Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of evidence-based clinical practice guidelines for breast cancer in health care quality improvements. A second systematic review.

Background: Traditionally, EB-CPGs have been believed to mainly improve the quality and consistency of health care, but this claim must be conclusively proven. We used the Donabedian three-dimensional model (structure, process, and patient outcomes) to assess improvements in the quality of medical care derived from implementing EB-CPGs. This study corresponds to the second systematic review carried out as a series of studies on different clinical issues that aim to evaluate the effectiveness of the application of the EB-CPG for improving the quality of care. Methods: We followed the methods described by the Cochrane Handbook and presented a descriptive analysis because of the high heterogeneity found across the included studies. We searched the Cochrane Central Register of Controlled Trials, PubMed, and EBSCO Host databases, as well as the grey literature, between 1990 and April 2021. No language restrictions were applied. Only randomised clinical trials (RCTs) were selected. Results: Of the total of 364 interventions included in the eleven RCTs evaluated, 11 (3%) were related to healthcare structure, 51 (14%) to the healthcare delivery process and 302 (83%) to patient outcomes. Regarding the impact of using the EB-CPGs, in 303 interventions (83%), there were no significant differences between the control and experimental groups. In 4 interventions (1%), the result favoured the control and intervention groups in 57 of the interventions (16%). Conclusions: Our study showed that EB-CPGs slightly enhanced the quality of health care in the three dimensions described by Donabedian. Future RCTs should improve their design and methodological rigour by considering the certainty of the evidence supporting the EB-CPGs recommendations. In that context, broader analyses could be performed, having more concise hypotheses for further research. Registration: PROSPERO CRD42020205594
A Second-Order Crank–Nicolson Leap-Frog Scheme for the Modified Phase Field Crystal Model with Long-Range Interaction

In this paper, we construct a fully discrete and decoupled Crank–Nicolson Leap-Frog (CNLF) scheme for solving the modified phase field crystal model (MPFC) with long-range interaction. The idea of CNLF is to treat stiff terms implicity with Crank–Nicolson and to treat non-stiff terms explicitly with Leap-Frog. In addition, the scalar auxiliary variable (SAV) method is used to allow explicit treatment of the nonlinear potential, then, these technique combines with CNLF can lead to the highly efficient, fully decoupled and linear numerical scheme with constant coefficients at each time step. Furthermore, the Fourier spectral method is used for the spatial discretization. Finally, we show that the CNLF scheme is fully discrete, second-order decoupled and unconditionally stable. Ample numerical experiments in 2D and 3D are provided to demonstrate the accuracy, efficiency, and stability of the proposed method.
Boosts in leaf-level photosynthetic capacity aid Pinus ponderosa recovery from wildfire

Forests mitigate climate change by sequestering massive amounts of carbon, but recent increases in wildfire activity are threatening carbon storage. Currently, our understanding of wildfire impacts on forest resilience and the mechanisms controlling post-fire recovery remains unresolved due to a lack of empirical data on mature trees in natural settings. Here, we quantify the physiological mechanisms controlling carbon uptake immediately following wildfire in mature individuals of ponderosa pine (Pinus ponderosa), a wide-spread and canopy-dominant tree species in fire-prone forests. While photosynthetic capacity was lower in burned than unburned trees due to an overall depletion of resources, we show that within the burned trees, photosynthetic capacity increases with the severity of damage. Our data reveal that boosts in the efficiency of carbon uptake at the leaf-level may compensate for whole-tree damage, including the loss of leaf area and roots. We further show that heightened photosynthetic capacity in remaining needles on burned trees may be linked with reduced water stress and leaf nitrogen content, providing pivotal information about post-fire physiological processes. Our results have implications for Earth system modeling efforts because measurements of species-level physiological parameters are used in models to predict ecosystem and landscape-level carbon trajectories. Finally, current land management practices do not account for physiological resilience and recovery of severely burned trees. Our results suggest premature harvest may remove individuals that may otherwise survive, irrevocably altering forest carbon balance.
Bias in the estimation of O-D flows from link counts

This is a study of the bias which can occur in some circumstances in the estimation of trip matrices from link counts by two popular methods: maximum entropy (ME) and information minimization (IM). In the case of uniform overall growth since the prior matrix, it is easy to demonstrate that the ME method overestimates those O-D flows which have been counted several times. The use of artificially-generated data-sets has shown that even when the growth is non-uniform, the bias is still present. Recent work has shown that the IM method too produced bias but this time in the opposite direction: O-D flows that have been counted several times are underestimated. These findings are confirmed algebraically by the use of small examples and numerically by the simulation of many somewhat larger examples. A new method is proposed which is a modification of the ME method.
Exploring the association of body mass index, mindful and emotional eating, and orthorexia

BACKGROUND Orthorexia nervosa (ON) is defined as a fixation on healthy eating behaviours. Research exploring ON and body mass index (BMI) has been inconsistent, with some findings indicating a positive relationship between ON and BMI, while other studies have suggested no relationship. To date, potential associations with emotional and mindful eating have been explored only in a vegan population. The present research adopted an exploratory approach and examined the relationship between orthorexia and BMI, and possible associations with emotional and mindful eating. The potential predictive value of mindful and emotional eating with respect to ON was also explored, while the role of four different types of emotional eating (happiness, sadness, anger, anxiety), utilising an emotional eating scale incorporating positive and negative emotions, was further explored. PARTICIPANTS AND PROCEDURE Two hundred and twenty-three participants completed the online survey that was distributed via social media to a British sample. RESULTS The findings suggested a negative correlation between ON and BMI. Participants who presented higher levels of orthorexia were more likely to display higher levels of focused eating, a central aspect of mindful eating, as well as lower levels of emotional eating in response to happiness – two elements that further predicted ON in multiple regression models. CONCLUSIONS The results suggest a need to conduct further research to explore the possible role of happiness as a potential protective tool against ON, and further suggest the likely negative role of some components of mindful eating in ON. Future directions are discussed in light of the present findings.
A Possible Detection of M31* with Chandra

Two independent sets of Chandra and HST images of the nuclear region of M31 allow registration of X-ray and optical images to ~0. ″1. This registration shows that none of the bright (~1037 ergs s-1) X-ray sources near the nucleus is coincident with the central supermassive black hole, M31*. A 50 ks Chandra HRC image shows 2.5 σ evidence for a faint (~1036 ergs s-1) discrete source that is consistent with the position of M31*. The Bondi radius of M31* is 0. ″9, making it one of the few supermassive black holes with a resolvable accretion flow. This large radius and the previous detections of diffuse X-ray-emitting gas in the nuclear region make M31* one of the most secure cases for a radiatively inefficient accretion flow and place some of the most severe constraints on the radiative processes in such a flow.
Observation of subkelvin superconductivity in 
Cd3As2
 thin films

We report the first experimental observation of superconductivity in Cd$_3$As$_2$ thin films without application of external pressure. Surface studies suggest that the observed transport characteristics are related to the polycrystalline continuous part of investigated films with homogeneous distribution of elements and the Cd-to-As ratio close to stoichiometric Cd$_3$As$_2$. The latter is also supported by Raman spectra of the studied films, which are similar to those of Cd$_3$As$_2$ single crystals. The formation of superconducting phase in films under study is confirmed by the characteristic behavior of temperature and magnetic field dependence of samples resistances, as well as by the presence of pronounced zero-resistance plateaux in $dV/dI$ characteristics. The corresponding $H_c-T_c$ plots reveal a clearly pronounced linear behavior within the intermediate temperature range, similar to that observed for bulk Cd$_3$As$_2$ and Bi$_2$Se$_3$ films under pressure, suggesting the possibility of nontrivial pairing in the films under investigation. We discuss a possible role of sample inhomogeneities and crystal strains in the observed phenomena.
First-order transition between magnetic order and valence bond order in a 2D frustrated Heisenberg model

We study the competition between magnetic order and valence bond order in a two-dimensional (2D) frustrated Heisenberg model introduced some time ago by Shastry and Sutherland (Physica B, 108 (1981) 1069) for which a configuration of dimers is known to be the ground state in a certain range of parameters. Using exact diagonalization of small clusters, linear spin wave theory and Schwinger boson mean-field theory, we argue that the transition between the two types of order is first order, and that it takes place inside the domain where magnetic long-range order is stable with respect to quantum fluctuations.
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of the PLM weights for every task resulting in increased cost for storing, sharing and serving the models. To address this, parameter-efficient fine-tuning (PEFT) techniques were introduced where small trainable components are injected in the PLM and updated during fine-tuning. We propose AdaMix as a general PEFT method that tunes a mixture of adaptation modules – given the underlying PEFT method of choice – introduced in each Transformer layer while keeping most of the PLM weights frozen. For instance, AdaMix can leverage a mixture of adapters like Houlsby or a mixture of low rank decomposition matrices like LoRA to improve downstream task performance over the corresponding PEFT methods for fully supervised and few-shot NLU and NLG tasks. Further, we design AdaMix such that it matches the same computational cost and the number of tunable parameters as the underlying PEFT method. By only tuning 0.1-0.2% of PLM parameters, we show that AdaMix outperforms SOTA parameter-efficient fine-tuning and full model fine-tuning for both NLU and NLG tasks.
Extraction and Quantification of Words Representing Degrees of Diseases: Combining the Fuzzy C-Means Method and Gaussian Membership

Background Due to the development of medical data, a large amount of clinical data has been generated. These unstructured data contain substantial information. Extracting useful knowledge from this data and making scientific decisions for diagnosing and treating diseases have become increasingly necessary. Unstructured data, such as in the Marketplace for Medical Information in Intensive Care III (MIMIC-III) data set, contain several ambiguous words that demonstrate the subjectivity of doctors, such as descriptions of patient symptoms. These data could be used to further improve the accuracy of medical diagnostic system assessments. To the best of our knowledge, there is currently no method for extracting subjective words that express the extent of these symptoms (hereinafter, “degree words”). Objective Therefore, we propose using the fuzzy c-means (FCM) method and Gaussian membership to quantify the degree words in the clinical medical data set MIMIC-III. Methods First, we preprocessed the 381,091 radiology reports collected in MIMIC-III, and then we used the FCM method to extract degree words from unstructured text. Thereafter, we used the Gaussian membership method to quantify the extracted degree words, which transform the fuzzy words extracted from the medical text into computer-recognizable numbers. Results The results showed that the digitization of ambiguous words in medical texts is feasible. The words representing each degree of each disease had a range of corresponding values. Examples of membership medians were 2.971 (atelectasis), 3.121 (pneumonia), 2.899 (pneumothorax), 3.051 (pulmonary edema), and 2.435 (pulmonary embolus). Additionally, all extracted words contained the same subjective words (low, high, etc), which allows for an objective evaluation method. Furthermore, we will verify the specific impact of the quantification results of ambiguous words such as symptom words and degree words on the use of medical texts in subsequent studies. These same ambiguous words may be used as a new set of feature values to represent the disorders. Conclusions This study proposes an innovative method for handling subjective words. We used the FCM method to extract the subjective degree words in the English-interpreted report of the MIMIC-III and then used the Gaussian functions to quantify the subjective degree words. In this method, words containing subjectivity in unstructured texts can be automatically processed and transformed into numerical ranges by digital processing. It was concluded that the digitization of ambiguous words in medical texts is feasible.
Hubble Space Telescope counts of Elliptical Galaxies: Constraints on Cosmological Models

The interpretation of galaxy number counts in terms of cosmological models is fraught with difficulty due to uncertainties in the overall galaxy population (mix of morphological types, luminosity functions etc.) and in the observations (loss of low surface brightness images, image blending etc.). Many of these can be overcome if we use deep high resolution imaging of a single class of high surface brightness galaxies, whose evolution is thought to be fairly well understood. This is now possible by selecting elliptical and S0 galaxies using Hubble Space Telescope images from the Medium Deep Survey and other ultradeep WFPC2 images. In the present paper, we examine whether such data can be used to discriminate between open and closed universes, or between conventional cosmological models and those dominated by a cosmological constant. We find, based on the currently available data, that unless elliptical galaxies undergo very strong merging since $z \sim 1$ (and/or very large errors exist in the morphological classifications), then flat models dominated by a cosmological constant are ruled out. However, both an Einstein-de Sitter ($\Omega_{0}=1$) model with standard passive stellar evolution and an open ($\Omega_{0}=0.05$) model with no net evolution ({\it i.e.} cancelling stellar and dynamical evolution) predict virtually identical elliptical and S0 galaxy counts. Based on these findings and the recent reportings of $H_{o} \simeq 80$ km/s Mpc/s, we find that the maximum acceptable age of the universe is 13.3 Gyrs and a value of $\leq 9$ Gyrs favored. A flat---$\Lambda \neq 0$---universe is therefore {\it not} a viable solution to the $H_{o}$/globular cluster age problem.
Is There a Circumbinary Planet around NSVS 14256825?

The cyclic behavior of (O–C) residuals of eclipse timings in the sdB+M eclipsing binary NSVS 14256825 was previously attributed to one or two Jovian-type circumbinary planets. We report 83 new eclipse timings that not only fill in the gaps in those already published but also extend the time span of the (O–C) diagram by three years. Based on the archival and our new data spanning over more than 17 years, we re-examined the up-to-date system (O–C). The data revealed a systematic, quasi-sinusoidal variation deviating from an older linear ephemeris by about 100 s. It also exhibits a maximum in the (O–C) near JD 2,456,400 that was previously unknown. We consider two most credible explanations of the (O–C) variability: the light propagation time due to the presence of an invisible companion in a distant circumbinary orbit, and magnetic cycles reshaping one of the binary components, known as the Applegate or Lanza–Rodonó effect. We found that the latter mechanism is unlikely due to the insufficient energy budget of the M-dwarf secondary. In the framework of the third-body hypothesis, we obtained meaningful constraints on the Keplerian parameters of a putative companion and its mass. Our best-fitting model indicates that the observed quasi-periodic (O–C) variability can be explained by the presence of a brown dwarf with the minimal mass of 15 Jupiter masses rather than a planet, orbiting the binary in a moderately elliptical orbit ( ) with a period of ∼10 years. Our analysis rules out the two-planet model proposed earlier.
The Mysterious Dimmings of the T Tauri Star V1334 Tau

We present the discovery of two extended ∼0.12 mag dimming events of the weak-lined T Tauri star V1334. The start of the first event was missed but came to an end in late 2003, and the second began in 2009 February, and continues as of 2016 November. Since the egress of the current event has not yet been observed, it suggests a period of >13 years if this event is periodic. Spectroscopic observations suggest the presence of a small inner disk, although the spectral energy distribution shows no infrared excess. We explore the possibility that the dimming events are caused by an orbiting body (e.g., a disk warp or dust trap), enhanced disk winds, hydrodynamical fluctuations of the inner disk, or a significant increase in the magnetic field flux at the surface of the star. We also find a ∼0.32 day periodic photometric signal that persists throughout the 2009 dimming which appears to not be due to ellipsoidal variations from a close stellar companion. High-precision photometric observations of V1334 Tau during K2 campaign 13, combined with simultaneous photometric and spectroscopic observations from the ground, will provide crucial information about the photometric variability and its origin.
Quantifying quantum invasiveness

We propose a resource theory of the quantum invasiveness of general quantum operations, i.e., those defined by quantum channels in Leggett-Garg scenarios. We are then able to compare the resource-theoretic framework of quantum invasiveness to the resource theory of coherence. We also show that the Fisher information is a quantifier of quantum invasiveness. This result allows us to establish a direct connection between the concept of quantum invasiveness and quantum metrology, by exploring the utility of the definition of quantum invasiveness in the context of metrological protocols.
Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury

Background: We aimed to develop and validate an automated machine learning (autoML) prediction model for cardiac surgery-associated acute kidney injury (CSA-AKI). Methods: Using 69 preoperative variables, we developed several models to predict post-operative AKI in adult patients undergoing cardiac surgery. Models included autoML and non-autoML types, including decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and artificial neural network (ANN), as well as a logistic regression prediction model. We then compared model performance using area under the receiver operating characteristic curve (AUROC) and assessed model calibration using Brier score on the independent testing dataset. Results: The incidence of CSA-AKI was 36%. Stacked ensemble autoML had the highest predictive performance among autoML models, and was chosen for comparison with other non-autoML and multivariable logistic regression models. The autoML had the highest AUROC (0.79), followed by RF (0.78), XGBoost (0.77), multivariable logistic regression (0.77), ANN (0.75), and DT (0.64). The autoML had comparable AUROC with RF and outperformed the other models. The autoML was well-calibrated. The Brier score for autoML, RF, DT, XGBoost, ANN, and multivariable logistic regression was 0.18, 0.18, 0.21, 0.19, 0.19, and 0.18, respectively. We applied SHAP and LIME algorithms to our autoML prediction model to extract an explanation of the variables that drive patient-specific predictions of CSA-AKI. Conclusion: We were able to present a preoperative autoML prediction model for CSA-AKI that provided high predictive performance that was comparable to RF and superior to other ML and multivariable logistic regression models. The novel approaches of the proposed explainable preoperative autoML prediction model for CSA-AKI may guide clinicians in advancing individualized medicine plans for patients under cardiac surgery.
The Effectiveness of Information Criteria in Determining Unit Root and Trend Status

This paper compares the performance of using an information criterion, such as the Akaike information criterion or the Schwarz (Bayesian) information criterion, rather than hypothesis testing in consideration of the presence of a unit root for a variable and, if unknown, the presence of a trend in that variable. The investigation is performed through Monte Carlo simulations. Properties considered are frequency of choosing the unit root status correctly, predictive performance, and frequency of choosing an appropriate subsequent action on the examined variable (first differencing, detrending, or doing nothing). Relative performance is considered in a minimax regret framework. The results indicate that use of an information criterion for determining unit root status and (if necessary) trend status of a variable can be competitive to alternative hypothesis testing strategies.
The Role of Selected Serpins in Gastrointestinal (GI) Malignancies

Gastrointestinal (GI) cancers, which are a diverse group of malignant diseases, represent a major healthcare problem around the world. Due to the lack of specific symptoms in the early stages as well as insufficient diagnostic possibilities, these malignancies occupy the leading position in the causes of death worldwide. The currently available tests have too many limitations to be part of routine diagnostics. Therefore, new potential biomarkers that could be used as diagnostic and prognostic factors for these cancers are still being sought. Among the proteins that might fit this role are serpins, which are serine protease inhibitors. Although the serpins themselves have been known for many years, they have recently become the centre of attention for many authors, especially due to the fact that a number of proteins in this family are involved in many stages of neoplasia formation, from angiogenesis through tumour growth to progression. Therefore, the aim of this review is to present the current knowledge about the significance of serpins in GI malignancies, especially their involvement in the development and progression of oesophageal, gastric, pancreatic and colorectal cancers. This review summarises and confirms the important roles of selected serpins in the pathogenesis of various GI cancers and also points to their promising roles as therapeutic targets. However, due to the relatively nonspecific nature of serpins, future research should be carried out to elucidate the mechanisms involved in tumour pathogenesis in more detail.