Miracle-dz/UniFAR-FTUs huggingface dataset:
Link Depth: Measuring How Far Searchers Explore Web

We focus on clarifying the unique characteristics of seeking behaviors after obtaining results from a search engine. We conducted an experimental study of Web information-seeking behaviors by comparing two different types of tasks by recording browser logs and screen capture video. The participants were 11 undergraduate and 5 graduate students. They were given two tasks: A "Report Task" in which they had to gather information to create a report on world history, and a "Trip Task," in which they had to plan for a trip. The results of analyses of the undergraduate students showed that they viewed more Web pages in the Trip Task than the Report Task. Furthermore, the results of both participant groups showed that for the Trip Task, participants tended to search deeper for pages through numerous links.
Functional Nano-Structures Using Atomic Layer Deposition

Functional Nano-Structures Using Atomic Layer Deposition Pedro M. Salgård Cunha This thesis is a study of the crossover between the fields of atomic layer deposition, block copolymer self-assembly and photovoltaics. The central research question is how the technique of atomic layer deposition (ALD) can be incorporated into the creation of nano-structured functional materials and devices, specifically in the areas of photovoltaics and biomimetics. The work aims to explore the capabilities of ALD as a strategy for overcoming two main challenges: the creation of extremely thin conformal metal oxide layers and the replication of complex high surface area templates. In these areas of fabrication on the nano-scale, ALD has consistently been shown to achieve more conformal depositions of higher quality and with greater thickness control than other thin film experimental techniques. Rather than understanding these challenges in their narrowest sense, the thesis seeks to explore the full range of possibilities inherent to the ALD process for a number of quite different applications, all of which are linked by their reliance on self-assembled templates or the creation of functional photovoltaic structures. The thesis begins by providing three background chapters. Chapter 1 covers photovoltaics, with an emphasis on liquid and solid-state electrolyte dye-sensitised solar cells. Chapter 2 is concerned with the self-assembly of microphase separating diblock copolymers and covers the special case of the gyroid morphology which is utilised extensively in the thesis. Chapter 3 describes the ALD technique. It deals with the physical and chemical underpinnings of this process, as well as its application for the coating of non-ideal substrates such as polymeric and high-aspect-ratio structures. Chapter 4 then introduces the key experimental techniques and methods utilised throughout the research. These introductory sections serve as the foundation for the four major experimental chapters of the thesis. Chapter 5 reports on the formation of gyroid-structured coreshell Cu/Cu2O/CuO solar cells via the post-deposition thermal oxidation of electrodeposited copper. Chapter 6 deals with the replication of gyroid-structured polystyrene templates using metal oxides deposited via ALD, for use in dye-sensitised solar cells. The chapter presents a novel ozone-based functionalisation scheme which overcomes the inherent difficulty of ALD nucleation on polymer surfaces. Chapter 7 covers two projects which are ongoing. One is focused on the application of ALD for the deposition of metal sulphides, and primarily describes the safety and experimental considerations for the installation of H2S as the sulphur source for this process. The other is concerned with the deposition of ultra-thin titania compact layers for dye-sensitised solar cells using ALD. Chapter 8 reports on the use of ALD in the biomimetic replication of the spectral response of the wing scales of the Papilio Blumei butterfly.
An Appropriate Boolean Query Reformulation Interface for Information Retrieval Based on Adaptive Generalization

When implementing an IR system that can support comprehensive searches from a wide variety of documents, it is crucial to have a mechanism for selecting appropriate query formulations. For this purpose, many IR systems can modify query terms by estimating the user's information need. However, because modified query terms are usually represented in a complicated form, it is difficult to judge how appropriate they are. In this research, we assume all relevant documents should contain words that correspond to concepts that the user would like to retrieve. Therefore, a Boolean query formula is one good way to represent a user's information need with high readability. To find the required concepts in a relevant document set, we have previously proposed a new IR system that calculates appropriate generalized concepts to represent the user's need. In this study, we implement a user interface that supports reformulation of IR queries by using abstract concepts
Strategy iteration algorithms for games and Markov decision processes

In this thesis, we consider the problem of solving two player infinite games, such as parity games, mean-payoff games, and discounted games, the problem of solving Markov decision processes. We study a specific type of algorithm for solving these problems that we call strategy iteration algorithms. Strategy improvement algorithms are an example of a type of algorithm that falls under this classification. We also study Lemke’s algorithm and the Cottle-Dantzig algorithm, which are classical pivoting algorithms for solving the linear complementarity problem. The reduction of Jurdzinski and Savani from discounted games to LCPs allows these algorithms to be applied to infinite games [JS08]. We show that, when they are applied to games, these algorithms can be viewed as strategy iteration algorithms. We also resolve the question of their running time on these games by providing a family of examples upon which these algorithm take exponential time. Greedy strategy improvement is a natural variation of strategy improvement, and Friedmann has recently shown an exponential lower bound for this algorithm when it is applied to infinite games [Fri09]. However, these lower bounds do not apply for Markov decision processes. We extend Friedmann’s work in order to prove an exponential lower bound for greedy strategy improvement in the MDP setting. We also study variations on strategy improvement for infinite games. We show that there are structures in these games that current strategy improvement algorithms do not take advantage of. We also show that lower bounds given by Friedmann [Fri09], and those that are based on his work [FHZ10], work because they exploit this ignorance. We use our insight to design strategy improvement algorithms that avoid poor performance caused by the structures that these examples use.
Speech applications in the eWALL project

This paper presents how technological progress may come to help smart homes development, namely smart caring-homes. It proposes two different software applications that have social, medical and psychological implications in the lives of people in need of special care as it is often the case for elders or people with physical impairments. These applications focus on processing the speech signal from inside the smart caring-homes and offering various metadata that can be used by care takers to assess a person's health state. The first application tries to count the number of people inside a room based solely on the detected speech signal, while the second application is represented by a cognitive game meant to stimulate the player's memory with a personalized test.
Vitamin D Deficiency in Children and Its Management: Review of Current Knowledge and Recommendations

Given the recent spate of reports of vitamin D deficiency, there is a need to reexamine our understanding of natural and other sources of vitamin D, as well as mechanisms whereby vitamin D synthesis and intake can be optimized. This state-of-the-art report from the Drug and Therapeutics Committee of the Lawson Wilkins Pediatric Endocrine Society was aimed to perform this task and also reviews recommendations for sun exposure and vitamin D intake and possible caveats associated with these recommendations.
Registration of multiple stained histological sections

The analysis of protein-level multigene expression signature maps computed from the fusion of differently stained immunohistochemistry images is an emerging tool in cancer management. Creating these maps requires registering sets of histological images, a challenging task due to their large size, the non-linear distortions existing between consecutive sections and to the fact that the images correspond to different histological stains and thus, may have very different appearance. In this manuscript, we present a novel segmentation-based registration algorithm that exploits a multi-class pyramid and optimizes a fuzzy class assignment specially designed for this task. Compared to a standard nonrigid registration, the proposed method achieves an improved matching on both synthetic as well as real histological images of cancer lesions.
Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery

We consider the problem of using a factor model we call {\em spike-and-slab sparse coding} (S3C) to learn features for a classification task. The S3C model resembles both the spike-and-slab RBM and sparse coding. Since exact inference in this model is intractable, we derive a structured variational inference procedure and employ a variational EM training algorithm. Prior work on approximate inference for this model has not prioritized the ability to exploit parallel architectures and scale to enormous problem sizes. We present an inference procedure appropriate for use with GPUs which allows us to dramatically increase both the training set size and the amount of latent factors. We demonstrate that this approach improves upon the supervised learning capabilities of both sparse coding and the ssRBM on the CIFAR-10 dataset. We evaluate our approach's potential for semi-supervised learning on subsets of CIFAR-10. We demonstrate state-of-the art self-taught learning performance on the STL-10 dataset and use our method to win the NIPS 2011 Workshop on Challenges In Learning Hierarchical Models' Transfer Learning Challenge.
Algorithms for Scheduling Real-Time Tasks with Input Error and End-to-End Deadlines

This paper describes algorithms for scheduling preemptive, imprecise, composite tasks in real-time. Each composite task consists of a chain of component tasks, and each component task is made up of a mandatory part and an optional part. Whenever a component task uses imprecise input, the processing times of its mandatory and optional parts may become larger. The composite tasks are scheduled by a two-level scheduler. At the high level, the composite tasks are scheduled preemptively on one processor, according to an existing algorithm for scheduling simple imprecise tasks. The low-level scheduler then distributes the time budgeted for each composite task across its component tasks so as to minimize the output error of the composite task.
The complete mitochondrial genome of the Bufo tibetanus (Anura: Bufonidae)

The total length of the Bufo tibetanus mitochondrial genome sequence is 17,405 bp. It consists of 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes and 1 displacement loop (D-loop). Except for eight tRNAs and nd6 genes, all other mitochondrial genes are encoded on the heavy strand (H strand). Most of the 22 tRNA genes can fold into a typical cloverleaf secondary structure by tRNAscan-SE, except for tRNASer. Molecular data presented here provide a useful toll for helping set the stage for further studies and the molecular evolution of the mitochondrial genome.
Comprehensive large-scale assessment of intrinsic protein disorder

MOTIVATION Intrinsically disordered regions are key for the function of numerous proteins. Due to the difficulties in experimental disorder characterization, many computational predictors have been developed with various disorder flavors. Their performance is generally measured on small sets mainly from experimentally solved structures, e.g. Protein Data Bank (PDB) chains. MobiDB has only recently started to collect disorder annotations from multiple experimental structures. RESULTS MobiDB annotates disorder for UniProt sequences, allowing us to conduct the first large-scale assessment of fast disorder predictors on 25 833 different sequences with X-ray crystallographic structures. In addition to a comprehensive ranking of predictors, this analysis produced the following interesting observations. (i) The predictors cluster according to their disorder definition, with a consensus giving more confidence. (ii) Previous assessments appear over-reliant on data annotated at the PDB chain level and performance is lower on entire UniProt sequences. (iii) Long disordered regions are harder to predict. (iv) Depending on the structural and functional types of the proteins, differences in prediction performance of up to 10% are observed. AVAILABILITY The datasets are available from Web site at URL: http://mobidb.bio. unipd.it/lsd. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
EKF-based 3D SLAM for structured environment reconstruction

This paper presents the extension and experimental validation of the widely used EKF-based SLAM algorithm to 3D space. It uses planar features extracted probabilistically from dense three-dimensional point clouds generated by a rotating 2D laser scanner. These features are represented in compliance with the symmetries and perturbation model (SPmodel) in a stochastic map. As the robot moves, this map is updated incrementally while its pose is tracked by using an extended Kalman filter. After showing how three-dimensional data can be generated, the probabilistic feature extraction method is described, capable of robustly extracting (infinite) planes from structured environments. The SLAM algorithm is then used to track a robot moving through an indoor environment and its capabilities in terms of 3D reconstruction are analyzed.
Spherically symmetric oxidation model of aluminum nanoparticles

Kinetics of oxidation of metal nanoparticles acquired practical importance with rapidly developing nanoenergetic systems and materials. Nanoenergetic thermites include mixtures of Al and metal oxides in nanoscale. Our research focuses on modeling aluminum combustion in nanoscale. The research problem is considered a spherically symmetric case and used the Cabrera Mott oxidation model to describe the kinetics of oxide growth on the aluminum nanoparticles to predict reaction temperature, thermal front velocity and oxidation time. We assumed that aluminum of radius 10 to 50 nm is covered by a thin oxide layer (1-4nm) and is surrounded by abundant amount of oxygen stored by oxidizers. The ball is rapidly heated up to ignition temperature to initiate self-sustaining oxidation reaction as a result of highly exothermic reaction. We investigated oxidation model numerically, using the COMSOL software. The software runs the finite element analysis along with the grid takes into account the geometric configuration of the body. In the oxide layer of excess concentrations of electrons and ions are dependent on the electric field potential with the corresponding of the Gibbs factors and that it conducts to the solution of a nonlinear Poisson equation for the electric field potential in a moving boundary domain.
The GridCAT: A Toolbox for Automated Analysis of Human Grid Cell Codes in fMRI

Human fMRI studies examining the putative firing of grid cells (i.e., the grid code) suggest that this cellular mechanism supports not only spatial navigation, but also more abstract cognitive processes. This research area, however, remains relatively unexplored, perhaps us to the complexities of data analysis. To overcome this, we have developed the Matlab-based Grid Code Analysis Toolbox (GridCAT), providing a graphical user interface, and open-source code, for the analysis of fMRI data. The GridCAT performs all analyses, from estimation and fitting of the grid code in the general linear model, to the generation of grid code metrics and plots. Moreover, it is flexible in allowing the specification of bespoke analysis pipelines; example data are provided to demonstrate the GridCAT’s main functionality. We believe the GridCAT is essential to opening this research area to the imaging community, and helping to elucidate the role of human grid codes in higher-order cognitive processes. Highlights The putative firing of grid cells (i.e., the grid code) can be examined using fMRI Necessary steps for grid code analysis are reviewed The Matlab-based grid code analysis toolbox (GridCAT) is introduced Automated grid code analysis can be conducted either via a graphical user interface or open-source code A detailed manual and an example dataset are provided
Frequency Analysis of Gradient Estimators in Volume Rendering

Gradient information is used in volume rendering to classify and color samples along a ray. In this paper, we present an analysis of the theoretically ideal gradient estimator and compare it to some commonly used gradient estimators. A new method is presented to calculate the gradient at arbitrary sample positions, using the derivative of the interpolation filter as the basis for the new gradient filter. As an example, we will discuss the use of the derivative of the cubic spline. Comparisons with several other methods are demonstrated. Computational efficiency can be realized since parts of the interpolation computation can be leveraged in the gradient estimation.
Wear and rim damage of UHMWPE acetabular cups in total hip replacement

Wear and fatigue of polyethylene acetabular cups have been reported to play a role in the failure of total hip replacements. Edge loading of hip replacements can occur where there is sub-optimal component positioning and/or joint laxity. Wear resistance can be improved by crosslinking but the manufacturing process of these materials involves post-irradiation thermal treatments to recombine free radicals and to stabilise the materials. Stabilisation can also be achieved by adding antioxidants. Material degradation due to oxidation and manufacturing process can result in rim cracking and/or fracture due to a reduction in mechanical properties and this has been observed in vivo. A requirement for pre-clinical hip simulator testing under edge loading conditions for all of these materials has therefore been identified. This thesis describes the development and evaluation of a hip simulator edge loading protocol using accelerated aged conventional UHMWPE acetabular liners as positive controls and commercially available crosslinked UHMWPE acetabular liners as negative controls. The edge loading protocol was then used to evaluate antioxidant stabilised liners in hip simulator tests. Explanted UHMWPE acetabular liners were evaluated for wear and damage mechanisms and compared with the damage observed on the hip simulator tested liners and new methodologies were developed to measure and analyse these explanted liners. The edge loading protocol produced cracking and subsurface damage in the aged UHMWPE liners but not in the non-aged crosslinked liners. Rim deformation was observed on all liners and the volume change produced was reduced under edge loading conditions for both types of UHMWPE liner. The antioxidant liners performed as well as the commercially available crosslinked liner in hip simulator tests and the rim deformation that was observed on explanted liners was replicated under edge loading conditions in the hip simulator tests. The edge loading protocol can be used in the future to test a range of UHMWPE materials, including aged materials, and explant analysis using the methodologies developed in this study can be used to inform the design of future simulator tests.
Games for Children with Cerebral Palsy

The objective of this study is to determine the suitability and feasibility of novel multimodal computer games utilizing Virtual Reality technology and gaming for children with Cerebral Palsy (CP). The goal of the games is to provide fun experiences and sensations to the user where he/she will become motivated to engage in physical activity, and thus, we may provide a medium for motor, speech, and memory rehabilitation. A common problem with children with CP is a reduction in motivation. Immersive Active Gaming (IAG) may allow these children to engage in physical activities despite their negative motivation and other psychological disorders such as depression. With our games we hope to not only encourage and motivate the participants to engage in physical activity but also promote equality. We can promote equality by designing and enabling games to be played by children with and without CP; utilizing appropriate interaction devices based on a child’s abilities. Sisters, brothers, parents, relative, and friends can all play the same games together with a child with CP. After all, we are all equal with our own strengths and weaknesses.
Gate quality ultrathin (2.5 nm) PECVD deposited oxynitride and nitrided oxide dielectrics

Ultrathin oxynitride using plasma assisted deposition was evaluated against thermal oxide and nitrided thermal oxide as an alternative direct tunneling gate dielectric to thermal oxide in the 2.5-nm regime. The oxynitride showed an enhanced high field effective mobility relative to the thermal oxide although the low field mobility was slightly depressed. The N/sub 2/O nitrided oxide showed an enhanced high field effective mobility with no degradation in low field mobility. The interface state density of the oxynitride was equivalent to that of the thermal and nitrided thermal oxides; a very welcome observation for this deposition chemistry and anneal conditions.
Study on Multiple Classifiers for Chinese Word Sense Disambiguation

In this paper, a new method of multiple layer classifiers integration based on single classifier is proposed which called Auto Weight Adjust. In the most used classifiers, Maximum Entropy (ME) model has excellent performance, and Naïve Bayesian (NB) is preferred by researchers for it’s simple and useful. So in our experiments we chose ME and NB as single classifiers and use the ME classifier result and the NB classifier result to fuse the final result. We use People Daily News (PDN) datasets to test our model, according to experiments our algorithm leads to less error and better performance than other algorithms. It’s outside test accurate reach to 0.88798.
Using DocBook and XML Technologies to Create Adaptive Learning Content in Technical Domains

This work presents an XML-based authoring methodology that facilitates the different tasks associated with the development of standards-compliant e-learning content development. The idea is to support a unified authoring process of adaptive e-learning content by adopting the manual writing metaphor . According to this metaphor, which is specially well-suited for technical domains, instructors are compelled to view e-learning material as the manuals normally written and used to teach a particular subject. The methodology is supported by the DocBook document model (an XML application) which has a number of tools associated that facilitate the implementation of the methodology. Other tasks such as the packaging of contents or publishing in the Learning Management System (LMS) can be automated from these manuals.