Miracle-dz/UniFAR-FTUs huggingface dataset:
An EOG-Based Human–Machine Interface for Wheelchair Control

Objective: Nonmanual human–machine interfaces (HMIs) have been studied for wheelchair control with the aim of helping severely paralyzed individuals regain some mobility. The challenge is to rapidly, accurately, and sufficiently produce control commands, such as left and right turns, forward and backward motions, acceleration, deceleration, and stopping. In this paper, a novel electrooculogram (EOG) based HMI is proposed for wheelchair control. Methods: A total of 13 flashing buttons, each of which corresponds to a command, are presented in the graphical user interface. These buttons flash on a one-by-one manner in a predefined sequence. The user can select a button by blinking in sync with its flashes. The algorithm detects the eye blinks from a channel of vertical EOG data and determines the user's target button based on the synchronization between the detected blinks and the button's flashes. Results: For healthy subjects/patients with spinal cord injuries, the proposed HMI achieved an average accuracy of 96.7% / 91.7% and a response time of 3.53 s/3.67 s with 0 false positive rates (FPRs). Conclusion: Using one channel of vertical EOG signals associated with eye blinks, the proposed HMI can accurately provide sufficient commands with a satisfactory response time. Significance: The proposed HMI provides a novel nonmanual approach for severely paralyzed individuals to control a wheelchair. Compared with a newly established EOG-based HMI, the proposed HMI can generate more commands with higher accuracy, lower FPR, and fewer electrodes.
Distributed space-time coding for multihop transmission in power line communication networks

In this paper, we consider transmission in relatively wide-stretched power line communication (PLC) networks, where repeaters are required to bridge the source-to-destination distance. In particular, it is assumed that each network node is a potential repeater and that multihop transmission is accomplished in an ad hoc fashion without the need for complex routing protocols. In such a scenario, due to the broadcasting nature of the power line channel, multiple repeater nodes may receive and retransmit the source message simultaneously. It is shown that, if no further signal processing is applied at the transmitter, simultaneous retransmission often deteriorates performance compared with single-node retransmission. We therefore advocate the application of distributed space-time block codes (DSTBCs) to the problem at hand. More specifically, we propose that each network node is assigned a unique signature sequence, which allows efficient combining at the receiver. Most notably, DSTBC-based retransmission does not require explicit collaboration among network nodes for multihop transmission and detection complexity is not increased compared with single-node retransmission. Numerical results for multihop transmission over PLC networks show that DSTBC-based retransmission achieves a considerably improved performance in terms of required transmit power and multihop delay compared with alternative retransmission strategies.
Ecosystem Alterations and Species Range Shifts: An Atlantic-Mediterranean Cephalaspidean Gastropod in an Inland Egyptian Lake

The eastern Atlantic and Mediterranean marine Cephalaspidea gastropod Haminoea orbignyana was collected from Lake Qarun (Fayoum, Egypt), a landlocked lake that has undergone a shift from freshwater to estuarine conditions in the past 100 years. Species identity was confirmed by both morphological (anatomical dissection and scanning electron microscopy) and molecular methods (COI gene phylogeny). Observations suggested a robust population of H. orbignyana in the lake with a density of ca. 64 individuals/m2 and ca. 105 egg masses/m2 during surveys conducted in the summer of 2013. The vast majority of snails and egg masses were found under rocks. Observations of egg masses in the lab showed a gradual change from whitish to yellow-green as the eggs matured and the release of veliger larvae alone after about a week. Although adult cephalaspideans readily consumed filamentous red and green algae, and cyanobacteria, laboratory trials showed that they consumed significantly more of the red alga Ceramium sp. , than of the green alga Cladophora glomerata, with consumption of Oscillatoria margaritifera being similar to those on the two algae. When grown on these resources for 16 days, H. orbignyana maintained their mass on the rhodophyte and cyanobacterium, but not in starvation controls. No cephalaspideans grew over the course of this experiment. Lake Qarun has been periodically restocked with Mediterranean fishes and prawns since the 1920s to maintain local fisheries, which represents a possible route of colonization for H. orbignyana. Yet, based on literature records, it seems more likely that invasion of the lake by this gastropod species has occurred only within the last 20 years. As human activities redistribute species through direct and indirect means, the structure of the community of this inland lake has become unpredictable and the long-term effects of these recent introductions are unknown.
Supervised Model Learning with Feature Grouping based on a Discrete Constraint

This paper proposes a framework of supervised model learning that realizes feature grouping to obtain lower complexity models. The main idea of our method is to integrate a discrete constraint into model learning with the help of the dual decomposition technique. Experiments on two well-studied NLP tasks, dependency parsing and NER, demonstrate that our method can provide state-of-the-art performance even if the degrees of freedom in trained models are surprisingly small, i.e., 8 or even 2. This significant benefit enables us to provide compact model representation, which is especially useful in actual use.
Hardness of Graph Pricing Through Generalized Max-Dicut

The Graph Pricing problem is among the fundamental problems whose approximability is not well-understood. While there is a simple combinatorial 1/4-approximation algorithm, the best hardness result remains at 1/2 assuming the Unique Games Conjecture (UGC). We show that it is NP-hard to approximate within a factor better than 1/4 under the UGC, so that the simple combinatorial algorithm might be the best possible. We also prove that for any ε > 0, there exists δ > 0 such that the integrality gap of nδ-rounds of the Sherali-Adams hierarchy of linear programming for Graph Pricing is at most 1/4 + ε. This work is based on the effort to view the Graph Pricing problem as a Constraint Satisfaction Problem (CSP) simpler than the standard and complicated formulation. We propose the problem called Generalized Max-Dicut(T), which has a domain size T + 1 for every T ≥ 1. Generalized Max-Dicut(1) is well-known Max-Dicut. There is an approximation preserving reduction from Generalized Max-Dicut on directed acyclic graphs (DAGs) to Graph Pricing, and both our results are achieved through this reduction. Besides its connection to Graph Pricing, the hardness of Generalized Max-Dicut is interesting in its own right since in most arity two CSPs studied in the literature, SDP-based algorithms perform better than LP-based or combinatorial algorithms --- for this arity two CSP, a simple combinatorial algorithm does the best.
Adolescent but not adult ethanol binge drinking modulates cocaine withdrawal symptoms in mice

Background Ethanol (EtOH) binge drinking is an increasingly common behavior among teenagers that induces long-lasting neurobehavioral alterations in adulthood. An early history of EtOH abuse during adolescence is highly correlated with cocaine addiction in adulthood. Abstinence of cocaine abuse can cause psychiatric symptoms, such as anxiety, psychosis, depression, and cognitive impairments. This study assessed the consequences of adolescent exposure to EtOH on the behavioral alterations promoted by cocaine withdrawal in adulthood. Methods We pretreated juvenile (34–47 days old) or adult (68–81 days old) mice with EtOH (1.25 g/kg) following a binge-drinking pattern. Then, after a three-week period without drug delivery, they were subjected to a chronic cocaine treatment in adulthood and tested under cocaine withdrawal by the ensuing paradigms: open field, elevated plus maze, prepulse inhibition, tail suspension test, and object recognition. Another set of mice were treated with the same EtOH binge-drinking procedure during adolescence and were tested immediately afterwards under the same behavioral paradigms. Results Adolescent EtOH pretreatment undermined the anxiogenic effects observed after cocaine abstinence, reduced prepulse inhibition, and increased immobility scores in the tail suspension test following cocaine withdrawal. Moreover, the memory deficits evoked by these substances when given separately were enhanced in cocaine-withdrawn mice exposed to EtOH during adolescence. EtOH binge drinking during adolescence also induced anxiety, depressive symptoms, and memory impairments when measured immediately afterwards. In contrast, neither EtOH nor cocaine alone or in combination altered any of these behaviors when given in adulthood. Conclusions EtOH binge drinking induces short- and long-term behavioral alterations and modulates cocaine withdrawal symptoms when given in adolescent mice.
Iterative MILP methods for vehicle-control problems

Mixed-integer linear programming (MILP) is a powerful tool for planning and control problems because of its modeling capability and the availability of good solvers. However, for large models, MILP methods suffer computationally. In this paper, we present iterative MILP algorithms that address this issue. We consider trajectory-generation problems with obstacle-avoidance requirements and minimum-time trajectory-generation problems. These problems involve vehicles that are described by mixed logical dynamical equations, a form of hybrid system. The algorithms use fewer binary variables than standard MILP methods, and require less computational effort.
Integrated optimal power flow for distribution networks in local and urban scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.
Opposite Effective Connectivity in the Posterior Cingulate and Medial Prefrontal Cortex between First-Episode Schizophrenic Patients with Suicide Risk and Healthy Controls

Objective The schizophrenic patients with high suicide risk are characterized by depression, better cognitive function, and prominent positive symptoms. However, the neurobiological basis of suicide attempts in schizophrenia is not clear. The suicide in schizophrenia is implicated in the defects in emotional process and decision-making, which are associated with prefrontal-cingulate circuit. In order to explore the possible neurobiological basis of suicide in schizophrenia, we investigated the correlation of prefrontal-cingulate circuit with suicide risk in schizophrenia via dynamic casual modelling. Method Participants were 33 first-episode schizophrenic patients comprising of a high suicide risk group (N = 14) and a low suicide risk group (N = 19). A comparison group of healthy controls (N = 15) were matched for age, gender and education. N-back tasking functional magnetic resonance imaging data was collected. Results Compared with healthy controls group, the two patients groups showed decreased task-related suppression during 2-back task state versus baseline state in the left posterior cingulate and medial prefrontal cortex; the hyper-connectivity from the left posterior cingulate cortex to the left medial prefrontal cortex existed in both schizophrenic patients groups, but hypo-connectivity in the opposite direction only existed in the schizophrenic patients group with high suicide risk. Conclusions The hyper-connectivity from the left posterior cingulate cortex to the left medial prefrontal cortex may suggest that the abnormal effective connectivity was associated with risk for schizophrenia. The hypo-connectivity in the opposite direction may represent a possible correlate of increased vulnerability to suicide attempt.
Homogenised Virtual Support Vector Machines

In many domains, reliable a priori knowledge exists that may be used to improve classifier performance. For example in handwritten digit recognition, such a priori knowledge may include classification invariance with respect to image translations and rotations. In this paper, we present a new generalisation of the Support Vector Machine (SVM) that aims to better incorporate this knowledge. The method is an extension of the Virtual SVM, and penalises an approximation of the variance of the decision function across each grouped set of “virtual examples”, thus utilising the fact that these groups should ideally be assigned similar class membership probabilities. The method is shown to be an efficient approximation of the invariant SVM of Chapelle and Scḧolkopf, with the advantage that it can be solved by trivial modification to standard SVM optimization packages and negligible increase in computational complexity when compared with the Virtual SVM. The efficacy of the method is demonstrated on a simple problem.
Data sampling through collaborative filtering for algorithm selection

Algorithm selection has been studied to specify the best possible algorithm(s) for a given problem instance. One of the major drawbacks of the algorithm selection methods is their need for the performance data. The performance data involves the performance of a set of algorithms on a group of problem instances. Depending on the problem domain, algorithms and the experimental settings, generating such data can be computationally expensive. ALORS [1] as a collaborative filtering based algorithm selection strategy addresses this issue by performing matrix completion. Matrix completion allows to generate algorithm selection models when the performance data is incomplete. Although ALORS is able to deal with varying data incompleteness levels, it ignores the quality and cost of the performance data. The present study offers a collaborative filtering based sampling strategy to designate which algorithm(s) to run on which instance(s). The goal is to provide either computationally cheap or highly informative incomplete performance data for algorithm selection.
Stress modulates intestinal secretory immunoglobulin A

Stress is a response of the central nervous system to environmental stimuli perceived as a threat to homeostasis. The stress response triggers the generation of neurotransmitters and hormones from the hypothalamus pituitary adrenal axis, sympathetic axis and brain gut axis, and in this way modulates the intestinal immune system. The effects of psychological stress on intestinal immunity have been investigated mostly with the restraint/immobilization rodent model, resulting in an up or down modulation of SIgA levels depending on the intensity and time of exposure to stress. SIgA is a protein complex formed by dimeric (dIgA) or polymeric IgA (pIgA) and the secretory component (SC), a peptide derived from the polymeric immunoglobulin receptor (pIgR). The latter receptor is a transmembrane protein expressed on the basolateral side of gut epithelial cells, where it uptakes dIgA or pIgA released by plasma cells in the lamina propria. As a result, the IgA-pIgR complex is formed and transported by vesicles to the apical side of epithelial cells. pIgR is then cleaved to release SIgA into the luminal secretions of gut. Down modulation of SIgA associated with stress can have negative repercussions on intestinal function and integrity. This can take the form of increased adhesion of pathogenic agents to the intestinal epithelium and/or an altered balance of inflammation leading to greater intestinal permeability. Most studies on the molecular and biochemical mechanisms involved in the stress response have focused on systemic immunity. The present review analyzes the impact of stress (mostly by restraint/immobilization, but also with mention of other models) on the generation of SIgA, pIgR and other humoral and cellular components involved in the intestinal immune response. Insights into these mechanisms could lead to better therapies for protecting against pathogenic agents and avoiding epithelial tissue damage by modulating intestinal inflammation.
Inverse MDS: Inferring Dissimilarity Structure from Multiple Item Arrangements

The pairwise dissimilarities of a set of items can be intuitively visualized by a 2D arrangement of the items, in which the distances reflect the dissimilarities. Such an arrangement can be obtained by multidimensional scaling (MDS). We propose a method for the inverse process: inferring the pairwise dissimilarities from multiple 2D arrangements of items. Perceptual dissimilarities are classically measured using pairwise dissimilarity judgments. However, alternative methods including free sorting and 2D arrangements have previously been proposed. The present proposal is novel (a) in that the dissimilarity matrix is estimated by “inverse MDS” based on multiple arrangements of item subsets, and (b) in that the subsets are designed by an adaptive algorithm that aims to provide optimal evidence for the dissimilarity estimates. The subject arranges the items (represented as icons on a computer screen) by means of mouse drag-and-drop operations. The multi-arrangement method can be construed as a generalization of simpler methods: It reduces to pairwise dissimilarity judgments if each arrangement contains only two items, and to free sorting if the items are categorically arranged into discrete piles. Multi-arrangement combines the advantages of these methods. It is efficient (because the subject communicates many dissimilarity judgments with each mouse drag), psychologically attractive (because dissimilarities are judged in context), and can characterize continuous high-dimensional dissimilarity structures. We present two procedures for estimating the dissimilarity matrix: a simple weighted-aligned-average of the partial dissimilarity matrices and a computationally intensive algorithm, which estimates the dissimilarity matrix by iteratively minimizing the error of MDS-predictions of the subject’s arrangements. The Matlab code for interactive arrangement and dissimilarity estimation is available from the authors upon request.
Late Restenosis After Both First-Generation and Second-Generation Drug-Eluting Stent Implantations Occurs in Patients With Drug-Eluting Stent Restenosis

Background—There are currently inadequate data about whether late restenosis occurs after drug-eluting stent (DES) implantation in patients with DES restenosis. Methods and Results—We collected data for 608 patients who received revascularization for DES restenosis between 2004 and 2012 and analyzed 688 lesions: 359 lesions treated with a first-generation DES (first DES) and 329 lesions treated with a second-generation DES (second DES). Two serial angiographic follow-ups were routinely planned for the patients (at 8 and 20 months after the procedure). Early follow-up angiography was performed for 620 lesions (90.1%), and recurrent restenosis occurred in 84 lesions (25.8%) in the first DES group and in 72 lesions (24.5%) in the second DES group (P=0.78). Target lesion revascularization was performed for 69 lesions (21.2%) in the first DES group and for 48 lesions (16.3%) in the second DES group (P=0.15). Late follow-up angiography was performed for 438 (87.1%) of the remaining 503 lesions (excluding target lesion revascularization lesions), and late restenosis was found in 35 lesions (15.8%) in the first DES group and in 28 lesions (14.7%) in the second DES group (P=0.79). Nonfocal-type restenosis, percentage diameter stenosis after the procedure, previous stent size ⩽2.5 mm, and right coronary artery ostial lesion were independent predictors of early restenosis. Nonfocal-type restenosis, percentage diameter stenosis at early follow-up, and stent fracture were independent predictors of late restenosis. Conclusions—Late restenosis occurs after both first DES implantation and second DES implantation for DES restenosis.
Network-coded fronthaul transmission for cache-aided C-RAN

In this paper, we study the cache-aided cloud radio access network (C-RAN) with wireless fronthaul, where multiple cache-enabled users are served by multiple cache-enabled transmitters that are connected to a cloud processor through a wireless fronthaul link. We put forth a caching-and-delivery scheme that combines network-coded fronthaul transmission with cache-aided interference management. By broadcasting network-coded messages, the cloud processor provides additional information of the requested files to the transmitters, so as to reduce the edge delivery time. Based on our scheme, an achievable normalized delivery time (NDT) is derived with respect to the cache sizes and the fronthaul capacity.
The Impact of Child Labor and School Quality on Academic Achievement in Brazil

We analyze the impact of child labor on school achievement using Brazilian school achievement test data from the 2003 Sistema Nacional de Avaliacao da Educacao Basica (SAEB). We control for the endogeneity of child labor using instrumental variable techniques, where the instrumental variable is the average wage for unskilled male labor in the state. Using our preferred OLS estimates, we find that child labor causes a loss in students' school achievement. Children and adolescents who do not work have better school performance than students who work. Up to two hours of work per day do not have a statistically significant effect on school performance, but additional hours decrease student's achievement. Differences in work conditions affect school performance. For high school students in Portuguese, compared to students who have schooling as their only activity, students who work only at home score 4 percent lower on the tests. Those students who only work outside the house are worse off than those who only work within the house, with test scores decreasing by 5 percent. Students who work both inside and outside the house have the lowest test scores of all the working conditions, decreasing by up to 7 percent.