Miracle-dz/UniFAR-FTUs huggingface dataset:
Rejective Sampling, Rerandomization, and Regression Adjustment in Survey Experiments

Abstract Classical randomized experiments, equipped with randomization-based inference, provide assumption-free inference for treatment effects. They have been the gold standard for drawing causal inference and provide excellent internal validity. However, they have also been criticized for questionable external validity, in the sense that the conclusion may not generalize well to a larger population. The randomized survey experiment is a design tool that can help mitigate this concern, by randomly selecting the experimental units from the target population of interest. However, as pointed out by Morgan and Rubin, chance imbalances often exist in covariate distributions between different treatment groups even under completely randomized experiments. Not surprisingly, such covariate imbalances also occur in randomized survey experiments. Furthermore, the covariate imbalances happen not only between different treatment groups, but also between the sampled experimental units and the overall population of interest. In this article, we propose a two-stage rerandomization design that can actively avoid undesirable covariate imbalances at both the sampling and treatment assignment stages. We further develop asymptotic theory for rerandomized survey experiments, demonstrating that rerandomization provides better covariate balance, more precise treatment effect estimators, and shorter large-sample confidence intervals. We also propose covariate adjustment to deal with remaining covariate imbalances after rerandomization, showing that it can further improve both the sampling and estimated precision. Our work allows general relationship among covariates at the sampling, treatment assignment and analysis stages, and generalizes both rerandomization in classical randomized experiments and rejective sampling in survey sampling.
AirDOS: Dynamic SLAM benefits from Articulated Objects

Dynamic Object-aware SLAM (DOS) exploits object-level information to enable robust motion estimation in dynamic environments. Existing methods mainly focus on identifying and excluding dynamic objects from the optimization. In this paper, we show that feature-based visual SLAM systems can also benefit from the presence of dynamic articulated objects by taking advantage of two observations: (1) The 3D structure of each rigid part of articulated object remains consistent over time; (2) The points on the same rigid part follow the same motion. In particular, we present AirDOS, a dynamic object-aware system that introduces rigidity and motion constraints to model articulated objects. By jointly optimizing the camera pose, object motion, and the object 3D structure, we can rectify the camera pose estimation, preventing tracking loss, and generate 4D spatio-temporal maps for both dynamic objects and static scenes. Experiments show that our algorithm improves the robustness of visual SLAM algorithms in challenging crowded urban environments. To the best of our knowledge, AirDOS is the first dynamic object-aware SLAM system demonstrating that camera pose estimation can be improved by incorporating dynamic articulated objects.
Oscillations and collective behavior in convective flows

Oscillation and collective behavior in convection-driven fluid columns are investigated and discussed in analogy with similar phenomenon observed for the flickering flames of candle bundles. It is shown experimentally that an ascending circular Helium gas column performs an oscillation which is similar in several aspects to the oscillation of diffusion flames. Increasing the nozzle diameter leads to a decrease in the oscillation frequency, while increasing the flow rate results in an increase in this frequency. For helium columns oscillating at nearby frequency and placed close to each other anti-phase synchronization and beating phenomena is observed. A simple toy-model based on elementary hydrodynamics describes the observed oscillations and leads to oscillation frequencies in the right order of magnitude.
Physics-based Human Motion Estimation and Synthesis from Videos

Human motion synthesis is an important problem with applications in graphics, gaming and simulation environments for robotics. Existing methods require accurate motion capture data for training, which is costly to obtain. Instead, we propose a framework for training generative models of physically plausible human motion directly from monocular RGB videos, which are much more widely available. At the core of our method is a novel optimization formulation that corrects imperfect image-based pose estimations by enforcing physics constraints and reasons about contacts in a differentiable way. This optimization yields corrected 3D poses and motions, as well as their corresponding contact forces. Results show that our physically-corrected motions significantly outperform prior work on pose estimation. We can then use these to train a generative model to synthesize future motion. We demonstrate both qualitatively and quantitatively significantly improved motion estimation, synthesis quality and physical plausibility achieved by our method on the large scale Human3.6m dataset [12] as compared to prior kinematic and physics-based methods. By enabling learning of motion synthesis from video, our method paves the way for large-scale, realistic and diverse motion synthesis.
Thermoelectric Polymer Aerogels for Pressure–Temperature Sensing Applications

The evolution of the society is characterized by an increasing flow of information from things to the internet. Sensors have become the cornerstone of the internet‐of‐everything as they track various parameters in the society and send them to the cloud for analysis, forecast, or learning. With the many parameters to sense, sensors are becoming complex and difficult to manufacture. To reduce the complexity of manufacturing, one can instead create advanced functional materials that react to multiple stimuli. To this end, conducting polymer aerogels are promising materials as they combine elasticity and sensitivity to pressure and temperature. However, the challenge is to read independently pressure and temperature output signals without cross‐talk. Here, a strategy to fully decouple temperature and pressure reading in a dual‐parameter sensor based on thermoelectric polymer aerogels is demonstrated. It is found that aerogels made of poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) can display properties of semiconductors lying at the transition between insulator and semimetal upon exposure to high boiling point polar solvents, such as dimethylsulfoxide (DMSO). Importantly, because of the temperature‐independent charge transport observed for DMSO‐treated PEDOT‐based aerogel, a decoupled pressure and temperature sensing can be achieved without cross‐talk in the dual‐parameter sensor devices.
Robust Estimation of Reflection Symmetry in Noisy and Partial 3D Point Clouds

—Detecting the reﬂection symmetry plane of an object represented by a 3D point cloud is a fundamental problem in 3D computer vision and geometry processing due to its various applications such as compression, object detection, robotic grasping, 3D surface reconstruction, etc. There exist several efﬁcient approaches for solving this problem for clean 3D point clouds. However, this problem becomes difﬁcult to solve in the presence of outliers and missing parts due to occlusions while scanning the objects through 3D scanners. The existing methods try to overcome these challenges mostly by voting-based techniques but fail in challenging settings. In this work, we propose a statistical estimator for the plane of reﬂection symmetry that is robust to outliers and missing parts. We pose the problem of ﬁnding the optimal estimator as an optimization problem on a 2-sphere that quickly converges to the global solution. We further propose a 3D point descriptor that is invariant to 3D reﬂection symmetry using the spectral properties of the geodesic distance matrix constructed from the neighbors of a point. This helps us in decoupling the chicken-and-egg problem of ﬁnding optimal symmetry plane and correspondences between the reﬂective symmetric points. We show that the proposed approach achieves the state-of-the-art performance on the benchmarks dataset.
Informed Sampling for Diversity in Concept-to-Text NLG

Deep-learning models for language generation tasks tend to produce repetitive output. Various methods have been proposed to encourage lexical diversity during decoding, but this often comes at a cost to the perceived fluency and adequacy of the output. In this work, we propose to ameliorate this cost by using an Imitation Learning approach to explore the level of diversity that a language generation model can reliably produce. Specifically, we augment the decoding process with a metaclassifier trained to distinguish which words at any given timestep will lead to high-quality output. We focus our experiments on conceptto-text generation where models are sensitive to the inclusion of irrelevant words due to the strict relation between input and output. Our analysis shows that previous methods for diversity underperform in this setting, while human evaluation suggests that our proposed method achieves a high level of diversity with minimal effect to the output’s fluency and adequacy.
Electrotactile Feedback For Enhancing Contact Information in Virtual Reality

This paper presents a wearable electrotactile feedback system to enhance contact information for mid-air interactions with virtual objects. In particular, we propose the use of electrotactile feedback to render the interpenetration distance between the user's finger and the virtual content is touched. Our approach consists of modulating the perceived intensity (frequency and pulse width modulation) of the electrotactile stimuli according to the registered interpenetration distance. In a user study (N=21), we assessed the performance of four different interpenetration feedback approaches: electrotactile-only, visual-only, electrotactile and visual, and no interpenetration feedback. First, the results showed that contact precision and accuracy were significantly improved when using interpenetration feedback. Second, and more interestingly, there were no significant differences between visual and electrotactile feedback when the calibration was optimized and the user was familiarized with electrotactile feedback. Taken together, these results suggest that electrotactile feedback could be an efficient replacement of visual feedback for enhancing contact information in virtual reality avoiding the need of active visual focus and the rendering of additional visual artefacts.
LSTM-Aided Hybrid Random Access Scheme for Machine-Type Communication in 5G-Enabled Industry 4.0

—5G enables Industry 4.0 through machine-type communication (MTC). Massive MTC (mMTC) and ultra-reliable and low-latency communication (URLLC) are two key 5G MTC scenarios to support diverse quality of service (QoS) requirements for Industry 4.0. In this paper, an LSTM-aided hybrid random access scheme (LSTMH-RA) is proposed to support 5G-enabled Industry 4.0 where mMTC and URLLC devices coexist. In the proposed LSTMH-RA scheme, mMTC devices access the network via a timing advance (TA)-aided four-step procedure to meet massive access requirement, while the access procedure of the URLLC devices is completed in two steps coupled with the mMTC devices’ access procedure to reduce latency. Furthermore, we propose an attention-based LSTM prediction model to predict the number of active URLLC devices, thereby determining the parameters of the multi-user detection algorithm to guarantee the latency and reliability access requirements of URLLC devices. We analyze the successful access probability of the LSTMH-RA scheme. Numerical results show that, compared with the benchmark schemes, the proposed LSTMH-RA scheme can signiﬁcantly improve the successful access probability, and thus satisfy the diverse QoS requirements of URLLC and mMTC devices.
Universality for Sets of Three-Valued Qubit Gates

How to find universal sets quantum gates (gates whose composition can form any othergate within a given range) is an important part of the development of quantum computation science that has been explored in the past with success. However, there has not been much development in extending this very same theory to a generalization of qubits known as quregisters or as we call them here qunits (quantum units of information analogous to qubits that use any natural number n of basis states instead of 2 as qubits do). In this paper we will first do a review of the theory behind some essential proofs of quantum gate universality for qubit gates. After that we will show a new way of extending those statements to arbitrary qutrit gates in an analogous manner.
Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning

Scope of reproducibility: We are reproducing Comparing Rewinding and Fine-tuning in Neural Networks from arXiv:2003.02389. In this work the authors compare three different approaches to retraining neural networks after pruning: 1) fine-tuning, 2) rewinding weights as in arXiv:1803.03635 and 3) a new, original method involving learning rate rewinding, building upon Lottery Ticket Hypothesis. We reproduce the results of all three approaches, but we focus on verifying their approach, learning rate rewinding, since it is newly proposed and is described as a universal alternative to other methods. We used CIFAR10 for most reproductions along with additional experiments on the larger CIFAR100, which extends the results originally provided by the authors. We have also extended the list of tested network architectures to include Wide ResNets. The new experiments led us to discover the limitations of learning rate rewinding which can worsen pruning results on large architectures. Results: We were able to reproduce the exact results reported by the authors in all originally reported scenarios. However, extended results on larger Wide Residual Networks have demonstrated the limitations of the newly proposed learning rate rewinding -- we observed a previously unreported accuracy degradation for low sparsity ranges. Nevertheless, the general conclusion of the paper still holds and was indeed reproduced.
Generalized Maslov Indices for Non-Hamiltonian Systems

We extend the definition of the Maslov index to a broad class of non-Hamiltonian dynamical systems. To do this, we introduce a family of topological spaces — which we call Maslov– Arnold spaces — that share key topological features with the Lagrangian Grassmannian, and hence admit a similar index theory. This family contains the Lagrangian Grassmannian, and much more. We construct a family of examples, called hyperplane Maslov–Arnold spaces, that are dense in the Grassmannian, and hence are much larger than the Lagrangian Grassmannian (which is a submanifold of positive codimension). The resulting index is then used to study eigenvalue problems for non-symmetric reaction–diffusion systems. A highlight of our analysis is a topological interpretation of the Turing instability: the bifurcation that occurs as one increases the ratio of diffusion coefficients corresponds to a change in the generalized Maslov index.
Measurement of keV-neutron capture cross sections and capture gamma-ray spectra of Cs-133 and I-127

The neutron capture cross sections and the capture gamma-ray spectra of 127 I and 133 Cs at incident neutron energies from 15 to 100 keV have been measured by the time-of-flight method. Capture gamma-rays were detected with an anti-Compton NaI(Tl) spectrometer, and the pulse-height weighting technique was applied to derive capture yields. The capture cross sections of 127 I and 133 Cs were determined using the standard capture cross section of 197 Au. The total errors of the cross sections were 3.8-5.1%. The obtained cross sections were compared with evaluated values in JENDL-4.0 and ENDF/B-VII.1. For 127 I, the energy dependence is different between the present results and the evaluations. For 133 Cs, the evaluated values in JENDL-4.0 agree with the present results but the evaluated values in ENDF/B-VII.1 are smaller than the present results by 14%–18%. The capture gamma-ray spectra of 133 Cs and 127 I were derived by unfolding the pulse height spectra with detector response functions.
Effects of seat pan and pelvis angles on the occupant response in a reclined position during a frontal crash

Current highly automated vehicle concepts include reclined seat layouts that could allow occupants to relax during the drive. The main objective of this study was to investigate the effects of seat pan and pelvis angles on the kinematics and injury risk of a reclined occupant by numerical simulation of a frontal sled test. The occupant, represented by a detailed 50th percentile male human body model, was positioned on a semi-rigid seat. Three seat pan angles (5, 15, and 25 degrees from the horizontal) were used, all with a seatback angle of 40 degrees from the vertical. Three pelvis angles (60, 70, and 80 degrees from the vertical), representing a nominal and two relaxed sitting positions, were used for each seat pan angle. The model was restrained using a pre-inflated airbag and a three-point seatbelt equipped with a pretensioner and a load limiter before being subjected to two frontal crash pulses. Both model kinematic response and predicted injury risk were affected by the seat pan and the pelvis angles in a reclined seatback position. Submarining occurrence and injury risk increased with lower seat pan angle, higher pelvis angle, and acceleration pulse severity. In some cases (in particular for a 15 degrees seat pan), a small variation in seat pan or pelvis angle resulted in large differences in terms of kinematics and predicted injury. This study highlights the potential effects of the seat pan and pelvis angles for reclined occupant protection. These parameters should be assessed experimentally with volunteers to determine which combinations are most likely to be adopted for comfort and with post mortem human surrogates to confirm their significance during impact and to provide data for model validation. The sled and restraint models used in this study are provided under an open-source license to facilitate further comparisons.
De Novo Powered Air-Purifying Respirator Design and Fabrication for Pandemic Response

The rapid spread of COVID-19 and disruption of normal supply chains has resulted in severe shortages of personal protective equipment (PPE), particularly devices with few suppliers such as powered air-purifying respirators (PAPRs). A scarcity of information describing design and performance criteria for PAPRs represents a substantial barrier to mitigating shortages. We sought to apply open-source product development (OSPD) to PAPRs to enable alternative sources of supply and further innovation. We describe the design, prototyping, validation, and user testing of locally manufactured, modular, PAPR components, including filter cartridges and blower units, developed by the Greater Boston Pandemic Fabrication Team (PanFab). Two designs, one with a fully custom-made filter and blower unit housing, and the other with commercially available variants (the “Custom” and “Commercial” designs, respectively) were developed; the components in the Custom design are interchangeable with those in Commercial design, although the form factor differs. The engineering performance of the prototypes was measured and safety validated using National Institutes for Occupational Safety and Health (NIOSH)-equivalent tests on apparatus available under pandemic conditions at university laboratories. Feedback was obtained from four individuals; two clinicians working in ambulatory clinical care and two research technical staff for whom PAPR use is standard occupational PPE; these individuals were asked to compare PanFab prototypes to commercial PAPRs from the perspective of usability and suggest areas for improvement. Respondents rated the PanFab Custom PAPR a 4 to 5 on a 5 Likert-scale 1) as compared to current PPE options, 2) for the sense of security with use in a clinical setting, and 3) for comfort compared to standard, commercially available PAPRs. The three other versions of the designs (with a Commercial blower unit, filter, or both) performed favorably, with survey responses consisting of scores ranging from 3 to 5. Engineering testing and clinical feedback demonstrate that the PanFab designs represent favorable alternatives to traditional PAPRs in terms of user comfort, mobility, and sense of security. A nonrestrictive license promotes innovation in respiratory protection for current and future medical emergencies.
The complete chloroplast genome sequence of Photinia × fraseri, a medicinal plant and phylogenetic analysis

Abstract Photinia × fraseri is a common ornamental arbor in the genus Photinia (family Rosaceae), which complete chloroplast (cp) genome was sequenced, assembled and annotated. The chloroplast genome of P. fraseri was 160,184 bp in length, including a large single copy (LSC) region of 88,121, a small single copy (SSC) region of 19,295 bp, and two inverted repeat (IR) regions of 26,384 bp. The GC contents of LSC, SSC, IR and whole genome are 36.5%, 34.1%, 30.3%, and 42.7%, respectively. There are 131 genes annotated, including 84 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. The phylogenetic analysis revealed that P. fraseri was most related to Photinia serratifolia as a sister group with 100% bootstrap support. The complete chloroplast genome sequences of P. fraseri will provide valuable genomic information to further illuminate phylogenetic classification of Photinia genus.
Enhancing Si3N4 Waveguide Nonlinearity with Heterogeneous Integration of Few-Layer WS2

The heterogeneous integration of low-dimensional materials with photonic waveguides has spurred wide research interest. Here, we report on the experimental investigation and the numerical modeling of enhanced nonlinear pulse broadening in silicon nitride waveguides with the heterogeneous integration of few-layer WS2. After transferring a few-layer WS2 flake of ∼14.8 μm length, the pulse spectral broadening in a dispersion-engineered silicon nitride waveguide has been enhanced by ∼48.8% in bandwidth. Through numerical modeling, an effective nonlinear coefficient higher than 600 m–1 W-1 has been retrieved for the heterogeneous waveguide indicating an enhancement factor of larger than 300 with respect to the pristine waveguide at a wavelength of 800 nm. With further advances in two-dimensional material fabrication and integration techniques, on-chip heterostructures will offer another degree of freedom for waveguide engineering, enabling high-performance nonlinear optical devices, such as frequency combs and quantum light sources.
The complete mitochondrial genome of Cephenemyia stimulator (Diptera: Oestridae)

Abstract Cephenemyia stimulator parasitizes roe deer (Capreolus capreolus) throughout its geographical distribution. The complete circular C. stimulator mitogenome was assembled, which is 16,407 bp in length, and encodes 13 protein-coding genes, 22 tRNA genes, and 2 rRNA genes. A phylogenetic tree was built with mitogenome sequences, including C. stimulator and 13 related Oestridae species, using Sarcophaga tuberosa as an outgroup.