Miracle-dz/UniFAR-FTUs huggingface dataset:
KELOP: distributed key-value lookup in wireless ad hoc networks

It is critical to discover and utilized shared services and resources in wireless ad hoc networks. While wireline networks can use domain name system (DNS) to perform such key-value lookups, designing scalable key-value lookup protocols with high success rates and low message overhead in the dynamic topologies of wireless ad hoc networks presents a nontrivial challenge. In this paper, we present KELOP, a key-value lookup protocol for wireless ad hoc networks. KELOP is a fully distributed best-effort protocol that relies only on the local information stored at each node to locate the closest estimates of the target. This strategy results in remarkably low control-message overhead. Simulation results show that, in addition to low message overhead, KELOP is able to provide lookup success rate close to 100% in most cases.
Recognition confidence scoring and its use in speech understanding systems

In this paper we present an approach to recognition confidence scoring and a set of techniques for integrating confidence scores into the understanding and dialogue components of a speech understanding system. The recognition component uses a multi-tiered approach where confidence scores are computed at the phonetic, word, and utterance levels. The scores are produced by extracting confidence features from the computation of the recognition hypotheses and processing these features using an accept/reject classifier for word and utterance hypotheses. The scores generated by the confidence classifier can then be passed on to the language understanding and dialogue modeling components of the system. In these components the confidence scores can be combined with linguistic scores and pragmatic constraints before the system makes a final decision about the appropriate action to be taken. To evaluate the system, experiments were conducted using the jupiter weather information system. An evaluation of the confidence classifier at the word-level shows that the system detects 66% of the recognizer? s errors with a false detection rate on correctly recognized words of only 5%. An evaluation was also performed at the understanding level using key-value pair concept error rate as the evaluation metric. When confidence scores were integrated into the understanding component of the system, a relative reduction of 35% in concept error rate was achieved.
Identification and Comparative Profiling of miRNAs in an Early Flowering Mutant of Trifoliate Orange and Its Wild Type by Genome-Wide Deep Sequencing

MicroRNAs (miRNAs) are a new class of small, endogenous RNAs that play a regulatory role in various biological and metabolic processes by negatively affecting gene expression at the post-transcriptional level. While the number of known Arabidopsis and rice miRNAs is continuously increasing, information regarding miRNAs from woody plants such as citrus remains limited. Solexa sequencing was performed at different developmental stages on both an early flowering mutant of trifoliate orange (precocious trifoliate orange, Poncirus trifoliata L. Raf.) and its wild-type in this study, resulting in the obtainment of 141 known miRNAs belonging to 99 families and 75 novel miRNAs in four libraries. A total of 317 potential target genes were predicted based on the 51 novel miRNAs families, GO and KEGG annotation revealed that high ranked miRNA-target genes are those implicated in diverse cellular processes in plants, including development, transcription, protein degradation and cross adaptation. To characterize those miRNAs expressed at the juvenile and adult development stages of the mutant and its wild-type, further analysis on the expression profiles of several miRNAs through real-time PCR was performed. The results revealed that most miRNAs were down-regulated at adult stage compared with juvenile stage for both the mutant and its wild-type. These results indicate that both conserved and novel miRNAs may play important roles in citrus growth and development, stress responses and other physiological processes.
Membrane Protein Stability Analyses by Means of Protein Energy Profiles in Case of Nephrogenic Diabetes Insipidus

Diabetes insipidus (DI) is a rare endocrine, inheritable disorder with low incidences in an estimated one per 25,000–30,000 live births. This disease is characterized by polyuria and compensatory polydypsia. The diverse underlying causes of DI can be central defects, in which no functional arginine vasopressin (AVP) is released from the pituitary or can be a result of defects in the kidney (nephrogenic DI, NDI). NDI is a disorder in which patients are unable to concentrate their urine despite the presence of AVP. This antidiuretic hormone regulates the process of water reabsorption from the prourine that is formed in the kidney. It binds to its type-2 receptor (V2R) in the kidney induces a cAMP-driven cascade, which leads to the insertion of aquaporin-2 water channels into the apical membrane. Mutations in the genes of V2R and aquaporin-2 often lead to NDI. We investigated a structure model of V2R in its bound and unbound state regarding protein stability using a novel protein energy profile approach. Furthermore, these techniques were applied to the wild-type and selected mutations of aquaporin-2. We show that our results correspond well to experimental water ux analysis, which confirms the applicability of our theoretical approach to equivalent problems.
UML2ALLOY: A tool for lightweight modelling of discrete event systems

Alloy is a textual language developed by Daniel Jackson and his team at MIT. It is a formal language, which has a succinct syntax and allows specification and automatic analysis of a wide variety of systems. On the other hand, the Unified Modelling Language (UML) is a semi-formal language, which is accepted by the software engineering community as the defacto standard for modelling, specification and implementation of Object based systems. This paper studies the integration of the UML and Alloy into a single CASE tool, which aims to take advantage of the positive aspect of both the UML and Alloy. Alloy and UML specification provide two views of the system. In order to synchronise the two views, we make use of the MDA style transformation. In particular, we shall present a Meta Object Facility (MOF) compliant metamodel for Alloy and define a model transformation from the UML metamodel to the Alloy metamodel. Based on the approach presented in the paper, we have implemented a tool called UML2Alloy for the modelling and analysis of Discrete Event Systems. To evaluate the tool, the paper presents a case study involving the modelling and analysis of a prototype manufacturing system.
Dynamic Bayesian Networks for NLU Simulation with Applications to Dialog Optimal Strategy Learning

In this paper, we propose to add a model for NLU-related error generation in a modular environment for computer-based simulation of man-machine spoken dialogs. This model is jointly designed with a user model. Both of them are based on the same underlying Bayesian network used with different parameters in such a way that it can generate a consistent user behavior, according to a goal and the interaction history, and been used as a concept classifier. The proposed simulation environment was used to train a reinforcement-learning algorithm on a simple form-filling task and the results of this experiment show that the addition of the NLU model helps pointing out problematic situations that may occur because of misunderstandings and modifying the dialog strategy accordingly
Runtime estimation for enumerating all mutually orthogonal diagonal Latin squares of order 10

In the present paper we estimate how long it will take state-of-the-art combinatorial algorithms to enumerate all possible mutually orthogonal diagonal Latin squares of order 10. For this purpose we first evaluate the performance of DLX algorithm and contemporary algorithms for solving SAT in application to finding orthogonal mates of an arbitrary diagonal Latin square of order 10. Then we estimate the number of diagonal Latin squares of order 10 and use this information in combination with some techniques for exploiting symmetries and equivalences to approximate the amount of time it would take to process them using existing hardware.
n-3 Polyunsaturated fatty acid supplementation reverses stress-induced modifications on brain monoamine levels in mice Published, JLR Papers in Press, November 8, 2007.

The aim of this study was to examine the effects of supplementation with n-3 polyunsaturated fatty acids (PUFAs) on stress responses in mice subjected to an unpredictable chronic mild stress (UCMS) procedure. Stress-induced modifications in coat and aggressiveness were evaluated, and phospholipid PUFA profiles and monoamine levels were analyzed in the frontal cortex, hippocampus, and striatum. The results showed that repeated exposure to mild stressors induced degradation in the physical state of the coat, lowered body weight gain, and increased aggressiveness, without any effect of n-3 PUFA supplementation. The UCMS induced a significant decrease in the levels of norepinephrine in the frontal cortex and striatum, and a nonsignificant decrease in the hippocampus. The tissue levels of serotonin (5-HT) were 40% to 65% decreased in the three brain regions studied. Interestingly, the n-3 PUFA supplementation reversed this stress-induced reduction in 5-HT levels. These findings showed that supplementation in n-3 long-chain PUFAs might reverse certain effects of UCMS in cerebral structures involved in stress-related behaviors.
Automatic face recognition for film character retrieval in feature-length films

The objective of this work is to recognize all the frontal faces of a character in the closed world of a movie or situation comedy, given a small number of query faces. This is challenging because faces in a feature-length film are relatively uncontrolled with a wide variability of scale, pose, illumination, and expressions, and also may be partially occluded. We develop a recognition method based on a cascade of processing steps that normalize for the effects of the changing imaging environment. In particular there are three areas of novelty: (i) we suppress the background surrounding the face, enabling the maximum area of the face to be retained for recognition rather than a subset; (ii) we include a pose refinement step to optimize the registration between the test image and face exemplar; and (iii) we use robust distance to a sub-space to allow for partial occlusion and expression change. The method is applied and evaluated on several feature length films. It is demonstrated that high recall rates (over 92%) can be achieved whilst maintaining good precision (over 93%).
Dictionary-free categorization of very similar objects via stacked evidence trees

Current work in object categorization discriminates among objects that typically possess gross differences which are readily apparent. However, many applications require making much finer distinctions. We address an insect categorization problem that is so challenging that even trained human experts cannot readily categorize images of insects considered in this paper. The state of the art that uses visual dictionaries, when applied to this problem, yields mediocre results (16.1% error). Three possible explanations for this are (a) the dictionaries are unsupervised, (b) the dictionaries lose the detailed information contained in each keypoint, and (c) these methods rely on hand-engineered decisions about dictionary size. This paper presents a novel, dictionary-free methodology. A random forest of trees is first trained to predict the class of an image based on individual keypoint descriptors. A unique aspect of these trees is that they do not make decisions but instead merely record evidence-i.e., the number of descriptors from training examples of each category that reached each leaf of the tree. We provide a mathematical model showing that voting evidence is better than voting decisions. To categorize a new image, descriptors for all detected keypoints are “dropped” through the trees, and the evidence at each leaf is summed to obtain an overall evidence vector. This is then sent to a second-level classifier to make the categorization decision. We achieve excellent performance (6.4% error) on the 9-class STONEFLY9 data set. Also, our method achieves an average AUC of 0.921 on the PASCAL06 VOC, which places it fifth out of 21 methods reported in the literature and demonstrates that the method also works well for generic object categorization.
Design of a microfabricated magnetic cell separator

A new magnetic separation idea utilizing several ideas from microfabrication and nanomagnetics is presented. The basic idea comes from our earlier work using asymmetry in obstacles and Brownian motion to effect separation of objetcs [10] by moving them in streams whose angle to the hydrodynamic average velocity is a function of the diffusion coefficient of the object. The device we propose here is not technically a Brownian ratchet device but uses the idea of force which acts at angle to the hydrodynamic flow. In our case, the force is generated by a magnetic field gradient which comes from an array of magnetized wires which lie at an angle 0 to a hydrodynamic field flow. The sum of the hydrodynamic force and the magnetic force create a new vector which as in the case of the Brownian ratchet moves the cell out of the main stream direction.
Using Web Quality Models and Questionnaires for Web Applications Understanding and Evaluation

As web applications (WebApps) continue to gain popularity, evaluating new generation WebApps poses challenges regarding use of current quality models and their included (sub-) characteristics. For instance, communicability and sense of community are characteristics often neglected in quality modeling. Considering the recently issued ISO/IEC 25010/25012 standards, we utilize our previously developed and recently revised quality models and framework, 2Q2U (Quality, Quality in use, actual Usability and User experience) in combination with SIQinU (Strategy to Improve Quality in Use), a purpose oriented improvement strategy. We show SIQinU's flexible approach through using questionnaires to measure and evaluate quality in use for WebApps. To illustrate this approach a practical case study for evaluating pragmatic and hedonic user perceptions for two online radio WebApps is conducted.
Gender Differences in the Initiation of Negotiations: A Meta-Analysis

Gender differences in the initiation of negotiation have been suggested to reinforce unequal distributions of resources between men and women. Because previous research had yielded heterogeneous results, the authors conducted a meta-analysis investigating gender differences in initiating negotiation. On the basis of social role theory, they hypothesized that women are less likely to initiate negotiations than men, but also that the effect varies depending on characteristics of the immediate negotiation situation and the wider societal context. The meta-analysis comprised 55 effect sizes with 17,504 individuals, including both students and employees. A random-effects model confirmed that women were indeed less likely to initiate negotiations than men (g = 0.20). Additional moderator analyses, tested with mixed-effects models and metaregressions, revealed that gender differences were smaller when situational ambiguity regarding the appropriateness of negotiating was low rather than high as well as when situational cues were more consistent with the female gender role than with the male gender role. Gender differences decreased by year of publication (from 1977 to 2016) but were unrelated to the degree of gender inequality in the countries in which the studies were conducted. The authors conclude that gender differences in the initiation of negotiation exist, but they are small and context-bound. Finally, they discuss mechanisms that alter the gender difference with a particular focus on potential starting points for practical interventions.
WEIGHTED PRINCIPAL COMPONENT MLLR FOR SPEAKER ADAPTATION

We present two new speaker adaptation methods which apply principal component analysis to maximum likelihood linear regression (MLLR) framework. If we apply MLLR after transforming the baseline mean vectors by their eigenvectors, the variance of the estimates for the MLLR matrix are inversely proportional to their corresponding eigenvalues. We describe two techniques to reduce the variance of the estimation, Principal Component MLLR (PC-MLLR) and Weighted Principal Component MLLR (WPC-MLLR). In experiments using sentences from the 1994 DARPA Wall Street Journal evaluation, the use of WPC-MLLR provided a relative reduction in word error rates of 15.1% for non-native speakers and 6.0% for native speakers compared to conventional MLLR.
Dynamic workload peak detection for slack management

In this paper an analytical study on dynamism and possibilities on slack exploitation by dynamic power management is presented. We introduce a specific workload decomposition method for work required for (streaming) application processing data tokens (e.g. video frames) with work behaviour patterns as a mix of periodic and aperiodic patterns. It offers efficient and computationally light method for speculation on considerable work variations and its exploitation in energy saving techniques. It is used by a dynamic power management policy which has low overhead and reduces both requirements for buffering space, and deadline misses (increase QoS). We evaluate our policy in experiments on MPEG4 decoding of several different input sequences and present results.
Construction of a Vibrio cholerae Vaccine Candidate Using Transposon Delivery and FLP Recombinase-Mediated Excision

ABSTRACT Recent efforts to develop a vaccine against the diarrheal disease cholera have focused on the use of live attenuated strains of the causative organism, Vibrio cholerae. The Ogawa lipopolysaccharide phenotype is expressed by many epidemic strains, and motility defects reduce the risk of reactive diarrhea in vaccine recipients. We therefore converted a motile Inaba+ vaccine candidate, Peru-2, to a nonmotile Ogawa+ phenotype using amariner-based transposon carrying rfbT, the gene required for expression of the Ogawa phenotype. Analysis of 22 nonmotile Peru-2 mutants showed that two were Ogawa+, and both of these strains had insertions in the flgE gene. It was possible to convert these strains to antibiotic sensitivity by introducing a recombinase that acts on sites flanking the antibiotic marker on the transposon. The resulting strains are competent for colonization in infant mice and may therefore be suitable as vaccine candidates for use either independently or in a combination with strains of different biotypes and serotypes.
First Steps Toward a Cryptography-Aware Language and Compiler

When developing secure, high-performance cryptographic software, the programmer is presented with a wide range of problems. Not only must they be conversant with pertinent scientific results, they must efficiently translate said results into a practical context. Unlike when writing normal programs, they are given little help from either the language or compiler: both are typically too general purpose to offer domain specific optimisation or analysis that would save the programmer time and reduce the potential for error. As a step toward solving this problem we present CAO, a cryptography-aware domain-specific language and associated compiler system. Rather than being a panacea, we pitch CAO as a mechanism for transferring and automating the expert knowledge of cryptographers into a form which is accessible to anyone writing security conscious software.
A Comparison of the Lubricating Mechanisms of Graphite Fluoride and Molybdenum Disulfide Films

A microscopic study of 440 C steel sliding surfaces lubricated by graphite fluoride or molybdenum disulfide solid lubricant rubbed films was conducted. The sliding surfaces, along with the friction, wear, and wear life were observed as a function of the number of sliding revolutions in three different atmospheres: moist air (10,000 ppm H2O), dry air (less than 20 ppm H2O), or dry argon (less than 20 ppm H2O). In general, the lubricating mechanisms of the two solid lubricants were found to be relatively similar; that is, a dynamic, thin, layer-like film (which sheared on relative motion) was formed between the two metallic surfaces. The mechanisms of failure were found to be somewhat different, however. Failure of MoS2 films was very dependent on atmospheric degradation, while that of graphite fluoride films was more dependent on flow of the lubricant film out of the contact zone
TomatEST database: in silico exploitation of EST data to explore expression patterns in tomato species

TomatEST is a secondary database integrating expressed sequence tag (EST)/cDNA sequence information from different libraries of multiple tomato species. Redundant EST collections from each species are organized into clusters (gene indices). A cluster consists of one or multiple contigs. Multiple contigs in a cluster represent alternatively transcribed forms of a gene. The set of stand-alone EST sequences (singletons) and contigs, representing all the computationally defined ‘Transcript Indices’, are annotated according to similarity versus protein and RNA family databases. Sequence function description is integrated with the Gene Ontologies and the Enzyme Commission identifiers for a standard classification of gene products and for the mapping of the expressed sequences onto metabolic pathways. Information on the origin of the ESTs, on their structural features, on clusters and contigs, as well as on functional annotations are accessible via a user-friendly web interface. Specific facilities in the database allow Transcript Indices from a query be automatically classified in Enzyme classes and in metabolic pathways. The ‘on the fly’ mapping onto the metabolic maps is integrated in the analytical tools. The TomatEST database website is freely available at .
Generating a Yiddish Speech Corpus, Forced Aligner and Basic ASR System for the AHEYM Project

To create automatic transcription and annotation tools for the AHEYM corpus of recorded interviews with Yiddish speakers in Eastern Europe we develop initial Yiddish language resources that are used for adaptations of speech and language technologies. Our project aims at the development of resources and technologies that can make the entire AHEYM corpus and other Yiddish resources more accessible to not only the community of Yiddish speakers or linguists with language expertise, but also historians and experts from other disciplines or the general public. In this paper we describe the rationale behind our approach, the procedures and methods, and challenges that are not specific to the AHEYM corpus, but apply to all documentary language data that is collected in the field. To the best of our knowledge, this is the first attempt to create a speech corpus and speech technologies for Yiddish. This is also the first attempt to work out speech and language technologies to transcribe and translate a large collection of Yiddish spoken language resources.