Miracle-dz/UniFAR-FTUs huggingface dataset:
Article Title: Extracting Non-linear Integrate-and-fire Models from Experimental Data Using Dynamic I–v Curves Extracting Non-linear Integrate-and-fire Models from Experimental Data Using Dynamic I–v Curves

This paper is made available online in accordance with publisher policies. Please scroll down to view the document itself. Please refer to the repository record for this item and our policy information available from the repository home page for further information. To see the final version of this paper please visit the publisher's website. Access to the published version may require a subscription. Abstract The dynamic I –V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current–voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected-conductance protocols. The resulting low-dimensional neu-ron models—of the refractory exponential integrate-and-fire type—provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons.
Drastic immunoreactivity changes between the immature and mature forms of the Sendai virus HN and F0 glycoproteins

The immunoreactivity of the Sendai virus HN and F0 glycoproteins was shown to mature before reaching the final form exhibited by the native mature proteins. The maturation process differed for the two proteins. The native F0 immunoreactivity was shown to be defined cotranslationally, and the addition of high-mannose sugar residues may represent the final step in defining the maturation of immunoreactivity. On the other hand, native HN immunoreactivity was slowly fashioned during the hour after the completion of protein synthesis. Although addition of high-mannose sugar could constitute a necessary step in this slow maturation process, it was shown not to be sufficient. Processing of high-mannose sugars and HN self-association in homodimers and homotetramers were investigated as possible steps involved in the slow maturation of HN immunoreactivity. They were found not to play a significant role. On the other hand, conformational changes presumably took place during the maturation of HN immunoreactivity. Drastic immunoreactivity differences were also demonstrated between the native and denatured forms of the glycoproteins. Possible implications of these results in defining the pathways of glycoprotein synthesis are discussed.
Understanding the internet as-level structure

The Internet is a vast distributed system consisting of a myriad of independent networks interconnected to each other by business relationships. The border gateway protocol is the glue that keeps this structure connected. Characterizing and modeling the Internet topology is important to our understanding of Internet routing and its interplay with technical, economic and social forces. In this thesis we address several challenges that emerge when studying the Internet connectivity. First, not all the observed changes in connectivity correspond to actual changes in the topology. There are changes that may be caused by transient routing dynamics while others are real topology changes. The problem of distinguishing between these two types of changes is non-trivial, and we call it the liveness problem. We propose a solution to this problem based on a birth/death model of observed links. This solution allows to accurately detect the permanent changes in the Internet topology graph and measure topology dynamics in an accurate way. The second problem in obtaining accurate topology models is the completeness problem , which consists in establishing how much of the real topology is missing from the observed data. We address the completeness problem by defining some bounds on how (in)complete is the graph provided by the current observation. The results using ground truth information obtained from a Tier-1 ISP indicate that the observed Internet graph contains most of the customer-provider links, but may be missing the vast majority of the peer-peer links. Finally, we study how protocol properties such as routing convergence and resilience to prefix hijack attacks depend on the connectivity and relationship between networks. We find that networks at the border of the Internet undergo more severe path exploration because of the higher number of paths available to reach other destinations. On the other hand, we show that Tier-1 networks have the fastest convergence time because of the limited number of alternative routes. In terms of prefix hijack attacks, we surprisingly find that Tier-1 networks at the core of the Internet are vulnerable to hijack attacks from customers because of the business nature of BGP route selection. Based on our observations, we formulate a connectivity recommendation for ISPs to increase their resiliency to these type of attacks.
Towards effective user-guided robot search (extended abstract)

In recent years there has been a growing interest amongst Human-Robot Interaction (HRI) researchers in the usage of robotic systems for exploration or search missions [6, 3, 4]. In the traditional approach to robot supervision by humans, knows as camera guided teleoperation [3], the operator navigates the robot while interpreting camera imagery. Both tasks require constant attention, and contribute to operator’s workload. Automating the robot navigation task, as suggested in [5], is one possible step to reduce workload. Another step is to eliminate the need to view live video, thus turning the interface to use asynchronous video. Recent work [3] on multi-robot interfaces investigated the usage of asynchronous operation schemes in the context of Urban Search And Rescue (USAR) missions [2]. With the asynchronous approach, robots explore the environment autonomously, while the operator is presented with recorded imagery (asynchronous) from the robots’ camera, rather than live imagery (synchronous). Asynchronous interfaces have several advantages. First, scaling up the number of robots is easier, since the operator no longer has to observe live video feeds from multiple robots. This can help to reduce operator’s workload when the number of robots is increased [4]. Moreover, communication constraints can limit the ability to stream live video from the robots and to control them in real-time. This could severely affect the operator’s ability to extract useful information and maintain spatial orientation [1]. With the
Generalized Insertion Region Guides for Delaunay Mesh Refinement

Mesh generation by Delaunay refinement is a widely used technique for constructing guaranteed quality triangular and tetrahedral meshes. The quality guarantees are usually provided in terms of the bounds on circumradius-to-shortest-edge ratio and on the grading of the resulting mesh. Traditionally circumcenters of skinny elements and middle points of boundary faces and edges are used for the positions of inserted points. However, recently variations of the traditional algorithms are being proposed that are designed to achieve certain optimization objectives by inserting new points in neighborhoods of the center points. In this paper we propose a general approach to the selection of point positions by defining one-, two-, and three-dimensional selection regions such that any point insertion strategy based on these regions is automatically endowed with the theoretical guarantees proven here. In particular, for the input models defined by planar linear complexes under the assumption that no input angle is le.
Statistical theories of model fitting

Statistics has long been concerned with fitting and choosing good models for data. In this chapter we discuss the statistical theory pertinent to the problem of generalization, and the reasons perceived by statisticians why they have not already solved the problem. This includes statistical decision theory, Bayes factors, probability scoring, shrinkage methods, model-averaging, C p , AIC and allied indices, and the use of performance bounds. The assessment of generalization performance is also discussed, an important task much neglected in the neural networks and machine learning literature. Statistics has been concerned with the fitting of models for centuries, and several competing theories have been developed over at least decades. Have these solved the problem of generalization? Some statisticians certainly think they have a good a solution as is possible. We will explore the parts of the argument most relevant to the machine learning and neural network community. The most pertinent reference for much of this material is Ripley (1996, Chapter 2); general modern references on statistical decision theory include Robert (1994), and Bernardo and Smith (1994).
Computer-Based Annotation of Putative AraC/XylS-Family Transcription Factors of Known Structure but Unknown Function

Currently, about 20 crystal structures per day are released and deposited in the Protein Data Bank. A significant fraction of these structures is produced by research groups associated with the structural genomics consortium. The biological function of many of these proteins is generally unknown or not validated by experiment. Therefore, a growing need for functional prediction of protein structures has emerged. Here we present an integrated bioinformatics method that combines sequence-based relationships and three-dimensional (3D) structural similarity of transcriptional regulators with computer prediction of their cognate DNA binding sequences. We applied this method to the AraC/XylS family of transcription factors, which is a large family of transcriptional regulators found in many bacteria controlling the expression of genes involved in diverse biological functions. Three putative new members of this family with known 3D structure but unknown function were identified for which a probable functional classification is provided. Our bioinformatics analyses suggest that they could be involved in plant cell wall degradation (Lin2118 protein from Listeria innocua, PDB code 3oou), symbiotic nitrogen fixation (protein from Chromobacterium violaceum, PDB code 3oio), and either metabolism of plant-derived biomass or nitrogen fixation (protein from Rhodopseudomonas palustris, PDB code 3mn2).
ASSIST: A Specialized Search Engine for the social sciences using text mining

The ASSERT search engine is a modular platform allowing us to plug in advance text mining tools. Extending the ASSERT search engine with existing TM tools we intend to get a simple and complete prototype to elicit user requirements in a collaborative way. Based on the users feedback received from their prototype evaluation we can continuously update and improve the embedded TM tools to obtain the final ASSIST search-engine.
The MoCA and ADL Items Separate Mild Cognitive Impairment and Dementia in Parkinson's Disease

The aim of this study is to establish a brief screening tool to classify PD patients as PD with normal cognition (PD-N), PD patients with mild cognitive impairment (PD-MCI) and PD patients with dementia (PD-D). There has been emerging evidence that the MoCA (Montreal Cognitive Assessment) shows potential for the brief assessment of cognition to differentiate among PD patients. One possible solution to further improve the discrimination among PD-D, PD-MCI and PD-N groups is to examine Instrumental Activities of Daily Living (IADL) measures in conjunction with the MoCA. A convenience sample of 162 patients suffering from PD and 53 volunteer control subjects were examined in a movement disorders center. Extensive neuropsychological testing was done to classify the PD patients into PD-N, PD-MCI or PD-D. The 24 patients were diagnosed as PD-D based on the Movement Disorders Society Task Force criteria. For PD-MCI, two criteria were used: 1.5SD:2 in one-domain (1.5 SD below the norms on two measures in at least one of four cognitive domains) and 1.5SD:1 in two-domains (1.5 SD below normative data in at least one measure but in two domains) which made a diagnosis of 34 and 39 PD-MCI patients respectively. The remaining patients were classified as PD-N. For both the MCI criteria, the results suggest that 1) for discriminating PD-MCI from PD-N, the MoCA is a sufficiently suitable screening measure that is not improved by adding ADL measures, 2) for distinguishing PD-D from PD-MCI, the MoCA and the full ADL-IS questionnaire can be administered to a patient suffering from PD. When time is limited and depending on the possibility of answering the questions regarding the ADL-IS items, the MoCA along with the Muddled and Complex Medication ADL-IS items should be administered. When no scores are obtained for Muddled, then MoCA along with Complex Medication ADL-IS item is sufficient to discriminate PD-D from PD-MCI. However, if no scores are obtained for Complex Medication item, then an average of four ADL-IS items should be taken along with the MoCA. This attractive brief screening tool helps in detection of cognitive impairment in the elderly.
Systematic Generation of An Irreducible Polynomial of an Arbitrary Degree m over Fp Such That p ≫ m

This paper proposes a method for generating an irreducible polynomial of an arbitrary degree m over an arbitrary prime field Fp such that p > m. The proposed method is closely related to the minimal polynomial determination and therefore it has the following features: its complexity has little dependency on the size of characteristic p, its calculation cost is explicitly given with degree m, and it can generate primitive polynomials when pm - 1 is factorized as the product of prime numbers. The restriction p > m comes from using Newtonpsilas formula.
NoSOCS in SDSS – I. Sample definition and comparison of mass estimates

We use Sloan Digital Sky Survey (SDSS) data to investigate galaxy cluster properties of the systems first detected within Digitized Second Palomar Observatory Sky Survey. With the high-quality photometry of SDSS, we derived new photometric redshifts and estimated richness and optical luminosity. For a subset of low-redshift (z ≤ 0.1) clusters, we have used SDSS spectroscopic data to identify groups in redshift space in the region of each cluster, complemented with massive systems from the literature to assure the continuous mass sampling. A method to remove interlopers is applied, and a virial analysis is performed resulting in the estimates of velocity dispersion, mass and a physical radius for each low-z system. We discuss the choice of maximum radius and luminosity range in the dynamical analysis, showing that a spectroscopic survey must be complete to at least M* + 1 if one wishes to obtain accurate and unbiased estimates of velocity dispersion and mass. We have measured X-ray luminosity for all clusters using archival data from ROSATAll Sky Survey. For a smaller subset (21 clusters), we selected temperature measures from the literature and estimated mass from the M-T x relation, finding that they show good agreement with the virial estimate. However, these two mass estimates tend to disagree with the caustic results. We measured the presence of substructure in all clusters of the sample and found that clusters with substructure have virial masses higher than those derived from T x . This trend is not seen when comparing the caustic and X-ray masses. That happens because the caustic mass is estimated directly from the mass profile, so it is less affected by substructure.
Simulation of MANETs: a qualitative comparison between JiST/SWANS and ns-2

Simulations play a vital role in the development and testing of ad-hoc networking protocols. However, the simulation of large networks is still a tedious task that consumes a lot of computing power, memory, and time. JiST/SWANS is a relatively new, Java-based ad hoc network simulator that reaches very good runtime behavior. Though the creators of JiST/SWANS already proved the capability of the simulation engine, they did not provide results that show the validity of simulations using the SWANS ad hoc network stack. In this paper, we compare protocols and models imple-mented in SWANS to the corresponding implementations in ns-2. Using identical input parameters, we show where results are comparable and analyze reasons for differences. By showing that results achieved with JiST/SWANS are equivalent to those of ns-2, we support the usage of JiST/SWANS. As ns-2 performance problems when simulating hundreds or thousands of nodes and the complex mixture of Tcl and C/C++ code in ns-2, JiST/SWANS could be an interesting alternative. For a further simplification when using JiST/SWANS, we shortly introduce our simulation execution framework, which allows for generation, execution and evaluation of complex simulation studies.
The attributes similar-degree of complex networks

The self-similarity of complex has extensive practical background in real world. It is similar to the phenomena of social relationships: “things of one kind come together, birds of a feather flock together”. Hence, we proposed the self-similarity network evolving model based on attributes similarity between the nodes. In network each node has the attribute value, by this computed similarity between the nodes. If two nodes attribute similarity falls in certain sector, then established the connection between nodes. The simulations make clear that the degree distribution of the self-similarity network similar to the small-world networks. The clustering and the average path of the self-similarity network are smaller than BA model and are bigger than small world. Similarity network model is a new characteristic of complex network except the BA mode and the small world mode. On the other hand, the self-similarity network has good robustness to random fault and deliberately attack.
Genetically modified luminescent bacteria Ralostonia solanacerum, Pseudomonas syringae, Pseudomonas savastanoi, and wild type bacterium Vibrio fischeri in biosynthesis of gold nanoparticles from gold chloride trihydrate

The effect of different genetically engineered bacteria, Pseudomonas syringae, Pseudomonas savastanoi, and Ralostonia solanacerum and also a natural marine bacterial species, Vibrio fischeri NRRL B-11177, is studied in producing gold nanoparticles. This is the first report about the biosynthesis of gold nanoparticles by natural and genetically engineered luminescent bacteria. These microorganisms reduced gold ions and produced fairly monodisperse nanoparticles. TEM analysis indicated that spherical nano gold particles in the different diameters and shapes were obtained at pH values of 6.64. In this biosynthesis protocol, the gold nanoparticles with desired shape and size can be prepared.
On relevance, time and query expansion

We present the results of our exploratory analysis on the relationship that exists between relevance and time. We observe how the amount of documents published in a given interval of time is related to the probability of relevance, and, using the time series analysis, we show the existence of a correlation between time and relevance. As an initial application of this analysis, we study query expansion exploiting the detection of publication time peaks over the Blog06 collection. We finally propose an effective approach for the query expansion in the blog search domain. Our approach is based on the documents publication trend being so completely independent of any external resource.
Sterol Synthesis in Diverse Bacteria

Sterols are essential components of eukaryotic cells whose biosynthesis and function has been studied extensively. Sterols are also recognized as the diagenetic precursors of steranes preserved in sedimentary rocks where they can function as geological proxies for eukaryotic organisms and/or aerobic metabolisms and environments. However, production of these lipids is not restricted to the eukaryotic domain as a few bacterial species also synthesize sterols. Phylogenomic studies have identified genes encoding homologs of sterol biosynthesis proteins in the genomes of several additional species, indicating that sterol production may be more widespread in the bacterial domain than previously thought. Although the occurrence of sterol synthesis genes in a genome indicates the potential for sterol production, it provides neither conclusive evidence of sterol synthesis nor information about the composition and abundance of basic and modified sterols that are actually being produced. Here, we coupled bioinformatics with lipid analyses to investigate the scope of bacterial sterol production. We identified oxidosqualene cyclase (Osc), which catalyzes the initial cyclization of oxidosqualene to the basic sterol structure, in 34 bacterial genomes from five phyla (Bacteroidetes, Cyanobacteria, Planctomycetes, Proteobacteria, and Verrucomicrobia) and in 176 metagenomes. Our data indicate that bacterial sterol synthesis likely occurs in diverse organisms and environments and also provides evidence that there are as yet uncultured groups of bacterial sterol producers. Phylogenetic analysis of bacterial and eukaryotic Osc sequences confirmed a complex evolutionary history of sterol synthesis in this domain. Finally, we characterized the lipids produced by Osc-containing bacteria and found that we could generally predict the ability to synthesize sterols. However, predicting the final modified sterol based on our current knowledge of sterol synthesis was difficult. Some bacteria produced demethylated and saturated sterol products even though they lacked homologs of the eukaryotic proteins required for these modifications emphasizing that several aspects of bacterial sterol synthesis are still completely unknown.
Biometry-based concentric tubes robot for vitreoretinal surgery

Vitreoretinal surgery requires dexterous manoeuvres of tiny surgical tools in the confined cavity of the human eye through incisions made on the sclera. The fulcrum effect stemming from these incisions limits the safely reachable intraocular workspace and may result in scleral stress and collision with the intraocular lens. This paper proposes a concentric tube robot for panretinal interventions without risking scleral or lens damage. The robot is designed based on biometric measurements of the human eye, the required workspace, and the ease of incorporation in the clinical workflow. Our system is suited to 23G vitreoretinal surgery, which does not require post-operative suturing, by comprising sub-millimetre concentric tubes. The proposed design is modular and features a rapid tube-exchange mechanism. To grasp and manipulate tissue, a sub-millimetre flexible gripper is fabricated. Experiments demonstrate the ability to reach peripheral retinal regions with limited motion at the incision point and no risk of lens contact.
Interactive display of isosurfaces with global illumination

In many applications, volumetric data sets are examined by displaying isosurfaces, surfaces where the data, or some function of the data, takes on a given value. Interactive applications typically use local lighting models to render such surfaces. This work introduces a method to precompute or lazily compute global illumination to improve interactive isosurface renderings. The precompiled illumination resides in a separate volume and includes direct light, shadows, and intersections. Using this volume, interactive globally illuminated renderings of isosurfaces become feasible while still allowing dynamic manipulation of lighting, viewpoint and isovalue.