Miracle-dz/UniFAR-FTUs huggingface dataset:
Fore-aft clearance controls how three-dimensional confinement affects micropropulsion

Systems of active particles are often affected by confinement due to nearby boundaries. Recently, there has been interest in the effect of confinement by complex three dimensional geometries, as might occur in structured environments such as porous media, foams, gels, or biological tissues and ducts. The effects of confinement for particles moving along boundaries has been extensively studied, but in three dimensions active particles move not only parallel to boundaries, but also towards or away from boundaries. The consequences of this fore-aft clearance is less well understood. Swimmers that actively remodel their environment create an ideal situation to study the effect of clearance, since they maintain a steady clearance while translating. By numerically studying the locomotion of the bacterium Helicobacter pylori, which de-gels surrounding gastric mucus to make a comoving pocket of fluid around itself, we show that the effect of three-dimensional confinement is controlled by clearance, rather than distance from a parallel boundary. Analytical calculations show that the effect of clearance can be understood in terms of flow structures, such as the generic pusher and puller flows of active particles, indicating that our results should apply to a wide range of confined active particles.
Summarization of the Measurement Method for Muzzle Vibration Responses

In order to getting the muzzle vibration responses with experiment methods,a lot of measuring sensors and methods had be developed. The muzzle vibration responses are the linear displacement,linear velocity linear acceleration,angular displacement,angular velocity and angular acceleration. The sensors used for the muzzle vibration responses include the eddy current type,laser CCD type,photoelectricity type and so on.By measuring linear displacement,the angular displacement is obtained.With the laser scanning vibrometer,based on the Doppler effect,the muzzle vibration velocity is measured.The angular velocity of the muzzle vibration is get by the angular velocity gyroscope.The acceleration sensors in piezo-effect type are widely used.With applying the new techniques and new principles,it can promote the development of the measuring methods for the muzzle vibration responses.
Randomized Block Adaptive Linear System Solvers

Randomized linear solvers randomly compress and solve a linear system with compelling theoretical convergence rates and computational complexities. However, such solvers suffer a substantial disconnect between their theoretical rates and actual efficiency in practice. Fortunately, these solvers are quite flexible and can be adapted to specific problems and computing environments to ensure high efficiency in practice, even at the cost of lower effectiveness (i.e., having a slower theoretical rate of convergence). While highly efficient adapted solvers can be readily designed by application experts, will such solvers still converge and at what rate? To answer this, we distill three general criteria for randomized adaptive solvers, which, as we show, will guarantee a worst-case exponential rate of convergence of the solver applied to consistent and inconsistent linear systems irrespective of whether such systems are over-determined, under-determined or rank-deficient. As a result, we enable application experts to design randomized adaptive solvers that achieve efficiency and can be verified for effectiveness using our theory. We demonstrate our theory on twenty-six solvers, nine of which are novel or novel block extensions of existing methods to the best of our knowledge.
Towards Web Phishing Detection Limitations and Mitigation

Web phishing remains a serious cyber threat responsible for most data breaches. Machine Learning (ML)-based anti-phishing detectors are seen as an effective countermeasure, and are increasingly adopted by web-browsers and software products. However, with an average of 10K phishing links reported per hour to platforms such as PhishTank and VirusTotal (VT), the deficiencies of such ML-based solutions are laid bare. We first explore how phishing sites bypass ML-based detection with a deep dive into 13K phishing pages targeting major brands such as Facebook. Results show successful evasion is caused by: (1) use of benign services to obscure phishing URLs; (2) high similarity between the HTML structures of phishing and benign pages; (3) hiding the ultimate phishing content within Javascript and running such scripts only on the client; (4) looking beyond typical credentials and credit cards for new content such as IDs and documents; (5) hiding phishing content until after human interaction. We attribute the root cause to the dependency of ML-based models on the vertical feature space (webpage content). These solutions rely only on what phishers present within the page itself. Thus, we propose Anti-SubtlePhish, a more resilient model based on logistic regression. The key augmentation is the inclusion of a horizontal feature space, which examines correlation variables between the final render of suspicious pages against what trusted services have recorded (e.g., PageRank). To defeat (1) and (2), we correlate information between WHOIS, PageRank, and page analytics. To combat (3), (4) and (5), we correlate features after rendering the page. Experiments with 100K phishing/benign sites show promising accuracy (98.8%). We also obtained 100% accuracy against 0-day phishing pages that were manually crafted, comparing well to the 0% recorded by VT vendors over the first four days.
Estimating the Entropy of Linguistic Distributions

Shannon entropy is often a quantity of interest to linguists studying the communicative capacity of human language. However, entropymust typically be estimated from observed data because researchers do not have access to the underlying probability distribution. While entropy estimation is a well-studied problem in other fields, there is not yet a comprehensive exploration of the efficacy of entropy estimators for use with linguistic data. In this work, we fill this void, studying the empirical effectiveness of different entropy estimators for linguistic distributions. In a replication of two recent information-theoretic linguistic studies, we find evidence that the reported effect size is over-estimated due to over-reliance on poor entropy estimators. We end this paper with a concrete recommendation for the entropy estimators that should be used in future linguistic studies.
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors

Generating high quality texts with high diversity is important for many NLG applications, but current methods mostly focus on building deterministic models to generate higher quality texts and do not provide many options for promoting diversity. In this work, we present a novel latent structured variable model to generate high quality texts by enriching contextual representation learning of encoder-decoder models. Specifically, we introduce a stochastic function to map deterministic encoder hidden states into random context variables. The proposed stochastic function is sampled from a Gaussian process prior to (1) provide infinite number of joint Gaussian distributions of random context variables (diversity-promoting) and (2) explicitly model dependency between context variables (accurate-encoding). To address the learning challenge of Gaussian processes, we propose an efficient variational inference approach to approximate the posterior distribution of random context variables. We evaluate our method in two typical text generation tasks: paraphrase generation and text style transfer. Experimental results on benchmark datasets demonstrate that our method improves the generation quality and diversity compared with other baselines.
Improved Approximation Algorithm for Graph Burning on Trees

Given a graph $G=(V,E)$, the problem of \gb{} is to find a sequence of nodes from $V$, called burning sequence, in order to burn the whole graph. This is a discrete-step process, in each step an unburned vertex is selected as an agent to spread fire to its neighbors by marking it as a burnt node. A node that is burnt spreads the fire to its neighbors at the next consecutive step. The goal is to find the burning sequence of minimum length. The \gb{} problem is NP-Hard for general graphs and even for binary trees. A few approximation results are known, including a $3$-approximation algorithm for general graphs and a $2$- approximation algorithm for trees. In this paper, we propose an approximation algorithm for trees that produces a burning sequence of length at most $\lfloor 1.75b(T) \rfloor + 1$, where $b(T)$ is length of the optimal burning sequence, also called the burning number of the tree $T$. In other words, we achieve an approximation factor of $(\lfloor 1.75b(T) \rfloor + 1)/b(T)$.
Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization

Reducing energy consumption is a critical point for neural network models running on edge devices. In this regard, reducing the number of multiply-accumulate (MAC) operations of Deep Neural Networks (DNNs) running on edge hardware accelerators will reduce the energy consumption during inference. Spiking Neural Networks (SNNs) are an example of bio-inspired techniques that can further save energy by using binary activations, and avoid consuming energy when not spiking. The networks can be configured for equivalent accuracy on a task through DNN-to-SNN conversion frameworks but their conversion is based on rate coding therefore the synaptic operations can be high. In this work, we look into different techniques to enforce sparsity on the neural network activation maps and compare the effect of different training regularizers on the efficiency of the optimized DNNs and SNNs.
The Effects of the Environment and Linear Actuators on Robot Morphologies

The field of evolutionary robotics uses principles of natural evolution to design robots. In this paper, we study the effect of adding a new module inspired by the skeletal muscle to the existing RoboGen framework: the linear actuator. Additionally, we investigate how robots evolved in a plain environment differ from robots evolved in a rough environment. We consider the task of directed locomotion for comparing evolved robot morphologies. The results show that the addition of the linear actuator does not have a significant impact on the performance and morphologies of robots evolved in a plain environment. However, we find significant differences in the morphologies of robots evolved in a plain environment and robots evolved in a rough environment. We find that more complex behavior and morphologies emerge when we change the terrain of the environment.
A landscape of peaks: The intermittency islands of the stochastic heat equation with Lévy noise

We show that the spatial profile of the solution to the stochastic heat equation features multiple layers of intermittency islands if the driving noise is non-Gaussian. On the one hand, as expected, if the noise is sufficiently heavy-tailed, the largest peaks of the solution will be taller under multiplicative than under additive noise. On the other hand, surprisingly, as soon as the noise has a finite moment of order $\frac2d$, where $d$ is the spatial dimension, the largest peaks will be of the same order for both additive and multiplicative noise, which is in sharp contrast to the behavior of the solution under Gaussian noise. However, in this case, a closer inspection reveals a second layer of peaks, beneath the largest peaks, that is exclusive to multiplicative noise and that can be observed by sampling the solution on the lattice. Finally, we compute the macroscopic Hausdorff and Minkowski dimensions of the intermittency islands of the solution. Under both additive and multiplicative noise, if it is not too heavy-tailed, the largest peaks will be self-similar in terms of their large-scale multifractal behavior. But under multiplicative noise, this type of self-similarity is not present in the peaks observed on the lattice.
Electrotactile Feedback Applications for Hand and Arm Interactions: A Systematic Review, Meta-Analysis, and Future Directions

Haptic feedback is critical in a broad range of human-machine/computer-interaction applications. However, the high cost and low portability/wearability of haptic devices remain unresolved issues, severely limiting the adoption of this otherwise promising technology. Electrotactile interfaces have the advantage of being more portable and wearable due to their reduced actuators’ size, as well as their lower power consumption and manufacturing cost. The applications of electrotactile feedback have been explored in human-computer interaction and human-machine-interaction for facilitating hand-based interactions in applications, such as prosthetics, virtual reality, robotic teleoperation, surface haptics, portable devices, and rehabilitation. This article presents a technological overview of electrotactile feedback, as well a systematic review and meta-analysis of its applications for hand-based interactions. We discuss the different electrotactile systems according to the type of application. We also discuss over a quantitative congregation of the findings, to offer a high-level overview into the state-of-art and suggest future directions. Electrotactile feedback systems showed increased portability/wearability, and they were successful in rendering and/or augmenting most tactile sensations, eliciting perceptual processes, and improving performance in many scenarios. However, knowledge gaps (e.g., embodiment), technical (e.g., recurrent calibration, electrodes’ durability) and methodological (e.g., sample size) drawbacks were detected, which should be addressed in future studies.
Numerical Simulation Methods on Dynamic Response of Partially-buried Structure Under Blast Loading

In this paper,the numerical simulation of the dynamic response inside partially-buried structures is studied out by the LS-DYNA3D program．During the simulation of the explosive loads,there are two meth- ods．One is that equivalent pressure time-histories inside explosive cavity are used to simulate the loads．The other is that using a piece of DYNA3D material specifically designed for simulating high explosive detonation (ALE)．The results indicate that the numerical simulated precision of method and the precision of Lagrangian method is very close．The precision of the ALE method is much higher than the above metioned two methods, but more computing time is required．So the equivalent pressure time-histories inside explosive cavity method is superior in practice．
New Upper Bounds on the Error Probability under ML Decoding for Spinal Codes and the Joint Transmission-Decoding System Design

Spinal codes are a type of capacity-achieving rateless codes that have been proved to approach the Shannon capacity over the additive white Gaussian noise (AWGN) channel and the binary symmetric channel (BSC). In this paper, we aim to analyze the bounds on the error probability of Spinal codes and design a joint transmission-decoding system. First, in the ﬁnite block-length regime, we derive new upper bounds on the Maximum Likelihood (ML) decoding error probability for Spinal codes over both the AWGN channel and the BSC. Then, based on the derived bounds, we formulate a rate maximization problem. As the solution exhibits an incremental-tail-transmission pattern, we propose an improved transmission scheme, referred to as the thresholded incremental tail transmission (TITT) scheme. Moreover, we also develop a dynamic TITT-matching decoding algorithm, called the bubble decoding with memory (BD-M) algorithm, to reduce the decoding time complexity. The TITT scheme at the transmitter and the BD-M algorithm at the receiver jointly constitute a dynamic transmission-decoding system for Spinal code, improving its rate performance and decoding throughput. Theoretical analysis and simulation results are provided to verify the superiority of the derived bounds and the proposed joint transmission-decoding system design.
Large deviations, moment estimates and almost sure invariance principles for skew products with mixing base maps and expanding on the average fibers

In this paper we show how to apply classical probabilistic tools for partial sums $\sum_{j=0}^{n-1}\varphi\circ\tau^j$ generated by a skew product $\tau$, built over a sufficiently well mixing base map and a random expanding dynamical system. Under certain regularity assumptions on the observable $\varphi$, we obtain a central limit theorem (CLT) with rates, a functional CLT, an almost sure invariance principle (ASIP), a moderate deviations principle, several exponential concentration inequalities and Rosenthal type moment estimates for skew products with $\alpha, \phi$ or $\psi$ mixing base maps and expanding on the average random fiber maps. All of the results are new even in the uniformly expanding case. The main novelty here (contrary to \cite{ANV}) is that the random maps are not independent, they do not preserve the same measure and the observable $\varphi$ depends also on the base space. For stretched exponentially $\al$-mixing base maps our proofs are based on multiple correlation estimates, which make the classical method of cumulants applicable. For $\phi$ or $\psi$ mixing base maps, we obtain an ASIP and maximal and concentration inequalities by establishing an $L^\infty$ convergence of the iterates $\cK^n$ of a certain transfer operator $\cK$ with respect to a certain sub-$\sig$-algebra, which yields an appropriate (reverse) martingale-coboundary decomposition.
Constraining Designs for Synthesis and Timing Analysis: A Practical Guide to Synopsys Design Constraints (Sdc)

This book serves as a hands-on guide to timing constraints in integrated circuit design. Readers will learn to maximize performance of their IC designs, by specifying timing requirements correctly. Coverage includes key aspects of the design flow impacted by timing constraints, including synthesis, static timing analysis and placement and routing. Concepts needed for specifying timing requirements are explained in detail and then applied to specific stages in the design flow, all within the context of Synopsys Design Constraints (SDC), the industry-leading format for specifying constraints.
Study on Course Timetable Planning

It is the distribution of time resource among course timetable planning problems that restricts room resource in utilization.Based on the distribution of time resource,this paper introduces a project to modify the timetable and to improve the project to answer the efficiency,fairness and transplantability in timetable planning.The result of the discussion of its performance shows that the application of the improved project can not only improve the efficiency,but also meet almost all the requirements on time in course timetable planning.At last,the acceptable degree of the time by analytic hierarchy process has been gained and the analysis shows that the application of the improved project can better fair factors in timetable.
Olfactory Loss and Beyond: A Practical Review of Chemosensory Dysfunction

Background: Our ability to smell and taste is dictated by 3 chemosensory systems with distinct physiologic mechanisms – olfaction, gustation, and chemesthesis. Although often overlooked, dysfunction of these spe-cial senses may have broad implications on multiple facets of patients’ lives –including safety, nutritional status, quality of life, mental health, and even cognitive function. As “loss of smell or taste” emerged as a common symptom of coronavirus disease 2019 (COVID-19), the importance of intact chemosensory function has been thrust into the spotlight. Despite the growing recognition of chemosensory dysfunction, this already highly prevalent condition will increasingly impact a larger and more diverse population, highlight-ing the need for improved awareness and care of these patients. Methods: Comtemporary review of chemosensory function and assessments. Conclusions: Although patient-reported chemosensory function measures highlight the ease of screening of chemosensory dysfunction, self-reported measures underestimate both the prevalence and degree of chemosensory dysfunction and do not adequately distinguish between olfaction, gustation, and chemesthesis. Mean-while, psychophysical assessment tools provide opportunities for more accurate, thorough assessment of the chemosenses when appropriate. Primary care providers are uniquely situated to identify patients burdened by chemosensory dysfunction and raise patient and provider awareness about the importance of chemosensory dysfunction. Identiﬁcation of chemosensory dysfunction, particularly olfactory dysfunction, may raise suspicion for many underlying medical conditions, including early detection of neurodegenerative conditions. Further-more, identiﬁcation and awareness of patients with chemosensory dysfunction may help primary care providers to identify those who may beneﬁt from additional therapeutic and safety interventions, or consultations with specialists for more detailed evaluations and management. (J Am Board Fam Med 2022;35:406–419.)
Assessing the Adequacy of Obstructive Sleep Apnea Diagnosis for High-Risk Patients in Primary Care

Introduction: The exact prevalence of obstructive sleep apnea (OSA) is unknown, and primary care providers are left with conflicting guidance on screening criteria from various institutions. The purpose of this study was to identify health care gaps in OSA diagnosis for patients at high risk of OSA. Methods: A retrospective medical record review was performed assessing adult patients (≥ 18 years) who had outpatient visits in family medicine clinics, located in the cities of Detroit, Troy, and Commerce, Michigan in 2018. The primary outcome was the number of patients assessed for OSA. Patients determined as high risk for OSA had at least 3 of the following criteria: (1) hypertension, (2) age 50 years and older, (3) male gender, and (4) body mass index > 35 kg/m2. Statistical approach included univariate and logistic regression analysis. Manual chart review of 200 randomly selected records was performed to determine the most common reasons for OSA screening. Results: Out of 30,022 patients, 4,911 (16.4%) were at high risk for OSA, of which 1,524 (31.0%) were assessed for OSA. Logistic regression analysis of high-risk patients revealed that male sex (odds ratio, 1.84; 95% CI, 1.51–2.26; P < .001) and body mass index > 35 kg/m2 (odds ratio, 4.96; 95% CI, 4.04–6.09; P < .001) were significantly associated with OSA evaluation. Race was not associated with OSA assessment. Conclusion: Because many individuals at high risk for OSA are not referred for evaluation, improved guidance on OSA screening based on objective risk factors is needed.
Sapphire irradiation by phosphorus as an approach to improve its optical properties

Abstract Ion beam-induced luminescence (IBIL) is a versatile technique used to elucidate the chemical bond’s nature and analyze the defects study and impurities present in the material. In this study, IBIL spectra of phosphorus-irradiated sapphire has been analyzed under 2 MeV proton beam as a function of ion dose ranging from 1 × 1014 to 10 × 1014 ions/cm2 at room temperature in the wavelength range of 200–1,000 nm. The IBIL spectrum shows three kinds of luminescence features. The bands centered at 419 nm as F center and 330 nm as F+ center are associated with oxygen vacancies. The third kind of luminescence feature located at 704 nm is related to chromium impurities present in the crystal. The luminescence spectrum of the phosphorus-irradiated sapphire has been correlated with the spectrum obtained from pristine sapphire. The finding indicates that the intensity of defects due to phosphorus irradiation is reduced. As the proton ion fluence increases, the F and F+ center luminescence intensity eventually varies; it turns out that in phosphorus-irradiated sapphire, single crystal defects were reduced and the optical quality was improved.