Search Results (729)

In recent years, digital microfluidic biochips (DMFBs), based on microfluidic technology, have attracted attention as compact and flexible experimental devices. DMFBs are widely applied in biochemistry and medical fields, including point-of-care clinical diagnostics and PCR testing. Among them, micro electrode dot array (MEDA) biochips, composed of numerous microelectrodes, have overcome the limitations of conventional chips by enabling finer droplet manipulation and real-time sensing, thus significantly improving experimental efficiency. While various studies have been conducted to enhance the utilization of MEDA biochips, few have considered the shape-dependent velocity characteristics of droplets in routing. Moreover, methods that do take such characteristics into account often face significant challenges in solving time. This study proposes a fast droplet routing method for MEDA biochips that incorporates shape-dependent velocity characteristics by utilizing the distance information to the target cell. The experimental results demonstrate that the proposed method achieves approximately a 67.5% reduction in solving time compared to existing methods, without compromising solution quality. Full article

This study investigates the effectiveness of passive design in low-rise residential buildings located in arid desert climates, using the Dubai Solar Decathlon Middle East (SDME) competition as a case study. This full-scale experiment offers a unique opportunity to evaluate design solutions under controlled, realistic conditions; prescriptive, modeled performance; and monitored performance assessments. The prescriptive assessment reviews geometry, orientation, envelope thermal properties, and shading. Most houses adopt compact forms, with envelope-to-volume and envelope-to-floor area ratios averaging 1 and 3.7, respectively, and window-to-wall ratios of approximately 17%, favoring north-facing openings to optimize daylight while reducing heat gain. Shading is strategically applied, horizontal on south façades and vertical on east and west. The thermal properties significantly exceed the local code requirements, with wall performance up to 80% better than that mandated. The modeled assessment uses Building Energy Models (BEMs) to simulate the impact of prescriptive measures on energy performance. Three variations are applied: assigning minimum local code requirements to all the houses to isolate the geometry (baseline); removing shading; and applying actual envelope properties. Geometry alone accounts for up to 60% of the variation in cooling intensity; shading reduces loads by 6.5%, and enhanced envelopes lower demand by 14%. The monitored assessment uses contest-period data. Indoor temperatures remain stable (22–25 °C) despite outdoor fluctuations. Energy use confirms that houses with good designs and airtightness have lower cooling loads. Airtightness varies widely (avg. 14.5 m³/h/m²), with some well-designed houses underperforming due to construction flaws. These findings highlight the critical role of passive design as the first layer for improving the energy performance of the built environment and advancing toward net-zero targets, specifically in arid desert climates. Full article

Since the monotonicity of the best approximant is crucial to establish partial ordering methods, in this paper, we, respectively, characterize the best approximants in Banach function spaces and Lorentz spaces ${\mathrm{\Gamma }}_{p,w}$, in which we especially focus on the monotonicity characterizations. We first study monotonicity characterizations of the metric projection operator onto sublattices in general Banach function spaces by the property $H_g$. The sufficient and necessary conditions for monotonicity of the metric projection onto cones and sublattices are then, respectively, established in ${\mathrm{\Gamma }}_{p,w}$. The Lorentz spaces ${\mathrm{\Gamma }}_{p,w}$ are also shown to be reflexive under the condition $R{B}_p$, which is the basis for the existence of the best approximant. As applications, by establishing the partial ordering methods based on the obtained monotonicity characterizations, the solvability and approximation theorems for best proximity points are deduced without imposing any contractive and compact conditions in ${\mathrm{\Gamma }}_{p,w}$. Our results extend and improve many previous results in the field of the approximation and partial ordering theory. Full article

Thermal management is an area of study in electronics focused on managing temperature to improve reliability and efficiency. When temperatures are too high, cooling systems are activated to prevent overheating, which can lead to reliability issues. To monitor the temperatures, sensors are often placed on-chip near hotspot locations. These sensors should be very small to allow them to be placed among compact, high-activity circuits. Often, they are connected to a central control circuit located far away from the hot spot locations where more area is available. This paper proposes sensing units for a novel temperature sensing architecture in the TSMC 180 nm process. This architecture functions by approximating the current through the sensing unit at a reference voltage, which is used to approximate the temperature in the digital back end using fitting functions. Sensing units are selected based on how well its temperature–current relationship can be modeled, sensing unit area, and power consumption. Many sensing units will be experimented with at different reference voltages. These temperature–current curves will be modeled with various fitting functions. The sensing unit selected is a diode-connected p-type MOSFET (Metal Oxide Semiconductor Field Effect Transistor) with a size of W = 400 nm, L = 180 nm. This sensing unit is exceptionally small compared to existing work because it does not rely on multiple devices at the sensing unit location to generate a PTAT or IPTAT signal like most work in this area. The temperature–current relationship of this device can also be modeled using a 2nd order polynomial, requiring a minimal number of trim temperatures. Its temperature error is small, and the power consumption is low. The range of currents for this sensing unit could be reasonably made on an IDAC. Full article

Reliable prediction of tunnel thruster performance under reverse, or off-design, reverse operating direction (ROD) conditions, is crucial for modern vessels that require bidirectional thrust from a single unit—such as yachts and offshore support vessels. Despite the increasing demand for such a capability, there remains limited understanding of the unsteady hydrodynamic behavior and performance implications of ROD operation. This study addresses this gap through a scale-resolving computational fluid dynamics (CFD) investigation of a full-scale, fixed-pitch propeller with a diameter of 0.62, installed in a tunnel geometry representative of yacht-class side thrusters. Using advanced turbulence modeling, we compare the thruster’s performance under both the normal operating direction (NOD) and ROD. The results reveal notable differences: in ROD, the upstream separation zone was more compact and elongated, average thrust increases by approximately 3–4%, and torque and pressure fluctuations rise by 15–30%. These findings demonstrate that a single tunnel thruster can meet bidirectional manoeuvring requirements. However, the significantly elevated unsteady loads during ROD operation offer a plausible explanation for the increased noise and vibration frequently observed in practice. Full article

A model for the flow and thermal explosion of a micropolar gas is investigated, assuming the equation of state for a real gas. This model describes the dynamics of a gas mixture (fuel and oxidant) undergoing a one-step irreversible chemical reaction. The real gas model is particularly suitable in this context because it more accurately reflects reality under extreme conditions, such as high temperatures and high pressures. Micropolarity introduces local rotational dynamic effects of particles dispersed within the gas mixture. In this paper, we first derive the initial-boundary value system of partial differential equations (PDEs) under the assumption of spherical symmetry and homogeneous boundary conditions. We explain the underlying physical relationships and then construct a corresponding approximate system of ordinary differential equations (ODEs) using the Faedo–Galerkin projection. The existence of solutions for the full PDE model is established by analyzing the limit of the solutions of the ODE system using a priori estimates and compactness theory. Additionally, we propose a numerical scheme for the problem based on the same approximate system. Finally, numerical simulations are performed and discussed in both physical and mathematical contexts. Full article

A broadband, efficient monolithic microwave integrated circuit power amplifier (MMIC PA) in OMMIC’s 0.1 μm GaN-on-Si technology for 5G millimeter-wave communication is presented. This study concentrates on the output matching design, which has an important influence on the PA’s performance. A compact one-order synthesized transformer network (STN) is adopted to match the 50 Ω load to the extracted large-signal output model of the transistor. A dual-objective strategy is developed for parameter optimization, incorporating the impedance transformation trajectory inside the predefined optimal impedance domain (OID) that satisfies the required specifications, with approximation to selected optimal load impedances. By introducing a custom adjustment factor β into the error function, coupled with an automated iterative tuning process based on S-parameter simulations, desired broadband matching results can be rapidly achieved. The proposed two-stage PA occupies a small chip area of only 1.23 mm² and demonstrates good frequency consistency over the 24–31 GHz band. Continuous-wave characterization shows a flat small-signal gain of 19.7 ± 0.5 dB; both the output power (P_out) and the power-added efficiency (PAE) at the 4 dB compression point remain smooth, ranging from 32.3 to 32.7 dBm and 35.5% to 37.8%, respectively. The peak PAE reaches up to nearly 40% at the center frequency. Full article

Winter squash (Cucurbita moschata Duchesne.) is a vegetable of high socioeconomic importance owing to the nutritional quality of its fruits, seeds, and seed oil. This study aims to review the main aspects related to the characterization, conservation, and breeding of C. moschata, emphasizing the studies with C. moschata accessions maintained by the Vegetable Germplasm Bank of the Federal University of Viçosa (BGH-UFV). Studies on C. moschata germplasm have reported high variability, particularly in Brazil. Currently, Brazil maintains six Cucurbita germplasm collections, kept in research and teaching institutions. The BGH-UFV collection, one of the largest in the country, contains approximately 350 accessions of C. moschata, mostly landraces collected from all over Brazil. Studies characterizing this germplasm have identified promising genotypes as sources of alleles for increasing the carotenoid content in the fruit pulp and oleic acid content in the seed oil. As part of a breeding program to increase seed oil productivity and improve the oil profile, studies with the BGH-UFV germplasm have identified C. moschata genotypes with seed oil productivity of up to 0.27 t ha⁻¹ and accessions producing oil with high oleic acid content (21 to 28%). The genetic breeding program of C. moschata conducted at the UFV has prioritized the development of compact growth habit genotypes to reduce plant spacing and increase seed and oil productivity. The works involving the collection of C. moschata maintained by the BGH-UFV corroborates the importance of this germplasm as a source of alleles for improving seed oil productivity and the oil profile. Full article

Some classical texts on the Sturm–Liouville equation ${(p(x)y^{\prime })}^{\prime }-q(x)y+\lambda \rho (x)y=0$ are revised to highlight further properties of its solutions. Often, in the treatment of the ensuing integral equations, $\rho =const$ is assumed (and, further, $\rho =1$). Instead, here we preserve $\rho (x)$ and make a simple change only of the independent variable that reduces the Sturm–Liouville equation to $y^{″}-q(x)y+\lambda \rho (x)y=0$. We show that many results are identical with those with $\lambda \rho -q=const$. This is true in particular for the mean value of the oscillations and for the analog of the Riemann–Lebesgue Theorem. From a mechanical point of view, what is now the total energy is not a constant of the motion, and nevertheless, the equipartition of the energy is still verified and, at least approximately, it does so also for a class of complex $\lambda$. We provide here many detailed properties of the solutions of the above equation, with $\rho =\rho (x)$. The conclusion, as we may easily infer, is that, for large enough $\lambda$, locally, the solutions are trigonometric functions. We give the proof for the closure of the set of solutions through the Phragmén–Lindelöf Theorem, and show the separate dependence of the solutions from the real and imaginary components of $\lambda$. The particular case of $q(x)=\alpha \rho (x)$ is also considered. A direct proof of the uniform convergence of the Fourier series is given, with a statement identical to the classical theorem. Finally, the proof of J. von Neumann of the completeness of the Laguerre and Hermite polynomials in non-compact sets is revisited, without referring to generating functions and to the Weierstrass Theorem for compact sets. The possibility of the existence of a general integral transform is then investigated. Full article

The classification of Unexploded Ordnance (UXO) from magnetometer data is a critical but challenging task, frequently hindered by the data scarcity required for training robust machine learning models. To address this, we leverage a high-fidelity digital twin to generate a comprehensive dataset of magnetometer signals from both UXO and non-UXO objects, incorporating complex remanent magnetization effects. In this study, we design and evaluate a custom Convolutional Neural Network (CNN) for UXO classification and compare it against classical machine learning baseline, including Random Forest and kNN. Our CNN model achieves a balanced accuracy of 84.65%, significantly outperforming traditional models that exhibit performance collapse under slight distortions such as additive noise, drift, and time-wrapping. Additionally, we present a compact two-block CNN variant that retains competitive accuracy while reducing the number of learnable parameters by approximately 33%, making it suitable for real-time onboard classification in underwater vehicle missions. Through extensive ablation studies, we confirm that architectural components, such as residual skip connections and element-wise batch normalization, are crucial for achieving model stability and performance. The results also highlight the practical implications of underwater vehicles for survey design, emphasizing the need to mitigate signal drift and maintain constant survey speeds. This work not only provides a robust deep learning model for UXO classification, but also offers actionable suggestions for improving both model deployment and data acquisition protocols in the field. Full article

In this study, a Ag/ZrO₂ hybrid coating prepared by the sol–gel method on a β-type Ti45Nb alloy was applied by the spin coating technique, and the microstructural, mechanical, electrochemical, and tribological properties of the surface were evaluated in a multi-dimensional manner. The hybrid solution was prepared using zirconium propoxide and silver nitrate and stabilized through a low-temperature two-stage annealing protocol. The crystal structure of the coating was determined by XRD, and the presence of dense tetragonal ZrO₂ phase and crystalline Ag phases was confirmed. SEM-EDS analyses revealed a compact coating structure of approximately 1.8 µm thickness with homogeneously distributed Ag nanoparticles on the surface. As a result of the electrochemical corrosion tests, it was determined that the open circuit potential shifted to more noble values, the corrosion current density decreased, and the corrosion rate decreased by more than 70% on the surfaces where the Ag/ZrO₂ coating was applied. In the tribological tests, a decrease in the coefficient of friction, narrowing of wear marks, and significant reduction in surface damage were observed in dry and physiological (HBSS) environments. The findings revealed that the Ag/ZrO₂ hybrid coating significantly improved the surface performance of the Ti45Nb alloy both mechanically and electrochemically and offers high potential for biomedical implant applications. Full article

An innovative high-order dimensionality reduction approach, which integrates a condensed finite-difference scheme with proper orthogonal decomposition techniques, has been explored for solving diffusion equations. The difference scheme with forth order accurate in both space and time is introduced through the idea of interpolation approximation. The quartic spline function and $(2,2)$ Padé approximation were utilized in space and time discretization, respectively. The stability and convergence were proven. Moreover, the dimensionality reduction formulas were derived using the proper orthogonal decomposition (POD) method, which is based on the matrix representation of the compact finite-difference scheme. The bases of the POD method were established by cumulative contribution rate of the eigenvalues of snapshot matrix that is different from the traditional ways in which the bases were established by the first eigenvalues. The method of cumulative contribution rate can optimize the degree of freedom. The error analysis of the reduced bases high-order POD finite-difference scheme was provided. Numerical experiments are conducted to validate the soundness and dependability of the reduced-order algorithm. The comparisons between the $(2,2)$ finite-difference method, the traditional POD method, and reduced dimensional method with cumulative contribution rate were discussed. Full article

This research presents the development and management principles of mobile resonant electrical systems designed for high-voltage generation, intended for non-destructive diagnostics of insulation in high-power electrical equipment. The core of the system is a series inductive–capacitive (LC) circuit characterized by a high quality (Q) factor and operating at high frequencies, typically in the range of 40–50 kHz or higher. Practical implementations of the LC circuit with Q-factors exceeding 200 have been achieved using advanced materials and configurations. Specifically, ceramic capacitors with a capacitance of approximately 3.5 nF and Q-factors over 1000, in conjunction with custom-made coils possessing Q-factors above 280, have been employed. These coils are constructed using multi-core, insulated, and twisted copper wires of the Litzendraht type to minimize losses at high frequencies. Voltage amplification within the system is effectively controlled by adjusting the current frequency, thereby maximizing voltage across the load without increasing the system’s size or complexity. This frequency-tuning mechanism enables significant reductions in the weight and dimensional characteristics of the electrical system, facilitating the development of compact, mobile installations. These systems are particularly suitable for on-site testing and diagnostics of high-voltage insulation in power cables, large rotating machines such as turbogenerators, and other critical infrastructure components. Beyond insulation diagnostics, the proposed system architecture offers potential for broader applications, including the charging of capacitive energy storage units used in high-voltage pulse systems. Such applications extend to the synthesis of micro- and nanopowders with tailored properties and the electrohydropulse processing of materials and fluids. Overall, this research demonstrates a versatile, efficient, and portable solution for advanced electrical diagnostics and energy applications in the high-voltage domain. Full article

Optical metasurfaces enable compact, lightweight and planar optical devices. Their performances, however, are still limited by design approximations imposed by their macroscopic dimensions. To address this problem, we propose a neural network-based multi-stage gradient optimization method to efficiently modulate nonlocal interactions between meta-atoms, which is one of the major effects neglected by current design methods. Our strategy allows for the use of these interactions as an additional design dimension to enhance the performance of metasurfaces and can be used to optimize large-scale metasurfaces with multiple parameters. As an example of application, we design a meta-hologram with a zero-order energy suppressed to 26% (theoretically) and 57% (experimentally) of its original value. Our results suggest that neural networks can be used as a powerful design tool for the next generation of high-performance metasurfaces with complex functionalities. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article