Miracle-dz/UniFAR-FTUs huggingface dataset:
The finance wage premium: Finnish evidence from a gender perspective

The growth in finance wages has contributed to the increase in top incomes over the last decades. The finance wage premium has been studied from various viewpoints in recent years, however, not from the gender perspective. Studies have shown that the gender wage gap tends to increase at top incomes. As finance wages are increasing and if the benefits of working in finance are mostly claimed by men, the overall gender wage gap will persist. Using Finnish registry data from 1990 to 2014, this paper shows that the finance wage premium differs considerably be-tween men and women. Overall, the finance premium has increased over time. The premium of men is larger than that of women at all hierarchy levels. Women at manager and expert positions in finance get a premium, but not at clerical level. Men on the other hand receive a premium at all hierarchy levels. The negative female effect is larger at higher points of the wage distribution, indicative of a glass ceiling effect. For men, the premium has increased especially at the top of the wage distribution.
From Working Tax Credit to Universal Credit: is the older workforce ready? Perspectives from employees and employers in Northern Ireland

Universal Credit (UC) entails an unprecedented expansion of welfare conditionality to those in work. Working-age adults (16–66) in the United Kingdom who are working part-time and on a low income will be subject to work related requirements until they earn the equivalent of 35 hours per week at national living wage. It is estimated that workers aged 50 to 66 will account for nearly a quarter of those claimants subject to in-work conditionality. A small-scale qualitative study was carried out with workers aged over 50 in receipt of Working Tax Credit (WTC) who are set to be migrated to UC. The researchers also interviewed employers who have people over 50 in their workforce. The findings show that there was limited awareness of UC and little support for in-work conditionality.
Arsenic Induced Free Radicals Mediated Genotoxicity and Protective Features of Ocimum Gratissium L.

Arsenic toxicity is a worldwide geogenic problem for large number of populations. The major problem of arsenicosis is generation of free radicals and related genotoxicity, In the present study three plants species Ocimum gratissimum L. , Ocimum sanctum, Ocimum basilicum, were examined by both in vivo and in vitro methods in Oryctolagus cuniculus L to know the free radical scavenging property in Sodium Arsenite induced oxidative stress and related genotoxicity. Oxidative stress was evaluated considering MDA, GSH, SOD, CAT & GPx, and genotoxicity was examined by comet assay and RAPD test. In the present study, Na3AsO3 was found to generate free radicals in lymphocytes of O. cuniculus and best recovery was reported (MDA-4.78 ± 0.05; GSH-2.87 ± 0.50;SOD-1.78 ± 0.03;CAT-2.72 ± 0.02;GPx-7.43 ± 0.01) under exposure of ethanolic leaf extract of O. gratissimum. Na3AsO3 was also found to cause polymorphic bands and increased comet tail in lymphocytes which was found significantly recovered by exposure of ethanolic leaf extract of O. gratissimum.
“Jonah’s gourd” and its early Byzantine interpretations

Many modern scholars consider the Old Testament book of Jonah being written in a boldly parodic manner. The narrative engages many details that sound humorous for a modern reader. However, from the standpoint of late Antique and early Medieval patristic exegesis, it is often unclear whether Byzantine interpreters perceived such passages laughable or at least inappropriate for a prophetic writing. This study presents a few examples of early Byzantine commentaries to the episode with Jonah and a gourd (Jonah 4:6–11). None of the commentaries expresses any explicit amusement caused by the discussed text. However, the style, method, or context of each commentary appears to be passing the traditional bounds of Bible interpretation. The earlier interpreters adhere to the most expected moral reading of Jonah 4, but they use epithets, metaphors, or omissions, which produce the effect of paradox comparable to the biblical wording itself. The later commentaries tend to involve unexpected and even provocative senses. In such interpretations, God can be thought of as being able to play with a human or even to fool and deceive. What seems us humorous in the Bible, Byzantine commentators take primarily as a paradox, which they did not explain or remove but elaborate further paradoxically. The later an interpreter is, the bolder his paradoxical approach appears. The results of the study provide some clues to understanding how the interpretation of humorous, parodic, or ironical passages were developing in the history of Byzantine intellectual culture.
Time series modelling methods to forecast the volume of self-assessment tax returns in the UK

ABSTRACT Her Majesty's Revenue and Customs (HMRC) has the ambitious target of making tax digital for all its customers and collecting tax in a more efficient, effective and accurate manner for both the government and UK taxpayers. Self-assessment tax returns, the biggest key business event for HMRC, is also one of the most popular digital services with over 90% of the approximately 12 million taxpayers in self assessment filing their return online each year. The majority of returns are filed in January immediately prior to the self-assessment deadline (31st January), putting significant pressure not only on the self-assessment digital service but also on all other HMRC digital services. Hence, understanding and predicting demand for the system is vital to provide a robust and responsive service. We therefore developed mathematical models with Bayesian inference techniques to forecast volumes of Self-assessment (SA) returns submitted online during January, providing accurate hourly predictions of traffic on the digital system in the run up to the SA deadline. Because none of the models being considered is believed to be the true model, we use an ensemble modelling technique that combines forecasts from different models to develop a less risky demand forecast.
How Artificial Life Researchers Can Help Address Complex Societal Challenges

The global COVID-19 pandemic has given rise to an unprecedented level of complex societal challenges to the humanity. Meanwhile, it also has created a huge demand for scientific expertise in modeling, simulation and analysis of epidemic and other socio-economical dynamics, to which Artificial Life researchers can make great contributions. This extended abstract presents a brief overview of projects the author has been working on in response to COVID-19 since early 2020, summarizing the lessons learned and identifying unique skills and abilities of Artificial Life researchers that have potential to help address various societal challenges.
La atenuación lingüística en el Corpus PRESEEA de Santiago de Chile

En este trabajo se presentan los principales resultados del estudio del fenómeno de la atenuación desde la perspectiva sociopragmática en el corpus PRESEEA de Santiago de Chile. Para cumplir este objetivo, se sigue la metodología de análisis propuesta en Cestero y Albelda (2012), Briz y Albelda (2013), Cestero y Rodríguez Alfano (2014) y Albelda et al. (2014), entre otros. De esta manera, se integran tres tipos de factores: lingüísticos, pragmático-discursivos y sociales. A partir de la revisión de nueve horas de grabación de la variedad chilena del español, registradas en 18 entrevistas semiestructuradas, se concluye que los hablantes presentan 750 actos de habla atenuados con 1731 recursos atenuadores. Se comprueba, asimismo, que la autoprotección es la principal función que cumplen los recursos de atenuación en el español chileno y que suele emplearse más la atenuación del modus, sobre todo mediante justificaciones y excusas. Finalmente, se concluye que la mayor variabilidad se produce en relación con los factores edad y nivel de instrucción de los informantes.
Elucidating the Energy- and Electron-Transfer Dynamics of Photon Upconversion in Self-Assembled Bilayers

Self-assembled bilayers of acceptor (A) and sensitizer (S) molecules on a metal oxide surface is a promising strategy to facilitate photon upconversion via triplet–triplet annihilation (TTA-UC) and extract charge from the upconverted state. The hypothesized mechanism for TTA-UC in a bilayer film includes low energy light absorption, triplet energy transfer, cross-surface energy migration, triplet–triplet annihilation, and electron injection into TiO2. Nonproductive processes can also occur including sensitizer-sensitizer TTA, radiative/nonradiative decay, back-electron transfer, and others. Steady-state and time-resolved emission/absorption spectroscopy were used to determine the rate constants of these processes. The rate constants indicate that S to A triplet energy transfer as well as S and A nonradiative rates are the primary efficiency-limiting processes for TTA-UC at the interface. This information is necessary to guide the design of new self-assembled UC films and is a critical stepping stone towar.
Soil properties: their prediction and feature extraction from the LUCAS spectral library using deep convolutional neural networks

<p>Soil, as a non-renewable resource, should be monitored continuously to prevent its degradation and promote sustainable agricultural management. Soil spectroscopy in the visible-near infrared range is a fast and cost-effective analytical technique to predict soil properties. The use of large soil spectral libraries can reduce the work needed to reliably estimate soil properties and obtain robust models capable of widespread applicability. Deep learning is apt for big data analysis, and this approach could herald a profound change in the way we model soil spectral data generally. Accordingly, we explored the modeling potential of deep convolutional neural networks (DCNNs) for soil properties based on a large soil spectral library. The European topsoil dataset provided by the Land Use/Cover Area frame Survey (LUCAS) was used without any pre-processing of spectra or covariates added. Two 16-layer DCNN models (ResNet-16 and VGGNet-16) were successfully used to make regression predictions of seven soil properties and classification predictions of soil texture into four groups and 12 levels. Our results showed that the ResNet-16 and VGGNet-16 models produced highly accurate predictions for most soil properties, being superior to either a shallow convolutional neural network and&#160;traditional machine learning approaches. Soil organic carbon content, nitrogen content, cation exchange capacity, pH, and calcium carbonate content were well predicted, having a ratio of performance to deviation (RPD)&#160;> 2.0. Soil potassium content was adequately predicted (1.4 &#8804; RPD&#160;&#8804; 2.0) and phosphorous content was poorly predicted (RPD&#160;< 1.4). The overall classification accuracy of soil texture was 0.749&#160;(four groups) and 0.566&#160;(12 levels). The position of feature wavelengths differed among the soil properties, for which multiple characteristic peaks were common. This study fully demonstrates the modeling potential of deep learning with soil hyperspectral data, which could bring us closer to achieving precision agriculture. </p>
Delayed Collapse of the North Pacific Intermediate Water After the Glacial Termination

Carbon release from the North Pacific in glacial‐interglacial cycles has been mainly linked to the North Pacific Intermediate Water (NPIW) formation and associated carbon/nutrient water upwelling and biological productivity changes. However, relationship between NPIW and atmospheric CO2 change in the early interglacial remains unclear. Here we report a high‐resolution sediment record of NPIW evolution based on paleo‐redox changes in the Western North Pacific during the last 400 ka. Our proxy and model results reveal a delayed collapse of NPIW after the glacial termination was coeval with decreased salinity of intermediate water and increased net rainfall in the North Pacific. Such weakened NPIW formation in the North Pacific probably make a contribution to maintain high atmospheric CO2 concentrations through weakened intermediate‐to‐deep ocean stratification and reduced subsurface biological pump net efficiency, countering the return to more stratified conditions in the Southern Ocean, which should drive down atmospheric CO2 during the early interglacial.
Inferring Jovian Electron Densities Using Plasma Wave Spectra Obtained by the Juno/Waves Instrument

The Waves instrument onboard the Juno spacecraft has plasma wave‐measuring capabilities using a single electric dipole antenna and a uniaxial magnetic search coil. Together, these simultaneously measure electric and magnetic field spectral densities in the frequency range 50 Hz–20 kHz, above which only electric field spectral densities are measured up to 41 MHz. A major objective of the Juno mission is to explore Jupiter's high‐latitude magnetosphere and ionosphere. One of the key contributions of the Waves instrument is the determination of electron densities from plasma wave spectra. Given the very high magnetic field strengths near Juno's perijove passes, established techniques cannot be utilized to infer electron densities since such highly magnetized space plasma conditions have not previously been met in planetary missions. By revisiting theoretical treatments of plasma waves, we describe a novel method to determine electron densities from plasma wave spectra that is unique to the near‐Jupiter region. In the absence of the commonly observed upper hybrid resonance frequency in high‐density space plasmas (e.g., the vicinities of Io, Ganymede, Enceladus, and the near‐Earth environment), we achieve this by identifying emission cutoffs at the lower hybrid frequency and electron plasma frequency. Further, we discuss the development of the process and tools for identifying and digitizing appropriate resonance and cutoff frequencies.
Relativistic B-Spline R-Matrix Calculations for Electron Collisions with Ytterbium

We have applied the full-relativistic Dirac B-Spline R-matrix method to obtain cross sections for electron scattering from ytterbium atoms. The results are compared with those obtained from a semi-relativistic (Breit-Pauli) model-potential approach and the few available experimental data.
Contamination of the Soil–Groundwater–Crop System: Environmental Risk and Opportunities

The increasing development of industries, resulting in a large volume of mining, smelting, and combustion wastes, and intense agricultural activities, due to demand for food and energy, have caused environmental hazards for food quality and ecosystems. This is a review on the contamination of the soil–groundwater–crop system and a potential reduction of the contamination by a gradual shift towards green economy within the European Union and on a worldwide scale. Available mineralogical and geochemical features from contaminated Neogene basins have shown a diversity in the contamination sources for soil and groundwater, and highlighted the need to define the contamination sources, hot spots, degree/extent of contamination, and provide ways to restrict the transfer of heavy metals/metalloids into the food chain, without the reduction of the agricultural and industrial production. Among harmful elements for human health and ecosystems, the contamination of groundwater (thousands of μg/L Cr(VI)) by industrial activities in many European countries is of particular attention. Although Cr(VI) can be reduced to Cr(III) and be completely attenuated in nature under appropriate pH and Eh conditions, the contamination by Cr(VI) of coastal groundwater affected by the intrusion of seawater often remains at the hundreds μg/L level. A positive trend between B and Cr(VI) may provide insights on the role of the borate [B(OH)4]− ions, a potential buffer, on the stability of Cr(VI) in coastal groundwater. Efforts are needed towards reducing toxic metal(loids) from the industrial wastewaters prior to their discharge into receptors, as well as the transformation of hazardous mining/industrial wastes to new products and applications to the optimization of agricultural management strategies.
Improving investment promotion agencies performance in attracting foreign direct investment

Purpose This study aims to investigate how investment promotion agencies (IPAs) attract funds effectively from emerging to established countries. Design/methodology/approach A qualitative action research (AR) study with data collected from focus groups and semi-structured interviews, observation and journaling. Comparative case studies are also presented to provide an external perspective to the researchers’ internal action researcher positions. Findings The research identifies four main factors that impact IPAs’ effectiveness in seeking a strategic asset in the UK from a developing country, China. The factors are policy advocacy, targeting industry, regional strategy and cultural adaption, which provide positive and significant influences on IPAs’ effectiveness. Research limitations/implications Little research has been published about the roles of IPAs in attracting foreign direct investment (FDI) from a developing to a developed country. The study uses an AR approach and case studies, which have not previously been used to investigate IPAs’ performance. The study extends the sparse extant research and provides insights into what influences the performance of IPAs, thus contributing to knowledge and practice. Practical implications The findings provide insights into the ways in which IPAs influence FDI flows. The research contributes to discipline knowledge and practice by identifying factors influencing funding in a non-traditional manner, that is from a developing to a developed country. Originality/value Little research has been published about the roles of IPAs in attracting FDI from a developing to a developed country. The study uses an AR approach and case study, which have not previously been used to investigate IPAs’ performance. The study extends the sparse extant research and provides insights into what influences the performance of IPAs, thus contributing to knowledge and practice.
Promotion of Critical Reading through the Use of Political Cartoons

Critical exploration of socio-political issues has been a topic strongly carried out in English classrooms in the last decades. This article is the result of a research study that shows what the use of political cartoons reveals about the promotion of critical reading in an EFL classroom at a private university in Colombia. The study was developed with fourteen students under a qualitative case study method. Workshops, teacher journals and focus-group interviews were used to collect data. The emerging categories show the positive results of using political cartoons and the change that the students had in their thoughts and actions in both the academic and social context. In the results, the students portray how they have perceived the ELT classroom, the importance of being a critical reader of texts and contexts, and how the different activities helped them construct their own critical awareness concerning social and political issues.
Do family firms pay less for external funding?

We examine the impact of family control on the cost of raising external funds by family enterprises. Using a sample of Australian publicly listed firms, we find a significantly negative relation between cost of newly raised capital and family control. Moreover, we show that this relationship varies with the quality of corporate governance and the quality of firm’s information environment. Furthermore, we conduct several robustness checks and consistently find that our main results remain unchanged. Overall, our evidence suggests that family firms have easier access to external financing fostered by family involvement in the ownership and control. JEL Classification: G31; G32; M41; M42
Adult ADHD Self-Report Scale Screener Ratings in College Students: Concurrent Validity and Test–Retest Reliability

The Adult ADHD Self-Report Scale screener is commonly used to determine if further evaluation of ADHD is required. However, despite use in college settings, the ASRS was not developed for this population, and limited relevant psychometric data exist. In this study, 190 college students completed the ASRS screener as well as a lengthier measure of the 18 DSM symptoms of ADHD. A subgroup (n = 141) completed the ASRS twice, with at least 1 week in between measures. Concurrent validity of ASRS scores was substantial (r = 0.73 with DSM inattentive symptoms and r = 0.57 with DSM hyperactive/impulsive symptoms) and test–retest reliability was adequate (r = 0.69 with an average interval of 42 days). However, the sensitivity of the screener was only moderate (66%), and approximately one-fifth of the students changed screening status (positive vs. negative) across the time interval. Implications for future research and practice are discussed.
Good Statistical Practices for Contemporary Meta-Analysis: Examples Based on a Systematic Review on COVID-19 in Pregnancy

Systematic reviews and meta-analyses have been increasingly used to pool research findings from multiple studies in medical sciences. The reliability of the synthesized evidence depends highly on the methodological quality of a systematic review and meta-analysis. In recent years, several tools have been developed to guide the reporting and evidence appraisal of systematic reviews and meta-analyses, and much statistical effort has been paid to improve their methodological quality. Nevertheless, many contemporary meta-analyses continue to employ conventional statistical methods, which may be suboptimal compared with several alternative methods available in the evidence synthesis literature. Based on a recent systematic review on COVID-19 in pregnancy, this article provides an overview of select good practices for performing meta-analyses from statistical perspectives. Specifically, we suggest meta-analysts (1) providing sufficient information of included studies, (2) providing information for reproducibility of meta-analyses, (3) using appropriate terminologies, (4) double-checking presented results, (5) considering alternative estimators of between-study variance, (6) considering alternative confidence intervals, (7) reporting prediction intervals, (8) assessing small-study effects whenever possible, and (9) considering one-stage methods. We use worked examples to illustrate these good practices. Relevant statistical code is also provided. The conventional and alternative methods could produce noticeably different point and interval estimates in some meta-analyses and thus affect their conclusions. In such cases, researchers should interpret the results from conventional methods with great caution and consider using alternative methods.