Miracle-dz/UniFAR-FTUs huggingface dataset:
THE LINK BETWEEN MOOD DISORDERS AND EPILEPSY: WHY IS IT IMPORTANT TO DIAGNOSE AND TREAT? *

Depression commonly is comorbid with epilepsy and, of the depressive disorders, major depression is most common. Depression is often comorbid with an anxiety disorder (eg, generalized anxiety, social phobia, post-traumatic stress disorder, panic disorder, or obsessive-compulsive disorder), in the general public and in persons with epilepsy (PWE). This discussion will focus on mood disorders in PWE and treatment options for those adult PWE with a unipolar mood disorder. The presentation of mood disorders forms a spectrum across patients. Mood disorders remain undiagnosed and undertreated in PWE, in part, because many healthcare providers think these disorders are a normal reaction to a chronic illness. However, recent epidemiologic studies suggest that the relationship may be bidirectional (ie, causal instead of merely comorbid), but the nature of this relationship is unclear. Undertreating depression in PWE not only jeopardizes patients’ psychiatric health but also undermines the patients’ ability to habituate to their medical illness or follow and comply with treatment regimens. Depression in epilepsy also has been shown to decrease the patient’s quality of life and increase the patient’s risk for suicide. Therefore, it is important to continue research into the mechanisms of mood/anxiety disorders and epilepsy and to make their diagnoses a higher priority in the management of PWE. There are limited evidence-based data for treating depression specifically in PWE. However, the psychiatric literature provides a framework for treatment strategies. As with treatment of depression in the general public, total remission is the treatment goal because residual symptoms are strong predictors of relapse. (Adv Stud Med. 2005;5(6C):S572-S578)
Acute and long-term outcome of cryoablation therapy of typical atrioventricular nodal reentrant tachycardia.

AIMS The purpose of this study was to evaluate the safety and efficacy of cryoablation in a large series of patients with typical (slow-fast) atrioventricular nodal reentrant tachycardia (AVNRT). METHODS AND RESULTS Between 2003 and 2007, 312 patients with typical AVNRT--median age of 53 years (range 10-92), 200 women (64%)--underwent cryoablation, using exclusively a 6 mm tip catheter tip. Acute success was achieved in 309 of 312 patients (99%). The overall recurrence rate was 18 of 309 (5.8%) during a mean follow-up of 673 +/- 381 days. Sixteen of these patients (89%) were successfully reablated. The recurrence rate was 9% in patients with residual dual atrioventricular (AV) nodal pathway post-ablation compared with 4% in those with complete elimination of slow pathway conduction (P = 0.05). No patient developed permanent AV block. CONCLUSION Cryoablation of AVNRT can be achieved with a high acute success rate and a reasonable recurrence rate at long-term follow-up. Complete abolition of slow pathway conduction seems to predict better late outcome.
Design of Intrusion Detection System using Fuzzy Class-Association Rule Mining based on Genetic Algorithm

Now security is considered as a major issue in networks, since the network has extended dramatically. Therefore, intrusion detection systems have attracted attention, as it has an ability to detect intrusion accesses effectively. These systems identify attacks and react by generating alerts or by blocking the unwanted data/traffic. The proposed system includes fuzzy logic with a data mining method which is a class-association rule mining method based on genetic algorithm. Due to the use of fuzzy logic, the proposed system can deal with mixed type of attributes and also avoid the sharp boundary problem. Genetic algorithm is used to extract many rules which are required for anomaly detection systems. An association-rulemining method is used to extract a sufficient number of important rules for the user’s purpose rather than to extract all the rules meeting the criteria which are useful for misuse detection. Experimental results with KDD99 Cup database from MIT Lincoln Laboratory show that the proposed method provides competitively high detection rates compared with crisp data mining.
Propositional Interval Neighborhood Temporal Logics

Logics for time intervals provide a natural framework for dealing with time in various areas of computer science and artificial intelligence, such as planning, natu- ral language processing, temporal databases, and formal specification. In this paper we focus our attention on propositional interval temporal logics with temporal modalities for neighboring intervals over linear orders. We study the class of propositional neigh- borhood logics (PNL) over two natural semantics, respectively admitting and exclud- ing point-intervals. First, we introduce interval neighborhood frames and we provide representation theorems for them; then, we develop complete axiomatic systems and semantic tableaux for logics in PNL.
From Bhindranwale to Bin Laden: The Rise of Religious Violence

My involvement in the study of religious terrorism began with the Sikhs. I had lived in the Punjab for several years, and in the early part of my academic career I had focused on the relationship between religion and politics in India in general and the Punjab in particular. During the 1980s, therefore, I watched with mounting horror as a spiral of violence developed between Sikh militants and the government. How could such affable, intelligent people be swept up in an encounter that was so vicious, so unforgiving?
Stiffness Performance of Multibody Robotic Systems

Stiffness can be considered of primary importance in order to guarantee the successful use of any robotic system for a given task. Therefore, this paper proposes procedures for carrying out both numerical and experimental estimations of stiffness performance for multibody robotic systems. The numerical procedure is based on models with lumped parameters for deriving the Cartesian stiffness matrix. The experimental procedure for the evaluation stiffness performance is based on a new measuring system named as Milli-CATRASYS (Milli Cassino tracking system) and on a trilateration technique
Elliptical Monogenic Wavelets for the Analysis and Processing of Color Images

This paper studies and gives new algorithms for image processing based on monogenic wavelets. Existing greyscale monogenic filter banks are reviewed and we reveal a lack of discussion about the synthesis part. The monogenic synthesis is therefore defined from the idea of wavelet modulation, and an innovative filterbank is constructed by using the Radon transform. The color extension is then investigated. First, the elliptical Fourier atom model is proposed to generalize the analytic signal representation for vector-valued signals. Then, a color Riesz-transform is defined so as to construct color elliptical monogenic wavelets. Our Radon-based monogenic filterbank can be easily extended to color according to this definition. The proposed wavelet representation provides efficient analysis of local features in terms of shape and color, thanks to the concepts of amplitude, phase, orientation, and ellipse parameters. The synthesis from local features is deeply studied. We conclude the paper by defining the color local frequency, proposing an estimation algorithm.
Toward Suboptimal Feature Selection

Feature selection can be defined as the problem of finding the optimal subset of features that meet some criterion, but in general it is an ill-posed problem. In practice, the only way to compare feature selection algorithms has been through generalization error. For this reason it is extremely rare to see optimality discussed in the context of feature selection. The first ones to make optimality claims in the literature were Koller and Sahami [2]. They propose a Markov blanket criterion for eliminating features, an approach that is not unlike learning a graph structure by finding conditional independencies in the data. A Markov blanket is defined as set of features M such that M ⊂ X and Xi / ∈ M is a Markov blanket for feature Xi if (Xi ⊥ X −M − {Xi}| M) [5]. This is equivalent to saying that the Markov blanket M subsumes all of the information contained in feature Xi not just with respect to the labels Y but with respect to all other features. In this way the Markov blanket can detect both irrelevant and redundant features. Koller and Sahami contend that the Markov blanket criterion is the optimal solution to the feature selection problem because it only removes features that are unnecessary, and conversely it removes all unnecessary features. The first part of the optimality claim is extremely persuasive. There should be no reason to keep a feature if there is another set of features that subsume all of the information it contains. The converse, however, is less convincing. To illustrate where this type of feature selection criterion should succeed, consider the artificial problem where you have n binary features and the label is the XOR of the first two features, which are independent of each other. The remaining features are either correlated with the label or are noise. A Markov Blanket algorithm should be able to remove not just the noise features but the correlated features as well. Because the first two features are all we need to determine the label precisely, additional features can only decrease the performance of the classifier. In this case the result is optimal in just about every sense. Unfortunately, in the real world this notion of optimality is not enough. The data is limited and noisy, features are often too plentiful, and rarely is there a deterministic relationship between a feature subset and the labels. In the absence of a clear-cut situation, the trade-off between model complexity and good classification is one that I believe can only be resolved by looking at the generalization error. The idea that there is some objective way to eliminate features independently of both generalization and an induction algorithm is appealing, but it contradicts all of the intuition I have developed while working with feature selection. In this paper I attempt to compare feature selection via Markov blankets to Boosting. I then
LANDSCAPE CONNECTIVITY: A GRAPH‐THEORETIC PERSPECTIVE

Ecologists are familiar with two data structures commonly used to represent landscapes. Vector-based maps delineate land cover types as polygons, while raster lattices represent the landscape as a grid. Here we adopt a third lattice data structure, the graph. A graph represents a landscape as a set of nodes (e.g., habitat patches) connected to some degree by edges that join pairs of nodes functionally (e.g., via dispersal). Graph theory is well developed in other fields, including geography (transportation networks, routing ap- plications, siting problems) and computer science (circuitry and network optimization). We present an overview of basic elements of graph theory as it might be applied to issues of connectivity in heterogeneous landscapes, focusing especially on applications of metapo- pulation theory in conservation biology. We develop a general set of analyses using a hypothetical landscape mosaic of habitat patches in a nonhabitat matrix. Our results suggest that a simple graph construct, the minimum spanning tree, can serve as a powerful guide to decisions about the relative importance of individual patches to overall landscape con- nectivity. We then apply this approach to an actual conservation scenario involving the
A taxonomy of model assumptions on which P is based and implications for added benefit in the sciences

ABSTRACT Although the null hypothesis significance testing procedure is problematic, many still favor the use of p-values as indicating the state of evidence against the model used to generate the p-value. From this perspective, p-values benefit science; or would benefit science if used correctly. In contrast, the novel argument to be presented introduces a taxonomy of assumptions included in the model; such as theoretical assumptions, auxiliary assumptions, statistical assumptions, and inferential assumptions. Careful attention is paid to the different categories of assumptions that models necessarily include to render p-value calculations sensible. Such careful attention suggests unappreciated limitations of p-values. Considering these limitations in the context of the descriptive statistics researchers routinely have available to them clarifies that p-values provide no added benefit to the scientist, above and beyond such descriptive statistics. The lack of added value, combined with the obvious harms documented in recent reviews, suggests that researchers in the sciences should rarely, or never, use p-values. Not even for indicating the state of evidence against models.
Dietary modification and genetic variability of atherosclerosis risk factors

The risk factors for atherosclerosis and coronary heart disease (CHD) are multiple and may interact with each other. Diet has a significant role among the main risk factors for atherosclerosis, as it regulates the levels of plasma lipids and lipoproteins, their oxidative modification or protection from oxidation, blood pressure, energy balance, and thrombogenesis. Nutrients can transfer their effects directly through plasma concentrations or modify the cell transduction or gene expression of important regulatory genes. The response to dietary modification varies between individuals. The plasma cholesterol response induced by dietary modification is at least partly regulated genetically and some of the variation is explained by other environmental factors. Apolipoprotein E (apo E) and apolipoprotein B (apo B) are the key regulatory proteins in cholesterol and lipoprotein metabolism. The genetic variation of apo E is associated with the plasma lipid levels and the CHD risk. The polymorphic variation of the apo B gene is also associated with increased plasma cholesterol and CHD risk. Obesity is associated with increased morbidity and mortality. Plasma lipid abnormalities, impaired glucose metabolism and increased blood pressure caused by obesity are the main reasons for increased CHD mortality among obese subjects. To study the magnitude of the response to dietary modification, genetically selected groups were investigated. Dietary modification had a significant impact on plasma total, LDL, and HDL cholesterol concentrations, and the individual response in plasma LDL cholesterol varied from 3 to 100%. The role of genetic variation in the apo E gene was not significant in the lipid response, but the blood pressure response was more distinct among subjects with the e4 allele than those with the e3 allele. The determination of apo B EcoRI and MspI gene polymorphisms revealed subjects with a greater response to diet, a finding which may have clinical importance in the future for the attempt to identify subjects for effective dietary counselling. The effect of caloric restriction on gene expression was studied in obese gallstone patients. Moderate weight reduction during caloric restriction was associated with reduced lipoprotein lipase gene expression, while the cholesteryl ester transfer protein gene expression remained unchanged. Some of the beneficial changes in plasma lipids and lipoproteins during and after weight reduction may be followed by altered transcription of their modifying genes. Meta-analysis is a modern and generally accepted method. Many clinical uncertainties can be solved by combining all the data available to a quantitative and objective analysis. However, the use of meta-analysis do not resolve the problem of the effect of publication bias.
A Fiber-Optics-Based Body Contact Sensor for a Flexible Manipulator

This paper presents a fiber-optic-based contact sensor for the body contact sensing of a flexible manipulator. The developed sensor is capable of providing both the magnitude of applied force and the contact location. A mathematical model of this sensor is developed. A sensor prototype is created and tested to illustrate the sensing principle of the proposed sensor. Sensor design and the fabrication procedure are presented. The developed sensor has a simple structure and is capable of working in high-electromagnetic interference environments. The sensor's performance has been experimentally evaluated. Test results show that the proposed sensor has an accuracy of 83.50% for the force magnitude measurement and an average error of 10.23° for the contact angle measurement.
A Qualitative Evaluation of the Acceptability of a Tailored Smartphone Alcohol Intervention for a Military Population: Information About Drinking for Ex-Serving Personnel (InDEx) App

Background Alcohol consumption in the UK Armed Forces is higher than in the general population, and this pattern continues after leaving the service. Smartphone apps may be useful to increase ex-serving personnel’s awareness of their alcohol consumption, support self-monitoring, and prompt a change in behavior. Objective The study aimed to explore the acceptability of Information about Drinking in Ex-serving personnel (InDEx), a tailored smartphone app, combined with personalized short message service (SMS) text messaging designed to target ex-serving personnel who meet the criteria for hazardous alcohol use. Methods The InDEx intervention included 4 key modules: (1) assessment and normative feedback, (2) self-monitoring and feedback, (3) goal setting and review, and (4) personalized SMS text messaging. A semistructured telephone interview study was conducted with ex-serving personnel after using the app for a 28-day period. Interviews were used to explore the acceptability of app modules and its functionality and the perceived changes in participant’s drinking. Interview transcripts were analyzed using inductive thematic analysis. Results Overall, 94% (29/31) participants who used InDEx agreed to take part in a telephone interview. Overall, 4 themes were identified: Credibility, Meeting their needs, Simplicity, and Helpful for ex-serving personnel. The importance of credibility, functionality, and meeting the individual needs of ex-serving personnel was emphasized. Acceptability and engagement with specific modules of the app and text messages were influenced by the following: (1) if they felt it provided credible information, (2) whether the content was appropriately personalized to them, (3) the ease of use, and (4) beliefs about their own drinking behaviors. Participants recommended that the app would be most suitable for personnel about to leave the Armed Forces. Conclusions InDEx was an acceptable smartphone app for ex-serving personnel for monitoring alcohol consumption and in providing meaningful feedback to the individual. Pages that met the participant’s interests and provided real time personalized, credible feedback on their drinking and text messages tailored to participant’s interactions with the app were particularly favored.
A principled methodology for the design of autonomous trading agents with cominatorial preferences in the presence of tradeoffs

Online auctions have become a popular method for business transactions. The variety of different auction rules, the restrictions in supply or demand, and the agents' combinatorial preferences for the different commodities, have led to the creation of a very complex multi-agent "environment" and a number of strategic tradeoffs. Designing an agent that deals efficiently with these tradeoffs has been a multi-pronged effort. Using game-theoretic approaches, some equilibria have been computed for relatively simple auctions. However, since these equilibria have limited practical application, due to the significant number of varying auctions that take place simultaneously, empirical approaches and experimental evaluations of various strategies have also been used. Furthermore, progress has been made into designing better agent architectures. This dissertation presents results in all of these directions (theoretical and empirical). We present a methodology for designing trading agents, and deciding their bidding strategy, when they participate in a large number of simultaneous auctions with a variety of rules. We use a modular, adaptive, scalable and robust agent architecture, combining principled methods and empirical knowledge. We decompose the problem faced by the agent into several components, and restrict communication between them. This allows us to analyze each component individually. The "optimizer" coordinates the effort of the entire system and determines the set of commodities that maximizes the utility of the agent. We provide a principled way of generating strategies for each bidding module. Then we use rigorous experimentation to explore the strategy space and determine the best combination of strategies. This enables the agent to perform efficiently against any opponent agents. We also expand this methodology to include design decisions based on the equilibria computed for particular auctions. Furthermore, we present several novel Bayes-Nash equilibria for mth price multi-unit auctions with multiple possible closing times, one of which is chosen randomly, in which multiple rounds of bidding can occur. We applied this methodology when creating WhiteBear, the winner of the 2002 and 2004 Trading Agent Competitions. We also present the "complete" set of experiments for determining an overall best strategy in TAC, which guided the design of WhiteBear. We show that by optimizing over the strategy space one obtains highly effective and flexible agents that outperform other designs.
Nuclear factor‐κB activation in schwann cells regulates regeneration and remyelination

Schwann cells (SCs) are crucial for peripheral nerve development and regeneration; however, the intrinsic regulatory mechanisms governing postinjury responses are poorly understood. Activation and deacetylation of nuclear factor‐κB (NF‐ κB) in SCs have been implicated as prerequisites for peripheral nerve myelination. Using GFAP‐IκBα‐dn mice in which NF‐ κB transcriptional activation is inhibited in SCs, we found no discernable differences in the quantity or structure of myelinated axons in adult facial nerves. Following crush injury, axonal regeneration was impaired at 31 days and significantly enhanced at 65 days in transgenic animals. Compact remyelination and Remak bundle organization were significantly compromised at 31 days and restored by 65 days post injury. Together, these data indicate that inhibition of NF‐κB activation in SCs transiently delays axonal regeneration and compact remyelination. Manipulating the temporal activation of nuclear factor‐κB in Schwann cells may offer new therapeutic avenues for PNS and CNS regeneration. © 2012 Wiley Periodicals, Inc.
Synthesizing Distributed Systems

In system synthesis, we transform a spe i ation into a system that is guaranteed to satisfy the spe i ation. When the system is distributed, the goal is to onstru t the system's underlying pro esses. Results on multi-player games imply that the synthesis problem for linear spe i ations is unde idable for general ar hite tures, and is nonelementary de idable for hierar hi al ar hite tures, where the pro esses are linearly ordered and information among them ows in one dire tion. In this paper we present a signi ant extension of this result. We handle both linear and bran hing spe i ations, and we show that a suÆ ient ondition for de idability of the synthesis problem is a linear or y li order among the pro esses, in whi h information ows in either one or both dire tions. We also allow the pro esses to have internal hidden variables, and we onsider ommuni ations with and without delay. Many pra ti al appli ations fall into this lass.
A New Intrinsic Characterization of the Contact System for Cu ves by Corank One Involutive Subdistributions

In our paper, we address the following question: “Which nonholonomic control systems are locally feedback equivalent to the canonical contact system on Jn(R;Rm )? ” We provide easily checkable necessary and sufficient conditio ns, expressed in terms of the original system, for such a feedback transformation to exist. Moreover, our proofs exhibit a deep geometry of contact systems.