Miracle-dz/UniFAR-FTUs huggingface dataset:
A semiautomatic method for pedestrian ground truth generation in thermal infrared on-board videos

Currently, pedestrian detection and tracking algorithms of Thermal Infrared (TIR) on-board videos encounter lack of comprehensive pedestrian datasets for benchmarking. The generation of ground truth is a tedious and error-prone task in the process of creating the dataset of annotated videos. This paper puts forward a novel semiautomatic video annotation method to facilitate annotating pedestrians in TIR on-board videos. The proposed method consists of two phases. In the first phase we learn the pedestrian appearance models online, then in the second phase we use the learned models to automatically annotate the pedestrian in the other frames. We present a video annotation tool to verify the effectiveness and reliability of our method. A comparison between our tool and the state of the art of onboard video annotating tools was performed, which showed how our annotation tool provides a high ground truth quality with shorter annotation time when annotating pedestrians in TIR on-board videos with bounding boxes.
Probabilistic Active Learning: A Short Proposition

Active Mining of Big Data requires fast approaches that ideally select for a user-specified performance measure and arbitrary classifier the optimal instance for improving the classification performance. Existing generic approaches are either slow, like error reduction, or heuristics, like uncertainty sampling. We propose a novel, fast yet versatile approach that directly optimises any user-specified performance measure: Probabilistic Active Learning (PAL). PAL follows a smoothness assumption and models for a candidate instance both the true posterior in its neighbourhood and its label as random variables. By computing for each candidate its expected gain in classification performance over both variables, PAL selects the candidate for labelling that is optimal in expectation. PAL shows comparable or better classification performance than error reduction and uncertainty sampling, has the same asymptotic linear time complexity as uncertainty sampling, and is faster than error reduction.
Investigation of self-monitoring in fluent aphasia with jargon

Background: Some individuals with fluent aphasia produce jargon errors in speech production. Jargon likely results from derailed encoding operations required for language production, although the exact mechanism remains debated. It is also unclear if persons who produce jargon are able to self-monitor; that is, detect the non-word status of their imminent utterance and self-correct the error. Aims: This study investigated the characteristics of speech monitoring in individuals with fluent aphasia who produce jargon. The association of speech monitoring with amount of jargon produced and success in auditory comprehension was examined. Further, the role of post-articulatory auditory feedback on speech-monitoring success was examined by introducing an auditory masker (white noise). Finally, the influence of task demands on amount of jargon and speech monitoring was examined. Methods & Procedures: Five individuals with fluent aphasia with jargon participated in the study. Speech monitoring was tested using three production tasks (picture naming, non-word repetition, and word repetition) under two listening conditions (normal listening and masking noise). Speech-monitoring score was derived from self-judgements of production accuracy. Auditory processing was examined in speech discrimination, lexical decision, and single-word identification tasks. Outcomes & Results: Results indicated that severity of self-monitoring impairment is: (1) strongly correlated with severity of jargon production, (2) poorly correlated with auditory processing abilities, (3) worse under masking noise, and (4) worse for naming compared to repetition. Conclusions: Overall, all five participants with jargon demonstrated severely impaired speech monitoring under both listening conditions across all three production tasks, suggesting that the role of speech-monitoring impairment in jargon cannot be disregarded. The increase in amount of jargon and severity of speech-monitoring failure with increased linguistic demands of the production task (as in picture naming and non-word repetition) raises the possibility of a post-semantic deficit in accessing phonological codes. This possible locus of deficit, and implications for understanding production of jargon, are discussed.
Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images

A model-based algorithm, termed exclusion region and position refinement (ERPR), is presented for improving the accuracy and repeatability of estimating the locations where vascular structures branch and cross over, in the context of human retinal images. The goal is two fold. First, accurate morphometry of branching and crossover points (landmarks) in neuronal/vascular structure is important to several areas of biology and medicine. Second, these points are valuable as landmarks for image registration, so improved accuracy and repeatability in estimating their locations and signatures leads to more reliable image registration for applications such as change detection and mosaicing. The ERPR algorithm is shown to reduce the median location error from 2.04 pixels down to 1.1 pixels, while improving the median spread (a measure of repeatability) from 2.09 pixels down to 1.05 pixels. Errors in estimating vessel orientations were similarly reduced from 7.2/spl deg/ down to 3.8/spl deg/.
15 Years of Application of Statistical Physics Methods to the Study of Software Systems

Despite the fact that software development is a design optimization process with nothing random, large software systems exhibit statistical properties that can be studied with the approach of statistical physics. In this keynote talk, I shall recall the history of the application of statistical physics methods to the study of software systems, since its inception at the beginning of 2000.
Interfacing with Proof Assistants for Domain Specific Programming Using EventML

This paper presents a paradigm for using proof assistants in the programming process. We demonstrate how the programming language EventML provides a useful interface to proof assistants throughout code development. Enhancing the use of proof assistants in programming will make them more valuable and accessible to a large community. We designed EventML specifically to cooperate with proof assistants at every stage of program creation. It will help programmers ensure correctness, document the code, and support modifications and improvements. Cooperation is especially effective when the proof assistant and the programming language share the same type system and when the proof assistant can generate executable code for the programming language, as is natural for proof assistants using constructive type theories.
Intramural spatial variation of optical tissue properties measured with fluorescence microsphere images of porcine cardiac tissue

This proceeding studies the optical fluorescence images of a porcine heart filled with microspheres of two colors, carmine and red. A significant difference in the total optical tissue attenuation coefficient was observed between excitation and emission for both carmine (excitation – 13±4(1/mm) and emission – 9.4±3(1/mm)) and red (excitation -29±5(1/mm) and emission – 25±5(1/mm)), indicating that optical tissue properties can change significantly for a small change in light wavelength. The above-mentioned large ranges of variation observed in the tissue attenuation coefficient for excitation and emission (both for carmine and red) suggest significant intramural variation of optical properties across the entire organ. Patterns of global spatial variation in optical attenuation properties in tissue across the entire organ were observed. A novel method using fluorescence microsphere images is presented for measurement of the tissue attenuation’s intramural variation across an entire organ.
The Secreted Wnt Antagonist Dickkopf-1 Is Required for Amyloid β-Mediated Synaptic Loss

Extensive evidence supports a central role for amyloid-β (Aβ) in the pathogenesis of Alzheimer's disease (AD). Synaptic loss mediated by Aβ in early stages of the disease might contribute to cognitive impairments. However, little is known about the mechanism by which Aβ induces the loss of synapses. The expression of the Wnt antagonist Dickkopf-1 (Dkk1) is increased in brains of AD patients and in AD transgenic mouse models, suggesting that dysfunction of Wnt signaling could contribute to AD pathology. Here we report that acute exposure to Aβ oligomers induces Dkk1 expression together with the loss of synaptic sites. Importantly, Dkk1-neutralizing antibodies suppress Aβ-induced synapse loss in mouse brain slices. In mature rat hippocampal neurons, Dkk1 decreases the number of synapses without affecting cell viability. Ultrastructural analyses revealed that Wnt blockade decreases the size of presynaptic and postsynaptic terminals. Time-lapse recordings of RFP-labeled stable synaptic sites demonstrate that Dkk1 induces the dispersal of synaptic components. These findings identify Dkk1 as a potential therapeutic target for the treatment of AD.
Tied posteriors: an approach for effective introduction of context dependency in hybrid NN/HMM LVCSR

This paper presents a method to improve the recognition rate of hybrid connectionist/HMM speech recognition systems. At the same time this approach allows the easy introduction of context dependent models in the hybrid framework. The approach is based on a standard hybrid connectionist/HMM recognizer, in which the neural nets are trained to estimate the a posteriori probabilities for all phones in each input frame. In the approach presented here, the probabilities of the neural nets are used to replace the codebook of a tied-mixture HMM system. Therefore the resulting system is called tied posterior. The advantages of this structure are that an arbitrary HMM-topology can be used, and that all context dependency and all clustering techniques used in tied-mixture systems can be applied to this hybrid speech recognition system. The approach has been evaluated on the Wall Street Journal (WSJ) database, with the result, that it outperforms the standard hybrid approach on this task.
Classes of LDPC codes constructed from elements of finite fields and cyclotomic cosets

In this paper, we derive two algebraic methods for constructing regular low density parity check (LDPC) codes - one based on elements of finite fields and the other directly based on cyclotomic cosets. We show that the constructed codes have high rates and are free of cycles of length four; consequently, they can be decoded using standard iterative decoding algorithms. In addition we compute the exact dimension and establish bounds on the minimum and stopping distances of the constructed codes.
Transcription Factor AP-2 Regulates Human Insulin-like Growth Factor Binding Protein-5 Gene Expression (*)

Insulin-like growth factor binding protein-5 (IGFBP-5) is an important modulator of IGF actions. IGFBP-5 mRNA is abundant in human fibroblasts and is regulated by cAMP. To understand the molecular mechanism underlying this cell type-specific expression and regulation, we isolated the 5′-flanking region of the human IGFBP-5 gene and fused it to a promoter-less reporter plasmid encoding luciferase. Transient transfection of the construct into fibroblasts displayed both constitutive and cAMP-induced promoter activity in an orientation-specific manner. Sequence analysis revealed the existence of distal and proximal consensus AP-2 recognition sites located 5′ from the TATA box. Both sequences bound specifically to human AP-2 in vitro by gel shift mobility assay. The possible role of AP-2 was examined by cotransfection of AP-2-deficient HepG2 cells with the IGFBP-5 promoter construct and a human AP-2 expression construct. Cotransfection with AP-2 significantly elevated IGFBP-5 promoter activity. This trans-activation was IGFBP-5 promoter and AP-2 specific. In AP-2 abundant fibroblasts, expression of AP-2B, a dominant-negative inhibitor of AP-2, suppressed IGFBP-5 promoter activity. In HepG2 cells, AP-2B alone had no significant effect, but the AP-2-induced activation of promoter activity was inhibited by AP-2B in a dose-dependent manner. The relative functional importance of the putative AP-2 binding sites was examined using a number of deletion mutants and point mutations. When the first two distal CCCCACCC-like putative AP-2 sites were deleted or mutated, there was no change in AP-2-induced trans-activation. Deletion or mutation of the proximal GCCNNNGGC-like sequences, however, abolished the AP-2-induced activation. These results suggest that AP-2 regulates the IGFBP-5 gene expression through the proximal GCCNNNGGC-like sequences. This AP-2-mediated trans-activation contributes at least in part to the constitutively high expression of IGFBP-5 in fibroblasts and to the cAMP responsiveness of this gene.
APPLICATION OF SELECTED AGENTS FOR WOOD LIQUEFACTION AND SOME PROPERTIES OF PARTICLEBOARDS PRODUCED WITH THE USE OF LIQUEFIED WOOD

This work presents the characteristics of wood liquefied using different types of solvents in terms of its application for binding particleboards. Standard pine particles from barked wood were used for the liquefaction experiments. The liquefaction reaction was carried out in high temperature conditions using a mixture of solvents from the polyhydroxy alcohol group, including glycerine, ethylene glycol, propylene glycol, diethylene glycol, and dipropylene glycol. The microstructure of both the liquefied wood and the liquefaction residues was determined by means of optical microscopy analysis. The basic parameters of the adhesive mixture modified with the liquefied wood, such as viscosity, pH and gel time were determined. Particleboards containing liquefied wood were produced. The following physicochemical and mechanical properties of the particleboards were measured: tensile strength, bending strength, modulus of elasticity, and formaldehyde content . The influence of the liquefying agent on the board properties was investigated. In all the tests, a control particleboard, bonded with a urea-formaldehyde adhesive resin with no inclusion of liquefied wood, was used for the purposes of comparison.
Community based approach for generating building layouts

In this paper we propose the design and evaluation of an algorithm capable of inferring basic floor plans from motion paths generated from smartphone sensors. First we shortly discuss the applicability of modern smartphones equipped with various sensors to create motion paths through premises. Some dead reckoning approaches which are used to track and calculate the position of devices are mentioned. After that we present an algorithm which shall use motion paths for the creation of maps holding probabilistic information regarding the accessibility of specific areas within a confined structure such as a building. The algorithm thus differs from traditional SLAM and mapping approaches in that it explicitly focuses on map generation and path interpretation and does not implement any sort of sensor-specific processing. In the concluding evaluation it is shown that the presented algorithm while still prone to certain types of bad input data can calculate free space from the motion paths with a sufficient accuracy for basic mapping tasks, especially if more input samples are used. Finally, various possible improvements are discussed which may improve the algorithms processing quality and robustness.
A multi-relational approach to spatial classification

Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their features. Spatial data can be represented as multi-relational data, however it presents novel challenges not present in multi-relational problems. One such problem is that spatial relationships are embedded in space, unknown a priori, and it is part of the algorithm's task to determine which relationships are important and what properties to consider. In order to determine when two entities are spatially related in an adaptive and non-parametric way, we propose a Voronoi-based neighbourhood definition upon which spatial literals can be built. Properties of these neighbourhoods also need to be described and used for classification purposes. Non-spatial aggregation literals already exist within the multi-relational framework, but are not sufficient for comprehensive spatial classification. A formal set of additions to the multi-relational data mining framework is proposed, to be able to represent spatial aggregations as well as spatial features and literals. These additions allow for capturing more complex interactions and spatial occurrences such as spatial trends. In order to more efficiently perform the rule learning and exploit powerful multi-processor machines, a scalable parallelized method capable of reducing the runtime by several factors is presented. The method is compared against existing methods by experimental evaluation on a real world crime dataset which demonstrate the importance of the neighbourhood definition and the advantages of parallelization.
Propagation loss in slow light photonic crystal waveguides

The field of nanophotonics is a major research topic, as it offers potential solutions to important challenges, such as the creation of low power, high bandwidth interconnects or optical sensors. Within this field, resonant structures and slow light waveguides are used to improve device performance further. Photonic crystals are of particular interest, as they allow the fabrication of a wide variety of structures, including high Q-factor cavities and slow light waveguides. The high scattering loss of photonic crystal waveguides, caused by fabrication disorder, however, has so far proven to be the limiting factor for device applications. In this thesis, I present a detailed study of propagation loss in slow light photonic crystal waveguides. I examine the dependence of propagation loss on the group index, and on disorder, in more depth than previous work by other authors. I present a detailed study of the relative importance of different components of the propagation loss, as well as a calculation method for the average device properties. A new calculation method is introduced to study different device designs and to show that photonic crystal waveguide propagation loss can be reduced by device design alone. These “loss engineered” waveguides have been used to demonstrate the lowest loss photonic crystal based delay line (35 dB/ns) with further improvements being predicted (< 20 dB/ns). Novel fabrication techniques were investigated, with the aim of reducing fabrication disorder. Initial results showed the feasibility of a silicon anneal in a nitrogen atmosphere, however poor process control led to repeatability issues. The use of a slow-fast-slow light interface allowed for the fabrication of waveguides spanning multiple writefields of the electron-beam lithography tool, overcoming the problem of stitching errors. The slow-fast-slow light interfaces were combined with loss engineering waveguide designs, to achieve an order of magnitude reduction in the propagation loss compared to a W1 waveguide, with values as low as 130 dB/cm being achieved for a group index around 60.
Under the Microscope: A Brief History of Microscopy

This is a brief history of the development of microscopy, from the use of beads and water droplets in ancient Greece, through the simple magnifying glass, to the modern compound microscope. The technology and optical theory are developed in a straightforward manner, and this leads to a description and explanation of the most modern technologies in electron microscopy, and scanning electron microscopy as well as the new scanning probe microscopies. A series of very interesting applications of the various microscopic techniques are described. The most recent pioneering techniques in near field and confocal optical microscope technologies are described and evaluated for their future importance.
Feature extraction and selection hybrid algorithm for hyperspectral imagery classification

Due to the enormous amounts of data contained in hyperspectral imagery, the main challenge for hyperspectral image classification is to improve the accuracy with less computation complexity. Hence, dimensionality reduction (DR) is often adopted, which includes two different kinds of methods, feature extraction and feature selection. In this paper, discrete wavelet transform (DWT) and affinity propagation (AP), which belong to feature extraction and feature selection respectively, are combined together to accomplish the DR task. Firstly, DWT-based features are extracted from the original hyperspectral data; secondly, AP is applied to select representative features from the obtained ones. Experimental results demonstrate that, compared with some other DR methods which only make use of feature extraction or feature selection, the features acquired by the hybrid technique make the classification results more accurate.
Effect of Compression on the Effective Thermal Conductivity and Thermal Contact Resistance in PEM Fuel Cell Gas Diffusion Layers

Heat transfer through the gas diffusion layer (GDL) of a PEM fuel cell is a key process in the design and operation a PEM fuel cell. The analysis of this process requires determination of the effective thermal conductivity as well as the thermal contact resistance between the GDL and adjacent surfaces/layers. In the present study, a guarded-hot-plate apparatus has been designed and built to measure the effective thermal conductivity and thermal contact resistance in GDLs under vacuum and atmospheric pressure. Toray carbon papers with the porosity of 78% and different thicknesses are used in the experiments under a wide range of compressive loads. Moreover, novel analytical models are developed for the effective thermal conductivity and thermal contact resistance and compared against the present experimental data. Results show good agreements between the experimental data and the analytical models. It is observed that the thermal contact resistance is the dominant component of the total thermal resistance and neglecting this phenomenon may result in enormous errors.Copyright © 2010 by ASME
Functional characterization of MT3‐MMP in transfected MDCK cells: progelatinase A activation and tubulogenesis in 3‐D collagen lattice

MT3‐MMP, a membrane‐anchored matrix metalloproteinase, has been proposed to participate in the remodeling of extracellular matrix either by direct proteolysis or via activating other enzymes such as progelatinase A. To test this hypothesis, we analyzed the effect of exogenously transfected MT3‐MMP in a tissue remodeling system: growth and tubulogenesis of Madin‐Darby canine kidney (MDCK) cells in collagen gels. Although the parental cells require MMP activities for both growth and tubulogenesis, over‐expression of wild‐type MT3‐MMP, but not its catalytically inactive mutant, leads to further enhancement of both processes, independent of its downstream substrate, progelatinase A. Mechanistically, MT3‐MMP accomplishes such an effect by displaying on cell surfaces as active species, ready to activate progelatinase A or degrade ECM molecules. These data strongly suggest that MT3‐MMP possesses the potential to directly enhance the growth and invasiveness of cells in vivo, two critical processes for development and carcinogenesis. —Kang, T. , Yi, J., Yang, W. , Wang, X. , Jiang, A. , and Pei D. Functional characterization of MT3‐MMP in transfected MDCK cells: progelatinase A activation and tubulogenesis in 3‐D collagen lattice. FASEB J. 14, 2559–2568 (2000)