Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Seizure and Epilepsy Using Higher Order Statistics in the EMD Domain

In this paper, a method using higher order statistical moments of EEG signals calculated in the empirical mode decomposition (EMD) domain is proposed for detecting seizure and epilepsy. The appropriateness of these moments in distinguishing the EEG signals is investigated through an extensive analysis in the EMD domain. An artificial neural network is employed as the classifier of the EEG signals wherein these moments are used as features. The performance of the proposed method is studied using a publicly available benchmark database for various classification cases that include healthy, interictal (seizure-free interval) and ictal (seizure), healthy and seizure, nonseizure and seizure, and interictal and ictal, and compared with that of several recent methods based on time-frequency analysis and statistical moments. It is shown that the proposed method can provide, in almost all the cases, 100% accuracy, sensitivity, and specificity, especially in the case of discriminating seizure activities from the nonseizure ones for patients with epilepsy while being much faster as compared to the time-frequency analysis-based techniques.
Fluorescence molecular tomography with optimal radon transform based surface reconstruction

Full angle non-contact fluorescence molecular tomography allows acquiring large data sets from complete angles, and simplifies the experimental setups. Accurately extracting animal surface is important for this kind of imaging systems. However, in in-vivo experiments, mouse breath movements and mechanical errors will influence the surface reconstruction. An optimal radon transform based surface reconstruction method is proposed to handle these two factors. The proposed method uses a line searching method to minimize the mismatch between the reconstructed 3D surface and the projected silhouettes at different angles. Therefore, the proposed method generates the optimal 3D surface compared to other methods based on radon transform. Results show that the mean mismatch of 3D surface generated is less than two CCD pixels (0.154 mm) in in-vivo experiments. In-vivo fluorescence molecular tomography is also performed to demonstrate the efficiency of the proposed method.
Application of angiotensin ii to healthy rat sciatic nerve can produce neuropathy without associated vasculopathy

Elevated angiotensin II (AII) levels have been associated with hypertension, diabetes, and polyneuropathy. It is unknown whether AII applied to healthy nerve can be used to model a confined neuronal injury by producing localized vasculopathy and associated neuropathy. In this study, angiotensin II (2.2 μg/ml) or saline was infused constantly via osmotic pump onto the sciatic nerve of 20 rats for 12 weeks. Nerve conduction studies were repeated every 4 weeks, and sciatic nerve was collected for pathological analysis at 12 weeks. Animals infused with AII showed a significant decrease in nerve fiber diameter (P < 0.001), axon diameter (P < 0.001), and myelin thickness (P < 0.001), despite the absence of electrophysiological changes. Surprisingly, there was no significant difference in vessel diameter or wall thickness. AII can cause structural alterations in healthy nerve without associated changes in vasculature, implying the existence of additional previously unrecognized mechanisms of AII‐induced neuronal injury. Muscle Nerve, 2010
Sketch based Image Retrieval using Learned KeyShapes (LKS)

Sketch based image retrieval is a particular case of the image retrieval problem, in which a query is not a regular example image. Instead, the query is a hand-drawn sketch representing what the user is looking for. This kind of problem has a lot of applications, in particular when an example image is not available. For instance, in searching for design pieces in digital catalogs. The natural ambiguity of sketches as well as the poor skills of drawing make the problem very challenging, which is reflected in the low performance achieved by current methods. In this work, we present a novel method for describing sketches based on detecting mid-level patterns called learned keyshapes. Our experiments were performed in two datasets, one with 1326 images and the other with approximately 15k images. Our results show an increase of effectiveness around 17% on the smaller dataset and 98% on the larger one, which represent new state-of-the-art performance in the sketch based image retrieval domain. We also show that our method allows us to achieve good performance even when we use around 20% of the sketch content.
MELD score measured day 10 after orthotopic liver transplantation predicts death and re-transplantation within the first year

Abstract Objective: The impact of early allograft dysfunction on the outcome after liver transplantation is yet to be established. We explored the independent predictive value of the Model for End-Stage Liver Disease (MELD) score measured in the post-transplant period on the risk of mortality or re-transplantation. Material and methods: Retrospective cohort study on adults undergoing orthotopic deceased donor liver transplantation from 2004 to 2014. The MELD score was determined prior to transplantation and daily until 21 days after. The risk of mortality or re-transplantation within the first year was assessed according to quartiles of MELD using unadjusted and adjusted stepwise Cox regression analysis. Results: We included 374 consecutive liver transplant recipients of whom 60 patients died or were re-transplanted. The pre-transplant MELD score was comparable between patients with good and poor outcome, but from day 1 the MELD score significantly diversified and was higher in the poor outcome group (MELD score quartile 4 versus quartile 1–3 at day 10: HR 5.1, 95% CI: 2.8–9.0). This association remained after adjustment for non-identical blood type, autoimmune liver disease and hepatocellular carcinoma (adjusted HR 5.3, 95% CI: 2.9–9.5 for MELD scores at day 10). The post-transplant MELD score was not associated with pre-transplant MELD score or the Eurotransplant donor risk index. Conclusion: Early determination of the MELD score as an indicator of early allograft dysfunction after liver transplantation was a strong independent predictor of mortality or re-transplantation and was not influenced by the quality of the donor, or preoperative recipient risk factors.
Adaptive strategies for collaborative work with scale quad-rotors

The purpose of this paper is to present strategies for the control of movement of rigid bodies via force actuators, possibly redundant. After a nonlinear feedback linealization of the considered dynamic models and the application of a suitable controller, an adaptive neural network based control component is incorporated in order to cope with modeling errors and disturbance rejection. An online sequential quadratic programing optimization with equality and inequality constraints assures an adequate configuration of actuator forces. Application to collaborative work in the transportation of a rigid body using a squadron of scale quad-rotors is studied.
Unveiling Mycoplasma hyopneumoniae Promoters: Sequence Definition and Genomic Distribution

Several Mycoplasma species have had their genome completely sequenced, including four strains of the swine pathogen Mycoplasma hyopneumoniae. Nevertheless, little is known about the nucleotide sequences that control transcriptional initiation in these microorganisms. Therefore, with the objective of investigating the promoter sequences of M. hyopneumoniae, 23 transcriptional start sites (TSSs) of distinct genes were mapped. A pattern that resembles the σ70 promoter −10 element was found upstream of the TSSs. However, no −35 element was distinguished. Instead, an AT-rich periodic signal was identified. About half of the experimentally defined promoters contained the motif 5′-TRTGn-3′, which was identical to the −16 element usually found in Gram-positive bacteria. The defined promoters were utilized to build position-specific scoring matrices in order to scan putative promoters upstream of all coding sequences (CDSs) in the M. hyopneumoniae genome. Two hundred and one signals were found associated with 169 CDSs. Most of these sequences were located within 100 nucleotides of the start codons. This study has shown that the number of promoter-like sequences in the M. hyopneumoniae genome is more frequent than expected by chance, indicating that most of the sequences detected are probably biologically functional.
Anti-Inflammatory Effects of Ellagic Acid on Acute Lung Injury Induced by Acid in Mice

Acute lung injury (ALI) is characterized by alveolar edema and uncontrolled neutrophil migration to the lung, and no specific therapy is still available. Ellagic acid, a compound present in several fruits and medicinal plants, has shown anti-inflammatory activity in several experimental disease models. We used the nonlethal acid aspiration model of ALI in mice to determine whether preventive or therapeutic administration of ellagic acid (10 mg/kg; oral route) could interfere with the development or establishment of ALI inflammation. Dexamethasone (1 mg/kg; subcutaneous route) was used as a positive control. In both preventive and therapeutic treatments, ellagic acid reduced the vascular permeability changes and neutrophil recruitment to the bronchoalveolar lavage fluid (BALF) and to lung compared to the vehicle. In addition, the ellagic acid accelerated the resolution for lung neutrophilia. Moreover, ellagic acid reduced the COX-2-induced exacerbation of inflammation. These results were similar to the dexamethasone. However, while the anti-inflammatory effects of dexamethasone treatment were due to the reduced activation of NF-κB and AP-1, the ellagic acid treatment led to reduced BALF levels of IL-6 and increased levels of IL-10. In addition, dexamethasone treatment reduced IL-1β. Together, these findings identify ellagic acid as a potential therapeutic agent for ALI-associated inflammation.
GhCAX3 Gene, a Novel Ca2+/H+ Exchanger from Cotton, Confers Regulation of Cold Response and ABA Induced Signal Transduction

As a second messenger, Ca2+ plays a major role in cold induced transduction via stimulus-specific increases in [Ca2+]cyt, which is called calcium signature. During this process, CAXs (Ca2+/H+ exchangers) play critical role. For the first time, a putative Ca2+/H+ exchanger GhCAX3 gene from upland cotton (Gossypium hirsutum cv. ‘YZ-1′) was isolated and characterized. It was highly expressed in all tissues of cotton except roots and fibers. This gene may act as a regulator in cotton’s response to abiotic stresses as it could be up-regulated by Ca2+, NaCl, ABA and cold stress. Similar to other CAXs, it was proved that GhCAX3 also had Ca2+ transport activity and the N-terminal regulatory region (NRR) through yeast complementation assay. Over-expression of GhCAX3 in tobacco showed less sensitivity to ABA during seed germination and seedling stages, and the phenotypic difference between wild type (WT) and transgenic plants was more significant when the NRR was truncated. Furthermore, GhCAX3 conferred cold tolerance in yeast as well as in tobacco seedlings based on physiological and molecular studies. However, transgenic plant seeds showed more sensitivity to cold stress compared to WT during seed germination, especially when expressed in N-terminal truncated version. Finally, the extent of sensitivity in transgenic lines was more severe than that in WT line under sodium tungstate treatment (an ABA repressor), indicating that ABA could alleviate cold sensitivity of GhCAX3 seeds, especially in short of its NRR. Meanwhile, we also found that overexpression of GhCAX3 could enhance some cold and ABA responsive marker genes. Taken together, these results suggested that GhCAX3 plays important roles in the cross-talk of ABA and cold signal transduction, and compared to full-length of GhCAX3, the absence of NRR could enhance the tolerance or sensitivity to cold stress, depending on seedling’s developmental stages.
Optimization of OFDMA-Based Cellular Cognitive Radio Networks

In this paper, we study the coexistence and optimization of a multicell cognitive radio network (CRN) which is overlaid with a multicell primary radio network (PRN). We propose a PRN-willingness-based design framework for coexistence and subchannel sharing, and a Lagrange duality based technique to optimize the weighted sum rate (WSR) of secondary users (SUs) over multiple cells. First, to avoid unacceptable SU interference to primary users (PUs), the PRN determines its interference margin based on its target performance metric and channel conditions, and broadcasts this information to the CRN. Second, each CRN cell optimizes its WSR and implements intercell iterative waterfilling (IC-IWF) to control the intercell interference. To account for the interference and transmit power limits at SUs, multilevel waterfilling (M-WF) and direct-power truncation (DPT) duality schemes are developed. Third, we develop a serial dual update technique which enables low-complexity and fast-convergence of the proposed duality schemes. Numerical results demonstrate the effects of multiple parameters, such as the number of SUs per cell, subchannel occupancy probability (SOP), and outage probability of the PUs. Our results show that the proposed duality schemes provide a large performance enhancement than the channel-greedy and access-fairness based resource allocation schemes.
BOXCQP : AN ALGORITHM FOR BOUND CONSTRAINED CONVEX QUADRATIC PROBLEMS

A quadratic programming problem with positive definite Hessian and bound constraints is solved, using a Lagrange multiplier approach. The proposed method falls in the category of exterior point, active set techniques. An iteration of our algorithm modifies both the minimization parameters in the primal space and the Lagrange multipliers in the dual space. Comparative results of numerical experiments are also reported.
A Parallel Distributed Arithmetic Implementation of the Discrete Wavelet Transform

The fine grained parallelism inherent in Field Programmable Gate Arrays (FPGAs) may be well exploited to implement the computation-intensive discrete wavelet transform. In this paper, we describe a parallel implementation of the discrete wavelet transform and its inverse using Virtex FPGAs. We make maximal utilization of the look-up table architecture of Virtex FPGAs by reformulating the wavelet computation in accordance with the parallel distributed arithmetic algorithm. The single chip implementation may be used effectively in the construction of low-power, waveletbased MPEG-4 and JPEG 2000 decoders.
Including Sensor Bias in Shape from Motion Calibration and Multisensor Fusion

Shape from Motion data fusion brings a greater degree of autonomy and sensor integration to intelligent systems in which fusion by constant linear transformations is appropriate. To illustrate this, we apply Shape from Motion techniques to applications involving both similar and disparate sensory information vectors. First, nearly autonomous force/torque sensor calibration is demonstrated through fusion of the individual channels of raw strain gauge data. Gathering only the raw sensor signals, the motion of the force vector (the " motion ") and the calibration matrix (the " shape ") are simultaneously extracted by singular value decomposition. This calibration example is provided to simply explain the mathematics. Disparate sensory information is fused in a " primordial learning " mobile robot through a similar eigenspace representation. This paper summarizes these shape from motion applications and presents an extension for simultaneously extracting sensor bias.
Molecular footprinting of skeletal tissues in the catshark Scyliorhinus canicula and the clawed frog Xenopus tropicalis identifies conserved and derived features of vertebrate calcification

Understanding the evolutionary emergence and subsequent diversification of the vertebrate skeleton requires a comprehensive view of the diverse skeletal cell types found in distinct developmental contexts, tissues, and species. To date, our knowledge of the molecular nature of the shark calcified extracellular matrix, and its relationships with osteichthyan skeletal tissues, remain scarce. Here, based on specific combinations of expression patterns of the Col1a1, Col1a2, and Col2a1 fibrillar collagen genes, we compare the molecular footprint of endoskeletal elements from the chondrichthyan Scyliorhinus canicula and the tetrapod Xenopus tropicalis. We find that, depending on the anatomical location, Scyliorhinus skeletal calcification is associated to cell types expressing different subsets of fibrillar collagen genes, such as high levels of Col1a1 and Col1a2 in the neural arches, high levels of Col2a1 in the tesserae, or associated to a drastic Col2a1 downregulation in the centrum. We detect low Col2a1 levels in Xenopus osteoblasts, thereby revealing that the osteoblastic expression of this gene was significantly reduced in the tetrapod lineage. Finally, we uncover a striking parallel, from a molecular and histological perspective, between the vertebral cartilage calcification of both species and discuss the evolutionary origin of endochondral ossification.
The effect of the Convention on International Trade in Endangered Species on scientific collections

The Convention on International Trade in Endangered Species (CITES) was conceived in the spirit of cooperation, with the aim of ensuring that the international trade in wild animals and plants, including all parts and derivatives, did not threaten their survival. However, concerns have been raised by scientists that CITES hinders the cross-border movement of scientific specimens. To our knowledge, no empirical analysis has been undertaken to demonstrate the existence of this effect. We test for a CITES effect on the collection record of orchids from Brazil and Costa Rica using the collection records of bromeliads, which are not covered by CITES, as a control. Highly significant effects are found in both countries.
Building English-Vietnamese Named Entity Corpus with Aligned Bilingual News Articles

Named entity recognition aims to classify words in a document into pre-defined target entity classes. It is now considered to be fundamental for many natural language processing tasks such as information retrieval, machine translation, information extraction and question answering. This paper presents a workflow to build an English-Vietnamese named entity corpus from an aligned bilingual corpus. The workflow is based on a state of the art named entity recognition tool to identify English named entities and map them into Vietnamese text. The paper also presents a detailed discussion about several mapping errors and differences between English and Vietnamese sentences that affect this task.
A Novel Resource Scheduling Algorithm for Computational Grid

Grid is an emerging technology for enabling resource sharing and coordinated problem solving in dynamic multiinstitutional heterogeneous virtual organizations. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed. A suitable and efficient scheduling algorithm is needed to schedule user tasks to heterogeneous resources distributed in the grid. We propose a genetic algorithm to solve the scheduling problems in computational grid. The proposed algorithm uses the optimal searching technique of genetic approach and takes different computing capabilities of nodes into consideration. The simulation result shows that proposed algorithm yields better performance when compared with other traditional heuristic approaches. General Terms Algorithm, Distributed Computing.
Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning

The learning of domain-invariant representations in the context of domain adaptation with neural networks is considered. We propose a new regularization method that minimizes the discrepancy between domain-specific latent feature representations directly in the hidden activation space. Although some standard distribution matching approaches exist that can be interpreted as the matching of weighted sums of moments, e.g. Maximum Mean Discrepancy (MMD), an explicit order-wise matching of higher order moments has not been considered before. We propose to match the higher order central moments of probability distributions by means of order-wise moment differences. Our model does not require computationally expensive distance and kernel matrix computations. We utilize the equivalent representation of probability distributions by moment sequences to define a new distance function, called Central Moment Discrepancy (CMD). We prove that CMD is a metric on the set of probability distributions on a compact interval. We further prove that convergence of probability distributions on compact intervals w.r. t. the new metric implies convergence in distribution of the respective random variables. We test our approach on two different benchmark data sets for object recognition (Office) and sentiment analysis of product reviews (Amazon reviews). CMD achieves a new state-of-the-art performance on most domain adaptation tasks of Office and outperforms networks trained with MMD, Variational Fair Autoencoders and Domain Adversarial Neural Networks on Amazon reviews. In addition, a post-hoc parameter sensitivity analysis shows that the new approach is stable w.r. t. parameter changes in a certain interval. The source code of the experiments is publicly available.
Change in cell shape is required for matrix metalloproteinase‐induced epithelial‐mesenchymal transition of mammary epithelial cells

Cell morphology dictates response to a wide variety of stimuli, controlling cell metabolism, differentiation, proliferation, and death. Epithelial‐mesenchymal transition (EMT) is a developmental process in which epithelial cells acquire migratory characteristics, and in the process convert from a “cuboidal” epithelial structure into an elongated mesenchymal shape. We had shown previously that matrix metalloproteinase‐3 (MMP3) can stimulate EMT of cultured mouse mammary epithelial cells through a process that involves increased expression of Rac1b, a protein that stimulates alterations in cytoskeletal structure. We show here that cells treated with MMP‐3 or induced to express Rac1b spread to cover a larger surface, and that this induction of cell spreading is a requirement of MMP‐3/Rac1b‐induced EMT. We find that limiting cell spreading, either by increasing cell density or by culturing cells on precisely defined micropatterned substrata, blocks expression of characteristic markers of EMT in cells treated with MMP‐3. These effects are not caused by general disruptions in cell signaling pathways, as TGF‐β‐induced EMT is not affected by similar limitations on cell spreading. Our data reveal a previously unanticipated cell shape‐dependent mechanism that controls this key phenotypic alteration and provide insight into the distinct mechanisms activated by different EMT‐inducing agents. J. Cell. Biochem. 105: 25–33, 2008. © 2008 Wiley‐Liss, Inc.