Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Bulk Composition on the Atmospheric Dynamics on Close-in Exoplanets

Super Earths and mini Neptunes likely have a wide range of atmospheric compositions, ranging from low molecular mass atmospheres of H2 to higher molecular atmospheres of water, CO2, N2, or other species. Here we systematically investigate the effects of atmospheric bulk compositions on temperature and wind distributions for tidally locked sub-Jupiter-sized planets, using an idealized 3D general circulation model (GCM). The bulk composition effects are characterized in the framework of two independent variables: molecular weight and molar heat capacity. The effect of molecular weight dominates. As the molecular weight increases, the atmosphere tends to have a larger day–night temperature contrast, a smaller eastward phase shift in the thermal phase curve, and a smaller zonal wind speed. The width of the equatorial super-rotating jet also becomes narrower, and the “jet core” region, where the zonal-mean jet speed maximizes, moves to a greater pressure level. The zonal-mean zonal wind is more prone to exhibit a latitudinally alternating pattern in a higher molecular weight atmosphere. We also present analytical theories that quantitatively explain the above trends and shed light on the underlying dynamical mechanisms. Those trends might be used to indirectly determine the atmospheric compositions on tidally locked sub-Jupiter-sized planets. The effects of the molar heat capacity are generally small. But if the vertical temperature profile is close to adiabatic, molar heat capacity will play a significant role in controlling the transition from a divergent flow in the upper atmosphere to a jet-dominated flow in the lower atmosphere.
Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning

Introduction: Development and validation of a deep learning algorithm to automatically identify and locate epiretinal memberane (ERM) regions in OCT images. Methods: OCT images of 468 eyes were retrospectively collected from a total of 404 ERM patients. One expert manually annotated the ERM regions for all images. A total of 422 images (90%) and the remainig 46 images (10%) were used as the training dataset and validation dataset for deep learning algorithm training and validation, respectively. One senior and one junior clinician read the images. The diagnostic results were compared. Results: The algorithm accurately segmented and located the ERM regions in OCT images. The image-level accuracy was 95.65%, and the ERM region-level accuracy was 90.14%, respectively. In comparison experiments, the accuracies of the junior clinician improved from 85.00% to 61.29% without the assistance of the algorithm to 100.00% and 90.32% with the assistance of the algorithm. The corresponding results of the senior clinician were 96.15%, 95.00% without the assistance of the algorithm, and 96.15%, 97.50% with the assistance of the algorithm. Conclusions: The developed deep learning algorithm can accurately segment ERM regions in OCT images. This deep learning approach may help clinicians in clinical diagnosis with better accuracy and efficiency.
Brighter galaxy bias: underestimating the velocity dispersions of galaxy clusters

We study the systematic bias introduced when selecting the spectroscopic redshifts of brighter cluster galaxies to estimate the velocity dispersion of galaxy clusters from both simulated and observational galaxy catalogues. We select clusters with Ngal > 50 at five low redshift snapshots from the publicly available De Lucia & Blaziot semi-analytic model galaxy catalogue. Clusters are also selected from the Tempel SDSS DR8 groups and clusters catalogue across the redshift range 0.021 6 z 6 0.098. We employ various selection techniques to explore whether the velocity dispersion bias is simply due to a lack of dynamical information or is the result of an underlying physical process occurring in the cluster, for example, dynamical friction experienced by the brighter cluster members. The velocity dispersions of the parent dark matter (DM) halos are compared to the galaxy cluster dispersions and the stacked distribution of DM particle velocities are examined alongside the corresponding galaxy velocity distribution. We find a clear bias between the halo and the semi-analytic galaxy cluster velocity dispersion on the order of σgal/σDM � 0.87 0.95 and a distinct difference in the stacked galaxy and DM particle velocities distribution. We identify a systematic underestimation of the velocity dispersions when imposing increasing absolute I-band magnitude limits. This underestimation is enhanced when using only the brighter cluster members for dynamical analysis on the order of 5 35%, indicating that dynamical friction is a serious source of bias when using galaxy velocities as tracers of the underlying gravitational potential. In contrast to the literature we find that the resulting bias is not only halo mass-dependent but that the nature of the dependence changes according to the galaxy selection strategy. We make a recommendation that, in the realistic case of limited availability of spectral observations, a strictly magnitude-limited sample should be avoided to ensure an unbiased estimate of the velocity dispersion.
Bipartite quantum states and random complex networks

We introduce a mapping between graphs and pure quantum bipartite states and show that the associated entanglement entropy conveys non-trivial information about the structure of the graph. Our primary goal is to investigate the family of random graphs known as complex networks. In the case of classical random graphs, we derive an analytic expression for the averaged entanglement entropy while for general complex networks we rely on numerics. For a large number of nodes n we find a scaling where both the prefactor c and the sub-leading O(1) term ge are characteristic of the different classes of complex networks. In particular, ge encodes topological features of the graphs and is named network topological entropy. Our results suggest that quantum entanglement may provide a powerful tool for the analysis of large complex networks with non-trivial topological properties.
The importance of viruses in ventilator-associated pneumonia

Abstract Objective: Ventilator-associated pneumonia (VAP) remains a challenge. The importance of viruses in VAP is not established. We sought to determine the prevalence of viruses in VAP and the outcomes of viral VAP. Design: Retrospective study of VAP over 3 years. The frequency of a viral process represented the primary endpoint. Clinical outcomes served as secondary endpoints. We identified variables independently associated with a virus and conducted sensitivity analyses to assess the interaction between type of infection and patient characteristics. Setting: Tertiary-care referral center. Patients: The final cohort consisted of 710 patients and a virus was isolated in 5.1%. Interventions: None. Results: The most common viruses included: rhinovirus, influenza A, and cytomegalovirus. Baseline characteristics were similar between those with and without viral infections. In logistic regression, immunosuppression (adjusted odds ratio [aOR], 2.97; 95% confidence interval [CI], 1.44–6.14) and stem-cell transplantation (SCT, aOR, 3.58; 95% CI, 1.17–10.99) were independently associated with a virus. The presence of either variable performed poorly as a screening test for a virus. In-hospital (22.4% vs 21.6%; P = .869) and 30-day (32.8% vs 27.9%; P = .448) mortality rates were similar between the cohorts, respectively. Sensitivity analyses restricted to patients without a mixed viral and bacterial infection or those who were immunocompetent yielded similar results. Conclusion: Although infrequent, a range of viruses may cause VAP. Viruses more often complicate SCT and immunosuppression, but one can isolate viruses in immunocompetent subjects. Viral VAP produces severe infection and results in high mortality rates. Clinical features do not differentiate viral from nonviral VAP.
Examination of the COVID-19 Pandemic’s Impact on Mental Health From Three Perspectives: Global, Social, and Individual

The extent of the deleterious effects of the COVID-19 pandemic on mental health is recognized ubiquitously. However, these effects are subject to many modulatory factors from a plethora of domains of examination. It is important to understand the intersection of societal and individual levels for global stressors compared with local phenomena and physical-health outcomes. Here, we consider three perspectives: international/cultural, social, and individual. Both the enduring threat of COVID-19 infection and the protective measures to contain contagion have important consequences on individual mental health. These consequences, together with possible remedial interventions, are the focus of this article. We hope this work will stimulate more research and will suggest factors that need to be considered in the coordination of responses to a global threat, allowing for better preparation in the future.
A SUZAKU OBSERVATION OF NGC 4593: ILLUMINATING THE TRUNCATED DISK

We report results from a 2007 Suzaku observation of the Seyfert 1 AGN NGC 4593. The narrow Fe Kα emission line has a FWHM width ∼ 4000 km s−1, indicating emission from ≳ 5000 Rg. There is no evidence for a relativistically broadened Fe K line, consistent with the presence of a radiatively efficient outer disk which is truncated or transitions to an interior radiatively inefficient flow. The Suzaku observation caught the source in a low-flux state; comparison to a 2002 XMM-Newton observation indicates that the hard X-ray flux decreased by 3.6, while the Fe Kα line intensity and width σ each roughly halved. Two model-dependent explanations for the changes in Fe Kα line profile are explored. In one, the Fe Kα line width has decreased from ∼10,000 to ∼4000 km s−1 from 2002 to 2007, suggesting that the thin disk truncation/transition radius has increased from 1000–2000 to ≳5000 Rg. However, there are indications from other compact accreting systems that such truncation radii tend to be associated only with accretion rates relative to Eddington much lower than that of NGC 4593. In the second model, the line profile in the XMM-Newton observation consists of a time-invariant narrow component plus a broad component originating from the inner part of the truncated disk (∼300 Rg) which has responded to the drop in continuum flux. The Compton reflection component strength R is ∼ 1.1, consistent with the measured Fe Kα line total equivalent width with an Fe abundance 1.7 times the solar value. The modest soft excess, modeled well by either thermal bremsstrahlung emission or by Comptonization of soft seed photons in an optical thin plasma, has fallen by a factor of ∼20 from 2002 to 2007, ruling out emission from a region 5 lt-yr in size.
What have we learnt from real‐life research in asthma and COPD? Standards and novel designs for the future

research found that the addi-tion of low-dose oral theophylline to ICS did not reduce exacerbations among adults with COPD at high risk of exacerbation. 12 This therapeutic option has now been removed from COPD clinical guidelines and physicians should no longer prescribe low-dose oral theophylline. Pragmatic trials can also take the form of cluster randomized trials where groups of patients rather than indi-viduals are randomized. This innovative study design is practical, financially viable and enables patient factors such as adherence to be assessed. 13 are randomized, the of finding, patient follow-up and management of primary can be potentially addressed.
Track structure modelling for ion radiotherapy

In its broadest terms, doctoral dissertation entitled "Track structure modelling for ion radiotherapy" is part of the supporting research background in the development of the ambitious proton radiotherapy project currently under way at the Institute of Nuclear Physics PAN in Krak\'ow. Another broad motivation was the desire to become directly involved in research on a topical and challenging subject of possibly developing a therapy planning system for carbon beam radiotherapy, based in its radiobiological part on the Track Structure model developed by prof. Robert Katz over 50 years ago. Thus, the general aim of this work was, firstly, to recapitulate the Track Structure model and to propose an updated and complete formulation of this model by incorporating advances made by several authors who had contributed to its development in the past. Secondly, the updated and amended (if necessary) formulation of the model was presented in a form applicable for use in computer codes which would constitute the "radiobiological engine" of the future therapy planning system for carbon radiotherapy, which the Krak\'ow ion radiotherapy research group wishes to develop. Lastly, currently available radiobiology data were analysed in terms of Track Structure Theory to supply exemplary parameters for cell lines (preferably, exposed in normal and anoxic conditions) to be used as possible input for carbon ion radiotherapy planning studies.
Optical supernova remnants in nearby galaxies and their influence on star formation rates derived from Hα emission

In this paper we present the most up-to-date list of nearby galaxies with optically detected supernova remnants (SNRs). We discuss the contribution of the H{\alpha} flux from the SNRs to the total H{\alpha} flux and its influence on derived star formation rate (SFR) for 18 galaxies in our sample. We found that the contribution of SNRs' flux to the total H{\alpha} flux is 5 $\pm$ 5 per cent. Due to the observational selection effects, the SNRs contamination of SFRs derived herein represents only a lower limit.
Emerging of Multidrug-Resistant Cronobacter sakazakii Isolated from Infant Supplementary Food in China

As a foodborne pathogen, Cronobacter can cause serious infections in restricted populations and lead to death or chronic sequelae. Although a number of investigations showed that Cronobacter isolates are susceptible to most antimicrobial agents, MDR Cronobacter isolates, isolated mainly from clinical cases but occasionally from foods, have been reported in recent years. ABSTRACT Cronobacter is a foodborne pathogen associated with severe infections in restricted populations and particularly with high mortality in neonates and infants. The prevalence and antimicrobial resistance (AMR) phenotype of Cronobacter cultured from powdered infant formula and supplementary food were studied. The virulence factors, AMR genes, and genomic environments of the multidrug-resistant isolates were further studied. A total of 1,055 Cronobacter isolates were recovered from 12,105 samples of powdered infant formula and supplementary food collected from 29 provinces between 2018 and 2019 in China. Among these, 1,048 isolates were from infant supplementary food and 7 were from powdered infant formula. Regarding antimicrobial resistance susceptibility, 11 (1.0%) isolates were resistant and two showed resistance to four antimicrobials (ampicillin [AMP], tetracycline [TET], sulfamethoxazole-trimethoprim [SXT], and chloramphenicol [CHL]), defined as MDR. These two MDR isolates were subsequently identified as Cronobacter sakazakii sequence type 4 (ST4) (C. sakazakii Crono-589) and ST40 (C. sakazakii Crono-684). Both MDR isolates contain 11 types of virulence genes and 7 AMR genes on their genomes. Meanwhile, the IncFIB plasmids of both MDR C. sakazakii isolates also harbored 2 types of virulence genes. Results of the genomic comparative analysis indicated that food-associated C. sakazakii could acquire antimicrobial resistance determinants through horizontal gene transfer (HGT). IMPORTANCE As a foodborne pathogen, Cronobacter can cause serious infections in restricted populations and lead to death or chronic sequelae. Although a number of investigations showed that Cronobacter isolates are susceptible to most antimicrobial agents, MDR Cronobacter isolates, isolated mainly from clinical cases but occasionally from foods, have been reported in recent years. In this study, we successfully identified two MDR Cronobacter sakazakii isolates from infant foods based on nationwide surveillance and genome sequencing in China. Genomic analysis revealed that these two MDR C. sakazakii strains acquired resistance genes from other species via different evolution and transmission routes. It is important to monitor MDR C. sakazakii isolates in infant foods, and appropriate control measures should be taken to reduce the contamination with and transmission of this MDR bacterium.
Measurements of branching fraction ratios and CP-asymmetries in suppressed B- -> D(-> K+ pi(-))K- and B- -> D(-> K+ pi(-))pi(-) decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- ->D(->K^+ pi^-)K^- and B^- ->D(->K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- ->D(->K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- ->D(->K^+ pi^-)pi^- decay are also reported.
Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning

Background/aims Fundus fluorescein angiography (FFA) is an important technique to evaluate diabetic retinopathy (DR) and other retinal diseases. The interpretation of FFA images is complex and time-consuming, and the ability of diagnosis is uneven among different ophthalmologists. The aim of the study is to develop a clinically usable multilevel classification deep learning model for FFA images, including prediagnosis assessment and lesion classification. Methods A total of 15 599 FFA images of 1558 eyes from 845 patients diagnosed with DR were collected and annotated. Three convolutional neural network (CNN) models were trained to generate the label of image quality, location, laterality of eye, phase and five lesions. Performance of the models was evaluated by accuracy, F-1 score, the area under the curve and human-machine comparison. The images with false positive and false negative results were analysed in detail. Results Compared with LeNet-5 and VGG16, ResNet18 got the best result, achieving an accuracy of 80.79%–93.34% for prediagnosis assessment and an accuracy of 63.67%–88.88% for lesion detection. The human-machine comparison showed that the CNN had similar accuracy with junior ophthalmologists. The false positive and false negative analysis indicated a direction of improvement. Conclusion This is the first study to do automated standardised labelling on FFA images. Our model is able to be applied in clinical practice, and will make great contributions to the development of intelligent diagnosis of FFA images.
Systematic Review and Meta-Synthesis about Patients with Hematological Malignancy and Palliative Care

Objective: The current study aims to review, appraise, and synthesize the available studies and recommend the significant clinical implications for healthcare professionals to understand the existing findings of palliative care experience among patients with hematology malignancy. Methods: After excluding the registered or ongoing systematic reviews in the PROSPERO database regarding the lived experience of palliative care among patients with HM, our systematic review and meta-analysis protocol was registered in PROSPERO [CRD42021270311]. A search for published articles in English between January 2000 and December 2020 was conducted among different electronic databases using PRISMA guidelines 2020. Meta-synthesis was accomplished using the JBI meta-aggregation method to synthesize the findings. The implemented approach involved all qualitative research and mixed-method studies that included a qualitative part. Results: This review contained eight studies which led to 25 codes and seven categories. Finally, three synthesized themes were developed: (1) Approaching the end of life among patients with Hematology Malignancy, (2) submission and surrender of patients with Hematology Malignancy during their terminal stage, and (3) Entrance to the palliative care world. Therefore, realizing the importance of palliative care services to patients with Hematology Malignancy by providing evidence-based education and timely referral is crucial. Conclusion: There was a substantial increase in the HMs rate with late referral to palliative care services. The results of this review may draw attention to some issues reported by patients with Hematology Malignancy. Scaling up palliative care services for those patients is essential to minimize end-of-life suffering and the long-term impact of inadequate palliative care for patients with Hematology Malignancy.
Electromechanical Coupling in Electroactive Polymers – a Visual Analysis of a Third-Order Tensor Field

Electroactive polymers are frequently used in engineering applications due to their ability to change their shape and properties under the influence of an electric field. This process also works vice versa, such that mechanical deformation of the material induces an electric field in the EAP device. This specific behavior makes such materials highly attractive for the construction of actuators and sensors in various application areas. The electromechanical behaviour of electroactive polymers can be described by a third-order coupling tensor, which represents the sensitivity of mechanical stresses concerning the electric field, i.e., it establishes a relation between a second-order and a first-order tensor field. Due to this coupling tensor's complexity and the lack of meaningful visualization methods for third-order tensors in general, an interpretation of the tensor is rather difficult. Thus, the central engineering research question that this contribution deals with is a deeper understanding of electromechanical coupling by analyzing the third-order coupling tensor with the help of specific visualization methods. Starting with a deviatoric decomposition of the tensor, the multipoles of each deviator are visualized, which allows a first insight into this highly complex third-order tensor. In the present contribution, four examples, including electromechanical coupling, are simulated within a finite element framework and subsequently analyzed using the tensor visualization method.
Evaluation and management of temporomandibular disorders. Part 2: an orthopaedic physical therapy update on examination and clinical reasoning

ABSTRACT Temporomandibular (TM) disorders afflict many people globally and, despite the presence of existing peer-reviewed material that assists conservative orthopedic providers, recent advances in knowledge indicate that updated resources are required for students, clinicians, and educators. This two-part series builds off previously published material to present newer supplementary information that can be useful during the evaluation and management processes. Content in Part 1 of this series includes a discussion about the factors that have been shown to contribute to TM disorders, an updated perspective of relevant pain science, a discussion of self-report outcome measures, and various different topics related to the examination of patients with TM disorders. Part 2 addresses information related to the temporomandibular joint disc, joint hypermobility, oral splints, and clinical reasoning. In combination with other available publications, this two-part series provides clinicians an opportunity to improve their delivery of effective and efficient clinical services for people diagnosed with TM disorders.