Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel decompression of seismic data on GPU using a lifting wavelet algorithm

Subsurface images are widely used by the oil companies to find oil reservoirs. The construction of these images involves to collect and process a huge amount of seismic data. Generally, the oil companies use compression algorithms to reduce the storage and transmission costs. Currently, the compression process is developed on-site using CPU architectures, whereas the construction of the subsurface images is developed on GPU clusters. For this reason, the decompression process has to be developed on GPU architectures. So, fast and parallel decompression algorithms are required to be implemented on GPUs. We implemented an algorithm that performs the decompression of seismic traces on GPU. The algorithm is based on a 2D Lifting Wavelet Transform. The decompression algorithm was developed in CUDA 6.5 and implemented into a GeForce GTX660 GPU. This algorithm was tested using different data sets supplied by an oil company. Experimental results allowed us to establish how the compression ratio affects the performance of our algorithm. Additionally, we also show how the number of threads per block affects this performance.
Towards a statistical grammar of usage for document retrieval in digital libraries

Due to the huge amount of available information via Internet, the identification of reliable and interesting items becomes more and more difficult and time consuming. The way we propose to cope with this difficulty consists in integrating a grammar of usage. We decide to ignore the nature, the content and the structure of resources. This paper is a position paper describing our intended work in the framework of multimedia information retrieval by browsing techniques within digital libraries. It relies on a usage-based indexing of resources. We describe a new approach taking advantage of the similarity between statistical modeling of language and document retrieval systems. We build syntax of usages and design a statistical grammar of usage (SGU) that allows resources classification to design personalized filtering.
Extracting Semantic Meaning from Photographic Annotations using a Hybrid Approach

This paper evaluates singular then hybrid methodologies for extracting semantics relevant to users in cataloguing and searching of personal photographs. It concentrates upon extraction of meaningful concepts within textual annotations focusing around geographical identification, together with references to people and objects concerning each image. A number of approaches are considered; machine learning, rule based and a novel hybrid approach encompassing previous techniques. This evaluation identifies the strengths of the singular approaches and defines rules best suited to differing extractions providing a higher performing hybrid method.
An Information and Communications Technology (ICT)-Enabled Method for Collecting and Collating Information about Pre-Service Teachers' Pedagogical Beliefs regarding the Integration of ICT.

This paper describes a method that utilized technology to collect and collate quantitative and qualitative data about pre-service teachers’ use of networked technologies during a 12-week undergraduate course, and the impact of this use on their pedagogical beliefs regarding the integration of information and communications technology (ICT). The technologies used captured and analysed students’ spoken and written communication while engaging in four synchronous online tasks, and also collected evaluation data from online interviews, surveys and diaries. The richness of data afforded by this ICT-enabled method enabled the research to produce a rich narrative of how the students used the technology and provided evidence of a change in pre-service teachers’ pedagogical beliefs during the course.
ATP-Dependent Chromatin Remodeling by the Cockayne Syndrome B DNA Repair-Transcription-Coupling Factor

ABSTRACT The Cockayne syndrome B protein (CSB) is required for coupling DNA excision repair to transcription in a process known as transcription-coupled repair (TCR). Cockayne syndrome patients show UV sensitivity and severe neurodevelopmental abnormalities. CSB is a DNA-dependent ATPase of the SWI2/SNF2 family. SWI2/SNF2-like proteins are implicated in chromatin remodeling during transcription. Since chromatin structure also affects DNA repair efficiency, chromatin remodeling activities within repair are expected. Here we used purified recombinant CSB protein to investigate whether it can remodel chromatin in vitro. We show that binding of CSB to DNA results in an alteration of the DNA double-helix conformation. In addition, we find that CSB is able to remodel chromatin structure at the expense of ATP hydrolysis. Specifically, CSB can alter DNase I accessibility to reconstituted mononucleosome cores and disarrange an array of nucleosomes regularly spaced on plasmid DNA. In addition, we show that CSB interacts not only with double-stranded DNA but also directly with core histones. Finally, intact histone tails play an important role in CSB remodeling. CSB is the first repair protein found to play a direct role in modulating nucleosome structure. The relevance of this finding to the interplay between transcription and repair is discussed.
Phase-Based UHF RFID Tracking With Nonlinear Kalman Filtering and Smoothing

In this paper, we present an UHF RFID location tracking system, which is based on measuring the phases of back scattered signals from RFID tag using multiple spatially distributed antennas at a single carrier frequency. The wavelength ambiguity of the phase measurements is resolved by using the extended Kalman filter (EKF) and the Rauch-Tung-Striebel (RTS) smoother, where the state includes the position, velocity and the phase offsets of antennas. The performance of the method is experimentally verified at 890 MHz using a commercially available RFID reader.
Colour preference, naturalness, vividness and colour quality metrics, Part 3: Experiments with makeup products and analysis of the complete warm white dataset

Light source colour quality is a complex phenomenon with several visual and cognitive components. Subjective colour preference, naturalness and vividness assessments of reddish cosmetic products in a viewing booth lit by light sources with a correlated colour temperature of 3200 K and to 550 lx were analysed and modelled by a new combined colour quality formula – a linear combination of a colour fidelity index and a measure of chroma change. Results of the warm white light sources described in all three parts of this work were merged. They were modelled by optimising the parameters of the same formula. The formula supports multi-LED light sources with moderately accentuated local spectral maxima to enhance object chroma over a moderate range.
Modified AODV Routing in Multi-Lane Changing Models in VANET

Vehicular Ad-hoc Network (VANET) is emerging as a standard routing protocol as a countermeasure for r apidly changing topology and high mobility of vehicles. An adhoc routing protocol could play a crucial role in V ANET applications, safeguarding both drivers and passeng ers. When dealing with vehicular mobility modeling, we distinguish between macro-mobility and micro-mobili ty. This paper proposes modification in AODV for the la ne changing models and their analysis so that the prop osed roadmap gives large impact on generation of traffic .
Efficient Gene Knockdown in Mouse Oocytes through Peptide Nanoparticle-Mediated SiRNA Transfection

The use of mouse oocytes as a model for studying female meiosis is very important in reproductive medicine. Gene knockdown by specific small interfering RNA (siRNA) is usually the first step in the study of the function of a target gene in mouse oocytes during in vitro maturation. Traditionally, the only way to introduce siRNA into mouse oocytes is through microinjection, which is certainly less efficient and strenuous than siRNA transfection in somatic cells. Recently, in research using somatic cells, peptide nanoparticle-mediated siRNA transfection has been gaining popularity over liposome nanoparticle-mediated methods because of its high efficiency, low toxicity, good stability, and strong serum compatibility. However, no researchers have yet tried transfecting siRNA into mouse oocytes because of the existence of the protective zona pellucida surrounding the oocyte membrane (vitelline membrane). We therefore tested whether peptide nanoparticles can introduce siRNA into mouse oocytes. In the present study, we showed for the first time that our optimized program can efficiently knock down a target gene with high specificity. Furthermore, we achieved the expected meiotic phenotypes after we knocked down a test unknown target gene TRIM75. We propose that peptide nanoparticles may be superior for preliminary functional studies of unknown genes in mouse oocytes.
Ab initio investigation of molecular hydrogen physisorption on graphene and carbon nanotubes

Density-functional theory is used to investigate hydrogen physisorption on a graphene layer and on single wall carbon nanotubes. Both external and internal adsorption sites of (9, 0) and (10, 0) carbon nanotubes have been studied with the hydrogen molecular axis oriented parallel or perpendicular to the nanotube wall. A range of hydrogen molecule binding sites has been examined and it is found that hydrogen binds weakly to each of the graphitic structures and at all adsorption sites examined. Calculations using different functionals reveal that the binding energies are a factor of 2 larger for hydrogen bound inside the nanotubes than for adsorption outside the nanotubes or on the graphene layer. Furthermore, configurations of the hydrogen molecular axis parallel to the nanotube wall or graphene layer bind more effectively than configurations where the axis is normal to the carbon nanostructures. The differing behavior between the carbon nanostructures is attributed to the curvature of the structure and the hydrogen-carbon electron interactions, where analysis of the electron density reveals evidence of charge redistribution with little charge transfer. The potential of hydrogen physisorption to carbon nanostructures for hydrogen storage and delivery is also discussed.
Markov Random Field for Image Concept Detection

Recent years have witnessed phenomenal growth in the number of internet multimedia documents, such as un-annotated scene images. Image concept detection is an important step for image query. In this paper, we tackle the problem of image concept detection, namely automatically detecting concepts in an un-annotated image. In fact, a scene image always contains multiple concepts. In order to detect all concepts in an image, traditional approaches only leverage single-concept detectors to detect them one by one, which may be ineffective in some cases. For example, the visual appearance described by a scene image consisting of a few concepts (e.g. "lion, grassland, Africa") may be difficult to distinguish solely by single-concept detectors. We propose a novel Markov random field for Image Concept Detection (MICD) model, which considers modeling the link of single-concept detectors and multi-concept detectors to enhance the precision of image concept detection. Single-concept detector can recognize single concept in an image, while multi-concept detector can effectively distinguish the multi-concept scene. Their fusion can lead to the improvement of detection precision. Additionally, the interdependencies between concepts are utilized to improve detection precision. In order to investigate the feasibility and effectiveness of our model, we conduct experiments on Corel and NUS-Wide collection. The experimental results demonstrate the effectiveness of our proposed approach.
Combining Multiple Classifiers for Automatic Text Categorization

In this paper we study the development of multiple classifier systems in the Chinese text categorization. Our objective is to develop efficient techniques to combine the strength of well-known classifiers such as linear classifiers, decision trees, Bayesian methods, neural networks, and support vector machines. We have experimented with Chinese documents from the Central News Agency and from the Web Openfind. Experiments show that our approaches significantly improve the classification accuracy of individual classifiers for Chinese text categorization as well as for web page classification.
Rate-controlled scheduling for networked multimedia applications

Multimedia applications over the Internet are becoming increasingly popular. The soft real-time constraints of this type of application have given rise to interesting issues for scheduling in the network as well as the end systems. The paper presents a rate-based task scheduling framework for the receiving hosts. As multimedia streams are expected to be played back at constant rate, the proposed scheme tries to maintain the specified output frame rate by assigning proper deadlines to the frames. A multimedia stream that falls behind can catch up by skipping some frames. Interference among tasks is prevented using rate-controlled servers (RCS). The performance of these schemes has been analyzed mathematically and evaluated by simulations.
Process mining of test processes : a case study

Process mining techniques attempt to extract non-trivial and useful information from event logs. For example, there are many process mining techniques to automatically discover a process model describing the causal dependencies between activities. Moreover, using conformance checking it is possible to investigate and quantify deviations between the real process and the modeled process. Several successful case studies have been reported in literature, all demonstrating the applicability of process mining. However, these case studies refer to rather structured administrative processes. In this paper, we investigate the applicability of process mining to less structured processes. We report on a case study where the ProM framework has been applied to the test processes of ASML (the leading manufacturer of wafer scanners in the world). This case study provides many interesting insights. On the one hand, process mining is also applicable to the less structured processes of ASML. On the other hand, the case study also shows the need for alternative mining approaches able to better visualize processes and provide more insights.
Enhanced peak picking for onset detection with recurrent neural networks

We present a new neural network based peak-picking algo- rithm for common onset detection functions. Compared to existing hand- crafted methods it yields a better performance and leads to a much lower number of false negative detections. The performance is evaluated on basis of a huge dataset with over 25k annotated onsets and shows a signicant improvement over existing methods in cases of signals with previously unknown levels.
Non-linear interferometric vibrational imaging

Coherent anti-Stokes Raman scattering (CARS) processes are "coherent," but the phase of the anti-Stokes radiation is lost by most incoherent spectroscopic CARS measurements. We propose a Raman microscopy imaging method called nonlinear interferometric vibrational imaging, which measures Raman spectra by obtaining the temporal anti-Stokes signal through nonlinear interferometry. With a more complete knowledge of the anti-Stokes signal, we show through simulations that a high-resolution Raman spectrum can be obtained of a molecule in a single pulse using broad band radiation. This could be useful for identifying the three-dimensional spatial distribution of molecular species in tissue.
Patterns in Datatype-generic Programming

Generic programming consists of increasing the expressive-ness of programs by allowing a wider variety of kinds of parameter than is usual. The most popular instance of this scheme is the C++ Standard Template Library. Datatype-generic programming is another instance, in which the parameters take the form of datatypes. We argue that datatype-generic programming is sufficient to express essentially all the genericity found in the Standard Template Library, and to capture the abstractions motivating many design patterns. Moreover, datatype-generic programming is a precisely-defined notion with a rigorous mathematical foundation, in contrast to generic programming in general and the C++ template mechanism in particular, and thereby offers the prospect of better static checking and a greater ability to reason about generic programs. This paper describes work in progress.
Foveal shape and structure in a normal population.

PURPOSE The shape of the human fovea presents important but still poorly characterized variations. In this study, the variability of the shape and structure of normal foveae were examined. METHODS In a group of 110 eyes of 57 healthy adults, the shape and structure of the fovea were analyzed by automated segmentation of retinal layer on high-resolution optical coherence tomography scans. In an additional group of 10 normal eyes of 10 patients undergoing fluorescein angiography, the size of the foveal avascular zone (FAZ) was correlated to foveal shape. RESULTS From the thickest to the thinnest fovea, there was a structural continuum ranging from a shallow pit with continuity of the inner nuclear layer (INL) over the center (seven eyes; 6.7%), to a complete separation of inner layers overlying a flat and thinner central outer nuclear layer (ONL; eight eyes; 7.3%). Central foveal thickness correlated inversely to the degree of inner layer separation and to the surface of the FAZ. CONCLUSIONS Foveal structure strongly correlates with its neurovascular organization. The findings support a developmental model in which the size of the FAZ determines the extent of centrifugal migration of inner retinal layers, which counteracts in some way the centripetal packing of cone photoreceptors.
Molecular docking studies of Traditional Chinese Medicinal compounds against known protein targets to treat non-small cell lung carcinomas

In silico drug design using virtual screening, absorption, distribution, metabolism and excretion (ADME)/Tox data analysis, automated docking and molecular dynamics simulations for the determination of lead compounds for further in vitro analysis is a cost effective strategy. The present study used this strategy to discover novel lead compounds from an in-house database of Traditional Chinese Medicinal (TCM) compounds against epithelial growth factor receptor (EGFR) protein for targeting non-small cell lung cancer (NSCLC). After virtual screening of an initial dataset of 2,242 TCM compounds, leads were identified based on binding energy and ADME/Tox data and subjected to automated docking followed by molecular dynamics simulation. Triptolide, a top compound identified by this vigorous in silico screening, was then tested in vitro on the H2347 cell line carrying wild-type EGFR, revealing an anti-proliferative potency similar to that of known drugs against NSCLC.
Pluronic P105/F127 mixed micelles for the delivery of docetaxel against Taxol-resistant non-small cell lung cancer: optimization and in vitro, in vivo evaluation

The aim of this work was to establish a novel polymeric mixed micelle composed of Pluronic P105 and F127 copolymers loaded with the poorly soluble antitumor drug docetaxel (DTX) against Taxol-resistant non-small cell lung cancer. A central composite design was utilized to optimize the preparation process, helping to improve drug solubilization efficiency and micelle stability. Prepared by a thin-film hydration method, the average size of the optimized mixed micelle was 23 nm, with a 92.40% encapsulation ratio and a 1.81% drug-loading efficiency. The optimized formulation showed high storage stability in lyophilized form, with 95.7% of the drug content remaining after 6 months’ storage at 4°C. The in vitro cytotoxicity assay showed that the IC50 values for Taxotere® and mixed micelles were similar for A549, while on A549/Taxol cell lines, DTX-loaded P105/F127 mixed micelles showed a superior hypersensitizing effect; their IC50 value (0.059 μg/mL) was greatly reduced compared to those of Taxotere injections (0.593 μg/mL). The in vivo pharmacokinetic study showed that the mixed-micelle formulation achieved a 1.85-fold longer mean residence time in circulation and a 3.82-fold larger area under the plasma concentration-time curve than Taxotere. In addition, therapeutic improvement of mixed micelles in vivo against A549/Taxol was obtained. The tumor inhibition rate of the micelles was 69.05%, versus 34.43% for Taxotere (P < 0.01). Therefore, it could be concluded from the results that DTX-loaded P105/F127 mixed micelles might serve as a potential antitumor drug delivery system to overcome multidrug resistance in lung cancer.
Loop-Aware Memory Prefetching Using Code Block Working Sets

Memory prefetchers predict streams of memory addresses that are likely to be accessed by recurring invocations of a static instruction. They identify an access pattern and prefetch the data that is expected to be accessed by pending invocations of the said instruction. A stream, or a prefetch context, is thus typically composed of a trigger instruction and an access pattern. Recurring code blocks, such as loop iterations may, however, include multiple memory instructions. Accurate data prefetching for recurring code blocks thus requires tight coordination across multiple prefetch contexts. This paper presents the code block working set (CBWS) prefetcher, which captures the working set of complete loop iterations using a single context. The prefetcher is based on the observation that code block working sets are highly interdependent across tight loop iterations. Using automated annotation of tight loops, the prefetcher tracks and predicts the working sets of complete loop iterations. The proposed CBWS prefetcher is evaluated using a set of benchmarks from the SPEC CPU2006, PARSEC, SPLASH and Parboil suites. Our evaluation shows that the CBWS prefetcher improves the performance of existing prefetchers when dealing with tight loops. For example, we show that the integration of the CBWS prefetcher with the state-of-the-art spatial memory streaming (SMS) prefetcher achieves an average speedup of 1.16× (up to 4× ), compared to the standalone SMS prefetcher.
Fixed Parameter Undecidability for Wang Tilesets

Deciding if a given set of Wang tiles admits a tiling of the plane is decidable if the number of Wang tiles (or the number of colors) is bounded, for a trivial reason, as there are only finitely many such tilesets. We prove however that the tiling problem remains undecidable if the difference between the number of tiles and the number of colors is bounded by 43. One of the main new tool is the concept of Wang bars, which are equivalently inflated Wang tiles or thin polyominoes.