Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlocal Collaborative l 0-Norm Prior for Image Denoising

Spatially adaptive nonparametric regression estimation is one of the most promising recent directions in image processing. The Transforms and Spectral Techniques Research Group at the Department of Signal Processing, Tampere University of Technology, has been active in this novel eld starting from about 2002. The results achieved with application to di¤erent image and video processing problems are very positive and completely support optimism following from general speculations concerning nonparametric modeling (e.g. [1]-[9]). Within this framework the Block Matching and 3-D Filtering (BM3D) algorithm has been developed which is currently one of the best performing denoising algorithms. In this paper a special prior is proposed allowing to reformulate mainly semi-heuristic nonlocal nonparametric techniques as global minimization of an energy criterion. It is shown that the basic hard-thresholding part of the BM3D algorithm can be derived as a minimizer of the proposed prior. The outstanding performance of BM3D is a strong argument in favor of this prior as an e¢ cient multilayer redundant image model.
Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection

The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called ‘K*Sync’, in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.
An update on PARP inhibitors for the treatment of cancer

The development of poly (adenosine diphosphate [ADP]) ribose polymerase (PARP) inhibitors (PARPi) has progressed greatly over the last few years and has shown encouraging results in the BRCA1/2 mutation–related cancers. This article attempts to summarize the rationale and theory behind PARPi, the clinical trials already reported, as well as ongoing studies designed to determine the role of PARPi in patients with and without germline mutations of BRCA genes. Future plans for PARPi both as monotherapy and in combination with standard cytotoxics, other biological agents, and as radiosensitizers are also covered. The widening scope of PARPi adds another important targeted agent to the growing list of molecular inhibitors; future and ongoing trials will identify the most effective role for PARPi, including for patients other than BRCA germline mutation carriers.
The reflexive imagery task: An experimental paradigm for neuroimaging

High-level cognitions can be triggered into consciousness through the presentation of external stimuli and the activation of certain action sets. These activations arise in a manner that is involuntary, systematic and nontrivial. For example, in the Reflexive Imagery Task (RIT), subjects are presented with visual objects and instructed to not think of the names of the objects. Involuntary subvocalizations arise on roughly 80% of the trials. We review the findings from this paradigm, discuss neural findings that are relevant to the RIT, and present new data that further corroborate the reliability and robustness of the RIT, a paradigm that could be coupled with neuroimaging technologies. We developed an RIT variant in which two, non-focal objects are presented simultaneously. In previous RITs, visual objects were presented only one at a time, in the center of the screen, and subjects were instructed to focus on the center of the screen, where these objects were presented. Replicating the RIT effect, involuntary subvocalizations still occurred on a high proportion of trials (M = 0.78). An RIT effect arose for both objects on a considerable proportion of the trials (M = 0.35). These findings were replicated in a second experiment having a different sample of subjects. Our findings are relevant to many subfields of neuroscience (e.g., the study of high-level mental processes, attention, imagery and action control).
Relations between structure and estimators in networks of dynamical systems

The article main focus is on the identification of a graphical model from time series data associated with different interconnected entities. The time series are modeled as realizations of stochastic processes (representing nodes of a graph) linked together via transfer functions (representing the edges of the graph). Both the cases of non-causal and causal links are considered. By using only the measurements of the node outputs and without assuming any prior knowledge of the network topology, a method is provided to estimate the graph connectivity. In particular, it is proven that the method determines links to be present only between a node and its “kins”, where kins of a node consist of parents, children and co-parents (other parents of all of its children) in the graph. With the additional hypothesis of strictly casual links, a similar method is provided that allows one to exactly reconstruct the original graph. Main tools for determining the network topology are based on Wiener, Wiener-Hopf and Granger filtering. Analogies with the problem of Compressing Sensing are drawn and two greedy algorithms to address the problem of reducing the complexity of the network structure are also suggested.
Performance Evaluation in Cellular (CDMA) System Using Smart Antenna with Adaptive Sectoring Method

As the number of subscribers to wireless services has increased enormously, the demand for the mobile phone continue to soar, and as the predicted demand for data traffic begins to materialize, CDMA network operators will need to use all available tools and strategies to meet the attendant capacity challenges. Smart antennas will certainly be among the most flexible and cost-effective of those tools, and using such systems to facilitate flexible, multiple sectorization schemes will likely be among the most promising strategies In this paper the beamforming and the channel effects in CDMA wireless system having number of users in cell sector system in the uplink has been studied. The effect of interference due to other users and the noise in the uplink transmission has been considered and the effect of beamforming algorithms like LSCMA in cellular CDMA has been analyzed. Simulation results show that capacity increases several folds in a CDMA cell having N sectors system per cell than omni-directional cell system if the perfect power control is considered.
Computer Science at Kent GCspy : An Adaptable Heap Visualisation Framework

GCspy is an architectural framework for the collection, transmission, storage and replay of memory management behaviour. It makes new contributions to the understanding of the dynamic memory behaviour of programming languages (and especially object-oriented languages that make heavy demands on the performance of memory managers). GCspy’s architecture allows easy incorporation into any memory management system: it is not limited to garbage-collected languages. It requires only small changes to the system in which it is incorporated but provides a simple to use yet powerful data-gathering API. GCspy scales to allow very large heaps to be visualised effectively and efficiently. It allows already-running, local or remote, systems to be visualised and those systems to run at full speed outside the points at which data is gathered. GCspy’s visualisation tool presents this information in a number of novel ways. Deep understanding of program behaviour is essential to the design of the next generation of garbage collectors and explicit allocators. Until now no satisfactory tools have been available to assist the implementer in gaining an understanding of heap behaviour. GCspy has been demonstrated to be a practical solution to this dilemma. It has been used to analyse production Java virtual machines running applications of realistic size. Its use has revealed important insights into the interaction between application program and JVM and has led to the development of better garbage collectors.
Comparative Study on Face Recognition Based on SVM of One-against-One and One-against-Rest Methods

A comparative study on face recognition based on two methods, SVM of One-against-One method and SVM of One-against-Rest method, has been carried out in this paper. Our method consists of three parts: Firstly, the image robustness on illumination and posture has been improved by the processing of the Gabor wavelet. Secondly, the bilateral 2DLDA technique on image is adopted to realize the dimension reduction of the large feature data. Finally, the SVM classifier has been used to classify facial features and accomplish face recognition. The face recognition is the multiple-classification issue, but the SVM is the essence of handling the binary classification problem. We used the traditional methods of One-against-One SVM and One-against-Rest SVM iteratively to train and test facial database samples to achieve the multiple-classification problems. In the experiment, the ORL face database was applied to compare the two classical methods. The result shows that the One-against-Rest SVM method has the priority of better recognition rate.
A Frequency-Domain Encoding for Neuroevolution

Neuroevolution has yet to scale up to complex reinforcement learning tasks that require large networks. Networks with many inputs (e.g. raw video) imply a very high dimensional search space if encoded directly. Indirect methods use a more compact genotype representation that is transformed into networks of potentially arbitrary size. In this paper, we present an indirect method where networks are encoded by a set of Fourier coefficients which are transformed into network weight matrices via an inverse Fourier-type transform. Because there often exist network solutions whose weight matrices contain regularity (i.e. adjacent weights are correlated), the number of coefficients required to represent these networks in the frequency domain is much smaller than the number of weights (in the same way that natural images can be compressed by ignore high-frequency components). This "compressed" encoding is compared to the direct approach where search is conducted in the weight space on the high-dimensional octopus arm task. The results show that representing networks in the frequency domain can reduce the search-space dimensionality by as much as two orders of magnitude, both accelerating convergence and yielding more general solutions.
Longest Common Extension with Recompression Tomohiro I

Given two positions i and j in a string T of length N , a longest common extension (LCE) query asks for the length of the longest common prefix between suffixes beginning at i and j. A compressed LCE data structure is a data structure that stores T in a compressed form while supporting fast LCE queries. In this article we show that the recompression technique is a powerful tool for compressed LCE data structures. We present a new compressed LCE data structure of size O(z lg(N/z)) that supports LCE queries in O(lgN) time, where z is the size of Lempel-Ziv 77 factorization without self-reference of T. Given T as an uncompressed form, we show how to build our data structure in O(N) time and space. Given T as a grammar compressed form, i.e., an straight-line program of size n generating T, we show how to build our data structure in O(n lg(N/n)) time and O(n + z lg(N/z)) space. Our algorithms are deterministic and always return correct answers.
Enhancing network management frameworks with SDN-like control

Traditional network management tools are too static and inflexible in today's enterprise and campus networks that have to support users with diversity of personal devices. Controller-based Software Defined Networking (SDN) paradigms are gaining popularity because of their promise to reduce the complexity of managing networks by automating the complex process of translating policy definitions to network provisioning and dynamic control. Though this approach provides fine-grained control over end-to-end network flows, they lack mature management and control tools. We propose an integrated network management and control system (i-NMCS) framework that combines legacy network management functions such as discovery, fault detection with the end-to-end flow provisioning and control enabled by SDN. We believe that such hybrid control will be key for incremental deployment of SDN functionality on today's networks.
Compiling with

I propose a new compiler architecture for compiling source-level programs into a combination of object code and a proof that the object code preserves certain properties of the source program. Such a certifying compiler is structured as a pipeline of certifying static analyses|analyses that produce an explicit proof of the code properties that they infer|along with certifying code transformations, which transform not only the code but also the input proof to a target proof. The purpose of a certifying compiler is to allow independent and easy veriication of the properties of the generated code without the cost of running a program analyzer and without the need to trust such a system. The certifying compiler complements earlier work on Proof-Carrying Code by providing an automatic way to produce the required safety proofs when the safety properties are statically decidable or can be checked at run time. The thesis is that this approach is more practical than approaches based on program veriication because it does not require the discovery of program invariants from the object code directly. Furthermore implementing a certifying compiler is easier than formally verifying a traditional compiler because the target proof does not have to mirror all of the heuristics and failed analysis attempts that occur during the compilation. I propose to demonstrate that state-of-the-art program analyses and compiler optimizations are implementable in the certifying compiler architecture.
Research of Parallel and Serial Concatenated Convolutional Codes Channel Coding Technology in Deep-Space Communication

This paper researches the Parallel Concatenated Convolutional Codes (PCCCs) and Serial Concatenated Convolutional Codes (SCCCs) channel encoders' theoretical performance and design criteria in deep-space communication. Using random interleaver and studying the random interleaver design algorithm. Theoretical analysis presents the reasons for their excellent performance. Different encoding techniques are considered and various channel conditions.
The Effect of Corpus Size on Case Frame Acquisition for Discourse Analysis

This paper reports the effect of corpus size on case frame acquisition for discourse analysis in Japanese. For this study, we collected a Japanese corpus consisting of up to 100 billion words, and constructed case frames from corpora of six different sizes. Then, we applied these case frames to syntactic and case structure analysis, and zero anaphora resolution. We obtained better results by using case frames constructed from larger corpora; the performance was not saturated even with a corpus size of 100 billion words.
The Effects of Chitosan-Hyaluronic Acid Blended Membrane on the Growth of Keratocytes

In order to construct a suitable scaffold for corneal cells culture and transplantation in vitro, different chitosan- hyaluronic acid blended membranes were prepared and the compatibility of chitosan and hyaluronic acid in blended membranes was studied. Rabbit keratocytes were seeded onto the blended membranes surface and the effects of the blended membranes on cells attachment and metabolism were investigated. The results showed that chitosan and hyaluronic acid had good compatibility in blended membranes within a certain blended ratio. Within the blending ratio of 1:0.05, hyaluronic acid could reduce the damage of chitosan membrane to cells and improve the adhersion and proliferation of cells on blended membranes. So chitosan and hyaluronic acid had good compatibility within a certain blended ratio. Hyaluronic acid could improve the biocompatibility between cells and membranes. The blended membrane had potential to be used as a scaffold for corneal cells culture in vitro and a carrier for corneal cells transplantation. Keywords-chitosan; hyaluronic acid; blended membrane; keratocytes
Exploring FSR open cluster candidates within $\sf |\Delta\ell|=20^\circ$ of the Galactic anticentre

Context. We investigate the nature of a sample of star cluster candidates detected as stellar overdensities towards the Galactic anticentre. Aims. Taken from the catalogue of Froebrich, Scholz, and Raftery (FSR), the sample contains 28 star cluster candidates located within $|\Delta\ell|=20^\circ$ of the anticentre. These are all the candidates in that sector classified by FSR with a high probability of being star clusters. Our main goals are to determine the fraction of such candidates that are unknown star clusters, to derive their astrophysical parameters, and to investigate the relationship of cluster parameters with position in the Galaxy. Methods. Properties of the star cluster candidates are investigated with field-star decontaminated 2MASS colour–magnitude diagrams and stellar radial density profiles. Results. All candidates present significant excesses in the radial density profiles, consistent with the method from which they were originally selected. Of the 28 candidates, 7 are previously known open clusters, 2 have been recently identified, and 6 are new ones with ages from 30 Myr to 1 Gyr. Among the remaining 13 candidates, 6 are uncertain cases that require deeper observations, while 7 appear to be important field fluctuations. The structure of part of the newly identified open clusters appears to be affected by interaction with giant molecular clouds in the Local and Perseus arms. Conclusions. When photometric and radial distribution properties are considered together, an important fraction of the stellar overdensities with a fluctuation level $\ga$$3\sigma$ are shown to be star clusters. Thus, catalogues of star cluster candidates, coupled to the present kind of study, are an important source for identifying unknown open clusters. Such efforts affect the understanding of the star-formation rate, cluster dynamical evolution, and Galactic structure, among others.
Vision based motorcycle detection using HOG features

In this paper, we present a motorcycle detection system in static images leading to its application in crash avoidance systems. Motorcycles are common mode of transport in ASEAN countries and contribute more road crashes than any other mode of transport. In our proposed system, motorbikes are detected based on the helmet and tyre color characteristics. This method involves the fusion of shape, color and corner features to hypothesize motorcycle locations in a video frame. The hypothesized locations are then classified using a support vector machine (SVM) classifier trained on histogram of oriented gradients (HOG) features of motorcycle database. The proposed technique was successfully designed and implemented on a standard PC. It was able to detect single and multiple motorcycles in videos with 96% detection rate.
Zinc finger nucleases: custom-designed molecular scissors for genome engineering of plant and mammalian cells

Custom-designed zinc finger nucleases (ZFNs), proteins designed to cut at specific DNA sequences, are becoming powerful tools in gene targeting—the process of replacing a gene within a genome by homologous recombination (HR). ZFNs that combine the non-specific cleavage domain (N) of FokI endonuclease with zinc finger proteins (ZFPs) offer a general way to deliver a site-specific double-strand break (DSB) to the genome. The development of ZFN-mediated gene targeting provides molecular biologists with the ability to site-specifically and permanently modify plant and mammalian genomes including the human genome via homology-directed repair of a targeted genomic DSB. The creation of designer ZFNs that cleave DNA at a pre-determined site depends on the reliable creation of ZFPs that can specifically recognize the chosen target site within a genome. The (Cys2His2) ZFPs offer the best framework for developing custom ZFN molecules with new sequence-specificities. Here, we explore the different approaches for generating the desired custom ZFNs with high sequence-specificity and affinity. We also discuss the potential of ZFN-mediated gene targeting for ‘directed mutagenesis’ and targeted ‘gene editing’ of the plant and mammalian genome as well as the potential of ZFN-based strategies as a form of gene therapy for human therapeutics in the future.
PROSPECTS OF CONNECTIVISM IN LIFELONG PROFESSIONAL TRAINING OF EARLY CHILDHOOD EDUCATOR IN THE FRAMEWORK OF DIGITAL PEDAGOGY - PERCEPTIONS, ATTITUDES AND INTENTIONS

The purpose of this study was to investigate early childhood educators’ perceptions, attitudes and intentions towards the exploitation of principles of connectivism concerning their professional training. The sample of this study was 744 early childhood educators, both educators with gradual professional experience, as well as prospective educators (students). This study was conducted with survey methods and the data were collected by using a questionnaire, developed by the researcher, which was based on the theory of connectivism and was created for the purposes of this study only. At the end of the study was noted that there are generally positive attitudes and intentions, regarding connectivism, that coexist with a relative hesitation. Results indicated that significant differences do exist between early childhood educators and senior students regarding their New Technologies usage profile and work experience. The necessity for training early childhood educators was highlighted, so as they will be able to explore and exploit the potential of participatory web 2.0 to lifelong learning and professional development. Implications for further research were discussed. Article visualizations:
The impact of corporate governance on the timeliness of corporate internet reporting by Egyptian listed companies

Purpose - This study seeks to examine the key factors that affect the timeliness of corporate internet reporting (CIR) by the Egyptian listed corporations on the Cairo and Alexandria Stock Exchange. Design/methodology/approach - The authors use firm characteristics and corporate governance variables to investigate the influence on the timeliness of CIR. They also develop a disclosure index to measure the timeliness of CIR for the listed Egyptian corporations. Findings - The primary analysis finds a significant relationship between the timeliness of CIR and firm size, type of industry, liquidity, ownership structure, board composition and board size. The results indicate that firms typically in the service sector, that are large and have a high rate of liquidity, a high proportion of independent directors, a large number of board directors and a high free float disclose more timely information on their web sites. Furthermore, a significant association between the entire independent variables and some items of timeliness of CIR is found. Originality/value - This study is one of the first empirical studies to investigate the relationship between the corporate governance and the timeliness of CIR in an emerging market.