Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and convergence analysis of distributed coevolutionary algorithms

A theoretical foundation is presented for modeling and convergence analysis of a class of distributed coevolutionary algorithms applied to optimization problems in which the variables are partitioned among p nodes. An evolutionary algorithm at each of the p nodes performs a local evolutionary search based on its own set of primary variables, and the secondary variable set at each node is clamped during this phase. An infrequent intercommunication between the nodes updates the secondary variables at each node. The local search and intercommunication phases alternate, resulting in a cooperative search by the p nodes. First, we specify a theoretical basis for a class of centralized evolutionary algorithms in terms of construction and evolution of sampling distributions over the feasible space. Next, this foundation is extended to develop a model for a class of distributed coevolutionary algorithms. Convergence and convergence rate analyses are pursued for basic classes of objective functions. Our theoretical investigation reveals that for certain unimodal and multimodal objectives, we can expect these algorithms to converge at a geometrical rate. The distributed coevolutionary algorithms are of most interest from the perspective of their performance advantage compared to centralized algorithms, when they execute in a network environment with significant local access and internode communication delays. The relative performance of these algorithms is therefore evaluated in a distributed environment with realistic parameters of network behavior.
Murine Typhus with Renal Involvement in Canary Islands, Spain

Murine typhus and “murine-thypus-like” disease are reemerging infectious diseases. In Canary Islands (Spain), a rather distinct clinical pattern characterized by higher incidence of complications, especially renal damage (including acute failure and urinalysis abnormalities), is apparent and highly suggestive. It could be related to different strains of Rickettsia typhi or other cross-reactive species.
Evaluation of the virtual mirror as a navigational aid for augmented reality driven minimally invasive procedures

The paper presents a user study investigating perceptual effects of a virtual mirror being used as a tangible interactive tool in a medical Augmented Reality scenario. In particular, we evaluated whether an additional perspective provided by the virtual mirror supports instrument guidance in terms of precision and straightness. 31 participants were asked to navigate an endoscopic instrument in a simulated minimally invasive port setting. Results show a significant higher precision of instrument guidance when a virtual mirror provides additional views of the target region.
Fast and Accurate Spatiotemporal Fusion Based Upon Extreme Learning Machine

Spatiotemporal fusion is important in providing high spatial resolution earth observations with a dense time series, and recently, learning-based fusion methods have been attracting broad interest. These algorithms project image patches onto a feature space with the enforcement of a simple mapping to predict the fine resolution patches from the corresponding coarse ones. However, the sophisticated projection, e.g., sparse representation, is always computationally complex and difficult to be implemented on large patches, which cannot grasp enough local structural information in the coarse patches. To address these issues, a novel spatiotemporal fusion method is proposed in this letter, using a powerful learning technique, i.e., extreme learning machine (ELM). Unlike traditional approaches, we devote to learning a mapping function on difference images directly, rather than the sophisticated feature representation followed by a simple mapping. Characterized by good generalization performance and fast speed, the ELM is employed to achieve accurate and fast fine patches prediction. The proposed algorithm is evaluated by five actual data sets of Landsat enhanced thematic mapper plus-moderate resolution imaging spectroradiometer acquisitions and experimental results show that our method obtains better fusion results while achieving much greater speed.
Association between XPF Polymorphisms and Cancer Risk: A Meta-Analysis

Background Xeroderma pigmentosum complementation group F (XPF or ERCC4) plays a key role in DNA repair that protects against genetic instability and carcinogenesis. A series of epidemiological studies have examined associations between XPF polymorphisms and cancer risk, but the findings remain inconclusive. Methodology/Principal Findings In this meta-analysis of 47,639 cancer cases and 51,915 controls, by searching three electronic databases (i.e., MEDLINE, EMBASE and CNKI), we summarized 43 case-control studies from 29 publications on four commonly studied polymorphisms of XPF (i.e., rs1800067, rs1799801, rs2020955 and rs744154), and we did not find statistical evidence of any significant association with overall cancer risk. However, in stratification analyses, we found a significant association of XPF-rs1799801 with a reduced cancer risk in Caucasian populations (4,845 cases and 5,556 controls; recessive model: OR = 0.87, 95% CI = 0.76–1.00, P = 0.049, P = 0.723 for heterogeneity test, I2 = 0). Further genotype-phenotype correlation analysis showed that the homozygous variant CC genotype carriers had higher XPF expression levels than that of the TT genotype carriers (Student’s t test for a recessive model: P = 0.046). No publication bias was found by using the funnel plot and Egger’s test. Conclusion This meta-analysis suggests a lack of statistical evidence for the association between the four XPF SNPs and overall risk of cancers. However, XPF-rs1799801 may be associated with cancer risk in Caucasian populations, which needs to be further validated in single large, well-designed prospective studies.
CD86 (B7-2) can function to drive MHC-restricted antigen-specific CTL responses in vivo.

Activation of T cells requires both TCR-specific ligation by direct contact with peptide Ag-MHC complexes and coligation of the B7 family of ligands through CD28/CTLA-4 on the T cell surface. We recently reported that coadministration of CD86 cDNA along with DNA encoding HIV-1 Ags i.m. dramatically increased Ag-specific CTL responses. We investigated whether the bone marrow-derived professional APCs or muscle cells were responsible for the enhancement of CTL responses following CD86 coadministration. Accordingly, we analyzed CTL induction in bone marrow chimeras. These chimeras are capable of generating functional viral-specific CTLs against vaccinia virus and therefore represent a useful model system to study APC/T cell function in vivo. In vaccinated chimeras, we observed that only CD86 + Ag + MHC class I results in 1) detectable CTLs following in vitro restimulation, 2) detectable direct CTLs, 3) enhanced IFN-gamma production in an Ag-specific manner, and 4) dramatic tissue invasion of T cells. These results support that CD86 plays a central role in CTL induction in vivo, enabling non-bone marrow-derived cells to prime CTLs, a property previously associated solely with bone marrow-derived APCs.
Practical Conditions for Well-behaved-ness of Anisotropic Voronoi Diagrams

Recently, simple conditions for well-behaved-ness of anisotropic Voronoi diagrams have been proposed. While these conditions ensure well-behaved-ness of two types of practical anisotropic Voronoi diagrams, as well as the geodesic-distance one, in any dimension, they are both prohibitively expensive to evaluate, and not well-suited for typical problems in approximation or optimization. We propose simple conditions that can be efficiently evaluated, and are better suited to practical problems of approximation and optimization. The practical utility of this analysis is enhanced by the fact that orphan-free anisotropic Voronoi diagrams have embedded triangulations as duals.
Optimization of Detection Time for Channel Efficiency in Cognitive Radio Systems

In cognitive radio (CR) systems, secondary users (SUs) have to detect the channel periodically during their data transmission to decide whether the channel is idle in order to avoid unacceptable interferences to primary users (PUs). The duration of the detection process in a cycle affects the channel efficiency of the SU. Also, the detection time needs to be adaptively adjusted due to path loss variations caused by movements of PUs and SUs. In this paper, we explore the issue on the detection time selection that aims at improving the channel efficiency. We formulate this issue as an optimization problem, but it is extremely difficult to get the explicit solution. A numerical optimization algorithm is proposed to obtain the numerical solution to the problem. Numerical results show that the highest channel efficiency can be achieved by the optimization of the detection time.
A Study of Secondary School EFL Teachers' Pedagogical Bclicfs and Classroom Practices

In order to understand the reality of the classroom and improve the teaching process, researching into teachers’ beliefs about their professional activities has been acknowledged in mainstream education in general and in language education in particular (Borg, 2006). This study investigated secondary school EFL teachers’ pedagogical beliefs and classroom practices. It specifically examined the instructional practices the teachers conducted in classrooms and the beliefs they hold about English teaching profession, English teaching and learning, and the contextual factors. The study used questionnaire, classroom observation, interviews of pre and post classroom observation, and lesson plan analysis for data collection. The findings revealed the teachers’ unrealistic interest and competence in their English teaching profession. That is, the teachers seemed to think that they were merely interested in English teaching profession and were competent for conducting classroom instructions effectively though the classroom observation data failed to confirm such professional interest and competence. The result also indicated the teachers’ shallow theoretical and practical conceptions of the communicative language teaching. In other words, the teachers did not seem to have clear ideas about the focus of the instruction, the roles of teachers and students, the nature of teaching materials, the type of classroom organization and management in employing communicative language teaching in their classrooms. Thus, the teachers’ classroom instructions revealed routine pattern of procedures (presentation, monitoring and discussion) that did not seem to reflect their mere pedagogical conception, communicative language teaching. Moreover, the teachers’ considered students’ limited language capacity and interest in learning the language as the major contextual factor affecting the teaching and learning process. Thus, it is recommended that the teachers need to have more theoretical and practical exposure of the English teaching profession and CLT mainly through reflective teaching and action research. %%%%ADDIS ABABA UNIVERSITY
Preparation of Nucleoside H-Phosphonoselenoate Monoesters Via the Phosphinate Approach

An efficient entry to nucleoside 3′-H-phosphonoselenoate monoesters via phosphinate intermediates was developed. It involves a reaction of suitably protected nucleosides with triethylammonium phosphinate in the presence of pivaloyl chloride, followed by selenization of the intermediate nucleoside phosphinates with triphenylphosphine selenide, to produce the corresponding nucleoside H-phosphonoselenoates in 86–92% yields.
Discovering event evolution graphs from newswires

In this paper, we propose an approach to automatically mine event evolution graphs from newswires on the Web. Event evolution graph is a directed graph in which the vertices and edges denote news events and the evolutions between events respectively, in a news affair. Our model utilizes the content similarity between events and incorporates temporal proximity and document distributional proximity as decaying functions. Our approach is effective in presenting the inside developments of news affairs along the timeline, which can facilitate users' information browsing tasks.
A Faster RCNN-Based Pedestrian Detection System

Pedestrian detection systems are receiving increasing attention in both industry and academia with the rapid development of autonomous automobiles which employ artificial intelligence. These systems must detect specific classes of objects such as pedestrians rather than generic objects. In this paper, we present a faster RCNN based pedestrian detection system which improves upon previous solutions. The proposed model takes arbitrary size images as inputs and generates bounding boxes and confidence scores for pedestrians. The system achieves good performance and is faster than the well known and frequently used methods in the literature.
GameTeen: New Tools for Evaluating and Training Emotional Regulation Strategies

The aim of this paper is to describe GameTeen, a novel instrument for the assessment and training of Emotional Regulation (ER) strategies in adolescent population. These new tools are based on the use of 3D serious games that can be played under different settings. The evolution of ER strategies will be monitored in two ways depending on the setting where the tool is presented. Firstly, in the laboratory, physiological signals and facial expressions of participants will be recorded. Secondly, in real life settings, ecological momentary assessment tools will be used to obtain answers from the subjects using their mobile phone. The goal is to obtain more attractive and reliable tools to evaluate and train ER strategies.
Routing, data gathering, and neighbor discovery in delay-tolerant wireless sensor networks

This paper investigates a class of mobile wireless sensor networks that are not connected most of the times. The characteristics of these networks is inherited from both delay tolerate networks (DTN) and wireless sensor networks. First, delay-tolerant wireless sensor networks (DTWSN) are introduced. Then, three main problems in the design space of these networks are discussed: Routing, data gathering, and neighbor discovery. An approach is proposed for deployment of DTWSNs based on the traditional opportunistic broadcast in delay tolerant networks with on-off periods. The delay and the throughput of the routing scheme were investigated in the DTN literature. However, the energy consumption was not studied thoroughly, which is focused here. Neighbor discovery in a sparse network could be a major source of energy consumption. Therefore, energy per contact measure is evaluated analytically based on the distribution of physical link duration. The results for 2D constant velocity model and random waypoint model are reported and the average PLD is suggested as an appropriate choice of beacon interval.
A Novel Analog Autocalibrating Phase-Voltage Converter for Signal Phase-Shifting Detection

In this study, we present a novel analog read-out circuit, operating a phase-voltage conversion, suitable for the detection of signal phase shifting for micro- and nano-sensor system applications. Its main characteristics are the following: good linearity in the considered phase-shift range, capability of phase sign detection, independence from input signal amplitudes, setting and zeroing of the offset, autocalibration, high sensitivity and resolution, and high accuracy and precision. For these reasons and, in particular, thanks to its simple internal topology, the developed circuit can be considered as a suitable analog interface for portable measurement systems. Experimental results, achieved through a laboratory breadboard and using sample signals, have confirmed, with respect to the other solutions reported in literature, better linearity, higher sensitivity (equal to about 37 mV/degree in the ±90° phase-shift range) and resolution (lower than 0.1° in the same phase-shift range) for both positive and negative phase variations. When a more reduced phase-shift range must be detected (i.e., for optical sensor applications), it is possible to set the circuit parameters to further increase sensitivity and resolution.
An adaptable patient-centric electronic health record system for personalized home care

The increasing ageing of population and the prevalence of chronic diseases push the adoption of home care processes that can delay or discontinue the access to hospitalization and specialized structures. To this end, ICT plays a crucial enabling role providing a growing ecosystem of diagnostic and monitoring devices, communication networks, and information management applications. As a part of this, advanced software architectures provide means for effective integration and management of clinical data produced by a variety of sources and accessed by a variety of actors involved in the care process. We describe the software architecture of an Electronic Health Record (EHR) system that exploits the Reflection architectural pattern to allow agile tailoring for the needs of different medical specialties. We then show how this adaptability can be further exploited to face a number of challenging requirements posed by the context of home care, including: patient-centric personalization of the record structure; user-adapted content presentation; automated support for compliance verification; systems medicine connection of clinical observations pertaining to different specialties; integration of users observations and data streams acquired from remote monitoring devices.
Computer vision techniques for background modelling in urban traffic monitoring

Jose Manuel Milla, Sergio Luis Toral, Manuel Vargas and Federico Barrero (2010). Computer Vision Techniques for Background Modeling in Urban Traffic Monitoring, Urban Transport and Hybrid Vehicles, Seref Soylu (Ed.), ISBN: 978-953-307-100-8, InTech, DOI: 10.5772/10179. Available from: http://www.intechopen. com/books/urban-transport-and-hybrid-vehicles/computer-vision-techniques-for-background-modeling-in-urban-traffic-monitoring
Stream-oriented FPGA computing in the Streams-C high level language

Stream oriented processing is an important methodology used in FPGA-based parallel processing. Characteristics of stream-oriented computing include high-data-rate flow of one or more data sources; fixed size, small stream payload (one byte to one word); compute-intensive operations, usually low precision fixed point, on the data stream; access to small local memories holding coefficients and other constants; and occasional synchronization between computational phases. We describe language constructs, compiler technology, and hardware/software libraries embodying the Streams-C system which has been developed to support stream-oriented computation on FPGA-based parallel computers. The language is implemented as a small set of library functions callable from a C language program. The Streams-C compiler synthesizes hardware circuits for multiple FPGAs as well as a multi-threaded software program for the control processor. Our system includes a functional simulation environment based on POSIX threads, allowing the programmer to simulate the collection of parallel processes and their communication at the functional level. Finally we present an application written both in Streams-C and hand-coded in VHDL. Compared to the hand-crafted design, the Streams-C-generated circuit takes 3x the area and runs at 1/2 the clock rate. In terms of time to market, the hand-done design took a month to develop by an experienced hardware developer. The Streams-C design rook a couple of days, for a productivity increase of 10x.
Family Quality of Life: Influence of Social Support, Gender and Parental Marital Status

This study examined the influence of gender, parental marital status and social support on family quality of life of college students. A total of 377 college students participated in this study with 106 male and 271 females. Family Quality of Life scale (FQOL) was used to measure three subscales, interaction, parenting and emotional well-being. ANOVA revealed that students with high social support scored higher in all subscales of family quality of life scale than those with low social support. The study also showed that students with married parents scored significantly higher in subscales of interaction, parenting, and emotional well-being than those from divorced parents. Gender difference showed that female students scored significantly higher than male students on interaction and parenting scales but there was no significant difference on emotional well-being scale for both genders.
Antithyroid Antibodies Are Implicated in Epileptogenesis of Adult Patients With Epilepsy

AbstractAntithyroid antibodies (Abs) are associated with epilepsy in steroid-responsive encephalopathy, but have been rarely studied in unselected epilepsy patients. This study aimed to characterize the prevalence and associated factors of antithyroid Abs and other auto-Abs in adult patients with epilepsy.Epilepsy patients without autoimmune disorders were surveyed for antinuclear antibody (ANA), anti-&bgr;2 glycoprotein 1 antibody (a&bgr;2GP1), anticardiolipin IgG Ab, antimicrosomal antibody (AMA), antithyroglobulin antibody (ATA), and thyroid function test.Of 319 patients, 75 (23.5%) were positive for at least 1 Ab. The most common Ab was anticardiolipin antibody (aCL) (30/319, 9.4%), followed by AMA (24/319, 7.5%), ANA (18/319, 5.6%), a&bgr;2GP1 (18/319, 6.5%), and ATA (6/319, 3.25%). Antimicrosomal Abs were significantly more frequent in patients who were female, older at disease onset, older at the time of study, and had unknown seizure etiology. The presence of aCL was significantly associated with more frequent seizures. Most patients with antithyroid Ab were female and had focal seizures with unknown etiology.The association of different auto-Abs with different factors suggests that they may have different roles in adult patients with epilepsy. Recurrent seizures and certain antiepileptic medications may cause the production of aCL. The role of antithyroid Abs in adult focal epilepsy with unknown cause, especially in females, warrants further evaluation because of the potential implications on treatment.
GeoCUTS: Geographic Clustering Using Travel Statistics

Web-based services often run experiments to improve their products. To carry out an effective experiment and evaluate the results appropriately, there must be a control group and at least one treatment group. Ideally all of these groups are disjoint, so that each user is given a specific treatment. Using geographical locations as units of experimentation is desirable because this does not require tracking individual users or browser cookies. With the popularity of mobile devices, a user may issue queries from multiple geographical locations. Hence, to be used as units of experimentation, geographical partitions should be chosen in a way that reduces transit between regions. The strategy of clustering users by region is common in advertising. Designated marketing areas (DMAs) are specifically designed for this purpose. However, DMAs are restricted to the US and their granularity is inflexible (there are around two hundred in total). Moreover, they are built based on population density - one DMA per metropolitan area - rather than mobile movement patterns. In this paper, we present GeoCUTS, an algorithm that forms geographical clusters to minimize movement between clusters while preserving rough balance in cluster size. We use a random sample of anonymized mobile user traffic to form a graph representing user movements, then construct a geographically coherent clustering of the graph. We propose a statistical framework to measure the effectiveness of clusterings and perform empirical evaluations showing that the performance of GeoCUTS is comparable to hand-crafted DMAs with respect to both novel and existing metrics. GeoCUTS offers a general and flexible framework for conducting geo-based experiments in any part of the world.