Miracle-dz/UniFAR-FTUs huggingface dataset:
Scale-reconfigurable miniature ferrofluidic robots for negotiating sharply variable spaces

Magnetic miniature soft robots have shown great potential for facilitating biomedical applications by minimizing invasiveness and possible physical damage. However, researchers have mainly focused on fixed-size robots, with their active locomotion accessible only when the cross-sectional dimension of these confined spaces is comparable to that of the robot. Here, we realize the scale-reconfigurable miniature ferrofluidic robots (SMFRs) based on ferrofluid droplets and propose a series of control strategies for reconfiguring SMFR’s scale and deformation to achieve trans-scale motion control by designing a multiscale magnetic miniature robot actuation (M3RA) system. The results showed that SMFRs, varying from centimeters to a few micrometers, leveraged diverse capabilities, such as locomotion in structured environments, deformation to squeeze through gaps, and even reversible scale reconfiguration for navigating sharply variable spaces. A miniature robot system with these capabilities combined is promising to be applied in future wireless medical robots inside confined regions of the human body.
STRONG CONSISTENCY RESULTS FOR LEAST SQUARES ESTIMATORS IN GENERAL VECTOR AUTOREGRESSIONS WITH DETERMINISTIC TERMS

A vector autoregression with deterministic terms and with no restrictions to its characteristic roots is considered. Strong consistency results for the least squares statistics are presented. This extends earlier results where deterministic terms have not been considered. In addition the convergence rates are improved compared with earlier results.Comments from S. Johansen are gratefully acknowledged.
RSC and GRFs confer promoter directionality by restricting divergent noncoding transcription

We show that the chromatin remodelling complex RSC and general regulatory factors (GRFs) limit transcription in the noncoding divergent direction, thereby increasing the directionality of promoters. The directionality of gene promoters—the ratio of protein-coding over divergent noncoding transcription—is highly variable. How promoter directionality is controlled remains poorly understood. Here, we show that the chromatin remodelling complex RSC and general regulatory factors (GRFs) dictate promoter directionality by attenuating divergent transcription relative to protein-coding transcription. At gene promoters that are highly directional, depletion of RSC leads to a relative increase in divergent noncoding transcription and thus to a decrease in promoter directionality. We find that RSC has a modest effect on nucleosome positioning upstream in promoters at the sites of divergent transcription. These promoters are also enriched for the binding of GRFs such as Reb1 and Abf1. Ectopic targeting of divergent transcription initiation sites with GRFs or the dCas9 DNA-binding protein suppresses divergent transcription. Our data suggest that RSC and GRFs play a pervasive role in limiting divergent transcription relative to coding direction transcription. We propose that any DNA-binding factor, when stably associated with cryptic transcription start sites, forms a barrier which represses divergent transcription, thereby promoting promoter directionality.
3 1 M ay 2 00 5 Bistable light detectors with nonlinear waveguide arrays

Bistability induced by nonlinear Kerr effect in arrays of coupled waveguides is studied and shown to be a means to conceive light detectors that switch under excitation by a weak signal. The detector is obtained by coupling two single 1D waveguide to an array of coupled waveguides with adjusted indices and coupling. The process is understood by analytical description in the conservative and continuous case and illustrated by numerical simulations of the model with attenuation.
Rapidly-Rotating Turbulence: An Experimental Perspective

© Cambridge University Press 2013. The evidence of the early experiments. We consider rapidly-rotating turbulence; that is, turbulence in which the fluctuating velocity in the rotating frame, u, is smaller than, or of the order of, ⌳Ω⌳ l, where Ω = Ωez is the bulk rotation vector and l a suitably defined integral scale. The Navier-Stokes equation in the rotating frame is. where p is the so-called reduced pressure, which incorporates the irrotational centrifugal force. It is conventional to introduce the Rossby number, Ro = u/Ωl, to measure the relative importance of the inertial and Coriolis forces, and so our primary interest is turbulence in which Ro = O(1), or smaller. It is well known that such turbulence is characterised by the presence of long, columnar eddies aligned with the rotation axis, and there has been much discussion as to the mechanism by which these columnar structures form. The various theories differ in detail, but all agree that inertial waves play an important role. (We shall review the properties of inertial waves in §8.2.). Several, now classic, experiments set the scene in the 1970s and 80s. Ibbetson & Tritton (1975) looked at freely-decaying turbulence in a rotating annulus in which Ro = O(1). Like all subsequent researchers, they observed that rotation causes the eddies to grow rapidly along the rotation axis, forming columnar structures. They also noted that inertial waves are important for transporting energy across the flow.
A small-distributed aerodynamic brake prototype and its effects on the vertical dynamics of high-speed electromagnetic suspension maglevs

Aerodynamic braking is a clean and environmentally friendly braking mode, and it does not use mechanical friction as its braking force. In this study, we discuss the development of a small-distributed aerodynamic brake prototype and its structure, working principle, ground test and test results. A computational fluid dynamics (CFD) method is developed to record the aerodynamic forces of the prototype, and the simulation results are validated with the wind tunnel test. On the basis of the CFD simulation, the panel opening and braking processes are modelled to analyse the vertical dynamic characteristics of a high-speed electromagnetic suspension maglev with aerodynamic brakes. In addition, a vehicle, guideway and levitation controller are modelled. Finally, a three-car system dynamic model is used to study the effects of the opening time, initial braking position and feedback gains. The aerodynamic forces of the first car show the most significant changes when the braking panels are opened. The increase in the longitudinal force is 15 461.16 N, and the vertical force varies from a lift force of 35 342.98 N to a downforce of 40 721.35 N. The maximum guideway deflection decreases as the opening time increases. The difference between the deflections recorded at the opening time of 0.064 s and 0.6 s is 1.2 mm. Furthermore, the vertical acceleration decreases as the opening time increases. The condition under which the vehicle brakes when the first car enters the object guideway has the maximum effect on the deflection of the guideway. To ensure levitation stability, influenced by the vertical change of the first car, a high feedback gain for the levitation clearance change is required. However, the levitation stability with aerodynamic brakes has low sensitivity to the feedback gains for the observed velocity and acceleration of the system.
Radiative corrections to $h^0\to WW^*/ZZ^*\to 4$\,leptons in the MSSM

The electroweak $\mc O(\alpha)$ radiative corrections to the decay of the lightest MSSM Higgs boson to four leptons are presented, improved by the two-loop corrections provided by the program package FeynHiggs. We also analyze the results in the decoupling limit and investigate the numeric impact of contributions from the genuine supersymmetric particle spectrum.
Improving Nursing Home Resident and Staff Experiences

The National Partnership to Improve Dementia Care in Nursing Homes (i.e., the National Partnership) was launched in March 2012. Using national Medicare, MinimumData Set, and Nursing HomeCompare data in CY 2010–2014, we examined changes in hospital readmissions for older post-acute skilled nursing facility (SNF) residents with Alzheimer’s disease or related dementias (ADRD) following the National Partnership. Using residents without ADRD as reference group to control for concurrent policy and SNF quality changes, we estimated linear probability models to examine the relationship between readmissions and the National Partnership for residents with ADRD, and also stratified the analysis by quality of SNFs. We found a decreasing trend in hospital readmissions over time. The risk of readmissions in residents with ADRD decreased additional 0.3 percentagepoints (p < .01) after the launch of the National Partnership. This relationship varied across SNFs with different quality, as it was stronger in high-quality compared to low-quality SNFs.
A Neural Network Approach to Create Minangkabau-Indonesia Bilingual Dictionary

Indonesia has many varieties of ethnic languages, and most come from the same language family, namely Austronesian languages. Coming from that same language family, the words in Indonesian ethnic languages are very similar. However, there is research stating that Indonesian ethnic languages are endangered. Thus, to prevent that, we proposed to create a bilingual dictionary between ethnic languages using a neural network approach to extract transformation rules using character level embedding and the Bi-LSTM method in a sequence-to-sequence model. The model has an encoder and decoder. The encoder functions read the input sequence, character by character, generate context, then extract a summary of the input. The decoder will produce an output sequence where every character in each time-step and the next character that comes out are affected by the previous character. The current case for experiment translation focuses on Minangkabau and Indonesian languages with 13761-word pairs. For evaluating the model’s performance, 5-Fold Cross-Validation is used.
Fe b 20 04 Zooming-in on the charge ordering in YBa 2 Cu

D. L. Feng, A. Rusydi, P. Abbamonte, L. Venema, I. Elfimov, R. Liang, D. A. Bonn, W. N. Hardy, C. Schüßler-Langeheine, S. Hulbert, C. -C. Kao and G. A. Sawatzky Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, V6T 1Z1, Canada. Materials Science Centre, University of Groningen, 9747 AG Groningen, The Netherlands. Department of Physics, Applied Surface Physics State Key Laboratory, and Synchrotron Radiation Research Center, Fudan University, Shanghai 200433, China National Synchrotron Light Source, Brookhaven National Laboratory, Upton, NY 11973, USA. and 5 II. Physikalisches Institut, Universität zu Köln, D-50937 Köln, Germany (Dated: March 22, 2022)
Demo: An Online Evidence-based Text Simplification Editor for Medical Text

It has become increasingly common for patients to turn to online resources to find medical and healthcare related information. This reflects recent advances in medicine as well as the large amount of educational resources available. Since many consumers use the Internet for reading medical information, providing this information optimized for non-specialists is essential. We are developing a medical text editor for use by medical professionals to support writing text optimized for comprehension and retention by average readers. We have developed several data-driven algorithms that identify difficult text and make suggested improvements. We evaluated these for their effect on text difficulty and on improving reader comprehension and have integrated those algorithms that were successful into an online prototype. To our knowledge, we are the first to provide an evidence-based text editor that combines algorithms shown to affect text difficulty and the resulting comprehension and retention.
Real-World Outcomes and Treatments Patterns Prior and after the Introduction of First-Line Immunotherapy for the Treatment of Metastatic Non-Small Cell Lung Cancer

Simple Summary The advent of immuno-oncology (IO) agents, particularly immune checkpoint inhibitors (ICIs), has changed the treatment landscape of non-small cell lung cancer (NSCLC). We performed a retro-prospective study to describe the patients’ outcomes prior to and after the local regulatory approval of pembrolizumab as a first-line (1L) treatment in the real-world setting of an Italian cancer centre. Analyses were performed of a total of 694 patients with no or unknown oncogene addicted tumour, grouped into Pre- (n = 344) and Post- (n = 350) 1L IO populations. The study provides evidence of improvements in overall survival associated with the introduction of 1L immunotherapy, suggesting that receiving immunotherapy in the first-line rather than in the second- or later lines of treatment may be more favourable. Abstract Background: This study provides insights into the treatment use and outcomes of metastatic non-small cell lung cancer (NSCLC) patients in a real-world setting prior to and after the availability of immuno-oncology (IO) regimens in the first line (1L). Methods: Metastatic NSCLC patients, who initiated systemic 1L anticancer treatment from 2014 to 2020, were identified from health records. Patients were grouped into Pre-1L IO and Post-1L IO, according to the availability of pembrolizumab 1L monotherapy at the date of initiating 1L systemic anticancer treatment. Patient characteristics, treatment patterns and outcomes were assessed by the cohort. Overall survival (OS) and real-world progression-free survival (rwPFS) were calculated using the Kaplan-Meier method. Results: The most common 1L treatment was platinum-based chemotherapy regimens in both groups (≥46%), followed by single-agent chemotherapy (27.0%) in Pre-1L IO and pembrolizumab (26.0%) in Post-1L IO. Median OS was 6.2 (95% CI 5.5–7.4) in Pre- and 8.9 months (95% CI 7.5–10.6) in Post-1L IO, while rwPFS was 3.7 (95% CI 3.3–4.2) and 4.7 months (95% CI 3.9–5.7), respectively. Conclusions: Even if a small proportion of patients received a 1L IO, the data showed an improved survival outcomes in the Post-1L IO group.
Structure of rapidly rotating axisymmetric stars. I, A numerical method for stellar structure and meridional circulation

We present a numerical method to calculate the mechanical and thermal structure of stationary axisymmetric inviscid rotating stars in which the velocity of the meridional flow is very slow. We further assume that the centrifugal force can be derived from a rotational potential. With these assumptions surfaces of constant temperature, pressure, and density coincide, i.e. the structure and the flow can be treated separately. Thus we first compute the structure of the rotating configuration and then calculate the flow pattern for the given configuration. In order to demonstrate how our method works, we have computed several sequences of stationary configurations for three different rotation laws.
Vertex maps between simplices, cubes, and crosspolytopes

We study the vertices of the polytopes of all affine maps (a.k.a. hom-polytopes) between higher dimensional simplices, cubes, and crosspolytopes. Systematic study of general hom-polytopes was initiated in [3]. The study of such vertices is the classical aspect of a conjectural homological theory of convex polytopes. One quickly runs into open problems even for simple source and target polytopes. The vertices of Hom(simplex_m,-) and Hom(-,cube_n) are easily understood. In this work we describe the vertex sets of Hom(box_m,simplex_n), Hom(diamond_m,simplex_n), and Hom(diamond_m,diamond_n). The emergent pattern in our arguments is reminiscent of diagram chasing in homological algebra.
Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Freeway on-ramp merging area is deemed to be typical bottlenecks section, which leads to low traffic efficiency, congestions, and frequent accidents. Most existing studies on merging for the connected and automated vehicles focus on merging at a single fixed merging point. However, the problem of coordination between merging vehicle and arterial traffic flow in the acceleration lane is ignored in the existing studies. This study proposes a merging model, which combined safety and coordination of CAVs with featuring optimal merging positions. The proposed model has two stages: one is analysis of merging velocity of the insertable gap and the other one is determining constraint condition of cooperative merging. The outputs of first stage are interval of merging speed and the mergeable range. The outputs of second stage are optional insertable gap and the corresponding driving scheme. Then, a traffic simulation experiment is designed to evaluate the proposed model. The simulation results show that the proposed model can effectively guarantee driving safety and make the merging process smoother with 28.7% reduction in travel time for the CAV merging. Furthermore, the proposed model does not sacrifice the interests of surrounding traffic to assist in CAV merging. The results indicate the promising potential of using the proposed methods can approximately get a fair use of road resources for each CAV.
Regularizing Transformer-based Acoustic Models by Penalizing Attention Weights

The application of deep learning has significantly advanced the performance of automatic speech recognition (ASR) systems. Various components make up an ASR system, such as the acoustic model (AM), language model (LM), and lexicon. Generally, the AM has benefited the most from deep learning. Numerous types of neural network-based AMs have been studied, but the structure that has received the most attention in recent years is the Transformer [1]. In this study, we demonstrate that the Transformer model is more vulnerable to input sparsity compared to the convolutional neural network (CNN) and analyze the cause of performance degradation through structural characteristics of the Transformer. Moreover, we also propose a novel regularization method that makes the transformer model robust against input sparsity. The proposed sparsity regularization method directly regulates attention weights using silence label information in forced-alignment and has the advantage of not requiring additional module training and excessive computation. We tested the proposed method on five benchmarks and observed an average relative error rate reduction (RERR) of 4.7%.
The Role of Titanium Particles and Ions in the Pathogenesis of Peri-Implantitis

Titanium (Ti) particles and ions have been investigated in recent years as important factors in the pathogenesis of peri-implantitis. However, their role in the pathogenesis is yet to be fully understood. A review of pertinent literature was performed in various databases to determine the current position of Ti particles and ions role in the pathogenesis of peri-implantitis. There are several in vitro, preclinical and clinical published studies that have addressed the role of Ti particles and ions in the pathogenesis of peri-implantitis. These studies explored the effect of Ti particles and ions in the pathogenesis of peri-implantitis with respect to foreign body reaction, cellular response, epigenetic mechanisms, namely DNA methylation, and the oral microbiome. Studies have shown that the release of Ti particles/ions during implant insertion, early healing stages, late healing stages, and treatments during peri-implantitis might contribute to peri-implantitis through different mechanisms, such as foreign body reaction, cellular response, DNA methylation, and shaping the oral microbiome by increasing dysbiosis. However, further studies are needed to elucidate the complex interactions between all these mechanisms and Ti particles/ions in the pathogenesis and progression of peri-implantitis.
Evolution of the Soil Report Carbon / Nitrogen in Relation with the Severity of the Bunette Groove of Cassava (SBM) in Three Agrosystems of the Yakonde Set (Y2) in the Reserve of the Biosphere of Yangambi, DRC

The occupation of earth, dominated by the peasant fields of Obama cassava in forest zone on the Yakonde set (Y2) in Yangambi in Congolese central pan (RDC), change quickly and the forest fragmentation bound to the roving agriculture on the giblets-burnt lands became one of the processes dominating the landscape dynamics. In addition to the machete and the ax, fire remained for the agriculturists of the region an excellent means to get rid of the cut vegetation and also to lead physical and chemical modifications quickly in the superficial layers of soil. To put in evidence, the evolution of the values of the C/N report of soil in report to those of the severity of the brunette groove of cassava (SBM) that rages currently in Yangambi (CWAVE project), three agrosystèmes of the Yakonde set (Y2) have been chosen: the secondary forest (FS), the forest recrû (RF) and the grassy fallow (JH). In every in every different type of forests, an extent of 50m x 50m was there cut, arranged and without use of fire and the cuttings healthy and infected of SBM of the cassava of the Obama variety have been planted in lines simple oriented north-south in under-parcels in repeated at random two blocks. In 19 pedological pits of the experimental site, 76 pedological samples have been appropriated in two slices of soil: 0 - 20 cm and 20 - 40 cm of depth. The total organic nitrogen of soil has been measured out by the Kjeldhal method and the carbon, by the method to the bichromate of potassium by humid way and to cold weather (Kombele, 2004, Kakuni, 2020). as for the severity of SBM, she/it has been determined by observations on symptomatic leaves and without the symptoms according to the methods of Sseruwagi and al. (2005) and Mware and al. (2009). The results gotten to four months of age of Obama cassava show that the middle values of the C/N are raised more in the grassy fallow (JH) with 8,76±3,43 and a severity of the SBM of 2,7, consistent of those of the secondary forest (FS) with 7,26±3,37 the C/N and a severity of the SBM of 2,4, those of the forest recrû (RF) with 5,28±3,02 the C/N and a severity of the SBM of 2,1.
Rissanen's Theorem and Econometric Time Series

In a typical empirical modeling context, the data generating process (DGP) of a time series is assumed to be known up to a finite-dimensional parameter. In such cases, Rissanen's (1986) theorem provides a lower bound for the empirically achievable distance between all possible data-based models and the true DGP. This distance depends only on the dimension of the parameter space. The present paper examines the empirical relevance of this notion to econometric time series and discusses a new version of the theorem that allows for nonstationary DGP's. Nonstationarity is relevant in many economic applications and it is shown that the form of nonstationarity affects, and indeed increases, the empirically achievable distance to the true DGP.
iCNN-Transformer: An improved CNN-Transformer with Channel-spatial Attention and Keyword Prediction for Automated Audio Captioning

Automated audio captioning (AAC) is a task to generates text description of an audio recording. Sound events, acoustic scene and the relationship between events are described in audio cap-tions. Currently, most AAC systems are based on encoder-decoder architecture, in which the decoder predicts the caption completely according to the features extracted from the audio clip. As a result, learning more efficient audio features allows the decoder to generate more appropriate descriptions. This paper proposes an approach to guide the generation of captioning by multi-level information extracted from audio clip. Specifically, we use two modules to obtain acoustic information for semantic expression. (1) A module that combines channel attention and spatial attention to pay more attention to important features. (2) A trained keyword prediction module to generate word-level guidance information. We apply our modules to the CNN-Transformer architecture and experiment in Clotho. The results show that the proposed approach can significantly improve the scores of various evaluation metrics and achieve the state-of-the-art performance in the Cross-entropy training stage.