Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised learning and evaluation of KITTI's cars detector with DPM

This paper carries out a discussion on the supervised learning of a car detector built as a Discriminative Part-based Model (DPM) from images in the recently published KITTI benchmark suite as part of the object detection and orientation estimation challenge. We present a wide set of experiments and many hints on the different ways to supervise and enhance the well-known DPM on a challenging and naturalistic urban dataset as KITTI. The evaluation algorithm and metrics, the selection of a clean but representative subset of training samples and the DPM tuning are key factors to learn an object detector in a supervised fashion. We provide evidence of subtle differences in performance depending on these aspects. Besides, the generalization of the trained models to an independent dataset is validated by 5-fold cross-validation.
Vehicle Color Recognition on Urban Road by Feature Context

Vehicle information recognition is a key component of intelligent transportation systems. Color plays an important role in vehicle identification. As a vehicle has its inner structure, the main challenge of vehicle color recognition is to select the region of interest (ROI) for recognizing its dominant color. In this paper, we propose a method to implicitly select the ROI for color recognition. Preprocessing is performed to overcome the influence of image quality degradation. Then, the ROI in vehicle images is selected by assigning the subregions with different weights that are learned by a classifier trained on the vehicle images. We train the classifier by linear support vector machine for its efficiency and high precision. The experiments are extensively validated on both images and videos, which are collected on urban roads. The proposed method outperforms other competing color recognition methods.
Compatible quadrangulation by sketching

Mesh quadrangulation has received increasing attention in the past decade. While previous works have mostly focused on producing a high quality quad mesh of a single model, the connectivity of the quadrangulation is typically difficult to control and varies among models even with similar shapes. In this paper, we propose a novel interactive framework for quadrangulating a set of models collectively with compatible connectivity. Furthermore, we demonstrate its application to 3D mesh morphing. In our approach, the user interactively sketches a skeleton within each model, and our method automatically computes compatible base domains for all models from these skeletons, on which the models are parameterized. With this novel parameterization, it is very easy to generate a pleasing and smooth 3D morphing sequence among these compatible models. The method yields quadrangulation with comparable quality to existing approaches, but greatly simplifies compatible re-meshing among a group of topologically equivalent models, in particular characters and animals models, with direct applications in shape blending and morphing. Copyright © 2009 John Wiley & Sons, Ltd. In this paper, we propose a novel interactive framework for quadrangulating a set of models collectively with compatible connectivity. Furthermore, we demonstrate its application to 3D mesh morphing. In our approach, the user interactively sketches a skeleton within each model, and our method automatically computes compatible base domains for all models from these skeletons, on which the models are parameterized.
The Impact of Small-Scale Structure on Cosmological Ionization Fronts and Reionization

The propagation of cosmological ionization fronts during the reionization of the universe is strongly influenced by small-scale gas inhomogeneities due to structure formation. These inhomogeneities include both collapsed minihalos, which are generally self-shielding, and lower density structures, which are not. The minihalos are dense and sufficiently optically thick to trap intergalactic ionization fronts, blocking their path and robbing them of ionizing photons until the minihalo gas is expelled as an evaporative wind. The lower density structures do not trap these fronts, but they can slow them down by increasing the overall recombination rate in the intergalactic medium (IGM). In this paper we study the effects of both types of inhomogeneities, including nonlinear clustering effects, and we find that both IGM clumping and collapsed minihalos have significant yet qualitatively different impacts on reionization. While the number density of minihalos on average increases strongly with time, the density of minihalos inside H II regions around ionizing sources is largely constant. Thus the impact of minihalos is essentially to decrease the number of ionizing photons available to the IGM at all epochs, which is equivalent to a reduction in the luminosity of each source. On the other hand, the effect of IGM clumping increases strongly with time, slowing down reionization and extending it. Thus while the impact of minihalos is largely degenerate with the unknown source efficiency, IGM clumping can help significantly in reconciling the recent observations of cosmic microwave background polarization with quasar absorption spectra at z ~ 6, which together point to an early but extended reionization epoch.
Evaluation of Twelve Real-Time Reverse Transcriptase PCR Primer-Probe Sets for Detection of Pandemic Influenza A/H1N1 2009 Virus

ABSTRACT Real-time reverse transcriptase PCR (rRT-PCR) assays have greatly contributed to the detection, control, and prevention of the pandemic influenza A/H1N1 2009 virus. To improve the rRT-PCR assays for detection of pandemic influenza A/H1N1 2009 virus, we evaluated the sensitivity, specificity, and performance of 12 rRT-PCR primer-probe sets [SW (a) to SW (l)] using a panel of virus strains and clinical specimens. These primer-probe sets were derived from published work and designed for detecting the hemagglutinin (HA) or the neuraminidase (NA) gene of the pandemic influenza A/H1N1 2009 virus. A primer-probe set, SW (CDC), developed by the Centers for Disease Control and Prevention (U.S. CDC) to target the HA gene of pandemic influenza A/H1N1 2009 virus, was used as a referee method. Our results demonstrated that although all primer-probe sets in this study had as high as 98.4 to 100% in silico coverage, some of the primer-probe sets had better specificity, sensitivity, and amplification efficiency than others. Two primer-probe sets, SW (h) and SW (l), which target the NA gene of pandemic influenza A/H1N1 2009 virus, were highly sensitive (104 copies/reaction), had high detection rates (56/60, P = 0.134, and 59/60, P = 1.000), and showed ideal specificity compared with SW (CDC). In addition, a cocktail of primer-probe sets targeted to the HA and NA genes displayed higher detection sensitivity than primer-probe sets targeting HA or NA alone, indicating that for practical applications, a combination of primer-probes targeting HA and NA genes is the best option for the detection of pandemic influenza A/H1N1 2009 virus.
DIFFRAC: a discriminative and flexible framework for clustering

We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The large convex optimization problem is solved through a sequence of lower dimensional singular value decompositions. This framework has several attractive properties: (1) although apparently similar to K-means, it exhibits superior clustering performance than K-means, in particular in terms of robustness to noise. (2) It can be readily extended to non linear clustering if the discriminative cost function is based on positive definite kernels, and can then be seen as an alternative to spectral clustering. (3) Prior information on the partition is easily incorporated, leading to state-of-the-art performance for semi-supervised learning, for clustering or classification. We present empirical evaluations of our algorithms on synthetic and real medium-scale datasets.
Invariant Scattering Convolution Networks

A wavelet scattering network computes a translation invariant image representation, which is stable to deformations and preserves high frequency information for classification. It cascades wavelet transform convolutions with non-linear modulus and averaging operators. The first network layer outputs SIFT-type descriptors whereas the next layers provide complementary invariant information which improves classification. The mathematical analysis of wavelet scattering networks explain important properties of deep convolution networks for classification. A scattering representation of stationary processes incorporates higher order moments and can thus discriminate textures having same Fourier power spectrum. State of the art classification results are obtained for handwritten digits and texture discrimination, with a Gaussian kernel SVM and a generative PCA classifier.
Adaptive sampling of reflectance fields

Image-based relighting achieves high quality in rendering, but it requires a large number of measurements of the reflectance field. This article discusses sampling techniques that improve on the trade-offs between measurement effort and reconstruction quality. Specifically, we (i) demonstrate that sampling with point lights and from a sparse set of incoming light directions creates artifacts which can be reduced significantly by employing extended light sources for sampling, (ii) propose a sampling algorithm which incrementally chooses light directions adapted to the properties of the reflectance field being measured, thus capturing significant features faster than fixed-pattern sampling, and (iii) combine reflectance fields from two different light domain resolutions. We present an automated measurement setup for well-defined angular distributions of the incident, indirect illumination. It is based on programmable spotlights with controlled aperture that illuminate the walls around the scene.
Brain Connectivity Dissociates Responsiveness from Drug Exposure during Propofol-Induced Transitions of Consciousness

Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia.
Maximization of Non-Monotone Submodular Functions

A litany of questions from a wide variety of scientific disciplines can be cast as non-monotone submodular maximization problems. Since this class of problems includes max-cut, it is NP-hard. Thus, general purpose algorithms for the class tend to be approximation algorithms. For unconstrained problem instances, one recent innovation in this vein includes an algorithm of Buchbinder et al. (2012) that guarantees a 1⁄2 approximation to the maximum. Building on this, for problems subject to cardinality constraints, Buchbinderet al. (2014) o_er guarantees in the range [0:356; 1⁄2 + o(1)]. Earlier work has the best approximation factors for more complex constraints and settings. For constraints that can be characterized as a solvable polytope, Chekuri et al. (2011) provide guarantees. For the online secretary setting, Gupta et al. (2010) provide guarantees. In sum, the current body of work on non-monotone submodular maximization lays strong foundations. However, there remains ample room for future algorithm development. Disciplines Computer Engineering | Computer Sciences Comments MS-CIS-14-01 This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/988 Maximization of Non-Monotone Submodular Functions Jennifer Gillenwater
Separating Populations with Wide Data: A Spectral Analysis

In this paper, we consider the problem of partitioning a small data sample drawn from a mixture of k product distributions. We are interested in the case that individual features are of low average quality γ, and we want to use as few of them as possible to correctly partition the sample. We analyze a spectral technique that is able to approximately optimize the total data size--the product of number of data points n and the number of features K--needed to correctly perform this partitioning as a function of 1/γ for K > n. Our goal is motivated by an application in clustering individuals according to their population of origin using markers, when the divergence between any two of the populations is small.
Endovascular Therapy of M2 Occlusion in IMS III: Role of M2 Segment Definition and Location on Clinical and Revascularization Outcomes

The authors reviewed the impact of revascularization on clinical outcomes in 83 patients with M2 occlusions in the Interventional Management of Stroke III trial according to specific M1–M2 segment anatomic features. AnmRS 0–2 outcome was associated with reperfusion for M2 trunk (n = 9) or M2 division (n = 42) occlusions, but not for M2 branch occlusions (n = 28). Of the 83 participants with M2 occlusion who underwent endovascular therapy, 41.0% achieved mRS 0–2 at 90 days, including 46.6% with modified TICI 2–3 reperfusion compared with 26.1% with modified TICI 0–1 reperfusion. They conclude that mRS 0–2 at 90 days was dependent on reperfusion for M2 trunk but not for M2 branch occlusions in IMS III. BACKGROUND AND PURPOSE: Uncertainty persists regarding the safety and efficacy of endovascular therapy of M2 occlusions following IV tPA. We reviewed the impact of revascularization on clinical outcomes in 83 patients with M2 occlusions in the Interventional Management of Stroke III trial according to specific M1-M2 segment anatomic features. MATERIALS AND METHODS: Perfusion of any M2 branch distinguished M2-versus-M1 occlusion. Prespecified modified TICI and arterial occlusive lesion revascularization and clinical mRS 0–2 end points at 90 days for endovascular therapy–treated M2 occlusions were analyzed. Post hoc analyses of the relationship of outcomes to multiple baseline angiographic M2 and M1 subgroup characteristics were performed. RESULTS: Of 83 participants with M2 occlusion who underwent endovascular therapy, 41.0% achieved mRS 0–2 at 90 days, including 46.6% with modified TICI 2–3 reperfusion compared with 26.1% with modified TICI 0–1 reperfusion (risk difference, 20.6%; 95% CI, −1.4%–42.5%). mRS 0–2 outcome was associated with reperfusion for M2 trunk (n = 9) or M2 division (n = 42) occlusions, but not for M2 branch occlusions (n = 28). Of participants with trunk and division occlusions, 63.2% with modified TICI 2a and 42.9% with modified TICI 2b reperfusion achieved mRS 0–2 outcomes; mRS 0–2 outcomes for M2 trunk occlusions (33%) did not differ from distal (38.2%) and proximal (26.9%) M1 occlusions. CONCLUSIONS: mRS 0–2 at 90 days was dependent on reperfusion for M2 trunk but not for M2 branch occlusions. For M2 division occlusions, good outcome with modified TICI 2b reperfusion did not differ from that in modified TICI 2a. M2 segment definition and occlusion location may contribute to differences in revascularization and good outcome between Interventional Management of Stroke III and other endovascular therapy studies.
Ultrastructural study on nephrin expression in experimental puromycin aminonucleoside nephrosis.

BACKGROUND Nephrin is a recently identified protein that is a key component of the slit diaphragm. This protein may play a crucial role in maintaining the glomerular filtration barrier, and mutations in the gene for nephrin reportedly lead to congenital nephrosis. However, the expression of nephrin in acquired glomerular disease has not yet been fully clarified. To address this issue, we analysed the expression and localization of nephrin by morphological analysis based on immunoelectron microscopy in normal glomeruli and in glomeruli from proteinuric experimental models. METHODS Twenty rats were divided into three experimental groups (n = 16 total) and a control group (n = 4). Rats in the experimental groups received a single intravenous injection of puromycin aminonucleoside (PAN), and were sacrificed at 1 (n = 4), 2 (n = 6) and 3 weeks (n = 6) post-injection. Nephrin expression was assessed by immunoelectron microscopy using a polyclonal antibody against nephrin and gold particles. It was quantified by counting the gold particles and the slit diaphragms and by measuring the average foot process width in microphotographs. RESULTS The average foot process width in the 1 week group (5924.5 +/- 1523.9 nm) was far greater than that of controls (1112.9 +/- 79.8 nm), but decreased thereafter. The average number of total gold particles per unit length (10 000 nm) of the glomerular basement membrane (GBM) underlying the foot processes was reduced at 1 week (26.0 +/- 9.5), compared with controls (335.3 +/- 125.5), but increased thereafter. Also, the average number of junctional gold particles per unit length of the GBM was lower than controls (208.4 +/- 1.7) at 1 week (10.1 +/- 3.5), but increased thereafter. There were no significant differences between the numbers of junctional gold particles per slit diaphragm among the groups, but significant differences were observed in the distributions of gold particles among the groups. Gold particles were more frequently seen in cytoplasm at 1 week. CONCLUSIONS The present ultrastructural studies showed that nephrin expression and its distribution were altered in PAN-treated rats, and this occurred in parallel with foot process effacement. Nephrin expression returned to normal with improved resolution of the effacement. Nephrin expression was found to be rather preserved in areas without foot process effacement, even in PAN-treated rats. The significance of the above findings in terms of proteinuria and foot process effacement needs further clarification.
Electron Microscopy of the Suckling Mouse Cataract Agent: a Noncultivable Animal Pathogen Possibly Related to Mycoplasma

The suckling mouse cataract agent (SMCA) is a filtrable (<220 nm), noncultivable agent isolated from ticks in Georgia in 1961. It grows to high titer in the eyes and brains of intracerebrally inoculated mice in which it induces cataract, uveitis, and chronic brain infection. SMCA in high titer may also be recovered from the tissues of embryonated hen eggs in which the infection is lethal within 4 to 9 days. Fine-structural studies of ultrathin sections of pellets obtained by ultracentrifugation of SMCA-infected egg allantoic fluids have revealed pleomorphic structures with morphological characteristics typical of mycoplasma. Similar organisms have been observed in egg allantoic fluids infected with an SMCA-related tick isolate, GT-48, but not in fluids from uninoculated control eggs. Mycoplasma-like entities were also observed in high concentration within retinal tissues of rats and mice studied at the time of maximal retinitis and uveitis after SMCA inoculation. Comparable tissues from normal mouse eyes were free of microorganisms. These fine-structural observations are in agreement with those reported by other investigators and suggest that SMCA-induced pathology is associated with an agent that resembles mycoplasma in size and morphology but differs from typical mycoplasma in its apparent non-cultivability on artificial media and its resistance to inactivation by broad-spectrum antibiotics.
Plant‐facilitated effects of exotic earthworm Pontoscolex corethrurus on the soil carbon and nitrogen dynamics and soil microbial community in a subtropical field ecosystem

Abstract Earthworms and plants greatly affect belowground properties; however, their combined effects are more attractive based on the ecosystem scale in the field condition. To address this point, we manipulated earthworms (exotic endogeic species Pontoscolex corethrurus) and plants (living plants [native tree species Evodia lepta] and artificial plants) to investigate their combined effects on soil microorganisms, soil nutrients, and soil respiration in a subtropical forest. The manipulation of artificial plants aimed to simulate the physical effects of plants (e.g., shading and interception of water) such that the biological effects of plants could be evaluated separately. We found that relative to the controls, living plants but not artificial plants significantly increased the ratio of fungal to bacterial phospholipid fatty acids (PLFAs) and fungal PLFAs. Furthermore, earthworms plus living plants significantly increased the soil respiration and decreased the soil NH 4 +‐N, which indicates that the earthworm effects on the associated carbon, and nitrogen processes were greatly affected by living plants. The permutational multivariate analysis of variance results also indicated that living plants but not earthworms or artificial plants significantly changed the soil microbial community. Our results suggest that the effects of plants on soil microbes and associated soil properties in this study were largely explained by their biological rather than their physical effects.
Shared or induced obsessive compulsive disorder: Is it a reality?

Background: Shared or induced obsessive compulsive disorder (OCD) is not yet a distinct diagnosis in classification of psychiatric disorders. In fact, though recognized as a diagnostic category, shared or induced psychotic disorders are rare and most of the literature is based on the case reports. Materials and Methods: We are reporting three case studies manifested with shared or induced OCD (cases with obsessive symptoms that were shared from the primary case in their family). Results: All the cases were treated considering shared or induced OCD as psychopathology. Response to treatment modalities in first and second case and poor response to treatment in third case is suggestive of shared or induced OCD as a distinct entity. It is different from shared psychosis in many ways. Conclusion: Shared or induced OCD is a distinct diagnosis. Greater awareness about this entity among mental health professionals is needed.
Impact of Aviation Highway-in-the-Sky Displays on Pilot Situation Awareness

Thirty-six pilots (31 men, 5 women) were tested in a flight simulator on their ability to intercept a pathway depicted on a highway-in-the-sky (HITS) display. While intercepting and flying the pathway, pilots were required to watch for traffic outside the cockpit. Additionally, pilots were tested on their awareness of speed, altitude, and heading during the flight. Results indicated that the presence of a flight guidance cue significantly improved flight path awareness while intercepting the pathway, but significant practice effects suggest that a guidance cue might be unnecessary if pilots are given proper training. The amount of time spent looking outside the cockpit while using the HITS display was significantly less than when using conventional aircraft instruments. Additionally, awareness of flight information present on the HITS display was poor. Actual or potential applications of this research include guidance for the development of perspective flight display standards and as a basis for flight training requirements.