Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the process of artistic creativity: process in context / Istraživanje procesa umjetničkog stvaralaštva: proces u kontekst

The aim of this paper was to explore the process of artistic creativity. We conducted focus groups with artists from different fields of art. A total of 23 artists participated, who were divided into three focus groups (architecture and design, visual arts and performing arts). This qualitative research method provided us with an insight into aspects of creative process that artists perceive as the most important. In the analysis of their creative process, the artists described their approaches to artistic creativity, from the development of an idea to the production of a piece of art, emphasizing the biggest challenges they face in their work. In this paper, we present the most important insights into the process of artistic creativity.Keywords: artistic creativity, creative process, inspiration, motivationÂ ---Â Cilj ovog rada bio je istražiti proces umjetničkog stvaralaštva. Proveli smo fokusne grupe s umjetnicima različitih područja umjetnosti. Ukupno je sudjelovalo 23 umjetnika koji su bili raspodijeljeni u tri fokusne grupe (arhitektura i dizajn, vizualne umjetnosti te izvedbene umjetnosti). Primjena kvalitativne istraživačke metode omogućila nam je uvid u teme koje umjetnici doživljavaju najvažnijima u svom stvaralačkom procesu. U analizi svog kreativnog procesa umjetnici su opisali svoje pristupe umjetničkom stvaralaštvu, od razvoja ideje do izvedbe umjetničkog djela, pri čemu su istakli i najveće izazove s kojima se u svom radu suočavaju. U ovom radu izlažemo najvažnije spoznaje o procesu umjetničkog stvaralaštva. Ključne riječi: umjetničko stvaralaštvo, kreativni proces, inspiracija, motivacija
Running across Europe: The rise and size of one of the largest sport markets

Who is doing a run with the running boom? The growth and governance of one of Europe's most popular sport activities / Jeroen Scheerder, Koen Breedveld and Julie Borgers -- Belgium (Flanders): trends and governance in running / Julie Borgers, Steven Vos and Jeroen Scheerder -- Denmark: running for the sake of running? A profile and segmentation of runners / Peter Forsberg -- England: the governance and history of running, the decision to run, and trends in running participation / Andrew Spiers, Spencer Harris, Angela Charlton and Peter Smale -- Finland: from elite running to mass running events / Hanna Vehmas and Jukka Lahti -- Germany: running participation, motivation and images / Kirstin Hallmann, Christoph Breuer and Soren Dallmeyer -- Greece: mass running, a new trend from ancient times? / Leonidas Petridis -- Hungary: the popularisation and expansion of amateur running culture / Szilvia Perenyi -- The Netherlands: rising participation rates, shifting segments / Paul Hover, Harold van der Werff and Koen Breedveld -- Slovenia: the case of Ljubljana marathon participants / Mojca Doupona Topi? and Samo Rauter -- Spain: a sociological analysis of the evolution and characteristics of running / Ramon Llopig-Goig and Anna Vilanova -- Running across Europe: the way forward / Koen Breedveld, Jeroen Scheerder and Julie Borgers
Evaluation of community-based care delivered by primary healthcare providers in management of hypertension in a rural area of West Bengal

Background: Lifestyle modifications and medication compliance are key strategies. Objectives: To evaluate the effect of community-based care delivered by trained primary healthcare providers in management of hypertension. Materials and Methods: A longitudinal study was conducted between two groups of newly diagnosed hypertensive patients to evaluate the impact of an educational intervention. Six blocks in a district were chosen with pairwise matching. All primary healthcare providers of one block in each pair were randomized to receive the intervention and the other was controlled. Next screening for risk factors, detection of hypertension, counseling, and follow-up care were provided. The patients within the control group received usual care as per clinician's discretion. A total of 227 patients in the “study” group and 230 patients in the “control” group were recruited from 12 subcenters selected randomly. Data analysis was done by χ2 test, t test, and GLM analysis using SPSS 16. Results: Patients in the intervention blocks demonstrated a statistically significant mean reduction in SBP of 16.14 ± 0.82 and DBP by 11.65 ± 0.53 compared to 9.83 ± 1.02 and 7.68 ± 0.66, respectively, in the control blocks after adjusting for age, sex, and baseline blood pressure at one-year follow-up. Regarding lifestyle-related cardiovascular risk factors, statistically significant differences were found in favor of the intervention group. Conclusion: The study supports and reinforces the utilization of trained primary healthcare providers under the NPCDCS program in screening and promoting blood pressure control by preventive services to hypertensive patients in the community.
Airborne observations and regional flux estimates of greenhouse gases

Methane is the second most important long-lived greenhouse gas. However, it is typically emitted to the atmosphere by spatially and temporally heterogeneous sources, meaning that local measurements cannot easily be extrapolated to represent global scales. As a consequence, its global sources and sinks are generally poorly quantified. This thesis focuses on the use of airborne observations to improve flux estimates of methane at regional scales. A commercially available cavity-enhanced absorption spectrometer has been modified here for airborne measurements of methane and carbon dioxide. An algorithm employing the system's simultaneous water vapour measurement has been derived, using laboratory experiments, to determine dry air mole fractions without the need for sample drying. The system was found to be relatively independent of the aircraft's motion and its measurements were found to be accurate to within 1.28 ppb (1 standard deviation repeatability at 1Hz of 2.48 ppb) for methane and 0.17 ppm (1 standard deviation repeatability at 1Hz of 0.66 ppm) for carbon dioxide.This new measurement capability has been deployed during three international field campaigns, data from which is used in this thesis. The composition of boreal biomass burning was measured in eastern Canada. Methane emission factors showed a high degree of variability (range 1.8 $\pm$\ 0.2 to 8.5 $\pm$\ 0.9 g (kg dry matter)$^{-1}$), accentuating the challenges with using a purely bottom-up approach to determine total methane emissions and that top-down constraints are needed. Two case studies have shown that an aircraft mass balance approach can be a valuable tool for deriving regional scale top-down flux estimates, when a suitable sampling strategy can be employed under appropriate atmospheric conditions. First, this technique was applied to the European Arctic wetlands; and second, its suitability to derive emissions from a megacity was investigated using London, UK as a test case. On both occasions, the derived fluxes were found to be in good agreement with coincident surface observations within the aircraft's sampling domain. In the case of the Arctic wetlands the excellent agreement with seasonally averaged surface observations allowed this information to be used for the evaluation of land surface models. Two commonly used models, the Joint UK Land Environment Simulator and Hybrid8 were found to underestimate the methane emission flux for this region by an order of magnitude, highlighting the large uncertainties present in future methane emission scenarios at regional scales under a changing climate.
A Consideration on High Accuracy Estimation of Successive Moving Baseline for a Slow Speed Robot Based on GNSS Positioning

GNSS (Global Navigation Satellite System) is currently used in a variety of applications, and its positioning accuracy requirements become more and more demanding. We focus on an automatic strawberry pollination robot (under development in Kobe City College of Technology) and study a method of successive moving baseline vector estimation. In this paper, we propose a method to estimate accurate successive moving baseline vectors based on the difference of the single GNSS receiver observables obtained at two successive observation time (epoch). Furthermore, we also propose a method to estimate the bias error included in the solution of the moving baseline vector. Throughout the experiment, the proposed method and the relative positioning method are compared, and the results show that the proposed method can provide the baseline vector with the accuracy of 1.06 cm.
Time-Lapse Seismic Matching for CO₂ Plume Detection via Correlation-Based Recurrent Attention Network

Time-lapse seismic data analysis is an effective technique for monitoring reservoir changes and plays an important role in CO2 plume detection. Theoretically, during CO2 geological storage, time-lapse seismic data corresponding to nonreservoirs should be consistent. However, due to changes in near-surface velocity, differences in the position of sources and receivers, and different acquisition parameters and instruments, the consistency of time-lapse data is poor, which seriously affects the application of time-lapse data. To solve this problem, a correlation-based recurrent attention network (CRAN) is proposed for consistency matching of time-lapse data. Cross correlation is a direct measure of the correlation between seismic traces. The improved loss function of the network based on cross correlation is beneficial for improving the matching accuracy. Recurrent neural networks (RNNs) can learn sequential relations and suitable for predicting time series. Therefore, RNNs are combined with convolutional neural networks to improve the network time sensitivity. Treating a large number of extracted features equally is not conducive to effective information recognition; thus, a channel attention mechanism is introduced to assign different weights to the features, thus improving the contribution of useful information. The test results of the synthetic and field data show that the proposed CRAN has an excellent enhancing effect on the repeatability of time-lapse data, and the matched data clearly reveal a plume of CO2.
Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.
Microwave Thermometry of Brain Tumors: A 2D Computational Feasibility Study

In this paper, we investigate the possibility of monitoring temperature changes in brain tumor during hyperthermia treatment using differential microwave imaging. This application can provide in-line and real-time temperature monitoring during hyperthermia treatment. The target of hyperthermia treatment is a tumor located in the brain. The evolution of temperature within the tumor corresponds to changes in its dielectric properties that are then reconstructed using differential microwave imaging using Born's approximation. For this task, we have adopted two matching media, the first on being a water bolus and the second one being a standard matching medium for head microwave imaging. We analyze the transmission coefficient of microwave signal penetrating from matching medium into head and provide initial reconstructions for both matching media. For the second matching medium only, a feasibility study is performed to determine the optimal working conditions using root mean square error metrics. The best reconstructions are provided to demonstrate the potential of differential microwave imaging in pursuing the temperature monitoring task.
THE INFLUENCE OF FRACTURE CHARACTERISTICS ON GROUNDWATER FLOW SYSTEMS IN FRACTURED IGNEOUS AND METAMORPHIC ROCKS OF NORTH CAROLINA (USA)

The yield of water wells drilled in crystalline rock aquifers is determined by the occurrence and interaction of open saturated fractures which decrease with increased depth outside of the influence of large-scale features such as fault zones. These trends suggest that in the shallow subsurface (i) fluid flow is controlled by specific fracture types and (ii) there is a bounding depth below which groundwater flow is significantly reduced. These hypotheses are tested in this paper. The analysis of fracture properties identified in boreholes offers an approach to investigate the depth evolution of groundwater systems in crystalline rocks. Optical televiewer caliper and heat pulse flow meter logs are utilized to investigate the attributes distributions orientations and the contribution to flow of 570 fractures that intersect 26 bedrock wells drilled in crystalline rocks of North Carolina. Results indicate that the dominant fracture types are foliation parallel fractures (FPFs) (42%) other fractures (32%) and sheet joints (26%). The boreholes are drilled into five lithologic terranes and intersect seven major lithologic and rock fabric types consisting of: (1) felsic gneiss (2) andesitic to basaltic flows (3) diorite (4) mafic gneiss (5) gneiss and amphibolite (6) gneiss and mylonite and (7) schist. The dominant fracture type in the upper 40 m is sheet joints. Rocks with sub-horizontal planar fabric prefer to develop FPFs instead of sheet joints. Fractures with the largest apertures are mostly restricted to shallow depths where sheet joints dominate. However some sheet joints and FPFs with large apertures are observed at depths greater than 40 m. Flow intervals identified from borehole logs reveal that sheet joints and FPFs are the dominant fracture type where the majority of flow is observed and are therefore likely to control most of the flow in the shallow subsurface. In contrast FPFs and other fractures are the dominant conduits for channeling flow at greater depths. Fracture and flow analyses indicate that the majority of flow (> 80%) occurs at depths shallower than 75 m suggesting the existence of a bounding depth in the shallow subsurface below which permeabilities of fractured crystalline rocks are significantly reduced.
New soil physical properties implemented in the Unified Model at PS18

This note describes the improvements to the Unified Model (UM) soil hydraulic and thermal properties implemented in Parallel Suite 18 (PS18) that became operational in April 2008. Also described are trials of a two-stream multi-layer canopy radiation scheme that has been implemented in PS20 and became operational in November 2008. The soil hydraulic properties affect the soils ability to hold water and the rate at which water moves through the soil. The soil moisture together with the soil hydraulic properties control transpiration from plants and direct evaporation from bare soil. The UM soil hydraulic properties are derived using the Cosby et al (1984) equations from information about soil texture; fractions of sand, silt and clay particles. Also, the soil thermal conductivity and heat capacity both depend on soil moisture and soil texture, so that these properties in turn influence the land surface temperature. Thus, soil moisture and the soil physical properties control the partitioning of net surface radiation into sensible, latent and ground heat fluxes. Improvements to the calculation of the soil thermal conductivity result in a reduction of the models northern hemisphere (NH) summer warm bias by about 0·2 K and a reduction in the models NH winter cold bias by over 0·5 K. Average errors in screen temperature for the NH winter are reduced by about 10%. During the summer, the new soil thermal conductivity gives a greater flow of heat from the surface into the ground which results in atmospheric cooling. While in winter, there is a greater flow of heat from the ground towards the surface resulting in a warming of the atmosphere. The direction of the ground heat flux depends on the vertical temperature gradient. Improvements to the model soil hydraulic parameters are found to significantly increase the model soil moisture, by reducing surface evaporation. The new soil hydraulic properties also significantly reduce errors in screen temperature and humidity. However, by reducing surface evaporation, the new soil hydraulic parameters cause the model to become warmer during the summer. The new two-stream multi-layer canopy radiation scheme is found to cool the model by about 0·25 K during the summer. In our trials, the effect of the full changes is to eliminate the UM NH summer warm bias.
Space Shuttle: A Test Vehicle for the Reliability of the SkyWater 130nm PDK for Future Space Processors

Recently the ASIC industry experiences a massive change with more and more small and medium businesses entering the custom ASIC development. This trend is fueled by the recent open hardware movement and relevant government and privately funded initiatives. These new developments can open new opportunities in the space sector – which is traditionally characterised by very low volumes and very high non-recurrent (NRE) costs – if we can show that the produced chips have favourable radiation properties. In this paper, we describe the design and tape-out of Space Shuttle, the first test chip for the evaluation of the suitability of the SkyWater 130nm PDK and the OpenLane EDA toolchain using the Google/E-fabless shuttle run for future space processors.
The Impact of International Student Mobility on Multicultural Competence and Career Development: The Case of Students from Latin America and the Caribbean in Barcelona

Every year, an increasing number of students decide to study abroad in non-English-speaking countries, and Spain is recently a very popular destination within Latin American and Caribbean (LAC) communities. This paper attempts to deepen our knowledge of the impact of international student mobility (ISM) on students’ multicultural identity and career development. To do so, the experiences of 10 LAC students who completed a one-year degree programme in Barcelona are examined. Semi-structured interviews were employed to evaluate the international experiences one year after their completion. During their post-mobility interviews, participants were able to reflect on the ISM through a structured dialogue that allowed them to analyse the experience from a distance. Findings indicate that the ISM helped them to grow personally and professionally and, one year after the stay, they are aware of this evolution. They show an increase in their self-confidence, and they see the experience as an opportunity for personal maturity. This suggests that universities should consider the importance of offering guidance to these students when they end their master’s degree and are considering their plans for the future.
Fusion of fMRI Multisource Data Using a Two-stream Separable 3D Network for the Diagnosis of Autism Spectrum Disorder

With the continuous development of neuroscience, the computer-aided diagnosis of autism spectrum disorder (ASD) has become a widely studied topic. An increasing number of research results have shown that functional connectivity networks (FCNs) based on resting-state functional magnetic resonance imaging (rs-fMRI) are effective in aiding the diagnosis of various neurological disorders including ASD. However, most conventional FCNs are static low-level networks based on pairwise correlations between brain regions, ignoring the time-varying nature of brain activity and high-level interactions across multiple brain regions of interest (ROIs), which limits application to brain disease diagnosis. In response to the above problems, we propose to fuse features from low-order and high-order dynamic functional connectivity data to train an ensemble classifier to improve classification performance. We first obtained dynamic functional connectivity networks (D-FCNs) based on the sliding window method, and then constructed new high-order dynamic functional connectivity networks based on the principle of “correlation of correlations” to further explore the higher-level and more complex interactions between multiple brain regions of interest. We then normalized and thresholded the dynamic functional connectivity data for both modalities to reduce the effects of noise and weak connectivity. In addition, considering that the fusion of multimodal data by supervised deep learning methods has shown more and more promising application prospects in the field of neuroimaging, we extracted the spatio- temporal features of low-order D-FCNs and high-order D-FCNs respectively through a Two- Stream separable 3D network and performed fusion classification for the diagnosis of ASD and normal control subjects. Our method achieved good ASD classification accuracy and verified that high-order dynamic functional connectivity data could provide additional information for ASD diagnosis.
Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study

Background Suboptimal diet is an important preventable risk factor for non-communicable diseases (NCDs); however, its impact on the burden of NCDs has not been systematically evaluated. This study aimed to evaluate the consumption of major foods and nutrients across 195 countries and to quantify the impact of their suboptimal intake on NCD mortality and morbidity. Methods By use of a comparative risk assessment approach, we estimated the proportion of disease-specific burden attributable to each dietary risk factor (also referred to as population attributable fraction) among adults aged 25 years or older. The main inputs to this analysis included the intake of each dietary factor, the effect size of the dietary factor on disease endpoint, and the level of intake associated with the lowest risk of mortality. Then, by use of disease-specific population attributable fractions, mortality, and disability-adjusted life-years (DALYs), we calculated the number of deaths and DALYs attributable to diet for each disease outcome. Findings In 2017, 11 million (95% uncertainty interval [UI] 10–12) deaths and 255 million (234–274) DALYs were attributable to dietary risk factors. High intake of sodium (3 million [1–5] deaths and 70 million [34–118] DALYs), low intake of whole grains (3 million [2–4] deaths and 82 million [59–109] DALYs), and low intake of fruits (2 million [1–4] deaths and 65 million [41–92] DALYs) were the leading dietary risk factors for deaths and DALYs globally and in many countries. Dietary data were from mixed sources and were not available for all countries, increasing the statistical uncertainty of our estimates. Interpretation This study provides a comprehensive picture of the potential impact of suboptimal diet on NCD mortality and morbidity, highlighting the need for improving diet across nations. Our findings will inform implementation of evidence-based dietary interventions and provide a platform for evaluation of their impact on human health annually.