Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of General and Study-Related Intraindividual Factors on Academic Learning Outcomes under COVID-19: A Cross-Sectional and Longitudinal Analysis

Little is known about the intraindividual dispositional factors related to cognitive, behavioral, and emotional academic learning outcomes under COVID-19. This study investigated (i) the associations of intraindividual factors, some related to studying (motivation to learn, self-regulated learning, and study resilience), others more general (soft skills, intolerance of uncertainty) with three situational academic learning outcomes (general distress, online self-regulated learning, study-related emotions), and (ii) the effect of time, intraindividual factors, online self-regulated learning, and study-related emotions on distress and achievement over the following three exam sessions. A total of 331 university students took part in the study during the first Italian nationwide lockdown (T1; March–May 2020). Of those, 121 also completed at least one follow-up (T2: August 2020; T3: September 2020; T4: February 2021). At T1, study-related dispositions and soft skills were positively associated with online self-regulated learning and study-related emotions, while study-related dispositions were also negatively associated with general distress. Intolerance of uncertainty was associated positively with general distress and negatively with study-related emotions. Longitudinal effects of T2 and T3 for intolerance of uncertainty and study-related emotions were observed for distress, while those for T4 were study-related dispositions for achievement. Nurturing intraindividual factors can help students cope with a prolonged stressful situation such as a pandemic.
The Lived Experience of Motherhood after Prison: A Qualitative Systematic Review

Abstract Despite the increasing number of women experiencing incarceration internationally, their experiences of motherhood after prison rarely studied. This review aims to explore and synthesize current research on the nature of the lived experience of motherhood after imprisonment. A qualitative synthesis review of English language-based articles published before January 2020 was used. 14 peer-reviewed qualitative studies were identified. The findings indicate that the post-release was a time when mothers re-claim their mothering role but faced significant challenges without sufficient support systems. It was also a time of reflection on the impact that the context of incarceration had on parenting roles and relationships with their children. The review found that we have limited understanding of the mothers’ current experiences of motherhood post-release. The reports are also insufficient to capture the mothers’ voice in different contexts. Further research is therefore required to explore the motherhood experience after release in greater depth and richness.
Neural network of superiority illusion predicts the level of dopamine in striatum

In evaluating the personality attributes and performance of the self, people are inclined to view themselves superior to others, a phenomenon known as superiority illusion (SI). This illusive outlook pervades people’s thoughts, creating hope for the future and promoting mental health. Although a specific cortico-striatal functional connectivity (FC) under dopaminergic modulation was previously shown to be implicated in SI, the underlying whole-brain mechanisms have remained unclarified. Herein, to reveal the neural network subserving individual’s SI, we conducted a data-driven, machine-learning investigation to explore the resting-state FC network across the whole brain. Using the locally-acquired resting-state functional magnetic resonance imaging data (n = 123), we identified a set of 15 FCs most informative in classifying individuals with higher-versus lower-than-average levels of SI in evaluating positive trait words (area under the curve [AUC] = 0.81). Among the 15 FCs, the contribution level to the classification was 11% by the previously-highlighted cortico-striatal FC alone, but 60% by the encompassing cortico-limbico-striatal network cluster. A newly-identified, cortico-thalamic FC and another FC cluster also demonstrated substantial contribution. The classification accuracy was generalized into an independent cohort (n = 36; AUC = 0.73). Importantly, using the same set of 15 FCs, we achieved prediction on an individual’s level of striatal dopamine D2 receptor availability (Pearson correlation, r = 0.46, P = 0.005). This is the first successful identification of the whole-brain neural network that simultaneously predicts the behavioral manifestation and molecular underpinning of an essential psychological process that promotes well-being and mental health. Significance Statement Superiority illusion (SI) is a basic self-referential framework that pervades people’s thoughts and promotes well-being and mental health. An aberrant form of SI has been reported in psychiatric conditions such as depression. Our hypothesis-free, data-driven investigation revealed the spatially-distributed neural network that for the first time achieved prediction on an individual’s levels of SI and the striatal dopaminergic transmission simultaneously. In principle, this multiple-biological-layer framework can be applicable to any behavioral trait to establish a link with its underlying neural network and neurochemical properties, which could quantitatively present the relation of its aberrant form with the pathophysiology of neuropsychiatric disorders. Future clinical research may aid in deriving a diagnostic biomarker for examining the related behavioral and neurochemical characteristics within individuals.
Adoption of digital health with a concept of patient as an organization

The paper has been conceptualized as it will script a new paradigm for the patient-based healthcare model. Where patients will evolve from mere consumers of resources to an organization as it produces resources as well. The patient will not only be monitored by the state but also be protected, empowered similar to Organization. This very concept will ensure the shift from exploitation to utilization.
Prediction of pedestrians’ wait-or-go decision using trajectory data based on gradient boosting decision tree

The road-crossing of pedestrians at unsignalized crosswalks is a major concern for road safety. Previous studies focused on explaining of the mechanism underlying this behavior, but a framework of prediction is missing. To predict this behavior, only variables measured before the decision is made should be considered. To explore whether historical data is able to predict the behavior, this paper investigates pedestrians’ wait-or-go (WOG) behavior based on trajectory data and a machine learning method, both of which have been rarely applied by previous studies. The use of trajectory data enables the analysis of several influential factors related to moving characteristics, which are critical for pedestrians’ decision making. The framework based on machine learning, combined with trajectory data, achieves good explanatory power and predictability of pedestrians’ WOG behavior. Moreover, a possible application of this study is the prediction of pedestrian road-crossing intention in the context of autonomous cars.
Future of Winter in Northeastern North America: Climate Indicators Portray Warming and Snow Loss That Will Impact Ecosystems and Communities

- Winters in northeastern North America have warmed faster than summers, with impacts on ecosystems and society. Global climate models (GCMs) indicate that winters will continue to warm and lose snow in the future, but uncertainty remains regarding the magnitude of warming. Here, we project future trends in winter indicators under lower and higher climate-warming scenarios based on emission levels across northeastern North America at a fine spatial scale (1/16°) relevant to climate-related decision making. Under both climate scenarios, winters continue to warm with coincident increases in days above freezing, decreases in days with snow cover, and fewer nights below freezing. Deep snow-packs become increasingly short-lived, decreasing from a historical baseline of 2 months of subnivium habitat to <1 month under the warmer, higher-emissions climate scenario. Warmer winter temperatures allow invasive pests such as Adelges tsugae (Hemlock Woolly Adelgid) and Dendroctonus frontalis (Southern Pine Beetle) to expand their range north-ward due to reduced overwinter mortality. The higher elevations remain more resilient to winter warming compared to more southerly and coastal regions. Decreases in natural snowpack and warmer temperatures point toward a need for adaptation and mitigation in the multi-million-dollar winter-recreation and forest-management economies.
XR Ulysses: addressing the disappointment of cancelled site-specific re-enactments of Joycean literary cultural heritage on Bloomsday

ABSTRACT Site-specific performances are shows created for a specific location and can occur in one or more areas outside the traditional theatre. Social gathering restrictions during the Covid-19 lockdown demanded that these shows be shut down. However, site-specific performances that apply emergent and novel mobile digital technologies have been afforded a compelling voice in showing how performance practitioners and audiences might proceed under the stifling constraints of lockdown and altered live performance paradigms, however they may manifest. Although extended reality (XR) technologies have been in development for a long time, their recent surge in sophistication presents renewed potentialities for site-specific performers to explore ways of bringing the physical world into the digital to recreate real-world places in shared digital spaces. In this research, we explore the potential role of digital XR technologies, such as volumetric video, social virtual reality (VR) and photogrammetry, for simulating site-specific theatre, thereby assessing the potential of these content creation techniques to support future remote performative events. We report specifically on adapting a real-world site-specific performance for VR. This case study approach provides examples and opens dialogues on innovative approaches to site-specific performance in the post-Covid-19 era.
Demand for inbound educational tourism: a note on relative differences and non-linear relationships

ABSTRACT We examine the demand for inbound educational tourism in Malaysia using non-stationary panel data methods. We find that educational tourism demand is influenced by income, costs of living, price of education, political stability and academic quality. However, the impact of income on demand is non-linear. Income has a significant positive impact on demand at the initial stage but this impact becomes negative after the threshold. Additionally, while demand is inversely related to educational price and cost of living, it is positively related to political stability and academic quality. We suggest that these findings be considered in formulating tourism policies.
Beyond Equal-Power Sparse NOMA: Two User Classes and Closed-Form Bounds on the Achievable Region

Non-orthogonal multiple access (NOMA) is a promising technology for future beyond-5G wireless networks, whose fundamental information-theoretic limits are yet to be fully explored. Considering regular sparse code-domain NOMA (with a fixed and finite number of orthogonal resources allocated to any designated user and vice versa), this paper extends previous results by the authors to a setting comprising two classes of users with different power constraints. Explicit rigorous closed-form analytical inner and outer bounds on the achievable rate (total class throughput) region in the large-system limit are derived and comparatively investigated in extreme-SNR regimes. The inner bound is based on the conditional vector entropy power inequality (EPI), while the outer bound relies on a recent strengthened version of the EPI. Valuable insights are provided into the potential performance gains of regular sparse NOMA in practically oriented settings, comprising, e.g., a combination of low-complexity devices and broadband users with higher transmit power capabilities, or combinations of cell-edge and cell-center users. The conditions for superior performance over dense code-domain NOMA (taking the form of randomly spread code-division multiple access), as well as a relatively small gap to the ultimate performance limits, are identified. The proposed bounds are also applicable for the analysis of interference networks, e.g., Wyner-type cellular models.
Late responses in the anterior insula reflect the cognitive component of pain: evidence of nonpain processing

Supplemental Digital Content is Available in the Text. Distinguishing sensory and cognitive aspects of pain-related insular activity and the temporal profile of anterior insula activity suggested a key role of cognitive modulation. Abstract Introduction: Pain is a complex experience influenced by sensory and psychological factors. The insula is considered to be a core part of the pain network in the brain. Previous studies have suggested a relationship between the posterior insula (PI) and sensory processing, and between the anterior insula (AI) and cognitive–affective factors. Objectives: Our aim was to distinguish sensory and cognitive responses in pain-related insular activities. Methods: We recorded spatiotemporal insular activation patterns of healthy participants (n = 20) during pain or tactile processing with painful or nonpainful movie stimuli, using a magnetoencephalography. We compared the peak latency between PI and AI activities in each stimulus condition, and between pain and tactile processing in each response. The peak latency and amplitude between different movies were then examined to explore the effects of cognitive influence. A visual analogue scale was used to assess subjective perception. Results: The results revealed one clear PI activity and 2 AI activities (early and late) in insular responses induced by pain/tactile stimulation. The early response transmitted from the PI to AI was observed during sensory-associated brain activity, whereas the late AI response was observed during cognitive-associated activity. In addition, we found that painful movie stimuli had a significant influence on both late AI activity and subjective perception, caused by nonpainful actual stimulation. Conclusions: The current findings suggested that late AI activation reflects the processing of cognitive pain information, whereas the PI and early AI responses reflect sensory processing.
REGIONAL ANALYSIS OF THE PACIFIC ALLIANCE COUNTRIES ON THE RELATIONSHIP BETWEEN INCOME INEQUALITY AND SOCIAL CAPITAL

Social capital is considered a productive resource for societies. The increase in social trust is usually related to both economic growth and a reduction in inequality. In Latin American countries, and particularly the economies that belong to the Pacific Alliance, the relationship between social capital and income inequalities has not been studied at regional level. The paper aims to analyze whether social capital impacts income inequality in the case of the Pacific Alliance regions. Dynamic panel data models were used, covering 72 regions during the period 2002-2011. The results show that the decline in generalized trust and congress trust impacts negatively income inequality, while government trust, police trust and company trust have not effect.
Selenium uptake by rocket plants (Eruca sativa) grown in a calcareous soil as affected by Se species, Se rate and a seaweed extract-based biostimulant application

Abstract. To investigate the potentiality of Eruca sativa (rocket) to be enriched in selenium (Se) and, thus, to promote human health through consumption, a pot experiment was designed. Two rates, 5 and 10 mg/kg soil, of either selenite or selenate sodium salts were applied to appropriate pots, each filled with 1 kg of calcareous soil. Rocket seedlings were transplanted and grown in these pots, and to half of the pots the biostimulant Actiwave was added. Twelve weeks later, the plants were harvested and Se concentrations determined in shoots and roots. Plant growth characteristics were measured and plants biometrics were assessed by soil plant analyses development (SPAD), normalised difference vegetation index (NDVI) and normalised difference red edge (NDRE). Sulfur (S) and phosphorus (P) concentrations in plant samples were also determined to discuss possible interactions among the three elements. The highest Se concentration of 1070.5 mg/kg dry weight (DW) was observed for the high selenate rate without biostimulant, placing rocket in the group of Se hyperaccumulator plants. Toxic effects were recorded for the plants that received the high selenate rate, whereas no toxicity symptoms were observed for either selenite rate. According to Se concentrations in controls, biostimulant application significantly suppressed Se uptake and significantly increased S and P uptake. The same negative biostimulant effect on Se concentration in plants was clear in selenate treatments. When the results were expressed as total uptake (mg/pot), positive correlations among Se, S and P were found for selenate treatments, whereas for selenite treatments, the opposite was observed. Impressively, 1.6 mg Se/pot on a DW basis was accumulated in rocket shoots in the low selenate-rate without biostimulant treatment, corresponding to approximately 30% of the added 5 mg of selenate.
A Landscape Evolution Modeling Approach for Predicting Three‐Dimensional Soil Organic Carbon Redistribution in Agricultural Landscapes

Soil erosion diminishes agricultural productivity by driving the loss of soil organic carbon (SOC). The ability to predict SOC redistribution is important for guiding sustainable agricultural practices and determining the influence of soil erosion on the carbon cycle. Here, we develop a landscape evolution model that couples soil mixing and transport to predict soil loss and SOC patterns within agricultural fields. Our reduced complexity numerical model requires the specification of only two physical parameters: a plow mixing depth, Lp, and a hillslope diffusion coefficient, D. Using topography as an input, the model predicts spatial patterns of surficial SOC concentrations and complex 3D SOC pedostratigraphy. We use soil cores from native prairies to determine initial SOC‐depth relations and the spatial pattern of remote sensing‐derived SOC in adjacent agricultural fields to evaluate the model predictions. The model reproduces spatial patterns of soil loss comparable to those observed in satellite images. Our results indicate that the distribution of soil erosion and SOC in agricultural fields can be predicted using a simple geomorphic model where hillslope diffusion plays a dominant role. Such predictions can aid estimates of carbon burial and evaluate the potential for future soil loss in agricultural landscapes.
Too many yet too few caesarean section deliveries in Bangladesh: Evidence from Bangladesh Demographic and Health Surveys data

Caesarean section (CS) use is rising rapidly in Bangladesh, though lack of CS use remains common among disadvantage women. This increases risks of long-term obstetric complications as well as maternal and child deaths among disadvantage women. We aimed to determine the interaction effects of women’s disadvantage characteristics on CS use in Bangladesh. For this we have analysed a total of 27,093 women’s data extracted from five rounds of Bangladesh Demographic and Health Survey conducted during 2004 and 2017/18. The outcome variable was CS use, coded as use (1) and non-use (0). The major exposure variables were individual level, household level, and community level characteristics. Multilevel logistic regression model was used to determine association of CS use with socio-demographic characteristics and the interactions of three variables: working status, wealth quintile, and place of residence. We found a 751% increase of CS use over the last 13 years—from 3.88% in 2004 to 33% in 2017/18. Nearly, 80% of the total CS operation occurred in the private health facilities followed by the government health facilities (15%). Women living in rural areas with no engagement in formal income generating activities showed a 11% (OR, 0.89, 95% CI, 0.71–0.99) lower use of CS in 2004. This association was further strengthened over time, and a 51% (OR, 0.49, 0.03–0.65) lower in CS use was reported in 2017/18. Similarly, around 12%-83% lower likelihoods of CS use were found among rural poor and poorer women. These indicate Bangladesh is facing a double burden of CS use, that is a group of women with improved socio-economic condition are using this life saving procedure without medical necessity while their counterpart of disadvantage characteristics could not access the service. Improved monitoring from the government along with support to use CS services for the disadvantage groups on necessity are important.
How the Big Bang End Up Inside a Black Hole

The standard model of cosmology assumes that our Universe began 14 Gyrs (billion years) ago with a hot Big Bang expansion out of nothing. It can explain a vast range of different astrophysical data from a handful of free cosmological parameters. However successful this model is, we have no direct evidence or fundamental understanding of some key assumptions: low entropy start, Inflation, Dark Matter and Dark Energy. Here we present a simpler and more physical explanation for the same observations that do not require such assumptions or new laws of Physics. It is based on the evidence that we live inside a Black Hole (BH) of mass $ M \simeq 5 \times 10^{22} M_{\odot}$, which we observed as cosmic acceleration. How did the Big Bang end up inside such a BH? We propose that 25 Gyrs ago, a very low density cloud with this mass collapsed and form a BH. The collapse continued inside until it reached neutron energy densities (GeV) over solar mass ($M_{\odot}$) causal regions that exploded, like supernovae, producing a bounce and the Big Bang expansion. During collapse, perturbations exit the horizon to re-enter during expansion, given rise to the observed universe. We review the theoretical and observational evidence for such BH Universe.
Measuring User Readiness of Kartu Tani on Technology Readiness Index (TRI) in Sumenep District

The government program related to Kartu Tani aims to provide welfare to farmers. However, until now it hasn't been realized, meaning that not all farmers accept the innovations given by the government. Measure user readiness to use Kartu tani to determine the success of implementing the technology. This study aims to determine a certain technical readiness index for Kartu Tani in Sumenep District. Almost all of the data were collected from farmers by a simple random sampling method using Hair 85 valid sample in Sumenep District. The measurement method used is TRI made with the four variables of optimism, innovation, discomfort, and insecurity. It is found that the preparation level of Kartu tani users is at a medium level of technical preparation, with a value of 3.33. The farmers' TRI value is considered to be moderate and needs to be improved.