Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaker diarization of French broadcast news

We report results on speaker diarization of French broadcast news and talk shows on current affairs. This speaker diarization process is a multistage segmentation and clustering system. One of the stages is agglomerative clustering using state-of-the-art speaker identification methods (SID). For the QMMs used in this stage, we tried many different feature parameters, including MFCCs, Gaussianized MFCCs, Gaussianized MFCCs with cepstral mean subtraction, and Gaussianized MFCCs with cepstral mean substraction containing only frames with high energy. We found that this last set of feature parameters gave the best results. Compared to Gaussianized MFCCs, these features reduced the diarization error rate (DER) by 12% on a development set and by 19% on a test set. We also combined clusters resulting from Gaussianized and non-Gaussianized feature sets. This cluster combination resulted in another 4% reduction in DER for both the development and the test sets. The best DER we have achieved is 15.4% on the development set, and 14.5% on the test set.
WSD as a Distributed Constraint Optimization Problem

This work models Word Sense Disambiguation (WSD) problem as a Distributed Constraint Optimization Problem (DCOP). To model WSD as a DCOP, we view information from various knowledge sources as constraints. DCOP algorithms have the remarkable property to jointly maximize over a wide range of utility functions associated with these constraints. We show how utility functions can be designed for various knowledge sources. For the purpose of evaluation, we modelled all words WSD as a simple DCOP problem. The results are competitive with state-of-art knowledge based systems.
Diagnostic Reverse-Transcription Polymerase Chain Reaction Kit for Filoviruses Based on the Strain Collections of all European Biosafety Level 4 Laboratories

Abstract A network of European biosafety level 4 laboratories has designed the first industry-standard molecular assay for all filoviruses species, based on the strain collections of all participants. It uses 5 optimized L gene primers and 3 probes, as well as an internal control with a separate detection probe. Detection limits (probit analysis, 95% detection chance) were as follows: Zaire ebolavirus, 487 copies/mL of plasma; Sudan ebolavirus Maleo, 586 copies/mL; Sudan ebolavirus Gulu, 1128 copies/mL; Cote d'Ivoire ebolavirus, 537 copies/mL; Reston ebolavirus, 4546 copies/mL; Lake Victoria marburgvirus Musoke, 860 copies/mL; and Lake Victoria marburgvirus Ravn, 1551 copies/mL. The assay facilitates reliable detection or exclusion screening of filovirus infections.
A Large-Scale Study of Online Shopping Behavior

The continuous growth of e-commerce has stimulated great interest in generating theories and models for online consumer behavior. While studies on online consumer behavior are widespread, research on relating Internet browsing activities to online shopping behavior are scarce. This paper provides an exploratory analysis on the relationship between online browsing habits and consumers' pre-shopping effort, as one of the indicators of shopping behavior. The data used in this study was extracted from 88,637 users with more than half a million shopping instances from two large online retailers, Amazon and Walmart. Our findings provide insights for scholars to form hypotheses and design models or theories to explain online consumer behavior. Practitioners may also use the results of this study to make strategic decisions.
CspA Regulates Pigment Production in Staphylococcus aureus through a SigB-Dependent Mechanism

ABSTRACT We report that the cold shock protein CspA of Staphylococcus aureus is required for maximal production of pigment. Results from transcriptional studies revealed that loss of CspA resulted in decreased expression of genes needed for the biosynthesis of 4,4′-diaponeurosporene and the alternative sigma factor SigB.
Thermodynamic Hypothesis as Social Choice: An Impossibility Theorem for Protein Folding

Protein Folding is concerned with the reasons and mechanism behind a protein's tertiary structure. The thermodynamic hypothesis of Anfinsen postulates an universal energy function (UEF) characterizing the tertiary structure, defined consistently across proteins, in terms of their aminoacid sequence. We consider the approach of examining multiple protein structure descriptors in the PDB (Protein Data Bank), and infer individual preferences, biases favoring particular classes of aminoacid interactions in each of them, later aggregating these individual preferences into a global preference. This 2-step process would ideally expose intrinsic biases on classes of aminoacid interactions in the UEF itself. The intuition is that any intrinsic biases in the UEF are expressed within each protein in a specific manner consistent with its specific aminoacid sequence, size, and fold (consistently with Anfinsen's thermodynamic hypothesis), making a 1-step, holistic aggregation less desirable. Our intention is to illustrate how some impossibility results from voting theory would apply in this setting, being possibly applicable to other protein folding problems as well. We consider concepts and results from voting theory and unveil methodological difficulties for the approach mentioned above. With our observations, we intend to highlight how key theoretical barriers, already exposed by economists, can be relevant for the development of new methods, new algorithms, for problems related to protein folding.
Effective personalized mobile search using KNN

Effective Personalized Mobile Search Using KNN, implements an architecture to improve user's personalization effectiveness over large set of data maintaining security of the data. User preferences are gathered through clickthrough data. Clickthrough data obtained is sent to the server in encrypted form. Clickthrough data obtained is classified into content concepts and location concepts. To improve classification and minimize processing time, KNN(K Nearest Neighborhood) algorithm is used. Preferences identified(location and content) are merged to provide effective preferences to the user. System make use of four entropies to balance weight between content concepts and location concepts. System implements client server architecture. Role of client is to collect user queries and to maintain them in files for future reference. User preference privacy is ensured through privacy parameters and also through encryption techniques. Server is responsible to carry out the tasks like training, reranking of the search results obtained and the concept extraction. Experiments are carried out on Android based mobile. Results obtained through experiments show that system significantly gives improved results over previous algorithm for the large set of data maintaining security.
Stable Interest Point Detection under Illumination Changes Using Colour Invariants

Stable interest point detection is relevant for many computer vision applications. However, most detectors are sensitive to illumination changes, as their response varies with image contrast. In the best case, detection stability is increased using a simple image formation model assuming that illumination effects cause slowly varying changes in the image. This does not accurately model shadows and shading (interaction between illumination and scene geometry). Therefore, a new detection method is presented here, which is based on the very popular Harris detector and on the m space [5]. It yields a detection which is invariant to shadows, shading and illumination colour for matte surfaces. A preprocessing scheme is proposed to reduce the sensitivity to colour artifacts caused by demosaicing. The new detector is evaluated on real images acquired under different illuminations by comparison with other interest point detectors. The detection stability is well enhanced, especially for scenes with complex geometry.
Expression of the ‘DEAD box’ RNA helicase p68 is developmentally and growth regulated and correlates with organ differentiation/maturation in the fetus

The human DEAD box protein p68 is an established RNA‐dependent ATPase and RNA helicase. p68 has been highly conserved in evolution and appears to be essential for normal growth, suggesting that this protein plays an important role in the cell. Although the biochemical activities of p68 are fairly well characterized, little is known about its biological function. This report shows that p68 is detectable in quiescent cell lines, but its expression is induced by serum, suggesting that this protein may play a role in cell growth. It is also shown that both p68 mRNA and protein are differentially expressed in adult tissues; in this case, however, the levels do not always correlate with proliferation status, suggesting that the regulation of expression in the animal may be different from that in cell lines. Finally, it is shown that p68 expression is developmentally regulated and appears to correlate with organ differentiation/maturation. These findings suggest that p68 expression may not simply reflect proliferation/differentiation status and that it appears to be regulated in a more complex way. © 1998 John Wiley & Sons, Ltd.
Reanimating the dead: reconstruction of expressive faces from skull data

Facial reconstruction for postmortem identification of humans from their skeletal remains is a challenging and fascinating part of forensic art. The former look of a face can be approximated by predicting and modeling the layers of tissue on the skull. This work is as of today carried out solely by physical sculpting with clay, where experienced artists invest up to hundreds of hours to craft a reconstructed face model. Remarkably, one of the most popular tissue reconstruction methods bears many resemblances with surface fitting techniques used in computer graphics, thus suggesting the possibility of a transfer of the manual approach to the computer. In this paper, we present a facial reconstruction approach that fits an anatomy-based virtual head model, incorporating skin and muscles, to a scanned skull using statistical data on skull / tissue relationships. The approach has many advantages over the traditional process: a reconstruction can be completed in about an hour from acquired skull data; also, variations such as a slender or a more obese build of the modeled individual are easily created. Last not least, by matching not only skin geometry but also virtual muscle layers, an animatable head model is generated that can be used to form facial expressions beyond the neutral face typically used in physical reconstructions.
Impact response of composite laminates with a hemispherical indenter

A model for predicting the contact duration, force, indentation, and displacement under impact has been developed for impact of a composite laminated plate with a hemispherical indenter. The governing equations were first proposed and then solved with the initial conditions along with the peak force condition. An expression forr each parameter has been obtained in a simple expression through straightforward derivation. Both static and dynamic tests have been conducted. Ten impact tests were conducted using a weight drop tower tester. Comparison between the, model predictions and the experimental data on the impact duration and impulse are provided, and were found to be within 14% for all tests involved. Comparison of the impact force-history also shows good accord.
Role of carbon nanotube dispersion in fracture toughening of plasma sprayed aluminum oxide-carbon nanotube nanocomposite coating

OF THE DISSERTATION ROLE OF CARBON NANOTUBE DISPERSION IN FRACTURE TOUGHENING OF PLASMA SPRAYED ALUMINUM OXIDE CARBON NANOTUBE NANOCOMPOSITE COATING by Kantesh Balani Florida International University, 2007 Miami, Florida Professor Arvind Agarwal, Major Professor Aluminum oxide (A12 0 3 , or alumina) is a conventional ceramic known for applications such as wear resistant coatings, thermal liners, heaters, crucibles, dielectric systems, etc. However applications of A120 3 are limited owing to its inherent brittleness. Due to its excellent mechanical properties and bending strength, carbon nanotubes (CNT) is an ideal reinforcement for A12 0 3 matrix to improve its fracture toughness. The role of CNT dispersion in the fracture toughening of the plasma sprayed A120 3-CNT nanocomposite coating is discussed in the current work. Pretreatment of powder feedstock is required for dispersing CNTs in the matrix. Four coatings namely spray dried A120 3 (A-SD), A120 3 blended with 4wt. % CNT (A4C-B), composite spray dried A120 3-4wt. % CNT (A4C-SD) and composite spray dried A120 3-8wt. % CNT (A8CSD), are synthesized by plasma spraying. Owing to extreme temperatures and velocities involved in the plasma spraying of ceramics, retention of CNTs in the resulting coatings necessitates optimizing plasma processing parameters using an inflight particle diagnostic sensor. A bimodal microstructure was obtained in the matrix that consists of fully melted
Probabilistic Testability Measure Before Pseudorandom Test Generation

It is proposed more suitable method of the testability analysis of the digital systems in comparison with known classical algorithmic and probabilistic methods. It is oriented on the complex combinational and sequential asynchronous logic circuits. Estimation of the testability is based on the topological analysis of the circuit. The new method and above mentioned methods were approved on the circuits of different complexity, including circuits from ISCAS'85, '89 Libraries. Proposed method can be used on gate-level and RT-level circuit description
Apoptosis in bovine granulosa cells in relation to steroid synthesis, cyclic adenosine 3',5'-monophosphate response to follicle-stimulating hormone and luteinizing hormone, and follicular atresia.

Apoptosis is a process of selective cell deletion implicated as a mechanism underlying the process of ovarian follicular atresia. The aims of this study were 1) to test the hypothesis that granulosa cell death during follicular (> or = 4 mm diameter) atresia in cows occurs by apoptosis and 2) to define relationships between the occurrence and degree of granulosa cell apoptosis, cAMP response to FSH or LH, extant aromatase activity, and other previously established biochemical and morphometric indices of granulosa cell function and follicular atresia in this species. Granulosa cells and follicular fluid from individual follicles 4-18 mm in diameter were collected from luteal-phase cow ovaries. Follicles were classified by morphometric criteria as "healthy" (n = 45) or atretic (n = 34). Apoptosis in granulosa cells from each follicle was inferred from detection of internucleosomal DNA cleavage by 3'-end radiolabeling; it was quantitated both subjectively from intensity of oligonucleosome labeling (apoptosis [AP] score = 0, 1, 2, or 3) and objectively by beta-counting of low-molecular weight gel fragments (labeling index; LI). Extant aromatase activity (ng estradiol produced/10(6) cells/3 h) and cAMP response (pmol/10(6) cells) to different doses of FSH or LH (1-10,000 ng/ml) was determined for granulosa cells from most healthy follicles (n = 39). Apoptosis was detected in granulosa cells from all atretic follicles as well as from 76% of healthy follicles, from 80% (16 of 20) of follicles with follicular fluid estradiol to progesterone ratios > 1, and from 71% (10 of 14) of follicles with extant aromatase activity (> 2 ng/10(6) cells/3 h). For healthy and atretic follicles, degree of DNA fragmentation was inversely related to the number of granulosa cells recovered (as percentage maximum by follicle size). In healthy follicles, FSH stimulated cAMP synthesis is a dose-dependent manner in granulosa cells from all follicles examined (> or = 4 mm), but only 36% of these had appreciable aromatase activity. The cAMP response to FSH (per cell) increased with follicle size from 4-7 mm in diameter and remained high in granulosa cells from follicles > or = 8 mm with aromatase activity; in cells without aromatase activity, cAMP response to FSH decreased with increasing follicle size > or 8 mm. The cAMP response to LH was generally low or undetectable in granulosa cells from 4-8-mm follicles; it then increased linearly with increasing follicle diameter > or = 8 mm, but to a greater degree in cells with aromatase activity than in cells without. (ABSTRACT TRUNCATED AT 400 WORDS)
Energy Efficient Dynamic Resource Allocation in NOMA Networks

Non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) is a promising technique for next generation wireless communications. Using NOMA, more than one user can access the same frequency-time resource simultaneously and multi-user signals can be separated successfully using SIC. In this paper, resource allocation algorithms for subchannel assignment and power allocation for a downlink NOMA network are investigated. Different from the existing works, here, energy efficient dynamic power allocation in NOMA networks is investigated. This problem is explored using the Lyapunov optimization method by considering the constraints on minimum user quality of service (QoS), the maximum transmit power limit. Based on the framework of Lyapunov optimization, the problem of energy efficient optimization can be broken down into three subproblems. Two of which are linear and the rest can be solved by introducing Lagrangian function. The mathematical analysis and simulation results confirm that the proposed scheme can achieve a significant utility performance gain and the energy efficiency and delay tradeoff is derived as $[{\rm O}(1/V),{\rm O}(V)]$ with $V$ as a control parameter under maintaining the queue stability.
Time refinement in a functional synchronous language

Concurrent and reactive systems often exhibit multiple time scales. For instance, in a discrete simulation, the scale at which agents communicate might be very different from the scale used to model the internals of each agent. We propose an extension of the synchronous model of concurrency, called reactive domains, to simplify the programming of such systems. Reactive domains allow the creation of local time scales and enable refinement, that is, the replacement of an approximation of a system with a more detailed version without changing its behavior as observed by the rest of the program. Our work is applied to the ReactiveML language, which extends ML with synchronous language constructs. We present an operational semantics for the extended language and a type system that ensures the soundness of programs.
Very high cycle fatigue characteristics of a chrome‐molybdenum steel treated by ultrasonic nanocrystal surface modification technique

Characterization of very high cycle fatigue (VHCF) performance is of significant issue for ensuring long-term durability and reliability of machinery and structural components due to the growing industrial demands and significant requirements of the advanced systems. In this study, VHCF characteristics of nanocrystallized skins (nanoskin) on JIS SCM435 (AISI 4137) steels were investigated as three different nanoskins on the surface, which was fabricated by altering the static load of ultrasonic nanocrystal surface modification (UNSM) treatment. The fatigue characterization, which shows linearly proportional correlation in the range of 80–120 µm depth of subsurface, was subjected to severe plastic deformation by altering the static loads of UNSM treatment to 40, 70 and 100 N, respectively. The fatigue strength increased up to 30% in the regime of VHCF. The improved strength mainly resulted from the generation of nanocrystalline structure, the enhanced surface uniformity, hardness and residual stress.
Predicting Privacy Behavior on Online Social Networks

Online Social Networks (OSNs) have come to play an increasingly important role in our social lives, and their inherent privacy problems have become a major concern for users. Can we assist consumers in their privacy decision-making practices, for example by predicting their preferences and giving them personalized advice? In order to accomplish this, we would need to study the factors that affect users’ privacy decision-making practices. In this paper, we intend to comprehensively investigate these factors in light of two common OSN scenarios: the case where other users request access to the user’s information, and the case where the user shares this information voluntarily. Using a real-life dataset from Google+ and three location-sharing datasets, we identify behavioral analogs to psychological variables that are known to affect users’ disclosure behavior: the trustworthiness of the requester/information audience, the sharing tendency of the receiver/information holder, the sensitivity of the requested/shared information, the appropriateness of the request/sharing activity, as well as some contextual information. We also explore how these factors work to affect the privacy decision making. Based on these factors we build a privacy decisionmaking prediction model that can be used to give users personalized advice regarding their privacy decisionmaking practices.
Differential Receptor Binding and Regulatory Mechanisms for the Lymphangiogenic Growth Factors Vascular Endothelial Growth Factor (VEGF)-C and -D*

VEGF-C and VEGF-D are secreted glycoproteins that induce angiogenesis and lymphangiogenesis in cancer, thereby promoting tumor growth and spread. They exhibit structural homology and activate VEGFR-2 and VEGFR-3, receptors on endothelial cells that signal for growth of blood vessels and lymphatics. VEGF-C and VEGF-D were thought to exhibit similar bioactivities, yet recent studies indicated distinct signaling mechanisms (e.g. tumor-derived VEGF-C promoted expression of the prostaglandin biosynthetic enzyme COX-2 in lymphatics, a response thought to facilitate metastasis via the lymphatic vasculature, whereas VEGF-D did not). Here we explore the basis of the distinct bioactivities of VEGF-D using a neutralizing antibody, peptide mapping, and mutagenesis to demonstrate that the N-terminal α-helix of mature VEGF-D (Phe93–Arg108) is critical for binding VEGFR-2 and VEGFR-3. Importantly, the N-terminal part of this α-helix, from Phe93 to Thr98, is required for binding VEGFR-3 but not VEGFR-2. Surprisingly, the corresponding part of the α-helix in mature VEGF-C did not influence binding to either VEGFR-2 or VEGFR-3, indicating distinct determinants of receptor binding by these growth factors. A variant of mature VEGF-D harboring a mutation in the N-terminal α-helix, D103A, exhibited enhanced potency for activating VEGFR-3, was able to promote increased COX-2 mRNA levels in lymphatic endothelial cells, and had enhanced capacity to induce lymphatic sprouting in vivo. This mutant may be useful for developing protein-based therapeutics to drive lymphangiogenesis in clinical settings, such as lymphedema. Our studies shed light on the VEGF-D structure/function relationship and provide a basis for understanding functional differences compared with VEGF-C.
Fast Unsupervised Incremental Parsing

This paper describes an incremental parser and an unsupervised learning algorithm for inducing this parser from plain text. The parser uses a representation for syntactic structure similar to dependency links which is well-suited for incremental parsing. In contrast to previous unsupervised parsers, the parser does not use part-of-speech tags and both learning and parsing are local and fast, requiring no explicit clustering or global optimization. The parser is evaluated by converting its output into equivalent bracketing and improves on previously published results for unsupervised parsing from plain text.