Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of antecedent pruning in fuzzy classification systems

Fuzzy classification rules are widely considered to be a well-suited representation of classification knowledge, as they allow readable and interpretable rule bases. This paper discusses the shapes of the resulting classification borders under consideration of different types of fuzzy sets, rule bases and t-norms, and thus which class distributions can be represented by such classification systems. We focus on discussing how antecedent pruning influences the classification behaviour of fuzzy classifiers. Our main goal is to give the potential user an insight into the classification behaviour of fuzzy classifiers. For this, 2D and 3D visualisations are mainly used to illustrate the cluster shapes and the borders between distinct classes.
Visceral Leishmaniasis and HIV Coinfection in the Mediterranean Region

Visceral leishmaniasis is hypoendemic in Mediterranean countries, where it is caused by the flagellate protozoan Leishmania infantum. VL cases in this area account for 5%–6% of the global burden. Cases of Leishmania/HIV coinfection have been reported in the Mediterranean region, mainly in France, Italy, Portugal, and Spain. Since highly active antiretroviral therapy was introduced in 1997, a marked decrease in the number of coinfected cases in this region has been reported. The development of new diagnostic methods to accurately identify level of parasitemia and the risk of relapse is one of the main challenges in improving the treatment of coinfected patients. Clinical trials in the Mediterranean region are needed to determine the most adequate therapeutic options for Leishmania/HIV patients as well as the indications and regimes for secondary prophylaxis. This article reviews the epidemiological, diagnostic, clinical, and therapeutic aspects of Leishmania/HIV coinfection in the Mediterranean region.
Therapeutic outcomes of transplantation of amniotic fluid-derived stem cells in experimental ischemic stroke

Accumulating preclinical evidence suggests the use of amnion as a source of stem cells for investigations of basic science concepts related to developmental cell biology, but also for stem cells’ therapeutic applications in treating human disorders. We previously reported isolation of viable rat amniotic fluid-derived stem (AFS) cells. Subsequently, we recently reported the therapeutic benefits of intravenous transplantation of AFS cells in a rodent model of ischemic stroke. Parallel lines of investigations have provided safety and efficacy of stem cell therapy for treating stroke and other neurological disorders. This review article highlights the need for investigations of mechanisms underlying AFS cells’ therapeutic benefits and discusses lab-to-clinic translational gating items in an effort to optimize the clinical application of the cell transplantation for stroke.
RISC assessment: A high-level language experiment

We present the result of an informal experiment comparing the performance of one Reduced Instruction Set Computer, RISC I, to five traditional computers, VAX-11/780, PDP-11/70, BBN C/70, MC68000, and Z8000, in a high-level language environment. Measuring either absolute performance or the penalty for using high-level languages, the best computer is RISC I.
To FUSE or Not to FUSE: Performance of User-Space File Systems

Traditionally, file systems were implemented as part of OS kernels. However, as complexity of file systems grew, many new file systems began being developed in user space. Nowadays, user-space file systems are often used to prototype and evaluate new approaches to file system design. Low performance is considered the main disadvantage of user-space file systems but the extent of this problem has never been explored systematically. As a result, the topic of user-space file systems remains rather controversial: while some consider user-space file systems a toy not to be used in production, others develop full-fledged production file systems in user space. In this paper we analyze the design and implementation of the most widely known user-space file system framework--FUSE--and characterize its performance for a wide range of workloads. We instrumented FUSE to extract useful statistics and traces, which helped us analyze its performance bottlenecks and present our analysis results. Our experiments indicate that depending on the workload and hardware used, performance degradation caused by FUSE can be completely imperceptible or as high as -83% even when optimized; and relative CPU utilization can increase by 31%.
Effective Text Classification by a Supervised Feature Selection Approach

The high dimensionality of data is a great challenge for effective text classification. Each document in a document corpus contains many irrelevant and noisy information which eventually reduces the efficiency of text classification. Automatic feature selection methods are extremely important to handle the high dimensionality of data for effective text classification. Feature selection in text classification focuses on identifying relevant information without affecting the accuracy of the classifier. Several feature selection methods have been proposed to improve the classification accuracy by reducing the original feature space. To improve the performance of text classification a new supervised feature selection approach has been proposed which develops a similarity between a term and a class. In this way every term will generate a score based on their similarity with all the classes and then all the terms will be ranked accordingly. The experimental results are presented on several TREC and Reuter data sets using knn classifier. The performances of the classifiers are compared using precision, recall, f-measure and classification accuracy. The proposed term selection approach is compared with document frequency thresholding, information gain, mutual information and chi square statistic. The empirical studies have shown that the proposed method performs significantly better than the other methods.
Fossil Evidence on Origin of the Mammalian Brain

Evidence from two early fossils suggests that brain enlargement and specialization proceeded in three pulses. Many hypotheses have been postulated regarding the early evolution of the mammalian brain. Here, x-ray tomography of the Early Jurassic mammaliaforms Morganucodon and Hadrocodium sheds light on this history. We found that relative brain size expanded to mammalian levels, with enlarged olfactory bulbs, neocortex, olfactory (pyriform) cortex, and cerebellum, in two evolutionary pulses. The initial pulse was probably driven by increased resolution in olfaction and improvements in tactile sensitivity (from body hair) and neuromuscular coordination. A second pulse of olfactory enhancement then enlarged the brain to mammalian levels. The origin of crown Mammalia saw a third pulse of olfactory enhancement, with ossified ethmoid turbinals supporting an expansive olfactory epithelium in the nasal cavity, allowing full expression of a huge odorant receptor genome.
Architecture and performance evaluation of a hybrid intrusion detection system for IP telephony

Convergence in networks and applications enables carrying voice, video, and other data on the same IP-based infrastructure, and provides various services related to these kinds of data in a unified way. Such a scheme benefits businesses substantially considering the lesser cost of building and managing a single network infrastructure instead of two separate ones. However, the same scheme poses serious threats to security solutions in general, and intrusion detection systems (IDSs) in particular. Inherited flaws and vulnerabilities in TCP/IP protocols at lower layers make voice susceptible to risks it has never been subjected to before in public switched telephone networks (PSTNs). Signaling and data delivery protocols at application layer have their weaknesses too which make breaching of confidentiality and integrity relatively easy. In this paper, we present the design and implementation of a hybrid, host-based intrusion detection system that is suitable for converged environments. Our design is unique in terms of providing an efficient combination of specification-based and signature-based detection techniques. Specification-based and signature-based detection modules provide solid awareness of the semantics as well as the syntax of the protocols involved. Our solution goes beyond addressing the issues of application layer protocols to address transport and network layer protocols as well in a unified way. The feasibility of our design is proven through the excellent detection accuracy and reasonable performance evaluation figures we get from our experiment. Copyright © 2010 John Wiley & Sons, Ltd.
Biomarkers for Screening, Diagnosis, and Monitoring of Ovarian Cancer

Serum tumor markers have a major role in the screening, diagnosis, and monitoring of most of the gynecologic cancers. Ovarian cancer is one of the deadliest of the group because it is so frequently asymptomatic until it has advanced to an untreatable stage. Even serum cancer antigen-125 (CA-125), clinically one of the most reliable serum markers for ovarian cancer, is elevated in only half of early-stage still-treatable tumors. Because of the very low prevalence of ovarian cancer in the general population, at present, there is no cost-effective imaging or simple microscopic screening test for ovarian cancer as there is for breast and cervical cancers. However, recent proteomics and nucleic acid–based analyses have shown great promise for the discovery of new and more useful serum biomarkers, which cumulatively might provide such a screening tool. In this review, we will discuss both the currently used serum tumor markers for screening, diagnosis, monitoring of ovarian cancer, and the novel biomarkers that are now under investigation and validation. Cancer Epidemiol Biomarkers Prev; 21(11); 1902–12. ©2012 AACR.
Web Services at the European Bioinformatics Institute

We present a new version of the European Bioinformatics Institute Web Services, a complete suite of SOAP-based web tools for structural and functional analysis, with new and improved applications. New functionality has been added to most of the services already available, and an improved version of the underlying framework has allowed us to include more applications. Information on the EBI Web Services, tutorials and clients can be found at http://www.ebi. ac.uk/Tools/webservices.
Remote Sensing of Human Body by Stepped-Frequency Continuous-Wave

Remote sensing of human body is very useful in many services. The micro-Doppler characteristic of human body can be detected to identify life target. In this paper, another new theoretical method to obtain the range and Doppler frequency of human body is proposed in which multiple periods stepped- frequency continuous-wave signal and moving target indication (MTI) filter are adopted. The simulation results illustrate the validity of this method and present the detection of the target range and the vibration frequency of heart beating and breathing.
A Developmental Roadmap for Learning by Imitation in Robots

In this paper, we present a strategy whereby a robot acquires the capability to learn by imitation following a developmental pathway consisting on three levels: 1) sensory-motor coordination; 2) world interaction; and 3) imitation. With these stages, the system is able to learn tasks by imitating human demonstrators. We describe results of the different developmental stages, involving perceptual and motor skills, implemented in our humanoid robot, Baltazar. At each stage, the system's attention is drawn toward different entities: its own body and, later on, objects and people. Our main contributions are the general architecture and the implementation of all the necessary modules until imitation capabilities are eventually acquired by the robot. Also, several other contributions are made at each level: learning of sensory-motor maps for redundant robots, a novel method for learning how to grasp objects, and a framework for learning task description from observation for program-level imitation. Finally, vision is used extensively as the sole sensing modality (sometimes in a simplified setting) avoiding the need for special data-acquisition hardware
Spatial distance dependent Chinese restaurant processes for image segmentation

The distance dependent Chinese restaurant process (ddCRP) was recently introduced to accommodate random partitions of non-exchangeable data [1]. The dd-CRP clusters data in a biased way: each data point is more likely to be clustered with other data that are near it in an external sense. This paper examines the dd-CRP in a spatial setting with the goal of natural image segmentation. We explore the biases of the spatial ddCRP model and propose a novel hierarchical extension better suited for producing "human-like" segmentations. We then study the sensitivity of the models to various distance and appearance hyperparameters, and provide the first rigorous comparison of nonparametric Bayesian models in the image segmentation domain. On unsupervised image segmentation, we demonstrate that similar performance to existing nonparametric Bayesian models is possible with substantially simpler models and algorithms.
Linked data for humanities research — The SPQR experiment

Ancient texts represent a primary source for research in the classics. A substantial body of digital material has evolved enriching these texts. Unfortunately these data are often distributed across myriad locations, stored in diverse and incompatible formats and are either not available online or are made available only in isolation. This paper describes an investigation into using linked data principles and technologies to build bridges between these islands of data to deliver an integrated data landscape through which researchers can explore and so seek to understand this data. The evaluation revealed that researchers were of the opinion that the linked data representation, and its visualisation as graphs, offers an intuitive and usable means of exploring and understanding the data, exceeding the capabilities offered by current online portals to classics data.
An Artificial Channel Experiment for Purifying Drainage Water Containing Arsenic by Using Eleocharis acicularis

This paper reports the results of an artificial channel experiment in which water containing arsenic was purified by using Eleocharis acicularis. The experiment was conducted to investigate the feasibility of phytoremediation by Eleocharis acicularis in civil engineering projects. In the experiment, 15 m2 of Eleocharis acicularis mats were laid in an artificial channel. Three sessions of artificial flow were implemented by leading 100.0 L of river water containing 0.234 mg/L of arsenic into the channel each time. The arsenic concentration of the leachate from the channel was analyzed. As the results of experiment, the arsenic concentrations of the leachate for the three sessions were 0.045 mg/L, 0.133 mg/L, and 0.249 mg/L. This shows that the arsenic concentration decreased during the first two sessions, whose flow totaled 200 L. The arsenic concentrations in the Eleocharis acicularis were 0.87 mg/kg, 1.01 mg/kg, and 4.16 mg/kg, which show that the plant absorbs arsenic. Moreover, it was found that the amount of sample water was reduced through evapotranspiration from the plant and the artificial channel.
Renal denervation in the management of resistant hypertension: current evidence and perspectives

Purpose of reviewCatheter-based renal denervation has emerged as a novel treatment modality for resistant hypertension. This review summarizes the current evidence on this procedure in treatment of resistant hypertension, limitations of available evidence and questions to be answered. Recent findingsThe SYMPLICITY studies showed that renal denervation is feasible in treating resistant hypertension, but failed to provide conclusive evidence on the size and durability of the antihypertensive, renal and sympatholytic effects, as well as the long-term safety. The definition of resistant hypertension was loose in the SYMPLICITY studies and the management of resistant hypertension was suboptimal. Future studies should have a randomized design and enroll truly resistant hypertension patients by excluding secondary hypertension, white-coat hypertension and nonadherent patients. Questions to be addressed by the ongoing and future trials include the long-term efficacy and safety of this procedure, identification of responders and uncovering of the underlying mechanisms. SummaryOnly well-designed, randomized clinical trials addressing the limitations of the SYMPLICITY studies will be able to demonstrate whether renal denervation is an efficacious treatment modality in resistant hypertension and in which patients. For now, renal denervation remains an experimental procedure and should only be offered to truly resistant hypertensive patients in a research context after careful selection.
Incidence of acute rheumatic fever in the world: a systematic review of population-based studies

Background: There is no systematic overview of prospective studies of incidence of acute rheumatic fever (ARF) in the world. Aim: To summarise all population-based studies of the incidence of ARF world wide. Method: A systematic review of prospective population-based studies of the overall mean and annual specific incidence of the first episode of ARF was carried out. Results: A systematic literature search identified 10 eligible studies from 10 countries on all continents, except Africa. The overall mean incidence rate of first attack of ARF was 5–51/100 000 population (mean 19/100 000; 95% CI 9 to 30/100 000). A low incidence rate of ⩽10/100 000 per year was found in America and Western Europe, while a higher incidence (>10/100 000) was documented in Eastern Europe, Middle East (highest), Asia and Australasia. Studies with longitudinal data displayed a falling incidence rate over time. Conclusion: Despite an apparent fall in incidence over time, ARF incidence rates remain relatively high in non-Western countries. No information is available for Africa.
Parallel Implementations of the Particle Filter Algorithm for Android Mobile Devices

The advent of emergent System-on-Chip (SoCs) and multiprocessor System-on-Chip (MPSocs) opens a new era on the small mobile devices (Smartphones, Tablets, ) in terms of computing capabilities and applications to be addressed. Given the ability of these devices to interact with the real world through the camera, is mandatory the development of efficient algorithms related to image processing and computer vision. We present a parallel implementation on mobile Android devices of the Particle Filter algorithm. We developed three different version of this algorithm. A Java sequential implementation and two Render script parallel versions, an ad-hoc implementation and a Paralldroid generated implementation. The results obtained by the parallel versions present an important speedup and a high accurate with a high processing rate of frame per seconds.
Semantic Segmentation of 3 D Particle Interaction Data Using Fully Convolutional DenseNet

Semantic segmentation has found applications in fields where it is necessary to localize an abstract feature by labeling each pixel in an image as belonging to one of a predefined set of classes. It most often employs a deep convolutional neural network architecture consisting of a downsampling path, which extracts high-level features from the image, and an upsampling path, which retrieves the resolution of the original image for pixel-wise classification. In this paper, we present the results of applying a semantic segmentation network to the analysis of particle interaction images derived from a novel detector technology, called the Liquid Argon Time Projection Chamber (LArTPC). Whereas it boasts of high neutrino detection efficiency and low background, the analysis of LArTPC-derived images has posed a challenge. In particular, removing cosmic ray-induced particles and reconstructing neutrino interactions from the images have required a combination of many algorithm-based frameworks. Deep neural nets, on the other hand, can provide an efficient end-to-end solution. We train a fully convolutional densenet (FC-DenseNet) [1] to perform pattern recognition in 3D – specifically, the pixel-wise classification of showers and tracks – on a simulation dataset. Our work will inform the analysis of future LArTPC experiments such as the Deep Underground Neutrino Experiment (DUNE).
Toll-like receptors in systemic lupus erythematosus: potential for personalized treatment

Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by the loss of tolerance to self-nuclear antigens. The symptoms of SLE, progression of pathology and the array of autoantibodies present in the serum differ significantly from patient to patient, which calls for a personalized approach to treatment. SLE is polygenic and strongly influenced by gender, ethnicity, and environmental factors. Data from genome-wide association studies suggests that polymorphisms in as many as 100 genes contribute to SLE susceptibility. Recent research has focused on genes associated with Toll-like receptors (TLRs), type I interferons, immune regulation pathways, and immune-complex clearance. TLR7 and TLR9 have been extensively studied using lupus-prone mouse models. In multiple systems overexpression of TLR7 drives disease progression but interestingly, a loss of TLR9 results in an almost identical phenotype. While TLR7 overexpression has been linked to human SLE, the possible role of TLR9 in human disease remains elusive. In the present review, we focus on TLR polymorphisms and TLR expression in SLE patients and discuss their potential as biomarkers for individualized treatment.
How to Compress (Reusable) Garbled Circuits

A fundamental question about (reusable) circuit garbling schemes is: how small can the garbled circuit be? Our main result is a reusable garbling scheme which produces garbled circuits that are the same size as the original circuit plus an additive poly(λ, d) bits, where λ is the security parameter and d is the circuit depth. Save the additive poly(λ, d) factor, this is the best one could hope for. In contrast, all previous constructions of even single-use garbled circuits incurred a multiplicative poly(λ) blowup. Our techniques result in constructions of attribute-based and (single key secure) functional encryption schemes where the secret key of a depth d circuit C consists of C itself, plus poly(λ, d) additional bits. All of these constructions are based on the subexponential hardness of the learning with errors problem. We also study the dual question of how short the garbled inputs can be, relative to the original input. We demonstrate a (different) reusable circuit garbling scheme, based on multilinear maps, where the size of the garbled input is the same as that of the original input, plus a poly(λ, d) factor. Similar to the above, this also results in attribute-based and (single key secure) functional encryption schemes where the size of the ciphertext encrypting an input x is the same as that of x, plus poly(λ, d) additional bits. ∗IBM Research. Email: cbgentry@us.ibm. com. †University of Toronto. Email: sgorbunov@cs.toronto. edu. This work was partially done while visiting IBM T. J. Watson Research Center. Supported by Alexander Graham Bell Canada Graduate Scholarship (CGSD3). ‡IBM Research. Email: shaih@alum.mit. edu. §MIT and University of Toronto. Email: vinodv@csail.mit. edu. Supported by an NSERC Discovery Grant, DARPA Grant number FA8750-11-2-0225, a Connaught New Researcher Award, an Alfred P. Sloan Research Fellowship, and a Steven and Renee Finn Career Development Chair from MIT. ¶University of Toronto. Email: dhinakaran5@cs.toronto. edu.