Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison Between QT and Corrected QT Interval Assessment by an Apple Watch With the AccurBeat Platform and by a 12‑Lead Electrocardiogram With Manual Annotation: Prospective Observational Study

Background Abnormal prolongation or shortening of the QT interval is associated with increased risk for ventricular arrhythmias and sudden cardiac death. For continuous monitoring, widespread use, and prevention of cardiac events, advanced wearable technologies are emerging as promising surrogates for conventional 12‑lead electrocardiogram (ECG) QT interval assessment. Previous studies have shown a good agreement between QT and corrected QT (QTc) intervals measured on a smartwatch ECG and a 12-lead ECG, but the clinical accuracy of computerized algorithms for QT and QTc interval measurement from smartwatch ECGs is unclear. Objective The prospective observational study compared the smartwatch-recorded QT and QTc assessed using AccurKardia’s AccurBeat platform with the conventional 12‑lead ECG annotated manually by a cardiologist. Methods ECGs were collected from healthy participants (without any known cardiovascular disease) aged >22 years. Two consecutive 30-second ECG readings followed by (within 15 minutes) a 10-second standard 12-lead ECG were recorded for each participant. Characteristics of the participants were compared by sex using a 2-sample t test and Wilcoxon rank sum test. Statistical comparisons of heart rate (HR), QT interval, and QTc interval between the platform and the 12-lead ECG, ECG lead I, and ECG lead II were done using the Wilcoxon sign rank test. Linear regression was used to predict QTc and QT intervals from the ECG based on the platform’s QTc/QT intervals with adjustment for age, sex, and difference in HR measurement. The Bland-Altman method was used to check agreement between various QT and QTc interval measurements. Results A total of 50 participants (32 female, mean age 46 years, SD 1 year) were included in the study. The result of the regression model using the platform measurements to predict the 12-lead ECG measurements indicated that, in univariate analysis, QT/QTc intervals from the platform significantly predicted QT/QTc intervals from the 12-lead ECG, ECG lead I, and ECG lead II, and this remained significant after adjustment for sex, age, and change in HR. The Bland-Altman plot results found that 96% of the average QTc interval measurements between the platform and QTc intervals from the 12-lead ECG were within the 95% confidence limit of the average difference between the two measurements, with a mean difference of –10.5 (95% limits of agreement –71.43, 50.43). A total of 94% of the average QT interval measurements between the platform and the 12-lead ECG were within the 95% CI of the average difference between the two measurements, with a mean difference of –6.3 (95% limits of agreement –54.54, 41.94). Conclusions QT and QTc intervals obtained by a smartwatch coupled with the platform’s assessment were comparable to those from a 12-lead ECG. Accordingly, with further refinements, remote monitoring using this technology holds promise for the identification of QT interval prolongation.
Use of artificial intelligence to assess the risk of coronary artery disease without additional (non-invasive) testing: validation in a low-risk to intermediate-risk outpatient clinic cohort

Objectives Predicting the presence or absence of coronary artery disease (CAD) is clinically important. Pretest probability (PTP) and CAD consortium clinical (CAD2) model and risk scores used in the guidelines are not sufficiently accurate as the only guidance for applying invasive testing or discharging a patient. Artificial intelligence without the need of additional non-invasive testing is not yet used in this context, as previous results of the model are promising, but available in high-risk population only. Still, validation in low-risk patients, which is clinically most relevant, is lacking. Design Retrospective cohort study. Setting Secondary outpatient clinic care in one Dutch academic hospital. Participants We included 696 patients referred from primary care for further testing regarding the presence or absence of CAD. The results were compared with PTP and CAD2 using receiver operating characteristic (ROC) curves (area under the curve (AUC)). CAD was defined by a coronary stenosis >50% in at least one coronary vessel in invasive coronary or CT angiography, or having a coronary event within 6 months. Outcome measures The first cohort validating the memetic pattern-based algorithm (MPA) model developed in two high-risk populations in a low-risk to intermediate-risk cohort to improve risk stratification for non-invasive diagnosis of the presence or absence of CAD. Results The population contained 49% male, average age was 65.6±12.6 years. 16.2% had CAD. The AUCs of the MPA model, the PTP and the CAD2 were 0.87, 0.80, and 0.82, respectively. Applying the MPA model resulted in possible discharge of 67.7% of the patients with an acceptable CAD rate of 4.2%. Conclusions In this low-risk to intermediate-risk population, the MPA model provides a good risk stratification of presence or absence of CAD with a better ROC compared with traditional risk scores. The results are promising but need prospective confirmation.
On the existence of ethylenediaminetetraacetic acid (EDTA) doped zinc sulphate heptahydrate crystal

It is argued that the ethylenediaminetetraacetic acid (EDTA) doped zinc sulphate heptahydrate crystal reported by Raja et al Spectrochim Acta 99A (2012) 23 is the well known zinc sulphate heptahydrate.
Nova KT Eri 2009: infrared studies of a very fast and small amplitude He/N nova

We present near-infrared spectroscopic and photometric observations of the nova KT Eridani taken during the first 100 days following its discovery in 2009 November. The JHK spectra of the object have been taken from the Mount Abu Infrared Observatory using the Near-Infrared Imager/Spectrometer. The spectra, typical of the He/N class novae, show strong He I emission lines together with H I and O I emission features. The H I, Pa-beta and Br-gamma spectral lines and the He I line at 2.0581 micron show broad wings with a relatively narrow central component. The broad wings extend to 1900 km/s while the central component has FWHM of 2100 km/s. The V and near-infrared JHK light curves show an additional small amplitude outburst near 40 days after optical maximum. The distance to the nova d = 6.3 +/- 0.1 kpc is derived using the MMRD relation and the estimated value of t2 = 5.7 +/- 0.3 days. The small value of t2 places KT Eri in the class of very fast novae. Using the value of the distance to the nova d, we estimate the height of the nova to be z = 3.3 +/- 0.1 kpc below the galactic plane. We have also calculated the upper limit for the ejecta mass for KT Eri to be in the range 2.4-7.4 x 10^(-5) Msun. Kinematic evidence is presented from the shape of the line profiles for a possible bipolar flow. We analyze the temporal evolution of the continuum and also discuss the possibility of KT Eri being a recurrent nova.
Central bank communication, shadow banking, and bank risk-taking: Theoretical model and PVAR empirical evidence

The rapid development of Chinese shadow banking, which relies on the banking system, significantly impacts nonneutral bank risk-taking. Central bank communication also plays a vital role in risk prevention and mitigation in the banking system in a modern central banking system. To address the issues of central bank communication, shadow banking, and bank risk-taking, we construct a new theoretical model that includes shadow banking based on the M-S model. Based on the central bank written communication index measured by the Monetary Policy Implementation Report 2009–2019 and balanced panel data of 35 listed banks, we design an empirical PVAR model. This study finds that central bank communication regarding domestic easing economy and policy positively affects bank risk-taking, while central bank communication and mechanism exists in China. Moreover, the growth rate of shadow banking size also positively encourages bank risk-taking. Furthermore, central bank communication regarding foreign policy is negatively related to bank risk-taking in the robustness test, supporting the above findings. The analysis of equity heterogeneity shows that the positive effect of central bank communication on bank risk-taking in shadow banking is more pronounced in small and medium-sized shareholdings. Further analyzing the economic consequences of central bank communication and shadow banking on bank risk-taking, we find that banks’ risk-taking positively affects their share of noninterest income and total asset size.
Identification of novel polymorphism in mammary-derived growth inhibitor gene of water buffalo and its expression analysis in the mammary gland

Abstract Mammary-derived growth inhibitor (MDGI), a member of the lipophilic family of fatty acid-binding proteins, plays an important role in the development, regulation, and differentiation of the mammary gland. The aim of the study was to identify polymorphism in the MDGI gene and its expression analysis in the mammary gland at various stages of lactation, in Indian buffalo. Nucleotide sequence analysis of MDGI gene in different breeds of riverine and swamp buffaloes revealed a total of 16 polymorphic sites and one Indel. Different transcription factor binding sites were predicted for buffalo MDGI gene promoter sequence, using online tools and in-silico analysis indicating that the SNPs in this region can impact the gene expression regulation. Phylogenetic analysis exhibited the MDGI of buffalo being closer to other ruminants like cattle, yak, sheep, and goats. Further, the expression analysis revealed that buffalo MDGI being highly expressed in well-developed mammary glands of lactating buffalo as compared to involution/non-lactating and before functional development to start the milk production stage in heifers. Stage-specific variation in expression levels signifies the important functional role of the MDGI gene in mammary gland development and milk production in buffalo, an important dairy species in Southeast Asia.
Uncertainty of nitrate‐N load computations for agricultural watersheds

Water quality samples for most streams are collected at variable frequencies within monitoring periods of different lengths. On the basis of discrete concentration data obtained from these monitoring studies, loads of various pollutants passing through a gaging station for selected periods may be calculated using various load estimation methods. In this paper, nitrate‐N load estimates were compared with their “true” values, calculated using 6 years of daily nitrate‐N concentration and average discharge data at an agricultural watershed in central Illinois. A Monte Carlo subsampling study was conducted to simulate different sampling scenarios for variable sampling frequencies and different monitoring durations. Load calculations were compared for each sampling scenario based on rating curve, ratio estimator, and flow‐weighted average estimator. In addition, two bias correction techniques (minimum variance unbiased estimator (MVUE) and smearing estimator) were applied to the rating curve method. The monitoring durations were 1, 2, 3, and 6 years, and the sampling frequencies ranged from weekly to bimonthly. The results demonstrated that a desired accuracy of the estimates could be achieved either by sampling more frequently or by monitoring the site longer. Although the ratio and the flow‐weighted average estimators had a small negative bias, in most cases rating curve estimators were positively biased when applied to the study site. Also, neither of the two bias correction techniques, MVUE and smearing estimator, decreased this positive bias. On the contrary, those techniques produced a higher bias, which resulted in increased root‐mean‐square error (RMSE). The rating curve uncorrected for bias, the simple ratio, and the flow‐weighted estimator had a significantly smaller RMSE for all sampling frequencies and all periods of record than the bias‐corrected rating curve methods.
Investigating protein–excipient interactions of a multivalent VHH therapeutic protein using NMR spectroscopy

ABSTRACT Multispecific therapeutic proteins come in a variety of formats, including bi- and tri-specific antibodies, dual-variable domain antibodies, and CrossMabs. These multivalent proteins are engineered to interact with multiple therapeutic target proteins with high specificity. Multi-domain proteins can be created by linking together a variety of high-affinity antibody fragments. The choice of protein domains and linkers not only affects the interactions of these molecules with therapeutic targets but also influences the intrinsic behavior in solution that affects their stability. The complexity of solution interactions may translate into developability and manufacturing challenges. Here, we use nuclear magnetic resonance (NMR) spectroscopy to study the solution behavior of a multivalent VHH molecule composed of three flexibly linked heavy-chain-only domains that show dramatic stabilization against thermal degradation in the presence of sucrose. A collection of NMR fingerprinting and profiling methods were used to simultaneously monitor the protein solution behavior and capture details of protein–excipient interactions. We provide a framework to characterize and begin to understand the role of molecular flexibility in protein stabilization with potential applications in the design of novel therapeutic protein scaffolds that include multivalent proteins, fusion proteins, antibody-drug conjugates, and proteins modified with flexible lipids. Alphabetical list of abbreviations Fab Fragment antigen-binding; Fc Fragment crystallizable; HMW High molecular weight; ∆HMW Difference between HMW species at stress temperature and 5°C controls; IgG Immunoglobulin G; mAbs Monoclonal antibodies; MV-VHH Multivalent VHH molecule with the format aC-L1-aC-L1-aD; NMR Nuclear magnetic resonance; scFv Single-chain fragment variable; SEC Size-exclusion chromatography; VHH Variable domain of Heavy chain of Heavy chain-only antibody
Echocardiographic changes after arteriovenous fistula creation in hemodialysis patients

Background: Pulmonary hypertension (PH) is common in end-stage renal disease (ESRD) patients and is associated with increased all-cause and cardiovascular mortality in this group. There is scarce data on the long-term effect of arteriovenous fistula (AVF) creation on pulmonary hypertension (PH) and the reflected changes in echocardiographic measurements. Materials and methods: This is a retrospective study of 54 patients who underwent AVF creation between 2009 and 2014 and with echocardiographic evaluations before and after surgery. We analyzed pairwise changes in right ventricular systolic pressure (RVSP), right atrial pressure (RAP) during systole, left ventricular mass (LVM), tricuspid regurgitation (TR), mitral E/E’ ratio, and ejection fraction (EF), as well as the factors that predicted change in RVSP after surgery. Results: The median time for the preoperative echocardiogram was 0.3 years (interquartile range (IQR) 0.2 – 0.7 years) prior to AVF creation, while the follow-up echo was done 1.3 (0.6 – 2.1) years after surgery. 67% of the patients had RVSP > 37 mmHg at baseline. There was a significant reduction in RVSP after AVF creation compared to baseline (median 33 (IQR 26 – 43) vs. 46 mmHg, p = 0.0015), with 59% of the patients experiencing a decrease and 19% remaining stable. There were also significant decreases in LVM (201 (143 – 256) vs. 215 (163 – 276), p = 0.045) and RAP systole (10 (10 – 15) vs. 3 (3 – 8); p < 0.001) after surgery. Higher preoperative weight (p = 0.038) and RVSP (p = 0.006), and use of loop diuretics (p = 0.015) were significantly associated with improvement in RVSP after AVF creation. Conclusion: Our results suggest that AVF creation is associated with a significant reduction or stable measurements of RVSP in the ESRD population, likely due to an improvement in volume status.
Timapiprant, a prostaglandin D2 receptor antagonist, ameliorates pathology in a rat Alzheimer’s model

PGD2 is a major brain prostaglandin and we report that timapiprant that is an antagonist for the PGD2 receptor DP2 reduces pathology and cognitive deficits in a transgenic rat model of Alzheimer’s. We investigated the relevance of the prostaglandin D2 pathway in Alzheimer’s disease, because prostaglandin D2 is a major prostaglandin in the brain. Thus, its contribution to Alzheimer’s disease merits attention, given the known impact of the prostaglandin E2 pathway in Alzheimer’s disease. We used the TgF344-AD transgenic rat model because it exhibits age-dependent and progressive Alzheimer’s disease pathology. Prostaglandin D2 levels in hippocampi of TgF344-AD and wild-type littermates were significantly higher than prostaglandin E2. Prostaglandin D2 signals through DP1 and DP2 receptors. Microglial DP1 receptors were more abundant and neuronal DP2 receptors were fewer in TgF344-AD than in wild-type rats. Expression of the major brain prostaglandin D2 synthase (lipocalin-type PGDS) was the highest among 33 genes involved in the prostaglandin D2 and prostaglandin E2 pathways. We treated a subset of rats (wild-type and TgF344-AD males) with timapiprant, a potent highly selective DP2 antagonist in development for allergic inflammation treatment. Timapiprant significantly mitigated Alzheimer’s disease pathology and cognitive deficits in TgF344-AD males. Thus, selective DP2 antagonists have potential as therapeutics to treat Alzheimer’s disease.
Dynamical architectures of planetary systems induced by orbital migration

The aim of this talk is to present the most recent advances in establishing plausible planetary system architectures determined by the gravitational tidal interactions between the planets and the disc in which they are embedded during the early epoch of planetary system formation. We concentrate on a very well defined and intensively studied process of the disc-planet interaction leading to the planet migration. We focus on the dynamics of the systems in which low-mass planets are present. Particular attention is devoted to investigation of the role of resonant configurations. Our studies, apart from being complementary to the fast progress occurring just now in observing the whole variety of planetary systems and uncovering their structure and origin, can also constitute a valuable contribution in support of the missions planned to enhance the number of detected multiple systems.
Anwendung der Fuzzy Logic in der Bildverarbeitung.

Es werden Aufgaben der Bildverarbeitung behandelt, bei denen keine festen Grenzen oder Beziehungen im Bildinhalt vorliegen.Obergnge der Bildinhalte sind fliessend.Ober Fuzzy Logic wird eine neue Beziehung der Zuordnung definiert.
PRESERVICE ELEMENTARY TEACHERS AND THE FUNDAMENTALS OF PROBABILITY

This study examined how preservice elementary teachers think about situations involving probability. Twenty-four preservice elementary teachers who had not yet studied probability as part of their preservice elementary mathematics coursework were interviewed using a task-based interview. The participants’ responses showed a wide variety of misconceptions about the meaning of probability. In particular, when they were asked to think about the probability of an irregularly shaped object, many participants had misconceptions about the classical and frequentist interpretations of probability. These findings suggest that instruction for preservice elementary teachers should address the meaning of probability, including the subjective, classical, and frequentist interpretations of probability. First published November 2011 at Statistics Education Research Journal: Archives
Archaeobotanical and isotopic analyses of waterlogged remains from the Neolithic pile-dwelling site of Zug-Riedmatt (Switzerland): Resilience strategies of a plant economy in a changing local environment

The excellent preservation of the waterlogged botanical remains of the multiphase Neolithic pile-dwelling site of Zug-Riedmatt (Central Switzerland) yielded an ideal dataset to delve into the issue of plant economy of a community spanning several decades. The study identified a major change in crops where oil plants played a key role in the site’s initial phase before being supplanted over the course of a few decades by naked wheat, barley and pea. Wild plants continued to be gathered albeit in different proportions. In the latest settlement phase, the changes in the local vegetation and in the values of the analyses of carbon stable isotopes suggest a less humid environment. The hypothesis is that the changes perceived in the plant economy represent a resilience strategy adopted by the inhabitants in reaction to short term local climatic alterations. The two types of soil sampling techniques (monolith and bulk) allowed comparing these results. While the density of plant remains appears to be underestimated among the samples collected by the monolith technique, the proportions of economic taxa remain unaffected. The findings thus reveal that when the bulk samplings are distributed carefully throughout multiphase sites and avoid mixing stratigraphical units, and if the samplings are representative of all archaeological features from a whole area, then each of the two techniques offer analogous results.
Machine Learning to Predict Homolytic Dissociation Energies of C−H Bonds: Calibration of DFT‐based Models with Experimental Data

Random Forest (RF) QSPR models were developed with a data set of homolytic bond dissociation energies (BDE) previously calculated by B3LYP/6‐311++G(d,p)//DFTB for 2263 sp3C−H covalent bonds. The best set of attributes consisted in 114 descriptors of the carbon atom (counts of atom types in 5 spheres around the kernel atom and ring descriptors). The optimized model predicted the DFT‐calculated BDE of an independent test set of 224 bonds with MAE=2.86 kcal/mol. A new data set of 409 bonds from the iBonD database (http://ibond.nankai.edu.cn) was predicted by the RF with a modest MAE (5.36 kcal/mol) but a relatively high R2 (0.75) against experimental energies. A prediction scheme was explored that corrects the RF prediction with the average deviation observed for the k nearest neighbours (KNN) in an additional memory of experimental data. The corrected predictions achieved MAE=2.22 kcal/mol for an independent test set of 145 bonds and the corresponding experimental bond energies.