Miracle-dz/UniFAR-FTUs huggingface dataset:
Models of synchronized hippocampal bursts in the presence of inhibition. II. Ongoing spontaneous population events.

1. We extended our computer model of the CA3 region of the hippocampal slice in order to study spontaneous activity occurring in the presence and absence of synaptic inhibition. This was done by providing a steady inward current to the excitatory neurons, whose value was randomly chosen for each cell. With the parameters used, many of the excitatory cells would, if synaptically isolated, remain quiescent, whereas others would burst periodically with periods as brief as 750 ms. Simulations were run for as long as 10 s of neural activity. 2. In the presence of synaptic inhibition, neural activity became organized into recurring, partially synchronized events: clusters of neurons (6% to 12% of the population) would discharge together, with a period averaging 340 ms, shorter than the burst period of any individual neuron. A consequence of periodic clusters of cellular bursts was the widespread occurrence of periodic synchronized synaptic potentials, as have been observed in hippocampal slices and human temporal neocortical slices. The periods between these synaptic potentials are similar in the model to those observed experimentally. 3. The period could be slowed by either increasing the time constant of the slow inhibitory postsynaptic potential (IPSP), or by making the excitatory synapses more powerful. The period seems to be generated in part as follows. Consider those cells with rapid spontaneous discharge rates. An upper bound for the period corresponds to the interval between 1) such a cell's becoming responsive enough to an excitatory synaptic input to burst, and 2) such a cell's bursting spontaneously (i.e., in response to its own intrinsic inward current). For cells with rapid spontaneous discharge rates, the interval defined in this way is approximately 350 ms. 4. Different cells participated in each cluster. A given cluster was initiated by one cell or by two cells bursting together, and spread via excitatory synapses. Excitatory synaptic paths could be traced from the initiating cell(s), directly or through other participants, to all cells participating in a cluster. Spread of activity was limited by two mechanisms, so that not all cells synaptically excited by a participating cell would themselves participate. First, cells might be refractory from having participated in a recent cluster (since the intercluster period was less than the refractory time from a cellular burst to its responsiveness to a synaptic stimulus). Second, some cells might be synaptically inhibited. Synaptic inhibition in this model did not act rapidly enough to suppress the cluster totally. (ABSTRACT TRUNCATED AT 400 WORDS)
Impact of Scale-free Topologies on Gossiping in Ad Hoc Networks

We show that scale-free topologies have a positive impact on the performance of gossiping algorithms in peer-to-peer overlay networks. This result is important in the context of ad hoc networks, where each node participates in controlling the network topology. Our study shows that, when combined with such topologies, typical gossiping algorithms tend to require fewer messages and experience smaller latency than when combined with other topologies, such as rings or grids. This suggests that the topology control scheme should aim at producing an overlay network that exhibits scale-free characteristics.
Applications of Low Altitude Remote Sensing in Agriculture upon Farmers' Requests– A Case Study in Northeastern Ontario, Canada

With the growth of the low altitude remote sensing (LARS) industry in recent years, their practical application in precision agriculture seems all the more possible. However, only a few scientists have reported using LARS to monitor crop conditions. Moreover, there have been concerns regarding the feasibility of such systems for producers given the issues related to the post-processing of images, technical expertise, and timely delivery of information. The purpose of this study is to showcase actual requests by farmers to monitor crop conditions in their fields using an unmanned aerial vehicle (UAV). Working in collaboration with farmers in northeastern Ontario, we use optical and near-infrared imagery to monitor fertilizer trials, conduct crop scouting and map field tile drainage. We demonstrate that LARS imagery has many practical applications. However, several obstacles remain, including the costs associated with both the LARS system and the image processing software, the extent of professional training required to operate the LARS and to process the imagery, and the influence from local weather conditions (e.g. clouds, wind) on image acquisition all need to be considered. Consequently, at present a feasible solution for producers might be the use of LARS service provided by private consultants or in collaboration with LARS scientific research teams.
Requirements for Consent-Based Communications in the Session Initiation Protocol (SIP)

The Session Initiation Protocol (SIP) supports communications across many media types, including real-time audio, video, text, instant messaging, and presence. In its current form, it allows session invitations, instant messages, and other requests to be delivered from one party to another without requiring explicit consent of the recipient. Without such consent, it is possible for SIP to be used for malicious purposes, including spam and denial-of-service attacks. This document identifies a set of requirements for extensions to SIP that add consent-based communications. This memo provides information for the Internet community.
Spectral scaling of the Leray-α model for two-dimensional turbulence

We present data from high-resolution numerical simulations of the Navier–Stokes-α and the Leray-α models for two-dimensional turbulence. It was shown previously (Lunasin et al 2007 J. Turbul. 8 30) that for wavenumbers k such that kα ≫ 1, the energy spectrum of the smoothed velocity field for the two-dimensional Navier–Stokes-α (NS-α) model scales as k−7. This result is in agreement with the scaling deduced by dimensional analysis of the flux of the conserved enstrophy using its characteristic time scale. We therefore hypothesize that the spectral scaling of any α-model in the sub-α spatial scales must depend only on the characteristic time scale and dynamics of the dominant cascading quantity in that regime of scales. The data presented here, from simulations of the two-dimensional Leray-α model, confirm our hypothesis. We show that for kα ≫ 1, the energy spectrum for the two-dimensional Leray-α scales as k−5, as expected by the characteristic time scale for the flux of the conserved enstrophy of the Leray-α model. These results lead to our conclusion that the dominant directly cascading quantity of the model equations must determine the scaling of the energy spectrum.
Practical Kernel-Based Reinforcement Learning

Kernel-based reinforcement learning (KBRL) stands out among approximate reinforcement learning algorithms for its strong theoretical guarantees. By casting the learning problem as a local kernel approximation, KBRL provides a way of computing a decision policy which converges to a unique solution and is statistically consistent. Unfortunately, the model constructed by KBRL grows with the number of sample transitions, resulting in a computational cost that precludes its application to large-scale or on-line domains. In this paper we introduce an algorithm that turns KBRL into a practical reinforcement learning tool. Kernel-based stochastic factorization (KBSF) builds on a simple idea: when a transition probability matrix is represented as the product of two stochastic matrices, one can swap the factors of the multiplication to obtain another transition matrix, potentially much smaller than the original, which retains some fundamental properties of its precursor. KBSF exploits such an insight to compress the information contained in KBRL's model into an approximator of fixed size. This makes it possible to build an approximation considering both the difficulty of the problem and the associated computational cost. KBSF's computational complexity is linear in the number of sample transitions, which is the best one can do without discarding data. Moreover, the algorithm's simple mechanics allow for a fully incremental implementation that makes the amount of memory used independent of the number of sample transitions. The result is a kernel-based reinforcement learning algorithm that can be applied to large-scale problems in both off-line and on-line regimes. We derive upper bounds for the distance between the value functions computed by KBRL and KBSF using the same data. We also prove that it is possible to control the magnitude of the variables appearing in our bounds, which means that, given enough computational resources, we can make KBSF's value function as close as desired to the value function that would be computed by KBRL using the same set of sample transitions. The potential of our algorithm is demonstrated in an extensive empirical study in which KBSF is applied to difficult tasks based on real-world data. Not only does KBSF solve problems that had never been solved before, but it also significantly outperforms other state-of-the-art reinforcement learning algorithms on the tasks studied.
1 2 Integration of Bayesian inference 3 techniques with mathematical modelling 4 5 6

Skeptical views of the scientific value of modelling argue that there is no 13 true model of an ecological system, but rather several adequate descriptions of 14 different conceptual basis and structure. My study addresses this question using a 15 complex ecosystem model, developed to guide the water quality criteria setting 16 process in the Hamilton Harbour (Ontario, Canada), along with a simpler plankton 17 model that considers the interplay among phosphate, detritus, and generic 18 phytoplankton and zooplankton state variables. Predictions from the two models 19 are combined using the respective standard error estimates as weights in a 20 weighted model average. The two eutrophication models are used in conjunction 21 with the SPAtially Referenced Regressions On Watershed attributes (SPARROW) 22 watershed model. The Bayesian nature of my work is used: (i) to alleviate problems 23 of spatiotemporal resolution mismatch between watershed and receiving waterbody 24 models; and (ii) to overcome the conceptual or scale misalignment between 25 processes of interest and supporting information. The lessons learned from this 26 study will contribute towards the development of integrated modelling frameworks. 27 28
Enzymatic and Genetic Characterization of Carbon and Energy Metabolisms by Deep-Sea Hydrothermal Chemolithoautotrophic Isolates of Epsilonproteobacteria

ABSTRACT The carbon and energy metabolisms of a variety of cultured chemolithoautotrophic Epsilonproteobacteria from deep-sea hydrothermal environments were characterized by both enzymatic and genetic analyses. All the Epsilonproteobacteria tested had all three key reductive tricarboxylic acid (rTCA) cycle enzymatic activities—ATP-dependent citrate lyase, pyruvate:ferredoxin oxidoreductase, and 2-oxoglutarate:ferredoxin oxidoreductase—while they had no ribulose 1,5-bisphosphate carboxylase (RubisCO) activity, the key enzyme in the Calvin-Benson cycle. These results paralleled the successful amplification of the key rTCA cycle genes aclB, porAB, and oorAB and the lack of success at amplifying the form I and II RubisCO genes, cbbL and cbbM. The combination of enzymatic and genetic analyses demonstrates that the Epsilonproteobacteria tested use the rTCA cycle for carbon assimilation. The energy metabolisms of deep-sea Epsilonproteobacteria were also well specified by the enzymatic and genetic characterization: hydrogen-oxidizing strains had evident soluble acceptor:methyl viologen hydrogenase activity and hydrogen uptake hydrogenase genes (hyn operon), while sulfur-oxidizing strains lacked both the enzyme activity and the genes. Although the energy metabolism of reduced sulfur compounds was not genetically analyzed and was not fully clarified, sulfur-oxidizing Epsilonproteobacteria showed enzyme activity of a potential sulfite:acceptor oxidoreductase for a direct oxidation pathway to sulfate but no activity of AMP-dependent adenosine 5′-phosphate sulfate reductase for a indirect oxidation pathway. No activity of thiosulfate-oxidizing enzymes was detected. The enzymatic and genetic characteristics described here were consistent with cellular carbon and energy metabolisms and suggest that molecular tools may have great potential for in situ elucidation of the ecophysiological roles of deep-sea Epsilonproteobacteria.
A Discriminative Latent Model of Image Region and Object Tag Correspondence

We propose a discriminative latent model for annotating images with unaligned object-level textual annotations. Instead of using the bag-of-words image representation currently popular in the computer vision community, our model explicitly captures more intricate relationships underlying visual and textual information. In particular, we model the mapping that translates image regions to annotations. This mapping allows us to relate image regions to their corresponding annotation terms. We also model the overall scene label as latent information. This allows us to cluster test images. Our training data consist of images and their associated annotations. But we do not have access to the ground-truth region-to-annotation mapping or the overall scene label. We develop a novel variant of the latent SVM framework to model them as latent variables. Our experimental results demonstrate the effectiveness of the proposed model compared with other baseline methods.
Entanglement of orbital angular momentum states between an ensemble of cold atoms and a photon

Recently, atomic ensemble and single photons were successfully entangled by using collective enhancement [D. N. Matsukevich et al., Phys. Rev. Lett. 95, 040405 (2005)], where atomic internal states and photonic polarization states were correlated in a nonlocal manner. Here, we experimentally clarified that in an ensemble of atoms and a photon system, there also exists an entanglement concerned with spatial degrees of freedom. Generation of higher-dimensional entanglement between remote atomic ensemble and an application to condensed matter physics are also discussed.
A Robust Dual Digital-Image Watermarking Technique

In this paper, a robust dual watermarking technique is suggested that incorporates two watermarks in a host image for improved protection and robustness. To embed the watermark robustly and imperceptibly, watermark bits are added to the significant coefficients of each subband selected by considering the human visual system (HVS) characteristics. A watermark, named boat (will be called the secondary watermark), is embedded in the wavelet domain of a primary watermark before being embedded in the host image. From the experimental results it can be observed that proposed method is robust to wide variety of attacks.
New perturbative solutions of the Kerr-Newman dilatonic black hole field equations

This work describes new perturbative solutions to the classical, four-dimensional Kerr-Newman dilaton black hole field equations. Our solutions do not require the black hole to be slowly rotating. The unperturbed solution is taken to be the ordinary Kerr solution and the perturbation parameter is effectively the square of the charge-to-mass ratio (Q/M){sup 2} of the Kerr-Newman black hole. The solutions show the expected conjugation (mirror) symmetry, which maps the small coupling sector to the strong coupling sector ({phi}{r_arrow}{minus}{phi}). We also calculate the gyromagnetic ratio of the black hole. {copyright} {ital 1997} {ital The American Physical Society}
An Analysis of the Determinants of Managerial Pay in the Czech Republic

The purpose of this paper is to examine the determinants of the variation inCzech managers' pay levels. The main questions we attempted to answer: Arethe managers in stateowned firms compensated differently than those inprivate owned firms? How much of hte difference in pay is explained bydifferences in individual characteristics and job levels? What is theimportance of the regional location or the industry affiliation of the firmsfor managerial pay differentials? For this purpose we used data from across-section of Czech managers in 1996 and estimated earnings equationsaugmented with a host of explanatory variables related to firm and jobcharacteristics.
On Novel Economic-Inspired Centrality Measures in Weighted Networks

Current information networks acting as the fundamental infrastructure of our society, possess the economic-social characteristics, so, in formulating new definitions and computational models for the networked environment, it is imperative to take economic and incentive considerations into account. The paperpsilas contribution is twofold: first, to characterize the economic implication of some proposed centrality in weighted network, we design the VCG (Vickrey-Clarke-Groves) overpayment based centrality in bi-connected networks, and compare it with existing global efficiency based centrality. Our experiments on weighted scale-free networks and small-world networks show the high correlation between global efficiency based centrality and VCG-based centrality (the Pearson correlation coefficients exceed 0.95); Then, inspired by the definition of global efficiency based centrality, we propose local efficiency based centrality, which, unlike global efficiency based centrality, can be calculated locally, and illustrates the effect of the proposed metric on the attack vulnerability of those weighted networks through comparing with strength-based attack.
DESIGN AND IMPLEMENTATION OF AN INDOOR LOCALIZATION SYSTEM FOR THE OMNIBOT OMNI-DIRECTIONAL PLATFORM

The design and implementation of an indoor absolute localization system for a novel threedegree-of-freedom (DOF) omni-directional mobile platform is presented. This localization system is a modification of the Cricket indoor localization system developed at the Massachusetts Institute of Technology (MIT) and is similar to the Global Positioning System (GPS) used in outdoor applications. The designed system has an active mobile architecture with actively transmitting beacons mounted on the mobile platform, and receivers (listeners) fixed at known positions on the ceiling of the operating environment. Position estimates of the mobile beacons, relative to a global coordinate system, are obtained using trilateration; a technique that determines the position of a beacon using distance estimates between the beacon and the fixed listeners. The distance estimates between the beacons and listeners are calculated using the time-of-flight of radio frequency and ultrasonic signals. Testing of the localization system was performed and experimental results are presented. These preliminary results indicate that the modified Cricket system has improved accuracy in distance and position estimation compared to the original system, as well as a higher position update rate when performing tracking of the mobile platform.
COMMENTARY The Subiculum Comes of Age

The subiculum has long been considered as a simple bidirectional relay region interposed between the hippocampus and the temporal cortex. Recent evidence, however, suggests that this region has specific roles in the cognitive functions and pathological deficits of the hippocampal formation. A group of 20 researchers participated in an ESF-sponsored meeting in Oxford in September, 2005 focusing on the neurobiology of the subiculum. Each brought a distinct expertise and approach to the anatomy, physiology, psychology, and pathologies of the subiculum. Here, we review the recent findings that were pre- sented at the meeting. V V C 2006 Wiley-Liss, Inc.
Codebugger: a software tool for cooperative debugging

Debugging of large-scale systems are essentially cooperative and need collaboration of group developers. However, most existing debugging tools are for single developer. With single-user tools, only one developer can operate the debugging process while others are frequently requested to gather before the screen of a single computer on solving problems, which makes error location and correction so inconvenient and inefficient. We developed Codebugger---a cooperative debugging tool for Java that supports group developers to participate in one debugging session and cooperate on solving problems at the same time. This paper introduces principles of cooperative software tools, the architecture of Codebugger and discusses some technical issues concerning its implementation.
Synthesis Of Self-resetting Stage Logic Pipelines

As designers began to pack multi-million transistors onto a single chip, their reliance on a global clocking signal to orchestrate the operations of the chip has started to face almost insurmountable difficulties. As a result, designers started to explore clockless circuits to avoid the global clocking problem. Recently, self-resetting circuits implemented in dynamic logic families have been proposed as viable clockless alternatives. While these circuits can produce excellent performances, they display serious limitations in terms of area cost and power consumption. A middle-of-the-road alternative, which can provide a good performance and avoid the limitations seen in dynamic self-resetting circuits, would be to implement self-resetting behavior in static circuits. This alternative has been introduced recently as Self-Resetting Stage Logic and used to propose three types of clockless pipelines. Experimental studies show that these pipelines have the potential to produce high throughputs with a minimum area overhead if a suitable synthesis methodology is available. This thesis proposes a novel synthesis methodology to design and verify clockless pipelines implemented in SRSL by taking advantage of the maturity of current CAD tools. This methodology formulates the synthesis problem as a combinatorial analytical problem for which a run-time efficient exact solution is difficult to derive. Consequently, a two-phase algorithm is proposed to synthesize these pipelines from gate netlists subject to user-specified constraints. The first phase is a heuristic based on the as-soon-as-possible scheduling strategy in which each gate of the netlist is assigned to a single pipeline stage without violating the period constraint of each pipeline stage. On the other hand, the second phase consists of a heuristic, based on the
Recommendation for online social feeds by exploiting user response behavior

In recent years, online social networks have been dramatically expanded. Active users spend hours communicating with each other via these networks such that an enormous amount of data is created every second. The tremendous amount of newly created information costs users much time to discover interesting messages from their online social feeds. The problem is even exacerbated if users access these networks via mobile devices. To assist users in discovering interesting messages efficiently, in this paper, we propose a new approach to recommend interesting messages for each user by exploiting the user's response behavior. We extract data from the most popular social network, and the experimental results show that the proposed approach is effective and efficient.
NOC architecture design for multi-cluster chips

For the next generation of multi-core processors, the on-chip interconnection networks must be efficient to achieve high data throughput and performance. Moreover, these interconnections must be flexible and scalable in order to provide parallel on-demand computing. For this reason, the goal of this paper is to present design decisions of a multi-cluster NoC (MCNoC) architecture in order to support collective communication patterns through topology reconfiguration on an FPGA-based multi-cluster chip. The MCNoCpsilas results show a small area occupation, low power consumption and high performance.