Miracle-dz/UniFAR-FTUs huggingface dataset:
Health, socioeconomic and genetic predictors of COVID-19 vaccination uptake: a nationwide machine-learning study

Reduced participation in COVID-19 vaccination programs is a key societal concern. Understanding factors associated with vaccination uptake can help in planning effective immunization programs. We considered 2,890 health, socioeconomic, familial, and demographic factors measured on the entire Finnish population aged 30 to 80 (N=3,192,505) and genome-wide information for a subset of 273,765 individuals. Risk factors were further classified into 12 thematic categories and a machine learning model was trained for each category. The main outcome was uptaking the first COVID-19 vaccination dose by 31.10. 2021, which has occurred for 90.3% of the individuals. The strongest predictor category was labor income in 2019 (AUC evaluated in a separate test set = 0.710, 95% CI: 0.708-0.712), while drug purchase history, including 376 drug classes, achieved a similar prediction performance (AUC = 0.706, 95% CI: 0.704-0.708). Higher relative risks of being unvaccinated were observed for some mental health diagnoses (e.g. dissocial personality disorder, OR=1.26, 95% CI : 1.24-1.27 ) and when considering vaccination status of first-degree relatives (OR=1.31, 95% CI:1.31-1.32 for unvaccinated mothers) We derived a prediction model for vaccination uptake by combining all the predictors and achieved good discrimination (AUC = 0.801, 95% CI: 0.799-0.803). The 1% of individuals with the highest risk of not vaccinating according to the model predictions had an average observed vaccination rate of only 18.8%. We identified 8 genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor of vaccination status in an independent subset (AUC=0.612, 95% CI: 0.601-0.623). Genetic effects were replicated in an additional 145,615 individuals from Estonia (genetic correlation=0.80, 95% CI: 0.66-0.95) and, similarly to data from Finland, correlated with mental health and propensity to participate in scientific studies. Individuals at higher genetic risk for severe COVID-19 were less likely to get vaccinated (OR=1.03, 95% CI: 1.02-1.05). Our results, while highlighting the importance of harmonized nationwide information, not limited to health, suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also those less likely to uptake COVID-19 vaccination. The results can support evidence-informed actions for COVID-19 and other areas of national immunization programs.
Predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies

Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy, however, only a fraction of the patients respond to it completely. To prevent over-treating patients with a toxic drug, there is an urgent need for biomarkers capable of predicting treatment response before administering the therapy. In this retrospective study, we developed interpretable, deep-learning based biomarkers to predict the pathological complete response (pCR, i.e. the absence of tumor cells in the surgical resection specimens) to neoadjuvant chemotherapy from digital pathology H&E images of pre-treatment breast biopsies. Our approach consists of two steps: In the first step, using deep learning, mitoses are detected and the tissue segmented into several morphology compartments including tumor, lymphocytes and stroma. In the second step, computational biomarkers are derived from the segmentation and detection output to encode slide-level relationships between the morphological structures with focus on tumor infiltrating lymphocytes (TILs). We developed and evaluated our method on slides from N=721 patients from three European medical centers with triple-negative and Luminal B breast cancers. The investigated biomarkers yield statistically significant prediction performance for pCR with areas under the receiver operating characteristic curve between 0.66 and 0.88 depending on the cancer subtype and center. The proposed computational biomarkers predict pathological complete response, but will require more evaluation and finetuning for clinical application. The results further corroborate the potential role of deep learning to automate TILs quantification, and their predictive value in breast cancer neoadjuvant treatment planning.
Pan-cancer analyses of the associations between 109 pre-existing conditions and cancer treatment patterns across 19 adult cancers

Comorbidities present considerable challenges to cancer treatment and care. However, little is known about the effect of comorbidity on cancer treatment decisions across a wide range of cancer types and treatment modalities. Harnessing a cohort of 280,543 patients spanning 19 site-specific cancers, we explored pan-cancer frequencies of 109 comorbidities. Multinomial logistic regression was used to analyse the relationship between comorbidities and cancer treatment types, while binomial logistic regression examined the association between comorbidities and chemotherapy drug types, adjusting for demographic and clinical factors. Patients with comorbidity exhibited lower odds of receiving chemotherapy and multimodality treatment. End-stage renal disease was significantly associated with a decreased odds of receiving chemotherapy and surgery. Patients with prostate cancer who have comorbid non-acute cystitis, obstructive and reflux uropathy, urolithiasis, or hypertension were less likely to receive chemotherapy. Among patients with breast cancer, dementia, left bundle branch block, peripheral arterial disease, epilepsy, Barrett’s oesophagus, ischaemic stroke, unstable angina and asthma were associated with lower odds of receiving multimodal chemotherapy, radiotherapy and surgery. Comorbidity is also consistently associated with the lower odds of receiving chemotherapy when comparing across 10 drug classes. Patients with comorbid dementia, intracerebral haemorrhage, subarachnoid haemorrhage, oesophageal varices, liver fibrosis sclerosis and cirrhosis and secondary pulmonary hypertension were less likely to receive antimetabolites. Comorbidity can influence the effectiveness and tolerability of cancer treatment and ultimately, prognosis. Multi-specialty collaborative care is essential for the management of comorbidity during cancer treatment, including prophylactic measures to manage toxicities.
ChromaStarPy: A Stellar Atmosphere and Spectrum Modeling and Visualization Lab in Python

We announce ChromaStarPy, an integrated general stellar atmospheric modeling and spectrum synthesis code written entirely in python V. 3. ChromaStarPy is a direct port of the ChromaStarServer (CSServ) Java modeling code described in earlier papers in this series, and many of the associated JavaScript (JS) post-processing procedures have been ported and incorporated into CSPy so that students have access to ready-made data products. A python integrated development environment (IDE) allows a student in a more advanced course to experiment with the code and to graphically visualize intermediate and final results, ad hoc, as they are running it. CSPy allows students and researchers to compare modeled to observed spectra in the same IDE in which they are processing observational data, while having complete control over the stellar parameters affecting the synthetic spectra. We also take the opportunity to describe improvements that have been made to the related codes, ChromaStar (CS), CSServ, and ChromaStarDB (CSDB), that, where relevant, have also been incorporated into CSPy. The application may be found at the home page of the OpenStars project: http://www.ap. smu.ca/OpenStars/.
J-PAS: The Javalambre-Physics of the Accelerated Universe Astrophysical Survey

The Javalambre-Physics of the Accelerated Universe Astrophysical Survey (J-PAS) is a narrow band, very wide field Cosmological Survey to be carried out from the Javalambre Observatory in Spain with a purpose-built, dedicated 2.5m telescope and a 4.7 sq.deg. camera with 1.2Gpix. Starting in late 2015, J-PAS will observe 8500sq.deg. of Northern Sky and measure $0.003(1+z)$ photo-z for $9\times10^7$ LRG and ELG galaxies plus several million QSOs, sampling an effective volume of $\sim 14$ Gpc$^3$ up to $z=1.3$ and becoming the first radial BAO experiment to reach Stage IV. J-PAS will detect $7\times 10^5$ galaxy clusters and groups, setting constrains on Dark Energy which rival those obtained from its BAO measurements. Thanks to the superb characteristics of the site (seeing ~0.7 arcsec), J-PAS is expected to obtain a deep, sub-arcsec image of the Northern sky, which combined with its unique photo-z precision will produce one of the most powerful cosmological lensing surveys before the arrival of Euclid. J-PAS unprecedented spectral time domain information will enable a self-contained SN survey that, without the need for external spectroscopic follow-up, will detect, classify and measure $\sigma_z\sim 0.5\%$ redshifts for $\sim 4000$ SNeIa and $\sim 900$ core-collapse SNe. The key to the J-PAS potential is its innovative approach: a contiguous system of 54 filters with $145\AA$ width, placed $100\AA$ apart over a multi-degree FoV is a powerful "redshift machine", with the survey speed of a 4000 multiplexing low resolution spectrograph, but many times cheaper and much faster to build. The J-PAS camera is equivalent to a 4.7 sq.deg. "IFU" and it will produce a time-resolved, 3D image of the Northern Sky with a very wide range of Astrophysical applications in Galaxy Evolution, the nearby Universe and the study of resolved stellar populations.
First detection and molecular identification of Rickettsia massiliae, a human pathogen, in Rhipicephalus sanguineus ticks collected from Southern Taiwan

The Rickettsia massiliae was firstly detected and identified in Rhipicephalus sanguineus ticks infested on dogs in Taiwan. A total of 1154 Rh. sanguineus ticks collected from 158 dogs of four districts of Tainan city were examined for Rickettsia infection by nested-PCR assay targeting the citrate synthase (gltA) and outer membrane protein B (ompB) genes of Rickettsia. The Rickettsia infection was detected with a general infection rate of 2.77%, and was detected in male, female and nymphal stage with an infection rate of 2.77%, 3.22% and 1.32%, respectively. Phylogenetic relationships were analyzed by comparing the gltA and ompB sequences obtained from 9 Taiwan strains and 16 other strains representing 13 genospecies of Rickettsia. Results revealed that all Taiwan strains were genetically affiliated to the same clades of R. massiliae (spotted fever group) and R. felis (transitional group), and can be discriminated from other genospecies of Rickettsia. This study provides the first evidence of R. massiliae, a pathogenic spotted fever Rickettsia, identified in Rh. sanguineus ticks and highlight the potential threat for the regional transmission of Rickettsia infection among humans in Taiwan.
Empirically Derived Patterns of Posttraumatic Stress and Growth: A Systematic Review

The relationship between posttraumatic stress (PTS) and posttraumatic growth (PTG) has been extensively studied; however, the nature of the relationship remains unclear. Inconsistencies in the literature could be, in part, due to the use of variable level approaches. Person centered methods may further our understanding of this relationship, as they enable the identification of clinically meaningful subgroups based on PTS/PTG scores. This review aimed to identify commonly found subgroups of PTS and PTG, clinically relevant factors that distinguish the subgroups and to critically appraise the utility of categorizing individuals into subgroups based on PTS/PTG scores. Five databases (Embase, Medline, Web of Science, PILOTS, and PsycINFO) were searched. Seven studies (with a total of eight study samples; n = 6,776) met the eligibility criteria. A narrative synthesis of the findings revealed that the majority of the analyses (n = 6) found three patterns of PTS/PTG. These were categorized as: (1) low PTS/PTG (representing 26.89% of the entire sample), (2) high PTS/PTG (weighted mean percentage = 20.05%), and (3) low PTS/high PTG (weighted mean percentage = 43.1%). The role of social support was examined in five studies and higher social support was consistently found to predict membership in the low PTS/high PTG class. All five studies that examined the role of trauma characteristics found that it was a significant predictor of class membership. These findings could inform the developments of tailored interventions. The utility of person-centered approaches was discussed and recommendations to improve the application and reporting of such methods were made.
Spontaneous down conversion in metal-dielectric interface - a possible source of polarization-entangled photons

Spontaneous down conversion in metal-dielectric interface in case of oblique laser excitation is considered. In this case it is possible to generate pairs of polarization entangled surface plasmon polaritons with high efficiency if to use excitation angle corresponding to the Kretschmann configuration for generated plasmons. The efficiency can be additionally enlarged if to use properly nanostructured metallic film allowing one to directly excite surface plasmon polaritons and to fulfill phase matching condition of them with generated surface plasmon polaritons.
Constraining Planck scale physics with CMB and Reionization Optical Depth

We present proof of principle for a two way interplay between physics at very early Universe and late time observations. We find a relation between primordial mechanisms responsible for large scale power suppression in the primordial power spectrum and the value of reionization optical depth $\tau$. Such mechanisms can affect the estimation of $\tau$. We show that using future measurements of $\tau$, one can obtain constraints on the pre-inflationary dynamics, providing a new window on the physics of the very early Universe. Furthermore, the new, re-estimated $\tau$ can potentially resolve moderate discrepancy between high and low-$\ell$ measurements of $\tau$, hence providing empirical support for the power suppression anomaly and its primordial origin.
Collective modes of vortex lattices in two-component Bose–Einstein condensates under synthetic gauge fields

We study collective modes of vortex lattices in two-component Bose–Einstein condensates subject to synthetic magnetic fields in mutually parallel or antiparallel directions. By means of the Bogoliubov theory with the lowest-Landau-level approximation, we numerically calculate the excitation spectra for a rich variety of vortex lattices that appear commonly for parallel and antiparallel synthetic fields. We find that in all of these cases there appear two distinct modes with linear and quadratic dispersion relations at low energies, which exhibit anisotropy reflecting the symmetry of each lattice structure. Remarkably, the low-energy spectra for the two types of fields are found to be related to each other by simple rescaling when vortices in different components overlap owing to an intercomponent attraction. These results are consistent with an effective field theory analysis. However, the rescaling relations break down for interlaced vortex lattices appearing with an intercomponent repulsion, indicating a nontrivial effect of an intercomponent vortex displacement beyond the effective field theory. We also find that high-energy parts of the excitation bands exhibit line or point nodes as a consequence of a fractional translation symmetry present in some of the lattice structures.
Using Normalization Process Theory to Evaluate an End-of-Life Pediatric Palliative Care Web-Based Training Program for Nurses: Protocol for a Randomized Controlled Trial

Background Palliative care (PC) is a new concept in Iraq, and there is no training for health care specialists or the public. The lack of education and training programs is the most important barrier for PC. Intermediate training is needed for nurses who regularly manage patients with life-threatening diseases. The End-of-Life Nursing Education Consortium for pediatric palliative care (PPC) program is intended for nurses who are interested in providing care to children with life-limiting diseases or providing support in the event of an accident or unexpected death. Objective Our trial aims to evaluate the effect of a web-based training course, using the Normalization Process Theory. It focuses on how complex interventions become routinely embedded in practice and on training of a sample of academic nurses in the application of PPC in routine daily practice. It hypothesizes that nurses will be able to provide PC for the pediatric population after completing the training. Methods This is a multicenter, parallel, pragmatic trial in 5 health care settings spread across a single city in Babylon Province, Iraq. Participants will be recruited and stratified into 2 categories (critical care units and noncritical care units). In the experimental condition, 86 nurses will be trained in the application of PPC for 2 weeks through a web-based training course powered by the Relais Platform. The nurses will be invited to participate via email or instant messaging (WhatsApp, Telegram, or Viber). They will provide end-of-life care in addition to usual care to children and adolescents with life-limiting conditions. In the control condition, 86 nurses will continue usual care. The program’s effectiveness will be assessed at the level of nurses only. We will compare baseline findings (before the intervention) with postintervention findings (after completing the training course). A further assessment will be performed 3 months after the course. As numerous unidentified factors can influence the effect of the training, we will perform a progressive evaluation to assess sample selection, application, and intervention value, as well as implementation difficulties. The nursing staff will not be blinded to the intervention, but will be blinded to the results. Results The study trial recruitment opened in July 2020. The first outcomes became available in December 2020. Conclusions The trial attempts to clarify the delivery of PC at the end of life through the implementation of a web-based training course among Iraqi nurses in the pediatric field. The study strengths include the usual practice setting, staff training, readiness of staff to participate in the study, and random allocation to the intervention. However, participants may drop out after being transferred to another department during the study period. Trial Registration ClinicalTrials.gov NCT04461561; https://clinicaltrials.gov/ct2/show/NCT04461561 International Registered Report Identifier (IRRID) PRR1-10.2196/23783
Improved Segmentation of Echocardiography With Orientation-Congruency of Optical Flow and Motion-Enhanced Segmentation

Quantification of left ventricular (LV) ejection fraction (EF) from echocardiography depends upon the identification of endocardium boundaries as well as the calculation of end-diastolic (ED) and end-systolic (ES) LV volumes. It's critical to segment the LV cavity for precise calculation of EF from echocardiography. Most of the existing echocardiography segmentation approaches either only segment ES and ED frames without leveraging the motion information, or the motion information is only utilized as an auxiliary task. To address the above drawbacks, in this work, we propose a novel echocardiography segmentation method which can effectively utilize the underlying motion information by accurately predicting optical flow (OF) fields. First, we devised a feature extractor shared by the segmentation and the optical flow sub-tasks for efficient information exchange. Then, we proposed a new orientation congruency constraint for the OF estimation sub-task by promoting the congruency of optical flow orientation between successive frames. Finally, we design a motion-enhanced segmentation module for the final segmentation. Experimental results show that the proposed method achieved state-of-the-art performance for EF estimation, with a Pearson correlation coefficient of 0.893 and a Mean Absolute Error of 5.20% when validated with echo sequences of 450 patients.
Cantilever Beam Equation for Almost Arbitrary Deflections: Derivation and Worked Examples

We derived a non-linear 4th-order ordinary differential equation the solutions of which lead to the exact shapes of the cantilever beam. The result of the equation in a non-dimensional form was found to depend on two parameters only: the angle of the beam at the fixed end, and the parameter encompassing the material characteristics and geometry of the beam. The parameter space was explored in detail and the results were used to suggest the areas in which they could be applied.
Saturation response of enhanced vegetation productivity attributes to intricate interactions

Evidence for the multifaceted responses of terrestrial ecosystems has been shown by the weakening of CO2 fertilization‐induced and warming‐controlled productivity gains. The intricate relationship between vegetation productivity and various environmental controls still remains elusive spatially. Here several inherent preponderances make China a natural experimental setting to investigate the interaction and relative contributions of five drivers to gross primary productivity for the period from 1982 to 2018 (i.e., elevated atmospheric CO2 concentrations, climate change, nutrient availability, anthropogenic land use change, and soil moisture) by coupling multiple long‐term datasets. Despite a strikingly prominent enhancement of vegetation productivity in China, it exhibits similar saturation responses to the aforementioned environmental drivers (elevated CO2, climatic factors, and soil moisture). The CO2 fertilization‐dominated network explains the long‐term variations in vegetation productivity in humid regions, but its effect is clearly attenuated or even absent in arid and alpine environments controlled by climate and soil moisture. Divergence in interactions also provides distinct evidence that water availability plays an essential role in limiting the potential effects of climate change and elevated CO2 concentrations on vegetation productivity. Unprecedented industrialization and dramatic surface changes may have breached critical thresholds of terrestrial ecosystems under the diverse natural environment and thus forced a shift from a period dominated by CO2 fertilization to a period with nonlinear interactions. These findings suggest that future benefits in terrestrial ecosystems are likely to be counteracted by uncertainties in the complicated network, implying an increasing reliance on human societies to combat potential risks. Our results therefore highlight the need to account for the intricate interactions globally and thus incorporate them into mitigation and adaptation policies.