Miracle-dz/UniFAR-FTUs huggingface dataset:
Firing Behavior and Network Activity of Single Neurons in Human Epileptic Hypothalamic Hamartoma

Objective: Human hypothalamic hamartomas (HH) are intrinsically epileptogenic and are associated with treatment-resistant gelastic seizures. The basic cellular mechanisms responsible for seizure onset within HH are unknown. We used intra-operative microwire recordings of single neuron activity to measure the spontaneous firing rate of neurons and the degree of functional connection between neurons within the tumor. Technique: Fourteen patients underwent transventricular endoscopic resection of HH for treatment-resistant epilepsy. Prior to surgical resection, single neuron recordings from bundled microwires (total of nine contacts) were obtained from HH tissue. Spontaneous activity was recorded for two or three 5-min epochs under steady-state general anesthesia. Off-line analysis included cluster analysis of single unit activity and probability analysis of firing relationships between pairs of neurons. Results: Altogether, 222 neurons were identified (mean 6 neurons per recording epoch). Cluster analysis of single neuron firing utilizing a mixture of Gaussians model identified two distinct populations on the basis of firing rate (median firing frequency 0.6 versus 15.0 spikes per second; p < 10−5). Cluster analysis identified three populations determined by levels of burst firing (median burst indices of 0.015, 0.18, and 0.39; p < 10−15). Unbiased analysis of spontaneous single unit behavior showed that 51% of all possible neuron pairs within each recording epoch had a significant level of firing synchrony (p < 10−15). The subgroup of neurons with higher median firing frequencies was more likely to demonstrate synchronous firing (p < 10−7). Conclusion: Hypothalamic hamartoma tissue in vivo contains neurons which fire spontaneously. The activity of single neurons is diverse but distributes into at least two electrophysiological phenoytpes. Functional linkage between single neurons suggests that HH neurons exist within local networks that may contribute to ictogenesis.
Models for the k-metric dimension

For an undirected graph G=(V,E), a vertex x \in V separates vertices u and v (where u,v \in V, u \neq v) if their distances to x are not equal. Given an integer parameter k \geq 1, a set of vertices L \subseteq V is a feasible solution if for every pair of distinct vertices, u,v, there are at least k distinct vertices x_1,x_2,. ,x_k \in L each separating u and v. Such a feasible solution is called a "landmark set", and the k-metric dimension of a graph is the minimal cardinality of a landmark set for the parameter k. The case k=1 is a classic problem, where in its weighted version, each vertex v has a non-negative weight, and the goal is to find a landmark set with minimal total weight. We generalize the problem for k \geq 2, introducing two models, and we seek for solutions to both the weighted version and the unweighted version of this more general problem. In the model of all-pairs (AP), k separations are needed for every pair of distinct vertices of V, while in the non-landmarks model (NL), such separations are required only for pairs of distinct vertices in V \setminus L. We study the weighted and unweighted versions for both models (AP and NL), for path graphs, complete graphs, complete bipartite graphs, and complete wheel graphs, for all values of k \geq 2. We present algorithms for these cases, thus demonstrating the difference between the two new models, and the differences between the cases k=1 and k \geq 2.
Case based reasoning as an extension of fault dictionary methods for linear electronic analog circuits diagnosis

El test de circuits es una fase del proces de produccio que cada vegada pren mes importancia quan es desenvolupa un nou producte. Les tecniques de test i diagnosi per a circuits digitals han estat desenvolupades i automatitzades amb exit, mentre que aquest no es encara el cas dels circuits analogics. D'entre tots els metodes proposats per diagnosticar circuits analogics els mes utilitzats son els diccionaris de falles. En aquesta tesi se'n descriuen alguns, tot analitzant-ne els seus avantatges i inconvenients. Durant aquests ultims anys, les tecniques d'Intelligencia Artificial han esdevingut un dels camps de recerca mes importants per a la diagnosi de falles. Aquesta tesi desenvolupa dues d'aquestes tecniques per tal de cobrir algunes de les mancances que presenten els diccionaris de falles. La primera proposta es basa en construir un sistema fuzzy com a eina per identificar. Els resultats obtinguts son forca bons, ja que s'aconsegueix localitzar la falla en un elevat tant percent dels casos. Per altra banda, el percentatge d'encerts no es prou bo quan a mes a mes s'intenta esbrinar la desviacio. Com que els diccionaris de falles es poden veure com una aproximacio simplificada al Raonament Basat en Casos (CBR), la segona proposta fa una extensio dels diccionaris de falles cap a un sistema CBR. El proposit no es donar una solucio general del problema sino contribuir amb una nova metodologia. Aquesta consisteix en millorar la diagnosis dels diccionaris de falles mitjancant l'addicio i l'adaptacio dels nous casos per tal d'esdevenir un sistema de Raonament Basat en Casos. Es descriu l'estructura de la base de casos aixi com les tasques d'extraccio, de reutilitzacio, de revisio i de retencio, fent emfasi al proces d'aprenentatge. En el transcurs del text s'utilitzen diversos circuits per mostrar exemples dels metodes de test descrits, pero en particular el filtre biquadratic es l'utilitzat per provar les metodologies plantejades, ja que es un dels benchmarks proposats en el context dels circuits analogics. Les falles considerades son parametriques, permanents, independents i simples, encara que la metodologia pot ser facilment extrapolable per a la diagnosi de falles multiples i catastrofiques. El metode es centra en el test dels components passius, encara que tambe es podria extendre per a falles en els actius.
A Linear Algebraic Solution of the Direct Kinematics of Parallel Manipulators Using a Camera

The e ect of the addition of a camera to the six leg lengths, in the solution of the direct kinematics of parallel manipulators, is studied here, for purposes of on-line implementation. The leg end-point positions are computed by intersecting the unmeasured motions of the joint and vision sensors. The direct kinematics is then written as a linear algebraic system constrained by the proper orthogonality of the rotation matrix, for which the solution is obtained using a decoupling technique together with the polar-decomposition theorem. The resulting algorithm is fast, robust to measurement noise, and provides, a unique solution.
First-Order and Monadic Second-Order Model-Checking on Ordered Structures

Model-checking for first- and monadic second-order logic in the context of graphs has received considerable attention in the literature. It is well-known that the problem of verifying whether a formula of these logics is true in a graph is computationally intractable but it does become tractable on interesting classes of graphs such as classes of bounded tree-width. In this paper we continue this line of research but study model checking for first- and monadic second-order logic in the presence of an ordering on the input structure. We do so in two settings: the general ordered case, where the input structures are equipped with a fixed order or successor relation, and the order invariant case, where the formulas may resort to an ordering but their truth must be independent of the particular choice of order. In the first setting we show very strong intractability results for most interesting classes of graphs. In contrast, in order invariant case we obtain tractability results for order invariant monadic second-order logic on the same classes of graphs as in the unordered case. For first-order logic, we obtain tractability of successor-invariant FO on planar graphs.
Peripheral vision annotation: noninterference information presentation method for mobile augmented reality

Augmented-reality (AR) systems present information about a user's surrounding environment by overlaying it on the user's real-world view. However, such overlaid information tends to obscure a user's field of view and thus impedes a user's real-world activities. This problem is especially critical when a user is wearing a head-mounted display. In this paper, we propose an information presentation mechanism for mobile AR systems by focusing on the user's gaze information and peripheral vision field. The gaze information is used to control the positions and the level-of-detail of the information overlaid on the user's field of view. We also propose a method for switching displayed information based on the difference in human visual perception between the peripheral and central visual fields. We develop a mobile AR system to test our proposed method consisting of a gaze-tracking system and a retinal imaging display. The eye-tracking system estimates whether the user's visual focus is on the information display area or not, and changes the information type from simple to detailed information accordingly.
Bayesian Chinese Spam Filter Based on Crossed N-gram

Naive Bayesian spam email filters are a wellknown and powerful type of filters that can easily be induced from a dataset of sample cases. However, the problem of segmenting words for Chinese email restricts its performance. In this paper, we present a Bayesian Chinese spam filter based on cross N-gram. This method does not need to carry on segmenting words for Chinese emails, so that it can avoid to be restricted by inaccurate words segmenting. It also needn't to install segmenting word dictionary and is easy to install in the user terminal to construct an individualized spam filter since the space and time efficiency are improved. The restriction on independence assumption of naive bayes method is relaxed in some degree. The results of experiments show that the proposed method can acquire a high accuracy ratio at low cost.
Detecting Temporal Change in Dynamic Sounds: On the Role of Stimulus Duration, Speed, and Emotion

For dynamic sounds, such as vocal expressions, duration often varies alongside speed. Compared to longer sounds, shorter sounds unfold more quickly. Here, we asked whether listeners implicitly use this confound when representing temporal regularities in their environment. In addition, we explored the role of emotions in this process. Using a mismatch negativity (MMN) paradigm, we asked participants to watch a silent movie while passively listening to a stream of task-irrelevant sounds. In Experiment 1, one surprised and one neutral vocalization were compressed and stretched to create stimuli of 378 and 600 ms duration. Stimuli were presented in four blocks, two of which used surprised and two of which used neutral expressions. In one surprised and one neutral block, short and long stimuli served as standards and deviants, respectively. In the other two blocks, the assignment of standards and deviants was reversed. We observed a climbing MMN-like negativity shortly after deviant onset, which suggests that listeners implicitly track sound speed and detect speed changes. Additionally, this MMN-like effect emerged earlier and was larger for long than short deviants, suggesting greater sensitivity to duration increments or slowing down than to decrements or speeding up. Last, deviance detection was facilitated in surprised relative to neutral blocks, indicating that emotion enhances temporal processing. Experiment 2 was comparable to Experiment 1 with the exception that sounds were spectrally rotated to remove vocal emotional content. This abolished the emotional processing benefit, but preserved the other effects. Together, these results provide insights into listener sensitivity to sound speed and raise the possibility that speed biases duration judgements implicitly in a feed-forward manner. Moreover, this bias may be amplified for duration increments relative to decrements and within an emotional relative to a neutral stimulus context.
Detection And Location Capabilities Of Multiple Infrasound Arrays

We have developed an integrated approach to locating an infrasound source that fuses local-array wave-number parameters and uncertainties into an overall location procedure. For local estimation of the velocity and azimuth, a small-array theory, based on maximum likelihood, has been given in earlier work that characterizes the large-sample uncertainty of the estimates and evaluates the theoretical missed-signal and false alarm probabilities. We have verified the theoretical uncertainties by computing empirical estimates using the frequency domain bootstrap on a gas-pipe explosion, a Titan IV B missile launch, and a Hawaii meteorite. Detection probabilities and wave-number uncertainties are then integrated into a Bayesian nonlinear regression procedure for evaluating the location capabilities of the particular global infrasound array that is proposed for the International Monitoring System (IMS). We show contour maps for the average expected areas of the 90% confidence ellipses produced by the overall fusion procedure. The results indicate that for a single-array false alarm probability of 10, the standard proposed IMS 4element array will detect over 90% of the signals at signal-to-noise ratios as low as . 6, with sufficient bandwidth. Location accuracies will require higher signal-to-noise ratios on the order of 2-4 and high single-array detection probabilities (>.90) to guarantee reasonable coverage (1000 km) for the 90% posterior probability ellipses. Eastern Hemisphere and Western Hemisphere 90% contour plots show almost complete coverage by expected uncertainty areas of 1000 km or less. 24th Seismic Research Review – Nuclear Explosion Monitoring: Innovation and Integration
Evolving context-free language predictors

Recurrent neural networks can represent and process simple context-free languages. However, the difficulty of finding with gradient-based learning appropriate weights for context-free language prediction motivates an investigation on the applicability of evolutionary algorithms. By empirical studies, an evolutionary algorithm proves to be more reliable in finding prediction solutions to a simple CFL. Moreover, the evolutionary algorithm demonstrates greater diversity by making use of a larger repertoire of dynamical behaviors for solving the problem.
Renal Dysfunction and Thrombolytic Therapy in Patients With Acute Ischemic Stroke

AbstractRenal dysfunction is a prevalent comorbidity in acute ischemic stroke patients requiring thrombolytic therapy. However, the effect of renal dysfunction on the clinical outcome of this population remains controversial.This study aimed to evaluate the safety and effectiveness of thrombolytic therapy in acute stroke patients with renal dysfunction using a meta-analysis.We systematically searched PubMed and EMBASE for studies that evaluated the relationship between renal dysfunction and intravenous tissue plasminogen activator (tPA) in patients with acute ischemic stroke. Poor outcome (modified Rankin Scale ≥2), mortality, and symptomatic intracranial hemorrhage (ICH) and any ICH were analyzed.Fourteen studies were included (N = 53,553 patients). The mean age ranged from 66 to 75 years. The proportion of male participants was 49% to 74%. The proportion of renal dysfunction varied from 21.9% to 83% according to different definitions. Based on 9 studies with a total of 7796 patients, the meta-analysis did not identify a significant difference in the odds of poor outcome (odds ratio [OR] = 1.06; 95% confidence interval [CI]: 0.96–1.16; I2 = 44.5) between patients with renal dysfunction and those without renal dysfunction. Patients with renal dysfunction were more likely to die after intravenous thrombolysis (OR = 1.13; 95% CI: 1.05–1.21; I2 = 70.3). No association was observed between symptomatic ICH (OR = 1.02; 95% CI: 0.94–1.10; I2 = 0) and any ICH (OR = 1.07; 95% CI: 0.96–1.18; I2 = 25.8). Renal dysfunction does not increase the risk of poor outcome and ICH after stroke thrombolysis. Renal dysfunction should not be a contraindication for administration of intravenous thrombolysis to eligible patients.
Stacking Cost Sensitive Models

A classifier induced from an imbalanced data set has, typically, a low error rate for the majority class and an unacceptable error rate for the minority class. This paper firstly provides a systematic study on the various methodologies that have tried to handle this problem. Finally, it presents an experimental study of these methodologies with a proposed stacking cost-sensitive ensemble and it concludes that such a framework can be a more effective solution to the problem.
Superpixels-based non-local means image denoising

Although the non-local means method achieves high performance in image denoising, its computation is very expensive. In this paper, we propose to reduce the complexity based on superpixel clustering. The idea is to first divide whole image into some superpixels based on pixels' similar geometry structure. Then the selection of similar patches is conducted in every superpixel. Experiments show that the proposed method has good denoising performance while the computation complexity is decreased in comparison with other algorithms.
CoSMiC: designing a mobile crowd-sourced collaborative application to find a missing child in situ

Finding a missing child is an important problem concerning not only parents but also our society. It is essential and natural to use serendipitous clues from neighbors for finding a missing child. In this paper, we explore a new architecture of crowd collaboration to expedite this mission-critical process and propose a crowd-sourced cooperative mobile application, CoSMiC. It helps parents find their missing child quickly on the spot before he or she completely disappears. A key idea lies in constructing the location history of a child via crowd participation, thereby leading parents to their child easily and quickly. We implement a prototype application and conduct extensive user studies to assess the design of the application and investigate its potential for practical use.
Capsaicin Protects Mouse Neuromuscular Junctions from the Neuroparalytic Effects of Botulinum Neurotoxin A

Botulinum neurotoxin A (BoNT/A), the most toxic, naturally occurring protein, cleaves synapse-associated protein of 25 kDa and inhibits acetylcholine release from motor nerve endings (MNEs). This leads to paralysis of skeletal muscles. Our study demonstrates that capsaicin protects mouse neuromuscular junctions from the neuroparalytic effects of BoNT/A. Bilateral injection of BoNT/A near the innervation of the Extensor digitorum longus (EDL) muscle of adult Swiss-Webster mice inhibited the toe spread reflex (TSR). However, when capsaicin was coinjected bilaterally, or injected 4 or 8 h before injecting BoNT/A, the TSR remained normal. In animals that were pretreated with capsazepine, capsaicin failed to protect against the neuroparalytic effects of BoNT/A. In vivo analyses demonstrated that capsaicin protected muscle functions and electromygraphic activity from the incapacitating effects of BoNT/A. The twitch response to nerve stimulation was greater for EDL preparations isolated from mice injected with capsaicin before BoNT/A. Capsaicin pretreatment also prevented the inhibitory effects of BoNT/A on end-plate currents. Furthermore, pretreatment of Neuro 2a cells with capsaicin significantly preserved labeling of synaptic vesicles by FM 1-43. This protective effect of capsaicin was observed only in the presence of extracellular Ca2+ and was inhibited by capsazepine. Immunohistochemistry demonstrated that MNEs express transient receptor potential protein of the vanilloid subfamily, TRPV1, the capsaicin receptor. Capsaicin pretreatment, in vitro, reduced nerve stimulation or KCl-induced uptake of BoNT/A into motor nerve endings and cholinergic Neuro 2a cells. These data demonstrate that capsaicin interacts with TRPV1 receptors on MNEs to reduce BoNT/A uptake via a Ca2+-dependent mechanism.
A Versatile Graph-Based Approach to Package Recommendation

An emerging trend in research on recommender systems is the design of methods capable of recommending packages instead of single items. The problem is challenging due to a variety of critical aspects, including context-based and user-provided constraints for the items constituting a package, but also the high sparsity and limited accessibility of the primary data used to solve the problem. Most existing works on the topic have focused on a specific application domain (e.g., travel package recommendation), thus often providing ad-hoc solutions that cannot be adapted to other domains. By contrast, in this paper we propose a versatile package recommendation approach that is substantially independent of the peculiarities of a particular application domain. A key aspect in our framework is the exploitation of prior knowledge on the content type models of the packages being generated that express what the users expect from the recommendation task. Packages are learned for each package model, while the recommendation stage is accomplished by performing a PageRank-style method personalized w.r. t. the target user's preferences, possibly including a limited budget. Our developed method has been tested on a TripAdvisor dataset and compared with a recently proposed method for learning composite recommendations.
Picture Watermarks Surviving General Affine Transformation and Random Distortion

We have extended a previously reported method immune to random distortion to make it immune to affine transformation as well. Although affine transformation consists of four geometric transformations (scaling, rotation, translation, and shearing), the proposed method requires only scale and rotation searching. Experimental evaluation showed that it can detect each geometric transformation. It can thus be used to create picture watermarks that are immune to a wide variety of geometric transformations.
Early and Late Postnatal Myocardial and Vascular Changes in a Protein Restriction Rat Model of Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) is a risk factor for cardiovascular disease in later life. Early structural and functional changes in the cardiovascular system after IUGR may contribute to its pathogenesis. We tested the hypothesis that IUGR leads to primary myocardial and vascular alterations before the onset of hypertension. A rat IUGR model of maternal protein restriction during gestation was used. Dams were fed low protein (LP; casein 8.4%) or isocaloric normal protein diet (NP; casein 17.2%). The offspring was reduced to six males per litter. Immunohistochemical and real-time PCR analyses were performed in myocardial and vascular tissue of neonates and animals at day 70 of life. In the aortas of newborn IUGR rats expression of connective tissue growth factor (CTGF) was induced 3.2-fold. At day 70 of life, the expression of collagen I was increased 5.6-fold in aortas of IUGR rats. In the hearts of neonate IUGR rats, cell proliferation was more prominent compared to controls. At day 70 the expression of osteopontin was induced 7.2-fold. A 3- to 7-fold increase in the expression of the profibrotic cytokines TGF-β and CTGF as well as of microfibrillar matrix molecules was observed. The myocardial expression and deposition of collagens was more prominent in IUGR animals compared to controls at day 70. In the low-protein diet model, IUGR leads to changes in the expression patterns of profibrotic genes and discrete structural abnormalities of vessels and hearts in adolescence, but, with the exception of CTGF, not as early as at the time of birth. Invasive and non-invasive blood pressure measurements confirmed that IUGR rats were normotensive at the time point investigated and that the changes observed occurred independently of an increased blood pressure. Hence, altered matrix composition of the vascular wall and the myocardium may predispose IUGR animals to cardiovascular disease later in life.