Miracle-dz/UniFAR-FTUs huggingface dataset:
Biased Coverage of Political Rumors: Partisan Bias in the Media’s Coverage of Political Rumors in the 2017 Presidential Election in South Korea Through Issue Filtering and Framing

This study aims to shed light on partisan bias that may appear in conventional media’s coverage of political rumors, using the 2017 presidential election in South Korea as a context. Specifically, we strive to uncover how media’s biased coverage of political rumors is embodied in the way major news media (1) select and (2) frame news stories to damage a candidate whose partisan leaning is less compatible with their ideological tendency. In light of these goals, the results of a content analysis show that the media paid more attention to political rumors concerning a candidate with a challenging ideological stance. Further, findings document that media firms tend to frame political rumors to stress failings concerning a strength of an ideologically discrepant candidate. Essentially, the results of the current research highlight traditional media’s liabilities in biased coverage of political rumors in terms of issue filtering and framing.
Efficacy of Intra Articular Steroid Injection and Platelet Rich Plasma in Patients with Osteoarthrithis

Objective: To compare the efficacy of intra-articular steroid injection and Platelet rich plasma in patients with Osteoarthrithis. Methodology: A randomized controlled trail study was conducted at Rheumatology Division of the Department of Medicine, Pakistan Institute of Medical Sciences, Islamabad after the acceptance of synopsis from December 2017 to May 2018. A total of 122 adult patients with unilateral or bilateral osteoarthritis of knee and were randomized into two treatment groups. In Group I, patients received intra-articular steroid injections and in Group II, patients received platelet rich plasma (PRP). WOMAC score was calculated at baseline and was subsequently assessed after 06 weeks and 3 months. Results: Age and gender distribution and mean WOMAC and VAS scores were similar in both groups at baseline (p>0.05). At six weeks, mean WOMAC score in steroid group was 32.1 ± 24.1 and it was 24.9 ± 21.3 in PRP group (P=0.084). Mean VAS in steroid group was 4.5 ± 2.5 and it was 3.9 ± 2.6 in PRP group (P=0.0.158). At three months, mean WOMAC score in steroid group was 39.1 ± 24.3 SD and it was 27.1 ± 21.9 SD in PRP group (P=0.005). At three months, mean VAS in steroid group was 5.6 ± 2.6 and it was 4.1 ± 2.7 in PRP group (P=0.003). Conclusions: The study outcomes were better in patients treated with PRP as compared to intra-articular steroid injection. Mean WMOAC and VAS scores were significantly lower after three months in PRP group as compared to steroid group.
The nature of nuclear Halpha emission in LINERs

To get insight in the nature of the ionized gas in the nuclear region of LINERs we have performed a study of HST Halpha imaging of 32 LINERs. The main conclusion from this analysis is that for the large majority of LINERs (84%) an unresolved nuclear source has been identified as well as extended emission with equivalent sizes ranging from few tens till about hundredths of parsecs. Their morphologies appear not to be homogeneous being basically grouped into three classes:nuclear outflow candidates (42%), core-halo morphologies (25%) and nuclear spiral disks (14%). Clumpy structures reminiscent of young stellar clusters are not a common property on LINERs. The remaining 5 galaxies are too dusty to allow a clear view of the ionized gas distribution. A size-luminosity relation has been found between the equivalent radius of the Halpha emission and the (2-10 keV) X-ray luminosities. Both ionised gas morphologies and the size-luminosity relation are indistinguishable from those of low luminosity Seyferts, suggesting the same origin for the NLR of LINERs and Seyferts. Also a relation between soft X-rays and ionized gas has been suggested for the first time in LINERs. From multiwavelength data, only 4 out of the 32 LINERs have no evidences on an AGN nature of theirnuclear sources from multiwavelength data, but extremely obscured AGNs cannot be discarded out given the Compton thick signatures of their X-ray emission. For the confirmed AGN LINERs, their Halpha imaging favour core-halo and outflow morphologies (65% of the cases). Finally, their calculated Eddington ratios show that our LINER sources radiate at sub-Eddington regime, with core-halo systems having on average larger Eddington ratios than outflow candidates.
Non-Gaussianity in String Cosmology: A Case Study

We study non-gaussianity effects, using the $\delta N$ formalism, in a multi-field inflationary model consisting of K\"ahler moduli derived from type IIB string compactification in the large volume limit. The analytical work in this paper mostly follows the separable potential method developed by Vernizzi and Wands. The numerical analysis is then used in computing non-gaussianity beyond slow-roll regime. The possibility of the curvaton scenario is also discussed. We give the condition for the existence of the curvaton and calculate the non-guassianity generated by the curvaton decay in the large volume limit.
Identification of the true elastic modulus of high density polyethylene from tensile tests using an appropriate reduced model of the elastoviscoplastic behavior

The rheological parameters of materials are determined in the industry according to international standards established generally on the basis of widespread techniques and robust methods of estimation. Concerning solid polymers and the determination of Young's modulus in tensile tests, ISO 527-1 or ASTM D638 standards rely on protocols with poor scientific content: the determination of the slope of conventionally defined straight lines fitted to stress-strain curves in a given range of elongations. This paper describes the approach allowing for a correct measurement of the instantaneous elastic modulus of polymers in a tensile test. It is based on the use of an appropriate reduced model to describe the behavior of the material. The model comes a thermodynamical framework and allows to reproduce the behavior of an HDPE Polymer until large strains, covering the elastoviscoplastic and hardening regimes. Well-established principles of parameter estimation in engineering science are used to found the identification procedure. It will be shown that three parameters only are necessary to model experimental tensile signals: the instantaneous ('Young's') modulus, the maximum relaxation time of a linear distribution (described with a universal shape) and a strain hardening modulus to describe the 'relaxed' state. The paper ends with an assessment of the methodology. Our results of instantaneous modulus measurements are compared with those obtained with other physical experiments operating at different temporal and length scales.
Optical properties of subvisual cirrus clouds measured by the OSIRIS instrument

Satellite-based measurements with limb viewing geometry give high-quality information about the atmosphere. However, low-altitude measurements are very sensitive to thin clouds, which act as a semi-reflective layer that can screen out the lower atmosphere and the earth’s surface. The work described in this thesis demonstrates the ability to retrieve the optical properties of these clouds from observations of scattered sunlight by the OSIRIS instrument. Retrievals from satellite measurements require a radiative transfer model wellsuited to the measurement geometry. For this reason the SASKTRAN model is used, which employs full spherical geometry. Since this model was not initially intended to model cloud-particle scattering, several sources for the light-scattering properties of ice crystals – from both first-principles algorithms and from in-cloud particle measurements – were incorporated. Also, since these properties violate several simplifying assumptions of the model, modifications to the model were required. With the work described in this thesis, SASKTRAN replicates in-cloud radiance measurements with high accuracy across the measured spectrum. Cloud property retrievals are demonstrated that use SASKTRAN in an iterative retrieval technique. Assuming an effective cloud particle size, cloud particle number densities are retrieved that replicate the spectral measurements with very good accuracy. The effect of cloud properties on ozone and stratospheric aerosol retrievals is investigated. Systematic biases that result from neglecting cloud-particle scattering are discussed. Coincident measurements from another satellite instrument shows very good agreement with OSIRIS cloud properties.
TOLERÂNCIA DE PERDA DE SOLO POR EROSÃO PARA OS PRINCIPAIS SOLOS DO ESTADO DE SANTA CATARINA

Soil loss tolerance refers to the maximum rate of annual soil loss that will permit crop productivity to be obtained economically and indefinitely. Besides the usual form, it can also be used in the Universal Soil Loss Equation as a criteria to better define terrace spacing on croplands. This research work was developed during 1998, at the Agroveterinary Center/UDESC, in Lages, Santa Catarina, Brazil, to establish soil loss tolerance values by water erosion for 73 soil profiles of Santa Catarina, grouped within 19 taxonomic classes, and using three methods: (a) Method I, based on both rooting depth and textural ratio between B and A horizons; (b) Method II, similar to Method I, plus the clay content in the A horizon; and (c) Method III, similar to Method II, plus the organic matter content in the 0-20 cm soil depth and the soil permeability of the soil profile. Tolerance values for the studied soils varied from 0.15 to 1.16 mm year-1, depending on both soil type and estimation method. Latosols (except for the brown/reddish), Podzolic soils, brown structured earth, Cambisols, and Quartz sands showed lower values of soil loss tolerance by method III - which is suggested for estimating T-values for these soils - than methods I and II. Litolic soils, brunizens, red and brown/reddish structured earth, and brown/reddish Latosols showed similar soil loss tolerance values, regardless of the method used. Therefore, for these soils, any of the three methods studied can be used for estimating soil loss tolerance values.
Adaptive Estimation and Detection Techniques with Applications

Hybrid systems have been identified as one of the main directions in control theory and attracted increasing attention in recent years due to their huge diversity of engineering applications. Multiple-model (MM) estimation is the state-of-the-art approach to many hybrid estimation problems. Existing MM methods with fixed structure usually perform well for problems that can be handled by a small set of models. However, their performance is limited when the required number of models to achieve a satisfactory accuracy is large due to time evolution of the true mode over a large continuous space. In this research, variable-structure multiple model (VSMM) estimation was investigated, further developed and evaluated. A fundamental solution for on-line adaptation of model sets was developed as well as several VSMM algorithms. These algorithms have been successfully applied to the fields of fault detection and identification as well as target tracking in this thesis. In particular, an integrated framework to detect, identify and estimate failures is developed based on the VSMM. It can handle sequential failures and multiple failures by sensors or actuators. Fault detection and target maneuver detection can be formulated as change-point detection problems in statistics. It is of great importance to have the quickest detection of such mode changes in a hybrid system. Traditional maneuver detectors based on simplistic models are not optimal and are computationally demanding due to the requirement of batch processing. In this presentation, a general sequential testing procedure is proposed for maneuver detection based on advanced sequential tests. It uses a likelihood marginalization technique to cope with the difficulty that the target accelerations are unknown. The approach essen-
Profiling post-COVID syndrome across different variants of SARS-CoV-2

Background: Self-reported symptom studies rapidly increased our understanding of SARS-CoV-2 during the pandemic and enabled the monitoring of long-term effects of COVID-19 outside the hospital setting. It is now evident that post-COVID syndrome presents with heterogeneous profiles, which need characterisation to enable personalised care among the most affected survivors. This study describes post-COVID profiles, and how they relate to different viral variants and vaccination status. Methods: In this prospective longitudinal cohort study, we analysed data from 336,652 subjects, with regular health reports through the Covid Symptom Study (CSS) smartphone application. These subjects had reported feeling physically normal for at least 30 days before testing positive for SARS-CoV-2. 9,323 individuals subsequently developed Long-COVID, defined as symptoms lasting longer than 28 days. 1,459 had post-COVID syndrome, defined as more than 12 weeks of symptoms. Clustering analysis of the time-series data was performed to identify distinct symptom profiles for post-COVID patients, across variants of SARS-CoV-2 and vaccination status at the time of infection. Clusters were then characterised based on symptom prevalence, duration, demography, and prior conditions (comorbidities). Using an independent testing sample with additional data (n=140), we investigated the impact of post-COVID symptom clusters on the lives of affected individuals. Findings: We identified distinct profiles of symptoms for post-COVID syndrome within and across variants: four endotypes were identified for infections due to the wild-type variant; seven for the alpha variant; and five for delta. Across all variants, a cardiorespiratory cluster of symptoms was identified. A second cluster related to central neurological, and a third to cases with the most severe and debilitating multi-organ symptoms. Gastrointestinal symptoms clustered in no more than two specific phenotypes per viral variant. The three main clusters were confirmed in an independent testing sample, and their functional impact was assessed. Interpretation: Unsupervised analysis identified different post-COVID profiles, characterised by differing symptom combinations, durations, and functional outcomes. Phenotypes were at least partially concordant with individuals reported experiences. Our classification may be useful to understand distinct mechanisms of the post-COVID syndrome, as well as subgroups of individuals at risk of prolonged debilitation. Funding: UK Government Department of Health and Social Care, Chronic Disease Research Foundation, The Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare, UK National Institute for Health Research, UK Medical Research Council, British Heart Foundation and Alzheimers Society, and ZOE Limited, UK.
Large N field theories from superstrings

These are introductory lectures on the correspondence between SU(N) gauge theories and Superstring Theory in anti-de Sitter geometries (AdS). The subject combines a number of different topics, including supersymmetric field theory, classical and quantum physics of black holes, string theory, string dualities, conformal field theories (CFT), and quantum field theory in anti-de Sitter spaces. We also discuss applications of this AdS/CFT correspondence to the large $N$ dynamics of pure QCD.
Results of the basic-VRS trial: clinical outcomes and cost-effectiveness of basic low vision rehabilitation in Portugal

Purpose The aim of this study was twofold: i) to investigate and characterize the clinical impact of vision rehabilitation in patients with vision impairment, and ii) to investigate the cost-effectiveness of a basic vision rehabilitation service in Portugal. Methods Patients diagnosed with age-related macular degeneration or diabetic retinopathy and visual acuity in the range 0.4 to 1.0 logMAR in the better-seeing eye were recruited. Participants were randomised to one of the study arms consisting of immediate intervention and delayed intervention. The intervention included: new refractive correction, optical reading aids, in-office training and advice about modifications at home. Visual ability, health-related quality-of-life and costs of the intervention were measured. Economic analysis was performed to evaluated if the intervention was cost-effective. The trial compared the outcomes 12-weeks after the start in both arms. Results Of the 46 participants, 34(74%) were diagnosed with diabetic retinopathy, 25(54%) were female and the mean age was 70.08 yrs (SD=8.74). In the immediate intervention arm visual ability was 0.28 logits (SD=1.14) at baseline and it increased to 0.91logits (SD=1.24) after the intervention (p<0.001). Changes in the delayed intervention arm were not statistically significant (mean improvement = 0.10 logits, SE=0.11, p=0.95). Acuity in the better seeing eye, near acuity and critical print size also improved during the study. The mean cost of the intervention was 118.79EURO (SD=24.37). Incremental cost-effectiveness ratio using the EQ-5D-5L index value was 3322EURO/QALY and 1235EURO/QALY when using near acuity. Conclusions The current study gives evidence of positive clinical impact of a basic vision rehabilitation intervention and that a basic vision rehabilitation service is cost-effective. These findings are important to clinical and rehabilitation practices and for planning vision rehabilitation services.
Accurate prognosis for localized prostate cancer through coherent voting networks and multi-omic data

Background: Prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing a stratification of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring closer surveillance and timely treatment decisions. Methods: We extend a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating novel model-selection technique to counter model overfitting. The CVN method is then applied to the problem of predicting an accurate prognosis (with a time granularity of 1 year) for patients affected by prostate cancer. The CVN is developed on a discovery cohort of 495 patients from the TCGA-PRAD collection, and validated on several other independent cohorts, comprising in total of 744 patients. Findings: We uncover seven multi-gene fingerprints, each comprising six to seven genes, that correspond to different input data types (mRNA expression, proteomic assays, or methylation) and different time points, for the event of progression-free survival (PFS) in patients diagnosed with prostate adenocarcinoma, who had not received prior treatment for their disease. On the test set for the discovery cohort, we attain Odds Ratios ranging from a minimum of 12.0 and a maximum of 21.0, with average 16.8, and geometric mean p-value 0.01; Cohen kappa values ranging from a minim of 0.29 to a maximum of 0.59, with average 0.47; and AUC ranging from a minimum of 0.62 to a maximum of 0.79, with average 0.72, with geometric mean p-value 0.01; significant (< 0.05) p-values for the log-rank tests are found in six cases, with geometric mean p-value 0.0006. On seven independent cohorts for 21 combinations of cohort vs fingerprint, we report Odds Ratios ranging from a minimum of 9.0 and a maximum of 40.0, with average 17.5, geometric mean p-value 0.003; Cohen kappa values ranging from a minimum of 0.18 to a maximum of 0.65, with average 0.4; and AUC ranging from a minimum of 0.61 to a maximum of 0.88, with average 0.76, geometric mean p-value 0.001. Many of the genes in our fingerprint have recorded prognostic power in some form of cancer, and have been studied for their functional roles in cancer on animal models or cell lines. Interpretation: The development of novel ML techniques tailored to the problem of uncovering effective multi-gene prognostic biomarkers is a promising new line of attack for sharpening our capability to diversify and personalize cancer patient treatments. For the challenging problem of discriminating between indolent and aggressive types of non-metastatic prostate cancer, we show that it is possible to attain accurate prognostic prediction with a granularity within a year, which is an improvement beyond the current state of the art.
Bullying perpetration, peer victimisation, suicidality, and their cumulative effect on preadolescents' behaviour and brain development

Background Adolescents' suicidality and peer bullying are rising as a serious public health concern globally. However, the neural correlates of perpetrators and the impact of different types of bullying perpetration/peer victimisation on preadolescents needs elucidation. Besides, there has been a lack of research studying the cumulative risk pattern of bullying perpetration/peer victimisation on preadolescents with suicidality. Methods We adopted a retrospective and longitudinal methodology by utilising the data from the Adolescent Brain Cognitive Development (ABCD) cohort. Firstly, participants were assigned into two groups (i.e., perpetrators vs non-perpetrators) based on their bullying perpetration experiences. Next, different types of bullying perpetration/peer victimisation (i.e., overt, relational, and reputational) were extracted to evaluate their associations with suicidal ideation (SI), non-suicidal self-injury (NSSI), and suicide attempt (SA) separately. Then, participants were further assigned into four groups (i.e., bully-uninvolved preadolescents without suicidality/NSSI history (HC group), bully-uninvolved preadolescents with SA (SA group), preadolescents with both SA and bullying perpetration (SA+P group), and preadolescents with both SA and peer victimisation (SA+V group)). We used multinomial logistic regression models, analysis of variance (ANOVA), and brain network analysis for assessing potential associations in study's objectives. Findings In total, 9992 individuals aged 11-12 years were included in our analysis. Of these individuals, 1111 (11.1%) were classified as perpetrators, and had significantly lower bilateral cortical volume in the superior frontal sulcus (SFS), lower functional connectivity within default mode network (DMN), and lower anti-correlation between DMN and dorsal attention network (DAN) than non-perpetrators. Additionally, preadolescents' overt, relational, and reputational perpetration/ victimisation experiences were all shown to be associated with suicidality/NSSI, despite varying strengths, while overt perpetration showed the strongest association with SA (OR 3.6 [95%CI 2.4-5.4]), followed by overt victimisation (2.4 [1.6-3.5]). Besides, the SA+V group was characterised by the highest psychopathology among four groups, while the SA+P group was characterised by the highest aggression among four groups. Lastly, lower bilateral cortical volume in the precentral gyrus (PCG) while higher cortical volume in both the lateral occipitotemporal cortex (LOTC) and posterior cingulate cortex (PCC) were found in the SA+P group when compared to SA and HC group. Interpretation Findings from the present study offered empirical evidence on the impact of bullying experience, suicidality and their cumulative risk on preadolescents' behavior and brain development, contributing to the growing literature on discerning the impact of different types of bullying perpetration/peer victimisation on preadolescents.