Miracle-dz/UniFAR-FTUs huggingface dataset:
Border Controls at the Mammalian Spinal Cord: Late-Surviving Neural Crest Boundary Cap Cells at Dorsal Root Entry Sites May Regulate Sensory Afferent Ingrowth and Entry Zone Morphogenesis

Boundary caps (BCs) form when neural crest cells, migrating ventrally alongside the neural tube, arrest at sites where axons will enter and exit. However, nothing is known of their subsequent fate and functions. We have found late-surviving neural crest BC cell clusters at proximal dorsal root entry sites throughout rat spinal cord development. Sensory afferents cross BCs to enter the spinal cord, while exiting astrocyte processes, destined to form the dorsal root entry zone (DREZ) after birth, are temporarily stalled in their vicinity. To test whether contact with BC cells influences neurite outgrowth from dorsal root ganglia, neurons were cultured on embryonic dorsal root/spinal cord cryosections. Neurites that entered CNS territory preferentially extended over BC cells. Thus, BC cells could be instrumental in regulating afferent ingrowth and DREZ morphogenesis in mammalian spinal cord development.
Stochastic consensus of linear multi-agent systems with multiplicative measurement noises

In this work, stochastic consensus of linear multi-agent systems with multiplicative measurement noises is investigated under undirected graphs. Based on the algebraic graph theory and the matrix theory, the consensus problem is converted into the stochastic stability problem of stochastic differential equations (SDEs) driven by multiplicative noises. Then by stochastic stability theorem for SDEs, the stochastic consensus conditions are given for the multi-agent systems. For the general linear multi-agent systems, the sufficient conditions for the mean square and the almost sure consensus are obtained based on the solution to an algebraic Riccati equation, where the consentability condition on the algebraic connectivity and the channel uncertainties is revealed. For the case of second-order integrator dynamics, by choosing some appropriate Lyapunov functions, the sufficient conditions for the mean square and the almost sure consensus, and the necessary conditions for the mean square consensus are derived. Moreover, it is shown that for any bounded noise intensities, the mean square and the almost sure consensus can be achieved by carefully choosing the control gain.
Organic Turkey Flocks: A Reservoir of Streptococcus gallolyticus subspecies gallolyticus

Streptococcus gallolyticus subspecies gallolyticus (S. gallolyticus) can colonise the gastrointestinal tract of humans and animals and is known to cause similar infections in both humans and animals. Data about the spread or prevalence in farm animals are missing. In this study, Trypton Soya Agar was modified to a selective medium enabling the isolation and quantification of S. gallolyticus from faecal samples. The bacterium was observed in 82 out of 91 faecal samples obtained from 18 different organic turkey flocks. The prevalence of shedding birds was estimated by the number of positive fresh droppings and reached up to 100% on most farms. Furthermore, for the first time S. gallolyticus was quantified in faeces from poultry flocks. The median of colony forming units (CFU) per gramme faeces was 3.6 x 105CFU/g. Typing of one isolate from each positive faecal sample by multilocus sequence typing delivered 24 sequence types (STs). Most of the isolates belonged to the clonal complex CC58. The same STs of this complex were detected in up to six different flocks. Partly, these flocks were located in various regions and stocked with varying breeding lines. Regarding the biochemical profiles of the same STs from different farms, the results did not contradict a spread of specific STs in the organic turkey production. Moreover, checking the pubMLST database revealed that STs found in this study were also found in other animal species and in humans. The high detection rate and the number of S. gallolyticus in turkey faeces indicate that this bacterium probably belongs to the common microbiota of the gastrointestinal tract of turkeys from organic flocks. Furthermore, the findings of this study support the suggestion of a possible interspecies transmission.
How useful are similarity word lists for indirect anaphora resolution

This work tests the use of word similarity lists for anaphora resolution in Portuguese and French corpora. We applied an automatic lexical acquisition technique over parsed texts to identify semantically similar words. We then made use of this lexical knowledge to resolve coreferential definite descriptions where the head noun of the anaphor is different from the head noun of its antecedent, which we call indirect anaphora. We compare the results in both languages with a baseline algorithm. Our proposed technique achieved an Fmeasure of 0.26 for Portuguese and 0.09 for French.
The Transcriptome of Lutzomyia longipalpis (Diptera: Psychodidae) Male Reproductive Organs

Background It has been suggested that genes involved in the reproductive biology of insect disease vectors are potential targets for future alternative methods of control. Little is known about the molecular biology of reproduction in phlebotomine sand flies and there is no information available concerning genes that are expressed in male reproductive organs of Lutzomyia longipalpis, the main vector of American visceral leishmaniasis and a species complex. Methods/Principal Findings We generated 2678 high quality ESTs (“Expressed Sequence Tags”) of L. longipalpis male reproductive organs that were grouped in 1391 non-redundant sequences (1136 singlets and 255 clusters). BLAST analysis revealed that only 57% of these sequences share similarity with a L. longipalpis female EST database. Although no more than 36% of the non-redundant sequences showed similarity to protein sequences deposited in databases, more than half of them presented the best-match hits with mosquito genes. Gene ontology analysis identified subsets of genes involved in biological processes such as protein biosynthesis and DNA replication, which are probably associated with spermatogenesis. A number of non-redundant sequences were also identified as putative male reproductive gland proteins (mRGPs), also known as male accessory gland protein genes (Acps). Conclusions The transcriptome analysis of L. longipalpis male reproductive organs is one step further in the study of the molecular basis of the reproductive biology of this important species complex. It has allowed the identification of genes potentially involved in spermatogenesis as well as putative mRGPs sequences, which have been studied in many insect species because of their effects on female post-mating behavior and physiology and their potential role in sexual selection and speciation. These data open a number of new avenues for further research in the molecular and evolutionary reproductive biology of sand flies.
Cryptanalysis and Improvement of an "Improved Remote Authentication Scheme with Smart Card'

Remote authentication schemes with smart cards have gained much attention in recent years. Recently Lee and Chiu proposed an improved remote authentication scheme with smart cards. It enables the user to freely choose his password and claim that their scheme is secure. Nevertheless, we present attacks and weaknesses of the scheme. Additionally, we propose a new improved scheme to counter these attacks.
Oscillations in Endogenous Inputs to Neurons Affect Excitability and Signal Processing

Synchrony and oscillations in neuronal firing play important roles in information processing in the mammalian brain. Here, we evaluate their role in controlling neuronal output in a well defined motor behavior, breathing, using an in vitro preparation from neonatal rat that generates respiratory-related motor output. In this preparation, phrenic motoneurons (PMNs) receive endogenous rhythmic inspiratory currents with prominent oscillations in the 20-50 Hz range. We recorded these inspiratory currents in individual PMNs and used them as test inputs for the same motoneuron (MN) during the normally silent expiratory periods. The impact of the oscillations on MN output was evaluated by filtering the currents before injection. Responses to unfiltered inspiratory currents were indistinguishable from voltage changes during spontaneous inspiratory periods. More than 90% of action potentials occurred within milliseconds [-2 to +4] of the oscillation peaks. The timing of action potentials was highly reproducible in response to unfiltered currents. Attenuation of the oscillations by low-pass filtering (<50 Hz) decreased the precision in action potential timing and significantly reduced the number of action potentials by ∼35%. The adrenergic agonist phenylephrine increased instantaneous firing frequency in responses evoked by square-wave or low-pass filtered inspiratory currents but had no effect on firing frequency evoked by unfiltered currents. We conclude that oscillations control the precise timing of action potentials, help to maximize synaptic drive efficiency, and constrain MN firing frequencies to those optimal for muscle contraction.
Application of GMM models to spoken language recognition

This paper presents research on automatic spoken language recognition based on statistical pattern recognition. As a model of identified language Gaussian Mixture Model was applied, both with diagonal and full covariance matrix. The influence of GMM order and parameterizations of speech signal on the recognition results were examined. Tests were done for 10 languages. Obtained results were discussed.
Human-Computer Interface using Gestures based on Neural Network

Gestures are powerful tools for non-ver bal communication. Human computer interface (HCI) is a growing field which reduces the complexity of interaction between human and machine in which gestures are used for conveying information or controlling the machine. In the present paper, static hand gestures are utilized for th is purpose. The paper presents a novel technique of recognizing hand gest ures i.e. A-Z alphabets, 0-9 numbers and 6 addition al control signals (for keyboard and mouse control) by extracting vari ous features of hand ,creating a feature vector tab le and training a neural network. The proposed work has a recognition rate of 99%.
A Reeection on Call-by-value

A number of compilers exploit the following strategy: translate a term to continuation-passing style (CPS) and optimize the resulting term using a sequence of reductions. Recent work suggests that an alternative strategy is superior: optimize directly in an extended source calculus. We suggest that the appropriate relation between the source and target calculi may be captured by a special case of a Galois connection known as a reeection. Previous work has focused on the weaker notion of an equational correspondence, which is based on equality rather than reduction. We show that Moggi's monad translation and Plotkin's CPS translation can both be regarded as reeections, and thereby strengthen a number of results in the literature.
A Doppler focusing approach for sub-Nyquist radar

We investigate the problem of a monostatic radar transceiver trying to detect a sparse target scene. Several past works employ compressed sensing (CS) algorithms to this type of problem, but either do not address sample rate reduction, impose constraints on the radar transmitter, or propose CS recovery methods with prohibitive dictionary size. Here, using the Xampling framework, we describe a sub-Nyquist sampling approach which overcomes the shortcomings of previous methods. Xampling allows reducing the number of samples needed to accurately represent the signal, directly in the analog-to-digital conversion process. After sampling, the entire digital recovery process is performed on the low rate samples without having to return to the Nyquist rate. With our recovery method we are able to obtain good detection performance even at SNRs as low as -25dB.
An efficient distributed cluster-head election technique for load balancing in wireless sensor networks

Energy constraint is the most critical problem in wireless sensor networks (WSNs). To address this issue, clustering has been introduced as an efficient way for routing. However, the available clustering algorithms do not efficiently consider the geographical information of nodes in cluster-head election. This leads to uneven distribution of cluster-heads and unbalanced cluster sizes that brings about uneven energy dissipation in clusters. In this paper, an Efficient Distributed Cluster-head Election technique for Load balancing (EDCEL) is proposed. The main criterion of the algorithm, dispersal of cluster-heads, is achieved by increasing the Euclidian distance between cluster-heads. Simulation results show the effectiveness of this approach in terms of balancing intra-cluster energy dissipation and lifetime longevity.
Linear-Time Algorithm for Update Games via Trap-Alternating-Strongly-Connected Components

An arena is a finite directed graph whose vertices are divided into two classes, V and V#; this forms the basic playground for a plethora of 2-players pebble games. We introduce and study a notion of connectivity for arenas, named trap-alternating-connectivity, where Player attempts to reach vertices while Player # works against. It is shown that every arena decomposes into trap-alternating-stronglyconnected components (ta-SCCs). Our main result is a linear time and space algorithm for computing this unique decomposition. Both the graph structures and the algorithm generalize the classical decomposition of a directed graph into its strongly-connected components (SCCs). The algorithm builds on a generalization of depth-first search (DFS), taking inspiration from Tarjan’s SCCs classical algorithm. The structures of palm-trees and jungles described in Tarjan’s original paper need to be revisited and generalized (i.e., ta-palm-trees and ta-jungles) in order to handle the 2-players pebble-game’s setting. This theory has direct applications in solving Update Games (UGs) faster. Dinneen and Khoussainov showed in 1999 that deciding who’s the winner in a given UG costs O(mn) time, where n is the number of vertices and m is the number of arcs. We solve that problem in Θ(m+n) linear time and space. The result is obtained by observing that the UG is a win for Player if and only if the arena comprises one single ta-SCC. It is also observed that the ta-palm-tree returned by the algorithm encodes routing information that an Θ(n)-space agent can consult to win the UG in O(1) time per move. Finally, the polynomial-time complexity for deciding Explicit McNaughton-Müller Games is also improved.
On the Effectiveness of Retransmission in Preserving Frame Error Rate over IEEE 802.11e/a WLANs

To preserve the frame error rate (FER) of multimedia applications in the polling-based HCCA of 802.11e/a WLAN is important especially under low signal-to-noise ratio (SNR) conditions. MAC frame retransmission is an effective technique to reduce the FER, especially when there has no better modulation and coding scheme (MCS) can be selected. The Surplus Bandwidth Allowance (SBA) field in the Traffic Specification (TSPEC) element in 802.11e standard specifies the excess allocation of time over and above the stated application rates belonging to this TSPEC, by taking into account the retransmissions. This paper first identifies the relationship between the surplus bandwidth allowance and the retransmissions, which is represented as the number of frame retransmission allowance within a polled TXOP (Transmission Opportunity). Then, it investigates the effectiveness of the retransmission technique in preserving the FER of traffic streams over 802.11e/a WLAN under low SNR, ranging from 5-14 dB. Simulation results show that to preserve the FER below 3% for MPEG-2 video traffic streams, the required SNR is reduced from 14 dB to 11 dB with one retry allowance, and can be further reduced to 9 dB if two retry allowances is adopted. This paper adopts IEEE 802.11 multipath channel model in simulation.
Preliminary report of NAD+-dependent amino acid dehydrogenase producing bacteria isolated from soil.

BACKGROUND Amino acid dehydrogenases (L-amino acid: oxidoreductase deaminating; EC 1.4.1.X) are members of the wider superfamily of oxidoreductases that catalyze the reversible oxidative deamination of an amino acid to its keto acid and ammonia with the concomitant reduction of either NAD+, NADP+ or FAD. These enzymes have been received much attention as biocatalysts for use in biosensors or diagnostic kits to screen amino acid metabolism disorders such as phenylketonuria (PKU), maple syrup urine disease (MSUD), homocystinuria (HCY) and hyperprolinemia. This study was aimed to isolation and screening of novel amino acid dehydrogenases from soil bacteriadehydrogenases from soil bacteria. METHODS The enzyme producing bacteria were selected among L-methionine and L-phenylalanine utilizers isolated from soil by thin layer chromatography, activity staining and confirmed by enzyme assay. Bacterial strains were identified by phenotypic and biochemical characteristics. The steady-state kinetic studies of enzymes were also performed. RESULTS In total of 230 tested strains, four of them were recognized as amino acid dehydrogenase producers that belong to species of Pseudomonas, Citrobacter and Proteus. They exhibited the desired NAD+-dependent dehydrogenase activities toward L-isoleucine, L-methionine, L-cysteine, L-serine and L-glutamine in oxidative deamination reaction. The specific activity of L-isoleucine dehydrogenase, L-methionine dehydrogenase and L-glutamine dehydrogenase for oxidative deamination of L-isoleucine, L-methionine and L-glutamine were 1.59, 1.2 and 0.73 U/mg, respectively. The Kcat/Km (s(-1). mM(-1)) values in these strains were as follows: L-isoleucine, 113.6, L-methionine, 62.05 and L-glutamine, 95.83. CONCLUSION This is the first report of occurrence a specific isoleucine dehydrogenase, glutamine dehydrogenase and methionine dehydrogenase in bacteria.
Modeling Neuron Selectivity Over Simple Midlevel Features for Image Classification

We now know that good mid-level features can greatly enhance the performance of image classification, but how to efficiently learn the image features is still an open question. In this paper, we present an efficient unsupervised midlevel feature learning approach (MidFea), which only involves simple operations, such as k-means clustering, convolution, pooling, vector quantization, and random projection. We show this simple feature can also achieve good performance in traditional classification task. To further boost the performance, we model the neuron selectivity (NS) principle by building an additional layer over the midlevel features prior to the classifier. The NS-layer learns category-specific neurons in a supervised manner with both bottom-up inference and top-down analysis, and thus supports fast inference for a query image. Through extensive experiments, we demonstrate that this higher level NS-layer notably improves the classification accuracy with our simple MidFea, achieving comparable performances for face recognition, gender classification, age estimation, and object categorization. In particular, our approach runs faster in inference by an order of magnitude than sparse coding-based feature learning methods. As a conclusion, we argue that not only do carefully learned features (MidFea) bring improved performance, but also a sophisticated mechanism (NS-layer) at higher level boosts the performance further.
Profiling and identifying users' activities with network traffic analysis

Traffic identification technique is used for classification of different network protocols and applications even with detection of users' network activities. In this paper, we conduct our study on some typical users' network activities and present a traffic identification method to describe the feature about users' behaviors. We convert users' network activities information into different sequences with frame size and inter-arrival time just like HMM model does. Then we use latent dirichlet allocation model to extract potential characterization from these activity sequences. We use some machine learning algorithms to classify different activities in the data, and we suggest a method to evaluate the mixed activities within a sequence. Our research shows that it is possible to distinguish exact users' on-line activities without inspection to packet payloads, and users' privacy may need more protection against traffic analysis.
Randomized Overhearing to Improve Routing and Energy Performance in Mobile Ad Hoc Networks * Sunho Lim

Since data transmission in wireless mobile ad hoc network (MANET) is broadcast in nature, every node receives or overhears every data transmission occurring in its vicinity. Some MANET routing protocols such as Dynamic Source Routing (DSR) exploit this feature to collect route information via overhearing. However, it poses a challenging problem when a power saving mechanism (PSM) such as the one specified in IEEE 802.11 is employed, where a packet advertisement period is separated from the actual data transmission period. When a node receives an advertised packet that is not destined to itself, it switches to a low-power state during the data transmission period, and thus, conserves power. Allowing no overhearing may critically deteriorate the performance of the underlying routing protocol, while unconditional overhearing may offset the advantage of using PSM. This chapter proposes a new communication mechanism, called RandomCast or Rcast, via which a sender can specify the desired level of overhearing in addition to the intended receiver. Therefore, it is possible that only a random set of nodes overhear and collect route information for future use. Extensive simulation using the ns-2 network simulator shows that Rcast improves not only the energy efficiency, but also the energy balance among the nodes compared This research was supported in part by NSF grants CCR-0098149, CCR-0208734, CCF-0429631, and EIA-0202007. E-mail address: sunho.lim@sdstate.edu E-mail address: c.yu91@csuohio.edu E-mail address: das@cse.psu. edu 116 Sunho Lim, Chansu Yu and Chita R. Das to the original IEEE 802.11 PSM and another recent similar mechanism, called OnDemand Power Management (ODPM) protocol.
Parallel algorithms for large scale constrained tensor decomposition

Most tensor decomposition algorithms were developed for in-memory computation on a single machine. There are a few recent exceptions that were designed for parallel and distributed computation, but these cannot easily incorporate practically important constraints, such as nonnegativity. A new constrained tensor factorization framework is proposed in this paper, building upon the Alternating Direction method of Multipliers (ADMoM). It is shown that this simplifies computations, bypassing the need to solve constrained optimization problems in each iteration, yielding algorithms that are naturally amenable to parallel implementation. The methodology is exemplified using nonnegativity as a baseline constraint, but the proposed framework can incorporate many other types of constraints. Numerical experiments are encouraging, indicating that ADMoM-based nonnegative tensor factorization (NTF) has high potential as an alternative to state-of-the-art approaches.