Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective cover and the use of space by finches: is closer better?

The use of space by small birds is strongly influenced by dense vegetation which serves as protection from attacking predators. Current evidence suggests that birds dependent upon such cover for safety will venture away from it only if their energy intake rate is significantly enhanced in doing so. We found, however, that three species of finches (Emberizidae) regularly fed well away from cover without a corresponding increase in energy intake rate. Observations and experimental results strongly suggest that the birds perceived cover as both safety and a source of attacks. For instance, birds fed farther away from cover containing visual obstructions that might conceal predators lying in ambush. Their use of space appeared to reflect a trade-off between the perceived risk of feeding too close to cover vs that of feeding too far away. This trade-off was also influenced by a bird's social environment; subordinate species fed farther from cover than dominant ones in an apparent effort to avoid direct aggression.
Manipulating Leaderboards to Induce Player Experience

Assessing and inducing player experience (pX) in games user research (GUR) is complicated because of the tradeoff between maintaining rigour through experimental control and having participants feel like they are engaged in play. To establish and evaluate an embedded method for inducing a sense of success or failure in participants during gameplay (e.g., to study how different players exhibit resilience to in-game failure), we manipulated leaderboard position in an experiment in which 155 participants played a Bejeweled clone. We show that manipulating success perception through leaderboards increases the player's perception of competence, autonomy, presence, enjoyment, and positive affect over manipulated failure. In addition, displaying the score enhances the effect on positive affect, autonomy and enjoyment, while not increasing detectability.
CD34− Hematopoietic Stem Cells: Current Concepts and Controversies

Recent data have suggested that human CD34− hematopoietic stem cells (HSCs) exist, challenging the concept that HSCs necessarily and exclusively express the CD34 antigen. In mice, quiescent HSCs have been shown to be mostly CD34−, but as a consequence of 5‐fluorouracil treatment or cytokine stimulation, differentiate into CD34+ cells. Of particular interest is a novel, specific marker to identify HSCs, namely the Hoechst dye efflux property, with which a distinct side population (SP) is identified. These SP cells are mostly CD34−, highly enriched for long‐term repopulating cells, and durably engraft in sublethally irradiated non‐obese diabetic/severe combined immunodeficient mice. Using a semiquantitative reverse transcription‐polymerase chain reaction, one of the ATP‐binding cassette (ABC) transporters, the breast cancer resistance protein (Bcrp) or ABC transporter G2 (ABCG2), was found to be highly expressed in SP cells as well as other primitive HSCs and to sharply drop with hematopoietic differentiation. Enforced expression of the ABCG2 cDNA resulted in a robust SP phenotype and a reduction in hematopoietic maturation. These data suggest that the Bcrp/ABCG2 gene contributes importantly to the generation of the SP phenotype, which allows for the selection of immature, pluripotent HSCs. The isolation of Bcrp/ABCG2+ cells appears to be an attractive tool to analyze and characterize HSCs, and may eventually allow for the purification of these cells for clinical purposes. In this review, current concepts on murine and human CD34− HSCs and their relationship with CD34+ HSCs are discussed.
Detection of applications within encrypted tunnels using packet size distributions

In protocol tunnelling, one application protocol is encapsulated within another carrier protocol. Application-layer tunnels are security threat for networks because those applications which are sometimes restricted by firewalls like high data-rate games, peer-to-peer file sharing, video streaming, etc are carried through the allowed protocols like HTTP, SSH, hence the firewall policy is thwarted. The existing techniques for detection of applications across the network, e.g. packet data analysis are not very successful, especially in encrypted tunnels i.e ones using HTTPS, TLS/SSL protocols as the carrier. This work describes a statistical approach to detect applications which are running using encrypted tunnels. Previous work has shown the packet size distribution to be an effective metric for detecting most network applications. Here the same technique is applied for encrypted tunnels. Statistical Chi-square test is used for the analysis of the selected applications' packet size distributions. From the results, it is shown that tunneled applications can be detected using packet size distribution in encrypted tunnels.
Subvoxel Accurate Graph Search Using Non-Euclidean Graph Space

Graph search is attractive for the quantitative analysis of volumetric medical images, and especially for layered tissues, because it allows globally optimal solutions in low-order polynomial time. However, because nodes of graphs typically encode evenly distributed voxels of the volume with arcs connecting orthogonally sampled voxels in Euclidean space, segmentation cannot achieve greater precision than a single unit, i.e. the distance between two adjoining nodes, and partial volume effects are ignored. We generalize the graph to non-Euclidean space by allowing non-equidistant spacing between nodes, so that subvoxel accurate segmentation is achievable. Because the number of nodes and edges in the graph remains the same, running time and memory use are similar, while all the advantages of graph search, including global optimality and computational efficiency, are retained. A deformation field calculated from the volume data adaptively changes regional node density so that node density varies with the inverse of the expected cost. We validated our approach using optical coherence tomography (OCT) images of the retina and 3-D MR of the arterial wall, and achieved statistically significant increased accuracy. Our approach allows improved accuracy in volume data acquired with the same hardware, and also, preserved accuracy with lower resolution, more cost-effective, image acquisition equipment. The method is not limited to any specific imaging modality and readily extensible to higher dimensions.
Implementation and Behavioural Analysis of Graph Clustering using Restricted Neighborhood Search Algorithm

Neighborhood Search Algorithm or RNSC is a cost- based clustering technique for clustering the graph into separate clusters, where each cluster has some similar properties. The properties considered in this case are low inter-connectivity and high intra-connectivity in clusters. This is implemented only for un-weighted and undirected graphs. This algorithm applies a heuristic approach in which we only consider the moves in the restricted neighborhood of previous move, i.e., after a move has been made the next move will only be allowed in the neighbor clusters of that move. After a fixed number of moves we apply diversification moves to avoid the solution reaching local- minima in-spite of global solution. A tabu list is also maintained to avoid same moves which it has made in the recent past. This technique reduces the run-time of clustering algorithm many- folds, as it skips those redundant cases which occur multiple times and don't improve the cost of the function. The plus point of this algorithm is improvement in run-time due to the data- structure it is maintaining to update the clustering. The updating of the clustering is very fast and thus makes the algorithm fast. The paper proposes an effective behaviour analysis of some parameters of this algorithm which may help in the future modification of this algorithm. For better analysis of RNSC algorithm we have used Random Scaled-Free graphs having more than 10,000 nodes. Thus in our approach RNSC algorithm is successfully implemented in C++ for a graph of more than 10,000 nodes.
Moderate Prenatal Alcohol Exposure Enhances GluN2B Containing NMDA Receptor Binding and Ifenprodil Sensitivity in Rat Agranular Insular Cortex

Prenatal exposure to alcohol affects the expression and function of glutamatergic neurotransmitter receptors in diverse brain regions. The present study was undertaken to fill a current gap in knowledge regarding the regional specificity of ethanol-related alterations in glutamatergic receptors in the frontal cortex. We quantified subregional expression and function of glutamatergic neurotransmitter receptors (AMPARs, NMDARs, GluN2B-containing NMDARs, mGluR1s, and mGluR5s) by radioligand binding in the agranular insular cortex (AID), lateral orbital area (LO), prelimbic cortex (PrL) and primary motor cortex (M1) of adult rats exposed to moderate levels of ethanol during prenatal development. Increased expression of GluN2B-containing NMDARs was observed in AID of ethanol-exposed rats compared to modest reductions in other regions. We subsequently performed slice electrophysiology measurements in a whole-cell patch-clamp preparation to quantify the sensitivity of evoked NMDAR-mediated excitatory postsynaptic currents (EPSCs) in layer II/III pyramidal neurons of AID to the GluN2B negative allosteric modulator ifenprodil. Consistent with increased GluN2B expression, ifenprodil caused a greater reduction in NMDAR-mediated EPSCs from prenatal alcohol-exposed rats than saccharin-exposed control animals. No alterations in AMPAR-mediated EPSCs or the ratio of AMPARs/NMDARs were observed. Together, these data indicate that moderate prenatal alcohol exposure has a significant and lasting impact on GluN2B-containing receptors in AID, which could help to explain ethanol-related alterations in learning and behaviors that depend on this region.
Energy-Efficient Dynamic Routing Protocol for Wireless Sensor Networks

Wireless detector nodes are deployed on a battleground and organize themselves in an exceedingly large- scale ad-hoc network. Traditional routing protocols don't take into consideration that a node contains solely a restricted provided energy. Optimal routing tries to maximise the length over that the sensing task is performed, however needs future knowledge. The proposed work use to simulate sensor network implementation and proceeded with saving energy for sensors. At initial phase basic functionality and collection of information (simulator, basic sensor functions etc) has been done. Network simulator has been used to provide the simulation and results of the proposed work. The results show that the performance of the proposed scheme for saving resources in wireless sensor network is better. Traditional AODV process scheme provide good solution for communication but proposed scheme have much better performance in saving resources and to increase packet delivery ratio.
N-Linked Protein Glycosylation Is Required for Full Competence in Campylobacter jejuni 81-176

ABSTRACT The recent sequencing of the virulence plasmid of Campylobacter jejuni 81-176 revealed the presence of genes homologous to type IV secretion systems (TFSS) that have subsequently been found in Helicobacter pylori and Wolinella succinogenes. Mutational analyses of some of these genes have implicated their involvement in intestinal epithelial cell invasion and natural competence. In this report, we demonstrate that one of these type IV secretion homologs, Cjp3/VirB10, is a glycoprotein. Treatment with various glycosidases and binding to soybean agglutinin indicated that the structure of the glycan present on VirB10 contains a terminal GalNAc, consistent with previous reports of N-linked glycans in C. jejuni. Site-directed mutagenesis of five putative N-linked glycosylation sites indicated that VirB10 is glycosylated at two sites, N32 and N97. Mutants in the N-linked general protein glycosylation (pgl) system of C. jejuni are significantly reduced in natural transformation, which is likely due, in part, to lack of glycosylation of VirB10. The natural transformation defect in a virB10 mutant can be complemented in trans by using a plasmid expressing wild-type VirB10 or an N32A substitution but not by using a mutant expressing VirB10 with an N97A substitution. Taken together, these results suggest that glycosylation of VirB10 specifically at N97 is required for the function of the TFSS and for full competence in C. jejuni 81-176.
A Simple Active Attack Against TCP

This paper describes an active attack against the Transport Control Protocol (TCP) which allows a cracker to redirect the TCP stream through his machine thereby permitting him to bypass the protection offered by such a system as a one-time password [SKEY] or ticketing authentication [Kerberos]. The TCP connection is vulnerable to anyone with a TCP packet sniffer and generator located on the path followed by the connection. Some schemes to detect this attack are presented as well as some methods of prevention and some interesting details of the TCP protocol behaviors.
Channel Selection Algorithm for Cognitive Radio Networks with Heavy-Tailed Idle Times

We consider a multichannel Cognitive Radio Network (CRN), where secondary users sequentially sense channels for opportunistic spectrum access. In this scenario, the Channel Selection Algorithm (CSA) allows secondary users to find a vacant channel with the minimal number of channel switches. Most of the existing CSA literature assumes exponential ON-OFF time distribution for primary user's (PU) channel occupancy pattern. This exponential assumption might be helpful to get performance bounds; but not useful to evaluate the performance of CSA under realistic conditions. An in-depth analysis of independent spectrum measurement traces reveals that wireless channels have typically heavy-tailed PU OFF times. In this paper, we propose an extension to the Predictive CSA framework and its generalization for heavy tailed PU OFF time distribution, which represents realistic scenarios. In particular, we calculate the probability of channel being idle for hyper-exponential OFF times to use in CSA. We implement our proposed CSA framework in a wireless test-bed and comprehensively evaluate its performance by recreating the realistic PU channel occupancy patterns. The proposed CSA shows significant reduction in channel switches and energy consumption as compared to Predictive CSA which always assumes exponential PU ON-OFF times. Through our work, we show the impact of the PU channel occupancy pattern on the performance of CSA in multichannel CRN.
Optimization Algorithms on Matrix Manifolds

Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms. It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction--illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development. In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis. It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists.
A Login System Using Mouse Dynamics

This paper will describe a login method for accessing computer systems, using mouse dynamics. The user needs to perform a task with his mouse pointer, and based on the performance of that task, the user is granted or denied access to the computer. Such a system could be a replacement for, or an addition to, the ordinary username/password system. A password based system has in general the disadvantage that passwords are either too hard to remember or too easy to guess. A system using biometrics has the advantage that people cannot forget it. A system using mouse dynamics has the additional advantage that no extra hardware is needed, like for example in the case of fingerprint biometrics.
Bit-Flip Aware Control-Flow Error Detection

Recent increase of transient fault rates has made processor reliability a major concern. Moreover performance improvements are required for many of today's embedded systems. At the same time software implemented fault detection remains the only option for off-the-shelf processors. Software methods, however, introduce significant performance overheads due to the additional instructions required for the detection. A good observation is that often code segments not susceptible to faults are protected. In this paper we propose a technique for systematic analysis of the bit-flip effects on the program control-flow in order to identify only those locations susceptible to control-flow errors and hence minimize the number of fault detection assertions. We instrument the code with minimal overhead, while maintaining high fault coverage level. Our experiments show that using the result of our bit-flip analysis and limiting the code instrumentation to only the susceptible locations releases 28.9% (on average) of the memory while the level of fault coverage remains the same as with full instrumentation.
Complexity lower bounds for computation trees with elementary transcendental function gates

We consider computation trees which admit as gate functions along with the usual arithmetic operations also algebraic or transcendental functions like exp, log, sin, square root (defined in the relevant domains) or much more general, Pfaffian functions. A new method for proving lower bounds on the depth of these trees is developed which allows to prove a lower bound /spl Omega/(/spl radic/(log N)) for testing membership to a convex polyhedron with N facets of all dimensions, provided that N is large enough. This method differs essentially from the previous approaches adopted for algebraic computation trees. <<ETX>>
Patterns of diversity and adaptation in Glomeromycota from three prairie grasslands

Arbuscular mycorrhizal (AM) fungi are widespread root symbionts that often improve the fitness of their plant hosts. We tested whether local adaptation in mycorrhizal symbioses would shape the community structure of these root symbionts in a way that maximizes their symbiotic functioning. We grew a native prairie grass (Andropogon gerardii) with all possible combinations of soils and AM fungal inocula from three different prairies that varied in soil characteristics and disturbance history (two native prairie remnants and one recently restored). We identified the AM fungi colonizing A. gerardii roots using PCR amplification and cloning of the small subunit rRNA gene. We observed 13 operational taxonomic units (OTUs) belonging to six genera in three families. Taxonomic richness was higher in the restored than the native prairies with one member of the Gigaspora dominating the roots of plants grown with inocula from native prairies. Inoculum source and the soil environment influenced the composition of AM fungi that colonized plant roots. Correspondingly, host plants and AM fungi responded significantly to the soil–inoculum combinations such that home fungi often had the highest fitness and provided the greatest benefit to A. gerardii. Similar patterns were observed within the soil–inoculum combinations originating from two native prairies, where five sequence types of a single Gigaspora OTU were virtually the only root colonizers. Our results indicate that indigenous assemblages of AM fungi were adapted to the local soil environment and that this process occurred both at a community scale and at the scale of fungal sequence types within a dominant OTU.
Circumscribed Interests in Higher Functioning Individuals with Autism Spectrum Disorders: An Exploratory Study

Circumscribed interests are a fascinating and an understudied phenomenon in some individuals with autism spectrum disorders (ASD). Research in this area is likely to contribute to our understanding of ASDs and to advancing developmental knowledge on learning processes used to adapt to the demands of everyday social life. This study reports on a survey of special interests in 96 children and adolescents with higher functioning ASD. The survey included listing of up to three special interests for each child, and the rating of level of interference of a given interest upon children's activities when by themselves and when in contact with family members, peers, and other adults. This information was collected for both preschool and elementary school years. Special interests were classified into eight categories in terms of their nature (rather than topic), which included the ways through which the interest was manifest and pursued. Results indicated that circumscribed interests (a) are the norm rather than the exception in this population (75% and 88% of the sample for the younger and the older age periods, respectively), (b) most frequently involve verbal learning and memorization of facts (65% and 81% for the younger and the older age periods, respectively), (c) often involve an element of interest in letters and numbers in the preschool years (35% of the sample), (d) greatly interfere with activities pursued by oneself or with others, and (e) level of interference is predictive of lower social and communicative adaptive behavior later in life. Given the ubiquity of circumscribed interests in this population, their verbal nature, and the passion that children with ASD invest in these pursuits, we suggest the need for studies that will trace the longitudinal course of learning profiles from early childhood and possible interventions that may address these areas.
Dictionary Look-Up Within Small Edit Distance

Let be a dictionary consisting of n binary strings of length m each, represented as a trie. The usual d-query asks if there exists a string in within Hamming distance d of a given binary query string q. We present a simple algorithm to determine if there is a member in within edit distanced of a given query string q of length m. The method takes time O(dmd+1) in the RAM model, independent of n, and requires O(dm) additional space. We also generalize the results for the case of the problem over a larger alphabet.
Empirical comparison of analog and digital auditory preprocessing for automatic speech recognition

Results from digital and analog filter bank preprocessors are compared in order to establish the validity of analog processing for automatic speech recognition (ASR) systems. Three systems are evaluated using speaker and context independent phoneme recognition tasks. The three ASR systems are identical except for the preprocessing techniques used to derive three signal representations: extraction of (1) the digital mel-frequency spectrum, (2) the mel-frequency spectrum from commercial discrete bandpass filters and (3) the exponential spectrum from analog VLSI bandpass filter bank. The discrete analog system exhibits a 38% increase in recognition accuracy over the digital preprocessing technique. The digital and analog VLSI-based techniques perform comparably (within 3% of each other).