Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of the lower hybrid drift instability at reconnection jet front

We investigate current‐driven modes developing at jet fronts during collisionless reconnection. Initial evolution of the reconnection is simulated using conventional 2‐D setup starting from the Harris equilibrium. Three‐dimensional PIC calculations are implemented at later stages, when fronts are fully formed. Intense currents and enhanced wave activity are generated at the fronts because of the interaction of the fast flow plasma and denser ambient current sheet plasma. The study reveals that the lower hybrid drift instability develops quickly in the 3‐D simulation. The instability produces strong localized perpendicular electric fields, which are several times larger than the convective electric field at the front, in agreement with Time History of Events and Macroscale Interactions during Substorms observations. The instability generates waves, which escape the front edge and propagate into the undisturbed plasma ahead of the front. The parallel electron pressure is substantially larger in the 3‐D simulation compared to that of the 2‐D. In a time ∼Ωci−1 , the instability forms a layer, which contains a mixture of the jet plasma and current sheet plasma. The results confirm that the lower hybrid drift instability is important for the front evolution and electron energization.
Framework for Knee Joint Movement Analysis with Inertial Sensors and Recursive Filters

Health and sports monitoring based on wireless low power and low range communication devices have been proposed by a number of commercial and scientific solutions. Low cost and small form devices allow data transfer and processing without cumbersome cabling. Inertial Measurement Units (IMU), that include an accelerometer, a gyroscope and sometimes may include one magnetometer, are used to determine body movement profile. Despite their inherent inaccuracy, these sensors are used for computing three-dimensional space object orientation. These computations are usually implemented with sensor fusion algorithms within devices that have enhanced computational capabilities.This paper presents a work that aims at estimating the limb and body trunk movements of a pedaling user/patient in a bicycle like device. The presented study has been undertaken within the Exobike project. The Exobike is a bicycle like exoskeleton where the lower limbs and the trunk of a user/patient are to be monitored using IMU data transferred through a radio frequency Bluetooth Low Energy protocol. This paper focuses on the use of IMU sensors and a type of recursive filters to estimate movement profile.
Development of G-Band Continuous-Wave Folded Waveguide Traveling-Wave Tube

A detailed development of a <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula>-band continuous-wave (CW) traveling-wave tube (TWT) with a 160-GHz<inline-formula> <tex-math notation="LaTeX">$\cdot \text{W}$ </tex-math></inline-formula> product of bandwidth power is reported in the present work, in which the electron optics system (EOS), the tapered phase velocity folded waveguide (TPVFW) slow wave structure (SWS), the modified pill-box window (MPBW), and experimental results are described. The prototype of the proposed TWT is fabricated with optimized structural parameters obtained by particle-in-cell (PIC) simulations. Moreover, the experimental results show that TWT with 27-W output power at the frequency of 220 GHz at 100% duty cycle is obtained at the operation voltage of 17.1 kV and the current of 62 mA. The proposed <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula>-band TWT will have broad applications in far-distance high-resolution imaging and large communications capacity.
Site-specific glycation of Aβ1–42 affects fibril formation and is neurotoxic

Aβ1–42 is involved in Alzheimer's disease (AD) pathogenesis and is prone to glycation, an irreversible process where proteins accumulate advanced glycated end products (AGEs). Nϵ-(Carboxyethyl)lysine (CEL) is a common AGE associated with AD patients and occurs at either Lys-16 or Lys-28 of Aβ1–42. Methyglyoxal is commonly used for the unspecific glycation of Aβ1–42, which results in a complex mixture of AGE-modified peptides and makes interpretation of a causative AGE at a specific amino acid residue difficult. We address this issue by chemically synthesizing defined CEL modifications on Aβ1–42 at Lys-16 (Aβ-CEL16), Lys-28 (Aβ-CEL28), and Lys-16 and -28 (Aβ-CEL16&28). We demonstrated that double-CEL glycations at Lys-16 and Lys-28 of Aβ1–42 had the most profound impact on the ability to form amyloid fibrils. In silico predictions indicated that Aβ-CEL16&28 had a substantial decrease in free energy change, which contributes to fibril destabilization, and a increased aggregation rate. Single-CEL glycations at Lys-28 of Aβ1–42 had the least impact on fibril formation, whereas CEL glycations at Lys-16 of Aβ1–42 delayed fibril formation. We also tested these peptides for neuronal toxicity and mitochondrial function on a retinoic acid-differentiated SH-SY5Y human neuroblastoma cell line (RA-differentiated SH-SY5Y). Only Aβ-CEL16 and Aβ-CEL28 were neurotoxic, possibly through a nonmitochondrial pathway, whereas Aβ-CEL16&28 showed no neurotoxicity. Interestingly, Aβ-CEL16&28 had depolarized the mitochondrial membrane potential, whereas Aβ-CEL16 had increased mitochondrial respiration at complex II. These results may indicate mitophagy or an alternate route of metabolism, respectively. Therefore, our results provides insight into potential therapeutic approaches against neurotoxic CEL-glycated Aβ1–42.
Factors That Influence Children’s Exits from the Special Supplemental Nutrition Program for Women, Infants, and Children: A Systematic Review

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides supplemental foods and nutritional education to low-income women and children up to the age of five. Despite evidence that WIC improves diet and nutrition and the nationwide availability of this program, many participants exit WIC before they are no longer eligible for benefits. To date no study has systematically reviewed factors that influence participants’ exits from WIC. The study systematically reviewed the relevant literature to identify factors related to discontinuing participation in WIC before children reach the age of five and 1503 citations were reviewed, 19 articles were read for full text review and eight studies met inclusion criteria. Participants’ higher socioeconomic status, attitudes and behaviors around breastfeeding, having shorter prenatal participation in WIC, administrative barriers, confusion regarding program eligibility, feelings of stigma and embarrassment at the store checkout lines, personal and family challenges, dissatisfaction with insufficient fruit and vegetables benefits and living in suburban areas or in the Southern US were salient factors that influenced WIC exits. These findings will be of interest to policymakers and stakeholders as they consider ways to increase participation and retention through program modernization and innovations.
Treatment of Breast Cancer-Related Lymphedema With Topical Tacrolimus: A Prospective, Open-Label, Single-Arm, Phase II Pilot Trial

Purpose Breast cancer-related lymphedema (BCRL) is a chronic, progressive side effect of breast cancer treatment, occurring in one-third of patients treated with axillary lymph node dissection and nodal radiotherapy. Cluster of differentiation 4-positive (CD4+) cells plays a key role in BCRL by facilitating inflammation and inhibiting lymphangiogenesis. Tacrolimus is an anti-inflammatory and immunosuppressive macrolide that targets CD4+ cells. Treatment of lymphedema with topical tacrolimus has revealed promising results in preclinical trials. This clinical trial was aimed at evaluating the feasibility, safety, and effect of tacrolimus in women with stage I or II BCRL, according to the International Society of Lymphology. Methods We conducted this open-label, single-arm, phase II pilot trial from September 2020 to April 2021. Eighteen women with BCRL stage I or II BCRL were treated with topical tacrolimus for 6 months and followed up at 3 and 6 months. The primary outcome was arm volume, and secondary outcomes were the lymphedema index (L-Dex), health-related quality of life (HRQoL), lymph flow and function, and safety and feasibility of the trial design. Results The mean lymphedema arm volume and L-Dex reduced significantly by 130.44 ± 210.13 mL (p < 0.05; relative reduction: 3.6%) and 3.54 ± 4.98 (p < 0.05), respectively, and health-related quality of life scores was improved significantly (p < 0.05). According to the MD Anderson scale, in terms of lymph flow and function, three patients (16.7%) showed improvement, while none showed worsening. Lymph flow or function showed no change according to the Arm Dermal Backflow scale. Conclusion In this trial, treatment with tacrolimus was safe and feasible in women with stage I or II BCRL. Tacrolimus alleviated BCRL in terms of improved arm volume, L-Dex, and HRQoL. Assessments of lymph flow and function were positive, although inconclusive. Larger randomized controlled trials are required to verify these findings. Trial Registration ClinicalTrials.gov Identifier: NCT04541290
Using Learning Analytics to Explore the Role of Self-regulation in students’ Achievements in Synchronous Online Learning

Learning analytics aims to understand and optimize learning process by collecting and analyzing traced learner’s data. To utilize its potential, it should involve educational theoretical frameworks to identify the indicators in the traced data as well as to interpret the results. In this paper, we use learning analytics to explore the role of students’ self-regulation in their achievements in synchronous online learning. The study identifies three indicators in students’ traced data to capture self-regulation: session attendance time, students’ submissions of self-assessments, and study regularity by assessing their correlations with the self-regulation scales measured by self-reported instruments. The results show that these indicators are positively correlated with the students’ achievements, so they can be used to predict students’ performance in synchronous online learning, and identify students at risk.
Empirical likelihood-based inference under imputation for missing response data

Inference under kernel regression imputation for missing response data is considered. An adjusted empirical likelihood approach to inference for the mean of the response variable is developed. A nonparametric version of Wilks' theorem is proved for the adjusted empirical log-likelihood ratio by showing that it has an asymptotic standard chi-squared distribution, and the corresponding empirical likelihood confidence interval for the mean is constructed. With auxiliary information, an empirical likelihood-based estimator is defined and an adjusted empirical log-likelihood ratio is derived. Asymptotic normality of the estimator is proved. Also, it is shown that the adjusted empirical log-likelihood ratio obeys Wilks' theorem. A simulation study is conducted to compare the adjusted empirical likelihood and the normal approximation methods in terms of coverage accuracies and average lengths of confidence intervals. Based on biases and standard errors, a comparision is also made by simulation between the empirical likelihood-based estimator and related estimators. Our simulation indicates that the adjusted empirical likelihood method performs competitively and that the use of auxiliary information provides improved inferences.
Monte Carlo simulation of three-dimensional islands

The usual kinetic Monte Carlo method is adapted, to treat off-lattice problems of multilayer growth (coverage $\ensuremath{\theta}g1)$ by molecular-beam epitaxy. This method takes into account the Schwoebel barrier, which comes out as a result of the choice of the potential interaction between the atoms. This method allows a free choice of the lattice mismatch, temperature, deposition flux rate, and interfacial energies. A particular choice of these parameters leads to the three-dimensional (3D) (Volmer-Weber) growth mode, whereas another choice of these parameters leads to the 2D-3D growth mode (Stranski-Krastanov). The 3D islands seem to obey scaling only approximately. Using this method, the surface stress inside a substrate and a (pyramidal) coherent 3D island is computed. Strong relaxations appear, not only at the edges of the 3D island (which is expected), but also in the proximity of the edges, and inside the 3D island. These particular sites inside the 3D island are located just beneath a step site of the upper layer. Moreover, these particular sites develop strong corrugations, which later are propagating along the layer. Strain-induced modulation of layers is thermally activated, so the steps could act as defects and nucleation sites for propagating roughness, in agreement with some theories and experimental facts.
Data-driven adaptive model-based predictive control with application in wastewater systems

This study is concerned with the development of a new data-driven adaptive model-based predictive controller (MBPC) with input constraints. The proposed methods employ subspace identification technique and a singular value decomposition (SVD)-based optimisation strategy to formulate the control algorithm and incorporate the input constraints. Both direct adaptive model-based predictive controller (DAMBPC) and indirect adaptive model-based predictive controller (IAMBPC) are considered. In DAMBPC, the direct identification of controller parameters is desired to reduce the design effort and computational load while the IAMBPC involves a two-stage process of model identification and controller design. The former method only requires a single QR decomposition for obtaining the controller parameters and uses a receding horizon approach to process input/output data for the identification. A suboptimal SVD-based optimisation technique is proposed to incorporate the input constraints. The proposed techniques are implemented and tested on a fourth order non-linear model of a wastewater system. Simulation results are presented to compare the direct and indirect adaptive methods and to demonstrate the performance of the proposed algorithms.
Design and development of a digital shared decision-making tool for stroke prevention in atrial fibrillation

Abstract Background Shared decision-making (SDM) is an approach in which patients and clinicians act as partners in making medical decisions. Patients receive the information needed to decide and are encouraged to balance risks, benefits, and preferences. Informative materials are vital to SDM. Atrial fibrillation (AF) is the most common cardiac arrhythmia and responsible for 10% of ischemic strokes, however 1/3 of patients are not on appropriate anticoagulation. Decision sharing may facilitate treatment acceptance, improving outcomes. Aims To develop a framework of the components needed to create novel SDM tools and to provide practical examples through a case-study of stroke prevention in AF. Methods We analyze the design values of a web-based SDM tool created to better inform AF patients about anticoagulation. The tool was developed in partnership with patient advocates, multi-disciplinary investigators, and private design firms. It was refined through iterative, recursive testing in patients with AF. Its effectiveness is being evaluated in a multisite clinical trial led by Stanford University and sponsored by the American Heart Association. Findings The main components considered when creating the Stanford AFib tool included: design and software; content identification; information delivery; inclusive communication, user engagement; patient feedback; clinician experience; and anticipation of implementation and dissemination. We also highlight the ethical principles underlying SDM; matters of diversity and inclusion, linguistic variety, accessibility, and health literacy. The Stanford AFib Guide patient tool is available at: https://afibguide.com and the clinician tool at https://afibguide.com/clinician. Conclusion Attention to a range of vital development and design factors can facilitate tool adoption and information acquisition by diverse cultural, educational, and socioeconomic subpopulations. With thoughtful design, digital tools may decrease decision regret and improve treatment outcomes across many decision-making situations in healthcare.
Comments on the hysteresis loop in ferroelastic LiCsSO4

Abstract Recent experiments on LiCsSO4 revealed a single stress-strain hysteresis loop for samples cut along the x-direction, and a double hysteresis loop for samples cut along the y-direction. In this paper we propose a Landau-based free-energy expansion which gives a qualitative explanation of the phenomenon. We also discuss the reasons why the observed curve is smooth and not rectangular as the simple theoretical model would imply.
Magnetohydrodynamic stability of flux-conserving tokamak equilibria

Large-scale magnetohydrodynamic instabilities of flux-conserving tokamak equilibria are studied computationally. Stable equilibria are found with up to 5% average . beta. As . beta. is increased, the observed instabilities take on a strong ballooning character, concentrating near the outer edge of the torus with a mix of poloidal harmonics.
Using an LSTM network to monitor industrial reactors using electrical 
capacitance and impedance tomography – a hybrid approach

The article presents a new concept for monitoring industrial tank reactors. The presented concept allows for faster and more reliable monitoring of industrial processes, which increases their reliability and reduces operating costs. The innovative method is based on electrical tomography. At the same time, it is non-invasive and enables the imaging of phase changes inside tanks filled with liquid. In particular, the hybrid tomograph can detect gas bubbles and crystals formed during industrial processes. The main novelty of the described solution is the simultaneous use of two types of electrical tomography: impedance and capacitance. Another novelty is the use of the LSTM network to solve the tomographic inverse problem. It was made possible by taking the measurement vector as a data sequence. Research has shown that the proposed hybrid solution and the LSTM algorithm work better than separate systems based on impedance or capacitance tomography.
TCAD-Enabled Machine Learning—An Efficient Framework to Build Highly Accurate and Reliable Models for Semiconductor Technology Development and Fabrication

The requirements on data-driven Machine Learning models for industrial applications are often stricter, compared to those used for academic purposes, as model reliability is critical in industrial environments. Herein is introduced a framework which enables automated data generation with the goal of efficiently providing a data set sufficient to build a reliable and actionable model. Essential to this framework is the placement of the model training/testing data points, which need to be well distributed across the defined input parameter space. The framework is applied to semiconductor fabrication, wherein TCAD, a set of simulation tools that reproduce the physical processing and the final electrical performance of semiconductor devices, is a well-established capability. Transistor-level processing data is reproduced with TCAD simulations, from which the Machine Learning model is built. The framework described here assures that the resulting Machine Learning model fulfills the accuracy requirements across the parameter space. As an example application, the final Machine Learning model is then used to modify the process for a transistor, to obtain both better electrical performance and reduced variability.
Bacon With Your Eggs? Applications of a New Bivariate Beta-Binomial Distribution

We present two everyday applications of a new bivariate beta-binomial distribution. Although the applications are familiar, they share unique characteristics that cannot be handled adequately by existing bivariate discrete distributions. These features are high levels of between- and within-trial correlation for the bivariate random variables. Our model is derived from a broad class of bivariate models based on a versatile, but little-known, family of distributions due to Sarmanov. For the applications presented, we show that our model fits observed data very well. In addition, for the bacon and eggs application, the model can be used to help improve the management of inventory in grocery stores.
Study on new magnetorheological chemical polishing process for GaN crystals: polishing solution composition, process parameters, and roughness prediction model

High-quality and high-efficiency processing of gallium nitride (GaN) crystals is urgently required for optoelectronic communications and other major industries. This study proposes a novel high-efficiency non-damage magnetorheological chemical polishing (MCP) process to overcome the existing problems of low efficiency and lattice distortion during processing. The effects of the MCP fluid composition and key processing parameters on the surface roughness and material removal rate (MRR) of GaN crystals were studied experimentally. The results showed that a compounded abrasive containing silica fluid exhibited better polishing effects than a single abrasive. The polishing efficiency could be improved by adding NaOH solid particles, and the MRR reached 13.19 nm min−1 when the pH of the MCP fluid was 10. The MRR increased gradually with an increase in the pole rotation speed and worktable speed and a decrease in the polishing gap. The surface roughness of the GaN crystals was improved from Ra 115 nm to Ra 0.375 nm after polishing for 4 h. The surface and sub-surface damage of the polished GaN crystals was analyzed using scanning electron microscope and transmission electron microscope. The results confirmed that the MCP process can realize the non-damage polishing of GaN crystals. Moreover, a prediction model for the surface roughness of GaN crystals in the MCP process was constructed. The overall difference between the actual and predicted surface roughness values for the model was 11.6%.
Classical and intermediate monocytes scavenge non-transferrin-bound iron and damaged erythrocytes

Myelomonocytic cells are critically involved in iron turnover as aged RBC recyclers. Human monocytes are divided in 3 subpopulations of classical, intermediate, and nonclassical cells, differing in inflammatory and migratory phenotype. Their functions in iron homeostasis are, however, unclear. Here, we asked whether the functional diversity of monocyte subsets translates into differences in handling physiological and pathological iron species. By microarray data analysis and flow cytometry we identified a set of iron-related genes and proteins upregulated in classical and, in part, intermediate monocytes. These included the iron exporter ferroportin (FPN1), ferritin, transferrin receptor, putative transporters of non-transferrin-bound iron (NTBI), and receptors for damaged erythrocytes. Consequently, classical monocytes displayed superior scavenging capabilities of potentially toxic NTBI, which were augmented by blocking iron export via hepcidin. The same subset and, to a lesser extent, the intermediate population, efficiently cleared damaged erythrocytes in vitro and mediated erythrophagocytosis in vivo in healthy volunteers and patients having received blood transfusions. To summarize, our data underline the physiologically important function of the classical and intermediate subset in clearing NTBI and damaged RBCs. As such, these cells may play a nonnegligible role in iron homeostasis and limit iron toxicity in iron overload conditions.