Miracle-dz/UniFAR-FTUs huggingface dataset:
Celiac Disease and Cardiovascular Risk: A Retrospective Case-Control Study

Background: The association of celiac disease (CD) with premature atherosclerosis, including increased carotid artery intima-media thickness and cardiovascular disease (CVD), is controversial. The aim of this study was to investigate this relationship. Methods: Clinical records of patients from Northern Sardinia referred to the Gastroenterology section of the Department of Medicine, University of Sassari, Italy, were analyzed. Unadjusted and adjusted odds ratios (ORs) for CVD with their 95% confidence intervals (CIs) were calculated according to established risk factors, including age, sex, diabetes, dyslipidemia, overweight/obesity, blood hypertension, and cigarette smoking, as well as a possible risk factor such as H. pylori infection. Results: In a total of 8495 patients (mean age 52.1 ± 17.3 years; 64.7% females), 2504 reported a diagnosis of CVD and 632 of CD. Logistic regression analysis showed a significantly reduced risk of CVD among patients with CD (OR 0.30, 95% CI 0.22–0.41). Moreover, the long duration of the gluten-free diet (GFD) was able to lower the risk of CVD in celiac patients. Finally, CD significantly decreased the frequency of carotid plaques (11.8% vs. 40.1%, p < 0.001). Conclusions. Our retrospective study demonstrated that CD reduces the risk of CVD in general and more specifically of carotid lesions after adjusting for potential confounders, especially in those on GFD for a long time.
Breast lesion classification based on absorption and composition parameters: a look at SOLUS first outcomes

A machine learning classification algorithm is applied to the SOLUS database to discriminate benign and malignant breast lesions, based on absorption and composition properties retrieved through diffuse optical tomography. The Mann-Whitney test indicates oxy-hemoglobin (p-value = 0.0007) and lipids (0.0387) as the most significant constituents for lesion classification, but work is in progress for further analysis. Together with sensitivity (91%), specificity (75%) and the Area Under the ROC Curve (0.83), special metrics for imbalanced datasets (27% of malignant lesions) are applied to the machine learning outcome: balanced accuracy (83%) and Matthews Correlation Coefficient (0.65). The initial results underline the promising informative content of optical data.
Kaifangfa and Translation of Coordinate Axes

Since ancient civilization, solving equations has become one of the most important subjects in mathematics and mathematics education. The extractions of square roots and cube roots were first dealt in Jiuzhang Suanshu in the setting of subdivisions. Extending these, Shisuo Kaifangfa and Zengcheng Kaifangfa were introduced in the 11th century and the subsequent development became one of the most important contributions to mathematics in the East Asian mathematics. The translation of coordinate axes plays an important role in school mathematics. Connecting the translation and Kaifangfa, we find strong didactical implications for improving students’ understanding the history of Kaifangfa together with the translation itself although the latter is irrelevant to the former’s historical development.
On the connections between the cdio framework and challenge-based learning

Challenge-based learning (CBL) is a learning approach that has received increased attention during the last years. In some of the publications about CBL the connections to the CDIO (conceive-design-implement-operate) framework is discussed, and the purpose of this paper is to discuss these connections further. CBL has connections to both Problem-based learning (PBL) and Project-based learning (PjBL), but while these are learning approaches, the CDIO framework has a program perspective, including aspects of learning approaches, and hence a wider scope. The connections and differences between CBL and CDIO are discussed based on the components of the CDIO Standards.
MECHANISMS OF SELF-REGULATION: A VIEW SYSTEMS

INTRODUCTION 23 PARADIGM VARIATIONS A DBASIC MODELS 25 Procedural, Epistemic, and Conceptual Divergence 26 Goal Selection 27 Goal Cognition 28 Strategic, On-Line Goal Coordination: The Systems Base 29 PROXIMAL VO ITIONAL REGULATORS 30 Goal (Standard) Setting 31 Self-Monitoring. 33 The Activation and Use of Standards 34 Discrepancy Detection, Self-Evaluative Judgment, Self-Consequation 35 The Implementation of Discrepancy-Reduction Skills 36 Self-Efficacy 37 METASKILLS ANDBOUNDARY CONDITIONS 38 Metaskills 39 Boundary Conditions 41 SELF-REGULATORY FAILURE: CONCEPTS AND DYNAMICS 42 FINAL COMMENT 44
A New Hybrid Fault Diagnosis Method for Wind Energy Converters

Fault diagnostic techniques can reduce the requirements for the experience of maintenance crews, accelerate maintenance speed, reduce maintenance cost, and increase electric energy production profitability. In this paper, a new hybrid fault diagnosis method based on multivariate empirical mode decomposition (MEMD), fuzzy entropy (FE), and an artificial fish swarm algorithm (AFSA)-support vector machine (SVM) is proposed to identify the faults of a wind energy converter. Firstly, the measured three-phase output voltage signals are processed by MEMD to obtain three sets of intrinsic mode functions (IMFs). The multi-scale analysis tool MEMD is used to extract the common modes matching the timescale. It studies the multi-scale relationship between three-phase voltages, realizes their synchronous analysis, and ensures that the number and frequency of the modes match and align. Then, FE is calculated to describe the IMFs’ complexity, and the IMFs-FE information is taken as fault feature to increase the robustness to working conditions and noise. Finally, the AFSA algorithm is used to optimize SVM parameters, solving the difficulty in selecting the penalty factor and radial basis function kernel. The effectiveness of the proposed method is verified in a simulated wind energy system, and the results show that the diagnostic accuracy for 22 fault modes is 98.7% under different wind speeds, and the average accuracy of 30 running can be maintained above 84% for different noise levels. The maximum, minimum, average, and standard deviation are provided to prove the robust and stable performance. Compared with the other methods, the proposed hybrid method shows excellent performance in terms of high accuracy, strong robustness, and computational efficiency.
Microwave radiative transfer through horizontally inhomogeneous precipitating clouds

Recent advances in cloud microphysical models have led to realistic three-dimensional distributions of cloud constituents. Radiative transfer schemes can make use of this detailed knowledge in order to study the effects of horizontal as well as vertical inhomogeneities within clouds. This study looks specifically at the differences between three-dimensional radiative transfer results and those obtained by plane parallel, independent pixel approximations in the microwave spectrum. A three-dimensional discrete ordinates method as well as a backward Monte Carlo method are used to calculate realistic radiances emerging from the cloud. Analyses between these models and independent pixel approximations reveal that plane parallel approximations introduce two distinct types of errors. The first error is physical in nature and is related to the fact that plane parallel approximations do not allow energy to leak out of dense areas into surrounding areas. In general, it was found that these errors are quite small for emission-dominated frequencies (37 GHz and lower) and that physical errors are highly pronounced only at scattering frequencies (85 GHz) where large deviations and biases up to 8 K averaged over the entire cloud were found. The second error is more geometric in nature and is related to the fact that plane parallel approximations cannot accommodate physical boundaries in the horizontal dimension for off-nadir viewing angles. The geometric errors were comparable in magnitude for all frequencies. Their magnitude, however, depends on a number of factors including the scheme used to deal with the edge, the nature of the surface, and the viewing angle.
Extended delay in endoscopic mucosal resection is not associated with adverse outcomes: Findings from the COVID-19 pandemic

Background and study aims The aim of this study was to investigate the impact of delayed endoscopic mucosal resection (EMR) of colorectal polyps on health outcomes. Patients and methods A bidirectional cohort study was completed. A baseline group consisting of all EMRs performed within a 15-month period before a province-wide, government-mandated cessation of EMR procedures due to the global pandemic was compared to EMRs impacted by the shutdown, defined as the COVID-19-delayed group. The primary outcome was the incidence of malignant polyps. Secondary outcomes included technical success, polyp recurrence at follow-up colonoscopy, advanced polyp histology, probability of meeting endoscopic criteria for adequate resection for malignant polyps, metastatic colorectal cancer, and complications. Results A total of 268 EMR procedures were included in the study cohort, of which 208 formed the baseline group and 60 were in the COVID-19-delayed group. The median (IQR) patient age was 72 (13.0) and 113 (41.2 %) were females. The median (IQR) wait time was 92 days (87.8) in the baseline group and 191 days (127.8) in the COVID-19-delayed group ( P < 0.001). Overall, there were no significant differences in the incidence of malignant polyps, technical success, polyp recurrence on follow-up colonoscopy, advanced polyp histology, adequate endoscopic resection for malignant polyps, metastatic colorectal cancer, or complications between the two groups ( P > 0.05 for all outcomes). Conclusions A longer wait time for EMR of colorectal polyps, increasing from a median of 92 to 191 days, was not associated with worse outcomes.
A Multi-Side Increase by Degrees Algorithm at Machine Learning

The conflict between validity and extensibility can be solved by using a multi side increase by degrees algorithm(shortened form MIDA) at machine learning in a data set with a feature space of high dimensionality and with large amount of samples that belong to many different classes.In the algorithm,the sample set is divided into several sample subsets step by step by double point.These feature subsets to match each sample set may be extracted at the same time.The method of different treatment to each sample subset is similas to that facing difficult problems people consider and seek a answer from different emphases and multi sides.The algorithm can classify the difficult problems effectually and raise the extensibility and reduce the complexity in condition of established accuracy.The multi side increase by degrees algorithm bases on a covering algorithm at machine learning.MIDA is used to classify a date set from Shanghai's stock,and the result is satisfied.
Constrained Bayes Estimation with Applications

Abstract Bayesian techniques are widely used in these days for simultaneous estimation of several parameters in compound decision problems. Often, however, the main objective is to produce an ensemble of parameter estimates whose histogram is in some sense close to the histogram of population parameters. This is for example the situation in subgroup analysis, where the problem is not only to estimate the different components of a parameter vector, but also to identify the parameters that are above, and the others that are below a certain specified cutoff point. We have proposed in this paper Bayes estimates in a very general context that meet this need. These estimates are obtained by matching the first two moments of the histogram of the estimates, and the posterior expectations of the first two moments of the histogram of the parameters, and minimizing, subject to these conditions, the posterior expectation of the Euclidean distance between the estimates and the parameters. Several applications of the m.
Mathematical research at the Aeronautical Research Laboratories 1939–1960

Abstract The Aeronautical Research Laboratories were established in Australia in 1939 as the CSIR Division of Aeronautics. Mathematicians were amongst the first staff employed, and their number reached a peak in the mid 1950s. They were an able group: in their subsequent careers 12 became Professors, 5 obtained higher doctorates, 6 became Fellows of the Australian Academy of Science and 6 Fellows of the Royal Society. They published over 100 papers, and these are discussed here under 11 separate headings. The length of discussion given here to the various areas of research is not uniform. I have emphasised those with which I am familiar and those that interest me personally. Nevertheless, I believe the present paper provides an accurate picture of the mathematical research that was carried out at ARL during the period under review, and makes it clear that mathematicians at ARL made substantial contributions to many areas of theoretical aeronautics.
Mapping Chinese Medical Entities to the Unified Medical Language System

Background Chinese medical entities have not been organized comprehensively due to the lack of well-developed terminology systems, which poses a challenge to processing Chinese medical texts for fine-grained medical knowledge representation. To unify Chinese medical terminologies, mapping Chinese medical entities to their English counterparts in the Unified Medical Language System (UMLS) is an efficient solution. However, their mappings have not been investigated sufficiently in former research. In this study, we explore strategies for mapping Chinese medical entities to the UMLS and systematically evaluate the mapping performance. Methods First, Chinese medical entities are translated to English using multiple web-based translation engines. Then, 3 mapping strategies are investigated: (a) string-based, (b) semantic-based, and (c) string and semantic similarity combined. In addition, cross-lingual pretrained language models are applied to map Chinese medical entities to UMLS concepts without translation. All of these strategies are evaluated on the ICD10-CN, Chinese Human Phenotype Ontology (CHPO), and RealWorld datasets. Results The linear combination method based on the SapBERT and term frequency-inverse document frequency bag-of-words models perform the best on all evaluation datasets, with 91.85%, 82.44%, and 78.43% of the top 5 accuracies on the ICD10-CN, CHPO, and RealWorld datasets, respectively. Conclusions In our study, we explore strategies for mapping Chinese medical entities to the UMLS and identify a satisfactory linear combination method. Our investigation will facilitate Chinese medical entity normalization and inspire research that focuses on Chinese medical ontology development.
Silicon-based tunable optical delay lines and switches for next generation optical telecommunications

We report our recent progress on reconfigurable optical true time delay lines (RTTDL) and optical switches. The RTTDL is composed of 8 stages of MZIs connected by 7 waveguide pairs with an incremental length difference. Variable optical attenuators are inserted in the delay waveguides to suppress crosstalk caused by the residual signals from noise paths. Transmission of a 25 Gbps PRBS signal confirms the signal fidelity after a maximum of 1.27 ns delay. The optical switch is based on a Benes architecture with Mach-Zehnder interferometers (MZI) as the switching elements. Both p-i-n diodes and silicon resistive micro-heaters are integrated in the MZI arms for electrical tuning and phase correction, respectively. The measured on-chip insertion loss of the 4×4 switch is < 8 dB. Transmission of a 50 Gb/s quadrature phase shift keying (QPSK) optical signal verifies its switching functionality.
Supporting mental health self-care discovery through a chatbot

Good mental health is imperative for one’s wellbeing. While clinical mental disorder treatments exist, self-care is an essential aspect of mental health. This paper explores the use and perceived trust of conversational agents, chatbots, in the context of crowdsourced self-care through a between-subjects study (N = 80). One group used a standalone system with a conventional web interface to discover self-care methods. The other group used the same system wrapped in a chatbot interface, facilitating utterances and turn-taking between the user and a chatbot. We identify the security and integrity of the systems as critical factors that affect users’ trust. The chatbot interface scored lower on both these factors, and we contemplate the potential underlying reasons for this. We complement the quantitative data with qualitative analysis and synthesize our findings to identify suggestions for using chatbots in mental health contexts.
Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence

In the last decade, organoids have gained popularity for developing mini-organs to support advancements in the study of organogenesis, disease modeling, and drug screening and, subsequently, in the development of new therapies. To date, such cultures have been used to replicate the composition and functionality of organs such as the kidney, liver, brain, and pancreas. However, depending on the experimenter, the culture environment and cell conditions may slightly vary, resulting in different organoids; this factor significantly affects their application in new drug development, especially during quantification. Standardization in this context can be achieved using bioprinting technology—an advanced technology that can print various cells and biomaterials at desired locations. This technology offers numerous advantages, including the manufacturing of complex three-dimensional biological structures. Therefore, in addition to the standardization of organoids, bioprinting technology in organoid engineering can facilitate automation in the fabrication process as well as a closer mimicry of native organs. Further, artificial intelligence (AI) has currently emerged as an effective tool to monitor and control the quality of final developed objects. Thus, organoids, bioprinting technology, and AI can be combined to obtain high-quality in vitro models for multiple applications.
Can the agglomeration of producer services boost China’s ‘going out’?

ABSTRACT As China has been encouraging enterprises to ‘go global’ and actively promoting the optimization of industrial structure, it is important to discuss the impact of its outward foreign direct investment (OFDI) considering producer service industry agglomeration. For analysing the mechanism by which the agglomeration of producer services affects China’s OFDI, this study uses inter-provincial panel data from 2004 to 2019 and a spatial Durbin model to empirically test the impact of producer service agglomeration on OFDI. We show that the agglomeration of producer services significantly promotes OFDI in a particular region through economies of scale and enterprise productivity improvement. And it also significantly promotes OFDI in its neighbouring regions. The effect of producer service agglomeration on OFDI shows regional heterogeneity. Namely, the agglomeration of producer services in the eastern region promotes the OFDI in this region and it has not had a significant impact on the OFDI in neighbouring regions. Further, the agglomeration of producer services in the central and western regions does not have a significant effect on their OFDI and that of neighbouring regions.
Integration of unsteady friction models in pipe flow simulations

Various approaches to integrate instantaneous acceleration models are examined. The basic physical model consists of the one-phase flow water hammer equations with the unsteady wall friction model of Brunone. The numerical scheme is based on characteristic upwind finite differences, representing an extension of the Godunov schemes to the non-conservative hyperbolic equations. The most accurate solutions result from the basic version of this method, which takes into account the effects of spatial and temporal derivatives of the unsteady friction term on the eigenvalues of the hyperbolic equations. A convergence analysis shows that second-order accuracy is obtained on smooth solutions with this approach, but only if the discontinuity in the unsteady friction correlation is removed. Two simpler numerical schemes treat the unsteady friction term as a source term and neglect its influence on the eigenvalues. The results obtained with the simplified schemes converge to the exact solutions, but exhibit larger numerical diffusivity than the basic version of the method.
Reconstruction of Mars Pathfinder Aeroheating and Heat Shield Response Using Inverse Methods

The Mars Pathfinder probe entered the Martian atmosphere in 1997 and contained instrumentation that provided measurements of the superlight ablator (SLA) heat shield subsurface temperature at different locations during the entry sequence. These measurements represented the first Martian aeroheating flight data since the Viking Lander missions. The objective of this paper is to reconstruct the Pathfinder entry vehicle’s aerothermal heating and heat shield material response using updated modeling tools and approaches in both direct and inverse manners. The direct approach consists of performing updated computational fluid dynamics calculations on a newly reconstructed entry trajectory to characterize the vehicle’s heating environment. From the calculated heating boundary conditions, the heat shield in-depth temperature response is computed using an updated thermal response and ablation model for the SLA material. These predictions are compared directly to the flight data. In addition to the direct compariso.
Pulsar observations and small-scale structure in interstellar H I

If small-scale structure is present in H I clouds, then H I absorption profiles towards pulsars with large proper motions should show changes on a time-scale of a few years. We have compared absorption measurements, made with an interval of about four years, towards two pulsars and find a marginal difference in one of them. If confirmed, this could imply structures on the scale of ∼ 1000 AU in H I clouds
Fundamental properties and performance of conventional bearings-only target motion analysis

This paper considers the problem of estimating the position and velocity of an object from noise corrupted bearing measurements obtained by a single moving observation platform. The process is inherently nonlinear and exhibits unusual observability properties that are geometry-dependent. A maximum likelihood estimate (MLE) of the target motion analysis solution is developed and its performance analyzed. A comparison is drawn between the MLE and two previously reported methods, a nonlinear modified-instrumental variable estimate (MIV) and the pseudo-linear estimate (PLE). Both the MIV and PLE are shown to derive from approximations to the nonlinear measurement equation and therefore share some common properties with the MLE. The limits on performance that can be expected from processing bearing data are detailed. Specifically, for long range-to-baseline geometries, approximate expressions for the Cramer-Rao bound are derived. Extension of the results to the practical filters approximately predicts numerically observed behavior. For less restrictive geometries, bounds are presented. Incorporation of a target speed constraint on the MLE results in a transition to a lower dimensional problem as noise level and range increases. Monte Carlo experimental results are presented and the improvements realized by the MLE techniques are evident.