Search Results (193)

This study focuses on S32654 super austenitic stainless steel (SASS) and systematically characterizes the morphology of the sigma (σ) phase and the segregation behavior of alloying elements in its as-cast microstructure. High-temperature confocal scanning laser microscopy (HT-CSLM) was employed to investigate the effect of the rare earth element yttrium (Y) on the solidification microstructure and σ phase precipitation behavior of SASS. The results show that the microstructure of SASS consists of austenite dendrites and interdendritic eutectoid structures. The eutectoid structures mainly comprise the σ phase and the γ₂ phase, exhibiting lamellar or honeycomb-like morphologies. Regarding elemental distribution, molybdenum displays a “concave” distribution pattern within the dendrites, with lower concentrations at the center and higher concentrations at the sides; when Mo locally exceeds beyond a certain threshold, it easily induces the formation of eutectoid structures. Mo is the most significant segregating element, with a segregation ratio as high as 1.69. The formation mechanism of the σ phase is attributed to the solid-state phase transformation of austenite (γ → γ₂ + σ). In the late stages of solidification, the concentration of chromium and Mo in the residual liquid phase increases, and due to insufficient diffusion, there are significant compositional differences between the interdendritic regions and the matrix. The enriched Cr and Mo cause the interdendritic austenite to become supersaturated, leading to solid-state phase transformation during subsequent cooling, thereby promoting σ phase precipitation. The overall phase transformation process can be summarized as L → L + γ → γ → γ + γ₂ + σ. Y microalloying has a significant influence on the solidification process. The addition of Y increases the nucleation temperature of austenite, raises nucleation density, and refines the solidification microstructure. However, Y addition also leads to an increased amount of eutectoid structures. This is primarily because Y broadens the solidification temperature range of the alloy and prolongs grain growth perio, which aggravates the microsegregation of elements such as Cr and Mo. Moreover, Y raises the initial precipitation temperature of the σ phase and enhances atomic diffusion during solidification, further promoting σ phase precipitation during the subsequent eutectoid transformation. Full article

Background/Objectives: Clinical laboratories are fundamental to healthcare systems, contributing to over 70% of clinical decisions while accounting for only 2–3% of hospital budgets. Among them, microbiology laboratories provide critical information that directly influences patient outcomes and satisfaction. This study presents a structured review of the current state of Lean Six Sigma (LSS) implementation in microbiology and comparable laboratory environments. The objective is to identify relevant contributions within the state of the art to highlight potential benefits applicable to microbiology laboratories and to detect persistent gaps and unresolved needs. Methods: A systematic literature review was performed across six databases (Web of Science, ScienceDirect, Scopus, ProQuest, PubMed, and Google Scholar) to identify studies published between 2012 and September 2024. After screening, 33 studies were selected for full-text analysis. Results: The selected literature was analyzed to assess the extent to which LSS methodologies have been applied in microbiology laboratories. Particular attention was given to the definition and use of key performance indicators (KPIs). While industry-adapted metrics such as cost reduction and turnaround time are commonly employed, clinical indicators, such as patient impact, satisfaction, and diagnostic accuracy, are underutilized. Additionally, the analysis revealed a frequent omission of the control phase in LSS projects, limiting long-term process monitoring. The review also identifies the most suitable LSS tools and evaluates how laboratories manage interruptions in routine workflows. Conclusions: Future research should prioritize the integration of clinical KPIs into LSS frameworks, establish robust control phases for sustained monitoring, and systematically address the impact of process interruptions on optimization efforts. Full article

For a quasi-two-dimensional nonlinear sigma model on the real Stiefel manifolds with a generalized (anisotropic) metric, the equations of a two-charge renormalization group (RG) for the homothety and anisotropy of the metric as effective couplings are obtained in a one-loop approximation. Normal coordinates and the curvature tensor are exploited for the renormalization of the metric. The RG trajectories are investigated and the presence of a fixed point common to four critical lines or four phases (tetracritical point) in the general case, or its absence in the case of an Abelian structure group, is established. For the tetracritical point, the critical exponents are evaluated and compared with those known earlier for a simpler particular case. Full article

Deep learning models possess the ability to precisely analyze medical images such as MRI, CT scans, and ultrasound images. This automated diagnostic process facilitates the early detection of kidney disease by identifying any abnormalities or signs of disease. Consequently, it allows for timely intervention and treatment, while also reducing the need for manual interpretation by radiologists or clinicians. As a result, the diagnosis process is expedited, leading to improved efficiency in healthcare. The proposed technique focuses on enhancing parallel convolutional layer architectures in kidney disease segmentation through the utilization of advanced optimization techniques. This approach integrates Firefly Sigma Seeker and MagWeight Rank methodologies into the design of these architectures. The Firefly Sigma Seeker methodology dynamically adjusts key parameters related to standard deviation during training to enable early stopping in the initial phase. Subsequently, MagWeight Rank optimizes parameter weighting and ranking within the architecture to prune less important weights, thereby reducing computational time and overfitting. By leveraging these techniques, the parallel convolutional layers are specifically tailored for kidney disease segmentation tasks. Finally, the Multi-Stream Neural Network (MSNN) efficiently classifies kidney disease. Through extensive experimentation and evaluation on kidney disease segmentation datasets, a comparative analysis of different architectures was conducted in terms of segmentation accuracy, computational efficiency, and scalability. The proposed framework achieves optimal segmentation performance, with an accuracy of 98.2%, a minimized loss of 0.1, a reduced computational time of 15 min and 4 s, and successfully avoids overfitting. Full article

Millimeter-wave radar is emerging as a key sensor technology not only for autonomous driving but also for various industrial applications, such as vital sign monitoring and structural displacement sensing using millimeter-wave FMCW radar, which must detect extremely small displacements on the sub-micron scale. Accurate displacement measurements fundamentally rely on obtaining precise intermediate frequency (IF) phase data over slow time (i.e., chirp-to-chirp intervals or pulse repetition time) generated by the radar sensor system. In this study, we developed a millimeter-wave FMCW radar sensor for displacement sensing using a 77–81 GHz radar transceiver MMIC (Monolithic Microwave Integrated Circuit) and evaluated its accuracy and precision through a series of experiments. First, we assessed the MMIC’s phase performance under static conditions using a rigid RF waveguide, and second, we measured a vibrating target using an industrial vibration shaker as a reference. The experiments demonstrated a maximum accuracy error of +0.359 degrees (1.907 μm displacement) and a maximum 3-sigma precision of ±0.358 degrees (±1.180 μm displacement), validating the feasibility of using millimeter-wave radar to measure very small displacements. Full article

This paper reviews recent developments in highly integrated all-digital frequency synthesizers suitable to deploy in low-power internet-of-things (IoT) applications. This review sets low power consumption as a key criterion for exploring the all-digital frequency synthesizer implemented in CMOS fabrication technology. The alignment with mainstream CMOS technology offers high-density, comprehensive, robust signal processing capability, making it very suitable for all-digital phase-locked loops to harvest that capacity, and it becomes inevitable. This review includes various divider-less low-power frequency synthesizers, including all-digital phase-locked loops (ADPLL), all-digital frequency-locked loops (ADFLL), and hybrid PLLs. This paper also discusses the latest architectural developments for ADPLLs to lead to low-power implementation, such as DTC-assisted TDC, embedded TDC, and various levels of hybridization in ADPLLs. Full article

The multipath effect is a critical factor that prevents the Global Navigation Satellite System (GNSS) from achieving millimeter-level positioning accuracy. A multipath hemispherical map (MHM) is a popular approach to achieving real-time multipath error mitigation. The premise of the constructed MHM model is that the residuals in the grid only contain multipath errors and noise without any outliers. However, when there are numerous obvious outliers in each grid, the traditional quality control method is unable to detect them effectively. Therefore, we propose a multipath hemispherical map with strict quality control (MHM-S) to mitigate multipath errors. This method first uses the maximum phase delay to eliminate obvious outliers. Then, the 3-sigma rule and F-test are applied to remove the remaining few outliers in the grid. After applying the proposed MHM-S method, the experimental results show that when the PRN20 satellite is affected by outliers, the standard deviation (STD) reduction rate of the MHM-S residuals is 12.03% compared with the residual STDs of the MHM model. In addition, we evaluate the capabilities of MHM-S with carrier phase observation (MHM-SC) and carrier phase and pseudo-range observation (MHM-SCP) models in multipath error mitigation. Especially in the east direction, the positioning accuracy of the MHM-SCP model is improved by 48% compared with the MHM-SC model. Full article

A programmable gain amplifier (PGA) is commonly used to optimize the input dynamic range of high-performance systems such as headphones and biomedical sensors. But PGA is rather sensitive to electromagnetic interference (EMI), which limits the precision of these systems. Many capacitor-less low-dropout regulator (LDO) schemes with high power supply rejection have been proposed to act as the independent power supply for PGA, which consumes additional power and area. This paper proposed a PGA with a high power supply rejection ratio (PSRR) and low power consumption, which serves as the analog front-end amplifier in the 20-bit sigma-delta ADC. The PGA is a two-stage amplifier with hybrid compensation. The first stage is the recycling folded cascode amplifier with the gain-boost technique, while the second stage is the class-AB output stage. The PGA was implemented in the 0.18 μm CMOS technology and achieved a 9.44 MHz unity-gain bandwidth (UGBW) and a 57.8° phase margin when driving the capacitor of 5.9 pF. An optimum figure-of-merit (FoM) value of 905.67 has been achieved with the proposed PGA. As the front-end amplifier of a high-precision ADC, it delivers a DC gain of 162.1 dB, the equivalent input noise voltage of 301.6 nV and an offset voltage of 1.61 μV. Within the frequency range below 60 MHz, the measured PSRR of ADC is below −70 dB with an effective number of bits (ENOB), namely 20 bits. Full article

Kaon condensation in hyperon-mixed matter [(Y+K) phase], which may be realized in neutron stars, is discussed on the basis of chiral symmetry. With the use of the effective chiral Lagrangian for kaon–baryon and kaon–kaon interactions; coupled with the relativistic mean field theory and universal three-baryon repulsive interaction, we clarify the effects of the s-wave kaon–baryon scalar interaction simulated by the kaon–baryon sigma terms and vector interaction (Tomozawa–Weinberg term) on kaon properties in hyperon-mixed matter, the onset density of kaon condensation, and the equation of state with the (Y+K) phase. In particular, the quark condensates in the (Y+K) phase are obtained, and their relevance to chiral symmetry restoration is discussed. Full article

To meet the requirement of low magnetic permeability, which, in turn, lowers the ferrite content of castings, of special interest is 316 stainless steel, whose low ferrite content renders it suitable also for nuclear power applications. Therefore, the effects of the composition and cooling rate of 316 stainless steel castings on the ferrite content are investigated. Three 316 stainless steel continuous casting samples with different compositions (primarily differing in the Ni content) are studied, i.e., low-alloy type (L-316), medium-alloy type (M-316), and high-alloy type (H-316). The austenite-forming element nickel of three different industrial samples is 10%, 12%, and 14%, respectively. The effect of the cooling rate on the ferrite content and precipitation phases of the high Ni content of the 316 stainless steel casting (H-316) is studied by remelting experiments and different methods of quenching of liquid steel. In both cases, the ferrite content and the precipitate phases in the microstructure are analyzed using SEM and EBSD. The results indicate that compositional changes within the 316 stainless steel range lead to changes in the solidification mode. In the L-316 casting, solidified by the FA mode (ferrite–austenite mode), ferrite precipitates first from the liquid phase, followed by the formation of austenite, and the ferrite content is 11.2%. In contrast, the ferrite content in the M-316 and H-316 castings, solidified by the AF mode (austenite–ferrite mode), is 2.88% and 2.45%, respectively. The effect of the solidification mode on the ferrite content is more obvious than that of the composition. The microstructure of the L-316 casting is mainly composed of the austenitic phase and the ferritic phase. The microstructure of the M-316 casting is composed of austenite, ferrite, and a small amount of sigma phase, with a small amount of ferrite transformed into the sigma phase. The microstructure of the H-316 casting is basically composed of austenite and the sigma phase, with the ferrite has been completely transformed into sigma phase. Changes in composition have a greater influence on the precipitate phases, while the solidification mode has a lesser impact. In the remelting experiments, the ferrite content in the H-316 ingot obtained through furnace cooling and air cooling is 1.49% and 1.94%, respectively, and the cooling rates are 0.1 °C/s and 3.5 °C/s, respectively. Under oil- and water-cooling conditions, with cooling rates of 11.5 °C/s and 25.1 °C/s, respectively, the ferrite content in the ingot is controlled to below 1%. The effect of the cooling rate on the precipitation phase of the H-316L ingot is that the amount of precipitated phase in the ingot decreases with an increase in cooling rate, but, when the cooling rate exceeds a certain value (air cooling 3.5 °C/s), the change in cooling rate has little effect on the amount of the precipitated phase. Full article

CoCrFeNi high-entropy alloys represent a novel structural material with considerable application potential in a variety of fields, including aerospace, automobiles, ships, machining, energy, soft magnetic materials, and hydrogen storage materials. The present study investigates the impact of the Al element on the structure and properties of the alloy. The preparation of the Al_xCr_1−xCoFeNi (x = 0.1, 0.2, 0.3, 0.4, 0.5) powders involved the use of a variety of elemental metal powders as raw materials and a mechanical alloying process at 350 rpm for 40 h. The sintering of the alloy powders was subsequently conducted using spark plasma sintering at 1000 °C. The microstructure of the alloys was analyzed using XRD, SEM, and EDS, and the properties were analyzed using a universal testing machine, a hardness measurement, friction and wear measurement, and an electrochemical workstation. The study shows that when x = 0.1, the crystal structure of Al_0.1Cr_0.9CoFeNi consists of a double FCC phase and a trace amount of σ phase. As the aluminum content increases, part of the FCC phase begins to transform to BCC. When x = 0.2~0.5, the alloy consists of a double FCC phase and a BCC phase and a trace amount of a sigma phase. As the BCC phase in the alloy increases, the tensile strength of the alloy increases, the ability to deform plastically decreases, and the hardness increases. The highest ultimate tensile strength of 1163.14 MPa is exhibited by Al_0.5Cr_0.5CoFeNi, while the minimum elongation is 26.98% and the maximum hardness value is 412.6 HV. In the initial stage of friction measurement, the wear mechanism of Al_xCr_1−xCoFeNi is adhesive wear. However, as the test time progresses, an oxide layer begins to form on the alloy’s surface, leading to a gradual increase in the friction coefficient. At this stage, the wear mechanism becomes a combination of both adhesive and abrasive wear. Once the oxidation process and the wear process have reached a dynamic equilibrium, the friction coefficient stabilizes, and the wear mechanism transitions to a state of abrasive wear. The Al_0.1Cr_0.9CoFeNi alloy demonstrates the lowest friction coefficient and wear rate, exhibiting values of 0.513 and 0.020 × 10⁻³ mm³/Nm, respectively, while the Al_0.5Cr_0.5CoFeNi alloy demonstrates the highest performance, with a self-corrosion voltage of 0.202 V in a 3.5 wt.% NaCl solution. The experimental findings demonstrate that, in the presence of a decline in the Cr element within a high-entropy alloy, an augmentation in the Al element can facilitate the transition of the FCC phase to the BCC phase within the alloy, thereby enhancing its mechanical properties. However, in the Al_xCr_1−xCoFeNi HEAs, the presence of the Cr-rich and Cr-poor phases invariably results in selective corrosion in a neutral NaCl solution. The corrosion resistance of this alloy is weaker than that of a single-phase solid solution alloy with a similar chemical composition that only undergoes pitting corrosion. Full article

Background/Objectives: Only a few studies performed at industrial scale in non-simulated conditions have investigated the effect of input variability from the product’s lifecycle on product quality. The purpose of this work was to identify the root causes for the low and variable hardness of core tablets prepared using high-shear wet granulation through batch statistical modeling and to verify the short- and long-term effectiveness of the improvement actions. Methods: The novelty of this study is the use of multivariate methods for the complex assessment of a wide data set belonging to two proportional composition strengths, manufactured at an industrial scale, with different tablet shapes and sizes, with the aim of identifying inter-related active ingredient and process variables with the highest impact on hardness value and for defining optimal processing conditions leading to a robust product. Results: Four main variables affecting the output variable were identified: API particle size, nozzle type used for granulation, wet discharge, and drying intensity. These were included in an updated control strategy (3 out of 4 variables having to be within the desired ranges: API d0.5 < 45 microns; granulation nozzle that ensures liquid dispersion into droplets; gentle wet discharge and drying processes). In the case of the product studied, the newly defined process conditions could even accommodate d0.5 up to 70 microns and still ensure adequate core tablet hardness (at least 30% above the lower specification limit) for the successive film-coating step. Conclusions: Besides the beneficial impact of reducing the risk for out-of-specification hardness results, this study also offered the benefit of cost avoidance and yield improvement. The improvement was confirmed through the significant average hardness increase (15–20%) and between-batch variability decrease, leading to decent sigma quality levels (2.5) for the control phase batches. Full article

The relationship between Lean Six Sigma, Industry 4.0 and sustainable manufacturing has been evaluated only to a limited extent within this domain of the published literature. A DMAIC-DMADV-based framework along with a phase-by-phase implementation path is proposed in this study to integrate Lean Six Sigma and Industry 4.0 technologies for achieving sustainable manufacturing. The paper also focused on identifying and prioritizing the critical success factors for the implementation of the proposed framework. The critical success factors identified through a literature review are ranked using the multi-decision criteria technique TOPSIS, with input from selected experts across various manufacturing companies. The results highlight that the most important enablers set clear sustainability goals, regularly monitor progress and have a skilled workforce. The findings provide actionable guidance for practitioners, and the study contributes to the existing body of knowledge by offering a comprehensive methodology to integrate Lean Six Sigma and Industry 4.0 for sustainable manufacturing. Further research must focus on the validation of the framework in diverse industrial settings and refining the sustainability assessment model to enhance its adaptability. Full article

This review is devoted to summarizing recent developments of the linear sigma model (LSM) in cold and dense two-color QCD (QC₂D), in which lattice simulations are straightforwardly applicable thanks to the disappearance of the sign problem. In QC₂D, both theoretical and numerical studies derive the presence of the so-called baryon superfluid phase at a sufficiently large chemical potential (${\mu }_q$), where diquark condensates govern the ground state. The hadron mass spectrum simulated in this phase shows that the mass of an iso-singlet ($I=0$) and $0^{-}$ state is remarkably reduced, but such a mode cannot be described by the chiral perturbation theory. Motivated by this fact, I have invented a LSM constructed upon the linear representation of chiral symmetry, more precisely Pauli–Gürsey symmetry. It is shown that my LSM successfully reproduces the low-lying hadron mass spectrum in a broad range of ${\mu }_q$ simulated on the lattice. As applications of the LSM, topological susceptibility and sound velocity in cold and dense QC₂D are evaluated to compare with the lattice results. Additionally, the generalized Gell–Mann–Oakes–Renner relation and hardon mass spectrum in the presence of a diquark source are analyzed. I also introduce an extended version of the LSM incorporating spin-1 hadrons. Full article

Overlaying welding is a technology that allows for the acquisition of structural materials with advantageous and complex operating properties. The substrate material can be a material with advantageous mechanical and plastic properties, and the coating can provide corrosion or abrasion (wear) resistance. Among coating application techniques, plasma transfer arc (PTA) overlay welding can be used, where the overlay ensures metallic continuity and high durability, but is a limitation in the joining technologies. Therefore, research was carried out on the possibility of making Co-rich PTA overlay welding coatings on duplex steel, which combine the unique properties of duplex steel and the abrasion resistance of the coating. The tests performed showed that it is possible to apply a coating on the edges of elements without unfavorable changes in the material associated with the formation of carbides and the sigma phase in the HAZ. The coating has a structure of a Co-rich solid solution and a net of eutectics with carbide precipitations. This allowed for high hardness (600 HV10) without the need for additional heat treatment procedures. Full article