Miracle-dz/UniFAR-FTUs huggingface dataset:
The Implications of an Idealized Large-Scale Circulation for Mechanical Work Done by Tropical Convection

A thermodynamic analysis is presented of an overturning circulation simulated by two cloud-resolving models, coupled by a weak temperature gradient parameterization. Taken together, they represent two separated regions over different sea surface temperatures, and the coupling represents an idealized large-scale circulation such as the Walker circulation. It is demonstrated that a thermodynamic budget linking net heat input to the generation of mechanical energy can be partitioned into contributions from the large-scale interaction between the two regions, as represented by the weak temperature gradient approximation, and from convective motions in the active warm region and the suppressed cool region. Model results imply that such thermodynamic diagnostics for the aggregate system are barely affected by the strength of the coupling, even its introduction, or by the SST contrast between the regions. This indicates that the weak temperature gradient parameterization does not introduce anomalous thermodynamic behavior. We find that the vertical kinetic energy associated with the large-scale circulation is more than three orders of magnitude smaller than the typical vertical kinetic energy in each region. However, even with very weak coupling circulations, the contrast between the thermodynamic budget terms for the suppressed and active regions is strong and is relatively insensitive to the degree of the coupling. Additionally, scaling arguments are developed for the relative values of the terms in the mechanical energy budget.
Allomorphs as paradigm indices: On-line experiments with Finnish free and bound stems

Two masked priming elements investigated the role of the system of stem allomorphs and the status of the nominative singular in lexical processing of Finnish inflected nouns. The results show that, first, free standing allomorphs significantly prime the corresponding nominative singular, e.g., 'saappaa-saapas'. Second, the results also show, that inflected nouns, e.g., 'sudelle', are equally strongly primed by the nominative singular, 'susi', than by an inflected form with a different stem, e.g., 'sutta'. We will argue that the stem allomorphs are separately represented at the form level and that the nominative singular does not enjoy a special status vis-a-vis other stem forms. The results are discussed in a decompositional framework that assumes separate levels of modality specific form representation and abstract lemma representation.
Mimicking Electronic Gaming Machine Player Behavior Using Reinforcement Learning

This study looks at how Reinforcement Learning (RL) approaches can be used to understand player behavior in Electronic Gaming Machines (EGMs) found in venues like casinos. The gaming business is keen to learn about the many types of player behavior and create virtual players mimicking these behaviors. To achieve this, we trained RL models to mimic player behavior by grouping different playing styles with K-means clustering and determining termination states for one of the playing behaviors. The Proximal Policy Optimization (PPO) and Actor Critic using Kronecker-Factored Trust Region (ACKTR) models were subsequently implemented, with the agents being re-warded based on their proximity to the termination states. Our findings suggest that the ACKTR model performed better than the PPO model, with the generated playing behavior demonstrating a high level of statistical similarity to real-world player behavior within the selected cluster.
Modeling the choice of shared micro-mobility services using XGBoost machine learning algorithm

Abstract. In recent years, shared micro-mobility services (e.g., bikes, e-bikes, and e-scooters) have been popularized at a rapid pace worldwide, which provide more choices for people’s short and medium-distance travel. Accurately modeling the choice of these shared micro-mobility services is important for their regulation and management. However, little attention has been paid to modeling their choice, especially with machine learning. In this paper, we explore the potential of the XGBoost model to model the three types of shared micro-mobility services, including docked bike, docked e-bike, and dockless e-scooter, in Zurich, Switzerland. The model achieves an accuracy of 72.6%. Moreover, the permutation feature importance is implemented to interpret the model prediction. It is found that trip duration, trip distance, and difference in elevation present higher feature importance in the prediction. The findings are beneficial for urban planners and operators to further improve the shared micro-mobility services toward sustainable urban mobility.
Periprocedural Off-label Use of Rivaroxaban in Patient with Atrial Fibrillation and a Persistent Left Atrial Appendage Thrombus Despite Standard Anticoagulation Therapy: A Case Report

Atrial fibrillation (AF) is a common cardiac arrhythmia characterized by irregular and rapid heart rates, which may lead to various complications, such as stroke, heart failure, and thrombus formation. One particular complication, the development of a left atrial appendage thrombus, increases the risk of thromboembolic events, posing significant health risks to affected individuals. Patients with atrial fibrillation with a left atrial appendage thrombus should receive oral anticoagulation with a non-vitamin K antagonist oral anticoagulant (NOAC), such as rivaroxaban in a standard dose of 15 mg or 20 mg, according to creatinine clearance. However, these guidelines do not provide clear instructions on managing patients with a left atrial appendage thrombus who have already been anticoagulated with 20 mg rivaroxaban for 21 days without thrombus resolution prior to cardioversion. In light of this, we attempted an off-label treatment approach by administering a double dose of rivaroxaban (15 mg twice daily) to a patient presenting with AF and a persistent left atrial appendage thrombus. This case report explores this innovative off-label treatment approach, emphasizing the importance of effective management strategies to mitigate the associated complications and improve patient outcomes. This case report describes a patient with atrial fibrillation and a left atrial appendage thrombus who underwent successful cardioversion after receiving 15 mg of rivaroxaban twice daily as an off-label treatment. The patient well tolerated the increased frequency of administration. This case report suggests that using 15 mg of rivaroxaban twice daily for 14-21 days as an off-label treatment may be viable for patients with atrial fibrillation and a persistent left atrial appendage thrombus despite standard anticoagulation therapy. Clinicians should consider this approach when developing treatment plans for these patients, especially when traditional management strategies have proven ineffective and while keeping in mind the findings of the X-VERT study.
An Experimental Investigation on the Relationship between MS Frequency Response and Coal and Gas Outburst

Microseismic (MS) frequency response is an important part of high-efficiency data mining to achieve the aim of coal and gas outburst (CGOB) early warning. Based on the variation pattern of acoustic emission (AE) signal in the coal failure process, the experimental characteristics of MS activity and typical signals CGOB were obtained in this study. First, the AE behavior of coal failure experiment was studied, and an explanation of laws was provided as follows: the fracture behavior of coal sample exhibits certain characteristics of AE response in terms of AE event count, signal amplitude, and frequency; each stage has its own physical meaning during the process of loading test. Based on these laws, CGOB experiments were carried out using a large CGOB physical simulation system with a MS monitoring system. Notching filter and wavelet packet transform technique were used in the denoising and feature extraction of six typical MS events (signals). The features of each stage, including the time-frequency domain, were extracted and quantitatively expressed. We finally arrive at the following conclusions: (1) CGOB exhibits significantly periodic characteristics, and each CGOB stage corresponds to the significant response characteristics of MS. CGOB presents varying characteristics, such as “valley-peaks-valley”. (2) From the incubation stage to happen stage of outburst, the spectrum significantly moved from extremely low frequency (100-200 Hz) to high-frequency band (approach to 1600 Hz). During the residual stage, MS frequency manifested the concentration distribution (50 Hz) and offered the advantage of energy concentration. (3) The phenomenon of signal energy also shows the trend of energy transform low to high and to low modes along with the process. Signals total energy distribution (42.81%, 1,437.5-1,812.5 Hz) in the happen stage are markedly larger than those of events in incubation stage (7.01%) and residual stage (1.44%). The methodology presented in this paper for CGOB signal analysis provides a new method to obtain MS response precursor and predict CGOB disaster. This approach can be useful for rockburst anticipation and control during mining in gas and highly stressed coal mines.
Characterisation of a multijet plasma device by means of mass spectrometric detection and iCCD imaging

Atmospheric pressure plasma jets (APPJs) have been one of the most studied nonthermal discharges in the past decade. Recently, the use of multiple jets in order to cover larger areas has become desirable. However, the interaction between neighboring jets is a common phenomenon that can greatly modify plasma characteristics up to the point of merging several jets into a single one. The present study focus on bringing new insight on this phenomenon, named jet-to-jet coupling, investigating the discharge modes (coupled and uncoupled) of a plasma source composed of an array of seven plasma jets arranged adjacent to one another and driven by a sinusoidal excitation. The experimental results achieved by means of mass spectrometry, show a considerable increase in ion concentrations in the plasma, up to some orders of magnitude in the case of negative ions, as an effect of jet-to-jet coupling. Temporally resolved imaging of the discharge also shows how the evolution and intensity of the discharge are greatly affected by jet-to-jet interaction. Air/helium mole fraction and negative ions concentration are regarded as the main possible parameters affecting the coupling phenomenon. Moreover, experimental results suggest that the presence of remnant conductive channels behind the ionization fronts governs the propagation of the next ionization fronts, independently from the direction of propagation (from the source toward the target or vice versa). Furthermore, a parametrical investigation of the coupled mode discharge showed the presence of a critical value of the imposed voltage for which a drastic change in the electrical characteristics of the discharge is observed.
Fluid–Solid Interaction Analysis on Iliac Bifurcation Artery: A Numerical Study

Atherosclerosis, which is commonly seen at regions with low wall shear stress (WSS) level in bifurcations, is a kind of fibro-fatty plaque accumulated on arterial walls. Aortic and iliac bifurcations have the highest proportion of patients among all atherosclerosis cases, thus it is necessary to numerically analyze the flow distribution and predict plaque positions in these bifurcations. Furthermore, using fluid–solid interaction (FSI) method could obtain a more exact flow pattern in arteries. In this study, a patient-specific model of aortic and iliac bifurcations was simulated with both FSI and rigid-wall cases. We analyzed the vessel deformation, WSS and flow distribution of this model. Computed tomography (CT) angiography was used in our study to create patient-specific model of aorto-iliac arteries. Real material properties and pulsatile fluid boundary conditions were applied in solid and fluid zones, respectively. We performed FSI and ordinary computational fluid dynamics (CFD) simulations with AYSYS 15.0 software (ANSYS Inc., Canonsburg, PA), and compared the diameter change, WSS and flow field between these two results. The diameter change between systolic phase and diastolic phase is 8–9% on abdominal aorta, and 3% on external and internal iliac arteries. The compliance of vessels corresponds to in-vivo observations. At peak systolic phase, the average WSS obtained in FSI simulation is 10% lower than in rigid-wall result, area of low-WSS region ([Formula: see text]) also increases by 78%. Wall deformation has a greater impact on WSS of those vessels with larger diameter, but hardly changes the shear level in smaller branches. Our result also shows that iliac bifurcations reveal more complicated secondary flow in systolic phase, comparing to other vessels, and stenosed iliac artery has more severe secondary flow than healthy artery. We obtained a feasible method for hemodynamic FSI research. The material parameters, boundary conditions and mesh could be used for further simulations, while the WSS and flow distribution may support clinical diagnosis and treatment. We concluded that compliance is a must-consider factor for simulating an accurate wall shear stress, because the vessel deformation in FSI simulation will significantly change the distribution of low-WSS zones. Moreover, more complicated secondary flow is detected in iliac arteries because it may interact between bifurcations. Stenosis in artery may also have a blocking effect on downstream blood flow.
A 3.02 pJ/Bit 3T-APS-Based In-Sensor Strong PUF Featuring Near-100% Hardware Reuse Ratio and High Resilience to Machine Learning Attacks

In this brief, we present an energy-efficient in-sensor strong physical unclonable function (PUF) based on the static entropy of 3-transistor active pixel sensor (3T-APS) structure that is widely-adopted in the CMOS image sensors (CIS). With ultra-small silicon area overhead of 0.25% dedicated to the added bias circuitries for column line and digital comparator for PUF bit generation, traditional 3T-APS-based CIS can be well-reused to construct the proposed strong PUF for authenticating the recorded images or videos. Taking advantage of the inherent high-resolution pixel array of CIS, the proposed strong PUF significantly extends the challenge-response-pair (CRP) space of the previous implementations. In addition, large CRP nonlinearity can be obtained by biasing the selected 3T-APS pixels at the subthreshold region, which further increases the complexity of the above extended CRP space and its resilience to various machine learning (ML) attacks. Moreover, the proposed strong PUF design is validated by the extensive measurement results of the prototype chips fabricated using a standard 65-nm CMOS process. Featuring a low energy consumption of 3.02 pJ/bit and a high area efficiency of $1.64\times 10^{33}$ bit/ $F^{2}$ , prediction error of 49.1%~51.84% can be achieved under various ML attacks based on artificial neural network, logistic regression, support vector machine and covariance matrix adaptation evolution strategy, with the number of adopted CRPs for training up to 10 million.
Raman self-frequency-shift of soliton crystal in a high index doped silica micro-ring resonator [Invited]

High index doped silica glass exhibiting low loss property and CMOS compatibility is a promising material in nonlinear optics. In this work, mode-locked soliton crystals (SCs) are demonstrated in a high-Q (>106) micro-ring resonator (MRR) made in this platform. The asymmetric spectra of SCs are numerically investigated and interpreted as the combined impact of Raman self-frequency shift (RSFS) and the wavelength-dependent loss. By precisely comparing the experimental and simulated spectra based on the perturbed Lugiato-Lefever equation (LLE), the Raman shock time is inferred to be at the range of 2.5 fs to 2.7 fs for this material.
Inertia for symmetric Toeplitz matrices

Abstract We try to factor symmetric Toeplitz matrix A by A = LPLT for finding inertia. We know A and P have the same inertia, namely they have eigenvalues of the same sign. Orthogonal or invertible matrix gives us special properties of this factorization. Thus this process gives us a partible way for finding sign of eigenvalues for symmetric Toeplitz matrices.
ON THE ROBUSTNESS OF PARTIAL AND MULTIPLE CORRELATION COEFFICIENT IN SAMPLING FROM A MIXTURE OF TWO NORMALS

In this paper; the null and non-null distributions of partial and multiple correlation coefficients are obtained when a sample of size N is taken from a mixture of two normal distributions with common covariance matrix ∑ mean vector μ1 and μ2 and mixing proportions ʎ and (1 — ʎ) respectively. Actual values of the size of these tests for one sided and two sided are obtained for some combination of parameters. Also, power of tests is computed. These calculations reveal that (i) for partial correlation coefficient, one sided tests are non-robust but the two sided tests are fairly robust . (ii) for multiple correlation coefficient, the level of significance remains very much stable and the power in a special case improves.
A new trust region method for nonsmooth nonconvex optimization

Abstract In this paper, we propose a nonsmooth trust region algorithm for nonconvex optimization problems. The algorithm is based on notion of the Goldstein -subdifferential, which are subgradients computed in some neighbourhoods of a point. The proposed method contains a new quadratic model of the classical trust region method, in which the gradient vector is replaced by a quasisecant. Then we apply a combined approach based on the Cauchy point and the dog-leg methods in order to solve the obtained model. The global convergence is established under some suitable assumptions. Finally, the algorithm is implemented in the MATLAB environment and applied on some nonsmooth test problems. Numerical results on some small-scale and large-scale nonsmooth optimization test problems illustrate the efficiency of the proposed algorithm in the practical computation.
Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three‐dimensional variational (3D‐Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations.
New approaches for track reconstruction in LHCb’s Vertex Locator

Starting with Upgrade 1 in 2021, LHCb will move to a purely software-based trigger system. Therefore, the new trigger strategy is to process events at the full rate of 30MHz. Given that the increase of CPU performance has slowed down in recent years, the predicted performance of the software trigger currently falls short of the necessary 30MHz throughput. To cope with this shortfall, the Upgrade High Level Trigger currently uses impact parameter cuts on VELO tracks to reduce the amount of tracks which require further processing. The presented work introduces an alternative approach to determine the impact parameter while achieving a more reliable uncertainty prediction than the current method, which could potentially improve the physics quality of these cuts at a later time.
Emissions codées par ondes planes en imagerie ultrasonore ultra-rapide

– Dans cet article une nouvelle methode pour l'imagerie ultrasonore medicale ultra-rapide par ondes planes est proposee. L'approche ici consiste a transmettre simultanement plusieurs ondes planes. Cette methode s'appuie sur l'encodage a l'emission des differentes ondes planes. La modelisation du probleme direct sous forme lineaire permet alors le decodage avant formation de voies des echos provenant du milieu. La methode proposee est validee par simulation acoustique. L'amelioration de la resolution spatiale est demontree sur un milieu compose de diffuseurs isoles. De plus, l'augmentation du contraste est illustree sur une inclusion hypo-echogene. Abstract – In this article a new emission method is proposed for plane wave ultra-fast ultrasound imaging. The principle consists in sending simultaneously several plane waves with different angles, each plane wave carrying a different emission code. The goal is to improve the image quality, compared to classical plane wave imaging, without decrease of the image rate. The linear model of the forward problem allows the decoding of the echoes coming from the medium. The method is validated on simulated data.
Nurses on the Front-Line of Diabetes Prevention

America is facing its first non-communicable, yet preventable, pandemic -Type 2 Diabetes Mellitus (T2DM) [1]. With approximately 14% of adults diagnosed with the disease and another 33% diagnosed with prediabetes, multiple stakeholders have committed to developing multilevel approaches to slow the rate of transition of prediabetes to T2DM [2]. Diabetes Prevention Program (DPP) is one evidence-based approach that has been referenced throughout many health care and health science journals. While physicians are noted as the gatekeepers of care, nurses and Advanced Practice Registered Nurses (APRNs) are employed across the care continuum to affect the incidence and outcomes of diabetes prevention and prediabetes management. Nurses, among the key providers of health care, are positioned to facilitate the implementation of evidence-based interventions (EBI), like the DPP, from clinical practice into community-based settings. However, the DPP remains largely an under-utilized approached within health care. There seems to be a knowledge-gap about the DPP and its scalability across diverse patient populations. The purpose of this educational manuscript is three-fold: (1) to provide background on the Diabetes Prevention Program, its use and scalability to real-world settings, (2) to address some of the challenges of DPP across cultures, and (3) to increase awareness of how policy supports and improves populations’ access to the DPP and its translational delivery models – reducing the prevalence of prediabetes, and hence diabetes, in this country.
Reduced Encoding Complexity for LDPC Codes Using Partially Random and Involutory Matrix Concept in the Generation of Parity Check Matrix

This study assesses the usefulness of the PhouChomVoy protected area by the local community to analyze the factors that influence individuals’ participation in the payment for environmental service program. This study uses a statistical analysis and econometric approach with data on 244 individuals. The results from the econometric equation show that the relevant factors are age, gender, status as the head of household, and income.