Miracle-dz/UniFAR-FTUs huggingface dataset:
Characteristics and survival of patients diagnosed with cardiac sarcoidosis: A case series

Background Sarcoidosis is a multiorgan system granulomatous disease of unknown etiology. It is hypothesized that a combination of environmental, occupational, and/or infectious factors provoke an immunological response in genetically susceptible individuals, resulting in a diversity of manifestations throughout the body. In the United States, cardiac sarcoidosis (CS) is diagnosed in 5% of patients with systemic sarcoidosis, however, autopsy results suggest that cardiac involvement may be present in > 50% of patients. CS is debilitating and significantly decreases quality of life and survival. Currently, there are no gold-standard clinical diagnostic or monitoring criteria for CS. Methods We identified patients with a diagnosis of sarcoidosis who were seen at the Simmons Center from 2007 to 2020 who had a positive finding of CS documented with cardiovascular magnetic resonance (CMR) and/or endomyocardial biopsy as found in the electronic health record. Medical records were independently reviewed for interpretation and diagnostic features of CS including late gadolinium enhancement (LGE) patterns, increased signal on T2-weighted imaging, and non-caseating granulomas, respectively. Extracardiac organ involvement, cardiac manifestations, comorbid conditions, treatment history, and vital status were also abstracted. Results We identified 44 unique patients with evidence of CS out of 246 CMR reports and 9 endomyocardial biopsy pathology reports. The first eligible case was diagnosed in 2007. The majority of patients (73%) had pulmonary manifestations, followed by hepatic manifestations (23%), cutaneous involvement (23%), and urolithiasis (20%). Heart failure was the most common cardiac manifestation affecting 59% of patients. Of these, 39% had a documented left ventricular ejection fraction of < 50% on CMR. Fifty eight percent of patients had a conduction disease and 44% of patients had documented ventricular arrhythmias. Pharmacotherapy was usually initiated for extracardiac manifestations and 93% of patients had been prescribed prednisone. ICD implantation occurred in 43% of patients. Patients were followed up for a median of 5.4 (IQR: 2.4–8.5) years. The 10-year survival was 70%. In addition to age, cutaneous involvement was associated with an increased risk of death (age-adjusted OR 8.47, 95% CI = 1.11–64.73). Conclusion CMR is an important tool in the non-invasive diagnosis of CS. The presence of LGE on CMR in a pattern consistent with CS has been shown to be a predictor of mortality and likely contributed to a high proportion of patients undergoing ICD implantation to decrease risk of sudden cardiac death. Clinical implications Additional studies are necessary to develop robust criteria for the diagnosis of CS with CMR, assess the benefit of serial imaging for disease monitoring, and evaluate the effect of immunosuppression on disease progression.
Conditional Gaussian mixture modelling for dietary pattern analysis

Summary. Free‐living individuals have multifaceted diets and consume foods in numerous combinations. In epidemiological studies it is desirable to characterize individual diets not only in terms of the quantity of individual dietary components but also in terms of dietary patterns. We describe the conditional Gaussian mixture model for dietary pattern analysis and show how it can be adapted to take account of important characteristics of self‐reported dietary data. We illustrate this approach with an analysis of the 2000–2001 National Diet and Nutrition Survey of adults. The results strongly favoured a mixture model solution allowing clusters to vary in shape and size, over the standard approach that has been used previously to find dietary patterns.
COVID anxiety and its predictors among Slovak adolescents

Introduction The COVID-19 pandemic and its related restrictions, mainly social distancing, had an impact on the mental health of various groups, including adolescents. Methods The main goal of our study was to explore the impact of gender, age, resilience (measured using the Brief Resilience Scale), attachment anxiety, attachment avoidance (both measured using the Experiences in Close Relationships Revised Scale for adolescents), and mental and general health (measured using items of SF-8 Health Survey) on COVID anxiety (measured using the COVID Anxiety Scale) among a sample of Slovak adolescents (N = 1,786, age 15 to 19, mean age = 16.8, SD = 1.2). The data were collected online between 13 April and 24 May 2021. Results Four nested linear regression models were fitted to the data and evaluated. The significant predictors that had a greater effect than our smallest effect size of interest (β = 0.10) were gender (β = −0.26, p < 0.001, where boys had lower scores in COVID anxiety), general and mental health (β = −0.13 and β = −0.14, respectively, both with p < 0.001), resilience (β = −0.12, p < 0.001), and attachment avoidance (β = −0.11, p < 0.001). Similarly, age and attachment anxiety were significant predictors with a lower effect size (β = 0.06, p = 0.003, and β = 0.09, p < 0.001, respectively). Discussion Our results are in line with previous research findings highlighting the importance of prevention and interventions programs focused mainly on preventing loneliness and social disconnection, fostering secure attachment with parents and peers, and increasing the resilience of adolescents, especially in the stressful time of a pandemic, to promote their mental health.
The Bahadur-Kiefer Representation of Lp Regression Estimators

We consider the following linear regression model: where are independent and identically distributed random variables, Yi, is real, Zi has values in Rm, Ui, is independent of Zi, and θ0 is an m-dimensional parameter to be estimated. The Lp estimator of θ0 is the value 6n such that Here, we will give the exact Bahadur-Kiefer representation of θn, for each p ≥ 1. Explicitly, we will see that, under regularity conditions, where and c is a positive constant, which depends on p and on the random variable X.
Toponym Resolution in Text with Neural Language Models

Toponym resolution concerns the task of mapping names for places (toponyms), previously detected in a textual document, into the corresponding locations on Earth (e.g., through geo- graphical coordinates). Complexity arises when a single place name refer to many real locations (e.g., Paris can refer to more than 50 places in over 20 countries around the world), making disambiguation a non-trivial procedure. We present a novel toponym resolution method based on deep learning, taking inspiration from recent methods achieving state-of- the-art results. The proposed neural network architecture is based on a pre-trained language model, sharing parameters for the processing of different inputs (e.g., the toponym to disambiguate along with the surrounding words). We use the HEALPix method to model toponym resolution as a classiﬁcation task. Subsequently, the result of the classiﬁcation is used to inform the prediction of geographic coordinates for each place name reference, through a separate layer that di- rectly applies the great circle distance as a loss function. Additionally, we also test the use of external geophysical in- formation, by using an additional term in the cost function for each geophysical property considered, thus allowing the model to obtain more information about the locations when making predictions. The proposed model was tested on col- lections of documents used and developed in previous studies. The obtained results show that the proposed model can signiﬁcantly outperform previous approaches.
From puppet-master creation to false detection

— Nowadays, many issues in society are affected by the misuse of deepfakes. One can say that we came to a point when prior knowledge of image processing is not a requirement for deepfake creation. With different motives, in a short period, and with limited resources, many deepfakes can appear on the internet. That brings us to testing that hypothesis of how easy and how fast someone can make a deepfake. In this paper several puppet-master creations are made for experimental purposes. In the aftermath of deepfake creation, an off-shelf available deepfake detection algorithm is applied for the detection analysis which is expected not to be universal solution for every type of deepfake realization. This brings us to high false detection, where specific cases are considered in this paper, like closed eye and head shape effects.
A regular Strouhal number for large-scale instability in the far wake of a rotor

Abstract The flow behind a model of a wind turbine rotor is investigated experimentally in a water flume using particle image velocimetry (PIV) and laser Doppler anemometry (LDA). The study performed involves a three-bladed wind turbine rotor designed using the optimization technique of Glauert (Aerodynamic Theory, vol. IV, 1935, pp. 169–360). The wake properties are studied for different tip speed ratios and free stream speeds. The data for the various rotor regimes show the existence of a regular Strouhal number associated with the development of an instability in the far wake of the rotor. From visualizations and a reconstruction of the flow field using LDA and PIV measurements it is found that the wake dynamics is associated with a precession (rotation) of the helical vortex core.
A Low-Complexity DNN-Based DoA Estimation Method for EHF and THF Cell-Free Massive MIMO

We study the problem of direction of arrival (DoA) estimation for cell-free massive MIMO (m-MIMO) systems operating over extremely high frequency (EHF) and terahertz (THF) bands, where the wireless channel can effectively be modeled by a line-of-sight path. For this model, a low-complexity deep neural network (DNN)-based method is proposed to estimate the DoA of a radio wave impinging on an access point (AP) equipped with an antenna array. To train the DNN, a special feature set is proposed obtained from the first superdiagonal entries of the spatial correlation matrix. This selection of features makes it possible to employ a DNN with only a few low-dimensional layers, which considerably speeds up training and processing. More importantly, it is shown that the trained DNN is robust against quantization noise in the array snapshot data. This property makes the centralized implementation of the proposed DNN-based method feasible, which is particularly well-suited for cell-free m-MIMO. Through extensive simulations, the new method is shown to achieve an estimation performance that nearly matches or exceeds that of classical bechmark methods, but with considerably reduced complexity.
Elemental Variability of PM 2.5 aerosols in Old Jeddah, Saudi Arabia

Air particulate matter with a diameter ≤ 2.5 µm (PM 2.5 ) has been assembled from the historical old Jeddah district (downtown) throughout the whole year. Additional PM 2.5 aerosols have been collected during the autumn and winter seasons from another newly constructed district inside Jeddah city (Alnaeem). The annual concentrations of the total mass of the PM 2.5 aerosols from old Jeddah and Alnaeem sites were found to be 43 ± 6 and 61 ± 14 µg/m 3 , respectively. These values are greater than the annual mass concentration of the air quality standards of the European Commission (EC, 25 µg/m 3 ) and the world health organization (WHO, 10 µg/m 3 ). The elemental analysis of the collected �ne atmospheric aerosols has been achieved by an energy dispersive X-ray �uorescence (EDXRF) with three secondary targets (CaF, Ge, and Mo). Quantitative elemental analyses of twenty-two (22) elements have been achieved starting from the low Z element (Na) up to the high Z element (Pb). Although the old Jeddah site is not well organized, the elemental concentrations and total mass concentrations are lower than other sites. The statistical analyses including enrichment factors, the correlation analysis of Pearson, and the principal component analysis reveal more information about the source identi�cation of the PM 2.5 aerosols collected from both locations. It was recognized that the quanti�ed elements Al, Si, K, Ca, Ti, Mn, Fe, Rb, and Sr originate from a natural source. On the other hand, the elements Ta, Br, Pb, Sc, Ni, Cu, Zn, and S originate from anthropogenic source. Finally, the elements Na, Cl, and Br come mainly from the sea spray source.
An Undergraduate Seminar Emphasizing Oral Presentation of Research Mathematics

ABSTRACT An undergraduate seminar in mathematics, featuring student lectures on advanced material, is an excellent way to introduce students to reading journal articles and graduate level texts, and to teach them to give oral presentations. These skills are important for all students. Here I give details of planning and running such a course, describing my experience using topics in theoretical computer science. Two guides for students are included which have proven very useful in teaching seminars. One gives students basic techniques for reading papers in mathematics, and the other leads students through giving an oral presentation.
Dynamics of high-voltage pulsed cylindrical sheath

A semi-analytic model of collisionless sheath in plasma immersion ion implantation (PI/sup 3/) for a step bias with finite rise time in cylindrical geometry has been developed. The model takes into account the formation of the presheath, predicts the sheath overshooting and its further recovery to the steady-state Child value. To verify the model, a sheath dynamics has been investigated experimentally on a 30-kV PI/sup 3/ setup using the positively biased Langmuir probe technique. The measurements have been carried out in argon and helium plasmas of inductively coupled and hot cathode plasma sources. The model predictions agreed well with the experimental results.
Numerical Studies of Stokes Flow in Confined Geometries

Title of thesis: NUMERICAL STUDIES OF STOKES FLOW IN CONFINED GEOMETRIES Yechun Wang, Master of Science, 2004 Thesis directed by: Professor Panagiotis Dimitrakopoulos Department of Chemical Engineering The current thesis includes two distinct projects. The first study involves the development of a novel three-dimensional Spectral Boundary Element algorithm for interfacial dynamics in Stokes flow. Our algorithm is the only available highorder/high-accuracy methodology for the problem of droplet deformation in viscous flows. By applying this algorithm to several interfacial problems, we find that our results are in excellent agreement with experimental findings, analytical predictions and previous numerical computations. The second project studies viscous flows over a protuberance on the inner wall of a solid microtube, a problem relevant to both physiological systems and microfluidic devices. The shear stress, drag and torque on the protuberance are determined as functions of the spreading angle and the relative size of the protuberance which may represent leukocytes, blood clots or endothelial cells on the microvessel wall. This study facilitates the understanding of mechano-transduction phenomena as well as cell adhesion in blood flow. NUMERICAL STUDIES OF STOKES FLOW IN CONFINED GEOMETRIES
The Costs of Job Displacement over the Business Cycle and Its Sources: Evidence from Germany

We document the sources behind the costs of job loss over the business cycle using administrative data from Germany. Losses in annual earnings after displacement are large, persistent, and highly cyclical, nearly doubling in size during downturns. A large part of the long-term earnings losses and their cyclicality is driven by declines in wages. Key to these long-lasting wage declines and their cyclicality are changes in employer characteristics, as displaced workers switch to lower-paying firms. Changes in characteristics of workers or displacing firms explain little of the cyclicality, though nonemployment durations correlated with losses in employer effects play a role. JEL: E32, J31, J42, J62, J63, J64, J65
THE EFFECT OF SITUATIONAL LEADERSHIP STYLE AND COMPENSATION TO IMPROVE EMPLOYEES PERFORMANCE AT BANK SECTOR IN BALI – INDONESIA

: The purpose of this study is to examine and determine the effect of situational leadership style and compensation on job satisfaction to improve performance. This study uses a quantitative method research design to test the models and instruments that have been developed by previous researchers through inferential statistics by using Structural Equation Modelling (SEM), with Partial Least Square (PLS) approach . The population consists of 187 employees of PT. Taspen Bank Mandiri Branch office Melati Denpasar Bali Indonesia and a sample collected is 75 employees. The research results showed that (1) situational leadership style has a positive and significant effect on job satisfaction, (2) compensation has a positive and significant effect on job satisfaction, (3) situational leadership style has a positive and significant effect on employee performance, (4) compensation has a positive and significant effect on employee performance, (5) job satisfaction has a positive and significant effect on employee performance. The implication of this study practically is providing contributions to strengthen the theory and results of previous studies and trust in the world of practice relating to the behavior of the influence of situational leadership style variables and compensation on job satisfaction and employee performance.
Measuring the Angular Accuracy of a Clinician-Performed Epley Maneuver Used to Treat Benign Paroxysmal Positional Vertigo

Introduction Particle repositioning maneuvers have become the criterion standard for managing benign paroxysmal positional vertigo. The Epley canalolith repositioning maneuver is used to treat posterior canal benign paroxysmal positional vertigo and is successful in up to 90% of cases. However, when performed, there are many clinician variabilities, and angles are approximate. It is not known how accurate each angle needs to be for the target canal to be adequately stimulated. The objective of this study was to measure the angular accuracy of clinician-guided Epley maneuvers using a three-axis accelerometer. Methods Ten healthy subjects were recruited; participants had no known audio vestibular pathology. Five right-hand–dominant clinicians performed Epley maneuvers on both ears of two different participants. Twenty maneuvers were carried out in total. Angular movements were recorded using a vestibular feedback electronic device, the SHIMMER accelerometer. Data were recorded and analyzed using the EYESWEB Open Platform. Results Results showed that there was angular error at every stage of the clinician-performed Epley maneuver. The most accurate movement was positioning the head to the left of 45 degrees for a left ear maneuver with an average error of 2.94 degrees. The least accurate was when positioning the patient to face the floor at 135 degrees from supine for a right ear maneuver with an average error of 17.6 degrees. Conclusion Even when experienced ENT clinicians perform a standard Epley maneuver, there is a wide range of angular inaccuracy at each stage. Face to floor is particularly inaccurate. However, given that a majority of procedures (90%) work on the first attempt, there must be an acceptable but unknown range of angular inaccuracy. Novel technologies could improve the angular accuracy, potentially give better results, and allow a broad range of individuals to perform a more accurate Epley maneuver.
Reexamining the 3-omega technique for thin film thermal characterization

The 3-omega method is widely used to measure thermal properties of thin films and interfaces. Generally, one-dimensional heat conduction across the film is assumed and the film capacitance is neglected. The change in the in-phase (real part) temperature response for the film-on-substrate case relative to the substrate-only case is, therefore, attributed to the sum of the bulk thermal resistance of the film and the thermal boundary resistance between the film and the substrate. Based on a rigorous and intuitive mathematical derivation, it is shown that this approach represents a limiting case, and that its use can cause significant errors in rather realistic situations when the underlying assumptions are not met. This article quantifies the error by introducing a new parameter called the ratio function R, which modifies the film thermal resistance and mathematically shows that it depends only on three dimensionless parameters that combine thermal properties and geometries of the film and the heated linewid.
Influence of the temperature on soil's exchangeable cations and cation exchange capacity, Derna district, Libya: A field and Laboratory study

This study conducted in Aljabal alakhdar (Green Mountain), Derna, Libya. It is the only wet region in Libya. Like other Mediterranean forests, it is exposed to the risk of fires. To assist in this, two different geographical units from the region (coastal and mountain), which been burned at different times; to identify whether these soils are regaining their pre-burn status over time. The studied properties were: the soil clay content, the soil organic matter (O M), the soil exchangeable cations and soil cation exchange capacity (CEC). It is obvious from the results that there is a relatively low clay content, compared to the contents of silt and sand, in both study sites and their burned and unburned areas. Soils of both study sites characterized by low organic matter content . The results indicated that, the basic exchangeable cations ranking was: Ca++ > Mg++ > Na+ > K+, in both study sites, for burned and unburned areas and at all depths. The rank order of these four cations did not change with depth in the four study areas except that sometimes-exchangeable potassium was more abundant than exchangeable sodium. The exchangeable calcium and magnesium account for about 80% of the CEC results so, the patterns of behaviour of the soil CEC are similar to the patterns of behaviour of these two elements.
Satellite Precipitation Measurements: What Have We Learnt About Cloud-Precipitation Processes From Space?

Precipitation is one of the fundamental elements that define global and regional climatology. Precipitation systems consist of a broad spectrum of three-dimensional structures in which microphysical processes interact with macro-scale processes in the cloud system and the ambient environment that prescribe the evolution of the system. Since 1970s, satellite observations of precipitation have been a fundamental tool in quantifying this complex interaction. They have first quantified the frequency and intensity of global precipitation, including remote areas over open oceans and polar regions, thus providing today’s precipitation climatology. More recently, satellite observations of cloud and precipitation have been exploited for understanding the physical mechanisms governing precipitation systems. A subset of these studies also provided observation-based metrics to probe physical processes operating in cloud-precipitation systems and to apply them as diagnostic measures for evaluating the representation of the processes in numerical models for better projections of future climate. In this chapter, we first review the theoretical basis of precipitation remote sensing from space and describe how it is practically applied in satellite missions. In the first part of the chapter, an
Bang-Bang Type Nonzero-sum Stochastic Differential Game and Related BSDEs with Discontinuous Generators

In this paper, we study a nonzero-sum stochastic differential game in Markovian framework. We show the existence of the Nash equilibrium point which is discontinuous and of bang-bang type under natural conditions. The main tool is the notion of backward stochastic differential equations which, in our case, are multidimensional with discontinuous generators with respect to z component.