Miracle-dz/UniFAR-FTUs huggingface dataset:
A Sperm–Plasma β-N-Acetyl-D-Hexosaminidase Interacting with a Chitinolytic β-N-Acetyl-D-Hexosaminidase in Insect Molting Fluid

Insects require molting fluids to shed the old cuticle during molting. β-N-acetyl-D-hexosaminidase, known as Hex1, together with various chitinases, is responsible for degrading the chitin component of the old cuticle. This study showed that another β-N-acetyl-D-hexosaminidase, termed OfHex3, interacted with Hex1 and functioned in the molting fluid, although the homolog of OfHex3 was known as a sperm–plasma enzyme functioning in egg–sperm recognition. OfHex3 is an enzyme cloned from the insect Asian corn borer, Ostrinia furnacalis, which is one of the most destructive pests of maize. The enzymatic activity analysis indicated that OfHex3 was able to degrade chitooligosaccharides, but at a lower rate than that of OfHex1. Because OfHex3 did not have substrate inhibition, we deduced that the presence of OfHex3 might help OfHex1 relieve substrate inhibition during chitin degradation during molting. The expression patterns of OfHex3 during O. furnacalis development were studied by real-time PCR as well as western blot. The results showed that both gene transcription and protein translation levels of OfHex3 were up-regulated during larval–larval molting. The tissue-specific expression pattern analysis indicated that OfHex3 was mostly localized in the fat body and testis. All these data further supported that Hex3 was involved in molting as well as in fertilization. This study may help to understand the complexity of cuticle degradation during insect molting, and may provide a possible target for pest control.
CREATING THE MESSAGE INFRASTRUCTURE Draft paper for submission to TEC, December 2009 Version 6

The ever-increasing power of computing infrastructure such as processing, storage and network bandwidth continues to enable new models of data management and analysis. The Mobile Environmental Sensor System Across Grid Environments (MESSAGE) set out to make use of such advances, combined with e-Science techniques, to support the capture, processing, archiving, analysis and visualisation of pollution data. This paper describes the e-Science infrastructure that was developed within MESSAGE to support these tasks.
Breast cancer stem cells

Cancer metastasis, resistance to therapies and disease recurrence are significant hurdles to successful treatment of breast cancer. Identifying mechanisms by which cancer spreads, survives treatment regimes and regenerates more aggressive tumors are critical to improving patient survival. Substantial evidence gathered over the last 10 years suggests that breast cancer progression and recurrence is supported by cancer stem cells (CSCs). Understanding how CSCs form and how they contribute to the pathology of breast cancer will greatly aid the pursuit of novel therapies targeted at eliminating these cells. This review will summarize what is currently known about the origins of breast CSCs, their role in disease progression and ways in which they may be targeted therapeutically.
Data Compression Using a Dictionary of Patterns

Most modern lossless data compression techniques used today, are based in dictionaries. If some string of data being compressed matches a portion previously seen, then such string is included in the dictionary and its reference is included every time it occurs. A possible generalization of this scheme is to consider not only strings made of consecutive symbols, but more general patterns with gaps between its symbols. In this paper we introduce an off-line method based on this generalization. We address the main problems involved in such approach and provide a good approximation to its solution
Verifying Stability of Dynamic Soft-Computing Systems

Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.
Enquiry-Based Learning Online: Course Development and Student Experience of a First-Year Enquiry-Based Learning Seminar

Online courses are increasing in popularity while universities are using first-year seminars to address the challenges of large impersonal classes, lack of student engagement, and increased skills development. Could the learning experience and benefits of an in-person first-year seminar be achieved through an online distance education (DE) format? How would students’ experience benefit from an online DE first-year seminar? At the University of Guelph, an online interdisciplinary first-year seminar was developed and offered four times. This essay includes reflections from the faculty instructor and educational developer who co-designed the course, results from pre- and post-course surveys completed by students, and interviews conducted with students.
Verifiable delegation of computation on outsourced data

We address the problem in which a client stores a large amount of data with an untrusted server in such a way that, at any moment, the client can ask the server to compute a function on some portion of its outsourced data. In this scenario, the client must be able to efficiently verify the correctness of the result despite no longer knowing the inputs of the delegated computation, it must be able to keep adding elements to its remote storage, and it does not have to fix in advance (i.e., at data outsourcing time) the functions that it will delegate. Even more ambitiously, clients should be able to verify in time independent of the input-size -- a very appealing property for computations over huge amounts of data. In this work we propose novel cryptographic techniques that solve the above problem for the class of computations of quadratic polynomials over a large number of variables. This class covers a wide range of significant arithmetic computations -- notably, many important statistics. To confirm the efficiency of our solution, we show encouraging performance results, e.g., correctness proofs have size below 1 kB and are verifiable by clients in less than 10 milliseconds.
Simulation Algorithms to NoC MPSoC Computers”

Many-core architectures offer high computational power and are particularly interesting for compute-intensive simulation tasks. The project focuses on the mapping of simulation algorithms to such innovative new architectures. Algorithms are thoroughly analyzed to identify the computationally critical and potentially parallelizable parts. Today, these steps are predominantly done by hand, and one goal of the project is the development of an analysis and mapping methodology to automate these steps. As nano-scaled semiconductor devices are especially prone to reliability harming factors like soft errors, fault tolerance techniques are seamlessly integrated.
Depalatalization in Spanish Revised

Anda, y que te ondulen con la 'permanén', y pa suavizarte que te den 'col-crém'. Se lo pués pedir a Victoria Kent, que lo que es a mí, no ha nacido quién. 1. The (scarcity of) data It is common in natural languages that the set of possible final consonants is a subset of the set of possible segments in all positions, and that an underlying segment that is not possible in final position is (minimally) changed to one of the subset. One such case is final depalatalization in Spanish, a process that has received wide attention in the phonological literature. In Spanish, nasals and laterals contrast in place of articulation; nasals show a three-way contrast and laterals, a two-way contrast: 1 (1) ca[m]a 'bed' po[l]o 'pole' ca[n]a 'white hair' po[]o 'chicken' ca[]a 'cane' Castilian Spanish, the variety on which we base our analysis, shows not only depalatalization but generalized centralization of any place to alveolar in word-final position (other varieties, such as Mexican Spanish, accept final [m], but all disallow palatals; cf. Harris 1984). There is no word with the form in (2), for any sequence X. Contreras (1977), following the generalization first posited by Alonso (1945), proposed a rule of nasal and lateral depalatalization that turns // into [n] and // into [l] before consonant and in word-final position. Harris (1983) used similar data to reformulate the rule in terms of syllable structure by replacing {C, #} by reference to the rhyme. 2 Nasal depalatalization provided an argument for cyclic application (as exemplified by the now famous triplet desdén–desdenes–desdeñes 'disdain (noun, singular) – disdains (noun, plural) – you disdain (subjunctive)'), which has been much quoted in subsequent literature psycholinguistic grounds. She was followed by Harris (1999) who gives detailed argumentation to " debunk once and for all the legend of Nasal Depalatalization " (47). In this
Voltage Enhancement and Reduction of Real Power Loss by Particle Swarm Optimization Algorithm Based on Membrane Computing

This paper proposes Particle Swarm optimization algorithm based on Membrane Computing (PSOMC) for solving optimal reactive power dispatch problem. PSOMC is designed with the framework and rules of a cell-like P systems, and particle swarm optimization with the neighbourhood search. In order to evaluate the efficiency of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other specified algorithms. Simulation results show that PSOMC is superior to other algorithms in reducing the real power loss and improving the voltage stability.
Limitations of incremental signal-tracing for FPGA debug

Developing state-of-the-art custom silicon can be a prohibitively expensive and risky undertaking, due in no small part to the need to perform thorough design verification. Field-Programmable Gate-Arrays offer a flexible platform for constructing prototypes to aid in their verification, but unlike software simulation, observability into these prototypes is a major challenge. Designers can choose to insert trace-instrumentation to enhance on-chip observability, but doing so often requires re-compiling the entire design for each new trace configuration. This work presents two contributions: to explore the limitations of incremental-synthesis for trace-buffer insertion, and to propose CAD optimizations exclusive to this application for improving runtime and routability. We find that 99.4% of all used cluster outputs (driving both combinational and sequential circuit signals) can be incrementally-traced to 75% of the free memory-capacity on an FPGA, an order of magnitude quicker than the original compilation and with a nominal impact on circuit delay, for a 20% minimum channel width (10% area) increase.
Ancestral Heterogeneity in a Biethnic Stroke Population

To test for and characterize heterogeneity in ancestral contributions to individuals among a population of Mexican American (MA) and non‐Hispanic white (NHW) stroke/transient ischemic attack (TIA) cases, data from a community‐based stroke surveillance study in south Texas were used. Strokes/TIA cases were identified (2004–2006) with a random sample asked to provide blood. Race‐ethnicity was self‐reported. Thirty‐three ancestry informative markers were genotyped and individual genetic admixture estimated using maximum likelihood methods. Three hypotheses were tested for each MA using likelihood ratio tests: (1) H0: μi = 0 (100% Native American), (2) H0: μi = 1.00 (100% European), (3) H0: μi = 0.59 (average European). Among 154 self‐identified MAs, estimated European ancestry varied from 0.26 to 0.98, with an average of 0.59 (SE = 0.014). We rejected hypothesis 1 for every MA and rejected hypothesis 2 for all but two MAs. We rejected hypothesis 3 for 40 MAs (20 < 59%, 20 > 59%). Among 84 self‐identified NHWs, the estimated fraction of European ancestry ranged from 0.83 to 1.0, with an average of 0.97 (SE = 0.014). Self‐identified MAs, and to a lesser extent NHWs, from an established bi‐ethnic community were heterogeneous with respect to genetic admixture. Researchers should not use simple race‐ethnic categories as proxies for homogeneous genetic populations when conducting gene mapping and disease association studies in multi‐ethnic populations.
Testability transformation

A testability transformation is a source-to-source transformation that aims to improve the ability of a given test generation method to generate test data for the original program. We introduce testability transformation, demonstrating that it differs from traditional transformation, both theoretically and practically, while still allowing many traditional transformation rules to be applied. We illustrate the theory of testability transformation with an example application to evolutionary testing. An algorithm for flag removal is defined and results are presented from an empirical study which show how the algorithm improves both the performance of evolutionary test data generation and the adequacy level of the test data so-generated.
HETA: Hadoop environment for text analysis

As a leading energy player, EDF (Électricité de France) actively works on new techniques to better understand customers' voice. In order to process unstructured and semi-structured massive text data, we have developed HETA, an application based on open source solutions which offers different text processing steps (document engineering, text analysis, clustering and visualization) on top of Hadoop. It is based on Mahout and uses sigma.js library for the visualization of the results as interactive graphs. HETA presents an ergonomic Web interface and is able to analyze any kind of unstructured (blog comments) and semi-structured (tweets, articles, etc.) massive text data. Being a modular and extensible application, HETA can be easily enhanced with the addition of advanced text mining methods.
Robot Beerpong: Model-Based Learning for Shifting Targets

De(cid:28)ning controls for robot to achieve precise goal-directed movements can be hard when using hand crafted solutions. Reinforcement Learning, particularly policy-search meth-ods provides a promising alternative which has already been successfully used for robot learning. Here the task is learned using a function that rewards desired movements and an algorithm that seeks to maximize the reward. In this paper we address the motor-task of Beerpong, that was solved us-ing reinforcement learning in the simulation-environment SL. We extended a model-based method to the setting of bandit-type reward, showing that it is able to out perform two benchmark algorithms in terms of rollouts on the setting of a stationary cup. Also, we proofed capability of our approach to generalize to changing environment.
Advanced e-voting system using Paillier homomorphic encryption algorithm

The increase of technology usage, especially in online storage data with cloud system, makes data security become one of the most important requirements for the user. One of the ways to protect the data is with encryption process, it as a process to change a data form into a new one that can only be read by the chosen recipient. This technology has been carried out in the election process with e-voting system. The high risk of security problem makes data encryption applied in the e-voting system. Thus, the ballot won't be interrupted by the insider or the outsider. The purpose of this research is to prove the effectiveness of the Paillier algorithm and its homomorphic property that implemented in an e-voting system. With homomorphic property, the system can calculate the sum of votes in ciphertext form without revealing the choice of the voters. The resulting ciphertext values will be different each other even though the same plaintext is encrypted, with a size of 4 times larger than the plaintext size. The success ratio for the system is 100% with the maximum number of messages that can be processed is 3.287. 937.778 messages.
Anomaly Detection for Video Surveillance Applications

We investigate the problem of anomaly detection for video surveillance applications. In our approach, we use a compression-based similarity measure to determine similarity between images in a video sequence. Images that are sufficiently dissimilar are deemed anomalous and stored to be compared against subsequent images in the sequence. The goal of our research is two-fold; in addition to detecting anomalous images, the issue of heavy computational and storage resource demands is addressed
Calibration of word posterior estimation in confusion networks for keyword search

Word posterior probability has been widely used as the confidence estimation of automatic speech recognition (ASR) systems and has been proved to be quite effective in related applications such as keyword search. However, word posterior probability tends to overestimate the true probability of a hypothesis, as it is computed on a subset of the total hypothesis space. In this paper, we show that a more accurate estimation of posterior can be obtained by using a calibration method based on the conditional random field (CRF) model. By using calibrated posterior estimation for keyword search task, we obtain a maximum absolute gain of 1.15% for single-word keyword search on the maximum term-weighted value (MTWV) metric on the OpenKWS14 Tamil dataset.
Extending dependencies with conditions for data cleaning

Data cleaning aims to effectively detect and repair errors and inconsistencies in real life data. The increasing costs and risks of dirty data highlight the need for data cleaning techniques. This paper provides an overview of recent advances in data cleaning, based on conditional dependencies, an extension of functional and inclusion dependencies for characterizing the consistency of relational data.
An Automated Approach for Writing Alloy Specifications Using Instances

We present aDeryaft, a novel technique for automating the writing of specifications in Alloy-a first-order relational logic with transitive closure. Alloy is particularly suitable for specifying structural properties of software, and has steadily been gaining popularity due to the rapid feedback that its SAT-based analyzer provides fully automatically. Alloy users however, still have to manually write specifications in a declarative language and use a paradigm that is different from the commonly used imperative programming paradigm. aDeryaft assists Alloy users in writing their specifications by providing a novel specification-writing approach, which is particularly tailored to users, such as engineers or practitioners in industry, who may not have much prior experience or proficiency in Alloy or similar logics. The user constructs by hand a few small concrete instances that represent the constraints of the software structure they want to specify. aDeryaft then fully automatically generates an executable Alloy specification, which represents the constraints that summarize the given structures. The generated specification is fully executable. For example, the Alloy Analyzer can use it to systematically enumerate a large number of concrete instances that satisfy the same constraints as the given instances. Indeed, a user may use aDeryaft to generate partial specifications while the user writes the rest of the specification by hand. To efficiently generate Alloy specifications, aDeryaft exploits the relational basis of Alloy and formulates graph properties that are likely to hold for the given instances. It then checks the properties for these instances and translates the valid properties into Alloy constraints, which it outputs as an Alloy specification. We illustrate aDeryaft's constraint generation on a variety of commonly used data structures.
Witty divas, nice mothers and tough girls in a sexist world: experiences and strategies of female influencers in online political debates

The aim of this article is to explain the reasons behind the persisting gender gap in online political communication by examining the experience of women who are among the most visible and active participants in the online discussions on political issues. Data gathered through in-depth interviews reveal that women employ specific strategies to succeed in this environment and to deal with sexist ad hominem assaults – they either emphasize qualities traditionally considered feminine and act as ‘witty divas’ or ‘nice mothers’ or accommodate to the masculine character of the environment by adopting a ‘tough approach’. Some of them even experiment with masculine profiles. These strategies seem to reproduce the traditional patriarchal binary frame and show that even influential women strategically subordinate themselves to the rules of the male-dominated participatory sphere.
Stylized Depiction in Mixed Reality

—The combination of real video images and virtual graphical objects is a basic principle in many computer graphics applications. In recent years, mixed reality has become a widespread technique for superimposing registered three-dimensional models on the real world. Whereas most mixed reality applications use conventional photorealistic rendering methods for overlaying their graphical content, alternative display methods are being developed. We discuss the use of artistic and illustrative rendering techniques for combined real-virtual environments. This concept has a dual purpose. Depending on the type of stylization used, a novel user experience can be created. For instance, the use of a technical illustration style can provide a more appropriate and useful display in a technical design application. Moreover, since the difference in visual realism between real and virtual scene elements is reduced, the environment can become more immersive for the user. In this article, we give a survey of methods for the artistic depiction of combined real-virtual environments and discuss potential applications.
Project Title-Puzzle Solver EE 368 – Digital Image Processing Sravan Bhagavatula

Most jigsaw puzzles that are available today consist of several 100 pieces of a single image, and can take several hours to solve. This project proposes to solve the puzzle simply by using a picture of all of the pieces, and an image of the final solution. Keywords-component; jigsaw puzzle; Scale Invariant Feature Transform;SIFT
Moment Conditions for Almost Stochastic Dominance

This study establishes necessary conditions for Almost Stochastic Dominance criteria of various orders. These conditions take the form of restrictions on algebraic combinations of moments of the probability distributions in question. The relevant set of conditions depends on the relevant order of ASD but not on the critical value for the admissible violation area. These conditions can help to reduce the information requirement and computational burden in practical applications. A numerical example and an empirical application to historical stock market data illustrate the moment conditions. The first four moment conditions in particular seem appealing for many applications.