Miracle-dz/UniFAR-FTUs huggingface dataset:
Techno-economic assessment of Ni removal from industrial wastewater by electrocoagulation using rectangular aluminium electrodes

The present research focuses on the removal of nickel Ni(II) from synthetic and industrial waste- water using rectangular aluminium electrodes. The main effect of electrocoagulation (EC) parameters to remove heavy metals in a batch electrolytic reactor was evaluated and the characteristics of the EC sludge were investigated to understand the behaviour of nickel during EC. The electrocoagulation process was applied to assess the effect of electrochemical parameters such as: initial pH (pH i ), current density ( j ), electrolyte concentration [NaCl], electrolysis time t EC and connection mode on removal efficiency of Ni(II), energy consumption, flow structure and treatment cost. The results indicated that maximum nickel removal was obtained with a bipolar connection, initial pH = 5.0, current density j = 1.388 mA cm –2 , electrolysis time t EC = 30 min and [NaCl] = 1.5 g L –1 . At optimal conditions, nickel removal reached over 95.51% with an energy consumption of barely 0.195 kWh m –3 . Once electrocoagulation performance was determined, economic treatment cost of the process was evaluated. In this way, a useful economic feasibility indicator is obtained, and it has been possible to show the effectiveness of this process in the treatment of industrial waste water with a total removal of Ni(II) and a low treatment cost. In the light of these results, this method promises interesting industrial applications.
Emotions in Crisis Coverage: How UK News Media Used Fear Appeals to Report on the Coronavirus Crisis

During crises, journalists rely on emotional appeals to alert the public. This includes fear appeals, i.e., journalistic depictions of threats and measures against them. Focusing on the coronavirus crisis, this study analyzes the prevalence of fear appeals in journalistic news, differences between outlets, and changes over time. It employs a manual content analysis of UK online news between January and May 2020 (N = 1048). Results indicate that, during the early phases of the coronavirus pandemic, journalists relied heavily on fear-inducing messages by emphasizing threats related to COVID-19 and, though to a lesser degree, measures against these threats. Besides differences between tabloids and quality outlets, we find that fear-inducing content decreased before the UK itself became most affected, indicating that coverage served a warning function rather than mirroring national affectedness. Overall, the study illustrates that fear appeals are common in coverage of crises, where they enable journalists to take on the role of public mobilizers and facilitators of crises response strategies, for instance by governments.
Recurrent Space-time Graphs for Video Understanding

Learning in the space-time domain remains a very challenging problem in machine learning and computer vision. Current computational models for understanding spatio-temporal visual data are heavily rooted in the classical single-image based paradigm. It is not yet well understood how to integrate information in space and time into a single, general model. We propose a neural graph model, recurrent in space and time, suitable for capturing both the local appearance and the complex higher-level interactions of different entities and objects within the changing world scene. Nodes and edges in our graph have dedicated neural networks for processing information. Nodes operate over features extracted from local parts in space and time and previous memory states. Edges process messages between connected nodes at different locations and spatial scales or between past and present time. Messages are passed iteratively in order to transmit information globally and establish long range interactions. Our model is general and could learn to recognize a variety of high level spatio-temporal concepts and be applied to different learning tasks. We demonstrate, through extensive experiments and ablation studies, that our model outperforms strong baselines and top published methods on recognizing complex activities in video. Moreover, we obtain state-of-the-art performance on the challenging Something-Something human-object interaction dataset.
circMTND5 Participates in Renal Mitochondrial Injury and Fibrosis by Sponging MIR6812 in Lupus Nephritis

Recent studies have focused on nuclear-encoded circular RNAs (circRNAs) in kidney diseases, but little is known about mitochondrial circRNAs. Differentially expressed circRNAs were analyzed by RNA deep sequencing from lupus nephritis (LN) biopsies and normal human kidneys. In LN renal biopsies, the most downregulated circRNA was circMTND5, which is encoded in the mitochondrial genome. We quantitated circMTND5 by qPCR and localized by fluorescence in situ hybridization (FISH). Mitochondrial abnormalities were identified by electron microscopy. The expression of mitochondrial genes was decreased, and the expression of profibrotic genes was increased on qPCR and immunostaining. RNA binding sites for MIR6812 and circMTND5 were predicted. MIR6812 expression was increased by FISH and qPCR. In HK-2 cells and its mitochondrial fraction, the role of circMTND5 sponging MIR6812 was assessed by their colocalization in mitochondria on FISH, RNA immunoprecipitation, and RNA pulldown coupled with luciferase reporter assay. circMTND5 knockdown upregulated MIR6812, decreased mitochondrial functional gene expression, and increased profibrotic gene expression. Overexpression of circMTND5 reversed these effects in hTGF-β stimulated HK-2 cells. Similar effects were observed in HK-2 cells with overexpression and with knockdown of MIR6812. We conclude that circMTND5 alleviates renal mitochondrial injury and kidney fibrosis by sponging MIR6812 in LN.
Characterization of Resistance and Virulence of Pasteurella multocida Isolated from Pet Cats in South China

Pasteurella multocida, one of the major zoonotic pathogens, may cause localized cellulitis, bacteremia, septic shock, and other symptoms in people. Accidental bites or scratches in close contact between humans and cats are one of the causes of P. multocida infection in humans. The prevalence of diseases due to P. multocida in humans may be rising as a result of the popularity of cat cafes in China. However, the epidemiology of P. multocida in cat-themed cafes in South China is yet to be reported. P. multocida in 92 healthy cats from four cafes with pet-cat themes was examined in their tonsils and oral cavities. The antibiotic susceptibility of each isolate was evaluated by using the disk-susceptibility testing method. The 19 P. multocida were selected for whole-genome sequencing (WGS), together with the genome data of eight previously described clinical strains isolated from humans, and the analysis of antimicrobial resistance (AMR) determinants, capsular genotyping, MLST genotyping, and virulence gene profiles was carried out. The results showed that 48.91% of cats (45/90) were positive for P. multocida. All isolated P. multocida stains were highly resistant to erythromycin (15 μg) (100%) and nonsensitive to fluoroquinolones (5 μg) (37.38%), while they were all susceptible to penicillin (10 untis), tetracycline (30 μg), doxycycline (30 μg), and chloramphenicol (30 μg). According to WGS analysis, those with the gyrA resistance gene were all insensitive to fluoroquinolone antibiotics. Virulence gene profiles showed that the genes pfhA, nanH, and plpB were practically all present in cats compared to humans. To conclude, increased antibiotic resistance, along with virulence factors, complicates the treatment of P. multocida infection. Thus, clinical treatment for P. multocida infection should be performed more cautiously.
Impact on the tensor-to-scalar ratio of incorrect Galactic foreground modelling

A key goal of many cosmic microwave background (CMB) experiments is the detection of gravitational waves, through their B-mode polarization signal at large scales. To extract such a signal requires modelling contamination from the Galaxy. Using the Planck experiment as an example, we investigate the impact of incorrectly modelling foregrounds on estimates of the polarized CMB, quantified by the bias in tensor-to-scalar ratio r, and optical depth ? �. We use a Bayesian parameter estimation method to estimate the CMB, synchrotron and thermal dust components from simulated observations spanning 30-353 GHz, starting from a model that fits the simulated data, returning r < 0.03 at 95 per cent confidence for an r = 0 model and r = 0.09 �� 0.03 for an r = 0.1 model. We then introduce a set of mismatches between the simulated data and assumed model. Including a curvature of the synchrotron spectral index with frequency, but assuming a power-law model, can bias r high by ��1? � (? �r �� 0.03). A similar bias is seen for thermal dust with a modified blackbody frequency dependence, incorrectly modelled as a power law. If too much freedom is allowed in the model, for example, fitting for spectral indices in 3�? pixel over the sky with physically reasonable priors, we find that r can be biased up to ��3? � high by effectively setting the indices to the wrong values. Increasing the signal-to-noise ratio by reducing parameters, or adding additional foreground data, reduces the bias. We also find that neglecting a ��1 per cent polarized free-free or spinning dust component has a negligible effect on r. These tests highlight the importance of modelling the foregrounds in a way that allows for sufficient complexity while minimizing the number of free parameters.
Phonons, pions and quasi-long-range order in spatially modulated chiral condensates

We investigate low-energy fluctuations in the real kink crystal phase of dense quark matter within the Nambu--Jona-Lasinio model. The modulated chiral condensate breaks both the translational symmetry and chiral symmetry spontaneously, which leads to the appearance of phonons and pions that are dominant degrees of freedom in the infrared. Using the Ginzburg-Landau expansion near the Lifshitz point, we derive elastic free energies for phonons and pions in dependence on the temperature and chemical potential. We show that the one-dimensional modulation is destroyed by thermal fluctuations of phonons at nonzero temperature, and compute the exponent that characterizes the anisotropic algebraic decay of quasicondensate correlations at long distance. We also estimate finite-volume effects on the stability of the real kink crystal and briefly discuss the possibility of its existence in neutron stars.
Agroecosystem model simulations reveal spatial variability in relative productivity in biomass sorghum and maize in Iowa, USA

Biomass sorghum (Sorghum bicolor L. Moench) is an annual C4 grass that has emerged as a candidate bioenergy crop but has not been widely grown in the United States. Corn (Zea mays L.), another annual C4 grass, has been produced on a large scale in the United States for biofuels. Iowa leads the nation in both corn and ethanol production. The high productivity of corn in Iowa creates the research question: could biomass sorghum be as or more productive than corn in the state in terms of bioenergy? Efforts to use crop models to fill the gaps left by field experimentation on biomass sorghum have also been limited thus far. To address our research question, we collected biophysical data on biomass sorghum grown in Iowa for two growing seasons, used them to develop a biomass sorghum module in an agroecosystem model (Agro‐IBIS), and predict the potential performance of biomass sorghum across Iowa compared to maize. Despite dry conditions in 2019 and 2020, average biomass sorghum yields were 17.20 Mg ha−1. By comparison, average corn aboveground biomass was higher in 2020 (22.02 Mg ha−1). Soil cores indicated average belowground biomass of 1.46 Mg ha−1, with roots concentrated near the surface (73% of biomass above 50 cm in a 1 m core). When biomass sorghum model parameters were calibrated with measured values, model output was in close agreement with measured biomass (slope = 0.932, R2 = 0.91) and evapotranspiration (slope = 0.757, R2 = 0.64). Subsequent regional simulations revealed a notable latitudinal gradient in biomass sorghum yield, with a strong linear relationship between yield and seasonal growing degree‐days (R2 = 0.89). When these yields were compared to simulated corn aboveground biomass yields, only 3.4% of the state had biomass sorghum yields that were significantly higher than corn. This number was reduced to 0.3% when comparing the crops in terms of energy ethanol yield. Thus, we conclude biomass sorghum must be improved to be competitive with corn as an annual biofuel crop in Iowa. This study provides a baseline against which to compare advancements in sorghum breeding for biomass and stress tolerance in Iowa.
Nuclear star clusters

We review the current knowledge about nuclear star clusters (NSCs), the spectacularly dense and massive assemblies of stars found at the centers of most galaxies. Recent observational and theoretical works suggest that many NSC properties, including their masses, densities, and stellar populations, vary with the properties of their host galaxies. Understanding the formation, growth, and ultimate fate of NSCs, therefore, is crucial for a complete picture of galaxy evolution. Throughout the review, we attempt to combine and distill the available evidence into a coherent picture of NSC evolution. Combined, this evidence points to a clear transition mass in galaxies of ∼109M⊙\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 10^9\,M_\odot$$\end{document} where the characteristics of nuclear star clusters change. We argue that at lower masses, NSCs are formed primarily from globular clusters that inspiral into the center of the galaxy, while at higher masses, star formation within the nucleus forms the bulk of the NSC. We also discuss the co-existence of NSCs and central black holes, and how their growth may be linked. The extreme densities of NSCs and their interaction with massive black holes lead to a wide range of unique phenomena including tidal disruption and gravitational-wave events. Finally, we review the evidence that many NSCs end up in the halos of massive galaxies stripped of the stars that surrounded them, thus providing valuable tracers of the galaxies’ accretion histories.
SALT LONG-SLIT SPECTROSCOPY OF LUMINOUS OBSCURED QUASARS: AN UPPER LIMIT ON THE SIZE OF THE NARROW-LINE REGION?

We present spatially resolved long-slit spectroscopy from the Southern African Large Telescope to examine the spatial extent of the narrow-line regions (NLRs) of a sample of eight luminous obscured quasars at 0.10 < z < 0.43. Our results are consistent with an observed shallow slope in the relationship between NLR size and L[O iii], which has been interpreted to indicate that NLR size is limited by the density and ionization state of the NLR gas rather than the availability of ionizing photons. We also explore how the NLR size scales with a more direct measure of instantaneous active galactic nucleus power using mid-IR photometry from the Wide Field Infrared Explorer, which probes warm to hot dust near the central black hole and so, unlike [O iii], does not depend on the properties of the NLR. Using our results as well as samples from the literature, we obtain a power-law relationship between NLR size and L8 μm that is significantly steeper than that observed for NLR size and L[O iii]. We find that the size of the NLR goes approximately as , as expected from the simple scenario of constant-density clouds illuminated by a central ionizing source. We further see tentative evidence for a flattening of the relationship between NLR size and L8 μm at the high-luminosity end, and propose that we are seeing a limiting NLR size of 10–20 kpc, beyond which the availability of gas to ionize becomes too low. We find that , consistent with a picture in which the L[O iii] is dependent on the volume of the NLR. These results indicate that high-luminosity quasars have a strong effect in ionizing the available gas in a galaxy.
GENERALIZATION OF THE MIXED TOPOLOGY

Wiweger [3] has introduced a new topology, in a linear spacc $X\backslash \not\in it1_{1}$ two topologics $\tau$ “ and $\tau$ , by the form of neighbourhood $\cup\vee(\underline{\backslash \prime}(U_{\ell}^{*}\cap iU))\backslash vheI^{\cdot}eU_{\iota}^{! }$ and $U$ are neighbourhoods of $0$ in the topologies $\tau and\tau$ lespectively $--1$ i and it is, in tlte case of lincar normed spacc, idcntical with $\tau$ on thc $\taubo$ undcd $sul\lrcorner scts$ , and is called the mixed topology associatcd with $\tau^{A}$ and $\tau$ . Persson [2] has madc an attempt to gcncralizc it in a locitlly convcx linear topological space by saying that it is thc finest locally $CO11\iota\prime c\backslash $ topology on
SPIDER. V. MEASURING SYSTEMATIC EFFECTS IN EARLY-TYPE GALAXY STELLAR MASSES FROM PHOTOMETRIC SPECTRAL ENERGY DISTRIBUTION FITTING

We present robust statistical estimates of the accuracy of early-type galaxy stellar masses derived from spectral energy distribution (SED) fitting as functions of various empirical and theoretical assumptions. Using large samples consisting of ∼40,000 galaxies from the Sloan Digital Sky Survey (SDSS; ugriz), of which ∼5000 are also in the UKIRT Infrared Deep Sky Survey (YJHK), with spectroscopic redshifts in the range 0.05 ⩽ z ⩽ 0.095, we test the reliability of some commonly used stellar population models and extinction laws for computing stellar masses. Spectroscopic ages (t), metallicities (Z), and extinctions (AV) are also computed from fits to SDSS spectra using various population models. These external constraints are used in additional tests to estimate the systematic errors in the stellar masses derived from SED fitting, where t, Z, and AV are typically left as free parameters. We find reasonable agreement in mass estimates among stellar population models, with variation of the initial mass function and extinction law yielding systematic biases on the mass of nearly a factor of two, in agreement with other studies. Removing the near-infrared bands changes the statistical bias in mass by only ∼0.06 dex, adding uncertainties of ∼0.1 dex at the 95% CL. In contrast, we find that removing an ultraviolet band is more critical, introducing 2σ uncertainties of ∼0.15 dex. Finally, we find that the stellar masses are less affected by the absence of metallicity and/or dust extinction knowledge. However, there is a definite systematic offset in the mass estimate when the stellar population age is unknown, up to a factor of 2.5 for very old (12 Gyr) stellar populations. We present the stellar masses for our sample, corrected for the measured systematic biases due to photometrically determined ages, finding that age errors produce lower stellar masses by ∼0.15 dex, with errors of ∼0.02 dex at the 95% CL for the median stellar age subsample.
Towards the human nasal microbiome: Simulating D. pigrum and S. aureus

The human nose harbors various microbes that decisively influence the wellbeing and health of their host. Among the most threatening pathogens in this habitat is Staphylococcus aureus. Multiple epidemiological studies identify Dolosigranulum pigrum as a likely beneficial bacterium based on its positive association with health, including negative associations with S. aureus. Carefully curated GEMs are available for both bacterial species that reliably simulate their growth behavior in isolation. To unravel the mutual effects among bacteria, building community models for simulating co-culture growth is necessary. However, modeling microbial communities remains challenging. This article illustrates how applying the NCMW fosters our understanding of two microbes’ joint growth conditions in the nasal habitat and their intricate interplay from a metabolic modeling perspective. The resulting community model combines the latest available curated GEMs of D. pigrum and S. aureus. This uses case illustrates how to incorporate genuine GEM of participating microorganisms and creates a basic community model mimicking the human nasal environment. Our analysis supports the role of negative microbe–microbe interactions involving D. pigrum examined experimentally in the lab. By this, we identify and characterize metabolic exchange factors involved in a specific interaction between D. pigrum and S. aureus as an in silico candidate factor for a deep insight into the associated species. This method may serve as a blueprint for developing more complex microbial interaction models. Its direct application suggests new ways to prevent disease-causing infections by inhibiting the growth of pathogens such as S. aureus through microbe–microbe interactions.
The Effect of Carbon Price Volatility on Firm Green Transitions: Evidence from Chinese Manufacturing Listed Firms

Accelerating the promotion of the green transition can help to achieve high-quality development in manufacturing industries. In terms of policies that encourage the transition to green production, carbon trading is a direct and effective means of achieving this goal, and the carbon price is an important regulator in trading. Normally, firms respond to carbon prices by making three behavioral choices: production restrictions, pollution reduction, and the technological transition to green production. This study examines the effect of carbon price volatility on the decision to conduct green production, i.e., transforming to sustainable technologies and processes. In addition, this paper also investigates whether organizational resource slack and organizational technical standards moderate the relationship between the carbon price volatility and firms’ green transitions. The results suggest that a steadily increasing carbon price will motivate firms to make a green transition, but if the carbon price is volatile, firms will be reluctant to make a green transition. This tendency to make a green transition is stronger when firms have resource slack and have implemented green technical standards. The findings provide empirical evidence and policy implications regarding how manufacturing firms can accelerate their green transition.
Computer Vision and Deep Learning for Precision Viticulture

During the last decades, researchers have developed novel computing methods to help viticulturists solve their problems, primarily those linked to yield estimation of their crops. This article aims to summarize the existing research associated with computer vision and viticulture. It focuses on approaches that use RGB images directly obtained from parcels, ranging from classic image analysis methods to Machine Learning, including novel Deep Learning techniques. We intend to produce a complete analysis accessible to everyone, including non-specialized readers, to discuss the recent progress of artificial intelligence (AI) in viticulture. To this purpose, we present work focusing on detecting grapevine flowers, grapes, and berries in the first sections of this article. In the last sections, we present different methods for yield estimation and the problems that arise with this task.
3D gravity with propagating torsion: The AdS sector

We study the general parity-preserving model of three-dimensional gravity with propagating torsion, with a focus on its nonlinear dynamics in the AdS sector. The model is shown to posses the black hole with torsion as a vacuum solution, provided we adopt certain restrictions on its coupling constants. The canonical analysis in the AdS asymptotic region yields the conserved charges of the black hole and the central charges of the asymptotic conformal symmetry.