Miracle-dz/UniFAR-FTUs huggingface dataset:
Phenolic Biotransformations in Wheatgrass Juice after Primary and Secondary Fermentation

Fermented wheatgrass juice was prepared using a two-stage fermentation process by employing Saccharomyces cerevisiae and recombinant Pediococcus acidilactici BD16 (alaD+). During fermentation, a reddish-brown hue appeared in wheatgrass juice due to production of different types of red pigments. The fermented wheatgrass juice has considerably higher content of anthocyanins, total phenols and beta-carotenes as compared to unfermented wheatgrass juice. It has low ethanol content, which might be ascribed to the presence of certain phytolignans in wheatgrass juice. Several yeast-mediated phenolic transformations (such as bioconversion of coumaric acid, hydroxybenzoic acid, hydroxycinnamic acid and quinic acid into respective derivatives; glycosylation and prenylation of flavonoids; glycosylation of lignans; sulphonation of phenols; synthesis of carotenoids, diarylnonanoids, flavanones, stilbenes, steroids, quinolones, di- and tri-terpenoids and tannin) were identified in fermented wheatgrass juice using an untargeted liquid chromatography (LC)-mass spectrometry (MS)-matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF)/time-of-flight (TOF) technique. The recombinant P. acidilactici BD16 (alaD+) also supported flavonoid and lignin glycosylation; benzoic acid, hydroxycoumaric acid and quinic acid derivatization; and synthesis of anthraquinones, sterols and triterpenes with therapeutic benefits. The information presented in this manuscript may be utilized to elucidate the importance of Saccharomyces cerevisiae and P. acidilactici BD16 (alaD+) mediated phenolic biotransformations in developing functional food supplements such as fermented wheatgrass juice.
Desirable Properties of Learning Function from Examples

In this paper, we argue that total three desirable properties should be satisfied so that a function to be learned or interpolated from a set of input-output examples can cross all the given examples with minimal oscillations among the examples. As long as the number of given examples exceeds the dimension of example and meanwhile none existing hyper-plane, in real vector space of example’s dimension, passes through all the given examples exactly, we can construct one simple function learning solution, which is expressed as a sum of two terms: one is an example-influence term that consists of the outputs of a number of basis functions and another is a linear term, to allow all the three desirable properties to be satisfied exactly. Experiments show that the solution can simulate both continuous and discontinuous functions even with very sparse given examples.
Anticancer effect of involucrasin A on colorectal cancer cells by modulating the Akt/MDM2/p53 pathway

Colorectal cancer (CRC) is the second leading cause of cancer mortality worldwide; however, there is still a lack of effective clinical anti-CRC agents. Naturally-occurring compounds have been considered a potentially valuable source of new antitumorigenic agents. Involucrasin A, a novel natural molecule, was isolated from Shuteria involucrata (Wall.) Wight & Arn by our team. In the present study, the anticancer activity of involucrasin A in HCT-116 CRC cells was evaluated. Firstly, the anti-proliferative effect of involucrasin A on HCT-116 cells was analyzed by sulforhodamine B and colony formation assays. The results revealed that involucrasin A exhibited a potent inhibitory effect on HCT-116 CRC cell proliferation in vitro. Subsequently, flow cytometry and western blotting indicated that involucrasin A induced apoptosis and upregulated the expression levels of apoptosis-related proteins, such as cleaved-caspase 6 and cleaved-caspase 9, in a dose-dependent manner. Mechanistically, involucrasin A significantly inhibited the phosphorylation of Akt and murine double minute 2 homologue (MDM2), which resulted in increased intracellular levels of p53. This was reversed by exogenous expression of the constitutively active form of Akt. Similarly, either knocking out p53 or knocking down Bax abrogated involucrasin A-induced proliferation inhibition and apoptosis. Together, the present study indicated that involucrasin A exerts antitumorigenic activities via modulating the Akt/MDM2/p53 pathway in HCT-116 CRC cells, and it is worthy of further exploration in preclinical and clinical trials.
Shear Viscosity from Lattice QCD

Understanding of the transport properties of the the quark-gluon plasma is becoming increasingly important to describe current measurements at heavy ion collisions. This work reports on recent efforts to determine the shear viscosity h in the deconfined phase from lattice QCD. The main focus is on the integration of the Wilson flow in the analysis to get a better handle on the infrared behaviour of the spectral function which is relevant for transport. It is carried out at finite Wilson flow time, which eliminates the dependence on the lattice spacing. Eventually, a new continuum limit has to be carried out which sends the new regulator introduced by finite flow time to zero. Also the non-perturbative renormalization strategy applied for the energy momentum tensor is discussed. At the end some quenched results for temperatures up to 4:5Tc are presented.
Untargeted Metabolomics Using UHPLC-HRMS Reveals Metabolic Changes of Fresh-Cut Potato during Browning Process

Surface browning plays a major role in the quality loss of fresh-cut potatoes. Untargeted metabolomics were used to understand the metabolic changes of fresh-cut potato during the browning process. Their metabolites were profiled by ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS). Data processing and metabolite annotation were completed by Compound Discoverer 3.3 software. Statistical analysis was applied to screen the key metabolites correlating with browning process. Fifteen key metabolites responsible for the browning process were putatively identified. Moreover, after analysis of the metabolic causes of glutamic acid, linolenic acid, glutathione, adenine, 12-OPDA and AMP, we found that the browning process of fresh-cut potatoes was related to the structural dissociation of the membrane, oxidation and reduction reaction and energy shortage. This work provides a reference for further investigation into the mechanism of browning in fresh-cut products.
Potential of Optical Spaceborne Sensors for the Differentiation of Plastics in the Environment

Plastics are part of our everyday life, as they are versatile materials and can be produced inexpensively. Approximately 10 Gt of plastics have been produced to date, of which the majority have been accumulated in landfills or have been spread into the terrestrial and aquatic environment in an uncontrolled way. Once in the environment, plastic litter—in its large form or degraded into microplastics—causes several harms to a variety of species. Thus, the detection of plastic waste is a pressing research question in remote sensing. The majority of studies have used Sentinel-2 or WorldView-3 data and empirically explore the usefulness of the given spectral channels for the detection of plastic litter in the environment. On the other hand, laboratory infrared spectroscopy is an established technique for the differentiation of plastic types based on their type-specific absorption bands; the potential of hyperspectral remote sensing for mapping plastics in the environment has not yet been fully explored. In this study, reflectance spectra of the five most commonly used plastic types were used for spectral sensor simulations of ten selected multispectral and hyperspectral sensors. Their signals were classified in order to differentiate between the plastic types as would be measured in nature and to investigate sensor-specific spectral configurations neglecting spatial resolution limitations. Here, we show that most multispectral sensors are not able to differentiate between plastic types, while hyperspectral sensors are. To resolve absorption bands of plastics with multispectral sensors, the number, position, and width of the SWIR channels are decisive for a good classification of plastics. As ASTER and WorldView-3 had/have narrow SWIR channels that match with diagnostic absorption bands of plastics, they yielded outstanding results. Central wavelengths at 1141, 1217, 1697, and 1716 nm, in combination with narrow bandwidths of 10–20 nm, have the highest capability for plastic differentiation.
Development of a Knowledge Graph for Automatic Job Hazard Analysis: The Schema

In the current practice, an essential element of safety management systems, Job Hazard Analysis (JHA), is performed manually, relying on the safety personnel’s experiential knowledge and observations. This research was conducted to create a new ontology that comprehensively represents the JHA knowledge domain, including the implicit knowledge. Specifically, 115 actual JHA documents and interviews with 18 JHA domain experts were analyzed and used as the source of knowledge for creating a new JHA knowledge base, namely the Job Hazard Analysis Knowledge Graph (JHAKG). To ensure the quality of the developed ontology, a systematic approach to ontology development called METHONTOLOGY was used in this process. The case study performed for validation purposes demonstrates that a JHAKG can operate as a knowledge base that answers queries regarding hazards, external factors, level of risks, and appropriate control measures to mitigate risks. As the JHAKG is a database of knowledge representing a large number of actual JHA cases previously developed and also implicit knowledge that has not been formalized in any explicit forms yet, the quality of JHA documents produced from queries to the database is expectedly higher than the ones produced by an individual safety manager in terms of completeness and comprehensiveness.
ADMM-Based Multi-Objective Control Scheme for Mitigating the Impact of High Penetration DER Integration in the Modern Distribution Systems

The high penetration of renewable energy sources in modern distribution networks poses challenges for grid voltage regulation. In this study, a multi-agent distributed voltage control strategy based on the proximal Jacobian alternating direction method of multipliers (PJ-ADMM) is proposed for distribution power systems with a high penetration of photovoltaic (PV) resources coordinated with battery energy storage systems (BESS). In this context, the active and reactive power outputs of the PV are locally optimized through smart inverters to improve the grid voltage with minimum power loss. Uncertainties associated with solar energy generation and load demands are considered in the defined scenarios. This study consists of two phases. In the first phase, the voltage control problem is formulated as an optimization problem to regulate the voltages within an acceptable limit with fast convergence. In the second phase, a coordinated voltage control strategy for smart PV inverters and BESS is proposed to allocate the power capacity of the battery energy storage systems and the active power loss reduction. Finally, the proposed method is tested on modified IEEE 13-bus, 33-bus and 141-bus distribution systems using MATLAB/Simulink and MATPOWER. A comparison of the results of the voltage profiles with and without the control algorithm demonstrated the efficacy, robustness, and scalability of the distributed scheme for voltage improvement and optimal utilization of PV power under different scenarios.
Ranking And Unranking Permutations WithApplications

Permutation theory has many applications in several fields of science and technology and it also has a charm in itself. Mathematica is particularly suitable for writing combinatorial algorithms because it provides many easy-to-use tools for handling lists. Several combinatorial built-in functions which involve permutations and combinations are available as standard add-on Mathematica packages. They are grouped under the name of DiscreteMath and are described by their author Steven Skiena in his book [7]. In this paper we focus on ranking and unranking procedures and we examine and implement alternative algorithms to the RankPermutations and NthPermutations already contained in the above mentioned add-on packages. Moreover we provide some applications of these ranking procedures in different topics such as probability, statistics and elementary calculus. Let /„={(), 1, . , n-\ } be the set of the nonnegative integers smaller than n and let A be a rc-set. We denote the set of all permutations of A by the n! -set:
Heavy oil modeling – a tutorial

Due to the ubiquitous occurrence of heavy oil reserves throughout the world, and the fact that these reserves are becoming an increasingly important source of new petroleum supply, it is important to understand the seismic response of these reservoirs. Although several authors have addressed this problem, the equations shown in their papers are given in different formulations which make a physical understanding of the techniques quite difficult. In this paper, we present a formulation which unifies the notation in these studies and shows how their implementations are equivalent. We then compute the frequency-dependent real and imaginary parts of the complex shear modulus from knowledge of the viscosity and temperature of the heavy oil, for a heavy oil example published in the literature. This also allows us to compute the attenuation curves for heavy oil.
Tackling colourism through storytelling in an online course for public health professionals

Objective: Strategic storytelling can be used to reframe dominant cultural narratives and improve community health outcomes. This pilot study assessed the impact of an original, online 3-week e-course, delivered from November to December 2021, in increasing learners’ knowledge of and concern for the seriousness of skin-shade discrimination and the use of skin-lightening products in India, increasing learners’ understanding of storytelling-based communication techniques for public health promotion, and increasing learners’ intentions to use strategic storytelling for social change. Design, Setting and Method: The course used case-method pedagogy to address colourism and cosmetic skin lightening. Learners (N = 25) completed a pre-course baseline survey on their knowledge and concerns regarding colourism and the use of skin-lightening products, as well as their expectations and interests in taking the course. Following course completion, learners completed a post-webinar survey. The Wilcoxon Signed-Rank test was used to assess differences from pre- to post-course surveys on quantitative items. Open-ended responses were also analysed using qualitative content analysis for recurring themes on learner interest and experience. Results: From pre- to post-course surveys, there were significant improvements in learners’ knowledge of skin shade discrimination and the use of skin-lightening products (p < .05). Learners indicated being more concerned about the seriousness of skin shade discrimination post-course compared to pre-course. Learners also described a positive learning experience and indicated that the e-course enhanced their understanding of strategic storytelling. Conclusion: Findings highlight the importance of an original e-course that uses case-method pedagogy to build knowledge and skills that addresses the impacts of colourism on the health of Indian adolescents and provides new directions for future research on health education interventions that aim to tackle colourism.
The Effect of the Integration of Metacognitive and Motivation Scaffolding Through a Pedagogical Agent on Self- and Co-Regulation Learning

Nowadays, online learning has become commonplace in higher education. Various factors influence the success of online learning. Factors such as low self-regulation and co-regulation of learning skills can affect student engagement and motivation in online learning activities. Therefore, it is essential to provide external support in the online learning process. Pedagogical agents are one solution to increasing self-regulation and co-regulation learning in online learning environments. This study aims to determine the effect of integrating metacognitive and motivation scaffolding support provided through pedagogical agents on self-regulation and co-regulation learning skills. This study uses a mixed-method explanatory sequential approach. A quasi-experimental method of the nonequivalent type (pretest and posttest) control group is used for quantitative data collection, and an in-depth survey is used to analyze qualitative data. The results showed that the learning support provided by pedagogical agents who act as scaffolders using metacognitive and motivation scaffolding integration has a significant impact on increasing students' self-regulation and co-regulation learning skills. Also, the results of qualitative data analysis supported the findings obtained from quantitative data. Research limitations and suggestions for further research are presented at the end of this article.
Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design

Abstract. Numerical models of ocean biogeochemistry are becoming the major tools used to detect and predict the impact of climate change on marine resources and to monitor ocean health. However, with the continuous improvement of model structure and spatial resolution, incorporation of these additional degrees of freedom into fidelity assessment has become increasingly challenging. Here, we propose a new method to provide information on the model predictive skill in a concise way. The method is based on the conjoint use of a k-means clustering technique, assessment metrics, and Biogeochemical-Argo (BGC-Argo) observations. The k-means algorithm and the assessment metrics reduce the number of model data points to be evaluated. The metrics evaluate either the model state accuracy or the skill of the model with respect to capturing emergent properties, such as the deep chlorophyll maximums and oxygen minimum zones. The use of BGC-Argo observations as the sole evaluation data set ensures the accuracy of the data, as it is a homogenous data set with strict sampling methodologies and data quality control procedures. The method is applied to the Global Ocean Biogeochemistry Analysis and Forecast system of the Copernicus Marine Service. The model performance is evaluated using the model efficiency statistical score, which compares the model–observation misfit with the variability in the observations and, thus, objectively quantifies whether the model outperforms the BGC-Argo climatology. We show that, overall, the model surpasses the BGC-Argo climatology in predicting pH, dissolved inorganic carbon, alkalinity, oxygen, nitrate, and phosphate in the mesopelagic and the mixed layers as well as silicate in the mesopelagic layer. However, there are still areas for improvement with respect to reducing the model–data misfit for certain variables such as silicate, pH, and the partial pressure of CO2 in the mixed layer as well as chlorophyll-a-related, oxygen-minimum-zone-related, and particulate-organic-carbon-related metrics. The method proposed here can also aid in refining the design of the BGC-Argo network, in particular regarding the regions in which BGC-Argo observations should be enhanced to improve the model accuracy via the assimilation of BGC-Argo data or process-oriented assessment studies. We strongly recommend increasing the number of observations in the Arctic region while maintaining the existing high-density of observations in the Southern Oceans. The model error in these regions is only slightly less than the variability observed in BGC-Argo measurements. Our study illustrates how the synergic use of modeling and BGC-Argo data can both provide information about the performance of models and improve the design of observing systems.
Strain and Strain Rate Tensor Mapping of Medial Gastrocnemius at Submaximal Isometric Contraction and Three Ankle Angles

Introduction: The aim of this study is to analyze the muscle kinematics of the medial gastrocnemius (MG) during submaximal isometric contractions and to explore the relationship between deformation and force generated at plantarflexed (PF), neutral (N) and dorsiflexed (DF) ankle angles. Method: Strain and Strain Rate (SR) tensors were calculated from velocity-encoded magnetic resonance phase-contrast images in six young men acquired during 25% and 50% Maximum Voluntary Contraction (MVC). Strain and SR indices as well as force normalized values were statistically analyzed using two-way repeated measures ANOVA for differences with force level and ankle angle. An exploratory analysis of differences between absolute values of longitudinal compressive strain (Eλ1) and radial expansion strains (Eλ2) and maximum shear strain (Emax) based on paired t-test was also performed for each ankle angle. Results: Compressive strains/SRs were significantly lower at 25%MVC. Normalized strains/SR were significantly different between %MVC and ankle angles with lowest values for DF. Absolute values of Eλ2 and Emax were significantly higher than Eλ1 for DF suggesting higher deformation asymmetry and higher shear strain, respectively. Conclusions: In addition to the known optimum muscle fiber length, the study identified two potential new causes of increased force generation at dorsiflexion ankle angle, higher fiber cross-section deformation asymmetry and higher shear strains.
Boundedness in a parabolic-parabolic quasilinear chemotaxis system with logistic source

This paper deals with the global existence and boundedness of the solutions for the chemotaxis system with logistic source \begin{eqnarray*} \left\{ \begin{array}{llll} u_t=\nabla\cdot(\phi(u)\nabla u)-\nabla\cdot(\varphi(u)\nabla v)+f(u),\quad &x\in \Omega,\quad t>0,\\ v_t=\Delta v-v+u,\quad &x\in\Omega,\quad t>0,\\ \end{array} \right. \end{eqnarray*} under homogeneous Neumann boundary conditions in a convex smooth bounded domain $\Omega\subset \mathbb{R}^n (n\geq2),$ with non-negative initial data $u_0\in C^0(\overline{\Omega})$ and $v_0\in W^{1,\theta}{(\Omega)}$ (with some $\theta>n$). The nonlinearities $\phi$ and $\varphi$ are assumed to generalize the prototypes \begin{eqnarray*} \phi(u)=(u+1)^{-\alpha},\,\,\,\,\,\, \varphi(u)=u(u+1)^{\beta-1} \end{eqnarray*} with $\alpha\in \mathbb{R}$ and $\beta\in \mathbb{R}$. $f(u)$ is a smooth function generalizing the logistic function \begin{eqnarray*} f(u)=ru-bu^\gamma,\,\,\,\,\,\, u\geq0,\,\,\text{with}\,\, r\geq0,\,\,b>0\,\,\text{and}\,\,\gamma>1. \end{eqnarray*} It is proved that the corresponding initial-boundary value problem possesses a unique global classical solution that is uniformly bounded provided that some technical conditions are fulfilled.