Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling galaxies with $f(E,L_z)$: a black hole in M32

A technique for the construction of axisymmetric distribution functions for individual galaxies is presented. It starts from the observed surface bright- ness distribution, which is deprojected to gain the axisymmetric luminosity density, from which follows the stars' gravitational potential. After adding dark mass components, such as a central black hole, the two-integral distribu- tion function (2I-DF) f(E,Lz), which depends only on the classical integrals of motion in an axisymmetric potential, is constructed using the Richardson- Lucy algorithm. This algorithm proved to be very efficient in finding f(E,Lz) provided the integral equation to be solved has been properly modified. Once the 2I-\df\ is constructed, its kinematics can be computed and compared with those observed. Many discrepancies may be remedied by altering the assumed inclination angle, mass-to-light ratio, dark components, and odd part of the 2I-DF. Remaining discrepancies may indicate, that the distribution function depends on the non-classical third integral, or is non-axisymmetric. The method has been applied to the nearby elliptical galaxy M32. A 2I-DF with ~55 degrees inclination and a central black hole (or other compact dark mass inside ~1pc) of 1.6-2*10^6 Msun fits the high-spatial-resolution kinema- tic data of van der Marel et al. remarkably well. 2I-DFs with a significantly less or more massive central dark mass or with edge-on inclination can be ruled out for M32. Predictions are made for HST-observations: spectroscopy using its smallest square aperture of 0.09"*0.09" should yield a non-gaussian central velocity profile with broad wings, true and gaussian-fit velocity dispersion of 150-170km/s and 120-130km/s, respectively.
Enjoyment of Physical Activity among Children and Adolescents: A Concept Analysis

Although enjoyment has been linked to participation in physical activity (PA), a thorough analysis of the concept is lacking. Health-related behavior research emphasizes the necessity of focusing on individual psychological requirements, such as enjoyment in PA, to boost children and adolescents’ motivation for PA. The current paper is a report on a conceptual analysis of the enjoyment of PA among children and adolescents. We adopted the concept analysis procedure by Walker and Avant. Several databases (PubMed, CINAHL, ERIC, PsychInfo, and Sport Discus) were searched and used to extract relevant articles about the enjoyment of PA. The review process yielded a final set of 72 papers. A refined definition of enjoyment in PA, attributes, cases, antecedents, and consequences of enjoyment in PA were presented. A conceptual understanding of enjoyment in PA can enable nurses to plan interventions that help children and adolescents get appropriate PA and improve their health habits.
Longitudinal Postvaccine SARS-CoV-2 Immunoglobulin G Titers, Memory B-Cell Responses, and Risk of COVID-19 in Multiple Sclerosis Over 1 Year

Background and Objectives Some disease-modifying treatments impair response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in multiple sclerosis (MS), potentially increasing the risk of breakthrough infections. We aimed to investigate longitudinal SARS-CoV-2 antibody dynamics and memory B cells after 2 and 3 messenger RNA (mRNA) vaccine doses and their association with the risk of COVID-19 in patients with MS on different treatments over 1 year. Methods Prospective observational cohort study in patients with MS undergoing SARS-CoV-2 mRNA vaccinations. Antispike (anti-S) immunoglobulin G (IgG) titers were measured by chemiluminescence microparticle immunoassay. Frequencies of spike-specific memory B cells were measured on polyclonal stimulation of peripheral blood mononuclear cells and screening of secreted antibodies by ELISA. Results We recruited 120 patients with MS (58 on anti-CD20 antibodies, 9 on sphingosine 1-phosphate (S1P) receptor modulators, 15 on cladribine, 24 on teriflunomide (TFL), and 14 untreated) and collected 392 samples up to 10.8 months after 2 vaccine doses. When compared with untreated patients, anti-CD20 antibodies (β = −2.07, p < 0.001) and S1P modulators (β = −2.02, p < 0.001) were associated with lower anti-S IgG, while TFL and cladribine were not. Anti-S IgG decreased with months since vaccine (β = −0.14, p < 0.001), independently of treatments. Within anti-CD20 patients, anti-S IgG remained higher in those with greater baseline B-cell counts and were not influenced by postvaccine anti-CD20 infusions. Anti-S IgG increase after a 3rd vaccine was mild on anti-CD20 and S1P modulators. Spike-specific memory B-cell responses were weaker on S1P modulators and anti-CD20 than on TFL and influenced by postvaccine anti-CD20 infusions. The frequency of breakthrough infections was comparable between DMTs, but the risk of COVID-19 was predicted by the last measured anti-S IgG titer before infection (OR = 0.56, 95% CI = 0.37–0.86, p = 0.008). Discussion Postvaccine anti-S IgG titers decrease over time regardless of MS treatment and are associated with breakthrough COVID-19. Both humoral and specific memory B-cell responses are diminished on S1P modulators. Within anti-CD20–treated patients, B-cell count at first vaccine determines anti-S IgG production, whereas postvaccine anti-CD20 infusions negatively affect spike-specific memory B cells.
A Novel Automated Approach to Mutation-Cancer Relation Extraction by Incorporating Heterogeneous Knowledge

Automatic extraction of relations between gene mutations and cancer entities occurring in the cancer literature using text mining can rapidly provide vital information to support precision cancer medicine. However, mutation-cancer relation extraction is more challenging than general relation extraction from free text, since it is often not possible without cancer-specific background knowledge and thus the model replies on a deeper understanding of complex surrounding tokens. We propose a deep learning model that jointly extracts mutations and their associated cancers. Background knowledge comes from two different knowledge bases which store different types of information about mutations. Given the different ways in which knowledge is stored in these two resources, we propose two separate methods for embedding knowledge, namely sentence-based knowledge integration and attribute-aware knowledge integration. The evaluation demonstrated that our model outperforms a number of baseline models and gains 96.00%, 92.57% and 94.57% F1 scores on three public datasets, EMU BCa, EMU PCa, and BRONCO, thus illustrating the effectiveness of our knowledge integration approach. The auxiliary experiments show that our models can utilize more informative text from the KBs and link the mutations to their corresponding cancer disease although the input text provides insufficient context.
CORRELATION OF CATHODOLUMINESCENCE INHOMOGENEITY WITH MICROSTRUCTURAL DEFECTS IN EPITAXIAL GAN GROWN BY METALORGANIC CHEMICAL-VAPOR DEPOSITION

We discuss the relationship between microstructure and luminescence efficiency for heteroepitaxial films of GaN grown on c-axis sapphire substrates by metalorganic chemical-vapor deposition. We directly characterize the correlation between threading dislocations as observed by transmission electron microscopy, surface morphology as observed by atomic force microscopy, and wavelength-resolved cathodoluminescence imaging. We show that the inhomogeneity in the luminescence intensity of these films near band edge can be accounted for by a simple model where nonradiative recombination at threading dislocations causes a deficiency of minority carriers and results in dark regions of the epilayer. An upper bound for average diffusion length is estimated to be 250 nm.
Noise correlation and its impact on the performance of multi‐material decomposition‐based spectral imaging in photon‐counting CT

Abstract Purpose It has been known that noise correlation plays an important role in the determination of the performance of spectral imaging based on two‐material decomposition (2‐MD). To further understand the basics of spectral imaging in photon‐counting CT toward optimal design and implementation, we study the noise correlation in multi‐MD (m‐MD) and its impact on the performance of spectral imaging. Method We derive the equations that characterize the noise and noise correlation in the material‐specific (basis) images in m‐MD, followed by a simulation study to verify the derived equations and study the noise correlation's impact on the performance of spectral imaging. Using a specially designed digital phantom, the study of noise correlation runs over the cases of two‐, three‐, and four‐MD (2‐MD, 3‐MD, and 4‐MD). Then, the noise correlation's impact on the performance of spectral imaging in photon‐counting CT is investigated, using a modified Shepp–Logan phantom. Results The results in 2‐MD show that, in‐line with what has been reported in the literature, the noise correlation coefficient between the material‐specific images corresponding to the basis materials approaches −1. The results in m‐MD (m ≥ 3) are more complicated and interesting, as the noise correlation coefficients between a pair of the material‐specific images alternate between ±1, and so do in the case of 4‐MD. The m‐MD data show that the noise in virtual monochromatic imaging (a form of spectral imaging) is moderate even though the noises in material‐specific (basis) images vary drastically. Conclusions The observation of noise correlation in 3‐MD, 4‐MD, and beyond (i.e., m‐MD) is informative to the community. The relationship between noise correlation and the performance of spectral imaging revealed in this work may help clinical medical physicists understand the fundamentals of spectral imaging based on MD and optimize the performance of spectral imaging in photon‐counting CT and other X‐ray imaging modalities.
The association between autistic traits and serum testosterone, oxytocin, and androstenedione levels in prepubertal male drug naive children with attention‐deficit/hyperactivity disorder

Children with attention‐deficit/hyperactivity disorder (ADHD) might have similar problems as in autism spectrum disorder (ASD) and show impairment in social behaviour. Also, there is a relationship between social relationship skills and ToM (theory of mind) skills of children with ADHD. Besides, ASD is associated with prenatal exposure to high levels of androgens, and oxytocin plays a role in the modulation of emotions, coping with stress, and social behaviour like ASD. In this study, the relationship between autistic traits and serum oxytocin, testosterone, and androstenedione levels in prepubertal male drug naive children with ADHD has been investigated.
Changes in the prevalence of metabolic syndrome in Korean adults after the COVID-19 outbreak

OBJECTIVES This study sought to reveal changes in the prevalence of metabolic syndrome (MetS) after the start of the coronavirus disease 2019 (COVID-19) pandemic and to identify the groups showing the greatest changes. METHODS We compared the prevalence of MetS between 2017–2019 (i.e., the 3-year period before the COVID-19 pandemic) and soon after the initial outbreak of COVID-19 in 2020 among 24,564 adults ≥19 years of age using data from the Korea National Health and Nutrition Examination Survey. RESULTS The prevalence of MetS increased steadily between 2017 and 2020 (29.4 to 35.3%, p for trend <0.001), with annual percent changes of 2.0%p, 2.2%p, and 1.7%p, respectively. Compared to 3 years before the COVID-19 pandemic, the prevalence of MetS significantly increased during the COVID-19 pandemic in males (6.2%p; 95% confidence interval [CI], 3.5 to 8.9) compared to females (1.5%p; 95% CI, −1.2 to 4.1). The age groups with the greatest increases in MetS prevalence after the COVID-19 pandemic were those in their 40s (4.6%p; 95% CI, 0.9 to 8.4) and 50s (5.8%p; 95% CI, 2.2 to 9.4). By educational background, the increase in MetS prevalence was greatest among those with a college degree or higher (5.1%p). The prevalence of MetS in high-income (5.3%p) and low-income (4.6%p) groups significantly increased. CONCLUSIONS The increasing trend in the overall prevalence of MetS continued during the COVID-19 pandemic. In particular, the prevalence of MetS among adult males in their 40s and 50s increased significantly after the COVID-19 outbreak in Korea.
Classification of SSVEP-EEG signals using CNN and Red Fox Optimization for BCI applications

Classification of electroencephalography (EEG) signals associated with Steady-state visually evoked potential (SSVEP) is prominent because of its potential in restoring the communication and controlling capability of paralytic people. However, SSVEP signals classification is a challenging task for researchers because of its low signal-to-noise ratio, non-stationary and high dimensional properties. A proficient technique has to be evolved to classify the SSVEP-based EEG data. In recent times, convolutional neural network (CNN) has reached a quantum leap in EEG signal classification. Therefore, the proposed system employs CNN to classify the SSVEP-based EEG signals. Though CNN has proved its proficiency in handling EEG signal classification problems, the calibration of hyperparameters is required to enhance the performance of the model. The calibration of a hyperparameter is a time-consuming task, hence proposed an automated hyperparameter optimization technique using the Red Fox Optimization Algorithm (RFO). The effectiveness of the algorithm is evaluated by comparing it with the performance of Harris Hawk Optimization (HHO), Flower Pollination Algorithm (FPA), Grey Wolf Optimization Algorithm (GWO) and Whale Optimization Algorithm (WOA) based hyperparameter optimized CNN applied to the SSVEP based EEG signals multiclass dataset. The experimental results infer that the proposed algorithm can achieve a testing accuracy of 88.91% which is higher than other comparative algorithms like HHO, FPA, GWO and WOA. The above-mentioned values clearly show that the proposed algorithm achieved competitive performance when compared to the other reported algorithm.
Temperature dependence of $\eta/s$: uncertainties from the equation of state

We perform a global model-to-data comparison on Au+Au collisions at $\sqrt{s_{NN}}=200$ GeV and Pb+Pb collisions at $2.76$ TeV and $5.02$ TeV, using a 2+1D hydrodynamics model with the EKRT initial state and a shear viscosity over entropy density ratio $(\eta/s)(T)$ with a linear $T$ dependence. To quantify the amount of uncertainty due to the choice of the equation of state (EoS), we compare analysis results based on four different EoSs: the well known $s95p$ parametrisation, an updated parametrisation based on the same list of particles in hadron resonance gas, but using recent lattice results for the partonic part of the EoS, and two new parametrisations based on the Particle Data Group 2016 particle list and the recent lattice results. We find that the choice of the EoS does affect the favoured minimum value of $\eta/s$, although within the confidence limits of the analysis. On the other hand, our analysis hardly constrains the temperature dependence of $\eta/s$, no matter the EoS.
Prediction of pathological staging and grading of renal clear cell carcinoma based on deep learning algorithms

Objective Deep learning algorithms were used to develop a model for predicting the staging and grading of renal clear cell carcinoma to inform clinicians’ treatment plans. Methods Clinical and pathological information was collected from 878 patients diagnosed with renal clear cell carcinoma in the Department of Urology, Peking University First Hospital. The patients were randomly assigned to the test set (n = 702) or the verification set (n = 176). Pathological staging and grading of renal clear cell carcinoma were predicted by preoperative clinical variables using deep learning algorithms. Receiver operating characteristic curves were used to evaluate the predictive accuracy as measured by the area under the receiver operating characteristic curve (AUC). Results For tumor pathological staging, AUC values of 0.933, 0.947, and 0.948 were obtained using the BiLSTM, CNN-BiLSTM, and CNN-BiGRU models, respectively. For tumor pathological grading, the AUC values were 0.754, 0.720, and 0.770, respectively. Conclusions The proposed model for predicting renal clear cell carcinoma allows for accurate projection of the staging and grading of renal clear cell carcinoma and helps clinicians optimize individual treatment plans.
COVID-19 and Excess All-Cause Mortality in the US and 20 Comparison Countries, June 2021-March 2022.

This study compares the COVID-19 per capita overall and excess mortality rates in the US vs rates for 20 Organization for Economic Co-operation and Development countries and the timing of any increases in excess mortality between June 2021 and December 2021 (Delta) and December 2021 to March 2022 (Omicron).
Humoral and Cellular Response of Transplant Recipients to a Third Dose of mRNA SARS-CoV-2 Vaccine: A Systematic Review and Meta-analysis

Background. High rates of nonresponse to 2 doses of mRNA severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine have been reported in transplant recipients. Several studies have investigated the efficacy of a third dose in this population. However, efficacy remains unclear, as response rates vary across studies. Therefore, we conducted a systematic review and meta-analysis to determine the efficacy of a third dose of any mRNA SARS-CoV-2 vaccine in transplant recipients. Methods. Preferred Reporting Items for Systematic Review and Meta-Analysis reporting guidelines (PROSPERO:CRD42021281498) were followed. Medline, Embase, and CENTRAL were searched from inception to December 2, 2021, without restrictions. All full-text studies reporting on the efficacy of a third dose of any mRNA SARS-CoV-2 vaccine in pediatric and adult transplant recipients were included. The National Institutes of Health quality assessment tool for case series and the Cochrane risk of bias tool determined study quality. Meta-analysis was performed via the DerSimonian-Laird random-effect model. Results. Of 84 records, 12 studies totaling 1257 patients met inclusion criteria. One study was a randomized controlled trial, whereas all other studies were observational. Across 7 studies (801 patients), humoral response after 3 doses was observed in 66.1% (95% confidence interval, 62.8%-69.4%; I2 = 0%) of transplant recipients. Triple immunosuppression, mycophenolate, antiproliferatives, and belatacept use were associated with reduced odds of humoral response in studies reporting multivariate analyses. Transplant recipients receiving a third dose displayed higher levels of neutralizing antibodies to SARS-CoV-2 variants (Alpha, Beta, and Delta) compared with placebo. Conclusions. A third dose SARS-CoV-2 mRNA vaccine should be strongly considered in transplant recipients. Limitations included lack of controlled studies and clinically relevant thresholds to determine response to vaccination.
The type Ia supernova rate in z ⩽ 1 galaxy clusters: implications for progenitors and the source of cluster iron

The iron mass in galaxy clusters is about six times larger than could have been produced by core-collapse supernovae (SNe), assuming the stars in the cluster formed with a standard initial mass function (IMF). SNe Ia have been proposed as the alternative dominant iron source. Different SN Ia progenitor models predict different 'delay functions', between the formation of a stellar population and the explosion of some of its members as SNe Ia. We use our previous measurements of the cluster SN Ia rate at high redshift to constrain SN Ia progenitor models and the star-formation epoch in clusters. The low observed rate of cluster SNe Ia at z ∼ 0-1 means that, if SNe Ia produced the observed amount of iron, they must have exploded at even higher z. This puts a >95 per cent upper limit on the mean SN Ia delay time of τ 3 Gyr. If these SFHs are confirmed, the entire range of τ will be ruled out. Cluster enrichment by core-collapse SNe from a top-heavy IMF will then remain the only viable option.
Toward effectiveness and agility of network security situational awareness using moving target defense (MTD)

Most enterprise networks are built to operate in a static configuration (e.g., static software stacks, network configurations, and application deployments). Nonetheless, static systems make it easy for a cyber adversary to plan and launch successful attacks. To address static vulnerability, moving target defense (MTD) has been proposed to increase the difficulty for the adversary to launch successful attacks. In this paper, we first present a literature review of existing MTD techniques. We then propose a generic defense framework, which can provision an incentive-compatible MTD mechanism through dynamically migrating server locations. We also present a user-server mapping mechanism, which not only improves system resiliency, but also ensures network performance. We demonstrate a MTD with a multi-user network communication and our data shows that the proposed framework can effectively improve the resiliency and agility of the system while achieving good network timeliness and throughput performance.
AGN-enhanced outflows of low-ionization gas in star-forming galaxies at 1.7

This work is supported by funding from the European Research Council Advanced Grant ERC–2010–AdG–268107–EARLY and by INAF Grants PRIN 2010, PRIN 2012 and PICS 2013. AC, OC, and MT acknowledge the grant MIUR PRIN 2010–2011. MB acknowledges support from the FP7 grant ‘eEASy’: (CIG 321913). RA acknowledges support from the ERC Advanced Grant 695671 ‘QUENCH’. We acknowledge the grants ASI n.I/023/12/0 ‘Attivita relative alla fase B2/C per la missione Euclid’ and MIUR PRIN 2010-2011 ‘The dark Universe and the cosmic evolution of baryons: from current surveys to Euclid’ and PRIN MIUR 2015 ‘Cosmology and Fundamental Physics: illuminating the Dark Universe with Euclid’.
Equality statements as rules for transforming arithmetic notation

This thesis explores children’s conceptions of the equals sign from the vantage point of notating task design. The existing literature reports that young children tend to view the equals sign as meaning “write the result here”. Previous studies have demonstrated that teaching an “is the same as” meaning leads to more flexible thinking about mathematical notation. However, these studies are limited because they do not acknowledge or teach children that the equals sign also means “can be exchanged for”. The thesis explores the “sameness” and “exchanging” meanings for the equals sign by addressing four research questions. The first two questions establish the distinction, in terms of task design, between the two meanings. Does the “can be exchanged for” meaning for the equals sign promote attention to statement form? Are the “can be exchanged for” and “is the same as” meanings for the equals sign pedagogically distinct? The final two research questions seek to establish how children might coordinate the two meanings, and connect them with their existing implicit knowledge of arithmetic principles. Can children coordinate “can be exchanged for” and “is the same as” meanings for the equals sign? Can children connect their implicit arithmetical knowledge with explicit transformations of notation? The instrument used is a specially designed notational computer-microworld called Sum Puzzles. Qualitative data are generated from trials with pairs of Year 5 (9 and 10 years), and in one case Year 8 (12 and 13 years), pupils working collaboratively with the microworld toward specified task goals. It is discovered that the “sameness” meaning is useful for distinguishing equality statements by truthfulness, whereas the “exchanging” meaning is useful for distinguishing statements by form. Moreover, a duality of both meanings can help children connect their own mental calculation strategies with transformations of properly formed notation.