Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous removal process of hydrogen sulfide and siloxanes and field application of iron hydroxide desulfurization agent for green hydrogen production from biogas

Biogas, one of renewable energies, is a key element necessary for a carbon-neutral policy and to build a hydrogen economy. In order to utilize biogas, impurities of biogas such as moisture, hydrogen sulfide(H2S), siloxanes, and VOCs should be removed. In particular, since H2S causes corrosiveness of equipment by sulfur oxides, and is harmful to the human body if leaked, it is a major target material to be removed. The minimum concentration of H2S obtainable from the wet method is several ppm. It is known, however that the iron hydroxide-based adsorbent in the dry method can obtain ultimately low concentration of H2S down to 0.1 ppm or less. The DeHyS was manufactured through a series of processes such as mixing iron cloride solution or iron sulfate solution, NaOH solution, and inorganic binder. During the adsorption process, H2S was removed in the form of iron sulfide through a chemical reaction, and siloxanes are known to be removed through physical adsorption. It was also applied to various biogas plant sites such as landfill gas, sewage sludge, livestock manure, and food waste. At this time, the H2S removal efficiency was known to be 99.9% or more, while simultaneous removal of 90% or more of the total siloxanes was possible. Moreover, the biogas produced at the Chungju Food Bioenergy Center was pretreated using the DeHyS and supplied to the nearby Chungju Bio Green Hydrogen Charging Station to produce hydrogen through steam methane reforming(SMR), producing 500 kg of hydrogen from 8,000 m3 of biogas per day.
Study of target volume effect on efficiency index and paddick comformty index for arteriovenous malformation treatment plans by gamma knife

Background: Since energy is the product of volume times dosage, volumes are given a weighting that is proportionate to the dose that they have received. This is a result that energy is a measure of how much substance has been absorbed. Aim of the study: The current study aimed to study the fluctuation of the efficiency index and Paddick with differences in the target volume. Method The efficiency index and conformance index data were computed for each of the thirty scheduled clinical treatments using the Leksell Gamma Knife® Icon™ version (11.1) and compared to the target volume. Data analysis was carried out using the available statistical package for Social Sciences. Result The value of efficiency index (ƞ50% ) for the 30 clinical stereotactic radiosurgery treatment plans ranged from 44% to 84% with a mean value of 63%. and value of conformity was 47% to 82% with a mean value of 60.6%, The study also showed a strong relationship between target volume and this indexes. Conclusion: Volumes are given a weighting that is proportional to the dose that they have absorbed because energy is the product of volume times dose, where there would be a correlation between efficiency and conformance improvements and an increase in the target volume
Symmetry reductions and exact solutions to the systems of nonlinear partial differential equations

In this paper, the Lie symmetry analysis is performed on the four systems of nonlinear partial differential equations (PDEs). One is the system of nonlinear coupled PDEs in a real physical application. The other system describes the unsteady liquid and gas flows in long pipelines. The third is the approximate equations for long waves in shallow water. The fourth is the general classical dispersiveless long wave equations. All of the point symmetries of the systems are presented for the first time, then the symmetry reductions and exact solutions to the systems are investigated.
True Random Number Generator Based on the Variability of the High Resistance State of RRAMs

Hardware-based security primitives like True Random Number Generators (TRNG) have become a crucial part in protecting data over communication channels. With the growth of internet and cloud storage, TRNGs are required in numerous cryptographic operations. On the other hand, the inherently dense structure and low power characteristics of emerging nanoelectronic technologies such as resistive-switching memories (RRAM) make them suitable elements in designing hardware security modules integrated in CMOS ICs. In this paper, a memristor based TRNG is presented by leveraging the high stochasticity of RRAM resistance value in OFF (High Resistive) state. In the proposal, one or two devices can be used depending on whether the objective is focused on saving area or obtaining a higher random bit frequency generation. The generated bits, based on a combination of experimental measurements and SPICE simulations, passed all 15 National Institute of Standards and Technology (NIST) tests and achieved a throughput of tens of MHz.
Accessibility to E-Commerce Websites for People with Disability in Indonesia

Using a website has become a primary method for delivering information, doing promotion, and marketing activities. E-commerce business people acknowledged the importance of developing a reliable website to reach the market through the internet, as part of e-service, especially in a country with a large market share like Indonesia. Unfortunately, not every e-commerce web designer is aware of the website accessibility criteria, the lack of awareness creates barriers for persons with disabilities to access e-commerce websites, as buyers and sellers. The accessibility gap of those website limits the ability of persons with disabilities to optimize the presence of e-commerce as an economic opportunity. We need to overcome the barriers to create an inclusive society in Indonesia. This paper aims to provide an overview of the accessibility of e-commerce websites in Indonesia, to find the common web accessibility issues, classified them comparatively into several tiers, type of issues, and then calculates the correlation of total issues with the number of visitors. This study analyzes 39 e-commerce websites. We evaluate based on Web Content Accessibility Guidelines (WCAG) 2.0, using an automated tool called "aXe". The study shows evidence of various accessibility issues of e-commerce websites in Indonesia, emphasizing the necessity of web designers to pay more attention to accessibility for users with disabilities. This study also provides several recommendations to website accessibility as part of e-service quality.
TiO2‐WO3 nanocube‐polyaniline hierarchical membrane for efficient removal of chromium in a photocatalytic membrane reactor

In this article, the rational design of a physically coated TiO2‐WO3 nanocube‐polyaniline photocatalytic membrane (hierarchical) reactor for the efficient reduction of chromium (VI) under visible light is discussed. The incorporation of TiO2‐WO3 in the polyaniline (PANI) membrane provides excellent hydrophilicity and high photo‐corrosion resistance and facilitates the rapid permeation of water with a flux rate of 12 L/m2 h and higher Cr (VI) reduction. The exposure of bare PANI membranes in Cr (VI) solution leads to over‐oxidation of PANI membrane and eventually leads to the destruction of the membrane. The hierarchical photocatalytic coating improves the lifetime of the membrane by blocking it from deprotonation. The photocatalytic membrane could offer 79.30% Cr (VI) reduction under visible light irradiation in a photocatalytic membrane reactor. After several reduction cycles, the membrane showed good self‐cleaning ability. The present work suggests that TiO2‐WO3 nanocube‐coated PANI hierarchical membrane is a promising approach for the reduction and removal of Cr (VI) from wastewater.
Asian option pricing with orthogonal polynomials

In this paper we derive a series expansion for the price of a continuously sampled arithmetic Asian option in the Black–Scholes setting. The expansion is based on polynomials that are orthogonal with respect to the log-normal distribution. All terms in the series are fully explicit and no numerical integration nor any special functions are involved. We provide sufficient conditions to guarantee convergence of the series. The moment indeterminacy of the log-normal distribution introduces an asymptotic bias in the series, however we show numerically that the bias can safely be ignored in practice.
Bragg–Williams Theory for Particles with a Size-Modulating Internal Degree of Freedom

The field of soft matter teems with molecules and aggregates of molecules that have internal size-modulating degrees of freedom. Proteins, peptides, microgels, polymers, micelles, and even some colloids can exist in multiple—often just two dominating—states with different effective sizes, where size can refer to the volume or to the cross-sectional area for particles residing on surfaces. The size-dependence of their accessible states renders the behavior of these particles pressure-sensitive. The Bragg–Williams model is among the most simple mean-field methods to translate the presence of inter-particle interactions into an approximate phase diagram. Here, we extend the Bragg–Williams model to account for the presence of particles that are immersed in a solvent and exist in two distinct states, one occupying a smaller and the other one a larger size. The basis of the extension is a lattice–sublattice approximation that we use to host the two size-differing states. Our model includes particle–solvent interactions that act as an effective surface tension between particles and solvent and are ignorant of the state in which the particles reside. We analyze how the energetic preference of the particles for one or the other state affects the phase diagrams. The possibility of a single phase-two phases-single phase sequence of phase transitions as a function of increasing temperature is demonstrated.
The XYG3 type of doubly hybrid density functionals

Doubly hybrid (DH) functionals have emerged as a new class of density functional approximations (DFAs), which not only have a nonlocal orbital‐dependent component in the exchange part, but also incorporate the information of unoccupied orbitals in the correlation part, being at the top rung of Perdew's view of Jacob's ladder in DFAs. This review article focuses on the XYG3 type of DH (xDH) functionals, which use a low rung functional to perform the self‐consistent‐field calculation to generate orbitals and densities, with which a top rung DH functional is used for final energy evaluation. We will discuss the theoretical background of the xDH functionals, briefly reviewing the adiabatic connection formalism, coordinate scaling relations, and Görling–Levy perturbation theory. General performance of the xDH functionals will be presented for both energies and structures. In particular, we will present the fractional charge behaviors of the xDH functionals, examining the self‐interaction errors, the delocalization errors and the deviation from the linearity condition, as well as their effects on the predicted ionization potentials, electron affinities and fundamental gaps. This provides a theoretical rationale for the observed good performance of the xDH functionals. WIREs Comput Mol Sci 2016, 6:721–747. doi: 10.1002/wcms.1274
The Acoustic Performance of Natural Composites in Reducing Stress Levels: Textile Industry

The porous characteristics of recycled natural fibres make them suitable for use as acoustic materials. Straw and water hyacinth fibres are natural materials that can potentially be used as composites in damping devices. This study evaluated the acoustic performance of two types of reinforced composites containing natural fibers (water hyacinth and rice straw) and gypsum adhesives in reducing stress levels in the textile industry. The evaluation was carried out through laboratory tests using impedance tubes and direct testing in a textile factory to reduce the stress level of production machine workers and operators. Rice straw and water hyacinth fibres were thoroughly mixed in proven mass ratios of 10% and 30% with water and gypsum plaster as a binder. The mixture was pressed into a mould at a pressure of 3 MPa before being heated in an oven at 900ºC for 5 hours. Perforations measuring 4 to 8 mm in diameter were then made at equal distances on the panels. Acoustic panel performance tests were carried out with impedance tubes according to ISO 10534-2 standards at sound frequencies ranging from 0 to 6400 Hz. Field tests were also conducted at a textile factory, with each machine unit generating a sound source of 100 to 110 dB. Heart rate data was collected, and noise measurements were carried out before and after the panels were installed in the area around the operating machines. The results showed that the rice straw-gypsum composite with four perforations performed the best, achieving an α coefficient of 1.0 at a frequency of 1500 Hz and an NRC of 0.50, indicating effective noise reduction. The installation of acoustic panels around the noise source in the textile industry reduced noise levels by up to 9.8 dB and was found to affect workers' heart rates, indicating reduced stress levels. The questionnaire results also showed a significant effect on the stress levels of workers. The use of natural fibers in composite materials has the potential to be an eco-friendly and sustainable solution for soundproofing applications. Doi: 10.28991/CEJ-2023-09-06-02 Full Text: PDF
The Trainer's Presence in Effective Gestalt Training

"Abstract: This paper explores the presence ofthe trainer as an essential and central part of effective Gestalt training. It attempts to define the subtle and complex concept of presence and suggests that it consists of five main aspects: being present, being authentic, maintaining creative indifference, practising inclusion, and attuning to the field. It looks at the challenges of presence for trainers as opposed to therapists, and begins to investigate how trainers can support and develop their presence. Key words: presence, trainer, here and now, authenticity, inclusion, creative indifference, attuning to the field, Gestalt training. "
Study of a First Approach to the Controlled Fermentation for Lambic Beer Production

Non-Saccharomyces yeasts represent a great source of biodiversity for the production of new beer styles, since they can be used in different industrial areas, as pure culture starters, in co-fermentation with Saccharomyces, and in spontaneous fermentation (lambic and gueuze production, with the main contribution of Brettanomyces yeast). The fermentation process of lambic beer is characterized by different phases with a characteristic predominance of different microorganisms in each of them. As it is a spontaneous process, fermentation usually lasts from 10 months to 3 years. In this work, an attempt was made to perform a fermentation similar to the one that occurred in this process with lactic bacteria, Saccharomyces yeast and Brettanomyces yeast, but controlling their inoculation and therefore decreasing the time necessary for their action. For this purpose, after the first screening in 100 mL where eight Brettanomyces yeast strains from D.O. “Ribeira Sacra” (Galicia) were tested, one Brettanomyces bruxellensis strain was finally selected (B6) for fermentation in 1 L together with commercial strains of Saccharomyces cerevisiae S-04 yeast and Lactobacillus brevis lactic acid bacteria in different sequences. The combinations that showed the best fermentative capacity were tested in 14 L. Volatile compounds, lactic acid, acetic acid, colour, bitterness, residual sugars, ethanol, melatonin and antioxidant capacity were analysed at different maturation times of 1, 2, 6 and 12 months. Beers inoculated with Brettanomyces yeast independently of the other microorganisms showed pronounced aromas characteristic of the Brettanomyces yeast. Maturation after 12 months showed balanced beers with “Brett” aromas, as well as an increase in the antioxidant capacity of the beers.
Using Machine Learning Classifiers in SAT Branching [Extended Abstract]

The Boolean Satisfiability Problem (SAT) can be framed as a binary classification task. Recently, numerous machine and deep learning techniques have been successfully deployed to predict whether a CNF has a solution. However, these approaches do not provide a variables assignment when the instance is satisfiable and have not been used as part of SAT solvers. In this work, we investigate the possibility of using a machine-learning SAT/UNSAT classifier to assign a truth value to a variable. A heuristic solver can be created by iteratively assigning one variable to the value that leads to higher predicted satisfiability. We test our approach with and without probing features and compare it to a heuristic assignment based on the variable's purity. We consider as objective the maximisation of the number of literals fixed before making the CNF unsatisfiable. The preliminary results show that this iterative procedure can consistently fix variables without compromising the formula's satisfiability, finding a complete assignment in almost all test instances.
Structure of Parallel Mechanism Combined with Waterbomb-Base-Inspired Origami

: Structure from the geometry and analysis of the three-spherical kinematic chain-base parallel mechanism have been studied. The parallel mechanism evolved from an origami fold as chain legs with three spherical kinematic chains becoming rigid bodies. The parallel mechanism with a three 6R kinematic chain as three chain legs is complicated. The reconﬁguration of the parallel mechanism with full tilt–circle movement, kinematic, and workspace are investigated, too. This parallel mechanism can be applied in speciﬁc applications with certain treatments.
A Survey of Graph Neural Networks on Synthetic Data

A Survey of Graph Neural Networks on Synthetic Data Brigham Stone Carson Department of Mathematics, BYU Master of Science We relate properties of attributed random graph models to the performance of GNN architectures. We identify regimes where GNNs outperform feedforward neural networks and non-attributed graph clustering methods. We compare GNN performance on our synthetic benchmark to performance on popular real-world datasets. We analyze the theoretical foundations for weak recovery in GNNs for popular oneand two-layer architectures. We obtain an explicit formula for the performance of a 1-layer GNN, and we obtain useful insights on how to proceed in the 2-layer case. Finally, we improve the bound for a notable result on the GNN size generalization problem by 1.
Wellness in the Workplace: An Analysis on the Office Environment and Mental Health in Chicago and NYC

Professionals in America spend five days a week, an average of 40 hours, in an office environment. These same people tailor their homes to be comfortable oases that inspire happiness, but is this same effort being made for these office spaces they somewhat call home especially after the COVID-19 pandemic? The question our team set out to ask is as follows: Should companies prioritize investing in better working environments with a focus to increase employee wellbeing and mental health? We use New York City and Chicago as subjects in our analysis to find a relationship between building aesthetics and employee wellbeing/mental health. Using WELL-certified square feet per resident, substance abuse, mental illness, happiness, and stress statistics, we paint a picture of how the work environment affects employees through a multi-method approach. Starting with the empirical analysis, we found two statistically significant correlations, however, these are not intuitive and in line with our literature review. Our normative analysis led to actionable insights surrounding the design of office spaces to benefit employees.
AP-XHPJ220070 1390..1409

Change detection tasks are commonly used to measure and understand the nature of visual working memory capacity. Across three experiments, we examine whether the nature of the memory signals used to perform change detection are continuous or all-or-none and consider the implications for proper measurement of performance. In Experiment 1, we find evidence from confidence reports that visual working memory is continuous in strength, with strong support for an equal variance signal detection model with no guesses or lapses. Experiments 2 and 3 test an implication of this, which is that K should confound response criteria and memory. We found K values increased by roughly 30% when criteria are shifted despite no change in the underlying memory signals. Overall, our data call into question a large body of work using threshold measures, like K, to analyze change detection data. This metric confounds response bias with memory performance and is inconsistent with the vast majority of visual working memory models, which propose variations in precision or strength are present in working memory. Instead, our data indicate an equal variance signal detection model (and thus, d’)—without need for lapses or guesses—is sufficient to explain change detection performance.
Text Mining in Online Social Networks: A Systematic Review

Summary Online social networks contain a large amount of data that can be converted into valuable and insightful information. Text mining approaches allow exploring large-scale data efficiently. Therefore, this study reviews the recent literature on text mining in online social networks in a way that produces valid and valuable knowledge for further research. The review identifies text mining techniques used in social networking, the data used, tools, and the challenges. Research questions were formulated, then search strategy and selection criteria were defined, followed by the analysis of each paper to extract the data relevant to the research questions. The result shows that the most social media platforms used as a source of the data are Twitter and Facebook. The most common text mining technique were sentiment analysis and topic modeling. Classification and clustering were the most common approaches applied by the studies. The challenges include the need for processing with huge volumes of data, the noise, and the dynamic of the data. The study explores the recent development in text mining approaches in social networking by providing state and general view of work done in this research area.
Towards Benchmarking Sampling-Based Kinodynamic Motion Planners with ML4KP

—This work introduces a benchmarking framework for sampling-based kinodynamic planning algorithms, built on top of ML4KP , a C++ library for efficient kinodynamic planning that allows to incorporate learned primitives for planning purposes. ML4KP is fast, has minimal dependencies, and provides implementations of state-of-the-art kinodynamic planners that can be used with minimal configuration for the included systems. In contrast to other motion planning libraries, ML4KP allows to directly generate solutions for dynamic systems, without the need for additional post-processing of obtained solution paths. ML4KP is intended to be used by the robot learning community that seek to use sampling-based motion planners, as well as members of the motion planning community interested in integrating machine learning tools. Project website: https://sites.google. com/ scarletmail.rutgers. edu/ml4kp/
Efficiently feeding single-mode fiber photonic spectrographs with an extreme adaptive optics system: on-sky characterization and preliminary spectroscopy

High-order wavefront correction is not only beneficial for high-contrast imaging, but also spectroscopy. The size of a spectrograph can be decoupled from the size of the telescope aperture by moving to the diffraction limit which has strong implications for ELT based instrument design. Here we present the construction and characterization of an extremely efficient single-mode fiber feed behind an extreme adaptive optics system (SCExAO). We show that this feed can indeed be utilized to great success by photonic-based spectrographs. We present metrics to quantify the system performance and some preliminary spectra delivered by the compact spectrograph.