Two-dimensional Techniques Research Articles

Decreased left atrial volume and preserved left atrial function in children with congenital Zika syndrome

Abstract Introduction The infection caused by Zika virus during pregnancy leads to congenital Zika syndrome (CZS). In a previous study of our group, we found that the heart is smaller in children with CZS, with few functional alterations. Left atrial strain imaging enables quantitative assessment of left atrial function, and recently its application has also shown promise in the pediatric population. Purpose To evaluate left atrial function in children affected by CZS, using echocardiogram and speckle tracking imaging technique. Methods This observational study was conducted with children with CZS using a two-dimensional speckle tracking technique to measure left atrial reservoir strain (LAS-r), conduit strain (LAS-cd), and contraction strain (LAS-ct). Also, to investigate the relationship between LAS-r and systolic excursion of the septum and lateral mitral annular plane (MAPSE), left atrial volume index and E/e’ ratio. Results A total of 52 patients were included, the median age of the studied population was 5 years (3 to 6), 59.6% male, and the body surface area was 0.66 [0.51, 0.90]. In the echocardiographic evaluation the left atrium volume index (ml/m²) was 13.15 [6.80, 18.00], considered smaller by the reference value. Also, the LAS-r (%) was 40.99 [24-70.5], LAS-cd (%) was 30,94 [32.5-52.5], LAS-cd (%) was 10,91 [5.2-24], values considered normal by the literature. Lateral MAPSE (cm) was 1.25 [0.81, 1.86] and septal MAPSE (cm) was 0.98 [0.78, 1.66] and E/e' ratio was 7.52 [4.57, 10.78]. A positive linear correlation was found between LAS-r and lateral MAPSE (r = 0.51, P = 0.019). Conclusion This original study with children with CZS shows that despite reduced atrial volume, the left atrial function remains normal, and correlates with left ventricular function evaluated by MAPSE. Further studies are needed to prospectively analyze the follow-up of left atrial morphology and function in this population.

Through-bond and through-space radiofrequency amplification by stimulated emission of radiation

Radio Amplification by Stimulated Emission of Radiation (RASER) is a phenomenon observed during nuclear magnetic resonance (NMR) experiments with strongly negatively polarized systems. This phenomenon may be utilized for the production of very narrow NMR lines, background-free NMR spectroscopy, and excitation-free sensing of chemical transformations. Recently, novel methods of producing RASER by ParaHydrogen-Induced Polarization (PHIP) were introduced. Here, we show that pairwise addition of parahydrogen to various propargylic compounds induces RASER activity of other protons beyond those chemically introduced in the reaction. In high-field PHIP, negative polarization initiating RASER is transferred via intramolecular cross-relaxation. When parahydrogen is added in Earth’s field followed by adiabatic transfer to a high field, RASER activity of other protons is induced via both J-couplings and cross-relaxation. This through-bond and through-space induction of RASER holds potential for the ongoing development and expansion of RASER applications and can potentially enhance spectral resolution in two-dimensional NMR spectroscopy techniques.

Hyaluronan-Based Hydrogels for 3D Modeling of Tumor Tissues.

Although routine two-dimensional (2D) cell culture techniques have advanced basic cancer research owing to their simplicity, cost-effectiveness, and reproducibility, they have limitations that necessitate the development of advanced three-dimensional (3D) tumor models that better recapitulate the tumor microenvironment. Various biomaterials have been used to establish these 3D models, enabling the study of cancer cell behavior within different matrices. Hyaluronic acid (HA), a key component of the extracellular matrix (ECM) in tumor tissues, has been widely studied and employed in the development of multiple cancer models. This review first examines the role of HA in tumors, including its function as an ECM component and regulator of signaling pathways that affect tumor progression. It then explores HA-based models for various cancers, focusing on HA as a central component of the 3D matrix and its mobilization within the matrix for targeted studies of cell behavior and drug testing. The tumor models discussed included those for breast cancer, glioblastoma, fibrosarcoma, gastric cancer, hepatocellular carcinoma, and melanoma. The review concludes with a discussion of future prospects for developing more robust and high-throughput HA-based models to more accurately mimic the tumor microenvironment and improve drug testing. Impact Statement This review underscores the transformative potential of hyaluronic acid (HA)-based hydrogels in developing advanced tumor models. By exploring HA's dual role as a critical extracellular matrix component and a regulator of cancer cell dynamics, we highlight its unique contributions to replicating the tumor microenvironment. The recent advancements in HA-based models provide new opportunities for more accurate studies of cancer cell behavior and drug responses. Looking ahead, these innovations pave the way for high-throughput, biomimetic platforms that could revolutionize drug testing and accelerate the discovery of effective cancer therapies.

Three-dimensional atomic insights into the metal-oxide interface in Zr-ZrO2 nanoparticles

Metal-oxide interfaces with poor coherency have specific properties comparing to bulk materials and offer broad applications in heterogeneous catalysis, battery, and electronics. However, current understanding of the three-dimensional (3D) atomic metal-oxide interfaces remains limited because of their inherent structural complexity and the limitations of conventional two-dimensional imaging techniques. Here, we determine the 3D atomic structure of metal-oxide interfaces in zirconium-zirconia nanoparticles using atomic-resolution electron tomography. We quantitatively analyze the atomic concentration and the degree of oxidation, and find the coherency and translational symmetry of the interfaces are broken. Atoms at the interface have low structural ordering, low coordination, and elongated bond length. Moreover, we observe porous structures such as Zr vacancies and nano-pores, and investigate their distribution. Our findings provide a clear 3D atomic picture of metal-oxide interface with direct experimental evidence. We anticipate this work could encourage future studies on fundamental problems of oxides, such as interfacial structures in semiconductor and atomic motion during oxidation process.

MRCNN: Multi-input residual convolution neural network for three-dimensional reconstruction of bubble flows from light field images

Accurate measurement of bubbles in air-water two-phase flows holds immense significance in the realm of thermal hydraulics assessments within nuclear reactors. Nevertheless, conventional bubble measurement techniques grapple with challenges encompassing system intricacy, limited real-time capabilities, and inaccuracies stemming from their inherent two-dimensional (2-D) nature. In response, we pioneered an innovative three-dimensional (3-D) analysis approach that leverages light field (LF) imaging diagnosis and deep learning algorithms. Unlike traditional 2-D reconstruction methods, our approach enables direct computation of bubble depth from LF images using digital refocusing technology. Following calibration, a seamless transformation is established between the camera coordinate system and the real-world coordinate system using a sharpness evaluation algorithm. This calibration process ensures precise alignment of refocused images with real-world positions. Subsequently, fully automated and highly accurate computations of bubble depth are realized from input images via the incorporation of a multi-input residual convolution neural network (MRCNN). The limitations of traditional two-dimensional imaging techniques are effectively addressed by this methodology, resulting in a reduction in measurement errors. The study confirms the feasibility of employing LF imaging diagnosis and deep learning algorithms for bubble measurements in an air-water two-phase flow, offering a significant improvement over traditional methods.

Two-Dimensional Mammography Imaging Techniques for Screening Women with Silicone Breast Implants: A Pilot Phantom Study.

This study aimed to evaluate the impact of three two-dimensional (2D) mammographic acquisition techniques on image quality and radiation dose in the presence of silicone breast implants (BIs). Then, we propose and validate a new International Atomic Energy Agency (IAEA) phantom to reproduce these techniques. Images were acquired on a single Hologic Selenia Dimensions® unit. The mammography of the left breast of a single clinical case was included. Three methods of image acquisition were identified. They were based on misused, recommended, and reference settings. In the clinical case, image criteria scoring and the signal-to-noise ratio on breast tissue (SNRBT) were determined for two 2D projections and compared between the three techniques. The phantom study first compared the reference and misused settings by varying the AEC sensor position and, second, the recommended settings with a reduced current-time product (mAs) setting that was 13% lower. The signal-difference-to-noise ratio (SDNR) and detectability indexes at 0.1 mm (d' 0.1 mm) and 0.25 mm (d' 0.25 mm) were automatically quantified using ATIA software. Average glandular dose (AGD) values were collected for each acquisition. A statistical analysis was performed using Kruskal-Wallis and corrected Dunn tests (p < 0.05). The SNRBT was 2.6 times lower and the AGD was -18% lower with the reference settings compared to the recommended settings. The SNRBT values increased by +98% with the misused compared to the recommended settings. The AGD increased by +79% with the misused settings versus the recommended settings. The median values of the reference settings were 5.8 (IQR 5.7-5.9), 1.2 (IQR 0.0), 7.0 (IQR 6.8-7.2) and 1.2 (IQR 0.0) mGy and were significantly lower than those of the misused settings (p < 0.03): 7.9 (IQR 6.1-9.7), 1.6 (IQR 1.3-1.9), 9.2 (IQR 7.5-10.9) and 2.2 (IQR 1.4-3.0) mGy for the SDNR, d' 0.1 mm, d' 0.25 mm and the AGD, respectively. A comparison of the recommended and reduced settings showed a reduction of -6.1 ± 0.6% (p = 0.83), -7.7 ± 0.0% (p = 0.18), -6.4 ± 0.6% (p = 0.19) and -13.3 ± 1.1% (p = 0.53) for the SDNR, d' 0.1 mm, d' 0.25 mm and the AGD, respectively. This study showed that the IAEA phantom could be used to reproduce the three techniques for acquiring 2D mammography images in the presence of breast implants for raising awareness and for educational purposes. It could also be used to evaluate and optimize the manufacturer's recommended settings.

Analysis of the Adsorption Behavior of Phenanthrene on Microplastics Based on Two-Dimensional Correlation Spectroscopy.

Microplastics (MPs), an emerging pollutant, widely co-occur with polycyclic aromatic hydrocarbons (PAHs) in the environment. Therefore, the interaction between MPs and PAHs has been the focus of much attention in recent years. In this study, three types of MPs, i.e., polypropylene, polystyrene, and poly(vinyl chloride), with the same main chain were selected as the adsorbents, with phenanthrene (PHE) as the representative PAHs. The adsorption mechanisms were explored from the perspective of the molecular spectral level using a combination of Fourier transform infrared spectroscopy (FT-IR) with a two-dimensional correlation technique. The adsorption kinetics results showed that the adsorption of PHE on the three MPs was dominated by chemisorption. However, the FT-IR analysis results indicated that no new covalent bond was created during the adsorption process. Based on the above research, a generalized two-dimensional (2D) correlation spectral technique was employed to investigate the sequence of functional group changes during the adsorption process for different MPs. Furthermore, the hybrid 2D correlation spectral technique explored the effect of side groups attached to the main chain molecules of MPs on adsorption. The results showed that for all three MPs, the functional groups in the side chain have a higher affinity for PHE, which is due to their higher hydrophobicity. This study provides a feasible way to analyze the adsorption of pollutants on MPs, and the results are important for understanding the adsorption interaction between PAHs and MPs in the aquatic environment.

Exploring the role of phosphorus in the clogging formation of subsurface flow constructed wetland by two-dimensional visualization technique

Phosphorus (P) is associated with microbial activity and can be retained in constructed wetland (CW) through adsorption and chemical precipitation. However, its potential impact on clogging remains poorly studied. In this study, a two-dimensional (2D) visualization technique was utilized to investigate the effect of P on clogging process inside subsurface flow constructed wetland (SSF-CW) during the operation. Tracer images analysis showed that the preferential flow pathway proportions of P-containing group (P-CW) and P-free group (C-CW) were 30.38 ± 1.07 % and 9.72 ± 0.47 %, respectively. The fractal dimension of preferential flow pathways in C-CW (1.57 ± 0.02) was lower than in P-CW (1.70 ± 0.03), indicating that the preferential flow pathways in P-CW exhibited more diversion and tortuosity. The removal efficiencies of both CWs exhibited an initial increase followed by a decrease, with P-CW generally demonstrating higher pollutant removal efficiencies. In P-CW, the primary pathway for P removal was chemical precipitation dominated by apatite P (CaP). Furthermore, the addition of P altered the composition of extracellular polymeric substances (EPS) and reduced the stability of microbial aggregates, resulting in higher effective porosity. This study provides new insights into the role of P in the clogging of SSF-CW and would contribute to optimizing CW clogging management.

Medical image segmentation based on simulated annealing and opposition-based learning island algorithm.

With the development of society and changes in the human living environment, people are increasingly attaching importance to their own health. Regarding medical imaging examinations of certain parts of the body, the process of medical image segmentation has become extremely important. This paper presents a novel hybrid algorithm: SAOBL-IA, a fusion of the Simulated Annealing(SA), Opposition-based Learning(OBL)and Island Algorithm(IA). The Island Algorithm itself suffers from slow convergence speed and the tendency to get stuck in local optimum. To address these limitations, we introduce opposition-based learning to enhance the search range and avoid local optimum. Furthermore, we leverage the simulated annealing approach to accelerate the convergence of SAOBL-IA. Comparing the experimental results, it can be seen that SAOBL-IA has better comprehensive performance. Subsequently, the SAOBL-IA algorithm is utilized in conjunction with an optimized two-dimensional OTSU fusion segmentation technique for the purpose of medical image processing. This study proposes an application of image segmentation based on the SAOBL-IA. The segmentation of pixels around the background and target regions using the two-dimensional OTSU method faces challenges in terms of accuracy. To address this issue, an adaptive thresholding technique known as Adaptive Forking is employed for optimization. By determining the slope of the fork based on the misclassified pixel ratio, enhanced segmentation accuracy can be achieved. This improved approach is then integrated with the SAOBL-IA algorithm and applied to the segmentation of lung medical images. The experimental findings show that the amalgamation of SAOBL-IA with the adaptive two-dimensional OTSU segmentation approach, as proposed in this study, manifests superior segmentation speed and enhanced precision in the context of medical image segmentation.

Effect of combined bacteria on the flax dew degumming process: Substance degradation sequence and changes in functional bacteria taxa

In this study, 16S rDNA high-throughput sequencing, Fourier transform infrared spectroscopy, and two-dimensional correlation spectroscopy techniques were used to analyze the mechanisms driving the sequence of degradation of gummy substances by the microbial community and hydrolytic enzymes during the flax dew degumming process. The results revealed that the inoculation of combined bacteria induced quorum sensing, modulated hydrolytic enzyme production, and reshaped the community structure. Lignin-degraded genera (Pseudomonas and Sphingobacterium) were enriched, and the relative abundances of pectin- and cellulose-degraded genera (Chryseobacterium) decreased in the early degumming stages. Hemicellulose-degraded genera (Brevundimonas) increased over the degumming time. Moreover, the abundance of lignin hydrolytic enzymes improved in the early stages, while the abundance of pectin hydrolytic enzymes increased at the end of degumming. Various types of functional bacteria taxa changed the sequence of substance degradation. Electron scanning microscopy and differential scanning calorimetry results indicated that the degumming, facilitated by the inoculation of combined bacteria, was nearly completed by 21 d. The fibers exhibited smoother and more intact properties, along with higher thermal stability, as indicated by a melting temperature of 71.54 °C. This study provides a reference for selecting precise degumming bacterial agents to enhance degumming efficiency.

Validation of An Efficient 2D-HPLC Method for The Determination of Pentazocine

Pentazocine is an opioid analgesic used to treat moderate to severe pains. The real analysis for the pharmaceutical products containing pentazocine is basically to ensure the correct dose and patient safety. This study developed and validated an improved high-performance liquid chromatography (HPLC) method in the selective and accurate quantification of pentazocine. Two-dimensional (2D) HPLC technique is employed to enhance the resolution and selectivity compared to conventional HPLC methods. The 2D-HPLC instrumentation consists of two C18 columns coupling with a switching valve to capture fractions from the first column, which is analyzed in the second column. The mobile phase was optimized to 45% acetonitrile and 55% water with 0.1% phosphoric acid. The method was validated in the International Conference on Harmonization guidelines and shows excellent linearity (R2=0.998), limit of detection of 1.58 μg/L, accuracy of 97.70–102.50%, and precision by relative standard deviation (RSD) of 1.02–4.20%. Selectivity was verified in resolving pentazocine from paracetamol, caffeine, ibuprofen, and oxycodone in laboratory mixtures. The utility of the 2D-HPLC method was demonstrated by accurate quantification of pentazocine in pharmaceutical injections and tablets unaffected in excipients. This research provides a rich validating technique to enhance the quality control testing of pharmaceuticals containing pentazocine.

In-cylinder flow evolution in the horizontal plane of a motoring compression ignition engine

This study used the two-dimensional particle image velocimetry technique to quantify the in-cylinder horizontal plane velocity field evolution in a swirl-supported light-duty single-cylinder diesel engine. The data were acquired at a constant engine speed of 1600 revolutions per minute. For each case, the distance of the laser sheet from the fire deck was varied (z = 5, 10, and 20 mm) to investigate the axial variations in the flow field during the flow evolution in the compression stroke. A vortex identification algorithm was used to detect the swirl center and its deviation from the rigid body rotation. A Bessel fit was obtained using the experimental data. The result revealed that the in-cylinder flow was not axisymmetric. The swirl center approached the geometrical center as the piston approached the top dead center. The flow evolved at the farthest plane from the fire deck. The axial diffusion of angular momentum resulted in the formation of the swirl flow structure in the plane closer to the fire deck. Angular momentum analysis of a simplified geometry has been presented to explain the swirl amplification. The estimated results were compared with the experimental results to show the momentum stratification in the engine cylinder later in the compression stroke.

Pulse-echo ultrasound attenuation tomography

Objective. We present the first fully two-dimensional attenuation imaging technique developed for pulse-echo ultrasound systems. Unlike state-of-the-art techniques, which use line-by-line acquisitions, our method uses steered emissions to constrain attenuation values at each location with multiple crossing wave paths, essential to resolve the spatial variations of this tissue property. Approach. At every location, we compute normalized cross-correlations between the beamformed images that are obtained from emissions at different steering angles. We demonstrate that their log-amplitudes provide the changes between attenuation-induced amplitude losses undergone by the different incident waves. This allows us to formulate a linear tomographic problem, which we efficiently solve via a Tikhonov-regularized least-squares approach. Main results. The performance of our tomography technique is first validated in numerical examples and then experimentally demonstrated in custom-made tissue-mimicking phantoms with inclusions of varying size, echogenicity, and attenuation. We show that this technique is particularly good at resolving lateral variations in tissue attenuation and remains accurate in media with varying echogenicity. Significance. Based on a similar principle, this method can be easily combined with computed ultrasound tomography in echo mode for speed-of-sound imaging, paving the way towards a multi-modal ultrasound tomography framework characterizing multiple acoustic tissue properties simultaneously.

Subchondral Bone Osteocyte Lacunae Morphology in End-Stage Osteoarthritis of the Human Tibial Plateau.

Subchondral bone remodeling, mediated by osteocytes within the lacuno-canalicular network, plays a crucial role in osteoarthritis (OA) progression. Following cell death, lacunae preserve integrity, offering insights into bone remodeling mechanisms. Limited and controversial data on osteocyte lacuna morphology in OA result from small sample sizes and two-dimensional (2D) techniques that have been used thus far. This study aimed to quantify three-dimensional (3D) osteocyte lacunar characteristics at well-defined tibial plateau locations, known to be differently affected by OA. Specifically, 11 tibial plateaus were obtained from end-stage knee-OA patients with varus deformity. Each plateau provided one sample from the less affected lateral compartment and two samples from the medial compartment, at minimum and maximum bone volume fraction (BV/TV) locations. High-resolution desktop micro-computed tomography (micro-CT) at 0.7μm voxel resolution imaged the 33 samples. Lacuna number density (Lc.N/BV) and lacuna volume density (Lc.TV/BV) were significantly lower (p < 0.02) in samples from the medial side with maximum BV/TV compared to lateral side samples. In the medial compartment at maximum local BV/TV, mean lacuna volume (Lc.V), total lacuna volume (Lc.TV), and Lc.TV/BV were significantly (p < 0.001) lower than in the region with minimum BV/TV. Lc.N/BV was also significantly lower (p < 0.02) at the maximum local BV/TV location compared to the region with minimum BV/TV. Our findings suggest that subchondral bone lacunae adapt to the changing loads in end-stage OA.

Revealing the complexity of meniscus microvasculature through 3D visualization and analysis

Three-dimensional information is essential for a proper understanding of the healing potential of the menisci and their overall role in the knee joint. However, to date, the study of meniscal vascularity has relied primarily on two-dimensional imaging techniques. Here we present a method to elucidate the intricate 3D meniscal vascular network, revealing its spatial arrangement, connectivity and density. A polymerizing contrast agent was injected into the femoral artery of human cadaver legs, and the meniscal microvasculature was examined using micro-computed tomography at different levels of detail and resolution. The 3D vascular network was quantitatively assessed in a zone-base analysis using parameters such as diameter, length, tortuosity, and branching patterns. The results of this study revealed distinct vascular patterns within the meniscus, with the highest vascular volume found in the outer perimeniscal zone. Variations in vascular parameters were found between the different circumferential and radial meniscal zones. Moreover, through state-of-the-art 3D visualization using micro-CT, this study highlighted the importance of spatial resolution in accurately characterizing the vascular network. These findings, both from this study and from future research using this technique, improve our understanding of microvascular distribution, which may lead to improved therapeutic strategies.

Adaptive temporal compression for reduction of computational complexity in human behavior recognition

The research on video analytics especially in the area of human behavior recognition has become increasingly popular recently. It is widely applied in virtual reality, video surveillance, and video retrieval. With the advancement of deep learning algorithms and computer hardware, the conventional two-dimensional convolution technique for training video models has been replaced by three-dimensional convolution, which enables the extraction of spatio-temporal features. Specifically, the use of 3D convolution in human behavior recognition has been the subject of growing interest. However, the increased dimensionality has led to challenges such as the dramatic increase in the number of parameters, increased time complexity, and a strong dependence on GPUs for effective spatio-temporal feature extraction. The training speed can be considerably slow without the support of powerful GPU hardware. To address these issues, this study proposes an Adaptive Time Compression (ATC) module. Functioning as an independent component, ATC can be seamlessly integrated into existing architectures and achieves data compression by eliminating redundant frames within video data. The ATC module effectively reduces GPU computing load and time complexity with negligible loss of accuracy, thereby facilitating real-time human behavior recognition.

Sitting Sideways Causes Different Femoral-Tibial Rotations in Each Knee.

Purpose According to a previous study, asymmetrical kneeling, such as sitting sideways, does not exhibit asymmetrical movements. Rotational analyses of each femur and tibia help explain why rotational knee kinematics while sitting sideways do not exhibit asymmetrical movement. We aimed to assess the rotation of the femur and tibia in normal knees while sitting sideways. Methods Each volunteer sat sideways under fluoroscopy. Two-dimensional and three-dimensional registration techniques were used. After evaluating the femoral rotation angle relative to the tibia at each flexion angle, the femoral and tibial sole rotation angles at each flexion angle were compared between the ipsilateral and contralateral knees. Results While sitting sideways, both knees showed femoral external rotation relative to the tibia with flexion. In the ipsilateral knees, the femurs exhibited an external rotation of 26.3 ± 8.0°, from 110° to 150° of flexion. Conversely, the tibia exhibited an external rotation of 12.2 ± 7.8°, from 110° to 150° of flexion. From 110° to 150° of flexion, femoral external rotation was significantly larger than tibial external rotation. In the contralateral knees, the femurs exhibited an internal rotation of 23.8 ± 6.3°, from 110° to 150° of flexion (110°, p < 0.001; 120°, p < 0.001; 130°, p < 0.001; 140°, p < 0.001; and 150°, p < 0.001). Contrastingly, the tibia exhibited an internal rotation of 30.4 ± 8.8°, from 110° to 150° of flexion, which was significantly larger than femoral internal rotation (110°, p = 0.002; 120°, p < 0.001; 130°, p < 0.001; 140°, p < 0.001; and 150°, p < 0.001). Conclusions Although bilateral knees exhibited femoral external rotation relative to the tibia while sitting sideways, the ipsilateral and contralateral knees showed femoral and tibial sole rotations in opposite directions. In particular, the contralateral knees might show a strained movement because both femurs and tibias exhibited internal rotation with flexion. Patients who have undergone guided-motion total knee arthroplasty (TKA) or medial-pivot TKAs might be advised to avoid sitting sideways.

Utilizing deep ocean water in yeast fermentation for enhanced mineral-rich biomass production and fermentative regulation by proteomics modulation

Deep Ocean Water (DOW) is rich in minerals and serves as a natural source of nutrients. However, due to the inorganic nature of these minerals, cultivating yeast in DOW could aid in the fermentation process, and simultaneously, the yeast can assimilate the minerals from DOW, resulting in a mineral-enriched yeast biomass. Focusing on three DOW sources off the eastern coast of Taiwan (TT-1, HL-1, HL-2), we fermented various yeast strains of Saccharomyces cerevisiae. Therefore, this study investigates the effects of DOW on yeast growth, alcohol dehydrogenase activity, and the biological absorption of mineral ions by the yeast. Additionally, this research employs two-dimensional electrophoresis techniques to examine how the absorbed minerals influence the regulation of yeast proteins, thereby affecting biomass and metabolism. In the result, S. cerevisiae BCRC 21689 demonstrated a remarkable ability to bio-absorb minerals such as magnesium, calcium, potassium, and zinc from DOW, enhancing its growth and fermentation performance. Proteomic analysis revealed significant shifts in the expression of 21 proteins related to glycolytic and energy metabolism, alcohol metabolism, and growth regulation, all influenced by DOW's mineral-rich environment. This indicates that DOW's mineral content is a key factor in upregulating essential enzymes in glycolytic metabolism and alcohol dehydrogenase. An increase in proteins involved in synthesis and folding processes was also observed, leading to a substantial increase in yeast biomass. This study underscores the potential of DOW as a natural enhancer in yeast fermentation processes, enriching the yeast with diverse minerals and modulating proteomic expression to optimize yeast growth and fermentation.

Investigation of the three-dimensional structure of low-swirl methane-hydrogen flames with multiple UV cameras-based OH* chemiluminescence tomography

Blending hydrogen with natural gas is useful for reducing CO2 emissions, but this alters the flame structure, creating challenges for flame stability. Numerous researches on methane-hydrogen flame structure have been carried out based on two-dimensional combustion diagnostic techniques such as flame chemiluminescence and planar laser-induced fluorescence. In this paper, a low-cost OH* chemiluminescence imaging system consisting of 8 ultraviolet (UV) cameras is proposed to reconstruct the three-dimensional (3D) structure of methane-hydrogen flames, and validated through use of the correlation coefficient. Further experimental investigations of the low-swirl methane-hydrogen flames are performed by this computed tomography of chemiluminescence (CTC) system. The flame properties are determined to evaluate the effects of various fractions of blended hydrogen on the flame structure, including the flame center of mass, flame surface density and fractal dimension. Results showed that the flame initially has bowl-shape structure. The flame height gradually decreases and the flame cross-sectional area increases as the blended hydrogen fraction increases. Meanwhile, the bottom of the flame moves toward the nozzle outlet. Nevertheless, when the blended hydrogen fraction reaches 50%, the flame transforms into a cup-shaped flame and shows a double-layer flame structure. When the flame is bowl-shaped, the flame center of mass moves away from the nozzle center axis with increasing blended hydrogen fraction, but the fractal dimension and flame surface density are not sensitive to the blended hydrogen fraction. In contrast, when the flame is cup-shaped, the flame center of mass moves towards the nozzle center axis, and the flame surface density and fractal dimension increase significantly, indicating the increase of flame wrinkling. These results reveal that blending hydrogen leads to two distinct flame structures and characteristics in low-swirl flame, also demonstrate that the proposed 3D low-cost CTC system based on multiple UV cameras is well-suited for combustion diagnostics.

Optimizing Frame Techniques in 2-Dimensional Video Models in a Learning Perspective

As competition for talent increases, electronic media are often used to convey information and influence students' points of view. Animated films are an electronic media that can be used to bridge learning to make it more interesting and provide a new environmental feel for students. According to research results conducted by Computer Technology Research (CRT), people only remember 20% of what they see and 30% of what they hear. Yet people remember 50% of what they see and hear and 80% of what they see, hear and do at the same time. This research aims to evaluate students' level of interest and enthusiasm for learning history through animation media. The research method was created using two-dimensional (2D) animation techniques using frame by frame animation techniques. The data obtained is the result of research from interviews, observations, literature studies and questionnaires conducted at SDN 3 Kutasari which is located in Banyumas Regency. The results of the questionnaire testing used a Likert scale and the average formula for the results of the calculation was 87.9%, so it was included in the agree category or worthy of being shown as a 2D animated short film.