic review was conducted according to PRISMA guidelines. Clinical studies published between 2005 and 2025 reporting outcomes of implant-retained auricular prostheses were searched in PubMed and Scopus databases. Data were extracted on implant type, survival rates, prosthetic performance, workflow, and complications. Risk of bias was assessed using appropriate tools based on each study design. Results: A total of thirty-two studies were included, comprising fifteen case reports, fifteen case series, one cohort study, and one prospective observational study. Implant survival was consistently high across all workflow categories, with failures predominantly associated with irradiated or anatomically compromised bone. Prosthetic outcomes were favorable, showing excellent esthetics, stable retention, and high patient satisfaction irrespective of manufacturing method, although digital and navigation-assisted workflows improved reproducibility, symmetry, and planning precision. Complication rates were low and generally limited to mild peri-abutment inflammation manageable with conservative care. The clinical case confirmed these findings, showing stable osseointegration, healthy soft tissues, and uncompromised prosthetic function at 6-year follow-up. Conclusions: Implant-retained auricular prostheses show predictable long-term success, independent of whether traditional, hybrid, or fully digital workflows are employed. Digital technologies enhance surgical accuracy, minimize morbidity, and streamline prosthetic fabrication, although high-quality comparative studies remain limited. Full article

This paper presents a PSCAD-based analysis of short-circuit faults and protection characteristics in a real distribution-level microgrid that integrates a 1 MWh battery energy storage system (BESS) with a 500 kW power conversion system (PCS) and a 500 kW photovoltaic (PV) plant connected to a 22.9 kV feeder. While previous studies often rely on simplified inverter models, this paper addresses the critical gap by integrating actual manufacturer-defined control parameters and cable impedances. This allows for a precise analysis of sub-millisecond transient behaviors, which is essential for developing robust protection schemes in inverter-dominated microgrids. The PSCAD model is first verified under grid-connected steady-state operation by examining PV output, BESS power, and grid voltage at the point of common coupling. Based on the validated model, DC pole-to-pole faults at the PV and ESS DC links and a three-phase short-circuit fault at the low-voltage bus are simulated to characterize the fault current behavior of the grid, BESS and PV converters. The DC fault studies confirm that current peaks are dominated by DC-link capacitor discharge and are strongly limited by converter controls, while the AC three-phase fault is mainly supplied by the upstream grid. As an initial application of the model, an instantaneous current change rate (ICCR) algorithm is implemented as a dedicated DC-side protection function. For a pole-to-pole fault, the ICCR index exceeds the 100 A/ms threshold and issues a trip command within 0.342 ms, demonstrating the feasibility of sub-millisecond DC fault detection in converter-dominated systems. Beyond this example, the validated PSCAD model and associated data set provide a practical platform for future research on advanced DC/AC protection techniques and protection coordination schemes in real BESS–PV microgrids. Full article

The sustained interest in efficient, low-cost, and straightforward-to-manufacture lasers has prompted intense research into organic semiconductor laser emitter materials in recent decades. The main focus of this research is determining the optical gains and losses of amplified spontaneous emission (ASE) in order to describe materials by their amplification signature. A method that has been used for decades as the standard technique for determining gain characteristics is the variable-stripe-length (VSL) method. The success of the VSL method has led to the development of further measurement techniques. These techniques provide a detailed insight into the nature of optical amplification. One such method is the scattered emission profile (SEP) method. In this study, we present an extension of the SEP method, the Diffracted Emission Profile (DEP) method. The DEP method is based on the detection of ASE by partial decoupling of waveguide modes diffracted by a one-dimensional grating integrated into a planar waveguide. Diffraction causes a proportion of the intensity to exit the waveguide, transferring the growth and decay process of the waveguide mode to the transverse mode profile of the diffracted mode. In the present article, an approach to determine the amplification signature of an organic copolymer is presented, utilizing partial decoupled radiation. Full article

This work presents the development of a differential-drive wheeled mobile robot educational prototype, manufactured using 3D additive techniques. The robot is powered by an embedded ARM-based computing system and uses open-source software. To validate the prototype, a trajectory-tracking task was successfully implemented. The aim of this contribution is to provide an easily replicable prototype for teaching automatic control and related engineering topics in academic settings. Full article

Background: Orbital dermoid cysts are common benign lesions; however, deep-seated or recurrent lesions near the orbital apex pose major surgical challenges due to their proximity to critical neurovascular structures. Lateral orbitotomy remains the reference approach, but accurate osteotomies and stable reconstruction can be difficult to achieve using conventional techniques. This study reports our initial experience using a fully digital, hospital-based point-of-care (POC) workflow to enhance precision and safety in complex orbital dermoid cyst surgery. Methods: We present a case series of three patients with orbital dermoid cysts treated at a tertiary center (2024–2025) using a comprehensive digital workflow. Preoperative assessment included CT and/or MRI followed by virtual surgical planning (VSP) with orbit–tumor segmentation and 3D modeling. Cutting guides and patient-specific implants (PSIs) were manufactured in-house under a certified hospital-based POC protocol. Surgical strategies were tailored to each lesion and included piezoelectric osteotomy, intraoperative navigation, intraoperative CT, and structured-light scanning when indicated. Results: Complete en bloc resection was achieved in all cases without capsular rupture or optic nerve injury. Intraoperative CT confirmed complete lesion removal and accurate PSI positioning and fitting. Structured-light scanning enabled radiation-free postoperative monitoring when used. All patients preserved full ocular motility, visual acuity, and facial symmetry, with no complications or recurrences during follow-up. Conclusions: The integration of VSP, in-house POC manufacturing, and image-guided surgery within a lateral orbitotomy approach provides a reproducible and fully integrated workflow. This strategy appears to improve surgical precision and safety while supporting optimal long-term functional and aesthetic outcomes in challenging orbital dermoid cyst cases. Full article

Digital Light Processing (DLP), which operates through a layer-by-layer deposition, has proven to be a promising technique for obtaining complex and customized architectures. However, there are still numerous unresolved challenges in ceramics additive manufacturing, among which is delamination due to suboptimal adhesion between the layers, which threatens the structural integrity and properties of samples. According to recent findings, excess surface hydroxyl groups were identified as being responsible for this defect; a suitable calcination pre-treatment of the ceramic powder could be effective in significantly mitigating delamination flaws in mullite DLP printed bodies. Therefore, in addition to optimizing the printable slurry formulation and printing parameters (mainly in terms of curing energy and layer resolution), this work aimed at investigating the influence of the calcination of a commercial mullite powder (added with magnesium nitrate hexahydrate, as a precursor of the sintering aid MgO) as a simple and effective treatment to additively shape ceramic bodies with limited flaws and enhanced density. The surface characteristics evolution of the mullite powder was investigated, specifically comparing samples after magnesium nitrate hexahydrate addition and ball-milling in water (labeled as BM), and after an additional calcination (BMC). In particular, the effect of the superficial -OH groups detected by FTIR analysis in the BM powder, but not in the BMC sample, was studied and correlated to the properties of the respective ceramic slurry in terms of rheological behavior and curing depth. The hydrophilicity of BM powders, due to superficial hydroxyls groups, affects ceramic powder dispersion and wettability by the resin, causing a weak interface. At the same time, it promotes photopolymerization of the light-sensitive resin, thus inducing the as-printed matrix embrittlement. Anyhow, its photopolymerization degree, equal to 67% and 55% for BM and BMC, respectively, was enough to guarantee the printability of both slurries. However, the use of BMC significantly reduced flaw occurrence in the as-printed bodies and the final density of the samples sintered at 1450 °C (without an isothermal step) was increased (approx. 60% and 50% of the theoretical value for BMC and BM, respectively). Thus, the target porosity of the ceramic bodies was guaranteed, and their structural integrity achieved without any increase in sintering temperature but with a simple powder treatment. Full article

Fused deposition modeling (FDM) suffers from unpredictable mechanical properties in nominally identical prints. Current quality assurance relies on destructive testing or expensive post-process inspection, while existing machine learning approaches focus primarily on printing parameters rather than real-time thermal environments. The objective of this proof-of-concept study is to develop a low-cost, non-destructive framework for predicting tensile strength during FDM printing by directly measuring convective thermal gradients surrounding the print. To accomplish this, we introduce thermal fingerprinting: a novel non-destructive technique that combines Background-Oriented Schlieren (BOS) imaging with machine learning to predict tensile strength during printing. We captured thermal gradient fields surrounding PLA specimens (n = 30) under six controlled cooling conditions using consumer-grade equipment (Nikon D750 camera, household hairdryers) to demonstrate low-cost implementation feasibility. BOS imaging was performed at nine critical layers during printing, generating thermal gradient data that was processed into features for analysis. Our initial dual-model ensemble system successfully classified cooling conditions (100%) and showed promising correlations with tensile strength (initial 80/20 train–test validation: R² = 0.808, MAE = 0.279 MPa). However, more rigorous cross-validation revealed the need for larger datasets to achieve robust generalization (five-fold cross-validation R² = 0.301, MAE = 0.509 MPa), highlighting typical challenges in small-sample machine learning applications. This work represents the first successful application of Schlieren imaging to polymer additive manufacturing and establishes a methodological framework for real-time quality prediction. The demonstrated framework is directly applicable to real-time, non-contact quality assurance in FDM systems, enabling on-the-fly identification of mechanically unreliable prints in laboratory, industrial, and distributed manufacturing environments without interrupting production. Full article

Background/Objectives: Isolated cleft lips and/or palates often require orthognathic treatment. Traditional planning based on 2D images and plaster models limits precision; therefore, virtual surgical planning (VSP) and Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) technologies are increasingly being used. The aim of this scoping review was to analyze the techniques, outcomes, and gaps in research on VSP in orthognathics for patients with isolated (non-syndromic) clefts. Methods: Searches were conducted in July 2025 in seven databases (including PubMed, Scopus, and Cochrane) without language restrictions, in accordance with the PRISMA guidelines for scoping reviews. Of the 2836 records, 36 publications were eligible after deduplication and full-text screening, and their Level of Evidence (LoE) was assessed using the Oxford CEBM scale. A risk of bias assessment was also conducted according to JBI tools. Results: The identified studies primarily comprised LoE III and IV; there were no systematic reviews or randomized controlled trials (LoE I). Descriptions of bimaxillary procedures and LeFort I osteotomies dominated. The most commonly used software was ProPlan CMF, Dolphin 3D, and Rhinoceros, although other tools have emerged in recent years. The available studies suggest that VSP increases translational and rotational accuracy and facilitates individualized treatment, and bimaxillary procedures bring better functional and aesthetic outcomes in patients with severe maxillary hypoplasia. Conclusions: Despite the growing interest in VSP in orthognathics, the scientific evidence is limited and mostly of lower quality. Well-designed prospective studies are needed to assess the long-term stability, quality of life, and cost-effectiveness of modern technologies. Full article

Printed electronics (PE) have emerged as a rapidly growing technology owing to their potential for low-cost fabrication, flexibility, and scalable device manufacturing. The dependence on fossil-based components raises environmental concerns, leading the scientific community toward sustainable solutions, aiming to reduce the accumulation of electronic waste (e-waste) in the environment and the emission of toxic gases, as well as to offer a circular solution in the sector. This review presents an in-depth overview of biobased polymeric materials in printed and organic (bio-)electronics. Firstly, the principal printing techniques are presented in detail. The review proceeds by outlining the various biobased synthetic and natural polymers, along with their blends, that are employed in the fabrication of biobased substrates for printed devices. Finally, the review emphasizes the existing challenges and constraints in the field of PE, along with the promising opportunities for its future advancement. Full article

Optical frames are used worldwide to correct visual impairments, protect from UV damage, or simply for fashion purposes. Optical frames are often made of poorly biodegradable and fossil-based materials, with designs not targeted to everyone’s tastes and requirements. Additive manufacturing processes allow personalisation of optical frames and the use of new sustainable biomaterials to replace fossil-based ones. This comprehensive review combines an extensive survey of the scientific literature, market trends, and information from other relevant sources, analysing the biomaterials currently used in additive manufacturing and identifying biomaterials (biopolymers, natural fibres, and natural additives) with the potential to be developed into biocomposites for printing optical frames. Requirements for optical devices were carefully considered, such as standards, regulations, and demands for manufacturing materials. By comparing with fossil-based analogues and by discussing the chemical, physical, and mechanical properties of each biomaterial, it was found that combining various materials in biocomposites is promising for achieving the desirable properties for printing optical frames. The advantages of the various techniques of this cutting-edge technology were also analysed and discussed for optical industry applications. This study aims to answer the central research question: which biopolymers and biocomposite constituents (natural fibres, plasticisers, and additives) have the ideal mechanical, thermal, physical, and chemical properties for combining into a biomaterial suitable for producing sustainable, customisable, and inclusive optical frames on demand, using additive manufacturing techniques. Full article

Background: Working capital management plays a critical role in ensuring business liquidity and financial sustainability. However, few studies in developing economies have employed multivariate statistical techniques to optimize working capital decisions. This study addresses this gap by applying discriminant analysis to classify Ecuadorian manufacturing firms according to their financial sustainability and business continuity. Methods: A quantitative approach was applied to a sample of 112 manufacturing companies located in Zone 3 of Ecuador, covering the 2017–2020 period. The model incorporated working capital indicators and the Z-Score index as independent variables, while company size served as the categorical dependent variable. Results: The discriminant function retained two significant predictors—Working Capital (2019) and Z-Score (2017)—with an eigenvalue of 0.191, a canonical correlation of 0.400, and an overall classification accuracy of 71.4%. Box’s M test (p = 0.000) indicated unequal covariance matrices, suggesting cautious interpretation but acceptable robustness of the model. Conclusions: This study concludes that working capital and Z-Score are effective indicators for assessing financial sustainability and predicting firm continuity. The findings provide practical insights for managers and policymakers to enhance financial efficiency and resource allocation. The originality of this work lies in the application of discriminant analysis to model financial sustainability in Ecuador’s manufacturing sector, offering a statistical foundation for future optimization models. Full article

Additive manufacturing has been adopted in several industries including the medical field to develop new personalised medical implants including tissue engineering scaffolds. Custom patient-specific scaffolds can be additively manufactured to speed up the wound healing process. The aim of this study was to design, fabricate, and evaluate a range of materials and scaffold architectures for 3D-printed wound dressings intended for soft tissue applications, such as skin repair. Multiple biocompatible polymers, including polylactic acid (PLA), polyvinyl alcohol (PVA), butenediol vinyl alcohol copolymer (BVOH), and polycaprolactone (PCL), were fabricated using a material extrusion additive manufacturing technique. Eight scaffolds, five with circular designs (knee meniscus angled (KMA), knee meniscus stacked (KMS), circle dense centre (CDC), circle dense edge (CDE), and circle no gradient (CNG)), and three square scaffolds (square dense centre (SDC), square dense edge (SDE), and square no gradient (SNG), with varying pore widths and gradient distributions) were designed using an open-source custom toolpath generator to enable precise control over scaffold architecture. An in vitro degradation study in phosphate-buffered saline demonstrated that PLA exhibited the greatest material stability, indicating minimal degradation under the tested conditions. In comparison, PVA showed improved performance relative to BVOH, as it was capable of absorbing a greater volume of exudate fluid and remained structurally intact for a longer duration, requiring up to 60 min to fully dissolve. Tensile testing of PLA scaffolds further revealed that designs with increased porosity towards the centre exhibited superior mechanical performance. The strongest scaffold design exhibited a Young’s modulus of 1060.67 ± 16.22 MPa and withstood a maximum tensile stress of 21.89 ± 0.81 MPa before fracture, while maintaining a porosity of approximately 52.37%. This demonstrates a favourable balance between mechanical strength and porosity that mimics key properties of engineered tissues such as the meniscus. Overall, these findings highlight the potential of 3D-printed, patient-specific scaffolds to enhance the effectiveness and customisation of tissue engineering treatments, such as meniscus repair, offering a promising approach for next-generation regenerative applications. Full article

Stone powder is an inevitable by-product generated during the processing of manufactured sand and gravel. Waste stone powder has been proven to affect concrete properties and has been applied in the transportation and hydropower fields. This study aims to convert waste granite stone powder (GP) to nuclear power concrete by replacing manufactured sand, investigating its effect on the workability, compressive strength, splitting tensile strength, impermeability, and freezing resistance of nuclear power concrete. The mechanism was further elucidated through thermogravimetric (TG), scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) techniques. The results show that with the increase in GP content, the slump, compressive strength, and splitting tensile strength of concrete increase first and then decrease, and the seepage height under pressure water decreases first and then increases. The workability, strength, and impermeability of concrete are optimal when GP content is 11.0%. Reasonable GP content improves the compactness of concrete by filling pores and optimizing aggregate gradation, resulting in decreases in porosity, with the size being the most probable and average pore size. Full article

Polyaniline (PANI), characterized by its proton-coupled redox mechanism and multicolor reversibility, is widely investigated for adaptive optical interfaces. Compared to inorganic oxides, PANI offers advantages in cost-effectiveness, mechanical flexibility, and molecular tunability; however, its practical implementation faces challenges related to kinetic limitations and environmental instability. This review presents a comprehensive analysis of PANI-based electrochromic materials, examining the intrinsic correlations among synthesis methodologies, microstructural characteristics, and optoelectronic performance. Synthesis strategies, including chemical oxidative polymerization, electrochemical deposition, and template-assisted techniques, are evaluated. Emphasis is placed on resolving the trade-off between optical contrast and switching kinetics by constructing high-surface-area porous nanostructures and inducing chain ordering via functional dopants to shorten ion diffusion paths and reduce charge transfer resistance. Fundamental electrochromic properties are subsequently discussed, with specific attention to degradation mechanisms triggered by environmental factors, such as pH drift, and stabilization strategies involving electrolyte engineering and composite design. Furthermore, the review addresses the evolution of applications from single-band monochromatic displays to dual-band smart windows for decoupled visible/near-infrared regulation and multifunctional integrated systems, including electrochromic supercapacitors and adaptive thermal management textiles. Finally, technical challenges regarding long-term durability, neutral color development, and large-area manufacturing are summarized to outline future research directions for PANI-based optical systems. Full article

Micro-motors are widely used in industrial applications, which require effective fault diagnosis to maintain safe equipment operation. However, fault signals from micro-motors often exhibit weak signal strength and ambiguous features. To address these challenges, this study proposes a novel fault diagnosis method. Initially, the Jump plus AM-FM Mode Decomposition (JMD) technique was utilized to decompose the measured signals into amplitude-modulated–frequency-modulated (AM-FM) oscillation components and discontinuous (jump) components. The proposed process extracts valuable fault features and integrates them into a new time-domain signal, while also suppressing modal aliasing. Subsequently, a novel Global Relationship Matrix (GRM) is employed to transform one-dimensional signals into two-dimensional images, thereby enhancing the representation of fault features. These images are then input into an Optimized Convolutional Neural Network (OCNN) with an AdamW optimizer, which effectively reduces overfitting during training. Experimental results demonstrate that the proposed method achieves an average diagnostic accuracy rate of 99.0476% for multiple fault types, outperforming four comparative methods. This approach offers a reliable solution for quality inspection of micro-motors in a manufacturing environment. Full article