Miracle-dz/UniFAR-FTUs huggingface dataset:
Space and Place

The Fourth Gospel uses space to arrange its narrative and uses its narrative to represent Johannine space and experience. The spaces alluded to in John are full of contestation and serve as identity markers. By Nathanael asking if anything good can come from Nazareth, he represents Nazareth and its inhabitants as insignificant. Yet, by Jesus seeing in Nathanael, not a Galilean but an Israelite, Jesus subverts the regional stereotypes operative in Nathanael and John’s narrative world but maybe reflective of John’s concrete experience. By denying the sacred places of Jerusalem and Samaria, and proposing worship in spirit and truth, the Johannine Jesus is theologically and socially located on the margins of sacred place but at the centre of sacred presence. When the Johannine Jesus sees the arrival of the Greeks as the ‘hour of glory’ he subverts diaspora existence and marginalises the centre, Palestine. If the ultimate place to access God in John is utopia, then this is, no place. Key Terms: 70 CE; Bible; Diaspora; Exile; First space; Focal space; Fourth Gospel; Galilee; Galileans; Gospel of John; Greeks; John; Johannine; Johannine community; Judea; Judeans; Mount Gerizim; Narrative; Palestine; Place; Place and space; Replacement motif; Restoration; Ritualisation; Samaritans; Second space; Second Temple; Supercessionism; Space; Temple; Third space; Utopia.
Characterization of Yeasts Isolated from Parmigiano Reggiano Cheese Natural Whey Starter: From Spoilage Agents to Potential Cell Factories for Whey Valorization

Whey is the main byproduct of the dairy industry and contains sugars (lactose) and proteins (especially serum proteins and, at lesser extent, residual caseins), which can be valorized by the fermentative action of yeasts. In the present study, we characterized the spoilage yeast population inhabiting natural whey starter (NWS), the undefined starter culture of thermophilic lactic acid bacteria used in Parmigiano Reggiano (PR) cheesemaking, and evaluated thermotolerance, mating type, and the aptitude to produce ethanol and bioactive peptides from whey lactose and proteins, respectively, in a selected pool of strains. PCR-RFLP assay of ribosomal ITS regions and phylogenetic analysis of 26S rDNA D1/D2 domains showed that PR NWS yeast population consists of the well-documented Kluyveromyces marxianus, as well as of other species (Saccharomyces cerevisiae, Wickerhamiella pararugosa, and Torulaspora delbrueckii), with multiple biotypes scored within each species as demonstrated by (GTG)5-based MSP-PCR. Haploid and diploid K. marxianus strains were identified through MAT genotyping, while thermotolerance assay allowed the selection of strains suitable to grow up to 48 °C. In whey fermentation trials, one thermotolerant strain was suitable to release ethanol with a fermentation efficiency of 86.5%, while another candidate was able to produce the highest amounts of both ethanol and bioactive peptides with potentially anti-hypertensive function. The present work demonstrated that PR NWS is a reservoir of ethanol and bioactive peptides producer yeasts, which can be exploited to valorize whey, in agreement with the principles of circularity and sustainability.
Structure design, fabrication and property investigation of water-based polyesters with notable surface hydrophilicity

Environmentally friendly waterborne polyesters (WPEs) were obtained by copolymerization of diethylene glycol (DEG), isophthalic acid (IPA) and 5-sulfoisophthalic acid monosodium salt (5-SSIPA). The effects of the 5-SSIPA content on the properties of the resultant copolymers, including dispersity, crystallinity, dynamic thermo-mechanical properties, thermal stability and surface properties, were investigated. The 5-SSIPA contents in the intended polymers were determined by the peak areas of proton nuclear magnetic resonance (1H-NMR) spectra. Transmission electron microscopy (TEM), electrophoretic light scattering (ELS) and dynamic light scattering (DLS) were used to characterize the dispersion and stability performance of waterborne polyester solutions. The crystallinity of the WPEs was determined using X-ray diffraction (XRD) and differential scanning calorimetry (DSC). As the 5-SSIPA content increased, the glass-transition temperature (Tg) of the WPEs increased significantly according to dynamic mechanical analysis (DMA), the thermal stability of the WPEs was deteriorated according to thermogravimetric analysis (TGA), surface roughness did not change according to atomic force microscopy (AFM), and their solid surface tension was increased from 28.47 to 32.90 mJ m−2 based on static contact angle measurements. Water contact angle (WCA) measurements proved that WPE dispersions could be used for enhancing the hydrophilicity of the PET surface.
Fine‐tuning biodiversity assessments: A framework to pair eDNA metabarcoding and morphological approaches

Accurate quantification of biodiversity can be demanding and expensive. Although environmental DNA (eDNA) metabarcoding can facilitate biodiversity assessments through non‐invasive, cost‐efficient and rapid surveys, the approach struggles to outperform traditional morphological approaches in providing reliable quantitative estimates for surveyed species (e.g. abundance and biomass). We present an integrated methodology for improving biodiversity surveys that pairs eDNA metabarcoding with morphological data, following a series of taxonomic and geographical filters. We demonstrate its power by applying it to a new spatiotemporal dataset generated on an Iberian‐wide distributed aquatic mesocosm infrastructure that spans a wide biogeographical gradient. By building upon the strengths that these two approaches offer, our framework improved taxonomic resolution for 30% of the taxa and enabled species’ traits (e.g. body size) and abundance to be assigned to 85% of the taxa in hybrid datasets. These results indicate that eDNA‐based assessments can complement, but not always replace, conventional approaches. Integrating conventional and modern eDNA metabarcoding approaches, already available in the ecologist's toolbox, will greatly enhance biodiversity assessments.
The Detection of Open and Leakage Faults for Prebond TSV Test Based on Weak Current Source

During the manufacturing process of three-dimensional integrated circuits (3-D ICs), many defects may occur in through-silicon vias (TSVs). These defects affect the integrity of the signal passing through TSVs, therefore detecting these defects in the early production stage is crucial. This article proposed a built-in-self-test (BIST) method with a simple test structure and easily implemented fault detection process. Due to the fact that the defects in TSVs influence the charge/discharge speed of TSVs’ equivalent capacitance, a weak current source is designed as the central part of the proposed test structure, which can measure the TSVs’ charge/discharge speed and quantify it using digital values. The effectiveness and robustness of the proposed method is validated by HSPICE simulation. The minimum measurable fault, test time, and test circuit area are also assessed in this article. The simulation results show that the method this article proposed can detect weaker faults, compared with the traditional test methods.
ERUO: a spectral processing routine for the MRR-PRO

Abstract. The Micro Rain Radar (MRR) PRO is a K-band Doppler weather radar, using frequency modulated continuous wave (FMCW) signals, developed by Metek Meteorologische Messtechnik GmbH (Metek) as successor to the MRR-2. Benefiting from four datasets collected during two field campaigns in Antarctica and Switzerland, we developed a processing library for snowfall measurements, named ERUO (Enhancement and Reconstruction of the spectrUm for the MRR-PRO), with a two-fold objective. Firstly, the proposed method addresses a series of issues plaguing the radar variables, which include interference lines, power drops at the extremes of the Doppler spectrum and abrupt cutoff of the transfer function. Secondly, the algorithm aims to improve the quality of the final variables, by lowering the minimum detectable equivalent attenuated reflectivity factor and extending the valid Doppler velocity range through antialiasing. The performance of the algorithm has been tested against the measurements of a co-located W-band Doppler radar. Information from a close-by X-Band Doppler dual-polarization radar has been used to exclude unsuitable radar volumes from the comparison. Particular attention has been dedicated to verify the estimation of the meteorological signal in the spectra covered by interferences.
The Devils

Undoubtedly the most notorious title in director Ken Russell's controversial filmography, The Devils (1973) caused a real furore on its initial theatrical release, only to largely disappear for many years. This book considers the film's historical context, as the timing of the first appearance of The Devils is of particular importance, its authorship and adaptation (Russell's auteur reputation aside, the screenplay is based on John Whiting's 1961 play of the same name, which was in turn based on Aldous Huxley's 1952 book The Devils of Loudun), and its generic hybridity. The book goes on to examine the themes prevalent in the film—this is the only film of Russell's which the director considered to be political—and considers the representation of gender and sexuality, gender fluidity, and how sex and religion clash to interesting and controversial effect. The book concludes by revisiting the film's censorship travails and the various versions of The Devils that have appeared on both big and small screens, and the film's legacy and influence.
Passive acoustic monitoring reveals the role of habitat affinity in sensitivity of sub‐tropical East Asian bats to fragmentation

Hydropower infrastructure represents a major driver of habitat loss and insular fragmentation worldwide, mostly across the tropics and sub‐tropics. Despite growing evidence of dam‐induced impacts on biodiversity, the effects of insular habitat fragmentation on species assemblages remain poorly understood, particularly for East Asian vertebrates. Here, we assess how insectivorous bats respond to forest fragmentation in Thousand Island Lake, a mega‐hydroelectric dam in East China. Bat assemblages were surveyed across 36 land‐bridge islands of different sizes and degrees of isolation, using AudioMoth recorders. Echolocation calls were classified into sonotypes, each corresponding to either single or multiple species, which were further classified according to their habitat affinities into forest or open‐space foragers. Based on 22 875 five‐min recordings from 108 detector‐nights, we recorded 15 bat sonotypes, eight of which we classified as forest sonotypes (2329 bat passes) and seven as open‐space sonotypes (52 277 bat passes). Overall, sonotype richness increased with island area, but only above a certain threshold (34 ha). Habitat affinity played an important role in ensemble‐level responses to fragmentation; forest sonotype richness increased with island area, whereas open‐space sonotype activity was higher in more isolated islands. Our results highlight the relevance of particularly large fragments (>1000 ha) to maintain area‐sensitive forest bat species. However, islands below 34 ha in size and those more isolated from the mainland are also of conservation value as they, correspondingly, harbour a variable (but substantial) number of species and concentrate higher activity of open‐space foragers. These findings further demonstrate that acoustic sampling methods, as the one presented here, are able to provide key information for evidence‐based policies aimed at halting the ongoing wave of dam‐induced biodiversity loss.
Perceived Security and Trust in Electronic Payment Systems: How They Affect the Decision to Use EPS During the COVID-19 Pandemic

Research aims: This study is intended to determine the influence of perceived security and trust on the decision to use digital payment systems during the COVID-19 pandemic.Design/Methodology/Approach: The type of data used in this study was primary data, which was collected using an online survey. Sample used in this study determined by purposive sampling method. The information collected was handled and analyzed using SEM-PLS.Research findings: This study shows the results that the presence of technical protection explicitly affects the perception of security and trust significantly. In addition, security also greatly affects an individual's confidence in the use of digital payment systems. However, of the various findings made in this study, trust is the only one that influences the choice in using EPS.Theoretical contribution/Originality: During this pandemic Covid-19, limited studies talk about consumers’ perceptions instead of technical protection of digital payment in detail. Meanwhile, consumers' security is the thing that needs to be studied further to create a comprehensive study result.Practitioner/Policy implication: Results of this study give some implications for the EPS providers to complete and develop a secure EPS system for users, especially in this pandemic era when the EPS users increase and people’s mobility is restricted in some areas.Research limitation/Implication: The implication of this research is to emphasize the importance of one's knowledge regarding risks when using an electronic payment system. It is because the use of EPS in the pandemic era is unavoidable. Therefore, not only providers must improve their security systems, but users must also be aware of the EPS risks and security. Nevertheless, the limitation of this study is that it only used samples in Indonesia; maybe the results will be different when applied in other countries with better EPS security systems.
Models@Runtime: The Development and Re-Configuration Management of Python Applications Using Formal Methods

Models@runtime (models at runtime) are based on computation reflection. Runtime models can be regarded as a reflexive layer causally connected with the underlying system. Hence, every change in the runtime model involves a change in the reflected system, and vice versa. To the best of our knowledge, there are no runtime models for Python applications. Therefore, we propose a formal approach based on Petri Nets (PNs) to model, develop, and reconfigure Python applications at runtime. This framework is supported by a tool whose architecture consists of two modules connecting both the model and its execution. The proposed framework considers execution exceptions and allows users to monitor Python expressions at runtime. Additionally, the application behavior can be reconfigured by applying Graph Rewriting Rules (GRRs). A case study using Service-Level Agreement (SLA) violations is presented to illustrate our approach.
pH and Reactive Oxygen Species‐Sequential Responsive Nano‐in‐Micro Composite for Targeted Therapy of Inflammatory Bowel Disease

Oxidative stress and abnormally high levels of reactive oxygen species (ROS) play an essential role in the pathogenesis and progression of inflammatory bowel disease (IBD). Oxidation‐responsive nanoparticles (NPs) are formulated from a phenylboronic esters‐modified dextran (OxiDEX) that degrades selectively in response to hydrogen peroxide (H2O2). OxiDEX NPs are coated with chitosan and encapsulated in a pH‐sensitive polymer to produce nano‐in‐micro composites. The microparticles are spherical with homogeneous particle size (53 ± 3 µm) and maintain integrity at acidic pH, preventing the premature release of the NPs in gastric conditions. The degradation of NPs is highly responsive to the level of H2O2, and the release of the drug is sustained in the presence of physiologically relevant H2O2 concentrations. The presence of chitosan on the particles surface significantly enhances NPs stability in intestinal pH and their adhesion on the intestinal mucosa. Compared to a traditional enteric formulation, this formulation shows tenfold decreased drug permeability across C2BBe1/HT29‐MTX cell monolayer, implying that lower amount of drug would be absorbed to the blood stream and, therefore, limiting the undesired systemic side effects. Based on these results, a successful nano‐in‐micro composite for targeted therapy of IBD is obtained by combination of the responsiveness to pH and ROS.
CFD Prediction of Ship Seakeeping and Slamming Behaviors of a Trimaran in Oblique Regular Waves

The main hull encounters waves at first and causes waves to break, when trimarans are subject to the slamming in head waves. At this moment, emergence phenomena of side hulls will not occur. Thus, the slamming study of trimarans in oblique waves presents further practical significance. In this study, a CFD method is used for trimaran seakeeping and slamming analysis. An overset grid technique is adopted to simulate ship motions in waves. Firstly, to further verify the present method, a series of verification and validation studies is conducted. Then, the motion responses and slamming pressure with different control parameters, such as forward speed and ship heading angle, are calculated and discussed. The comparative results indicate that the seakeeping and slamming behaviors of trimarans differ significantly from those of conventional monohull ships. Finally, severe bow slamming and green water in oblique waves are also observed and investigated, which should be given enough attention during ship design and evaluation.
EEG-Based Emotion Recognition of Deaf Subjects by Integrated Genetic Firefly Algorithm

In recent years, many researchers have explored different methods to obtain discriminative features for electroencephalogram-based (EEG-based) emotion recognition, but a few studies have been investigated on deaf subjects. In this study, we have established a deaf EEG emotion dataset, which contains three kinds of emotion (positive, neutral, and negative) with 15 subjects. Ten kinds of time–frequency domain features and eleven kinds of nonlinear dynamic system features were extracted from the EEG signals. To obtain the optimal feature combination and optimal classifier, an integrated genetic firefly algorithm (IGFA) was proposed. The multi-objective function with variable weight was utilized to balance the classification accuracy and the feature reduction ratio that are contradictory goals to find brighter fireflies in each generation. To retain the historical optimal solution and reduce the feature dimension, an optimal population protection scheme and subgroups generation scheme was carried out. The experimental results show that the averaged feature reduction rate of the proposed method is 0.959, and the averaged classification accuracy is 0.961. By investigating important brain regions, deaf subjects have common areas in the frontal and temporal lobes for EEG emotion recognition, while individual areas occur in the occipital and parietal lobes.
Imprint of planet formation in the deep interior of the Sun

Stars grow by accreting gas that has an evolving composition owing to the growth and inward drift of dust (pebble wave), the formation of planetesimals and planets, and the selective removal of hydrogen and helium by disk winds. We investigated how the formation of the Solar System may have affected the composition and structure of the Sun, and whether it plays any role in solving the solar abundance problem. We simulated the evolution of the Sun from the protostellar phase to the present age and attempted to reproduce spectroscopic and helioseismic constraints. We performed chi-squared tests to optimize our input parameters. We confirmed that, for realistic models, planet formation occurs when the solar convective zone is still massive; thus, the overall changes due to planet formation are too small to significantly improve the chi-square fits. We found that solar models with up-to-date abundances require an opacity increase of 12% to 18% centered at $T=10^{6.4}$ K to reproduce the available observational constraints. This is slightly higher than, but is qualitatively in good agreement with, recent measurements of higher iron opacities. These models result in better fits to the observations than those using old abundances; therefore, they are a promising solution to the solar abundance problem. Using these improved models, we found that planet formation processes leave a small imprint in the solar core, whose metallicity is enhanced by up to 5%. This result can be tested by accurately measuring the solar neutrino flux. In the improved models, the protosolar molecular cloud core is characterized by a primordial metallicity in the range 0.0127-0.0157 and a helium mass fraction in the range 0.268-0.274. (abridged)
Measuring Secondary Nucleation through Single Crystal Seeding

This article presents a novel assessment method for secondary nucleation rates using a well-controlled, small scale seeding procedure. The procedure comprises the seeding of a well-monitored, stirred, supersaturated solution by a carefully selected single crystal under conditions at which spontaneous nucleation does not occur. The determined number of particles in time were translated to a suspension density using a calibration performed with monodisperse polymer spheres. The increasing crystal suspension density in time subsequently allowed the determination of the secondary nucleation rate under very specific conditions of supersaturation and temperature. The secondary nucleation rate was measured as a function of seed crystal size and supersaturation. It was observed that the time elapsed between the moment a single seed crystal is added and the moment the suspension density started to increase is larger when the seeded crystals are smaller and the supersaturation is lower. A systematic study of second.
Learning Analytics for Diagnosing Cognitive Load in E-Learning Using Bayesian Network Analysis

A learner’s cognitive load is highly associated with their academic achievement within learning systems. Diagnostic information about a learner’s cognitive load is useful for achieving optimal learning, by enabling the learner to manage and control their cognitive load in the e-learning environment. However, little empirical research has been conducted to obtain diagnostic information about the cognitive load in e-learning systems. The purpose of this study was to analyze a personalized diagnostic evaluation for a learner’s cognitive load in an e-learning system, using the Bayesian Network (BN) as a learning analytic method. Data from 700 learners were collected from Cyber University. A learner’s cognitive load level was measured in terms of three components: extraneous cognitive load, intrinsic cognitive load, and germane cognitive load. The BN was built by representing the relationship among the extraneous cognitive load, intrinsic cognitive load, germane cognitive load, and academic achievement. The conditional and marginal probabilities in the BN were estimated. This study found that the BN provided diagnostic information about a learner’s level of cognitive load in the e-learning system. In addition, the BN predicted the learner’s academic achievement in terms of their different cognitive load patterns. This study’s results imply that diagnostic information related to cognitive load helps learners to improve academic achievement by managing and controlling their cognitive loads in the e-learning environment. In addition, instructional designers are able to offer more appropriately customized instructional methods by considering learners’ cognitive loads in online learning.