Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of soft x-ray detection performance in superconducting-tunnel-junction array detectors with close-packed arrangement by three-dimensional structure

Superconducting-tunnel-junction (STJ) array detectors have exhibited excellent characteristics for fluorescence-yield x-ray absorption fine structure (XAFS) for trace light elements in structural and functional materials. For XAFS, we have developed new fabrication processes for close-packed STJ pixels by using a three-dimensional structure (3D-STJ), in which the layers of STJ pixels are formed after caldera planarization of the base SiO2 layer deposited on the patterned wiring leads. The 3D-STJ has an operation yield of 88% and a mean energy resolution of 23.8 +/−1.9 eV for the C-Kα x-ray.
Magnetic and Structural Properties of Iridates and Cuprates in Reduced Dimensions

Magnetic and Structural Properties of Iridates and Cuprates in Reduced Dimensions Andreea Lupascu Doctor of Philosophy Graduate Department of Physics University of Toronto 2015 Physics at reduced dimensionality has seen an increased interest in the last decade, due to the novel properties that arise in low-dimensional materials. In this dissertation, we have employed scattering and absorption x-ray techniques to investigate the magnetic and structural properties of two classes of transition metal-oxides with reduced dimensionality: Sr2IrO4 (a 5d layered perovskite iridate) and Ba2IrO4 (a 3d cuprate). X-ray Resonant Magnetic Scattering (XRMS) was used to study the magnetic properties of epitaxially-strained Sr2IrO4 thin films grown via pulsed laser deposition. Epitaxial strain proves to be a great way of tuning the magnetic transition temperature TN of Sr2IrO4, a system in which the interplay between the strong spin-orbit coupling and crystal field renders the magnetic properties very sensitive to small structural distortion. The strong magneto-elastic coupling in Sr2IrO4 is also illustrated by the observation of a spontaneous magnetostriction effect in a 20-nm thin film sample, which increases significantly at the onset of magnetic ordering, and could be attributed to the strong spin-orbit interactions in the 5d oxide. The 20-nm film also exhibits a smoothly evolving field-driven phase transition, which is irreversible at 5 K. Finally, the XRMS study of a Sr2IrO4 single-crystal under an applied magnetic field displays a rich field-driven phase diagram, characterized by magnetic domain re-population, a hysteresis behaviour, and a change in magnetic domain size with temperature. A combination of Micro-Fluorescence (μXRF) and Micro-Diffraction (μXRD) was developed to study the structural properties of nanocrystals obtained via mechanical exfoliation. The structural studies have focused on the thickness dependence of the “4.7
The Transcriptome Response to Azole Compounds in Aspergillus fumigatus Shows Differential Gene Expression across Pathways Essential for Azole Resistance and Cell Survival

The opportunistic pathogen Aspergillus fumigatus is found on all continents and thrives in soil and agricultural environments. Its ability to readily adapt to novel environments and to produce billions of spores led to the spread of azole-resistant A. fumigatus across the globe, posing a threat to many immunocompromised patients, including critically ill patients with severe influenza or COVID-19. In our study, we sought to compare the adaptational response to azoles from A. fumigatus isolates that differ in azole susceptibility and genetic background. To gain more insight into how short-term adaptation to stressful azole compounds is managed through gene expression, we conducted an RNA-sequencing study on the response of A. fumigatus to itraconazole and the newest clinically approved azole, isavuconazole. We observed many similarities in ergosterol biosynthesis up-regulation across isolates, with the exception of the pan-azole-resistant isolate, which showed very little differential regulation in comparison to other isolates. Additionally, we found differential regulation of membrane efflux transporters, secondary metabolites, iron metabolism, and various stress response and cell signaling mechanisms.
Distinct Clades of Protein Phosphatase 2A Regulatory B’/B56 Subunits Engage in Different Physiological Processes

Protein phosphatase 2A (PP2A) is a strongly conserved and major protein phosphatase in all eukaryotes. The canonical PP2A complex consists of a catalytic (C), scaffolding (A), and regulatory (B) subunit. Plants have three groups of evolutionary distinct B subunits: B55, B’ (B56), and B’’. Here, the Arabidopsis B’ group is reviewed and compared with other eukaryotes. Members of the B’α/B’β clade are especially important for chromatid cohesion, and dephosphorylation of transcription factors that mediate brassinosteroid (BR) signaling in the nucleus. Other B’ subunits interact with proteins at the cell membrane to dampen BR signaling or harness immune responses. The transition from vegetative to reproductive phase is influenced differentially by distinct B’ subunits; B’α and B’β being of little importance, whereas others (B’γ, B’ζ, B’η, B’θ, B’κ) promote transition to flowering. Interestingly, the latter B’ subunits have three motifs in a conserved manner, i.e., two docking sites for protein phosphatase 1 (PP1), and a POLO consensus phosphorylation site between these motifs. This supports the view that a conserved PP1-PP2A dephosphorelay is important in a variety of signaling contexts throughout eukaryotes. A profound understanding of these regulators may help in designing future crops and understand environmental issues.
Multiple linear regression models for the estimation of water flows for forest management and planning in Türkiye

While there are many factors, including climatology, geography, topography, vegetation and soil, that affect hydrologic processes, understanding the role of forests seems most essential, due to their manageable nature. In this study, a holistic approach was taken, and possible factors affecting streamflow, including tree, sapling, shrub, herb and soil strata, were measured for 29 small catchments/stream basins located in Turkey. Linear regression models were developed in order to estimate water flow (m³‧ha−1). Several models were suggested for use in practice. These models were based on the data on hand and displayed a sufficient level of explained variance in the dependent variable. Model 5, based on the variablesof catchment area (ha), drainage density, ratio of coniferous stand areas in the catchment (%), tree volume (m³‧ha−1), leaf area index, number of short saplings (number‧ha−1), and topsoil sand rate (%), was recommended for flow estimation, achieving a 0.73 adjR² value for test data. These variables can be obtained as part of a survey and water managers can use them to estimate water flow of the catchment. The generated models can be used in multiple-use planning of forests, e.g. in adjusting the volume of stands to get optimum benefit from wood and water production. One of the most interesting results and one that was opposite to that documented in the general literature, was the positive correlation between tree volume and flow per hectare, which suggests a strategy of growing older tree stands to enable greater water production.
An information-theoretic framework for optimization with applications in source coding and pattern recognition

This work develops a unified approach for hard optimization problems involving data association, i.e. the assignment of data to classes in order to minimize a specified cost. The diverse problems which fit this informal definition include: vector quantization, piecewise regression, statistical classifier design, as well as combinatorial optimization problems such as graph partitioning. Whereas standard methods are susceptible to finding poor local optima, the suggested approach has some potential for avoiding local optima, yet without the computational complexity of stochastic annealing. The method is based on ideas from information theory and statistical physics, and builds on the clustering work of Rose, Gurewitz, and Fox. The optimization problem is embedded in a framework in which data are assigned to classes in probability, with the distributions chosen to minimize the expected cost given constrained "randomness" (Shannon's entropy). The constrained optimization is equivalent to minimization of the Helmholtz free energy, with the temperature a Lagrange multiplier controlling the entropy and cost. Thus, a deterministic annealing (DA) algorithm is motivated, where the expected cost and randomness are reduced with temperature. The primary contribution of the dissertation involves challenging structurally-constrained assignment problems. The research culminates with the development of a general approach for incorporating structural constraints within the optimization framework. This is accomplished by quantifying achievement of the structure and identifying a second Lagrange multiplier which is optimized to achieve a level of constraint consistent with the entropy and cost objectives. The resulting versatile optimization approach is applicable to fundamental problems in supervised learning--statistical classification and piecewise regression--as well as to structured vector quantizer design. The method is developed for statistical classification and shown to outperform known techniques for the design of nearest-prototype, radial basis function, and multilayer perceptron-based classifiers, while often retaining design complexity comparable to or only moderately greater than that of strict descent methods. Substantial performance improvements are achieved for challenging problems involving high-dimensional data and large class overlap.
Strategies and resources of mode-division-multiplexed optical fibre transmission based on LP and orbital angular momentum modes

We present research into the capacity and spectral efficiency of various spatial and mode division multiplexed transmission schemes in multimode optical fibres, including MIMO schemes based linearly polarized (LP) modes and orbital angular momentum (OAM) modes. We estimate their spectral efficiency by calculating the transmission matrix and considering mode coupling under different schemes. We also consider the signal-processing prefix for LP-MIMO and OAM based technologies to calculate the effective spectral efficiency. Simulation results show LP-MIMO using step-index fibre can support higher spectral efficiency than both LP-MIMO with graded-index fibre and OAM, while LP-MIMO with gradedindex fibre has similar levels of spectral efficiency as OAM. We further compare the computational resources required to support the signal processing algorithms in order to achieve certain amount of capacity or spectral efficiency and reveal the scaling of computational resources with capacity in different MDM schemes. Considering the implementation of MIMO algorithms and any processing required to support spatial light modulator (SLM) based optical crosstalk equalization schemes, we demonstrate that OAM-based MDM has the lowest computational resource requirement and offers a much higher spectral efficiency with limited computational resource in both processing power and memory size requirements resulting from intermodal group velocity dispersion in multimode fibres. We also show that OAM based schemes could save significant signal processing energy overhead due to its low computational resource requirement.
Hybrid Chaos Particle Swarm Optimization algorithm for smart Cloud Service System based on optimization resource scheduling and allocation

To enhance the smart Cloud Service System for diverse user requirements in 5G and other service networks, this study leverages resource utilization and multi-tenancy network slicing operation costs. Specifically, we propose a multi-tenancy network resource allocation strategy based on the Chaos Particle Swarm Optimization (CPSO) algorithm. In a multi-tenancy network (MTN), we lease the wireless spectrum resources of the infrastructure provider’s base station, construct access service slices as network slice services, and offer network access services to users. Introduce detailed formulation of the relationship between MTN and users, represented as a multi-master and multi-slave construct that defines the strategy space and profit function after MTN decision-making. Reverse induction is used to analyze the proposed model, and a distributed iterative algorithm is proposed to obtain the optimal throughput demand of users and the optimal slice cost of MTN. Simulation results demonstrate that the proposed strategy can effectively enhance resource utilization and user satisfaction while reducing energy consumption.
Ge-rich SiGe waveguides for mid-infrared photonics

The extension of silicon photonics towards the mid infrared (mid-IR) spectral range has recently attracted a lot of attention. The development of photonic devices operating at these wavelengths is crucial for many applications including environmental and chemical sensing, astronomy and medicine. Recent works regarding the development of Ge-rich SiGe waveguides on graded buffer layers will be presented. It will be shown that these waveguides demonstrate low loss and strong mode confinement for a large range of wavelengths and that they have a good potential for being a major building block of mid-infrared photonic integrated circuits.
Musi-ABC for Predicting Musical Emotions

To address the issues of insufficient accuracy and low training efficiency in general musical emotion prediction models, we propose the muSi-ABC architecture for predicting music emotions. Specifically, in the feature extraction stage of music emotions, we use a benchmark feature set to ensure that the extracted music emotion features adhere to standardization. In the prediction stage, we introduce the muSi-ABC architecture which first utilizes a 2D-ConvNet (two dimensional-Convolutional Neural network) to extract partial critical features in music emotions. Then, the BiLSTM (Bi-directional Long Short Term Memory) neural network is employed to learn contextual sequential information of past and future music emotions from the obtained partial critical features. Furthermore, the SA (Self-Attention) module is applied to obtain the complete critical features highly relevant to music emotions, thereby improving prediction accuracy and training efficiency. Through ablation experiments conducted at different time term lengths, the roles of ConvNet model and SA module, as well as the advantages of the proposed muSi-ABC architecture over other ablated models in terms of training efficiency and prediction accuracy, are verified. Additionally, it is observed that representing music emotions using long term feature information for the same song can enhance prediction accuracy. Finally, contrast experimental results demonstrate that the proposed architecture outperforms other benchmark methods in terms of prediction accuracy. Moreover, it is validated that the outlier points contained in the music emotions features extracted based on the benchmark feature set help discover the variations trends of music emotions.
3D precision measurements of meter sized surfaces using low cost illumination and camera techniques

Using dedicated stereo camera systems and structured light is a well-known method for measuring the 3D shape of large surfaces. However the problem is not trivial when high accuracy, in the range of few tens of microns, is needed. Many error sources need to be handled carefully in order to obtain high quality results. In this study, we present a measurement method based on low-cost camera and illumination solutions combined with high-precision image analysis and a new approach in camera calibration and 3D reconstruction. The setup consists of two ordinary digital cameras and a Gobo projector as a structured light source. A matrix of dots is projected onto the target area. The two cameras capture the images of the projected pattern on the object. The images are processed by advanced subpixel resolution algorithms prior to the application of the 3D reconstruction technique. The strength of the method lays in a different approach for calibration, 3D reconstruction, and high-precision image analysis algorithms. Using a 10 mm pitch pattern of the light dots, the method is capable of reconstructing the 3D shape of surfaces. The precision (1σ repeatability) in the measurements is <10 µm over a volume of 60 × 50 × 10 cm3 at a hardware cost of ~2% of available advanced measurement techniques. The expanded uncertainty (95% confidence level) is estimated to be 83 µm, with the largest uncertainty contribution coming from the absolute length of the metal ruler used as reference.
Business transformation at the vegetable trading post: Foundational development strategy for the future

This study, conducted in Nueva Ecija, Philippines, explores the issue of business transformation at vegetable trading posts, aiming to propose a strategic approach for future development. Grounded in strategic management theory (Porter, 1985) and using a case study methodology, the research scrutinizes the current business operations of trading posts and the dynamic context they operate within. It identifies several challenges trading posts face, including the low bargaining power of farmers, small quantities of produce, and erratic pricing mechanisms. A key finding is the potential benefits of integrating digital technologies to enhance operational efficiency and market reach (Bharadwaj et al., 2013). Furthermore, it emphasizes the importance of establishing more resilient and inclusive supply chains. This research contributes to the ongoing discourse on sustainable agricultural practices and opens avenues for innovative business transformation strategies in the vegetable trading sector. It serves as a key reference for policymakers, stakeholders, and researchers interested in sustainable agricultural practices.
Factors Affecting Bias Temperature Instability in 4H-SiC MOS Capacitors

The threshold voltage of 4H-SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) show instability during normal operation, especially after bias temperature stress (BTS), and this phenomenon is called bias temperature instability (BTI). In this work, to study the factors affecting threshold voltage (Vth) instability of SiC MOSFETs, flat-band voltage (Vfb) instability of 4H-SiC metal-oxide-semiconductor (MOS) capacitors is discussed instead. Some factors, including the polarity of gate bias stress, stress time, and stress temperature, are analyzed by performing one-way bias stress C-V measurements in the devices. Firstly, positive bias stress leads to a positive Vfb shift, and negative bias stress leads to a negative one. Moreover, the Vfb shift appears to exhibit a linear relationship with log (stress time). Furthermore, the Vfb shift decreases over the temperature range of 225 K to 400 K, but slightly increases at 475 K. Finally, the Vfb stability of the MOS devices fabricated by 1200 °C NO post-oxidation annealing (POA) and those fabricated by 1250 °C NO POA is similar.
Rational PCR Reactor Design in Microfluidics

Limit of detection (LOD), speed, and cost for some of the most important diagnostic tools, i.e., lateral flow assays (LFA), enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR), all benefited from both the financial and regulatory support brought about by the pandemic. From those three, PCR has gained the most in overall performance. However, implementing PCR in point of care (POC) settings remains challenging because of its stringent requirements for a low LOD, multiplexing, accuracy, selectivity, robustness, and cost. Moreover, from a clinical point of view, it has become very desirable to attain an overall sample-to-answer time (t) of 10 min or less. Based on those POC requirements, we introduce three parameters to guide the design towards the next generation of PCR reactors: the overall sample-to-answer time (t); lambda (λ), a measure that sets the minimum number of copies required per reactor volume; and gamma (γ), the system’s thermal efficiency. These three parameters control the necessary sample volume, the number of reactors that are feasible (for multiplexing), the type of fluidics, the PCR reactor shape, the thermal conductivity, the diffusivity of the materials used, and the type of heating and cooling systems employed. Then, as an illustration, we carry out a numerical simulation of temperature changes in a PCR device, discuss the leading commercial and RT-qPCR contenders under development, and suggest approaches to achieve the PCR reactor for RT-qPCR of the future.
Improving Enzymatic Saccharification of Peach Palm (Bactris gasipaes) Wastes via Biological Pretreatment with Pleurotus ostreatus

The white-rot fungus Pleurotus ostreatus was used for biological pretreatment of peach palm (Bactris gasipaes) lignocellulosic wastes. Non-treated and treated B. gasipaes inner sheaths and peel were submitted to hydrolysis using a commercial cellulase preparation from T. reesei. The amounts of total reducing sugars and glucose obtained from the 30 d-pretreated inner sheaths were seven and five times higher, respectively, than those obtained from the inner sheaths without pretreatment. No such improvement was found, however, in the pretreated B. gasipaes peels. Scanning electronic microscopy of the lignocellulosic fibers was performed to verify the structural changes caused by the biological pretreatments. Upon the biological pretreatment, the lignocellulosic structures of the inner sheaths were substantially modified, making them less ordered. The main features of the modifications were the detachment of the fibers, cell wall collapse and, in several cases, the formation of pores in the cell wall surfaces. The peel lignocellulosic fibers showed more ordered fibrils and no modification was observed after pre-treatment. In conclusion, a seven-fold increase in the enzymatic saccharification of the Bactris gasipaes inner sheath was observed after pre-treatment, while no improvement in enzymatic saccharification was observed in the B. gasipaes peel.
Development and evaluation of ready to serve (RTS) beverage from bael (Aegle marmelose Correa.)

A research study was carried out to develop a RTS beverage by exploiting the nutritional and organoleptic properties of bael fruit pulp. Six treatment combinationsof bael RTS with 10, 15 and 20% of pulp concentration and 10 and 15°B of TSS were prepared based on the review of literature. The biochemical and organoleptic properties of the prepared RTS were evaluated during storage. The pH, ascorbic acid and antioxidant activity of the RTS decreased with the storage, while acidity and total sugars increased. Results of the sensory evaluation showed that there was a significant difference between treatments in terms of color, flavor, taste, body and overall acceptability. From the results of quality assessments, the formulated bael RTS beverage with 15% pulp and 15°B TSS was found to be superior and suitable for consumption up to 12 weeks without any significant changes in the quality characteristics.