Miracle-dz/UniFAR-FTUs huggingface dataset:
New microstructural insights into neutron-irradiated tungsten

The development of appropriate materials for fusion reactors that can sustain high neutron fluencies at elevated temperatures remains a great challenge. Tungsten is one of the promising candidate materials for plasma-facing components of future fusion reactors, due to several favorable properties as for example a high melting point, a high sputtering resistivity, and a low coefficient of thermal expansion. The microstructural details of a tungsten sample with a 1.25 dpa (displacements per atom) damage dose after irradiation at 800°C were examined by transmission electron microscopy (TEM). Three types of radiation-induced defects were observed, analyzed and characterized: (i) voids with sizes ranging from 10 nm to 65 nm, (ii) dislocation loops with a size of up to 10 nm and (iii) W-Re-Os containing σand χ-type precipitates. The distribution of voids as well as the nature of the occurring dislocation loops were studied in detail. In addition, nano-chemical analyses revealed that the σand χ-type precipitates, which are sometimes attached to voids, are surrounded by a solid solution cloud enriched with Re. For the first time the crystallographic orientation relationship of the σand χ-phases to the W-matrix was specified. Furthermore, electron energy-loss spectroscopy could not unambiguously verify the presence of He within individual cavities.
Digital dating abuse perpetration and impact: The importance of gender

ABSTRACT Although measurement and prevalence of digital dating abuse (DDA) in young people’s relationships is of growing research interest, youth perceptions of the behaviours and the impact on victims are yet to be fully understood. This study explored thirty-eight (16–24 year old) youth’s perceptions of DDA behaviours and descriptors of the emotional impact of the behaviours on victims. A predominant theme of gender differences emerged, with five subthemes: (a) men tend to engage in sexual-related behaviours, (b) men and women undertake different controlling and monitoring behaviours, (c) the role of reputation shapes the impact on men, (d) serious negative emotions characterise the impact on women, and (e) some men misconceive the severity of the impact on women. Findings move discussions beyond DDA prevalence and frequency to reveal that young people perceive DDA to have significant emotional consequences for victims and that there are gender differences in the perpetration and impact of DDA. These perspectives provide a valuable contribution to the development of gender-sensitive DDA measures, DDA prevention initiatives and support programmes for youth experiencing DDA.
Bearing Defect Classification Algorithm Based on Autoencoder Neural Network

The postproduction defect classification and detection of bearings still relies on manual detection, which is time-consuming and tedious. To address this, we propose a bearing defect classification network based on an autoencoder to enhance the efficiency and accuracy of bearing defect detection. An improved autoencoder is used to reduce dimension feature extraction and reduce large-scale images to small-scale images through encoder dimensional reduction. Defect classification is completed by feeding the extracted features into a convolutional classification network. Comparative experiments show that the neural network can effectively complete feature selection and substantially improve classification accuracy while avoiding the laborious algorithm of the conventional method.
Effect of Various Types of ENSO Events on Moisture Conditions in the Humid and Subhumid Tropics

Moisture anomaly conditions within humid and subhumid tropics that are associated with different types of El Niño and La Niña phenomena are described and analyzed with a focus on their spatial distribution and seasonal variability. Five dryness indices (Keetch–Byram Drought Index, Weighted Anomaly Standardized Precipitation Index, Standardized Precipitation Index, Palmer Drought Severity Index, and Percent of Normal Precipitation) were derived from ECMWF (European Centre for Medium-Range Weather Forecasts) fifth generation reanalysis (ERA5) reanalysis and University Corporation for Atmospheric Research (UCAR) datasets for the period from 1979 to 2019. Cross-correlation analysis was used to evaluate the relationships between the El Niño Southern Oscillation (ENSO) and selected dryness indices. To describe the seasonal variability of the ENSO–surface moisture relationships, the composite maps of dryness indices in different seasons were analyzed. The results showed a significant heterogeneity of the ENSO-induced moisture anomaly conditions both within and across various geographical regions. Four main areas in humid and subhumid tropics with the maximum effects of El Niño/La Niña events on the surface moisture conditions were found: Southeast Asia and Australia, Eastern and South Africa, Northeastern and Eastern South America, and Central America. It was shown that the effects of La Niña were usually opposite to those of El Niño, while the responses to the two types of El Niño differed mostly in the moisture anomaly intensity and its spatial patterns.
Separation of carrier-free holmium-166 from neutron-irradiated dysprosium targets

Holmium-166 ([sup 166]Ho, t[sub 1/2] = 26.4 h) is utilized in radiotherapeutic applications such as radioimmunospecific pharmaceuticals, bone marrow ablation, and radiation synovectomy. High specific activity [sup 166]Ho can be obtained from the decay of dysprosium-166 ([sup 166]Dy, t[sub 1/2] = 81.5 h). Dysprosium-166 is produced by the [sup 164]Dy[n,[gamma]][sup 165]Dy[n,[gamma]][sup 166]Dy reaction in a nuclear reactor. The applicability of reversed phase ion-exchange chromatographic methods was demonstrated for the separation of carrier-free [sup 166]Ho from milligram quantities of [sup 164]Dy[sub 2]O[sub 3] irradiated targets. An efficient and quantitative separation was achieved utilizing a metal-free HPLC system with Dowex AG 50WX12 or Aminex-A5 cation exchangers and [alpha]-hydroxy-isobutyric acid ([alpha]-HIBA) as the eluent (0.085 M, pH = 4.3 adjusted with NH[sub 4]OH). The Aminex-A5 column gave a separation factor of approximately 10[sup 3] between Ho and Dy. Subsequent to the acidic destruction of the Ho-HIBA complex, Ho[sup 3+] was further purified on a small cation-exchange column from acidic chloride solutions. The separation was achieved within 2 h, with a 95% overall radiochemical yield for carrier-free [sup 166]Ho with a Dy breakthrough of < 0.1%. 32 refs., 7 figs., 1 tab.
Dark Web in the Dark: Investigating when Transactions Take Place on Cryptomarkets

Abstract Online illicit marketplaces known as cryptomarkets have gained considerable attention from the media, government authorities, law enforcement agencies, and researchers. An increasing number of studies have investigated various aspects of these cryptomarkets' characteristics, such as product categories, sale volumes, and the number of listings and vendors. However, there is a gap in the literature regarding whether illegal transactions (of illicit drugs) take place during the day or week. This study fills this gap by tracing Bitcoin addresses associated with the six previously leading and most active cryptomarkets—Silk Road, Silk Road 2.0, Agora, Evolution, Nucleus, and Abraxas—to identify the specific timings of these transactions. This study reveals clear patterns of activity on the marketplaces. First, transactions more often take place at night in European countries (Germany, Netherlands, the UK), the US, and Canada, where the cryptomarket drug trade is most active. Second, there are more transactions on Mondays, Tuesdays, and Wednesdays, and fewer on Saturdays and Sundays. This indicates that the retail drug trade accounts for a large part of the cryptomarkets. Further, this study examines the impact of a cryptomarket policing effort known as Operation Onymous, and indicates that this policing effort only displaced users among these marketplaces and did not deter their activity, even in the short-term. It also suggests that Operation Onymous did not alter users’ transaction patterns.
Long-Haul COVID-19: Putative Pathophysiology, Risk Factors, and Treatments

Long-haul COVID-19 illness first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is mysterious as it affects COVID-19 survivors at all levels of disease severity, even younger adults and children. While the precise definition may be lacking, the defining symptoms are fatigue, dyspnea, and headache that last for months after hospital discharge. The less typical symptoms may include cognitive impairments, chest and joint pains, myalgia, smell and taste dysfunctions, cough, mood changes, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long-haul COVID-19, which the current review aims to address. In brief, long-haul COVID-19 may be driven by long-term lung and brain damage and unresolved inflammation from multiple sources. The associated risk factors may include female sex, more than five early symptoms, early dyspnea, and specific biomarkers like D-dimer. While only rehabilitation training has been useful for long-haul COVID-19, therapeutics repurposed from mast cell activation syndrome, myalgic encephalomyelitis/chronic fatigue syndrome, and pulmonary fibrosis also hold potential. In sum, this review hopes to provide the current understanding of what is known about long-haul COVID-19.
Wire breaking localization of parallel steel wire bundle using acoustic emission tests and finite element analysis

The precise localization of cable damage is a major issue in bridge engineering. The acoustic emission (AE) method has been applied to detect defects for cable structures in bridges. In this paper, an AE localization method is proposed to localize both lateral and longitudinal positions of defects in a parallel steel wire bundle composed of seven steel wires. The proposed method is verified numerically and experimentally. Tension failure test of the parallel steel wire bundle composed of seven wires was carried out, and the precise localization of defects was realized by through modal AE techniques and the analysis of the characteristics of AE signal. A Multiphysics model based on COMSOL was established to facilitate the visualization of stimulated AE propagated in the parallel wire bundle. The propagation mechanism of AE signal was studied, and the feasibility of localization method was verified.
The promotion of Festuca sinensis heavy metal stress tolerance mediated by Epichloë endophyte

Background: Festuca sinensis is a perennial grass of the genus Festuca, which has strong stress tolerance and high adaptability. F. sinensis normally symbiotic with Epichloë endophyte. In order to evaluate the possibility of F. sinensis-endophyte association as bioremediation grass in heavy metal polluted soils, the effects and mechanism of the F. sinensis-endophyte interaction under heavy metal stress was investigated. Results: The growth performance and physiology variations of F. sinensis with (E+) and without endophyte (E-) were evaluated after they were subjected to Zn2+ and Cd2+ treatments. The results showed that heavy metal treatments had significant effects on plants as the growth indices of plants under Zn2+ and Cd2+ treatments had significant differences compared with plants under control treatment (P<0.05). Zn2+ treatment had positive effects on plants whereas Cd2+ treatment had negative effects. The plants under Cd2+ treatment produced more lolitrem B (P<0.05). Endophyte increased host heavy metal stress tolerance by promoting host growth as the E+ plants had significantly higher plant height, tiller number, root length (P<0.05). Endophyte also promoted host Zn2+ ion absorbing and induced more endogenous hormone production (P<0.05). Conclusions: These results suggested that Epichloë regulated host growth and physiology to improve association tolerance to environmental conditions.
Estimation of Antioxidant Potential of Individual Components Present in Complex Mixture of Withania somnifera (Ashwagandha) Root Fraction by Thin-Layer Chromatography—2,2-Diphenyl-1-Picrylhdrazyl Method

A thin-layer chromatography–2,2-diphenyl-1-picrylhdrazyl (TLC—DPPH) method has been developed for the quantification of withanolides and simultaneous estimation of antioxidant potential of each constituent present in a complex mixture. High-performance thin-layer chromatography (HPTLC) of withanolide-rich fraction of Withania somnifera root was performed on Si 60F254 HPTLC plates with dichloromethane-toluene-methanol-acetone-diethyl ether (6.5:7:4:1.5:1, v/v) as a mobile phase for the separation of withanolides and on the basis of RF values 0.07, 0.55, 0.61, 0.63, 0.66, and 0.77 for withanoside V, withaferine A, 1,2-deoxywithastramonolide, withanone, withanolide A, and withanolide B, respectively. The concentrations of withanoside V, withaferine A, 1,2-deoxywithastramonolide, withanone, withanolide A, and withanolide B were 0.86, 12.9, 1.92, 1.52, 5.24, and 4.52 mg g−1 respectively. A TLC-DPPH rapid test was used to assess the free-radical scavenging activity of constituents in withanolide-rich fraction for the first time. In withanolides, withanoside V and withanolide B show the highest antioxidant potential. In unknown compounds, peak No. 17 at RF 0.92 has the highest antioxidant potential and peak No. 16 at RF 0.87 has recorded the lowest antioxidant potential. It is also found that some of the unidentified components had significant antioxidant potential. This technique has several advantages; therefore, this method will be useful for rapidly validating the Ayurvedic products containing W. somnifera.
Is it riskier to meet 100 people outdoors or 14 people indoors? Comparing public and expert perceptions of COVID-19 risk.

People have limited capacity to process and integrate multiple sources of information, so how do they integrate multiple contextual risk factors for Coronavirus disease (COVID-19) infection? In June 2020, we elicited risk perceptions from a nationally representative sample of the public (N = 800) using three psychologically-distinct tasks. Responses were compared to a sample of medical experts who completed the same tasks. Relative to experts, the public perceived lower risk associated with environmental factors (such as whether a gathering takes place indoors or outdoors) and were less inclined to treat risk factors as multiplicative. Our results are consistent with a heuristic simply to "avoid people" and with a coarse (e.g., "safe or unsafe") classification of social settings. A further task, completed only by the general public sample, generated novel evidence that when infection risk competes with risk in another domain (e.g., a different medical risk), people perceive a lower likelihood of contracting the virus. These results inform the policy response to the pandemic and have implications for understanding differences between expert and lay perception of risk. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Managing External Volatility: Policy Frameworks in Non-Reserve Issuing Economies

Since the global financial crisis, non-reserve-issuing economies (NREs) have been highly sensitive to episodes of external pressures. With monetary policy independence constrained by this sensitivity, many NREs have utilized other policy instruments. This paper confirms the vulnerability of NREs to external shocks and finds that in some circumstances managing such shocks with multiple instruments can both lessen the policy response required from any one policy tool to financial and external shocks and increase the effectiveness of policies in stabilizing macro-financial conditions. Effectiveness however does not always imply appropriateness, which rests on an evaluation of potential trade-offs and unintended consequences.
Evaluating the WHO’s framing and crisis management strategy during the early stage of COVID-19 outbreak

Abstract The outbreak of COVID-19 has posed an unprecedented threat to the functioning of our society and led to a substantial loss of lives. In this paper, we systematically analyzed the World Health Organization (WHO)’s policy framing and management of the pandemic. The performance of the WHO can be evaluated in two aspects: the timeliness of their risk assessment, such as the announcements of a Public Health Emergency of International Concern (PHEIC) and pandemic, and the communication interfaces between the WHO and other stakeholders. Our study reveals that, while the WHO has made timely decisions in risk assessments, there were profound limitations in the current communication interfaces and feedback loops between the WHO, member states and other stakeholders. We recommend redesigning the current alert system so that the level of warning and the accompanying policy recommendations could more accurately reflect the threat and escalating nature of a pandemic outbreak.
Reconstructing Magma Storage Depths for the 2018 Kı̄lauean Eruption From Melt Inclusion CO2 Contents: The Importance of Vapor Bubbles

The 2018 lower East Rift Zone (LERZ) eruption and the accompanying collapse of the summit caldera marked the most destructive episode of activity at Kı̄lauea Volcano in the last 200 years. The eruption was extremely well‐monitored, with extensive real‐time lava sampling as well as continuous geodetic data capturing the caldera collapse. This multiparameter data set provides an exceptional opportunity to determine the reservoir geometry and magma transport paths supplying Kı̄lauea’s LERZ. The forsterite contents of olivine crystals, together with the degree of major element disequilibrium with carrier melts, indicates that two distinct crystal populations were erupted from Fissure 8 (termed high‐ and low‐Fo). Melt inclusion entrapment pressures reveal that low‐Fo olivines (close to equilibrium with their carrier melts) crystallized within the Halema’uma’u reservoir (∼2‐km depth), while many high‐Fo olivines (>Fo81.5; far from equilibrium with their carrier melts) crystallized within the South Caldera reservoir (∼3–5‐km depth). Melt inclusions in high‐Fo olivines experienced extensive post‐entrapment crystallization following their incorporation into cooler, more evolved melts. This favored the growth of a CO2‐rich vapor bubble, containing up to 99% of the total melt inclusion CO2 budget (median = 93%). If this CO2‐rich bubble is not accounted for, entrapment depths are significantly underestimated. Conversely, reconstructions using equation of state methods rather than direct measurements of vapor bubbles overestimate entrapment depths. Overall, we show that direct measurements of melts and vapor bubbles by secondary‐ion mass spectrometry and Raman spectroscopy, combined with a suitable H2O‐CO2 solubility model, is a powerful tool to identify the magma storage reservoirs supplying volcanic eruptions.
Mycotoxins Analysis in Cereals and Related Foodstuffs by Liquid Chromatography-Tandem Mass Spectrometry Techniques

In the entire world, cereals and related foodstuffs are used as an important source of energy, minerals, and vitamins. Nevertheless, their contamination with mycotoxins kept special attention due to harmful effects on human health. The present paper was conducted to evaluate published studies regarding the identification and characterization of mycotoxins in cereals and related foodstuffs by liquid chromatography coupled to (tandem) mass spectrometry (LC-MS/MS) techniques. For sample preparation, published studies based on the development of extraction and clean-up strategies including solid-phase extraction, solid-liquid extraction, and immunoaffinity columns, as well as on methods based on minimum clean-up (quick, easy, cheap, effective, rugged, and safe (QuEChERS)) technology, are examined. LC-MS/MS has become the golden method for the simultaneous multimycotoxin analysis, with different sample preparation approaches, due to the range of different physicochemical properties of these toxic products. Therefore, this new strategy can be an alternative for fast, simple, and accurate determination of multiclass mycotoxins in complex cereal samples.
Threshold benchmarking for feature ranking techniques

In prediction modeling, the choice of features chosen from the original feature set is crucial for accuracy and model interpretability. Feature ranking techniques rank the features by its importance but there is no consensus on the number of features to be cut-off. Thus, it becomes important to identify a threshold value or range, so as to remove the redundant features. In this work, an empirical study is conducted for identiﬁcation of the threshold benchmark for feature ranking algorithms. Experiments are conducted on Apache Click dataset with six popularly used ranker techniques and six machine learning techniques, to deduce a relationship between the total number of input features (N) to the threshold range. The area under the curve analysis shows that ≃ 33-50% of the features are necessary and sufficient to yield a reasonable performance measure, with a variance of 2%, in defect prediction models. Further, we also find that the log 2 (N) as the ranker threshold value represents the lower limit of the range.
A comparison of block preconditioners for isogeometric analysis discretizations of the incompressible Navier–Stokes equations

We deal with numerical solution of the incompressible Navier–Stokes equations discretized using the isogeometric analysis (IgA) approach. Similarly to finite elements, the discretization leads to sparse nonsymmetric saddle‐point linear systems. The IgA discretization basis has several specific properties different from standard FEM basis, most importantly a higher interelement continuity leading to denser matrices. We are interested in iterative solution of the resulting linear systems using a Krylov subspace method (GMRES) preconditioned with several state‐of‐the‐art block preconditioners. We compare the efficiency of the ideal versions of these preconditioners for three model problems (for both steady and unsteady flow in two and three dimensions) and investigate their properties with focus on the IgA specifics, that is, various degree and continuity of the discretization basis. Our experiments show that the block preconditioners can be successfully applied to the systems arising from high continuity IgA, moreover, that the high continuity can bring some benefits in this context. For example, some of the preconditioners, whose convergence is h‐dependent in the steady case, seem to be less sensitive to the mesh refinement for higher continuity discretizations. In the unsteady case, we generally get faster convergence for higher continuity than for C0 continuous discretizations of the same degree for most of the preconditioners.
A Survey of Applied Behaviour Analysis Practitioners in Australia: Education, Training, and Barriers to Professional Practice

In Australia, the prevalence of autism has increased over the past decade. This has resulted in increased demand for safe and effective interventions and supports. Many evidence-based interventions for individuals with autism have been derived from the scientific discipline of Applied Behaviour Analysis (ABA). However, the professional practice of ABA is not yet formally regulated in Australia, and there are no national practice standards or qualification requirements for practitioners providing ABA-based interventions. In addition, very little is known about the qualifications and experiences of those in Australia who currently design and implement ABA intervention programs, information that would assist in developing practice standards and regulations for the profession. These regulatory and knowledge gaps have the potential to impact the safety of both consumers and practitioners. The aim of the current study, therefore, was to survey those who categorised themselves as ABA practitioners and, based on the analysis of the data, answer relevant questions about the status of the profession and provide recommendations for the development of ABA as a profession in Australia.