Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuronal spike event generation by memristors

New memristors-based neuronal spike event generator is introduced. By using the dynamic properties of conditional resistance switching of a practical bistable memristive device, the neuronal action potential is generated describing both the integrate-and-fire spiking events and the long enough refractory period of nerve membrane cells. The memristor offers the dual time-constants which model the unbalanced charging and discharging periods of the spike signals. With a Pt/TiO2/Pt memristive device having the ROFF/RON resistance ratio of 3000, the memristor-based spike generator offers spike trains with about 0.03% duty.
Identification of the Question Focus: Combining Syntactic Analysis and Ontology-based Lookup through the User Interaction

Most question-answering systems contain a classifier module which determines a question category, based on which each question is assigned an answer type. However, setting up syntactic patterns for this classification is a big challenge. In addition, in the case of ontology-based systems, the answer type should be aligned to the queried knowledge structure. In this paper, we present an approach for determining the answer type semi-automatically. We first identify the question focus using syntactic parsing, and then try to identify the answer type by combining the head of the focus with the ontology-based lookup. When this combination is not enough to make conclusions automatically, the user is engaged into a dialog in order to resolve the answer type. User selections are saved and used for training the system in order to improve its performance over time. Further on, the answer type is used to show the feedback and the concise answer to the user. Our approach is evaluated using 250 questions from the Mooney Geoquery dataset.
A Spatial Filtering Specification for the Autologistic Model

The autologistic model describes binary correlated data; its spatial version describes georeferenced binary data exhibiting spatial dependence. The conventional specification of a spatial autologistic model involves difficult-to-nearly-impossible computations to ensure that appropriate sets of probabilities sum to 1. Work summarized here accounts for spatial autocorrelation by including latent map pattern components as covariates in a model specification. These components derive from the surface zonation scheme used to aggregate attribute data, to construct a geographic weights matrix, and to evaluate geographic variability. The illustrative data analysis is based upon field plot observations for the pathogen Phytophthora capsici that causes disease in pepper plants. Results are compared with pseudolikelihood and Markov chain Monte Carlo estimation techniques, both for the empirical example and for two simulation experiments associated with it. The principal finding is that synthetic map pattern variables, which are eigenvectors computed for a geographic weights matrix, furnish an alternative, successful way of capturing spatial dependency effects in the mean response term of a logistic regression model, avoiding altogether the need to use other than traditional standard techniques to estimate model parameters.
Multilingual exemplar-based acoustic model for the NIST Open KWS 2015 evaluation

In this paper, we investigate the use of the proposed non-parametric exemplar-based acoustic modeling for the NIST Open Keyword Search 2015 Evaluation. Specifically, kernel-density model is used to replace GMM in HMM/GMM (Hidden Markov Model / Gaussian Mixture Model) or DNN in HMM/DNN (Hidden Markov Model / Deep Neural Network) acoustic model to predict the emission probability of HMM states. To get further improvement, likelihood score generated by the kernel-density model is discriminatively tuned by the score tuning module realized by a neural network. Various configurations for score tuning module have been examined to show that simple neural network with 1 hidden layer is sufficient to fine tune the likelihood score generated by the kernel-density model. With this architecture, our exemplar-based model outperforms the 9-layer-DNN acoustic model significantly for both the speech recognition and keyword search tasks. In addition, our proposed exemplar-based system provides complementary information to other systems and we can further benefit from system combination.
Not Yet Game Over: A Reappraisal of Video Game Addiction

The rapid expansion of video gaming in an internet-using society has brought on a renewed focus on the phenomenon of video game addiction. Despite this focus, there remains a crucial absence of consensus over the diagnostic criteria of video game addiction. Currently both psychological and behavioral interventions regard screen time as an indicator of video game addiction. However, these interventions are challenged by substantial literature that increasingly regard time to not be a predictor of addiction. To build onto the work that has been done, this paper argues that time is an inadequate criterion in which to ascertain video game addiction, proposing that a physiological-based criteria be used in conjunction with contextualized understandings of video game dynamics to approach video game addiction. This realignment is all the more pressing as video games begin a transition from a leisure activity to its current orientation as a viable career option.
SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks

In this paper, we propose SpreadViz, a web tool for exploration and visualization of spreading processes in social networks. SpreadViz consists of three main modules, namely graph exploration and analytics, detection of influential nodes, and interactive visualization. More precisely, SpreadViz offers the following functionalities: (i) It computes and visualizes various centrality criteria towards understanding how the position of a node in the network affects its spreading properties, (ii) It offers a wide range of criteria for the detection of single and multiple influential nodes and comparison among them, (iii) It effectively visualizes the spread of influence in the network as well as the performance of each method. In our demonstration, we invite the audience to interact with SpreadViz, exploring, analyzing, and visualizing the spreading processes over various real-world social networks. The tool is available online.
Modelling Winners and Losers in Contingent Valuation of Public Goods: Appropriate Welfare Measures and Econometric Analysis

Contingent valuation is now the most widely used method for valuing non-marketed goods in cost-benefit analysis. Yet, despite the fact that many externalities manifest themselves as costs to some and benefits to others, most studies restrict willingness to pay to being non-negative. This can result in significant errors in policymaking. This paper examines the importance of this, explores appropriate welfare measures for assessing losses and gains, demonstrates how these can be elicited explicitly, highlights the sensitivity of the results of such studies to the econometric specification employed and suggests ways of dealing with it. Finally, the implications for policy are examined.
Summary of the Group-Variation Equations

A brief summary is given of the Group-Variation Equations and the island diagram confinement mechanism, with an explanation of the prediction that the cylinder-topology minimal-area spanning surface term in the correlation function of two Wilson loops at large N c , when it exists, must have a pre-exponential factor, which for large area A of the minimal-area cylinder-topology spanning surface, decreases with increasing A at least as fast as 1/ ln(σA), where σ is the area law parameter. This prediction is expected to be testable in lattice calculations. A Group-Variation Equation [1] expresses the derivative with respect to the coupling constant g, of a coefficient in the 1/N expansion [2] of a VEV or correlation function of Wilson loops, in terms of a sum of modified Feynman diagrams, related to the ordinary Feynman diagrams contributing to that VEV or correlation function. The modifications to the Feynman diagrams are: (1) Each window in an ordinary planar diagram is weighted by the VEV of the Wilson loop that forms its perimeter. The gluon and FP propagators are first resolved into sums over paths, so that the window weights become weights in the sums over paths. (2) A planar diagram can have " islands " , which look like planar vacuum bubbles, drawn within its windows. The non-simply connected window that surrounds one or more islands, is weighted by the correlation function of the two or more Wilson loops that form its perimeter. Again, the gluon and FP propagators are first resolved into sums over paths, so that the window weights become weights in the sums over paths. (3) Each planar diagram is multiplied by a numerical coefficient, which is the derivative , at M = 1, of the " chromatic polynomial " , C(M), of the diagram. The
Organization and Plasticity of Sodium Channel Expression in the Mouse Olfactory and Vomeronasal Epithelia

To understand the molecular basis of neuronal excitation in the mammalian olfactory system, we conducted a systematic analysis of the organization of voltage-gated sodium (Nav) channel subunits in the main olfactory epithelium (MOE) and vomeronasal organ (VNO) of adult mice. We also analyzed changes in Nav channel expression during development in these two systems and during regeneration of the MOE. Quantitative PCR shows that Nav1.7 is the predominant isoform in both adult MOE and VNO. We detected pronounced immunoreactivity for Nav1.7 and Nav1.3 in axons of olfactory and vomeronasal sensory neurons (VSNs). Analysis of Nav1.2 and Nav1.6 revealed an unexpected subsystem-specific distribution. In the MOE, these Nav channels are absent from olfactory sensory neurons (OSNs) but present in non-neuronal olfactory cell types. In the VNO, Nav1.2 and Nav1.6 are confined to VSNs, with Nav1.2-immunoreactive somata solely present in the basal layer of the VNO. The subcellular localization of Nav1.3 and Nav1.7 in OSNs can change dramatically during periods of heightened plasticity in the MOE. During the first weeks of development and during regeneration of the olfactory epithelium following chemical lesion, expression of Nav1.3 and Nav1.7 is transiently enhanced in the somata of mature OSNs. Our results demonstrate a highly complex organization of Nav channel expression in the mouse olfactory system, with specific commonalities but also differences between the MOE and the VNO. On the basis of their subcellular localization, Nav1.3 and Nav1.7 should play major roles in action potential propagation in both MOE and VNO, whereas Nav1.2 and Nav1.6 are specific to the function of VSNs. The plasticity of Nav channel expression in OSNs during early development and recovery from injury could reflect important physiological requirements in a variety of activity-dependent mechanisms.
Insecure primitive elements in an ElGamal signature protocol

Abstract Consider the classical ElGamal digital signature scheme based on the modular relation αm ≡ yrrs[p]. In this work, we prove that if we can compute a natural integer i such that αi mod p is smooth and divides p − 1, then it is possible to sign any given document without knowing the secret key. Therefore we extend and reinforce Bleichenbacher's attack presented at Eurocrypt'96.
The Twisting X-ray Isophotes of the Elliptical Galaxy NGC 720

We present spatial analysis of the deep (57ks) ROSAT HRI X-ray image of the E4 galaxy NGC 720. The orientation of the HRI surface brightness is consistent with the optical position angle $(PA)$ interior to semi-major axis $a\sim 60\arcsec$ (optical $R_e\sim 50\arcsec$). For larger $a$ the isophotes twist and eventually $(a\gtrsim 100\arcsec)$ orient along a direction consistent with the $PA$ measured with the PSPC data (Buote & Canizares 1994) -- the $\sim 30\arcdeg$ twist is significant at an estimated 99% confidence level. We argue that this twist is not the result of projected foreground and background sources, ram pressure effects, or tidal distortions. If spheroidal symmetry and a nearly isothermal hot gas are assumed, then the azimuthally averaged radial profile displays features which, when combined with the observed $PA$ twist, are inconsistent with the simple assumptions that the X-ray emission is due either entirely to hot gas or to the combined emission from hot gas and discrete sources. We discuss possible origins of the $PA$ twist and radial profile features (e.g., triaxiality).
Rethinking the ESP game

The ESP Game was designed to harvest human intelligence to assign labels to images - a task which is still difficult for even the most advanced systems in image processing. However, the ESP Game as it is currently implemented encourages players to assign "obvious" labels, which can be easily predicted given previously assigned labels. We present a language model which can assign probabilities to the next label to be added. This model is then used in a program, which plays the ESP game without looking at the image. Even without any use of the actual image, the program manages to agree with the randomly assigned human partner on a label for 69% of all images, and for 81% of images which have at least one "off-limits" term assigned to them. We discuss how the scoring system and the design of the ESP game can be improved to encourage users to add less predictable labels, thereby improving the quality of the collected information.
The Examination of Organizational Respect in Relation to Organizational Culture

This paper is an in-depth examination of the connection between organizational respect and the strong roots of organizational culture. Throughout this thesis, we will examine the importance of management recognizing and implementing respect, how respect affects other behaviors and characteristics of employees, and ways in which employees tend to feel the most respected. Additionally, we will closely examine the importance of establishing feelings of support, caring, and collaboration within an organization in efforts to create an environment filled with respect. Another concept that will be examined is the idea of person-culture fit, and how the alignment of values between employees and the overall organization can ultimately make or break its success. These concepts are important, because they collaboratively determine whether or not the organization will be able to sustain itself going forward. By the end of this paper, you will have a better understanding of the importance of organizational respect and how it contributes to organizational culture, as well as how organizational respect influences organizational culture and influences employee fit in organizations.
Osmoregulation and salinity tolerance in the Antarctic midge, Belgica antarctica: seawater exposure confers enhanced tolerance to freezing and dehydration

SUMMARY Summer storms along the Antarctic Peninsula can cause microhabitats of the terrestrial midge Belgica antarctica to become periodically inundated with seawater from tidal spray. As microhabitats dry, larvae may be exposed to increasing concentrations of seawater. Alternatively, as a result of melting snow or following rain, larvae may be immersed in freshwater for extended periods. The present study assessed the tolerance and physiological response of B. antarctica larvae to salinity exposure, and examined the effect of seawater acclimation on their subsequent tolerance of freezing, dehydration and heat shock. Midge larvae tolerated extended exposure to hyperosmotic seawater; nearly 50% of larvae survived a 10-day exposure to 1000 mOsm kg–1 seawater and ∼25% of larvae survived 6 days in 2000 mOsm kg–1 seawater. Exposure to seawater drastically reduced larval body water content and increased hemolymph osmolality. By contrast, immersion in freshwater did not affect water content or hemolymph osmolality. Hyperosmotic seawater exposure, and the accompanying osmotic dehydration, resulted in a significant correlation between the rate of oxygen consumption and larval water content and induced the de novo synthesis and accumulation of several organic osmolytes. A 3-day exposure of larvae to hyperosmotic seawater increased freezing tolerance relative to freshwater-acclimated larvae. Even after rehydration, the freezing survival of larvae acclimated to seawater was greater than freshwater-acclimated larvae. Additionally, seawater exposure increased the subsequent tolerance of larvae to dehydration. Our results further illustrate the similarities between these related, yet distinct, forms of osmotic stress and add to the suite of physiological responses used by larvae to enhance survival in the harsh and unpredictable Antarctic environment.
Controlled Sparsity Kernel Learning

Multiple Kernel Learning(MKL) on Support Vector Machines(SVMs) has been a popular front of research in recent times due to its success in application problems like Object Categorization. This success is due to the fact that MKL has the ability to choose from a variety of feature kernels to identify the optimal kernel combination. But the initial formulation of MKL was only able to select the best of the features and misses out many other informative kernels presented. To overcome this, the Lp norm based formulation was proposed by Kloft et. al. This formulation is capable of choosing a non-sparse set of kernels through a control parameter p. Unfortunately, the parameter p does not have a direct meaning to the number of kernels selected. We have observed that stricter control over the number of kernels selected gives us an edge over these techniques in terms of accuracy of classification and also helps us to fine tune the algorithms to the time requirements at hand. In this work, we propose a Controlled Sparsity Kernel Learning (CSKL) formulation that can strictly control the number of kernels which we wish to select. The CSKL formulation introduces a parameter t which directly corresponds to the number of kernels selected. It is important to note that a search in t space is finite and fast as compared to p. We have also provided an efficient Reduced Gradient Descent based algorithm to solve the CSKL formulation, which is proven to converge. Through our experiments on the Caltech101 Object Categorization dataset, we have also shown that one can achieve better accuracies than the previous formulations through the right choice of t.
NV-TS: A Fault Tolerance Transaction System Based on Persistent Memory

The scalability of future high performance computing (HPC) systems are challenged by high failure rates. So fault tolerance technique will play a more important role in future HPC field. Currently, the checkpoint-restart technique is the main fault tolerance technique. However, the checkpoint-restart approach results in a very high overhead, which influences the efficiency of HPC systems seriously. In this paper, we leverage the emerging NVRAM technology and propose to combine transaction and NVRAM technique to design a new fault tolerance technique. We present NV-TS, a fault tolerance transaction system based on NVRAM. NV-TS guarantee that the update of application state is atomic and durable. If the system crashes suddenly during the application execution, the atomicity of transaction will ensure the consistency of application state. After the system restarts, the application could continue to run. Our experiment shows that NV-TS could improve the performance of fault tolerance with a small memory overhead.
Understanding ERS Coherence over Urban Areas

C-band SAR interferometry has been widely used for several Earth related studies (topography, volcanology, forestry etc.). Nevertheless, not much attention has been paid to urban areas and coherence has been used for classification purposes only. In this study we focused on the meaning of coherence of an urban area and performed several analysis in order to understand what causes decorrelation. Two test sites have been considered: Gothenburg in Sweden and Naples in Italy. For both cities we had a reasonable number of coherence images with one-day and long-period acquisition interval. SAR amplitude images have also been considered. Using RGB colour composite combinations of SAR and InSAR imagery, we could relate the level of coherence of a part of a city either to topography, InSAR system geometry and position of the targets or to image processing or to structural typologies.
Prognostic Significance of Single Progesterone Receptor Positivity

AbstractSingle progesterone receptor positive (PgR+), especially in form of ER−/PgR+/HER2−, is a nonnegligible phenomenon. Little is known about the characteristics and the role of single PgR positive in this phenotype. Therefore, we explore the significance of single PgR positivity by comparing ER−/PgR+/HER2− breast cancers with triple negative breast cancers (TNBCs). Three thousand nine hundred sixty-six cases of primary invasive breast carcinoma operated consecutively from January 2005 to May 2008 in Cancer Hospital, Chinese Academy of Medical Sciences were examined. Two hundred forty (6%) cases were identified as ER−/PgR+/HER2− breast cancers and 348 (8.8%) cases as TNBCs. Clinicopathological characteristics and survivals were analyzed respectively and then compared between 2 subtypes.Compared with patients with TNBCs, ER−/PgR+/HER2− tumor tended to have lower tumor grade (Grade 3: 45.7% vs. 37.5%, P = 0.051) and smaller tumor size (P = 0.036). However, no differences were found between ER−/PgR+/HER2− and TNBC patients in relapse-free survival (RFS) and OS. The 5-year RFS rates were 80.7% and 77.4%, respectively (P = 0.330) and the 5-year OS rates were 88.0% and 85.2%, respectively (P = 0.290). ER−/PgR+/HER2− patients receiving adjuvant endocrine treatment had better RFS (P = 0.016) and overall survival (OS) (P < 0.0001) than patients receiving no endocrine therapy.This exclusive analysis of patients with ER−/PgR+/HER2− breast cancers showed that this subtype exhibited an aggressive behavior as TNBC, suggesting that it should also be regarded as biologically distinctive group and single PgR positive itself is not a good prognostic factor. However, adjuvant endocrine therapy could still benefit this group of patients. Further investigations should be done to elucidate the underlying mechanism.
Effects of NeuroBike Cycling on EEG Brain Activity and Mathematical Performance: An Intervention Study

The general purpose of the study was to promote the research on effects of physical activity on mathematical performance and brain functions, which is of particular interest regarding children’s education as well as for all adults. Several studies have identified an influence of cycling on cognitive processes and brain activity. In the present study, we investigated effects of cycling training on a special bicycle on spontaneous EEG brain activity and on mathematical performance of young adults. Participants performed different interventions (special bicycle - NeuroBike, common bicycle, daily activity) in a two-week intervention with three 20-minute training sessions per week. Spontaneous EEG was recorded before and after each training condition at rest as well as during different mathematical tests (algebra, arithmetic, geometry) before and after the two-week intervention. Behavioral data show reduced mathematical performance in geometry after the NeuroBike and common bicycle intervention in comparison to daily activity. EEG data reveal increased temporal and occipital theta power, occipital alpha power, and parietal and occipital beta power after the two week intervention without acute influence of NeuroBike cycling at rest. Repeated NeuroBike training lead to increased frontal power in all frequency bands as well as temporal theta and alpha power during algebra performance. The results indicate that continuous training on a NeuroBike fosters a beneficial brain state for learning at resting state, but does not lead instantaneously to an optimum brain state for active spatial processing in mathematical problem solving.