Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Evidence for Representational Persistence Within Events

How does the brain process continuous experiences so they can be remembered? Evidence suggests that people perceive their experience as a series of distinct and meaningful events. Information encountered within the same event shows greater temporal integration into memory as well as enhanced neural representational similarity. Although these data support the theory that the brain builds and maintains a mental model of the current event that represents recently encountered stimulus information, this hypothesis has not been directly tested. We used fMRI in humans (N = 21, 13 female) to test whether within-event neural similarity indicates the persistence of stimulus representations in a mental model. Participants viewed trial-unique visual images that were grouped into events. We calculated neural pattern similarity across time in the category-selective visual cortex to measure stimulus persistence. Pattern similarity was enhanced within, compared with between, events in the object-sensitive left lateral occipital (LO) cortex. This was specific to situations when objects could persist within a mental model, suggesting modulation of neural activity based on the features and structure of the event. Left LO object persistence was correlated with activity in a medial prefrontal cortex (mPFC) region linked to representing mental models within events. mFPC activity also correlated with pattern similarity in the hippocampus but more generally across stimulus categories. Critically, left LO similarity was related to estimates of temporal proximity in memory. The data suggest that temporal neural stability reflects stimulus persistence in mental models and highlight the importance of within-event representational stability in the transformation of experience to memory. SIGNIFICANCE STATEMENT How does the brain process continuous experiences so they can be remembered? One idea is that information persists in mental models during stable events, facilitating the organization of events in memory. Using fMRI pattern similarity analysis, we found enhanced similarity within, compared with between, events in the object-sensitive LO but only when objects could persist within a mental model. mPFC activity correlated with left LO similarity when objects persisted within an event; in contrast, mPFC activity correlated with hippocampal similarity across stimulus categories. Left LO persistence was also related to the remembered temporal proximity of stimuli. The data suggest the brain dynamically maintains stimulus information in mental models during events, supporting the transformation of experience into memory.
Understanding intercalation structures formed under graphene on Ir(111)

The coverage-dependent intercalation of oxygen, CO, hydrogen, alkali metals, and halogens between graphene and Ir(111) is investigated using density functional theory with van der Waals corrections. By comparing adsorption on clean Ir to intercalation we show that the presence of the graphene layer shifts the stability of the adsorption structures towards higher coverages, with oxygen as the only exception preferring low-coverage intercalation structures. In general, we find that the preferred adsorption site of the intercalant is important for the stability of intercalation structures, where an atop adsorption site favors higher-coverage structures compared to a hollow adsorption site. Overall, the predicted stable intercalation structures are in good agreement with experimentally observed intercalation structures. We calculate doping levels of intercalated graphene and show that there is a correlation between the amount of charge transfer to or from the graphene sheet and the graphene binding energy, which is an indication for ionic bonding between the graphene sheet and the intercalants. We show that the graphene doping level can be tuned almost continuously between strong $n$-type doping for the alkali metals and strong $p$-type doping for F. Further, we calculate C $1s$ core-level shifts for intercalated graphene and show that these are correlated with the calculated doping level. The obtained values for graphene doping levels and core-level shifts are qualitatively in good agreement with available experimental values, but we find quantitative disagreements of up to 0.3 eV.
Quantitative Biomarkers for Cancer Detection Using Contrast-Free Ultrasound High-Definition Microvessel Imaging: Fractal Dimension, Murray’s Deviation, Bifurcation Angle & Spatial Vascularity Pattern

A growing body of evidence indicates that there is a strong correlation between microvascular morphological features and malignant tumors. Therefore, quantification of these features might allow more accurate differentiation of benign and malignant tumors. The main objective of this research project is to improve the quantification of microvascular networks depicted in contrast-free ultrasound microvessel images. To achieve this goal, a new series of quantitative microvessel morphological parameters are introduced for differentiation of breast masses using contrast-free ultrasound-based high-definition microvessel imaging (HDMI). Using HDMI, we quantified and analyzed four new parameters: 1) microvessel fractal dimension (mvFD), a marker of tumor microvascular complexity; 2) Murray’s deviation (MD), the diameter mismatch, defined as the deviation from Murray’s law; 3) bifurcation angle (BA), abnormally decreased angle; and 4) spatial vascular pattern (SVP), indicating tumor vascular distribution pattern, either intratumoral or peritumoral. The new biomarkers have been tested on 60 patients with breast masses. Validation of the feature’s extraction algorithm was performed using a synthetic data set. All the proposed parameters had the power to discriminate the breast lesion malignancy (p < 0.05), displaying BA as the most sensitive test, with a sensitivity of 90.6%, and mvFD as the most specific test, with a specificity of 92%. The results of all four new biomarkers showed an AUC = 0.889, sensitivity of 80% and specificity of 91.4% In conclusion, the added value of the proposed quantitative morphological parameters, as new biomarkers of angiogenesis within breast masses, paves the way for more accurate breast cancer detection with higher specificity.
Atomistic Simulation of the Structural, Thermodynamic, and Elastic Properties of Li2TiO3

Lithium-based ceramics, such as lithium metatitanate, have been proposed for adoption in the breeder blanket region of a fusion reactor. In this article, we report a combination of empirical and density functional theory (DFT) simulations employing “on-the-fly” pseudopotentials for Li2TiO3. The smoothing parameters of the plane-wave pseudopotentials were optimized to ensure an appropriate level of precision for determination of structural, thermodynamic, and elastic properties. As the elastic properties of lithium metatitanate are not well-known, the efficacy of the DFT simulations employing the new pseudopotentials was explored using Li2O and TiO2 where experimental data are available. These pseudopotentials are then used to investigate the three intermediate temperature phases of Li2TiO3 (i.e., C2/c, C2/m, and P3112). Finally, we examine the elastic properties of Li2TiO3 using both DFT and an empirical potential model and find it to be, irrespective of space group, more resistant to deformation than oth.
Asphaltene Adsorption onto an Iron Surface: Combined Near-Infrared (NIR), Raman, and AFM Study of the Kinetics, Thermodynamics, and Layer Structure

A combination of near-infrared (NIR) spectroscopy, Raman microscopy, and atomic force microscopy (AFM) was used to analyze the adsorption behavior of petroleum macromolecules (asphaltenes) on an iron (Fe) surface. A partial least-squares (PLS/PLSR) regression method was used for determining the concentration from NIR spectroscopic data. A Langmuir model was used to fit the experimental data. Effective kinetic and thermodynamic parameters (Gibbs energy of adsorption, adsorption/desorption rate constant, maximal adsorbed mass density) of asphaltenes adsorbed from benzene solution were evaluated: the maximum adsorbed mass density (Γmax) was found to be 4.90 ± 0.07 mg m−2; the adsorption constant (K) was found to be 0.084 ± 0.007 L mg−1; and a value of 34.3 ± 0.2 kJ mol−1 was calculated for the effective Gibbs energy of absorption (−ΔGads). The structure of the adsorbed layer was also analyzed by AFM. Asphaltenes were found to form aggregates on Fe surface with an average size of a few hundred nanometers. The.
Diagnosis of Coronavirus Disease 2019 by Potential Laboratory Factors

Objectives: Coronavirus disease 2019 (COVID-19) associated by infection and high death rate. The unresolved questions about the fatality rate of COVID-19 are most probably related to cytokine storm syndrome. There is currently no specific medication. Understanding the pathogenic pathway of this disease will lead to production of treatment and decreases of death rate. The aim of this study is to investigate changes of peripheral blood parameters (Interleukin-6, Ferritin and hematological parameters) in COVID-19 patients, which may be beneficial in the management of patients. Methods: In this comparative study, we collected data of 270 subjects in two groups according RT-PCR test results, including 133 patients with COVID-19 and 137 patients with non-COVID-19, between March 20 and May 21, 2020. After obtaining the ethics code from the ethics committee, the clinical characteristics and laboratory findings of patients were collected from electronic Health Information Systems using data collection forms in Shahid Jalil hospital of Yasuj university of medical sciences. The data were analyzed by SPSS software version 20. Descriptive statistics and chi-square, Mann-Whitney U, Kruskal-Wallis tests and Pearson's correlation coefficient were used to analyse the data. Results: The enrolled COVID-19 patients consisted of 53.4% males and 46.6% females with the medium age of 45.56±18.55 years and there were 50.04% males and 49.6% females with the medium age of 45.59±17.0 years for non COVID-19 patients. There was no significant difference in the age and sex ratio between two populations under study. The proportion interstitial abnormalities evidenced by CT imaging in COVID-19 patients was 91.0%, while, 4.4% abnormalities were found in non-COVID-19 patients. The mean IL-6 and Ferritin levels and hematological parameters in two groups of patients with COVID-19 and non- COVID-19 were significantly different across all comparisons. There was a direct positively correlated between serum level of IL-6, Ferritin levels and hematological parameters including WBC, Lymphocytes, Neutrophils and Hb, except for platelets (negatively correlate), with COVID-19. Conclusion: In conclusion, inflammatory markers specifically IL-6 and Ferritin and hematological parameters (WBC, Lymphocytes, Neutrophils, Platelet and Hb) were correlated with the severity of COVID-19. Measurement of IL-6, Ferritin and hematological indices might be workable tests to diagnosis and prognosis of patients with COVID-19.
Adsorptive Removal of Saturated and Unsaturated Fatty Acids Using Ion-Exchange Resins

One of the pretreatment approaches for decreasing the initial acid content of waste vegetable oil or nonedible oils with high initial free fatty acid content, with an objective of obtaining a suitable starting raw material for the production of biodiesel, is the adsorption of the free acids using ion-exchange resins. The present work deals with investigation of adsorption characteristics of saturated (stearic) and unsaturated (oleic) fatty acids on different ion exchange resins (polymeric strong (Indion 810) and weak (Indion 850 and Indion 860) anion exchange resins). The ion exchange resins contain tertiary or quaternary amino functional groups on the styrene-divinyl benzene copolymer matrix which can facilitate the adsorption of acids. Kinetic adsorption studies have been carried out initially to determine the contact time required to reach the adsorption equilibrium between fatty acid adsorbed on the resin and remaining fatty acid present in the oil. Equilibrium adsorption studies have been carried out.
Does Political Polarization Lead to a Rise in Government Debt?

: Existing politico-economic theories offer two mutually conflicting predictions on whether an increase in the degree of political polarization entails a rise or a decline in government debt. This article estimates the effect of political polarization on government debt, utilizing panel data of the OECD countries from 1962 to 2015. The empirical analysis finds that an increase in the degree of political polarization leads to an increase in government debt, which provides supportive evidence for Alesina and Tabellini (1990) and the like. This finding remains the same across different estimation models, without and with instrumenting the explanatory variable of political polarization.
Shaping Future Opportunities for Biomass Gasification-The Role of Integration

A considerable number of studies indicate that biofuels produced from lignocellulosic biomass will most probably play a significant role in achieving the climate goals stated in the Paris agreement. Several candidate technologies could be implemented to produce these fuels, and one of the most promising is thermal gasification. Gasification is a robust technology that has been demonstrated successfully at industrial scale and shown to be able to achieve high conversion efficiencies and relatively low production costs. However, there are currently no large-scale plants in operation or under construction, since such plants are unable to compete with their fossil counterparts under current conditions. This thesis explores how different forms and levels of integration could facilitate deployment of large-scale biomass gasification for future production of biofuels. Three levels of integration are considered, a technological level, a process level and a value-chain level. Different integration concepts are then assessed with respect to these levels. From a technology perspective, the implications of switching feedstock are studied. At the process level, heat integration with existing sawmill plants as well as integration of an electrolyser unit with a gasification plant are investigated. From a value chain perspective, integration with the value chain for producing fuels for use the Swedish iron and steel industry is considered, as well as integration with the electricity system. The results presented in this thesis indicate that the different integration options investigated can contribute to making biofuel production through biomass gasification more cost-efficient. Switching gasifier feedstock can lower biofuel production costs by up to 42%. Efficient heat integration with sawmills is the most attractive option to decrease production costs from a plantowner perspective. Integration of a flexible gasification unit equipped with CO2 capture capacity for either long-term storage or re-use as feedstock for biomethane production through the Sabatier reaction with hydrogen produced through electrolysis increases the economic competitiveness of the gasification unit, while stimulating increased construction of renewable electricity generation capacity. The thesis thus demonstrates that well-planned integration of biomass gasification plants can contribute significantly to making the technology more competitive.
Geochronology of Proterozoic rocks of the Sandia-Manzano-Los Pinos Uplift: implications for the timing of crustal assembly of the southwestern United States

New U-Pb zircon geochronologic data from plutons in the Sandia-Manzano-Los Pinos uplift are in agreement with older data that there were two major plutonic episodes, one at 1.66-1.65 Ga and the other at 1.46-1.45 Ga. These plutons are manifestations of a regional polyphase tectonic evolution for New Mexico during the Mazatzal and Picuris orogenies, respectively. Paleoproterozoic magmatism involved a bimodal rhyolite-basalt section of the basal Manzano Group; a new U-Pb zircon ICPMS age of 1665±16 Ma on the Sevilleta Metarhyolite Ma agrees with published ID-TIMS ages of 1662±1 Ma for the Sevietta Metarhyolite and 1662±2 Ma for interlayered mafic volcanic rocks. New ICPMS ages of 1655±14 Ma for the Manzanita, 1661±17 Ma for the Ojito, and 1662±14 Ma for the Los Pinos plutons, combined with older U-Pb dates, suggest these plutons overlap in age across the entire uplift. The 1.65-1.66 Ga plutons are interpreted to represent a magmatic arc system where plutons were intruding their own volcanic edifice and also intruding developing syn-contractional, arc-related sedimentary basins. New ICPMS U-Pb zircon ages from Mesoproterozoic plutons yield 1453±12 Ma for the Sandia and 1456±13 Ma for the Priest pluton. These plutons overlap in age, are about 20 Ma older than previously thought, and were emplaced syntectonically during the Picuris orogeny. 40Ar/39Ar data from coarse-grained muscovite crystals associated with these plutons yield complementary geochronologic information. In some cases, the muscovite ages are more precise than those obtained from zircon. Paired with our refined zircon ages, cooling ages obtained from muscovite provide insight into the secular thermal architecture of the Sandia-Manzano-Los Pinos uplift. 161
Dynamic Connectivity in a Financial Network Using Time-Varying DCCA Correlation Coefficients

Abstract This paper aims to analyse the connectivity of 13 stock markets, between 1998 and 2019, with a time-varying proposal, to evaluate evolution of the linkage between these markets over time. To do so, we propose to use a network built based on the correlation coefficients from the Detrended Cross-Correlation Analysis, using a sliding windows approach. Besides allowing for analysis over time, our approach also enables us to verify how the network behaves for different time scales, which enriches the analysis. We use two different properties of networks: global efficiency and average grade, to measure the network’s connectivity over time. We find that the markets under analysis became more connected before the subprime crisis, with this behavior extending even after the Eurozone crisis, showing that during extreme events there is an increase in financial risk, as found in the international literature.
Relationship between Intrapersonal Intelligence of Iranian EFL University Male and Female Learners and Their Grammar Ability

This study aimed to discover the possible relationship between intrapersonal intelligence and grammatical ability of Iranian EFL male and female learners. To this purpose, 139 undergraduate English students (46 males and 93 females), with the age range of 22-32, were selected through a TOEFL test as the participants. To obtain the needed data, the instruments used were a 119-item Multiple Intelligences Questionnaire (MIDAS) to assess the participants’ intrapersonal intelligence, and a 30-item grammar TOEFL test to the measure their grammar ability. The obtained data were analyzed through descriptive statistics, Pearson correlation and linear regression. The difference between male and female students in grammar ability and intrapersonal intelligence was determined by independent samples t-test. The results indicated a statistically significance relationship between intrapersonal intelligence and English grammar ability scores. The results also revealed no significant difference between male and female students in terms of intrapersonal intelligence and English grammar ability. The findings of this study may assist language teachers, policy makers and curriculum designers to consider the role of intrapersonal intelligence as a helpful construct in learning English grammar.
The Evolution of Cognitive Biases in Human Learning.

Cognitive biases like underinference, the hard-easy effect, and recurrently non-monotonic confidence are evolutionarily puzzling when viewed as persistent flaws in how people learn from environmental feedback. To explain these empirically robust cognitive biases from an evolutionary perspective, we propose a model of ancestral human learning based on the cultural-evolutionary-theoretic hypothesis that the primary selection pressure acting on ancestral human cognition pertained not to learning individually from environmental feedback, but to socially learning task-specific knowledge. In our model-which is inspired by classical Bayesian models-an ancestral human learner (the student) attempts to learn task-specific knowledge from a role model, with the option of switching between different tasks and role models. Suppose that the student's method of learning from their role model is a priori uncertain-in that it can either be successful imitation learning or de facto innovation learning-and the ecological fitness costs of meaningfully retaining environmental feedback are high. Then, the student's fitness-maximizing strategy does not retain their environmental feedback and-depending on the choice of model parameters-can be characterized by all of the aforementioned cognitive biases. Specifically, in order for the evolutionarily optimal estimate of confidence in this learning environment to be recurrently non-monotonic, it is necessary (as long as the environment's marginal payoff function satisfies a plausible quantitative condition) that a positive proportion of ancestral humans' attempted imitation learning was unknowingly implemented as de facto innovation learning. Moreover, an ecologically rational strategy of selective social learning can plausibly cause the evolutionarily optimal estimate of confidence to be recurrently non-monotonic in the empirically documented way: general increase with an intermediate period of decrease.
Transformation Of Learning For Early Childhood Education Through Parent Assistance In The Pandemic Covid-19

The 2019 corona virus disease (Covid-19) outbreak that hit countries in the world, presents its own challenges for educational institutions, especially early childhood education. To fight Covid-19, the Government prohibits gathering, social distancing and physical distancing, wearing masks and always washing hands and maintaining cleanliness. The Covid-19 pandemic has disrupted conventional learning processes. So we need a solution to answer these problems. Online learning is an alternative that can solve this problem. This study aims to determine strategies that can be applied in the learning transformation process through parental assistance in online learning for early childhood education children during the Covid 19 pandemic. The research method used is a descriptive qualitative approach. Data collected through observation, interviews and documentation. Interviews were conducted with 7 informants including the principal, parents of students and teachers. In this study, the sample determine using purposive sampling technique. The results showed that the model of parental assistance in online learning during the Covid-19 pandemic at Kingdom School, namely (1) parents ensure children and pay attention to material from the teacher, (2) accompany children when making homework, (3) people parents take part in any material provided by the teacher, (4) parents are also involved in online learning from the teacher. Meanwhile, the obstacles faced by parents in accompanying young children in online learning during the Covid-19 pandemic are not maintaining children's enthusiasm, not giving enough time, bad mood children and children bored and distracted by other things such as toys. The solution is First, by means of communication with the teacher. Second, creating a positive atmosphere. Third, enforcing discipline and Fourth, making learning videos for children.