Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Organized Stigmergic Document Maps: Environment as a Mechanism for Context Learning

Social insect societies and more specifically ant colonies, are distributed systems that, in spite of the simplicity of their individuals, present a highly structured social organization. As a result of this organization, ant colonies can accomplish complex tasks that in some cases exceed the individual capabilities of a single ant. The study of ant colonies behavior and of their self-organizing capabilities is of interest to knowledge retrieval/management and decision support systems sciences, because it provides models of distributed adaptive organization which are useful to solve difficult optimization, classification, and distributed control problems, among others. In the present work we overview some models derived from the observation of real ants, emphasizing the role played by stigmergy as distributed communication paradigm, and we present a novel strategy to tackle unsupervised clustering as well as data retrieval problems. The present ant clustering system (ACLUSTER) avoids not only short-term memory based strategies, as well as the use of several artificial ant types (using different speeds), present in some recent approaches. Moreover and according to our knowledge, this is also the first application of ant systems into textual document clustering. KEYWORDS: Swarm Intelligence, Ant Systems, Unsupervised Clustering, Data Retrieval, Data Mining, Distributed Computing, Document Maps, Textual Document Clustering.
Screening Reliable Reference Genes for RT-qPCR Analysis of Gene Expression in Moringa oleifera

Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associated with important agronomical traits. Here, we screened reliable reference genes for accurately quantifying the expression of target genes using the technique of real-time quantitative polymerase chain reaction (RT-qPCR) in M. oleifera. Eighteen candidate reference genes were selected from a transcriptome database, and their expression stabilities were examined in 90 samples collected from the pods in different developmental stages, various tissues, and the roots and leaves under different conditions (low or high temperature, sodium chloride (NaCl)- or polyethyleneglycol (PEG)- simulated water stress). Analyses with geNorm, NormFinder and BestKeeper algorithms revealed that the reliable reference genes differed across sample designs and that ribosomal protein L1 (RPL1) and acyl carrier protein 2 (ACP2) were the most suitable reference genes in all tested samples. The experiment results demonstrated the significance of using the properly validated reference genes and suggested the use of more than one reference gene to achieve reliable expression profiles. In addition, we applied three isotypes of the superoxide dismutase (SOD) gene that are associated with plant adaptation to abiotic stress to confirm the efficacy of the validated reference genes under NaCl and PEG water stresses. Our results provide a valuable reference for future studies on identifying important functional genes from their transcriptional expressions via RT-qPCR technique in M. oleifera.
SZE Signals in Cluster Models

The upcoming generation of SZE surveys will shed fresh light onto the study of clusters. What will this new observational window reveal about cluster properties? What can we learn from combining X-ray, SZE, and optical observations? How do variations in the gas entropy profile, dark matter concentration, accretion pressure, and intracluster medium (ICM) mass fraction affect SZE observables? We investigate the signature of these important cluster parameters with an analytic model of the ICM. Given the current uncertainties in ICM physics, our approach is to span the range of plausible models motivated by observations and a small set of assumptions. We find a tight relation between the central Compton parameter and the X-ray luminosity outside the cluster core, suggesting that these observables carry the same information about the ICM. The total SZE luminosity is proportional to the thermal energy of the gas, and is a surprisingly robust indicator of cluster mass: $L_{SZ} \propto f_{ICM} M^{5/3}$. We show that a combination of $L_{SZ}$ and the half-luminosity radius $r_{SZ}$ provides a measure of the potential energy of the cluster gas, and thus we can deduce the total energy content of the ICM. We caution that any systematic variation of the ICM mass fraction will distort the expected $L_{SZ} - M$ calibration to be used to study the evolution of cluster number density, and propose a technique using kSZ to constrain $f_{ICM}(M,z)$.
A comparative assessment of ant colony optimization algorithms for the minimum weight vertex cover problem

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to the Minimum Weight Vertex Covering Problem in different problem cases and shown that Elitist Ant System and MinMax Ant System give better solutions for larger test cases while run-times for all algorithms were similar.
Excitatory neuronal connectivity in the barrel cortex

Neocortical areas are believed to be organized into vertical modules, the cortical columns, and the horizontal layers 1–6. In the somatosensory barrel cortex these columns are defined by the readily discernible barrel structure in layer 4. Information processing in the neocortex occurs along vertical and horizontal axes, thereby linking individual barrel-related columns via axons running through the different cortical layers of the barrel cortex. Long-range signaling occurs within the neocortical layers but also through axons projecting through the white matter to other neocortical areas and subcortical brain regions. Because of the ease of identification of barrel-related columns, the rodent barrel cortex has become a prototypical system to study the interactions between different neuronal connections within a sensory cortical area and between this area and other cortical as well subcortical regions. Such interactions will be discussed specifically for the feed-forward and feedback loops between the somatosensory and the somatomotor cortices as well as the different thalamic nuclei. In addition, recent advances concerning the morphological characteristics of excitatory neurons and their impact on the synaptic connectivity patterns and signaling properties of neuronal microcircuits in the whisker-related somatosensory cortex will be reviewed. In this context, their relationship between the structural properties of barrel-related columns and their function as a module in vertical synaptic signaling in the whisker-related cortical areas will be discussed.
Cleaning Data with Bayesian Methods

Data in many domains suffers corrupting processes. Our goal in this paper is to clean such data – i.e. reverse the effects of these corrupting processes. In part, we seek to produce data which supports the creation of better learners, but primarily, we want to produce data faithful to the “untampered, original” set. Previous techniques have attempted to use learners to predict problems with class values in data sets. These techniques have now been applied not only to detect but also to correct errors in data. However, these techniques suffer several problems: they can only actually correct noise in the class attribute, they do not fully leverage dependencies among attributes, and they are inappropriate for data sets with no distinguished class attribute. More recent techniques have looked at characterizing errors in non-class attributes. We use Bayesian techniques to take advantage of dependencies between attributes in a principled manner and to exploit expert knowledge of the relationships among the attributes. Our technique models the domain and noise generation process, rates its confidence that each instance is noisy (or asserts that the instance is clean), and suggests incremental corrections to nodes which appear to be corrupted.
Robust Camera Calibration using Inaccurate Targets

Accurate intrinsic camera calibration is essential to any computer vision task that involves image based measurements. Given its crucial role with respect to precision, a large number of approaches have been proposed over the last decades. Despite this rich literature, steady advancements in imaging hardware regularly push forward the need for even more accurate techniques. Some authors suggest generalizations of the camera model itself, others propose novel designs for calibration targets or different optimization schemas. In this paper we take a completely different route by directly addressing one of the most overlooked problems in practical calibration scenarios. Specifically, we drop the assumption that the target is known with enough precision and we adjust it in an iterative way as part of the whole process. This is in fact the case with the typical target used in most of the calibration literature, which is usually printed on paper and stitched on a flat surface. In the experimental section we show that even with such a cheaply crafted target it is possible to obtain a very accurate camera calibration that outperforms those obtained with well-known standard techniques.
Epidemiology and Risk Factors of Tooth Loss among Iranian Adults: Findings from a Large Community-Based Study

Objectives. To investigate the prevalence of tooth loss and different prosthetic rehabilitations among Iranian adults, as well as the potential determinants of tooth loss. Methods. In a cross-sectional community-based study conducted among 8094 Iranian adults living in Isfahan province, a self-administered questionnaire was used to assess epidemiologic features of tooth loss. Results. Thirty-two percent of subjects had all their teeth, 58.6% had lost less than 6, and 7.2% of participants had lost more than 6 teeth. One hundred and sixty-nine individuals (2.2%) were edentulous. Among participants, 2.3% had single jaw removable partial denture, 3.6% had complete removable denture in both jaws, and 4.6% had fixed prosthesis. Others reported no prosthetic rehabilitation (89.5%). In the age subgroup analysis (≤35 and >35 years old) tooth loss was more prevalent among men than women (OR = 2.8 and 1.9, resp., P < 0.01). Also, in both age groups, current and former smokers had higher levels of tooth loss than nonsmokers (P < 0.001 and P < 0.05, resp.). In addition, tooth loss was positively related to metabolic abnormality for age group >35 years (adjusted OR = 1.29, P < 0.01). Conclusions. Tooth loss is highly prevalent in Iranian adult population. Community programs promoting oral health for prevention of tooth loss should be considered taking into account its major determinants including lower educational level, male gender, smoking, and metabolic abnormality.
Mitochondrial DNA analysis of eneolithic trypillians from Ukraine reveals neolithic farming genetic roots

The agricultural revolution in Eastern Europe began in the Eneolithic with the Cucuteni-Trypillia culture complex. In Ukraine, the Trypillian culture (TC) existed for over two millennia (ca. 5,400–2,700 BCE) and left a wealth of artifacts. Yet, their burial rituals remain a mystery and to date almost nothing is known about the genetic composition of the TC population. One of the very few TC sites where human remains can be found is a cave called Verteba in western Ukraine. This report presents four partial and four complete mitochondrial genomes from nine TC individuals uncovered in the cave. The results of this analysis, combined with the data from previous reports, indicate that the Trypillian population at Verteba carried, for the most part, a typical Neolithic farmer package of mitochondrial DNA (mtDNA) lineages traced to Anatolian farmers and Neolithic farming groups of central Europe. At the same time, the find of two specimens belonging to haplogroup U8b1 at Verteba can be viewed as a connection of TC with the Upper Paleolithic European populations. At the level of mtDNA haplogroup frequencies, the TC population from Verteba demonstrates a close genetic relationship with population groups of the Funnel Beaker/ Trichterbecker cultural complex from central and northern Europe (ca. 3,950–2,500 BCE).
Reliability of planar and FinFET SONOS devices for NAND flash applications - Field enhancement vs. barrier engineering

The reliability of sub-40nm SONOS NAND devices with various tunnel oxide thickness and FinFET structures are studied for future NAND Flash application. SONOS intrinsically has slow erase speed and high erase saturation for tunnel oxide ranging from 25 to 45 Å. Furthermore, the endurance degradation occurs very early at low P/E≪10, owing to the nature of electron de-trapping mechanism at tunnel oxide ≫ 20A. Thus planar SONOS is not suitable for NAND Flash applications. On the other hand, when SONOS is applied to FinFET structure, significantly faster erase speed is obtained, owing to the field enhancement effect. However, it is still hard to erase below the initial Vt. We conclude that barrier engineering, such as BE-SONOS is more efficient in providing faster erase speed at lower erase voltages without endurance degradation. We also estimated the large density (4Mb) array distribution of sub-40 nm SONOS and BE-SONOS devices, and found that the distribution width is quite insensitive to the tunnel oxide thickness. This suggests that for future scaled NAND devices the edge effect is more important in determining the P/E distribution than the tunnel oxide thickness variation.
A functional magnetic resonance imaging study of visuomotor processing in a virtual reality‐based paradigm: Rehabilitation Gaming System

The Rehabilitation Gaming System (RGS) has been designed as a flexible, virtual‐reality (VR)‐based device for rehabilitation of neurological patients. Recently, training of visuomotor processing with the RGS was shown to effectively improve arm function in acute and chronic stroke patients. It is assumed that the VR‐based training protocol related to RGS creates conditions that aid recovery by virtue of the human mirror neuron system. Here, we provide evidence for this assumption by identifying the brain areas involved in controlling the catching of approaching colored balls in the virtual environment of the RGS. We used functional magnetic resonance imaging of 18 right‐handed healthy subjects (24 ± 3 years) in both active and imagination conditions. We observed that the imagery of target catching was related to activation of frontal, parietal, temporal, cingulate and cerebellar regions. We interpret these activations in relation to object processing, attention, mirror mechanisms, and motor intention. Active catching followed an anticipatory mode, and resulted in significantly less activity in the motor control areas. Our results provide preliminary support for the hypothesis underlying RGS that this novel neurorehabilitation approach engages human mirror mechanisms that can be employed for visuomotor training.
Validity of instruction leaflets for parents to measure their child's weight and height at home: results obtained from a randomised controlled trial

Objectives To compare the validity of parent-reported height, weight and body mass index (BMI) values of children (aged 4–10 years), when measured at home by means of newly developed instruction leaflets in comparison with simple estimated parental reports. Design Randomised controlled trial with control and intervention group using simple randomisation. Setting Belgian children and their parents recruited via schools (multistage cluster sampling design). Participants 164 Belgian children (53% male; participation rate 62%). Intervention Parents completed a questionnaire including questions about the height and weight of their child. Parents in the intervention group received instruction leaflets to measure their child's weight and height. Classes were randomly allocated to the intervention and control groups. Nurses measured height and weight following standardised procedures up to 2 weeks after parental reports. Outcome measures Weight, height and BMI category of the child were derived from the index measurements and the parental reports. Results Mean parent-reported weight was slightly more underestimated in the intervention group than in the control group relative to the index weights. However, for all three parameters (weight, height and BMI), correlations between parental reports and nurse measurements were higher in the intervention group. Sensitivity for underweight and overweight/obesity was respectively, 75% and 60% in the intervention group, and 67% and 43% in the control group. Weighed κ for classifying children in the correct BMI category was 0.30 in the control group and was 0.51 in the intervention group. Conclusions Although mean parent-reported weight was slightly more underestimated in the intervention than in the control group, correlations were higher and there was considerably less misclassification into valid BMI categories for the intervention group. This pattern suggests that most of the parental deviations from the index measurements were probably due to random errors of measurement and that diagnostic measures could improve by encouraging parents to measure their children's weight and height at home by means of instruction leaflets.
Understanding overlay characteristics of a large-scale peer-to-peer IPTV system

This article presents results from our measurement and modeling efforts on the large-scale peer-to-peer (p2p) overlay graphs spanned by the PPLive system, the most popular and largest p2p IPTV (Internet Protocol Television) system today. Unlike other previous studies on PPLive, which focused on either network-centric or user-centric measurements of the system, our study is unique in (a) focusing on PPLive overlay-specific characteristics, and (b) being the first to derive mathematical models for its distributions of node degree, session length, and peer participation in simultaneous overlays. Our studies reveal characteristics of multimedia streaming p2p overlays that are markedly different from existing file-sharing p2p overlays. Specifically, we find that: (1) PPLive overlays are similar to random graphs in structure and thus more robust and resilient to the massive failure of nodes, (2) Average degree of a peer in the overlay is independent of the channel population size and the node degree distribution can be fitted by a piecewise function, (3) The availability correlation between PPLive peer pairs is bimodal, that is, some pairs have highly correlated availability, while others have no correlation, (4) Unlike p2p file-sharing peers, PPLive peers are impatient and session lengths (discretized, per channel) are typically geometrically distributed, (5) Channel population size is time-sensitive, self-repeated, event-dependent, and varies more than in p2p file-sharing networks, (6) Peering relationships are slightly locality-aware, and (7) Peer participation in simultaneous overlays follows a Zipf distribution. We believe that our findings can be used to understand current large-scale p2p streaming systems for future planning of resource usage, and to provide useful and practical hints for future design of large-scale p2p streaming systems.
A comparative analysis of the effects of instructional design factors on student success in e-learning: multiple-regression versus neural networks

This study explores the relationship between the student performance and instructional design. The research was conducted at the E-Learning School at a university in Turkey. A list of design factors that had potential influence on student success was created through a review of the literature and interviews with relevant experts. From this, the five most import design factors were chosen. The experts scored 25 university courses on the extent to which they demonstrated the chosen design factors. Multiple-regression and supervised artificial neural network (ANN) models were used to examine the relationship between student grade point averages and the scores on the five design factors. The results indicated that there is no statistical difference between the two models. Both models identified the use of examples and applications as the most influential factor. The ANN model provided more information and was used to predict the course-specific factor values required for a desired level of success. Keywords: e-learning; distance education; instructional design factors; multimedia systems; artificial neural networks DOI: 10.1080/09687760802649889
Effects of Selective Cyclooxygenase-2 Inhibitor NS-398 Pretreatment on the Rat Spinal Cord after Contusion Injury

Background : Secondary spinal cord injury (SCI) that follows an initial mechanical insult can exacerbate the overall damage, limit the restorative processes and eventually lead to an increased neurological deficit. We hypothesized that selective inhibition of cyclooxygenase-2 (COX-2) may decrease the delayed cell death, and so this will contribute to decreased level of the secondary injury. Methods : The dorsal surface of the cord at the T9 level was subjected to weight drop impact using a 10 g rod. To block COX-2 activation, a selective COX-2 inhibitor (NS-398) was administered (5 mg/kg, i.p.) 15 min prior to SCI. The COX-1, COX-2, Caspase-3 and PGE 2 expressions were measured by real time quantitative RT-PCR and fluorescence immunostaining. Results : Many activated caspase-3 positive cells were observed at 6 h and they increased until 72 h after SCI. The expression of COX-2 peaked at 6 h after SCI, while the COX-1 expression was unaffected. The principal cells that showed a COX-2 expression were the neurons and microglia. Pretreatment with NS-398 caused a significant decrease in the expression of prostaglandin E2 and activated caspase-3 positive cells after SCI. Conclusion : These data suggest that COX-2 is one of the main factors related with the pathologic deficits from secondary SCI.
Approximate Solution of the Multiple Watchman Routes Problem With Restricted Visibility Range

In this paper, a new self-organizing map (SOM) based adaptation procedure is proposed to address the multiple watchman route problem with the restricted visibility range in the polygonal domain W. A watchman route is represented by a ring of connected neuron weights that evolves in W, while obstacles are considered by approximation of the shortest path. The adaptation procedure considers a coverage of W by the ring in order to attract nodes toward uncovered parts of W. The proposed procedure is experimentally verified in a set of environments and several visibility ranges. Performance of the procedure is compared with the decoupled approach based on solutions of the art gallery problem and the consecutive traveling salesman problem. The experimental results show the suitability of the proposed procedure based on relatively simple supporting geometrical structures, enabling application of the SOM principles to watchman route problems in W.