Miracle-dz/UniFAR-FTUs huggingface dataset:
Formation of a Dense Flux Rope by a Siphon Flow

The interaction of siphon flow with an initially linear Alfvén wave within an isolated chromospheric loop is investigated. The loop is modeled using 1.5D magnetohydrodynamics (MHD). The siphon flow undergoes a hydrodynamic (HD) shock, which allows the Alfvén instability to amplify the propagating waves as they interact with the shock and loop footpoints. The amplification leads to nonlinear processes strongly altering the loop equilibrium. Azimuthal twists of are generated and the loop becomes globally twisted with an azimuthal magnetic field of . The flow is accelerated to due to the propagating shock waves that form. Near the end of the simulation, where the nonlinear processes are strongest, flow reversal is seen within the descending leg of the loop, generating upflows up to . This flow reversal leads to photospheric material being “pulled” into the loop and spreading along its entirety. Within about 2.5 hr, the density increases by a factor of about 30 its original value.
Pengembangan Media Pembelajaran Berbasis Digital pada Materi Teks Drama untuk Meningkatkan Keterampilan Berbicara Siswa Kelas Xl SMK Bina Satria Medan

This study aimed to develop and assess the feasibility of digital-based learning media for drama text material in class XI SMK Bina Satria Medan. The Four-D Model technique proposed by Thiagarajan was used, consisting of four stages: define, design, develop, and disseminate. Data were collected through questionnaires, documentation, interviews, and tests. The results showed that the developed learning media was valid, with an average score of 76.38% across all aspects. Student learning outcomes also improved, with an average score of 92.6%, indicating the effectiveness of the learning media. The material expert validator scored it at 86.3%, while the media expert validator scored it at 90%. In conclusion, the digital-based learning media developed in this study is valid, effective, and practical for use in class XI SMK Bina Satria Medan.
An Exploratory Study Investigating Factors Influencing the Outpatient Delivery of Geriatric Rehabilitation

Background: Outpatient delivery of geriatric rehabilitation (GR) might contribute to preserving the accessibility and quality of GR, whilst dealing with an increasing demand for healthcare in an aging population. However, the application of outpatient GR differs between GR facilities. This study aimed to gain insight into factors influencing outpatient GR utilization. Methods: In this case study, 24 semi-structured interviews were conducted with physicians, physiotherapists, nurse practitioners, occupational therapists, and managers in GR. Interviews were transcribed and analyzed using summative content analysis. Results: Various patient-related barriers for using outpatient GR were mentioned including lacking social support and limited capacities and self-management skills. Additionally, professional-related barriers included a lack of awareness and consensus among care professionals regarding the possibilities and potential advantages of outpatient GR. Yet, most perceived barriers were related to efficiency and organization of outpatient GR (e.g., reimbursement system, lacking practical guidance). Still, most participants were in favor of increasing outpatient GR because of expected advantages for patients, GR organizations, and society. Conclusions: Despite experienced barriers, there seems to be agreement on the need to increase outpatient GR application. It is recommended to use the present findings to develop and evaluate new ways of organizing and reimbursing outpatient GR.
Multi-frequency entanglement router system

A high performance free-space Wavelength Division Multiplexed (WDM) transceiver system is assessed as to its viability for routing collinear entangled photons in place of the classical optical signals for which it was designed. Explicit calculations demonstrate that entanglement in the input state is retained through transit of the system without intrinsic loss. Introducing spatial degrees of freedom changed the entanglement so that it could be manifested at remote locations, as required in non-local Bell test measurements or Quantum Key Distribution (QKD) Protocols. It was also found that by adding proper components, the exit state could be changed from being frequency entangled to polarization entangled, with respect to the (remote) paths of the photons. Finally it was found possible to route a complete entangled state to either of the two remote users by proper selection of the discrete frequencies in the input state. Each entanglement in the photon states was maximal, hence suited for Quantum Information Processing (QIP) applications.
Seismic Response of Rocking Bridge Bents with Parameterized Flag-Shaped Hysteretic Behavior

ABSTRACT: The present work investigates the seismic performance of a rocking bridge bent, which is either freestanding or hybrid (supplemented with energy dissipation and recentering devices), exhibiting flag-shaped hysteretic behaviour. Such hybrid systems have been proposed by several researchers as high-performance systems that can survive major earthquakes without substantial damage. This study considers three different structural rocking systems with either negative, zero, or positive lateral stiffness and compares their seismic performance with the pertinent freestanding structure. Both pulse-type and nonpulse-type ground motions are considered. The analysis demonstrates performance enhancement as the stiffness of the system increases and as the size of the columns decreases. However, this improvement is marginal among the examined stiffness systems. Further, it is shown that depending on the characteristics of the examined earthquake record, a different rocking design solution (e.g. freestanding, hybrid with negative/zero/positive stiffness) might exhibit better seismic behaviour.
A computational study of vertical tunneling transistors based on graphene-WS2 heterostructure

In this paper, for the first time, we present a computational study on electrical characteristics of field effect tunneling transistors based on a vertical graphene-WS2 heterostructure and vertical graphene nanoribbon (GNR)-WS2 heterostructure (VTGNRFET). Our model uses the nonequilibrium Green's function formalism along with an atomistic tight binding (TB) method. The TB parameters are extracted by fitting the bandstructure to first principles results. We show that, due to the advantage of switching between tunneling and thermionic transport regimes, an improvement can be achieved in the electrical characteristics of the device. We find that the increase of the number of WS2 layers enhances the on/off conductance ratio but degrades the intrinsic gate-delay time. The results indicate that the on/off conductance ratio of VTGNRFET increases with decreasing the GNR width.
Automatic bone outer contour extraction from B-modes ultrasound images based on local phase symmetry and quadratic polynomial fitting

Analyzing ultrasound (US) images to get the shapes and structures of particular anatomical regions is an interesting field of study since US imaging is a non-invasive method to capture internal structures of a human body. However, bone segmentation of US images is still challenging because it is strongly influenced by speckle noises and it has poor image quality. This paper proposes a combination of local phase symmetry and quadratic polynomial fitting methods to extract bone outer contour (BOC) from two dimensional (2D) B-modes US image as initial steps of three-dimensional (3D) bone surface reconstruction. By using local phase symmetry, the bone is initially extracted from US images. BOC is then extracted by scanning one pixel on the bone boundary in each column of the US images using first phase features searching method. Quadratic polynomial fitting is utilized to refine and estimate the pixel location that fails to be detected during the extraction process. Hole filling method is then applied by utilize the polynomial coefficients to fill the gaps with new pixel. The proposed method is able to estimate the new pixel position and ensures smoothness and continuity of the contour path. Evaluations are done using cow and goat bones by comparing the resulted BOCs with the contours produced by manual segmentation and contours produced by canny edge detection. The evaluation shows that our proposed methods produces an excellent result with average MSE before and after hole filling at the value of 0.65.
Photometric Identification of Cool White Dwarfs Photometric Identification of Cool White Dwarfs

We investigate the use of a narrowband DDO51 ﬁlter for photometric identiﬁcation of cool white dwarfs. We report photometric observations of 30 known cool white dwarfs with temperatures ranging from 10,000 K down to very cool temperatures ( (cid:1) 3500 K). Follow-up spectroscopic observations of a sample of objects selected using this ﬁlter and our photometric observations show that DDO51 ﬁlter photometry can help select cool white dwarf candidates for follow-up multiobject spectroscopy by rejecting 65% of main-sequence stars with the same broadband colors as the cool white dwarfs. This technique is not selective enough to efﬁciently feed single-object spectrographs. We present the white dwarf cooling sequence using this ﬁlter. Our observations show that very cool white dwarfs form a sequence in the r (cid:2) DDO versus r (cid:2) z color-color diagram and demonstrate that signiﬁcant improvements are needed in white dwarf model atmospheres.
Meta analysis of clinical trials of transcranial magnetic stimulation for chronic pelvic pain syndrome

In recent years, repeated transcranial magnetic stimulation has been used in clinical trials for the treatment of chronic pelvic pain syndrome, but its efficacy needs to be further verified. We aimed to summarize and discuss randomized controlled studies to provide clinical reference evidence for the future use of repeated transcranial magnetic stimulation in the treatment of chronic pelvic pain syndrome.
Printed in Sri Lanka EFFECT OF N, K, CI ON PHOTOSYNTHESIS AND WATER RELATIONS OF OPEN POLLINATED TALL (typica)

C 0 2 assimilation and plant water status were measured in sand-culture-grown amputated coconut seedlings treated with three levels ofN, K, and CI and subjected to different soil water deficit conditions. Application of increased levels ofN and K enhanced the assimilation of C 0 2 while individual and combined effects of N,K, and CI improved the water economy of coconut seedlings. Under the soil water deficit conditions, adequate supply ofN helped to maintain high leaf water potential by the accumulation of solutes like proline and sugars. Whereas, adequate supply of K and CI themselves acted as osmotica by increased accumulation of these nutrients in leaf tissues, although other solute concentrations such as those of sugars and proline were reduced. Our data show that maintenance of sufficient levels of N and K contribute to the growth of the coconut seedling through improved gaseous exchange, C 0 2 assimilation and better partitioning of assimilated carbon into shoot and roots, potassium and C1 are further important for maintenance of water status of coconut seedlings by improved stomatal regulation, water uptake and osmotic adjustment of tissues under water deficit conditions.
3 D reconstruction from Compton camera images

Thyroid cancer is a prevalent disease, and nuclear imaging methods play a vital role in its diagnosis and treatment. However, the current imaging modalities, such as SPECT and PET, have limitations in terms of size, cost, sensitivity and tracer flexibility, hindering their widespread usage and impeding progress in clinical understanding of the treatment. In this context, the Compton camera, with its smaller size, reduced cost, higher sensitivity and capability to handle multiple tracers emerges as a potential alternative for diagnosing various cancer types. This thesis addresses the development of a 3D image reconstruction method for radiopharmaceutical distribution from Compton data. The proposed solution aims to meet the practicality criteria of medical radionuclide examination. A Monte Carlo simulator is developed to generate synthetic data, and a baseline reconstruction method is established. Through computational optimization and regularization techniques, the reconstruction method is refined. Evaluation is conducted on both synthetic and real data. The proposed method exhibits comparable qualitative performance to state-ofthe-art methods, while being versatile and time-sensitive. The experimental evaluation demonstrates its practical usefulness and potential for incorporation into a clinical solution.
Online Forecasting of Synchronous Time Series Based on Evolving Linear Models

This paper suggests evolving linear models as a powerful alternative for online forecasting of synchronous time series. First, using a priori knowledge of an expert, all known possible features are clustered in some categories so that each category includes homogeneous features. Then, a novel evolving correlation-based forward subset selection technique is used to determine relevant features from each category. Next, based on the selected features, an estimation of the output of the system is modeled through an evolving adaptive linear regression model. In evolving systems, selected features and their associated weights could vary over time based on new incoming data samples which contain new information. Finally, a soft combination of output estimations of all categories, in a new sense of Takagi–Sugeno fuzzy system, gives the prediction of the output of the system at each sampling time. The approach offers a certain new view at the enhancement of evolving forecasting models. The proposed approach embodies recursive learning and one-step-ahead incremental algorithms that progressively modify the model to ensure continuous learning, and self-organization of the model structure and its parameters. Two real-world problems, forecasting electricity load of the Electric Reliability Council of Texas region and stock price forecasting of technology sector of Standard & Poor’s 500 index, are provided to validate the developed method. Pros and cons of the proposed approach are comprehensively discussed and shown through simulation results and comparisons with other state-of-the-art techniques.
On the Complexity of SOS Programming and Applications in Control Systems

The minimization of a linear cost function subject to the condition that some matrix polynomials depending linearly on the decision variables are sums of squares of matrix polynomials (SOS) is known as SOS programming. This paper proposes an analysis of the complexity of SOS programming, in particular of the number of linear matrix inequality (LMI) scalar variables required for establishing whether a matrix polynomial is SOS. This number is analyzed for real and complex matrix polynomials, in the general case and in the case of some exact reductions achievable for some classes of matrix polynomials. An analytical formula is proposed in each case in order to provide this number as a function of the number of variables, degree and size of the matrix polynomials. Some tables reporting this number are also provided as reference for the reader. Two applications in control systems are presented in order to show the usefulness of the proposed results.
Asymmetry flip in angle-resolved photoelectron spectra of rare gas atoms by intense circularly polarized few-cycle pulses

We examine the phenomenon of the flip in the asymmetry in the emission direction of photoelectrons from rare gas atoms upon the ionization by a circularly polarized few-cycle laser field, and derive an analytical formula representing the photoelectron kinetic energy at which the asymmetry flip occurs based on the semiclassical tunnel ionization theory. We show that the energy at which the asymmetry flip occurs varies sensitively to the duration of few-cycle laser pulses and propose that the pulse duration can be determined experimentally using this analytical formula for the asymmetry flip energy.
Hemostatic and Rheological Variables and Risk of Cardiovascular Disease

Increasing blood levels of hemostatic variables may increase the risk of thrombosis, while increasing levels of rheological variables which reduce blood flow may increase the risk of ischemic events. Systematic reviews of prospective cohort studies of hemostatic and rheological variables suggest that increasing blood levels of fibrinogen, von Wille-brand factor, tissue plasminogen activator antigen, fibrin D-dimer, hematocrit, viscosity
Iterative temporal differencing with fixed random feedback alignment support spike-time dependent plasticity in vanilla backpropagation for deep learning

In vanilla backpropagation (VBP), activation function matters considerably in terms of non-linearity and differentiability. Vanishing gradient has been an important problem related to the bad choice of activation function in deep learning (DL). This work shows that a differentiable activation function is not necessary any more for error backpropagation. The derivative of the activation function can be replaced by an iterative temporal differencing (ITD) using fixed random feedback weight alignment (FBA). Using FBA with ITD, we can transform the VBP into a more biologically plausible approach for learning deep neural network architectures. We don't claim that ITD works completely the same as the spike-time dependent plasticity (STDP) in our brain but this work can be a step toward the integration of STDP-based error backpropagation in deep learning.
Global climate impacts of stochastic deep convection parameterization in the NCAR CAM5

In this study, the stochastic deep convection parameterization of Plant and Craig (PC) is implemented in the Community Atmospheric Model version 5 (CAM5) to incorporate the stochastic processes of convection into the Zhang‐McFarlane (ZM) deterministic deep convective scheme. Its impacts on deep convection, shallow convection, large‐scale precipitation and associated dynamic and thermodynamic fields are investigated. Results show that with the introduction of the PC stochastic parameterization, deep convection is decreased while shallow convection is enhanced. The decrease in deep convection is mainly caused by the stochastic process and the spatial averaging of input quantities for the PC scheme. More detrained liquid water associated with more shallow convection leads to significant increase in liquid water and ice water paths, which increases large‐scale precipitation in tropical regions. Specific humidity, relative humidity, zonal wind in the tropics, and precipitable water are all improved. The simulation of shortwave cloud forcing (SWCF) is also improved. The PC stochastic parameterization decreases the global mean SWCF from −52.25 W/m2 in the standard CAM5 to −48.86 W/m2, close to −47.16 W/m2 in observations. The improvement in SWCF over the tropics is due to decreased low cloud fraction simulated by the stochastic scheme. Sensitivity tests of tuning parameters are also performed to investigate the sensitivity of simulated climatology to uncertain parameters in the stochastic deep convection scheme.
Teaching Strategies of Chinese Language History Class Based on Brain Science

Brain science and education are both new emerging research fields which received much international attention. At present, there have set up research organizations and institutions of bigger children, in their studies there are several characteristics as follows: choosing different research entry points, exploring the research mode connecting brain science and education, paying attention to application research questions, and adopting advanced research tools and techniques. In this study, we attempt to analyze and sort out the advanced teaching research materials from abroad, start from the perspective of brain science, and probe into scientific and effective classroom teaching strategies. According to the physiological characteristics of the brain and the latest relevant research, this study explores and presents teaching strategies that are suitable for the Chinese language history classes.
Hierarchical Clustering With Multi-View Point Based Similarity Measure

Clustering is a technique for finding similarity groups in data, called clusters. It groups data instances that are similar to each other in one cluster and data instances that are very different from each other into different clusters. Clustering is often called an unsupervised learning. In this paper Hierarchical clustering is used to find the cluster relationship between data objects in the data set. We introduce a novel multi-viewpoint based similarity measure and two related clustering methods. The main difference of our novel method from the existing one is that it uses only single view point for which it is the base and where as the mentioned clustering with Multi-Viewpoint Based Similarity Measure uses many different viewpoints of objects and are assumed to not be in the same cluster with two objects being measured. Based on this novel method two criterion functions are proposed for document clustering. We compared this clustering algorithm with other measures in order to verify the improvement of novel method.
Accurate Determination of the Landé G-Factors for 5s2 1 S0 and 5s5p 3P0 States of the 87Sr Atom

In the ultra-cold <sup>87</sup>Sr atomic system, the Zeeman shift of the clock transition was measured with the σ<sup>±</sup>-polarized interrogation to accurately determine the g-factors of the 5s<sup>2</sup><sup>1</sup>S<inf>0</inf> and 5s5p <sup>3</sup>P<inf>0</inf> states.
The Emerging Role of Lipoproteins in Atherogenesis: Beyond LDL Cholesterol

Low-density lipoprotein cholesterol has a well-established role in atherogenesis and the development of coronary heart disease. However, despite effective lowering of low-density lipoprotein cholesterol, many patients continue to have cardiovascular events. It has subsequently emerged that several additional dyslipidemic states promote atherogenesis. In particular, the atherogenic lipoprotein phenotype comprising an elevation of triglycerides and triglyceride-rich lipoproteins; decreased concentrations of high-density lipoprotein cholesterol; and increased small, dense low-density lipoprotein cholesterol, in addition to impaired postprandial lipemia, have been demonstrated to have profound effects on the arterial wall. As such, these factors have become important targets in the development of effective strategies to prevent atherosclerotic cardiovascular disease.