Miracle-dz/UniFAR-FTUs huggingface dataset:
Power line detect system based on stereo vision and FPGA

In recent years, Unmanned Aerial Vehicle (UAV) is widely used for power lines patrol. While it's more efficient than manually patrolling, the UAV may easily collide with power lines. Therefore, measures must be taken to detect the distance between UAV and power lines. This paper presents a real-time power line detect system based on binocular vision techniques, which contains a hardware platform based on FPGA to calculate real time disparity map. We adopt a robust stereo matching algorithm based on cross-based arbitrary shape support region method to calculate the depth image. As power lines in captured images are always too slender to be recognized in depth map, we propose a matching cost initial method based on morphology and mini-census transform to preserve the edge of the power lines in depth images. Our tests show that this new method can properly preserves the power lines of texture-less images in depth map.
The Relationship between Subjective and Objective Measures of Sleepiness

Abstract : The purpose of the present study was to examine the relationship among the Multiple Sleep Latency Test (MSLT), lapses during a tapping task, a visual analog scale (VAS) and the Stanford sleepiness scale (SSS). Subjects were 80 male adult nonsmokers (age 20.3 + or - 2.7 years). The MSLT, SSS, and the VAS were obtained at two-hour intervals beginning at 0700 h. On the MSLT, sleep latency was measured from lights out to first spindle, K-complex or rapid-eye- movement (REM) period. The tapping task (lapses) was administered each day at 0600 h, but became nonsignificant as the day progressed. Correlations of objective and subjective measures from scores summed over both days were not significant. The two objective measures were significantly correlated throughout the day and over days as were the subjective measures. This study reaffirms the importance of time of day in sleepiness, and suggests that subjective and objective measures cannot be used interchangeably and may measure different aspects of sleepiness.
Modeling the process of ageing in face images

The process of ageing causes significant alterations in the facial appearance of individuals. When compared with other sources of variation in face images (e.g. variation due to changes in pose and expression), appearance variation due to ageing displays some unique characteristics. For example ageing variation is specific to a given individual, it occurs slowly and it is affected significantly by other factors, such as the health, gender and the lifestyle of the individual. In this paper we describe how the effects of ageing on facial appearance can be explained using a parameterized statistical model. We present experimental results to show that reasonably accurate estimates of age can be made for unseen images. We also show that we can improve our results significantly by taking into account the fact that different individuals age in different ways and by considering the effect of lifestyle. We also demonstrate how the proposed framework can be used for simulating ageing effects on new face images, in order to predict how an individual might look like in the future, or how he/she used to look in the past. Experimental and visual results on simulation of age effects are presented.
A Deep, High-Resolution Survey at 74 MHz

We present a 74 MHz survey of a 165 deg2 region located near the north Galactic pole. This survey has an unprecedented combination of both resolution (25″ FWHM) and sensitivity (σ as low as 24 mJy beam-1). We detect 949 sources at the 5 σ level in this region, enough to begin exploring the nature of the 74 MHz source population. We present differential source counts, spectral index measurements, and the size distribution as determined from counterparts in the high-resolution FIRST 1.4 GHz survey. We find a trend of steeper spectral indices for the brighter sources. Further, there is a clear correlation between spectral index and median source size, with the flat spectrum sources being much smaller on average. Ultra-steep spectrum objects (α ≤ -1.2; Sν ∝ να) are identified, and we present high-resolution VLA follow-up observations of these sources which, identified at such a low frequency, are excellent candidates for high-redshift radio galaxies.
On the failure of pseudo-nullity of Iwasawa modules

We consider the family of CM-fields which are pro-p p-adic Lie extensions of number fields of dimension at least two, which contain the cyclotomic Z_p-extension, and which are ramified at only finitely many primes. We show that the Galois groups of the maximal unramified abelian pro-p extensions of these fields are not always pseudo-null as Iwasawa modules for the Iwasawa algebras of the given p-adic Lie groups. The proof uses Kida's formula for the growth of lambda-invariants in cyclotomic Z_p-extensions of CM-fields. In fact, we give a new proof of Kida's formula which includes a slight weakening of the usual assumption that mu is trivial. This proof uses certain exact sequences involving Iwasawa modules in procyclic extensions. These sequences are derived in an appendix by the second author.
Acute and Chronic Effects of Dietary Lactose in Adult Rats Are not Explained by Residual Intestinal Lactase Activity

Neonatal rats have a high intestinal lactase activity, which declines around weaning. Yet, the effects of lactose-containing products are often studied in adult animals. This report is on the residual, post-weaning lactase activity and on the short- and long-term effects of lactose exposure in adult rats. Acutely, the postprandial plasma response to increasing doses of lactose was studied, and chronically, the effects of a 30% lactose diet fed from postnatal (PN) Day 15 onwards were evaluated. Intestinal lactase activity, as assessed both in vivo and in vitro, was compared between both test methods and diet groups (lactose vs. control). A 50%–75% decreased digestive capability towards lactose was observed from weaning into adulthood. Instillation of lactose in adult rats showed disproportionally low increases in plasma glucose levels and did not elicit an insulin response. However, gavages comprising maltodextrin gave rise to significant plasma glucose and insulin responses, indicative of a bias of the adult GI tract to digest glucose polymers. Despite the residual intestinal lactase activity shown, a 30% lactose diet was poorly digested by adult rats: the lactose diet rendered the animals less heavy and virtually devoid of body fat, whereas their cecum tripled in size, suggesting an increased bacterial fermentation. The observed acute and chronic effects of lactose exposure in adult rats cannot be explained by the residual intestinal lactase activity assessed.
Figaro : An Object-Oriented Probabilistic Programming Language

We introduce an object-oriented paradigm for probabilisti c programming, embodied in the Figaro language. Models in Figaro are objects, and may have properties such as conditions, constraints and relationships t o other objects. Figaro model classes are created by inheriting functionality from existing classes. Figaro provides a modular, compositional Metropolis-Hastings al gorithm, and gives the modeler optional control over it. Figaro is tightly integra ted into the Scala programming language, giving it access to a rich type system, co ntrol abstractions and libraries.
Computational poroelasticity — A review

Computational physics has become an essential research and interpretation tool in many fields. Particularly in reservoir geophysics, ultrasonic and seismic modeling in porous media is used to study the properties of rocks and to characterize the seismic response of geologic formations. We provide a review of the most common numerical methods used to solve the partial differential equations describing wave propagation in fluid-saturated rocks, i.e., finite-difference, pseudospectral, and finite-element methods, including the spectral-element technique. The modeling is based on Biot-type theories of dynamic poroelasticity, which constitute a general framework to describe the physics of wave propagation. We explain the various techniques and discuss numerical implementation aspects for application to seismic modeling and rock physics, as, for instance, the role of the Biot diffusion wave as a loss mechanism and interface waves in porous media.
Factors Related to Persistence of Freshmen, Freshman Transfers, and Nonfreshman Transfer Students. Professional File. Number 99, Spring 2006.

This study examined second-term and second-year retention of freshmen (n=6,054) and nonfreshman transfer students (n=2,733) from DePaul University, a large, urban, private institution. The predictor variables included both achievement and noncognitive measures collected at DePaul and on the ACT Assessment. Two questions formed the basis for this research: Do variables that predict retention for freshmen (transfer and first time) maintain their validity for predicting retention for nonfreshman transfer students? Do the noncognitive data collected on the ACT Assessment enhance the institution’s ability to predict retention? To identify variables that predict second-term and second-year retention, logistic regression models were developed separately for freshmen and nonfreshman transfer students. The results supported the use of both institutional and ACT Assessment achievement and noncognitive measures to predict retention. Moreover, variables that predicted retention for freshmen generally predicted retention for transfer students.
Design and Validation of a Fully Implantable, Chronic, Closed-Loop Neuromodulation Device With Concurrent Sensing and Stimulation

Chronically implantable, closed-loop neuromodulation devices with concurrent sensing and stimulation hold promise for better understanding the nervous system and improving therapies for neurological disease. Concurrent sensing and stimulation are needed to maximize usable neural data, minimize time delays for closed-loop actuation, and investigate the instantaneous response to stimulation. Current systems lack concurrent sensing and stimulation primarily because of stimulation interference to neural signals of interest. While careful design of high performance amplifiers has proved useful to reduce disturbances in the system, stimulation continues to contaminate neural sensing due to biological effects like tissue-electrode impedance mismatch and constraints on stimulation parameters needed to deliver therapy. In this work we describe systematic methods to mitigate the effect of stimulation through a combination of sensing hardware, stimulation parameter selection, and classification algorithms that counter residual stimulation disturbances. To validate these methods we implemented and tested a completely implantable system for over one year in a large animal model of epilepsy. The system proved capable of measuring and detecting seizure activity in the hippocampus both during and after stimulation. Furthermore, we demonstrate an embedded algorithm that actuates neural modulation in response to seizure detection during stimulation, validating the capability to detect bioelectrical markers in the presence of therapy and titrate it appropriately. The capability to detect neural states in the presence of stimulation and optimally titrate therapy is a key innovation required for generalizing closed-loop neural systems for multiple disease states.
Convergence estimates for the numerical approximationof homoclinic solutionsBj

This article is concerned with the numerical computation of homoclinic solutions converging to a hyperbolic or semi-hyperbolic equilibrium of a system _ u = f(u;). The approximation is done by replacing the original problem by a boundary value problem on a nite interval and introducing an additional phase condition to make the solution unique. Numerical experiments have indicated that the parameter is much better approximated than the homoclinic solution. This was proved in Schecter (1995) for phase conditions fulllling an additional 'niceness' assumption, which is unfortunately not satissed for the phase condition most commonly used in numerical experiments and which actually suggested the super-convergence result. Here, this result is proved for arbitrary phase conditions. Moreover, it is shown that it is suucient to approximate the original boundary value problem to rst order when considering semi-hyperbolic equilibria extending a result of Schecter (1993).
Automatic Design Space Exploration of Register Bypasses in Embedded Processors

Register bypassing is a popular and powerful architectural feature to improve processor performance in pipelined processors by eliminating certain data hazards. However, extensive bypassing comes with a significant impact on cycle time, area, and power consumption of the processor. Recent research therefore advocates the use of partial bypassing in a processor. However, accurate performance evaluation of partially bypassed processors is still a challenge, primarily due to the lack of bypass-sensitive retargetable compilation techniques. No existing partial bypass exploration framework estimates the power and area overhead of partial bypassing. As a result, the designers end up making suboptimal design decisions during the exploration of partial bypass design space. This paper presents PBExplore - an automatic design-space-exploration framework for register bypasses. PBExplore accurately evaluates the performance of a partially bypassed processor using a bypass-sensitive compilation technique. It synthesizes the bypass control logic and estimates the area and energy overhead of each bypass configuration. PBExplore is thus able to effectively perform multidimensional exploration of the partial bypass design space. We present experimental results of benchmarks from the MiBench suite on the Intel XScale architecture on and demonstrate the need, utility, and exploration capabilities of PBExplore.
Review article: the dietary management of Crohn's disease

Enteral feeding has been shown to be as effective as primary therapy for Crohn's disease, but it requires high patient motivation, may be unpalatable and is expensive. However, in adolescents with growth failure and when corticosteroid therapy is contra‐indicated or has failed, it may become the treatment of choice. Furthermore, dietary therapy allows circumvention of the adverse side‐effects of repeated courses of steroids.
Characterization of nutritionally variant streptococci by biochemical tests and penicillin-binding proteins

A comparative study of 60 strains of nutritionally variant streptococci (NVS) with 34 strains of Streptococcus mitis and 37 strains of Streptococcus sanguis II showed the presence of a red chromophore which was absent in the other streptococcal species. By using the conventional microbiological tests, only small differences were found between the NVS and the two other related species. In contrast a clear-cut delineation was found by the API 20 Strep system of identification. All NVS contained pyrrolidonylarylamidase, an enzyme which was absent in S. mitis and S. sanguis II strains, and lacked the alkaline phosphatase enzyme which was present in 56% of S. mitis strains and 62% of S. sanguis II strains. According to the additional enzymatic and biochemical tests of the API 20 Strep system, there were three biotypes among NVS. The major biotype included 33 of 60 strains which were characterized by the presence of both alpha- and beta-galactosidases and the capacity to hydrolyze trehalose. This biotype also showed a specific pattern of penicillin-binding proteins. These results show that NVS are recognized as a separate variety distinct from S. mitis and S. sanguis II species, despite some common biochemical properties. Moreover, the delineation of 33 strains with a specific biotype and a specific penicillin-binding protein pattern strongly suggests that a large part of NVS strains belong to an individual species.
Parameter Screening in Microfluidics Based Hydrodynamic Single-Cell Trapping

Microfluidic cell-based arraying technology is widely used in the field of single-cell analysis. However, among developed devices, there is a compromise between cellular loading efficiencies and trapped cell densities, which deserves further analysis and optimization. To address this issue, the cell trapping efficiency of a microfluidic device with two parallel micro channels interconnected with cellular trapping sites was studied in this paper. By regulating channel inlet and outlet status, the microfluidic trapping structure can mimic key functioning units of previously reported devices. Numerical simulations were used to model this cellular trapping structure, quantifying the effects of channel on/off status and trapping structure geometries on the cellular trapping efficiency. Furthermore, the microfluidic device was fabricated based on conventional microfabrication and the cellular trapping efficiency was quantified in experiments. Experimental results showed that, besides geometry parameters, cellular travelling velocities and sizes also affected the single-cell trapping efficiency. By fine tuning parameters, more than 95% of trapping sites were taken by individual cells. This study may lay foundation in further studies of single-cell positioning in microfluidics and push forward the study of single-cell analysis.
CoDeL: A Human Co-detection and Labeling Framework

We propose a co-detection and labeling (CoDeL) framework to identify persons that contain self-consistent appearance in multiple images. Our CoDeL model builds upon the deformable part-based model to detect human hypotheses and exploits cross-image correspondence via a matching classifier. Relying on a Gaussian process, this matching classifier models the similarity of two hypotheses and efficiently captures the relative importance contributed by various visual features, reducing the adverse effect of scattered occlusion. Further, the detector and matching classifier together make our model fit into a semi-supervised co-training framework, which can get enhanced results with a small amount of labeled training data. Our CoDeL model achieves decent performance on existing and new benchmark datasets.
Adaptive Kalman smoothing of AR signals disturbed by impulses and colored noise

In this paper, we describe a new and computationally efficient adaptive system for the enhancement of autoregressive (AR) signals which are disturbed by additive white or colored noise and impulsive noise. The system is comprised of an adaptive Kalman filter operating as a fixed lag smoother and a subsystem for AR parameter estimation. A superior performance is achieved by implementing a feedback loop between the Kalman filter output and the parameter estimation. Accordingly, the AR parameters are obtained from the enhanced signal and the influence of the disturbing noise on the parameter estimation is damped down. Impulsive noise is suppressed by an outlier detection scheme and by freezing the Kalman filter update during presence of impulses. The subsystem for AR parameter estimation can operate in a block processing mode or on a sample per sample basis. Another advantage of the adaptive Kalman filter is its tracking capability for short-time stationary signals.
Fast Level Set Multi-View Stereo on Graphics Hardware

In this paper, we show the importance and feasibility of much faster multi-view stereo reconstruction algorithms relying almost exclusively on graphics hardware. Reconstruction algorithms have been steadily improving in the last few years and several state-of-the-art methods are nowadays reaching a very impressive level of quality. However all these modern techniques share a very lengthy computational time that completely forbids their more widespread use in practical setups: the typical running time of such algorithms range from one to several hours. One possible solution to this problem seems to lie in the use of graphics hardware: more and more computer vision techniques are taking advantage of the availability of cheap computational horsepower and divert graphics hardware from its original purpose to accelerate the early stages of some algorithms. We present here an almost full implementation on graphics hardware of a multi-view stereo algorithm based on surface deformation by a PDE: this algorithm tries to minimize the error between input images and predicted ones by re- projection via the surface. As it mainly works on whole images, it is well suited for graphics hardware. We show how we succeeded to bring the whole reconstruction time within minutes. Results for synthetic and real data sets are presented with computational times and compared with those of other state-of-the-art algorithms.
Wearable Common Sense: Gisting Conversations with Contextual Information and Common Sense

This paper introduces a system that incorporates both contextual and commonsensical information to understand the gist of an informal, face-to-face conversation. We show that wearable devices, such as PDAs or cell phones, can provide the valuable contextual information critical for robust classification of a detailed conversation topic. 1. Motivation Once wearable computers are able to capture the gist of a user's conversation, an enormous number of potential applications become possible. However, current topicspotting methods have met with little success in characterizing spontaneous conversations involving hundreds of potential topics [3]. This paper claims that performance can be greatly improved by making use of not only the text of a transcription, but also contextual and commonsensical information from the dialogue. Why is this problem hard? Even with the latest speech recognition engines trained to a user's voice, accuracy rates for spontaneous speech recognition fall below 35%. Conversation transcripts like the one shown below are difficult even for a human to comprehend. Store going to stop and listen to type of its cellular and fries he backed a bill in the one everyone get a guess but that some of the past like a salad bar and some offense militias cambers the site fast food them and the styrofoam large chicken nuggets son is a pretty pleased even guess I as long as can’t you don’t have to wait too long its complicity sunrise against NAFTA pact if for lunch Additional context, such as information that the conversation is occurring in a cafeteria, or more precisely, waiting in line to be served, would help many people understand that the user is talking about what to get for lunch. Prior knowledge about the conversation participants and the time of day may also significantly augment a person’s ability to infer the gist of the interaction. Our work suggests that the additional contextual and commonsensical information that a human can employ for inference on the transcript above is equally helpful to a probabilistic model.
Homogenization of spectral problems in bounded domains with doubly high contrasts

Homogenization of a spectral problem in a bounded domain with a high contrast in both stiffness and density is considered. For a special critical scaling, two-scale asymptotic expansions for eigenvalues and eigenfunctions are constructed. Two-scale limit equations are derived and relate to certain non-standard self-adjoint operators. In particular they explicitly display the first two terms in the asymptotic expansion for the eigenvalues, with a surprising bound for the error of order $\varepsilon^{5/4}$ proved.