Miracle-dz/UniFAR-FTUs huggingface dataset:
A parallel solution to XML query application

Since various XML query applications have come to the fore recently, performance optimization becomes the research hotspot. With the popularity of multi-core computing condition, parallelization appears as an important optimization measure. The paper presents a parallel solution to XML query application through the combination of parallel XML parsing and parallel XML query. The XML parsing is based on arbitrary XML data partition and parallel sub-tree construction with the final merging procedure. After XML parsing, the region encodings of XML data are obtained for relation matrix construction in that the XPath evaluation in query procedure is based on relation matrix. The matrix construction procedure and query primitives are parallelized to boost performance. As a whole, our solution makes use of multi-core environment through parallelization of key execution stages in query process. The key execution stages are verified by experiment and the whole effect of the solution is presented.
Gene Encoding Chitinase 3-Like 1 Protein (CHI3L1) is a Putative Oncogene

An important task in understanding oncogenesis is the identification of those genes whose copy number and expression increase during tumorigenesis. Previously, in an effort to identify genes which could be used as molecular markers for glial tumors, we compared gene expression in glioblastoma to the normal brain cells. Among the genes with the most pronounced increased expression in tumors there was CHI3L1, encoding the secreted chitinase 3-like 1 protein (also known as HC gp-39 or YKL-40). Expression of CHI3L1 was found increased significantly in various tumors in comparison with corresponding normal tissues. Here we show that CHI3L1 can decrease the doubling time of 293 cells. We have also demonstrated that CHI3L1 allows the anchorage-independent growth in soft agar and, in addition, stable CHI3L1 expression made 293 cells tumorigenic: these cells stimulate the initiation of tumors after their xenograft transplantation into the Wistar rat brains. Thus, the overexpression of CHI3L1 is likely to be critical in the development of some tumors and when we gain more information about mechanisms of CHI3L1 oncogenicity, it could be used as one of the potential targets for anticancer therapy.
The Disciplinary Status of Consumer Behavior: A Sociology of Science Perspective on Key Controversies

Critics within the consumer behavior field have consistently debated three fundamental issues about the field’s defining properties and goals: (1) whether consumer behavior should be an independent discipline, (2) what is (and is not) consumer behavior, and (3) whether our field should be interdisciplinary. Taking the perspective of the sociology of science leads us to conclude that (1) consumer behavior is not an independent discipline; (2) consumer behavior is distinguished from other fields by its focus on a consumer role, emphasizing the acquisition, consumption, and disposal of marketplace products, services, and experiences; and (3) consumer behavior is not an interdisciplinary field.
Higher-order semantic labelling for inductive datatype systems

We give a novel transformation for proving termination of higher-order rewrite systems in the format of Inductive Data Type Systems (IDTSs) by Blanqui, Jouannaud and Okada. The transformation called higher-order semantic labelling attaches algebraic semantics of the arguments to each function symbol. We systematically define the labelling and show that labelled systems give termination models in the frame-work of Fiore, Plotkin and Turi's binding algebras. As applications, we give simple proofs of termination of the explicit substitution system λ X and currying transformation via higher-order semantic labelling. Moreover, we prove a new result of modularity of termination of IDTSs by introducing the notion of solid IDTSs. We prove that termination is preserved under the disjoint union of an IDTS and a higher-order program scheme.
Quorum Sensing Primes the Oxidative Stress Response in the Insect Endosymbiont, Sodalis glossinidius

Background Sodalis glossinidius, a maternally transmitted bacterial endosymbiont of tsetse flies (Glossina spp.), uses an acylated homoserine lactone (AHL)-based quorum sensing system to modulate gene expression in accordance with bacterial cell density. The S. glossinidius quorum sensing system relies on the function of two regulatory proteins; SogI (a LuxI homolog) synthesizes a signaling molecule, characterized as N-(3-oxohexanoyl) homoserine lactone (OHHL), and SogR1 (a LuxR homolog) interacts with OHHL to modulate transcription of specific target genes. Methodology/Principal Findings We used a tiling microarray to analyze the S. glossinidius transcriptome in the presence and absence of exogenous OHHL. The major finding is that OHHL increases transcription of a large number of genes that are known to be involved in the oxidative stress response. We also show that the obligate symbiont of the rice weevil, Sitophilus oryzae (SOPE), maintains copies of the quorum sensing regulatory genes that are found in S. glossinidius. Molecular evolutionary analyses indicate that these sequences are evolving under stabilizing selection, consistent with the maintenance of their functions in the SOPE symbiosis. Finally, the expression studies in S. glossinidius also reveal that quorum sensing regulates the expression of a cryptic, degenerate gene (carA) that arose from an ancient deletion in the last common ancestor of S. glossinidius and SOPE. Conclusions/Significance This oxidative stress response is likely mandated under conditions of dense intracellular symbiont infection, when intense metabolic activity is expected to generate a heavy oxidative burden. Such conditions are known to arise in the bacteriocytes of grain weevils, which harbor dense intracellular infections of symbiotic bacteria that are closely related to S. glossinidius. The presence of a degenerate carA sequence in S. glossinidius and SOPE indicates the potential for neofunctionalization to occur during the process of genome degeneration.
Image compression using adaptive sparse representations over trained dictionaries

Sparse representation is a common approach for reducing the spatial redundancy by modelling an image as a linear combination of few atoms taken from an analytic or trained dictionary. This paper introduces a new image codec based on adaptive sparse representations wherein the visual salient information is considered into the rate allocation process. Firstly, the regions of the image that are more conspicuous to the human visual system are extracted using a classical graph-based method. Further, block-based sparse representation over a trained dictionary coupled with an adaptive sparse representation is proposed, such that the adaptivity is achieved by appropriately assigning more atoms of the dictionary to the blocks belonging to the salient regions. Experimental results show that the proposed method outperforms the existing image coding standards, such as JPEG and JPEG2000, which use an analytic dictionary, as well as the state-of-the-art codecs based on trained dictionaries.
Enhancing Keylogger Detection Performance of the Dendritic Cell Algorithm by an Enticement Strategy

Evasive software keyloggers hide their malicious behaviors to defeat run-time detection. In this paper, based on the analysis of the evasion mechanisms used by common software keyloggers, we established a framework for their detection. Using an enticement strategy, the framework we built could induce keyloggers exhibited more obvious malicious activities by mimicking user keystrokes. These 'amplified' activities are then correlated by the dendritic cell algorithm (an immune-inspired algorithm) to final determine the existence of a keylogger in a host. Preliminary experimental results showed that the framework could improve the performance of keylogger detection and hard to evade. Index Terms—keylogger, keystroke simulation, dendritic cell algorithm (DCA), correlation
Combining Multiple Techniques for Intrusion Detection

Summary Most intrusion detection systems (IDS) are based on a single algorithm that is designed to either model the normal behaviour patterns or attack signatures in network data traffic. Most often, these systems fail to provide adequate alarm capability that reduces false positive and false negative rates. We here propose a double multiple-model approach capable of enhancing the overall performance of IDS. In a first step, every group of identical intrusion detection models are combined independently of the rest of the groups to produce a fused intrusion detection model. Then all the fused models are fused to produce the final intrusion detection model. Our IDS model adopted three reasoning methods: Naive Bayesian, Neural Nets, and Decision Trees. We used Darpa attack taxonomy and the KDD Intrusion Detection Dataset to demonstrate the working of our IDS model.
Mustajuuri - An application and toolkit for interactive audio processing

Mustajuuri is a freeware application and toolkit for audio signal processing. It is designed for quick prototyping, testing and combination of audio or MIDI processing modules. Its main focus is on efficient and low-latency real-time operation. Mustajuuri offers an extremely flexible plugin architecture. By creating new plugins programmmers can extend Mustajuuri to meet new needs. The C++ API takes into account the necessary features of audio signal processing and application development: low-latency real-time audio signal processing, easy debugging, graphical and text-mode user interfaces, internationalization and portability (currently supported on IRIX and Linux, but Windows port is possible). Mustajuuri also offers developers a rich set of support libraries that contain audio-related signal processing and graphics tools. Mustajuuri is licensed under the Library GNU Public License and it is available for download from the home-page: http://www.tml. hut.fi/~tilmonen/mustajuuri/.
A Ε-domination Based Multi-objective Particle Swarm Optimization

A multi-objective particle swarm optimization algorithm based on ε-dominance is proposed. The ε-dominance is applied to update the external set in order to obtain the Pareto set with better distribution, and the dynamic adjustment strategy, which made the algorithm achieving the search and approximation to the Pareto set, is adopted in the iterative process of the ε-Pareto solution set. Three benchmark cases were tested and the results show that this algorithm is much more efficient than the DNPSO.
PROD: Relayed file retrieving in overlay networks

To share and exchange the files among Internet users, peer-to-peer (P2P) applications build another layer of overlay networks on top of the Internet infrastructure. In P2P file sharing systems, a file request takes two steps. First, a routing message is generated by the client (request initiator) and spread to the overlay network. After the process finishes, the location information of the requested file is returned to the client. In the second step, the client establishes direct connection(s) with the peer(s) who store a copy of that file to start the retrieving process. While numerous research projects have been conducted to design efficient, high-performance routing algorithms, few work concentrated on file retrieving performance. In this paper, we propose a novel and efficient algorithm - PROD to improve the file retrieving performance in DHT based overlay networks. In PROD, when a file or a portion of a file is transferred from a source peer to the client, instead of creating just one direct link between these two peers, we build an application level connection chain. Along the chain, multiple network links are established. Each intermediate peer on this chain uses a store-and-forward mechanism for the data transfer. PROD also introduces a novel topological based strategy to choose these peers and guarantees the transmission delay of each intermediate link is much lower than the direct link. We conducted extensive simulation experiments and the results shown that PROD can greatly reduce the transfer time per file in DHT base P2P systems.
Multi-sourced Data Storage and Index Construction for Equipment Condition Assessment

With constant promotion and deepening of smart power grids, the data volume of power grid operation and equipment monitoring gain exponential growth and the environment of big data in electric system forms. Many platforms are deployed to meet different demands of equipment operation and maintenance. Since these platforms are independent and cannot be used in coordination, multi-sourced heterogeneous data become mainstream. Integrated storage and performance optimization of multi-sourced heterogeneous data are critical for condition assessment of power transmission and transformation equipment and security operation of power systems. In the paper, it focuses on the integration and optimization of multi-sourced data and design a storage schema of big data which can distributedly process and analyze data. It presents the storage schema of multi-sourced data based on HBase and a description method of metadata, which achieve the lossless and scalable integration of multi-sourced data. To solve the problem of low query efficiency due to the nonsupport of HBase for secondary index, it also proposes a constructing approach of secondary index for the attributes which are often used in the query tree of condition assessment. Extensive experiments show that the proposed storage schema of multi-sourced data and secondary index constructing approach have better query performance and index updating efficiency.
A Family Particle Swarm Optimization Based on Tree Structure

For the independence of particles in original particle swarm optimization (PSO), we had proposed the family PSO (FPSO) previously. To study the relationship between families and set up effective management to the families in the FPSO, a family tree was introduced into the FPSO. Based on the proposed tree structure of FPSO (Tree-FPSO) different tasks could be conveniently assigned to different families according to their places in the family tree. Simulations for six benchmark functions demonstrated the advantage and effectiveness of Tree-FPSO. The experiments also showed that families playing different roles were very important to improve the performance at the convergence speed and this made the PSO higher efficiency.
Be Close to Me and I Will Be Honest. How Social Distance Influences Honesty

We conducted a laboratory experiment to examine how honesty depends on social distance. Participants cast dice and reported the outcomes to allocate money between themselves and fellow students or the socially distant experimenter. They could lie about outcomes to earn more money. We found that dishonesty increases with social distance. However, responsiveness to social distance depends on personal preferences about inequity and honesty as a moral value. We observed selfish "black lies" but not altruistic "white lies" (outcomes were not understated to reduce inequality). Our results suggest that the reduction of social distance can promote honesty in social interactions.
Disease Burden of Dengue in the Philippines: Adjusting for Underreporting by Comparing Active and Passive Dengue Surveillance in Punta Princesa, Cebu City

Dengue virus (DENV) is a serious threat to public health. Having reliable estimates of the burden of dengue is important to inform policy and research, but surveillance systems are not designed to capture all symptomatic DENV infections. We derived the rate of reporting of dengue by comparing active surveillance of symptomatic DENV infections in a prospective community-based seroepidemiological cohort study (N = 1008) of acute febrile illness in Punta Princesa, Cebu City, Philippines, with passive surveillance data from the Cebu City Health Department. Febrile episodes detected in a weekly follow-up of participants were tested for serotype-specific DENV by hemi-nested reverse transcription-polymerase chain reaction (nested RT-PCR) and acute/convalescent blood samples tested by dengue IgM/IgG enzyme immunoassay. We estimated the burden of dengue in the Philippines in disability-adjusted life years (DALYs), and conducted a probabilistic sensitivity analysis using Monte-Carlo simulations to address uncertainty. The results showed a 21% cumulative reporting rate of symptomatic DENV infections, equivalent to an expansion factor of 4.7 (95% certainty level [CL]: 2.2–15.1). Based on surveillance data in the Philippines for 2010–2014, we estimated 794,255 annual dengue episodes (95% CL: 463,000–2,076,000) and a disease burden of 535 (95% CL: 380–994) DALYs per million population using age weights and time discounting and 997 (95% CL: 681–1,871) DALYs per million population without age and time adjustments. Dengue imposes a substantial burden in the Philippines; almost 10 times higher than estimated for rabies, about twice the burden of intestinal fluke infections, and about 10% of the burden of tuberculosis. Our estimates should inform policy makers and raise awareness among the public.
MENTA: inducing multilingual taxonomies from wikipedia

In recent years, a number of projects have turned to Wikipedia to establish large-scale taxonomies that describe orders of magnitude more entities than traditional manually built knowledge bases. So far, however, the multilingual nature of Wikipedia has largely been neglected. This paper investigates how entities from all editions of Wikipedia as well as WordNet can be integrated into a single coherent taxonomic class hierarchy. We rely on linking heuristics to discover potential taxonomic relationships, graph partitioning to form consistent equivalence classes of entities, and a Markov chain-based ranking approach to construct the final taxonomy. This results in MENTA (Multilingual Entity Taxonomy), a resource that describes 5.4 million entities and is presumably the largest multilingual lexical knowledge base currently available.
Defining DNA-Based Operational Taxonomic Units for Microbial-Eukaryote Ecology

ABSTRACT DNA sequence information has increasingly been used in ecological research on microbial eukaryotes. Sequence-based approaches have included studies of the total diversity of selected ecosystems, studies of the autecology of ecologically relevant species, and identification and enumeration of species of interest for human health. It is still uncommon, however, to delineate protistan species based on their genetic signatures. The reluctance to assign species-level designations based on DNA sequences is in part a consequence of the limited amount of sequence information presently available for many free-living microbial eukaryotes and in part a consequence of the problematic nature of and debate surrounding the microbial species concept. Despite the difficulties inherent in assigning species names to DNA sequences, there is a growing need to attach meaning to the burgeoning amount of sequence information entering the literature, and there is a growing desire to apply this information in ecological studies. We describe a computer-based tool that assigns DNA sequences from environmental databases to operational taxonomic units at approximately species-level distinctions. This approach provides a practical method for ecological studies of microbial eukaryotes (primarily protists) by enabling semiautomated analysis of large numbers of samples spanning great taxonomic breadth. Derivation of the algorithm was based on an analysis of complete small-subunit (18S) rRNA gene sequences and partial gene sequences obtained from the GenBank database for morphologically described protistan species. The program was tested using environmental 18S rRNA data sets for two oceanic ecosystems. A total of 388 operational taxonomic units were observed for 2,207 sequences obtained from samples collected in the western North Atlantic and eastern North Pacific oceans.
Efficient Global Programming Model for Discriminant Analysis

— Conventional statistical analysis includes the capacity to systematically assign individuals to groups. We suggest alternative assignment procedures, utilizing a set of interrelated goal programming formulations. This paper represents an effort to suggest ways by which the discriminant problem might reasonably be addressed via straightforward linear goal programming formulations. Simple and direct, such formulations may ultimately compete with conventional approaches - free of the classical assumptions and possessing a stronger intuitive appeal. We further demonstrate via simple illustration the potential of these procedures to play a significant part in addressing the discriminant problem, and indicate fundamental ideas that lay the foundation for other more sophisticated approaches.
Image Enhancement Using Homomorphic Filtering and Adaptive Median Filtering for Balinese Papyrus (Lontar)

Balinese papyrus (Lontar) is one of the most popular media to write for more than a hundred years in Indonesia. Balinese papyrus are used to document things that are considered important in the past. Most of the balinese papyrus suffered damage caused by weathering, edible fungus and insects making it is difficult to read. One of the efforts made to preserve the existence of balinese papyrus is to perform digitization of it. The problems most often encountered in the process of digitizing the image of the balinese papyrus is less good results as there is noise caused by its conditions that have been damaged and the uneven distribution illumination in this part of the image. In this study the authors propose to combine homomorphic filtering with adaptive median filtering to perform image enhancement. Surve results obtained show the percentage of the average respondents stated that the image enhancement results are good is 83.4%, the percentage of the average respondents stated that the image enhancement results are very good is 4% and the percentage of the average respondents stated that the image enhancement results are enough is 12, 6%.
A linear tuning ring VCO for spectrum monitor receiver in cognitive radio applications

A ring oscillator is designed and implemented on standard 130nm CMOS technology for wide range frequency tuning purpose in a spectrum monitor receiver used in cognitive radio applications. The three-stage differential ring oscillator is tuned by an array of MOS varactors, which is controlled by a novel staggered voltage offset system for improved tuning linearity. The proposed ring oscillator achieves a measured tuning range from 4.85GHz to 7.15GHz, consuming 4.2mA current from a 1.2V supply voltage. The measured phase noise is −82.5 dBc/Hz at 1MHz offset from an operating frequency of 4.88GHz. The die area of the oscillator core is about 70µm×50µm.
A shorted waveguide-stub coupling mechanism for narrow-band multimode coupled resonator filters

A shorted waveguide-stub coupling mechanism is presented for implementing narrow-band multimode coupled cavity filters without coupling screws. The coupling element is a shorted rectangular waveguide stub placed in the end walls of cylindrical filter cavities, using perturbation of the magnetic fields to obtain coupling between degenerate modes. This structure is well suited to analysis and design with the efficient and accurate mode-matching method. Coupling coefficients and resonator frequencies can be controlled by varying cavity dimensions and the length, width, and depth of the rectangular coupling element. The accuracy with which the coupling can be realized and the elimination of coupling screws reduce the amount of tuning substantially. A third-order Chebyshev filter, realized in a triple-mode cavity with no coupling screws and only two tuning screws, is presented to verify the use of the coupling structure.