Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrophysiological indicators of surprise and entropy in dynamic task-switching environments

This event-related brain potential (ERP) study aimed at bridging two hitherto widely separated domains of cognitive neuroscience. Specifically, we combined the analysis of cognitive control in a cued task-switching paradigm with the fundamental question of how uncertainty is encoded in the brain. Two functional models of P3 amplitude variation in cued task-switching paradigms were put to an empirical test: (1) According to the P3b surprise hypothesis, parietal P3b waveforms are related to surprise over switch cues. (2) According to the P3a entropy hypothesis, frontal P3a waveforms are associated with entropy over switch outcomes. In order to examine these hypotheses, we measured the EEG while sixteen healthy young participants performed cued task-switching paradigms closely modeled to the Wisconsin Card Sorting Test (WCST). We applied a factorial design, with number of tasks (two vs. three viable tasks), cue explicitness (task cuing vs. transition cuing), and cue contingency (prospectively-signaled cuing vs. feedback-based cuing) as independent variables. The ERP results replicated the commonly reported P3b effect associated with task switches, and further showed that P3a amplitudes were related to the entropy of switch outcomes, thereby supporting both hypotheses. Based on these ERP data, we suggest that surprise over task switches, and entropy over switch outcomes, constitute dissociable functional correlates of P3b and P3a ERP components in task-switching paradigms, respectively. Finally, a theoretical integration of the findings is proposed within the framework of Sokolov's (1966) entropy model of the orienting response (OR).
Accurate anchor-free node localization in wireless sensor networks

There has been a growing interest in the applications of wireless sensor networks in unattended environments. In such applications, sensor nodes are usually deployed randomly in an area of interest. Knowledge of accurate node location is essential in order to correlate the gathered data to the origin of the sensed phenomena and assure the relevance of the reported information. In this paper, we present an efficient anchor-free protocol for localization in wireless sensor networks. Each node discovers its neighbors that are within its transmission range and estimates their ranges. Our algorithm fuses local range measurements in order to form a network wide unified coordinate systems while minimizing the overhead incurred at the deployed sensors. Scalability is achieved through grouping sensors into clusters. Simulation results show that the proposed protocol achieves precise localization of sensors and maintains consistent error margins.
A stochastic model of human-machine interaction for learning dialog strategies

We propose a quantitative model for dialog systems that can be used for learning the dialog strategy. We claim that the problem of dialog design can be formalized as an optimization problem with an objective function reflecting different dialog dimensions relevant for a given application. We also show that any dialog system can be formally described as a sequential decision process in terms of its state space, action set, and strategy. With additional assumptions about the state transition probabilities and cost assignment, a dialog system can be mapped to a stochastic model known as Markov decision process (MDP). A variety of data driven algorithms for finding the optimal strategy (i.e., the one that optimizes the criterion) is available within the MDP framework, based on reinforcement learning. For an effective use of the available training data we propose a combination of supervised and reinforcement learning: the supervised learning is used to estimate a model of the user, i.e., the MDP parameters that quantify the user's behavior. Then a reinforcement learning algorithm is used to estimate the optimal strategy while the system interacts with the simulated user. This approach is tested for learning the strategy in an air travel information system (ATIS) task. The experimental results we present in this paper show that it is indeed possible to find a simple criterion, a state space representation, and a simulated user parameterization in order to automatically learn a relatively complex dialog behavior, similar to one that was heuristically designed by several research groups.
Overview 2010 of ARL Program on Network Science for Human Decision Making

The Army Research Laboratory program on the Network Science of Human Decision Making brings together researchers from a variety of disciplines to work on a complex research problem that defies confinement within any single discipline. Consequently, new and rewarding solutions have been obtained for a problem of importance to society and the Army, that being, the human dimension of complex networks. This program investigates the basic research foundation of a science of networks supporting the linkage between the cognitive and social domains as they relate to human decision making. The research strategy extends recent methods of non-equilibrium statistical physics to non-stationary, renewal stochastic processes characteristic of the interactions among nodes in complex networks. The theoretical analyses of complex networks, although mathematically rigorous, often elude analytic solutions and require simulation and computation to analyze the underlying dynamic process. The information transfer between two complex networks is calculated using the principle of complexity management as well as direct numerical calculation of the decision making model developed within the project.
Measurement of Flow in Single Blood Vessels Including Cardiac Output by Local Thermodilution

On the basis of local thermodilution a method for measuring blood flow in a single vessel was elaborated. The measurement was accomplished by a special catheter with an injection orifice and a thermistor. The accuracy of the method was studied both in model and in vivo experiments on dogs (in jugular vein, in carotid and pulmonary artery) and good correlation was found with direct methods.
Comparison of endosonography-guided vs. percutaneous biliary stenting when papilla is inaccessible for ERCP

Background Endoscopic retrograde cholangiopancreatography (ERCP) and biliary stenting fails in 5–10% patients of malignant biliary obstruction because papilla is inaccessible. Percutaneous transhepatic biliary drainage (PTBD) is an accepted alternative. Endosonography-guided biliary drainage (EUS-BD) has been described recently. Aim To compare success rates and complications of EUS-BD and PTBD internal stenting. Methods This retrospective study included failed ERCP in inoperable malignant biliary obstruction due to inaccessible papilla undergoing PTBD or EUS-BD. Percutaneous transhepatic cholangiography guided/EUS-guided rendezvous procedures were excluded. When PTBD internal stenting failed, external drainage was performed. EUS-BD was performed using either intra- or extrahepatic approach, and stents were placed by transmural (choledocho-duodenostomy or hepatico-gastrostomy) or antegrade approach. Self-expandable metallic stents or plastic stents were placed in both groups. Success of internal stenting and complications were compared using t-test and chi-squared test. Results Retrospective review of 6 years of records (2005–2011) revealed 50 patients meeting the required criteria. EUS-BD was attempted in 25 and PTBD in 26 patients (one crossover from EUS-BD to PTBD). Internal stenting was technically and clinically successful in 23/25 (92%) EUS-BD vs. 12/26 (46%) PTBD (p < 0.05). External catheter drainage was performed in remaining 14 PTBD patients. Complications occurred in 5/25 (20%) EUS-BD (one major, four minor) and in 12/26 (46%) PTBD (four major, eight minor; p < 0.05). Late stent occlusion occurred in one EUS-BD and three PTBD. Conclusions In this retrospective study comparing success and complications of EUS-BD and PTBD in patients with inoperable malignant biliary obstruction and inaccessible papilla, EUS-BD was found superior to PTBD for both comparators.
Modeling wireless fading channels via stochastic differential equations: identification and estimation based on noisy measurements

This paper is concerned with modeling and identification of wireless channels using noisy measurements. The models employed are governed by stochastic differential equations (SDEs) in state space form, while the identification method is based on the expectation-maximization (EM) algorithm and Kalman filtering. The algorithm is tested against real channel measurements. The results presented include state space models for the channels, estimates of inphase and quadrature components, and estimates of the corresponding Doppler power spectral densities (DPSDs), from sample noisy measurements. Based on the available measurements, it is concluded that state space models of order two are sufficient for wireless flat fading channel characterization.
Modeling and Simulation of Molecular Communication Systems With a Reversible Adsorption Receiver

In this paper, we present an analytical model for the diffusive molecular communication (MC) system with a reversible adsorption receiver in a fluid environment. The widely used concentration shift keying is considered for modulation. The time-varying spatial distribution of the information molecules under the reversible adsorption and desorption reaction at the surface of a receiver is analytically characterized. Based on the spatial distribution, we derive the net number of adsorbed information molecules expected in any time duration. We further derive the net number of adsorbed molecules expected at the steady state to demonstrate the equilibrium concentration. Given the net number of adsorbed information molecules, the bit error probability of the proposed MC system is analytically approximated. Importantly, we present a simulation framework for the proposed model that accounts for the diffusion and reversible reaction. Simulation results show the accuracy of our derived expressions, and demonstrate the positive effect of the adsorption rate and the negative effect of the desorption rate on the error probability of reversible adsorption receiver with last transmit bit-1. Moreover, our analytical results simplify to the special cases of a full adsorption receiver and a partial adsorption receiver, both of which do not include desorption.
Molecular viral epidemiology and clinical characterization of acute febrile respiratory infections in hospitalized children in Taiwan

Acute respiratory infection (ARI) is a leading cause of morbidity and hospitalization in children. To profile the viruses causing ARI in children admitted to a community‐based hospital in central Taiwan, a cross‐sectional study was conducted on children under 14 years of age that were hospitalized with febrile ARI. Viral etiology was determined using conventional cell culture and a commercial respiratory virus panel fast assay (xTAG RVP), capable of detecting 19 different respiratory viruses and subtype targets. Demographic, clinical, and laboratory data were recorded and analyzed. The RVP fast assay identified at least one respiratory virus in 130 of the 216 specimens examined (60.2%) and rose to 137 (63.4%) by combining the results of cell culture and RVP fast assay. In order of frequency, the etiological agents identified were, rhinovirus/enterovirus (24.6%), respiratory syncytial virus (13.8%), adenovirus (11.5%), parainfluenza virus (9.2%), influenza B (8.4%), influenza A (5.4%), human metapneumovirus (4.6%), human coronavirus (2%), and human bocavirus (2%). Co‐infection did not result in an increase in clinical severity. The RVP assay detected more positive specimens, but failed to detect 6 viruses identified by culture. The viral detection rate for the RVP assay was affected by how many days after admission the samples were taken (P = 0.03). In conclusion, Rhinovirus/enterovirus, respiratory syncytial virus, and adenovirus were prevalent in this study by adopting RVP assay. The viral detection rate is influenced by sampling time, especially if the tests are performed during the first three days of hospitalization. J. Med. Virol. 87:1860–1866, 2015. © 2015 Wiley Periodicals, Inc.
Best-first Model Merging for Hidden Markov Model Induction

This report describes a new technique for inducing the structure of Hidden Markov Models from data which is based on the general `model merging' strategy (Omohundro 1992). The process begins with a maximum likelihood HMM that directly encodes the training data. Successively more general models are produced by merging HMM states. A Bayesian posterior probability criterion is used to determine which states to merge and when to stop generalizing. The procedure may be considered a heuristic search for the HMM structure with the highest posterior probability. We discuss a variety of possible priors for HMMs, as well as a number of approximations which improve the computational efficiency of the algorithm. We studied three applications to evaluate the procedure. The first compares the merging algorithm with the standard Baum-Welch approach in inducing simple finite-state languages from small, positive-only training samples. We found that the merging procedure is more robust and accurate, particularly with a small amount of training data. The second application uses labelled speech data from the TIMIT database to build compact, multiple-pronunciation word models that can be used in speech recognition. Finally, we describe how the algorithm was incorporated in an operational speech understanding system, where it is combined with neural network acoustic likelihood estimators to improve performance over single-pronunciation word models.
A Rapid Method for the Extraction and Analysis of Carotenoids and Other Hydrophobic Substances Suitable for Systems Biology Studies with Photosynthetic Bacteria

A simple, rapid, and inexpensive extraction method for carotenoids and other non-polar compounds present in phototrophic bacteria has been developed. The method, which has been extensively tested on the phototrophic purple non-sulphur bacterium Rhodospirillum rubrum, is suitable for extracting large numbers of samples, which is common in systems biology studies, and yields material suitable for subsequent analysis using HPLC and mass spectroscopy. The procedure is particularly suitable for carotenoids and other terpenoids, including quinones, bacteriochlorophyll a and bacteriopheophytin a, and is also useful for the analysis of polar phospholipids. The extraction procedure requires only a single step extraction with a hexane/methanol/water mixture, followed by HPLC using a Spherisorb C18 column, with a mobile phase consisting of acetone-water and a non-linear gradient of 50%–100% acetone. The method was employed for examining the carotenoid composition observed during microaerophilic growth of R. rubrum strains, and was able to determine 18 carotenoids, 4 isoprenoid-quinones, bacteriochlorophyll a and bacteriopheophytin a as well as four different phosphatidylglycerol species of different acyl chain compositions. The analytical procedure was used to examine the dynamics of carotenoid biosynthesis in the major and minor pathways operating simultaneously in a carotenoid biosynthesis mutant of R. rubrum.
Influence of Psychologic Features on Rehabilitation Outcomes in Patients with Subacute Stroke Trained with Robotic-Aided Walking Therapy

Objective The aim of this study was to investigate whether the rehabilitation outcomes with robotic-aided gait therapy may be affected by patients’ and caregivers’ psychologic features after subacute stroke. Design This is a controlled, longitudinal, observational pilot study conducted on 42 patients divided in robotic-assisted gait training plus conventional physical therapy group, robotic-assisted gait training dropout group, and conventional physical therapy group. The outcome measures were walking ability (Functional Ambulation Category) and independency in activities of daily living (Barthel Index) measured before and after intervention. Psychologic features were measured before intervention using the Hospital Anxiety and Depression Scale, the Eysenck Personality Questionnaire, and recovery locus of control in the patients and the State-Trait Anxiety Inventory and the Beck Depression Inventory in the caregivers. Results Patient anxiety was significantly higher in those who refused/abandoned robotic therapy (P = 0.002). In the subjects allocated to the robotic group, the recovery of walking ability was significantly affected by the perceived recovery locus of control (P = 0.039, odds ratio = 14); and the recovery of independency in activities of daily living, by anxiety (P = 0.018, odds ratio = 0.042). Conversely, psychologic factors did not significantly affect the outcomes of conventional rehabilitation. Conclusions Psychologic features, particularly recovery locus of control and anxiety, affected the rehabilitative outcomes of the patients involved in robotic treatment more than those in conventional rehabilitation.
Adjacency-Faithfulness and Conservative Causal Inference

Most causal inference algorithms in the literature (e.g., Pearl (2000), Spirtes et al. (2000), Heckerman et al. (1999)) exploit an assumption usually referred to as the causal Faithfulness or Stability condition. In this paper, we highlight two components of the condition used in constraint-based algorithms, which we call "Adjacency-Faithfulness" and "Orientation-Faithfulness". We point out that assuming Adjacency-Faithfulness is true, it is in principle possible to test the validity of Orientation-Faithfulness. Based on this observation, we explore the consequence of making only the Adjacency-Faithfulness assumption. We show that the familiar PC algorithm has to be modified to be (asymptotically) correct under the weaker, Adjacency-Faithfulness assumption. Roughly the modified algorithm, called Conservative PC (CPC), checks whether Orientation-Faithfulness holds in the orientation phase, and if not, avoids drawing certain causal conclusions the PC algorithm would draw. However, if the stronger, standard causal Faithfulness condition actually obtains, the CPC algorithm is shown to output the same pattern as the PC algorithm does in the large sample limit. We also present a simulation study showing that the CPC algorithm runs almost as fast as the PC algorithm, and outputs significantly fewer false causal arrowheads than the PC algorithm does on realistic sample sizes. We end our paper by discussing how score-based algorithms such as GES perform when the Adjacency-Faithfulness but not the standard causal Faithfulness condition holds, and how to extend our work to the FCI algorithm, which allows for the possibility of latent variables.
Corrosion Testing of a Heat Treated 316 L Functional Part Produced by Selective Laser Melting

Selective Laser Melting (SLM) shows a big potential among metal additive manufacturing (AM) technologies. However, the large thermal gradients and the local melting and solidification processes of SLM result in the presence of a significant amount of residual stresses in the as built parts. These internal stresses will not only affect mechanical properties, but also increase the risk of Stress Corrosion Cracking (SCC). A twister used in an air extraction pump of a condenser to create a swirl in the water, was chosen as a candidate component to be produced by SLM in 316 L stainless steel. Since the main expected damage mechanism of this component in service is corrosion, corrosion tests were carried out on an as-built twister as well as on heat treated components. It was shown that a low temperature heat treatment at 450℃ had only a limited effect on the residual stress reduction and concomitant corrosion properties, while the internal stresses were significantly reduced when a high temperature heat treatment at 950℃ was applied. Furthermore, a specific stress corrosion sensitivity test proved to be a useful tool to evaluate the internal stress distribution in a specific component.
Behavioral modeling of digital transmitters with time delay neural networks

In this work a novel time delay neural network based complex baseband model is proposed for fully digital pulse driven power amplifier concepts. It will be shown that the given technique is able to capture the non-linear effects related to the analog components of the transmitter. Results based on simulations and measurements indicate an accurate modeling performance over a wide frequency range.
Dispatches Dispatches Dispatches Dispatches Dispatches Mycobacterium Tuberculosis Beijing Genotype Emerging in Vietnam

A high degree of diversity of Mycobacterium tuberculosis has been shown with restriction fragment length polymorphism (RFLP) typing using IS6110 as a probe, particularly in countries like the Netherlands, where many tuberculosis (TB) cases occur among immigrants (1). However, in the Beijing region of China, a particular genotype was found in >80% of the TB patients and was thus designated the Beijing genotype (2). In other parts of China and in Asian countries such as Mongolia, Thailand, and Korea, 40% to 50% of the tested M. tuberculosis isolates represented this genotype (2). Although Beijing genotype strains carry a large number of IS6110 insertion elements, the IS6110 RFLP patterns are highly similar (2). Moreover, the spoligopatterns of Beijing genotype strains are identical and distinct from those of other M. tuberculosis strains (1), which suggests that strains of the Beijing genotype have emerged recently from a single ancestor. Reasons for the predominance of a narrow range of genotypes may include limited contact with other populations or a selective advantage of certain strains due to reduced sensitivity to vaccine-induced immunity. For instance, wide-scale application of vaccines against whooping cough (Bordetella pertussis) has led to shifts in the populations of circulating pathogens (3). BCG vaccination, which has been applied widely in China since the early 1950s, may have led to a similar shift in the population of M. tuberculosis. Alternatively, a selective advantage may be provided by reduced sensitivity to anti-TB drugs. The Beijing genotype was associated with recent transmission of drug-resistant strains in Cuba, Germany, Russia, and Estonia (4-7). The largest known epidemic of multidrug-resistant TB in North America was caused by the " W " strain, a variant of the Beijing genotype (8). Vietnam is one of 22 countries in which 80% of the world's new TB cases occur (9). Among these 22 countries, Vietnam has one of the most successful directly observed therapy short-course programs, with a cure rate of approximately 90% and a case-detection rate estimated at 67% in 1996 and at >70% since then (National Tuberculosis Programme, unpub. data). BCG coverage has been high (>80%) during the past decade, and the level of primary multidrug resistance was recently estimated at 2.3% (9,10). We investigated the spread of M. tuberculosis Beijing genotype strains in Vietnam and whether the spread is associated with BCG vaccination status or drug resistance. To assess whether the Mycobacterium tuberculosis Beijing genotype is emerging in Vietnam, …
ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders

We consider learning a causal ordering of variables in a linear nongaussian acyclic model called LiNGAM. Several methods have been shown to consistently estimate a causal ordering assuming that all the model assumptions are correct. But the estimation results could be distorted if some assumptions are violated. In this letter, we propose a new algorithm for learning causal orders that is robust against one typical violation of the model assumptions: latent confounders. The key idea is to detect latent confounders by testing independence between estimated external influences and find subsets (parcels) that include variables unaffected by latent confounders. We demonstrate the effectiveness of our method using artificial data and simulated brain imaging data.