Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolving scale-free topologies using a Gene Regulatory Network model

A novel approach to generating scale-free network topologies is introduced, based on an existing artificial Gene Regulatory Network model. From this model, different interaction networks can be extracted, based on an activation threshold. By using an Evolutionary Computation approach, the model is allowed to evolve, in order to reach specific network statistical measures. The results obtained show that, when the model uses a duplication and divergence initialisation, such as seen in nature, the resulting regulation networks not only are closer in topology to scale-free networks, but also exhibit a much higher potential for evolution.
Robustness of several kernel-based fast adaptation methods on noisy LVCSR

We have been investigating the use of kernel methods to improve conventional linear adaptation algorithms for fast adaptation, when there are less than 10s of adaptation speech. On clean speech, we had shown that our new kernel-based adaptation methods, namely, embedded kernel eigenvoice (eKEV) and kernel eigenspace-based MLLR (KEMLLR) outperformed their linear counterparts. In this paper, we study their unsupervised adaptation performance under additive and convoluted noises using the Aurora4 Corpus, with no assumption or prior knowledge of the noise type and its level. It is found that both eKEV and KEMLLR adaptation continue to outperform MAP and MLLR, and the simple reference speaker weighting (RSW) algorithm continues to perform favorably with KEMLLR. Furthermore, KEMLLR adaptation gives the greatest overall improvement over the speaker-independent model by about 19%.
Object recognition in extended image databases using a mobile client-server architecture

This paper presents a novel approach for object recognition in extended image databases using a mobile client-server architecture. The proposed approach relies upon feature detection and description to characterize textured objects within the image. The similarity search is performed on descriptor arrays by computing the distance between the query descriptor compared with reference descriptors extracted offline. The key contributions of the approach are the high accuracy, the time-effectiveness and the scalability of the method towards large image datasets. The developed method is first, integrated on a mobile platform and, then, deployed on a client-server architecture to deal with high volume image galleries. Experiments are performed to evaluate the performances of the system in real-life environment conditions and the obtained results demonstrate the relevance of the proposed approach.
Passivity and Output Synchronization of Complex Dynamical Networks With Fixed and Adaptive Coupling Strength

This paper considers a complex dynamical network model, in which the input and output vectors have different dimensions. We, respectively, investigate the passivity and the relationship between output strict passivity and output synchronization of the complex dynamical network with fixed and adaptive coupling strength. First, two new passivity definitions are proposed, which generalize some existing concepts of passivity. By constructing appropriate Lyapunov functional, some sufficient conditions ensuring the passivity, input strict passivity and output strict passivity are derived for the complex dynamical network with fixed coupling strength. In addition, we also reveal the relationship between output strict passivity and output synchronization of the complex dynamical network with fixed coupling strength. By employing the relationship between output strict passivity and output synchronization, a sufficient condition for output synchronization of the complex dynamical network with fixed coupling strength is established. Then, we extend these results to the case when the coupling strength is adaptively adjusted. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the proposed criteria.
In for the Long Haul — Models of Sustained Graduate Support and Education

This paper seeks to articulate the problem of lack of timeliness in the provision of support for graduating students. The authors demonstrate how drawing together employability and enterprise support in the period after graduation can address that problem and present a narrative of a knowledge exchange (KE), showing how KE has the potential to enhance the delivery of enterprise education. Two distinct areas of literature provide the theoretical basis for the paper: the extensive enterprise education literature and the much less extensive work on KE and knowledge transfer (KT). The authors explain their KE process and draw on external and internal evaluation evidence from graduate support programmes to highlight the importance of links between theory and practice in delivery settings. They envisage a model that does not treat entrepreneurship and employment as necessarily separate career choices, recognizes the need to align funding for both streams of support, reinforces the value of engaging with employers to develop graduate career options, and emphasizes the importance of a focus on the years after graduation. The paper contributes to the debate about models of enterprise education and provides insight into KE in this context.
SPH Fluids for Viscous Jet Buckling

We present a novel meshfree technique for animating free surface viscous liquids with jet buckling effects, such as coiling and folding. Our technique is based on Smoothed Particle Hydrodynamics (SPH) fluids and allows more realistic and complex viscous behaviors than the preceding SPH frameworks in computer animation literature. The viscous liquid is modeled by a non-Newtonian fluid flow and the variable viscosity under shear stress is achieved using a viscosity model known as Cross model. The proposed technique is efficient and stable, and our framework can animate scenarios with high resolution of SPH particles in which the simulation speed is significantly accelerated by using Computer Unified Device Architecture (CUDA) computing platform. This work also includes several examples that demonstrate the ability of our technique.
Long-Term Benzodiazepine Use and Salivary Cortisol: The Netherlands Study of Depression and Anxiety (NESDA)

Background: As benzodiazepines (BZDs) have anxiolytic effects, it is expected that they influence the stress system. During short-term treatment, BZD use was found to suppress cortisol levels. However, little research has been done on the effects of long-term BZD administration on the hypothalamic-pituitary-adrenal (HPA) axis. Methods: The association between long-term BZD use and cortisol levels was investigated in subjects of the Netherlands Study of Depression and Anxiety with a lifetime diagnosis of anxiety or depression (n = 1531). The subjects were categorized as "daily BZD users" (n = 96), "infrequent BZD users" (n = 172), and "nonusers" (n = 1263). Possible associations between characteristics of BZD use (dose, duration, and dependence) and salivary cortisol levels were analyzed. Main Outcome Measure: Subjects provided 7 saliva samples, from which 4 cortisol indicators were calculated: the cortisol awakening response, diurnal slope, evening cortisol, and cortisol suppression after ingestion of 0.5 mg of dexamethasone. Results: Daily users used BZDs for a median duration of 26.5 months and had a median daily dosage of 6.0 mg as measured in diazepam equivalents. Evening cortisol levels were significantly lower in daily users (P = 0.004; effect size: d = 0.24) and infrequent users (P = 0.04; effect size: d = 0.12) compared to nonusers. We did not find significant differences in the cortisol awakening response, diurnal slope, or in the dexamethasone suppression test. Conclusions: Despite the finding of slightly lower evening cortisol levels in daily and infrequent BZD users compared to nonusers, results indicate that long-term BZD use is not convincingly associated with HPA axis alterations.Abbreviations: BZD - benzodiazepines, HPA axis - hypothalamic-pituitary-adrenal axis, CAR - cortisol awakening response, DST - dexamethasone suppression test
Grayscale medical image compression using feedforward neural networks

In this paper, feedforward neural network trained with the backpropagation algorithm is proposed to compress grayscale medical images. In this new method, a three hidden layer feedforward network (FFN) is applied directly as the main compression algorithm to compress an MRI image. After training with sufficient sample images, the compression process will be carried out on the target image. The coupling weights and activation values of each neuron in the hidden layer will be stored after training. Compression is then achieved by using smaller number of hidden neurons as compare to the number of image pixels due to lesser information being stored. Experimental results show that the FFN is able to achieve comparable compression performance to popular existing medical image compression schemes such as JPEG2000 and JPEG-LS.
Biological Activity of Chemical Compounds and Their Molecular Structure-Information Approach

A method is proposed for bioscreening chemical compounds. We propose the systemic signs within the framework of an informational approach and the statistical method of compare of molecular qualitative characters. Using the methods of information theory, we offer four classification rules that allow statistically reliably distinguish preparations with high biological action (radioprotection). For the practical use of the rules is sufficient to know only the atomic structure of the molecule. We also use a descriptor that describes the average quasi-valence number of molecules. Quasi-valence number associated with the electrostatic potential of the molecule. It is established that the biological activity of chemical compounds is related with the existence of threshold effects. We have also demonstrated that mathematical informational function is related to the physical properties of molecules (hydrophobicity, electrostatic potential).
Green cooperative communication techniques for intelligent transportation systems

The current scenario of transportation infrastructure demands the need for developing efficient intelligent transportation systems (ITS) because of the increased population, changes in population density, traffic congestion, etc. Recent literature on ITS discuss on the need for green cooperative diversity techniques to improve the energy efficiency of the wireless nodes which are embedded in the transportation infrastructure. In the present work, we propose single-input-multiple-output (SIMO) and spatial modulation (SM) techniques for multiple antenna cooperative ITS in order to improve the energy efficiency of wireless nodes. Moreover, the symbol error probability (SEP) performance and energy efficiency of the proposed techniques are analyzed and compared with the traditional techniques. From the simulation results, it has been inferred that energy efficiency of cooperative ITS can be improved by employing SIMO technique, whereas both energy and spectral efficiency improvement can be obtained by employing SM technique.
Reactive fillers based on SWCNTs functionalized with matrix-based moieties for the production of epoxy composites with superior and tunable properties

Composite materials based on epoxy matrix and single-walled carbon nanotubes (SWCNTs) are able to exhibit outstanding improvements in physical properties when using a tailored covalent functionalization with matrix-based moieties containing terminal amines or epoxide rings. The proper choice of grafted moiety and integration protocol makes it feasible to tune the composite physical properties. At 0.5 wt% SWCNT loading, these composites exhibit up to 65% improvement in storage modulus, 91% improvement in tensile strength, and 65% improvement in toughness. A 15 °C increase in the glass transition temperature relative to the parent matrix was also achieved. This suggests that a highly improved interfacial bonding between matrix and filler, coupled to improved dispersion, are achieved. The degradation temperatures show an upshift in the range of 40–60 °C, which indicates superior thermal performance. Electrical conductivity ranges from ∼10−13 to ∼10−3 S cm−1, which also shows the possibility of tuning the insulating or conductive behaviour of the composites. The chemical affinity of the functionalization moieties with the matrix and the unchanged molecular structure at the SWCNT/matrix interface are responsible for such improvements.
In the Service of Self-Determination: Teacher Education, Service-Learning, and Community Reorganizing

Influenced by Third World Liberation social movements in the United States and abroad, this article applies a serve-the-people concept to service-learning in education. Rooted in pedagogies more traditionally associated with ethnic studies and community organizing, and informed by sociocultural and critical frameworks in education, this article offers insights from school community spaces that serve K–12 youth from different urban working-class neighborhoods. Transformative opportunities for grassroots collaboration, learning, agency, and community reorganizing are explored with implications for students, teachers, teacher educators, and community workers concerned with social justice.
Students as Scholars & Writers: Teaching & Assessing Undergraduate Writing in a Capstone Course

This paper presents an innovative approach for engaging and assessing undergraduate students in the writing process. Through an iterative, intensive course design that includes both in-classroom and online teaching, our Capstone course integrates writing instruction as students learn a new topic, gather and analyze data, and write a research paper complete with an introduction, literature review, findings section, and discussion/conclusion. Based on five semesters of observations, survey data, content analysis, and student reflective writing, we discuss the processes students undergo while learning to research and write as social science scholars. We find student outcomes beyond what we initially expected.
Absence of aromatase protein and mRNA expression in endometriosis.

BACKGROUND Aromatase has been reported to be involved in estrogen biosynthesis and expressed in eutopic and ectopic endometrium of endometriosis patients. The objective of the present study was to investigate its expression and localization in three distinct types of endometriosis. METHODS Human peritoneal, ovarian and rectovaginal endometriotic lesions and matched eutopic endometrium were collected from patients during laparoscopy. Aromatase protein localization (immunohistochemistry, n = 63) and mRNA expression [quantitative polymerase chain reaction (Q-PCR), n = 64] were assessed. RESULTS No aromatase protein was detected by immunohistochemistry in either the glandular or stromal compartment of endometriotic lesions or eutopic endometrium, while it was strong in placental syncytiotrophoblasts, granulosa and internal theca cells from pre-ovulatory follicles, and luteal cells from corpus luteum. By Q-PCR, low but discernible levels of aromatase expression were found in endometriomas, probably due to follicular expression. Transcripts for aromatase were barely detectable in only a few peritoneal and rectovaginal endometriotic lesions, and a few eutopic endometrium samples, probably due to contaminating surrounding tissues (adipose tissue, intact peritoneum). CONCLUSIONS Unlike previous studies, we observed no aromatase protein in any of the endometriosis types, and barely detectable aromatase mRNA expression, suggesting that locally produced aromatase (within endometriotic lesions) may be less implicated in endometriosis development than previously postulated. Potential factors responsible for these discrepancies are discussed.
An Overview of Associative Classifiers

Associative classification is a new classification approach integrating association mining and classification. It becomes a significant tool for knowledge discovery and data mining. This paper presents a critical overview of certain aspects on modelling associative classifiers including event association mining, computational complexity in mining associations, methods of constructing associative classifiers based on the association patterns discovered, some similarities and differences among the reported associative classification systems, and experimental comparisons of these associative classifiers with the conventional classification system such as C4.5.
Geometry-based Muscle Modeling for Facial Animation

We present a muscle model and methods for muscle construction that allow to easily create animatable facial models from given face geometry. Using our editing tool, one can interactively specify coarse outlines of the muscles, which are then automatically created to fit the face geometry.Our muscle model incorporates different types of muscles and the effects of bulging and intertwining muscle fibers. The influence of muscle contraction onto the skin is simulated using a mass-spring system that connects the skull, muscle, and skin layers of our model.
Structure of an L27 Domain Heterotrimer from Cell Polarity Complex Patj/Pals1/Mals2 Reveals Mutually Independent L27 Domain Assembly Mode*

Background: Tandem L27 domains are important for multidomain proteins to assemble into supramolecular complexes for cell polarity regulation. Results: Tandem L27 domain-mediated tripartite Patj/Pals1/Mals2 and DLG1/CASK/Mals2 complexes form in a mutually independent assembly mode. Conclusion: The mutually independent assembly mode may be a novel mechanism for tandem L27 domain-mediated, tripartite complex formation. Significance: These findings reveal the distinct mechanism of tandem L27 domain-mediated assembly of obligate supramolecular complexes. The assembly of supramolecular complexes in multidomain scaffold proteins is crucial for the control of cell polarity. The scaffold protein of protein associated with Lin-7 1 (Pals1) forms a complex with two other scaffold proteins, Pals-associated tight junction protein (Patj) and mammalian homolog-2 of Lin-7 (Mals2), through its tandem Lin-2 and Lin-7 (L27) domains to regulate apical-basal polarity. Here, we report the crystal structure of a 4-L27 domain-containing heterotrimer derived from the tripartite complex Patj/Pals1/Mals2. The heterotrimer consists of two cognate pairs of heterodimeric L27 domains with similar conformations. Structural analysis and biochemical data further show that the dimers assemble mutually independently. Additionally, such mutually independent assembly of the two heterodimers can be observed in another tripartite complex, Disks large homolog 1 (DLG1)/calcium-calmodulin-dependent serine protein kinase (CASK)/Mals2. Our results reveal a novel mechanism for tandem L27 domain-mediated, supramolecular complex assembly with a mutually independent mode.
First-Year Physical Education Teachers’ Experiences With Teaching African Refugee Students

The purpose of this study was to analyze and explore the experiences of eight first-year physical education teachers who have taught African refugee students. Interviews were conducted at the end of each participant’s first year of teaching. The findings of this study highlight the vast different learning styles of students from Africa and the strategies that these teachers trialed and incorporated into their lessons in an attempt to minimize the disruptions they experienced when first introduced to the students. The results of this study, together with information from the literature, suggest that the training and education of teachers in Australia must incorporate strategies for teaching students from different backgrounds, cultures, and living situations to better facilitate the inclusion of them in school-based activities and learning.
The blessed dementia scale as a screening test for dementia

The Blessed Dementia Scale (DS) is a brief behavioural scale based on the interview of a close informant. Its validity as a screening test was evaluated in 105 demented patients and 123 community residents. The DS proved to be a sensitive and specific screening test for dementia, especially when items related to personality changes were omitted by constructing a revised DS (RDS). Both the DS and RDS correlated with the patients' neuropsychological test performance. They also differentiated patients with different degrees of dementia. In the screening of dementia the cut‐off point of 4 in the DS gave a sensitivity of 90% and a specificity of 84%. In the RDS the cut‐off point of 1.5 gave a sensitivity of 93% and a specificity of 97%. Behavioural rating scales such as the DS are valuable in the screening of dementia, especially when combined with cognitive testing. In addition they can be used in the evaluation of the degree of disability and in the planning of social support.
On the Measurement and Prediction of Web Content Utility: A Review

Nowadays, various types and large amount of content are available on the Web. Characterizing the Web content and predicting its inherent usefulness become important problems that may benefit many applications such as information filtering and content recommendation. In this article, we present a brief review of the existing measurements and the corresponding prediction methods for Web content utility. Specially, we focus on three close and widely studied tasks, i.e., content popularity prediction, content quality prediction, and scientific article impact prediction. While reviewing the existing work in each of the above three tasks, we mainly aim to answer the following two fundamental questions: how to measure the Web content utility, and how to make the predictions under the measurement. We find that while the three tasks are closely related, they bear subtle differences in terms of prediction urgency, feature extraction, and algorithm design. After that, we discuss some future directions in measuring and predicting Web content utility
Young adults and wine consumption a qualitative application of the theory of planned behavior

Purpose – The aim of this study is to identify perceptions, attitudes and behavior of young adults concerning wine consumption, using the “theory of planned behavior” as a theoretical framework. Design/methodology/approach – The aim of this study is to identify perceptions, attitudes and behavior of young adults concerning wine consumption, using the “theory of planned behavior” as a theoretical framework. Findings – The major findings are that attitudes and subjective norms are, apparently, the components with most influence on behavior of young people in relation to wine consumption. For the consumers group, attitudes seem to be the most crucial component, especially the “interest in alcohol”. They drink it in special occasions for sociability and to disinhibit. Regarding the non-consumers group, the main attitude is “dislike taste”. Also the subjective norms, are very present, especially parents, society, friends and publicity, in consumers group. The non-consumers have the perception of greater parent.
Improve the performance of bus-assisted vehicular ad hoc networks via cooperative game theory

Vehicular ad hoc networks (VANETs) is an efficient enabler for safe and efficient Intelligent Transport Systems. The introduction of intermediate vehicles improves the performance of VANETs prominently. In this paper, we introduce buses as intermediate vehicles to improve the system efficiency. We also introduce the coalition game model to study the relationships between buses and add incentives for buses to cooperate with each other. According to theory of Shapley value, we find the solution to the buses coalition game satisfying efficiency symmetry and marginality. In the solution, buses that work as a coalition could obtain more payoff than they work alone. Thus, a bus is willing to cooperate with others and the coalition will maintain stability. The performance of VANETs will be improved due to the cooperation of buses. We have used the Opportunistic Network Environment (ONE) simulator to verify the high performance of the proposed mechanism in terms of higher delivery ratio.