Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single Acidic Residue Can Guide Binding Site Selection but Does Not Govern QacR Cationic-Drug Affinity

Structures of the multidrug-binding repressor protein QacR with monovalent and bivalent cationic drugs revealed that the carboxylate side-chains of E90 and E120 were proximal to the positively charged nitrogens of the ligands ethidium, malachite green and rhodamine 6G, and therefore may contribute to drug neutralization and binding affinity. Here, we report structural, biochemical and in vivo effects of substituting these glutamate residues. Unexpectedly, substitutions had little impact on ligand affinity or in vivo induction capabilities. Structures of QacR(E90Q) and QacR(E120Q) with ethidium or malachite green took similar global conformations that differed significantly from all previously described QacR-drug complexes but still prohibited binding to cognate DNA. Strikingly, the QacR(E90Q)-rhodamine 6G complex revealed two mutually exclusive rhodamine 6G binding sites. Despite multiple structural changes, all drug binding was essentially isoenergetic. Thus, these data strongly suggest that rather than contributing significantly to ligand binding affinity, the role of acidic residues lining the QacR multidrug-binding pocket is primarily to attract and guide cationic drugs to the “best available” positions within the pocket that elicit QacR induction.
A semi-automatic method for extracting a taxonomy for nuclear knowledge using hierarchical document clustering based on concept sets

In this paper, we present a text mining approach for the semiautomatic extraction of taxonomy of concepts for nuclear knowledge and evaluate the achievable results. Taxonomies are a fundamental part of any knowledge management strategy or framework. We propose a method for hierarchical document clustering based on the notion of frequent concept sets. Most clustering algorithms treat documents as a bag of words and bypass the important relationships between words, such as synonyms. In this method, we consider the semantic relationship between words and use a domain thesaurus (ETDE/INIS) to identify concepts. To validate the method, we conducted a case study in which we implemented a prototype, generating a taxonomy for nuclear knowledge with the goal of conceptually mapping the scientific production of the Brazilian Nuclear Energy Commission (CNEN).
A statewide needs assessment using focus groups: perceived challenges and goals in providing inclusive recreation services in rural communities.

The purposes of this study were two-fold: (a) to explore the use of focus groups as a method of conducting a statewide needs assessment and (b) to conduct a statewide needs assessment on the recreation needs, constraints, and recommendations related to serving persons with disabilities in community settings. Inclusion of people with disabilities in community-based recreation is beneficial to all people. Despite the benefits, constraints continue to exist. Continual assessment at a statewide level helps providers understand the interests and needs of citizens. The focus group format was an excellent means of assessing needs, as well as an effective way to connect service providers with people with disabilities, and rural residents with urban service providers. The format also yielded results with much greater detail and intensity of feeling than traditional surveys. Results of the needs assessment showed persistent constraints for people with disabilities and service providers. These constraints included lack of awareness, acceptance, and information about people with disabilities; lack of prepared recreation staff, social inclusion, and physical access; and lack of communication and networking between various service agencies and consumers. Focus group participants, comprised of providers and consumers, generated viable strategies to address the constraints. The majority of the strategies focused on increased communication among service providers and constituents through training, education, or networking. Study implications relate to the use of focus groups as a method of conducting needs assessments and to the inclusion of people with disabilities in community recreation. First, focus groups proved to be a viable and rich method for parks and recreation professionals to conduct needs assessments. Focus groups allowed service providers to hear firsthand accounts of community needs and concerns, potentially uncovering unmet needs and generating solutions that had not been considered. By listening to community needs in a personal way, trusting relationships were built with constituents. Furthermore, focus groups introduced participants to each other, gave people an opportunity to exchange ideas, encouraged community spirit, and increased the likelihood of forming spontaneous community partnerships and networks, which is especially critical in rural areas with less recreational infrastructure. Second, this study pointed to the need for ongoing education about inclusion and people with disabilities. The study also pointed to the need to create active, productive networks of service providers, including parks/recreation services, human services, and people with disabilities and their families.
FEMALE AND MALE GENETIC EFFECTS ON OFFSPRING PATERNITY: ADDITIVE GENETIC (CO)VARIANCES IN FEMALE EXTRA-PAIR REPRODUCTION AND MALE PATERNITY SUCCESS IN SONG SPARROWS (MELOSPIZA MELODIA)

Ongoing evolution of polyandry, and consequent extra‐pair reproduction in socially monogamous systems, is hypothesized to be facilitated by indirect selection stemming from cross‐sex genetic covariances with components of male fitness. Specifically, polyandry is hypothesized to create positive genetic covariance with male paternity success due to inevitable assortative reproduction, driving ongoing coevolution. However, it remains unclear whether such covariances could or do emerge within complex polyandrous systems. First, we illustrate that genetic covariances between female extra‐pair reproduction and male within‐pair paternity success might be constrained in socially monogamous systems where female and male additive genetic effects can have opposing impacts on the paternity of jointly reared offspring. Second, we demonstrate nonzero additive genetic variance in female liability for extra‐pair reproduction and male liability for within‐pair paternity success, modeled as direct and associative genetic effects on offspring paternity, respectively, in free‐living song sparrows (Melospiza melodia). The posterior mean additive genetic covariance between these liabilities was slightly positive, but the credible interval was wide and overlapped zero. Therefore, although substantial total additive genetic variance exists, the hypothesis that ongoing evolution of female extra‐pair reproduction is facilitated by genetic covariance with male within‐pair paternity success cannot yet be definitively supported or rejected either conceptually or empirically.
vGrid: a framework for building autonomic applications

With rapid technological advances in networkinfrastructure, programming languages, compatiblecomponent interfaces and so many more areas, today thecomputational Grid has evolved with the potential ofseamless aggregation, integration and interactions. Thishas made it possible to conceive a new generation ofrealistic, scientific and engineering simulations ofcomplex physical phenomenon. These applications willsymbiotically and opportunistically combinecomputations, experiments, observations, and real-timedata, and will provide important insights into complexphenomena. However, the phenomena being modeled areinherently complex, multi-phased, multi-scaled, dynamicand heterogeneous (in time space and state). Furthermore, their implementations involve multipleresearchers with scores of models, hundreds ofcomponents and dynamic compositions and interactionsbetween these components. The underlying Gridinfrastructure is similarly heterogeneous and dynamic,globally aggregating large numbers of independentcomputing and communication resources, data stores andsensor networks. The combination of the two results inapplication development, configuration and managementcomplexities that break current paradigms that are basedon passive components and static compositions. In fact,we have reached a level of complexity, heterogeneity, anddynamism that our programming environments andinfrastructure are becoming unmanageable/insecure [3]. In this paper we attempt to explore an alternativeprogramming paradigm and management technique thatis based on strategies used by biological systems to dealwith complexity, heterogeneity and uncertainty. Thisapproach is referred to as autonomic computing [1]. Wediscuss key technologies to enable the development ofautonomic Grid applications. We also present amiddleware architecture that sits on top of the existingGrid middleware, intelligently managing and executingautonomic applications with huge computationalrequirements over limited Grid resources. We discuss indetail how the proposed vGrid middleware can be used todynamically control and manage large-scale forest firesimulation.
Performance Degraded by the Sensor Noise at Pixel Level Image Fusion

Remote sensing is defined as obtaining information about a Performance metrics for measuring absolute degradation and their gain in fused image quality are proposed when fusing noisy input modalities. This considers fusion of noise patterns, is also developed and used to evaluate the perceptual effect of noise corrupting homogenous image regions (i.e. areas with no salient features). These metrics are employed to compare the performance of different image fusion methodologies and feature selection/information fusion strategies operating under noisy input conditions. The aim of this paper is to define appropriate metrics which measure the effects of input sensor noise on the performance of image fusion systems. ’ noisy fusion’’ metrics are developed and used, in the first two scenarios, to measure the effects of additive sensor noise on the performance of several signal-level image fusion algorithms operating across a range of input signal-to-noise ratio (SNR) values.
Reexamining DNS From a Global Recursive Resolver Perspective

The performance and operational characteristics of the Domain Name System (DNS) protocol are of deep interest to the research and network operations community. In this paper, we present measurement results from a unique dataset containing more than 26 billion DNS query-response pairs collected from more than 600 globally distributed recursive DNS resolvers. We use this dataset to reaffirm findings in published work and notice some significant differences that could be attributed both to the evolving nature of DNS traffic and to our differing perspective. For example, we find that although characteristics of DNS traffic vary greatly across networks, the resolvers within an organization tend to exhibit similar behavior. We further find that more than 50% of DNS queries issued to root servers do not return successful answers, and that the primary cause of lookup failures at root servers is malformed queries with invalid top-level domains (TLDs). Furthermore, we propose a novel approach that detects malicious domain groups using temporal correlation in DNS queries. Our approach requires no comprehensive labeled training set, which can be difficult to build in practice. Instead, it uses a known malicious domain as anchor and identifies the set of previously unknown malicious domains that are related to the anchor domain. Experimental results illustrate the viability of this approach, i.e., we attain a true positive rate of more than 96%, and each malicious anchor domain results in a malware domain group with more than 53 previously unknown malicious domains on average.
Implicit Enumeration of Patterns ( Preliminary Version )

Condensed representations of pattern collections have been recognized to be important building blocks of inductive databases, a promising theoretical framework for data mining, and recently they have been studied actively. However, there has not been much research on how condensed representations should actually be represented. In this paper we study implicit enumeration of patterns, i.e., how to represent pattern collections by listing only the interestingness values of the patterns. The main problem is that the pattern classes are typically huge compared to the collections of interesting patterns in them. We solve this problem by choosing a good ordering of listing the patterns in the class such that the ordering admits effective pruning and prediction of the interestingness values of the patterns. This representation of interestingness values enables us to quantify how surprising a pattern is in the collection. Furthermore, the encoding of the interestingness values reflects our understanding of the pattern collection and thus the size of the encoding can be used to evaluate the correctness of the assumptions.
Hybrid Features for Speaker Independent Hindi Speech Recognition

Isolated spoken Hindi digits recognition performance has been evaluated using HTK (Hidden Markov Model Toolkit). This paper introduces and motivates the use of hybrid features for isolated Hindi digits recognition system. The speech recog- nizers use a parametric form of a signal to get the most important distinct features of speech signal for recognition task. In this paper Mel-frequency cepstral coefficients (MFCC), Perceptual linear prediction (PLP) coefficients along with two newly modified hybrid features are used for isolated Hindi digits recognition. Two modified hybrid features Bark frequency cepstral coefficients (BFCC) and Revised perceptual linear prediction (RPLP) coefficients were obtained from combination of MFCC and PLP. Ex- periments were performed for both clean as well as on noisy data. In this experiment six different noises: Car noise, F16 noise, Factory noise, Speech noise, LYNX noise and Operation room noise have been added to clean Hindi digits database at different SNR levels to get noisy database. The recognition performance with BFCC features was better than that with MFCC features. RPLP features have shown best recognition performance as compared to all other features for both noisy and clean databases.
PHYSICAL ACTIVITY IN VIRTUAL REALITY

The purpose of this conference is to discuss about research on human physical activity based on Virtual Reality (VR). VR 1) offers a unique compromise between control and ecological property of the studied situation, 2) enables to enrich/modify the physical environment, 3) provides control on the multisensory feedback given to the user, 4) and has the potential to enhance motivation and increase the number of repetition in motor skills training. Recent democratisation of immersive technologies, with the development of cheap interactive devices for videogames, has encouraged research in this domain. In this conference, we will address examples of perception-action coupling analysis based on VR, will analyse how technical choices could affect the behaviour of the studied subjects, and will expose perspectives in motor skills training based on VR.
Influences of Institutional and Labor Market Characteristics on Careers in Japanese Companies

There are two dominant perspectives (namely, the cultural and economic perspectives) that are used to explain aspects of the Japanese employment system such as lifetime employment and the seniority principle. Cultural explanations (e.g., Abegglen; Nakane) tend to rely on Confucianism and familism to explain the Japanese employment system. On the other hand, the theory of the internal labor market is one of the popular theories used to explain the system, shedding light on firm-specific skills (e.g., Aoki; Koike). By using both cultural and economic perspectives, I examine workers' careers in Japanese corporations and then compare the effects of each perspective on the careers. In addition, I perform multi-level analysis (at the national, organizational field, and individual organizational characteristic levels) because individual workers tend to be exposed to multiple institutions although culturalists simply assume that individuals belong to national institutions (e.g., Confucianism) of which the unique employment system is a natural outgrowth. By using the Working Person Survey (2008), I perform logistic, ordinal logistic and OLS regressions. Some of my results show that having general skills has significant effects on the workers' careers and that having firm-specific skills is found to have negative effects on income and on being a regular worker. These results are inconsistent with the past literature and show that the Japanese corporation attaches importance to general skills. Although general skills have positive effects on careers, the workers' age still has a relatively large effect on them.
INCLUDING MEAN-VARIANCE RELATIONSHIPS IN HETEROSKEDASTIC MIXED LINEAR MODELS : THEORY AND APPLICATION

In mixed linear models, it is usually assumed that both residual and random effects have homogeneous components of variance. This paper presents models and corresponding techniques of estimation to relax this restrictive assumption. Models proposed include log link functions linearly relating variance components to explanatory variables that can be either discrete or continuous. Special emphasis is given to two aspects of modelling. First, a structural model for residual variances is considered which incorporates, in addition to classical covariates, a function of the data expectation to take into account mean-variance relationships. Secondly, residual and random effect component of variances are linked via a linear functional relationship. Estimation and testing procedures are based on restricted maximum likelihood procedures (REML) via the expectation-maximization (EM) algorithm. The procedure is illustrated by the analysis of birth weight of rats that were used in a toxicology experiment.
Autonomic Control for Quality Collaborative Video Viewing

We present an autonomic controller for quality collaborative video viewing, which allows groups of geographically dispersed users with different network and computer resources to view a video in synchrony while optimizing the video quality experienced. The autonomic controller is used within a tool for enhancing distance learning with synchronous group review of online multimedia material. The autonomic controller monitors video state at the clients’ end, and adapts the quality of the video according to the resources of each client in (soft) real time. Experimental results show that the autonomic controller successfully synchronizes video for small groups of distributed clients and, at the same time, enhances the video quality experienced by users, in conditions of fluctuating bandwidth and variable frame rate.
Laminin and Fibronectin Treatment Leads to Generation of Dendritic Cells with Superior Endocytic Capacity

Background Sampling the microenvironment at sites of microbial exposure by dendritic cells (DC) and their subsequent interaction with T cells in the paracortical area of lymph nodes are key events for initiating immune responses. Most of our knowledge of such events in human is based on in vitro studies performed in the absence of extracellular matrix (ECM) proteins. ECM in basement membranes and interstitial spaces of different tissues, including lymphoid organs, plays an important role in controlling specific cellular functions such as migration, intracellular signalling and differentiation. The aim of this study was, therefore, to investigate the impact of two abundant ECM components, fibronectin and laminin, on the phenotypical and functional properties of DC and how that might influence DC induced T-cell differentiation. Methodology/Principal Findings Human monocyte derived DC were treated with laminin and fibronectin for up to 48 hours and their morphology and phenotype was analyzed using scanning electron microscopy, flow cytometry and real time PCR. The endocytic ability of DC was determined using flow cytometry. Furthermore, co-culture of DC and T cells were established and T cell proliferation and cytokine profile was measured using H3-thymidine incorporation and ELISA respectively. Finally, we assessed formation of DC-T cell conjugates using different cell trackers and flow cytometry. Our data show that in the presence of ECM, DC maintain a ‘more immature’ phenotype and express higher levels of key endocytic receptors, and as a result become significantly better endocytic cells, but still fully able to mature in response to stimulation as evidenced by their superior ability to induce antigen-specific T cell differentiation. Conclusion These studies underline the importance of including ECM components in in vitro studies investigating DC biology and DC-T cell interaction. Within the context of antigen specific DC induced T cell proliferation, inclusion of ECM proteins could lead to development of more sensitive assays.
A Novel Framework for the Identification and Analysis of Duplicons between Human and Chimpanzee

Human and other primate genomes consist of many segmental duplications (SDs) due to fixation of copy number variations (CNVs). Structure of these duplications within the human genome has been shown to be a complex mosaic composed of juxtaposed subunits (called duplicons). These duplicons are difficult to be uncovered from the mosaic repeat structure. In addition, the distribution and evolution of duplicons among primates are still poorly investigated. In this paper, we develop a statistical framework for discovering duplicons via integration of a Hidden Markov Model (HMM) and a permutation test. Our comparative analysis indicates that the mosaic structure of duplicons is common in CNV/SD regions of both human and chimpanzee genomes, and a subset of core duplicons is shared by the majority of CNVs/SDs. Phylogenetic analyses using duplicons suggested that most CNVs/SDs share common duplication ancestry. Many human/chimpanzee duplicons flank both ends of CNVs, which may be hotspots of nonallelic homologous recombination.
A signal detection method based on auto-correlation for the listen-before-transmit

To avoid collisions of calling from users of the same dell group, the technique of listen-before-transmit (LBT) is employed in in the Third Generation High Frequency Automatic Link Establishment. In this paper a signal detection method based on the transformed sample auto-correlation matrix is proposed for the LBT. This method makes use of the property that the signal is usually pertinent, while the noise is randomly scattered. So it can be adapted in the condition when the power of the noise and the signal is unknown to us. Comparing with several traditional methods, this method performs best in our computer simulations, taking account of the LBT. While the role factors that will improve the performance of the method are discussed and simulated.
The Symbol Grounding Problem Has Been Solved : Or Maybe Not ?

First of all, as a new chair of the AMD TC, I would like to thank the former chair, Dr. Zhengyou Zhang for his role in leading our community and his initiation of a new IEEE transaction on AMD. Also, on the behalf of the AMD TC, I appreciate your continuous supports for our activities. The AMD TC is the largest one among IEEE CIS TCs, (see http://ieee-cis.org/technical/welcome/). Therefore, our activities are also expected to be among the most exciting. In order to cope with the expectations, I would like to enrich and extend our activities, especially ICDL with more people from different disciplines, and co-location of ICDL with other related and major conferences such as EpiRob and IEEE CIS conferences. Furthermore, we should have a systematic way to encourage the authors of ICDL to submit their extended papers to TAMD. We need your continuous supports for these extensions. Thank you for your cooperation in advance.