Search Results (42)

Achieving accurate fit in implant-supported prostheses is critical for avoiding mechanical complications; however, the influence of digital manufacturing techniques and abutment designs on misfit and preload remains unclear. This study evaluated the impact of different manufacturing techniques (CAD-cast and 3D printing) and abutment connection types (engaging [E], non-engaging [NE]) on the misfit and preload of implant-supported cantilevered fixed dental prostheses (ICFDPs). Misfit was measured at six points using scanning electron microscopy, and preload was assessed via eight strain gauges placed buccally and lingually on four implants. Frameworks were torqued to 35 Ncm, retorqued after 10 min, and subjected to 200,000 cycles of loading. Mean preload values ranged from 173.4 ± 79.5 Ncm (PF) to 330 ± 253.2 Ncm (3DP). Preload trends varied depending on the abutment type and manufacturing technique, with the 3DP group showing higher preload in engaging (E) abutments, whereas the CAD-cast group showed the opposite pattern. Although preload values varied numerically, these differences were not statistically significant (p = 0.5). In terms of misfit, significant differences were observed between groups (p < 0.05), except between CAD-cast E (86.4 ± 17.8 μm) and 3DP E (84.1 ± 19.2 μm). Additionally, E and NE abutments showed significant differences in misfit within both CAD-cast and 3DP groups. Overall, 3DP frameworks showed superior fit over CAD-cast. These findings suggest that 3DP may offer improved clinical outcomes in terms of implant–abutment fit. Full article

Integrating three-dimensional printing (3DP) in healthcare has modernized medical diagnostics and therapies by presenting various accurate, efficient, and patient-specific tailored solutions. This review critically examines the integration of 3DP in the development of miniaturized devices specifically tailored for point-of-care testing (PoCT) applications in healthcare. Focusing on progressive additive manufacturing techniques, such as material extrusion, vat photopolymerization, and powder bed fusion, the review classifies and evaluates their contributions toward designing compact, portable, and patient-specific diagnostic devices. Unlike previous reviews that treat 3DP or PoCT generically, this work uniquely bridges the technical innovations of 3DP with clinical applications by analyzing wearable sensors, biosensors, lab-on-chip systems, and microfluidic platforms. It highlights recent case studies, performance metrics, and the role of 3DP in enhancing diagnostic speed, accessibility, and personalization. The review also explores challenges such as material standardization and regulatory hurdles while outlining future directions involving artificial intelligence (AI), the Internet of Things (IoT), and multifunctional integration. This focused assessment establishes 3DP as a transformative force in decentralized and precision healthcare. Full article

In this paper, a workflow for creating advanced aerodynamics design dashboards is proposed. A CAD modeler is directly linked to the CFD simulation results so that the designer can explore in real time, assisted by virtual reality (VR), how shape parameters affect the aerodynamics and choose the optimal combination to optimize performance. In this way, the time required for the conception of a new component can be drastically reduced because, even at the preliminary stage, the designer has all the necessary information to make more thoughtful choices. Thus, this work sets a highly ambitious and innovative goal: to create a smart design dashboard where every shape parameter is directly and in real-time linked to the results of the high-fidelity analyses. The OPAM (Open Parametric Aircraft Model), a simplified model of the Boeing 787, was considered as a case study. CAD parameterization and mesh morphing were combined to generate the design points (DPs), while Reduced Order Models (ROMs) were developed to link the results of the CFD analyses to the chosen parameterization. The ROMs were exported as FMUs (Functional Mockup Units) to be easily managed in any environment. Finally, a VR design dashboard was created in the Unity environment, enabling the interaction with the geometric model in order to observe in a fully immersive and intuitive environment how each shape parameter affects the physics involved. The MetaQuest 3 headset has been selected for these tests. Thus, the use of VR for a design platform represents another innovative aspect of this work. Full article

Handmade papers, as carriers of paper-based cultural relics, have played a crucial role in the development of human culture, knowledge, and civilization. Understanding the intricate relationship between the structural properties and degradation mechanisms of handmade papers is essential for the conservation of historical documents. In this work, an artificial dry-heat-accelerated aging method was used to investigate the interplay among the mechanical properties of paper, the degree of polymerization (DP) of cellulose, the chemical composition, the hydrogen bond strength, the crystallinity, and the degree of hornification for paper fibers. The results demonstrated for the first time that the mechanical properties of handmade bamboo paper exhibited an initial plateau region, a rapid decline region, and sometimes a second plateau region as it undergoes a dry-heat aging process. The changes in cellulose, hemicellulose, and lignin content were tracked throughout these three stages. The lignin content was relatively stable, while the cellulose and hemicellulose content decreased, which was consistent with the observed decline in mechanical properties. When the DP of cellulose decreased to the range of 600–400, there was a critical point in the mechanical properties of the paper, marking a transition from the initial stable region to a rapid decline region. The fiber embrittlement caused by cellulose chain breakage resulting from the decrease in DP was counteracted by the enhancement of intermolecular hydrogen bonds and the hornification process. A second stable region appeared when the DP was less than 400, marking a transition from a balanced or slightly decreasing trend in the initial plateau region to a sharp decline. This study also discussed for the first time that the formation of the second plateau region may be due to the presence of hemicellulose and lignin, which hinder the further aggregation of cellulose and maintain the structural stability of the fiber cell. The findings of this study can provide guidance for improving ancient book preservation strategies. On the one hand, understanding how these components affect the durability of paper can help us better predict and slow down the aging of ancient books. On the other hand, specific chemical treatment methods can be designed to stabilize these components and reduce their degradation rate under adverse environmental conditions. Full article

Flight-by-feel (FBF) is an approach to flight control that uses dispersed sensors on the wings of aircraft to detect flight state. While biological FBF systems, such as the wings of insects, often contain hundreds of strain and flow sensors, artificial systems are highly constrained by size, weight, and power (SWaP) considerations, especially for small aircraft. An optimization approach is needed to determine how many sensors are required and where they should be placed on the wing. Airflow fields can be highly nonlinear, and many local minima exist for sensor placement, meaning conventional optimization techniques are unreliable for this application. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm extracts information from a dense array of flow data using singular value decomposition and linear discriminant analysis, thereby identifying the most information-rich sparse subset of sensor locations. In this research, the SSPOP algorithm is evaluated for the placement of artificial hair sensors on a 3D delta wing model with a 45$°$ sweep angle and a blunt leading edge. The sensor placement solution, or design point (DP), is shown to rank within the top one percent of all possible solutions by root mean square error in angle of attack prediction. This research is the first to evaluate SSPOP on a 3D model and the first to include variable length hairs for variable velocity sensitivity. A comparison of SSPOP against conventional greedy search and gradient-based optimization shows that SSPOP DP ranks nearest to optimal in over 90 percent of models and is far more robust to model variation. The successful application of SSPOP in complex 3D flows paves the way for experimental sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel. Full article

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the mvm operation involving a 32 × 32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs. Full article

Differential privacy, a cornerstone of privacy-preserving techniques, plays an indispensable role in ensuring the secure handling and sharing of sensitive data analysis across domains such as in census, healthcare, and social networks. Histograms, serving as a visually compelling tool for presenting analytical outcomes, are widely employed in these sectors. Currently, numerous algorithms for publishing histograms under differential privacy have been developed, striving to balance privacy protection with the provision of useful data. Nonetheless, the pivotal challenge concerning the effective enhancement of precision for small bins (those intervals that are narrowly defined or contain a relatively small number of data points) within histograms has yet to receive adequate attention and in-depth investigation from experts. In standard DP histogram publishing, adding noise without regard for bin size can result in small data bins being disproportionately influenced by noise, potentially severely impairing the overall accuracy of the histogram. In response to this challenge, this paper introduces the SReB_GCA sanitization algorithm designed to enhance the accuracy of small bins in DP histograms. The SReB_GCA approach involves sorting the bins from smallest to largest and applying a greedy grouping strategy, with a predefined lower bound on the mean relative error required for a bin to be included in a group. Our theoretical analysis reveals that sorting bins in ascending order prior to grouping effectively prioritizes the accuracy of smaller bins. SReB_GCA ensures strict $ϵ$-DP compliance and strikes a careful balance between reconstruction error and noise error, thereby not only initially improving the accuracy of small bins but also approximately optimizing the mean relative error of the entire histogram. To validate the efficiency of our proposed SReB_GCA method, we conducted extensive experiments using four diverse datasets, including two real-life datasets and two synthetic ones. The experimental results, quantified by the Kullback–Leibler Divergence (KLD), show that the SReB_GCA algorithm achieves substantial performance enhancement compared to the baseline method (DP_BASE) and several other established approaches for differential privacy histogram publication. Full article

Anticipating and planning for the urgent response to large-scale disasters is critical to increase the probability of survival at these events. These incidents present various challenges that complicate the response, such as unfavorable weather conditions, difficulties in accessing affected areas, and the geographical spread of the victims. Furthermore, local socioeconomic factors, such as inadequate prevention education, limited disaster resources, and insufficient coordination between public and private emergency services, can complicate these situations. In large-scale emergencies, multiple demand points (DPs) are generally observed, which requires efforts to coordinate the strategic allocation of human and material resources in different geographical areas. Therefore, the precise management of these resources based on the specific needs of each area becomes fundamental. To address these complexities, this paper proposes a methodology that models these scenarios as a multi-objective optimization problem, focusing on the location-allocation problem of resources in Mass Casualty Incidents (MCIs). The proposed case study is Mexico City in a earthquake post-disaster scenario, using voluntary geographic information, open government data, and historical data from the 19 September 2017 earthquake. It is assumed that the resources that require optimal location and allocation are ambulances, which focus on medical issues that affect the survival of victims. The designed solution involves the use of a metaheuristic optimization technique, along with a parameter tuning technique, to find configurations that perform at different instances of the problem, i.e., different hypothetical scenarios that can be used as a reference for future possible situations. Finally, the objective is to present the different solutions graphically, accompanied by relevant information to facilitate the decision-making process of the authorities responsible for the practical implementation of these solutions. Full article

The optimization of the geometry of a centrifugal fan is performed at maximum power and high-efficiency design points (DPs) to improve impeller efficiency. Two design variables defining the shape of fan blade are selected for the optimization. The optimal values of the geometry parameters of the impeller blades are identified by employing virtual flow simulations. The results of virtual experiments indicate the influence of the parameters of the blade geometry on its efficiency. With the optimization of impeller blade geometry, the efficiency of the fan is improved with respect to the reference model, as confirmed by comparing the performance curves. Herein, we discuss the results obtained in virtual tests by identifying the influence of DPs on the performance characteristics of centrifugal fans. Full article

This paper proposes a controller to track the maximum power point (MPP) of a photovoltaic (PV) system using a fractional-order proportional integral derivative (FOPID) controller. The employed MPPT is operated based on a dp/dv feedback approach. The designed FOPID-MPPT method includes a differentiator of order (μ) and integrator of order (λ), meaning it is an extension of the conventional PID controller. FOPID has more flexibility and achieves dynamical tuning, which leads to an efficient control system. The contribution of our paper lies is optimizing FOPID-MPPT parameters using Aquila optimizer (AO). The obtained results with the proposed AO-based FOPID-MPPT are contrasted with those acquired with moth flame optimizer (MFO). The performance of our FOPID-MPPT controller with the conventional technique perturb and observe (P&O) and the classical PID controller is analyzed. In addition, a robustness test is used to assess the performance of the FOPID-MPPT controller under load variations, providing valuable insights into its practical applicability and robustness. The simulation results clearly prove the superiority and high performance of the proposed control system to track the MPP of PV systems. Full article

Three-dimensional printing by fused deposition modeling (FDM) coupled with hot-melt extrusion (HME) is a point of convergence of research efforts directed toward the development of personalized dosage forms. In addition to the customization in terms of shapes, sizes, or delivered drug doses, the modulation of drug release profiles is crucial to ensure the superior efficacy and safety of modern 3D-printed medications compared to those of conventional ones. Our work aims to solidify the groundwork for the preparation of 3D-printed tablets that ensure the sustained release of diclofenac sodium. Specifically, we achieved the fast release of a diclofenac sodium dose to allow for the prompt onset of its pharmacological effect, further sustaining by the slow release of another dose to maintain the effect over a prolonged timeframe. In this regard, proper formulation and design strategies (a honeycomb structure for the immediate-release layer and a completely filled structure for the sustained-release layer) were applied. Secondarily, the potential of polyvinyl alcohol to function as a multifaceted polymeric matrix for both the immediate and slow-release layers was explored, with the objective of promoting the real-life applicability of the technique by downsizing the number of materials required to obtain versatile pharmaceutical products. The present study is a step forward in the translation of HME-FDM-3DP into a pharmaceutical manufacturing methodology. Full article

We present a fifth-order finite-difference Hermite weighted essentially non-oscillatory (HWENO) method for solving the Degasperis–Procesi (DP) equation in this paper. First, the DP equation can be rewritten as a system of equations consisting of hyperbolic equations and elliptic equations by introducing an auxiliary variable, since the equations contain nonlinear higher order derivative terms. Then, the auxiliary variable equations are solved using the Hermite interpolation, while the HWENO scheme is performed for the hyperbolic equations. Compared with the popular WENO-type scheme, the most important feature of the HWENO scheme mentioned in this paper is the compactness of its spatial reconstruction stencil, which can achieve the fifth-order accuracy of the expected design with only three points, while the WENO method requires five points. Finally, we demonstrate the effectiveness of the HWENO method in various aspects by conducting some benchmark numerical tests. Full article

This paper reports for the first time a drain-pumped (DP) mixer using Gallium Nitride (GaN) HEMT technology. Specifically, it describes a method aimed to predict the optimum bias conditions for active DP-mixers, leading to high conversion gain (CG) and linearity, along with the efficient use of the local oscillator drive level. A mixer prototype was designed and fabricated according to the discussed design principles; it exhibited a CG and an input third-order intercept point (IIP3) of $+10$dB and $+11$dBm, respectively, with a local oscillator power level of 20 dBm at about $3.7$ GHz. In terms of gain and linearity, both figures exceed the documented limitations for the class of mixers considered in this work. To the authors’ best knowledge, this is the first DP mixer operating in the S-band. The prototype was also tested in a radar-like setup operating in the S-band frequency-modulated continuous-wave (FMCW) mode. Measurements carried out in the radar setup resulted in $+39.7$dB and $+34.7$dB of IF signal-to-noise-ratio (SNR) for the DP and the resistive mixers, respectively. For comparison purposes, a resistive mixer was designed and fabricated using the same GaN HEMT technology; a detailed comparison between the two topologies is discussed in the paper, thus further highlighting the capability of the DP-mixer for system applications. Full article

In this study, the microstructure and performance of newly designed dual-phase steel (DP590) after joining by flash butt welding (FBW) for vehicle wheel rims was analysed and compared by two simulations, i.e., physical simulation and numerical simulation, due to the high acceptance of these two methodologies. Physical simulation is regarded as a thermal–mechanical solution conducted by the Gleeble 3500 simulator and which can distribute the heat-affected zone (HAZ) of the obtained weld joint into four typical HAZs. These are coarse-grained HAZ, fine-grained HAZ, inter-critical HAZ and sub-critical HAZ. A combination of ferrite and tempered martensite leads to the softening behaviour at the sub-critical HAZ of DP590, which is verified to be the weakest area, and influences the final performance due to ~9% reduction of hardness and tensile strength. The numerical simulation, relying on finite element method (FEM) analysis, can distinguish the temperature distribution, which helps us to understand the relationship between the temperature distribution and real microstructure/performance. Based on this study, the combination of physical and numerical simulations can be used to optimise the flash butt welding parameters (flash and butt processes) from the points of temperature distribution (varied areas), microstructure and performance, which are guidelines for the investigation of flash butt welding for innovative materials. Full article

Pathogenic bacteria possess a remarkable ability to adapt to fluctuating host environments and cause infection. Disturbing bacterial central metabolism through inhibition of 1-deoxy-d-xylulose 5-phosphate synthase (DXPS) has the potential to hinder bacterial adaptation, representing a new antibacterial strategy. DXPS functions at a critical metabolic branchpoint to produce the metabolite DXP, a precursor to pyridoxal-5-phosphate (PLP), thiamin diphosphate (ThDP) and isoprenoids presumed essential for metabolic adaptation in nutrient-limited host environments. However, specific roles of DXPS in bacterial adaptations that rely on vitamins or isoprenoids have not been studied. Here we investigate DXPS function in an adaptation of uropathogenic E. coli (UPEC) to d-serine (d-Ser), a bacteriostatic host metabolite that is present at high concentrations in the urinary tract. UPEC adapt to d-Ser by producing a PLP-dependent deaminase, DsdA, that converts d-Ser to pyruvate, pointing to a role for DXPS-dependent PLP synthesis in this adaptation. Using a DXPS-selective probe, butyl acetylphosphonate (BAP), and leveraging the toxic effects of d-Ser, we reveal a link between DXPS activity and d-Ser catabolism. We find that UPEC are sensitized to d-Ser and produce sustained higher levels of DsdA to catabolize d-Ser in the presence of BAP. In addition, BAP activity in the presence of d-Ser is suppressed by β-alanine, the product of aspartate decarboxylase PanD targeted by d-Ser. This BAP-dependent sensitivity to d-Ser marks a metabolic vulnerability that can be exploited to design combination therapies. As a starting point, we show that combining inhibitors of DXPS and CoA biosynthesis displays synergy against UPEC grown in urine where there is increased dependence on the TCA cycle and gluconeogenesis from amino acids. Thus, this study provides the first evidence for a DXPS-dependent metabolic adaptation in a bacterial pathogen and demonstrates how this might be leveraged for development of antibacterial strategies against clinically relevant pathogens. Full article