Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer of humoural immunity over two generations in urban pigeons

Maternal antibodies (MatAb) are known to provide passive protection early in life for young vertebrates but their effects on the development of offspring immune response across generations are still unknown. Here, we investigated the effects of antigen exposure (keyhole limpet haemocyanin, KLH) experienced by urban pigeon (Columba livia) females on the amount of antigen-specific antibodies (Abs) transferred into the egg yolk of their daughters and on the humoural immune response towards this same antigen in their grandchildren. We found that chicks from KLH-injected maternal grandmothers had a higher humoural response than chicks from sham-injected grandmothers. However, we did not detect a significant effect of female KLH exposure on the ability of their daughters to transmit anti-KLH Abs into their eggs. These results suggest that antigen exposure at one generation may shape the immune profile of offspring over two next generations, although the underlying mechanisms remain to be investigated.
An Efficient Global Optimization Approach to Multi Robot Path Exploration Problem Using Hybrid Genetic Algorithm

This paper presents a novel scheme for global path exploration to multi robots environment using hybrid implementation of evolutionary heuristic. This scheme is used to find an optimal path for each mobile robot to move in a static environment expressed by a weighted graph with nodes and links. The interesting part of this scheme is that the chromosome structure is designed to cluster the landmarks (nodes) in the environment. The rendezvous point for robots to meet at last is selected by using making centroid technique. We used a fixed length chromosome. Each robot has a starting point and a rendezvous point under the assumption that the robot passes each point in the cluster only once. Experimental results are presented to illustrate the performance of the proposed scheme. The scheme was tested on a set of different problems with encouraging results.
Elastic Places

The diversity and complexity of modern computing platforms makes the development of high-performance software challenging. Designing scalable software requires tuning for a large set of resources, including cores (parallelism), memory bandwidths, and various levels of private and shared caches, as well as developing strategies for optimizing locality. But highly optimized implementations are often inefficient when executed on a different platform. This is the performance portability problem. One approach to scalability and portability is to tune the amount of work per task based on runtime overheads and concurrency. This results in a better balance between parallelism and scheduling overheads, but it can neither tune data reuse nor avoid inter-task interference. We propose a complementary approach that consists in tuning the amount of resources allocated to tasks and combine it with software-defined task topologies to provide portable locality. These ideas are combined into a low-overhead resource management scheme called Elastic Places. Elastic Places is implemented in the XiTAO software framework but the core ideas are equally applicable to other languages and runtimes. Experimental results on an AMD-based NUMA machine and an Intel Knights Landing system show that elastic places provides both high scalability and performance portability, with speed-ups of up to 2.3× on both platforms compared to state-of-the-art runtimes.
Effect of combining multiple micronutrients with iron supplementation on Hb response in children: systematic review of randomized controlled trials

Abstract Objectives To study the effect of combining multiple (two or more) micronutrients with Fe supplementation on Hb response, when compared with placebo and with Fe supplementation, in children. Data sources Electronic databases, personal files, hand search of reviews, bibliographies of books, and abstracts and proceedings of international conferences. Review methods Randomized controlled trials evaluating change in Hb levels with interventions that included Fe and multiple-micronutrient supplementation in comparison to placebo alone or Fe alone were analysed in two systematic reviews. Results Twenty-five trials were included in the review comparing Fe and micronutrient supplementation with placebo. The pooled estimate (random effects model) for change in Hb with Fe and micronutrient supplementation (weighted mean difference) was 0·65 g/dl (95 % CI 0·50, 0·80, P < 0·001). Lower baseline Hb, lower height-for-age Z score, non-intake of ‘other micronutrients’ and malarial non-hyperendemic region were significant predictors of greater Hb response and heterogeneity. Thirteen trials were included in the review comparing Fe and micronutrient supplementation with Fe alone. The pooled estimate for change in Hb with Fe and micronutrient supplementation (weighted mean difference) was 0·14 g/dl (95 % CI 0·00, 0·28, P = 0·04). None of the variables were found to be significant predictors of Hb response. Conclusions Synthesized evidence indicates that addition of multiple micronutrients to Fe supplementation may only marginally improve Hb response compared with Fe supplementation alone. However, addition of ‘other micronutrients’ may have a negative effect. Routine addition of unselected multiple micronutrients to Fe therefore appears unjustified for nutritional anaemia control programmes.
Classification of German verbs using nouns in argument positions and aspectual features

This paper provides evidence that aspectual verb classes (Vendler, 1967) can be induced from nominal fillers in argument positions and aspectual features. We classified 35 German verbs in a supervised learning procedure using a support vector machine classifier and a classification into five aspectual classes (Richter and van Hout, 2015) as gold standard and observed excellent and substantial agreements.
Retroperitoneal calcifying fibrous tumor mimicking an adrenal tumor

Establishing the etiology of a retroperitoneal tumor may be difficult due to close proximity of multiple organs. Evaluation of retroperitoneal tumors often leads to surgery, many times to obtain a definitive diagnosis and rule out malignancy. Calcifying fibrous tumors (CFT) are very rare soft tissue tumors occurring most often in young patients. They are most often found arising in the thoracic cavity, mediastinum, abdominal cavity and extremities and usually have a benign clinical course. Macrocscopically, the tumors are well circumscribed and firm with a white-tan appearance. Histologically, CFT comprised a hypocellular proliferation of bland spindle cells, densely hyalinized collagen, chronic lymphoplasmacytic inflammation and dystrophic calcifications. Other considerations in the pathologic differential diagnosis include solitary fibrous tumor and inflammatory myofibroblastic tumor.
Price Trends in India and Their Implications for Measuring Poverty

The Indian national sample surveys collect data on the unit values of a large number of foods which can be used to compute price index numbers that can be compared with the official national price indexes, the Consumer Price Index for Agricultural Labourers (CPIAL) for rural India, and the Consumer Price Index for Industrial Workers (CPIIW) for urban India. Over the five years from 1999? 2000 to 2004-05, the food component of the CPIAL understated the rate of food price inflation. This overstatement is likely attributable to the use of long outdated weights (from 1983), and the resultant overweighting of cereals, particularly coarse cereals, whose prices fell relative to other foods. The overall weight of food in the CPIAL is also too large, so that the growth in the general CPIAL was understated during this period when food prices fell relative to nonfood prices. Under conservative assumptions, I calculate that the 5 year growth in the reported CPIAL of 10.6 percent should have been 14.3 percent. Indian poverty lines are held constant in real terms and are updated using the food and non-food components of the official indices weighted by the food shares of households near the poverty line. Because these weights come from a 1973? 4 survey, food is heavily over weighted for the contemporary poor, and the nominal poverty lines are understated, both because the CPIAL food index is understated, and because too much weight is assigned to food in a period when food prices have been falling relative to nonfood prices. As a result, and ignoring other problems with the counts (doubtful interstate and intersectoral price indexes and the growing discrepancy between surveys and national accounts), the official poverty counts for rural India in 2004-5 are too low; the official headcount ratio of 28.3 percent should be closer to 31 percent; at current rates of rural poverty reduction, this eliminates more than three years of progress. More generally, it is clear that the weights used for price indexes should be updated more frequently than is presently the case, something that could be straightforwardly done using India's regular system of household expenditure surveys.
Coupled Simulation of Device Performance and Heating of Vertically Stacked Three-Dimensional Integrated Circuits

We have developed a method for calculating the temperature distribution of a three-dimensional (3D) integrated circuit (IC) and the performance of a single device self-consistently. At the device level, we resolve effects of channel temperatures and thermal boundary conditions on device performance. Thus we obtain non-isothermal device characteristics for a representative device of the technology node used to fabricate the 3D-IC. At the 3D-IC level, we first approximate the average heat generation of each device on the chip using a statistical Monte Carlo method. We second determine effects of the chip layout and the fabrication materials on thermal coupling. Next we calculate thermal profile of the 3D-IC in conjunction with the individual device operations, 3D-IC layout and full-chip workload statistics. Our technique offers a numerical method to isolate affects of chip layout, floor-plan and operational activity on 3D-IC thermal profile. Thus it enables designers to pinpoint potential hotspots, and test new design paradigms for cooling methods.
Increasing reliability in network traffic anomaly detection

Network traffic anomalies stand for a large fraction of the Internet traffic and compromise the performance of the network resources. Detecting and diagnosing these threats is a laborious and time consuming task that network operators face daily. During the last decade researchers have concentrated their efforts on this problem and proposed several tools to automate this task. Thereby, recent advances in anomaly detection have permitted to detect new or unknown anomalies by taking advantage of statistical analysis of the traffic. In spite of the advantages of these detection methods, researchers have reported several common drawbacks discrediting their use in practice. Indeed, the challenge of understanding the relation between the theory underlying these methods and the actual Internet traffic raises several issues. For example, the difficulty of selecting the optimal parameter set for these methods mitigates their performance and prevent network operators from using them. Moreover, due to the lack of ground truth data, approximate evaluations of these detection methods prevent to provide accurate feedback on them and increase their reliability. We address these issues, first, by proposing a pattern-recognition-based detection method that overcomes the common drawbacks of anomaly detectors based on statistical analysis, second, by providing both a benchmark tool that compares the results from diverse detectors and ground truth data obtained by combining several anomaly detectors. The proposed pattern-recognition-based detector takes advantage of image processing techniques to provide intuitive outputs and parameter set. An adaptive mechanism automatically tuning its parameter set according to traffic fluctuations is also proposed. The resulting adaptive anomaly detector is easily usable in practice, performs a high detection rate, and provides intuitive description of the anomalies allowing to identify their root causes. A benchmark methodology is also developed in order to compare several detectors based on different theoretical background. This methodology allows researchers to accurately identify the differences between the results of diverse detectors. We employ this methodology along with an unsupervised combination strategy to combine the output of four anomaly detectors. Thereby, the combination strategy increases the overall reliability of the combined detectors and it detects two times more anomalies than the best detector. We provide the results of this combination of detectors in the form of ground truth data containing various anomalies during 10 years of traffic.
Lidar determination of the composition of atmosphere aerosols

Theoretical and experimental studies of the feasibility of using DIfferential SCatter (DISC) lidar to measure the composition of atmospheric aerosols are described. This technique involves multiwavelength measurements of the backscatter cross section of aerosols in the middle infrared, where a number of materials display strong restrahlen features that significantly modulate the backscatter spectrum. The theoretical work indicates that a number of materials of interest, including sulfuric acid, ammonium sulfate, and silicates, can be discriminated among with a CO2 lidar. An initial evaluation of this procedure was performed in which cirrus clouds and lower altitude tropospheric aerosols were developed. The observed ratio spectrum of the two types of aerosol displays structure that is in crude accord with theoretical expectations.
Sparse structured associative memories as efficient set-membership data structures

We study the use of sparse structured associative memories as a memory-efficient and computationally-efficient data structure for representing a set of elements when one wishes to perform set-membership queries and some errors (false positives) are tolerable. Associative memories, when viewed as representing a set, enjoy a number of interesting properties, including that set membership queries can be carried out even when the input (query element) is only partially known or is partially corrupted. The associative memories considered here (initially proposed in [Gripon and Berrou, 2011]) encode the set in the edge structure of a graph. In this paper we generalize this construction to encode the set in the edge structure of a hypergraph. We derive bounds on the false positive rates (the probability that the associative memory erroneously declares that an element is in the stored set when it, in fact, was not). Interestingly, the proposed structures enjoy many of the same properties as Bloom filters (e.g., they have zero false negative rate, the time to perform an insert and lookup does not depend on the number of elements stored, and the false positive rate can be reduced by using additional memory for storage), while also offering the properties of associative memories (allowing for queries on partial or corrupted inputs).
Health Evaluation in Software Ecosystems

Context: The quality of a Software Ecosystem (SECO) platform and its available products are important characteristics to ensure its success. However, this concept goes beyond the traditional approaches of quality assurance, including concepts such as SECO ́s health. Objectives: The aim of this study is propose an evaluation process to application of health metrics. In addition, this metrics were formalized to make feasible your application and improve the obtained results. Method: A systematic mapping was conducted with the aim of analyzing the SECO quality research area, highlighting the state of the art and identifying its main characteristics. In addition, the main approaches and metrics present in the literature for SECO quality and health evaluation are detailed. This work presents an observational study used to define relevant heath metrics considering an evaluation process. Results: The metrics were formalized and evaluated by specialists. A health evaluation process was developed to applicate this metrics. This process is supported by an architecture named
Online News Discussions

This study examines personality traits and motivations in association with individuals’ online news comment behavior. A survey of 517 participants indicated that those who were more agreeable and narcissistic were motivated for posting comments on online news. Motivations including informing, getting feedback, and exhibitionism predicted the frequency of posting on news comment sections, while social connection was a major predictor of commenting on the news shared in social media. Implications for using this online opinion-posting mechanism are discussed.
Natural Language Generation from Pictographs

We present a Pictograph-to-Text translation system for people with Intellectual or Developmental Disabilities (IDD). The system translates pictograph messages, consisting of one or more pictographs, into Dutch text using WordNet links and an ngram language model. We also provide several pictograph input methods assisting the users in selecting the appropriate pictographs.
CloudDVMM: Distributed Virtual Machine Monitor for Cloud Computing

With the wide application of virtualization and cloud computing, it becomes an increasingly urgent problem of how to use a virtual machine monitor to integrate the increasing amount of distributed cloud computing nodes to improve their utility and reliability. Existing popular virtual machine monitors like Xen, VMware ESX Server, etc. are mostly acts as a fundamental infrastructure for the virtualization of one single cloud computing node. However, there are few researches on a virtual machine monitor for those distributed nodes under cloud computing environment. This paper introduces a novel distributed virtual machine monitor for cloud computing (CloudDVMM). We present its theoretical model, architecture and key technologies. Experiments and comparisons with existing researches show that CloudDVMM achieves better performance in distributed architecture, extensibility, etc. and is promising for meeting the integration requirements of distributed virtual computing and cloud computing environments.
A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training

When an electronic nose (E-nose) is used to distinguish different kinds of gases, the label information of the target gas could be lost due to some fault of the operators or some other reason, although this is not expected. Another fact is that the cost of getting the labeled samples is usually higher than for unlabeled ones. In most cases, the classification accuracy of an E-nose trained using labeled samples is higher than that of the E-nose trained by unlabeled ones, so gases without label information should not be used to train an E-nose, however, this wastes resources and can even delay the progress of research. In this work a novel multi-class semi-supervised learning technique called M-training is proposed to train E-noses with both labeled and unlabeled samples. We employ M-training to train the E-nose which is used to distinguish three indoor pollutant gases (benzene, toluene and formaldehyde). Data processing results prove that the classification accuracy of E-nose trained by semi-supervised techniques (tri-training and M-training) is higher than that of an E-nose trained only with labeled samples, and the performance of M-training is better than that of tri-training because more base classifiers can be employed by M-training.
Mobile Visual Computing

Smart phones are becoming visual computing powerhouses. Using sensors such as camera, GPS, and others, the device can provide a new user interface to the real world, augmenting user's view of the world with additional information and controls. Combining computation with image capture allows new kind of photography that can be more expressive than is possible to obtain with a traditional camera. New APIs allow harnessing more computation power of a smart phone to visual processing than what one can obtain from just a CPU.
A Novel, Broadcasting-Based Algorithm For Vehicle Speed Estimation In Intelligent Transportation Systems Using Ad-hoc Networks

There has been a lot of research effort recently dedicated to identifying appropriate communication paradigm based on car-to-car communication for evaluation of traffic conditions. This paper introduces a novel way of evaluation of one such condition the average speed of all cars in a street in an urban area using simple broadcasting protocol. The paper presents the protocol, describes the simulation model and reports the results that have been achieved using simulation and real wireless devices communications, but in a static mode, i.e. the devices are not moving. It is anticipated that the real-tests will confirm the conclusions drawn in the paper.
NICMOS Imaging of Infrared-Luminous Galaxies

We present near-infrared images obtained with the Hubble Space Telescope NICMOS camera for a sample of nine luminous [LIGs: LIR(8–1000 μm) ≥ 1011 L⊙] and 15 ultraluminous (ULIGS: LIR ≥ 1012 L⊙) infrared galaxies. The sample includes representative systems classified as warm (f25 μm/f60 μm > 0.2) and cold (f25 μm/f60 μm ≤ 0.2) based on the mid-infrared colors and systems with nuclear emission lines classified as H II (i.e., starburst), QSO, Seyfert, and LINER. The morphologies of the sample galaxies are diverse and provide further support for the idea that they are created by the collision or interactions of spiral galaxies. Although no new nuclei are seen in the NICMOS images, the NICMOS images do reveal new spiral structures, bridges, and circumnuclear star clusters. The colors and the luminosities of the observed clusters are consistent with them being young (107–108 yr), formed as a result of galactic interactions, and having masses much greater than those of Galactic globular clusters. In NGC 6090 and VV 114, they are preferentially situated along the area of overlap of the two galactic disks. With the exception of IR 17208-0018, all of the ULIGs have at least one compact (2.2 μm FWHM ≤ 200 pc) nucleus. Analysis of the near-infrared colors (i.e., m1.1–1.6 vs. m1.6–2.2) derived from 1. ″1 diameter apertures suggests that the warm galaxies have near-infrared colors consistent with QSO+hot dust emission and the cold galaxies, as a group, have near-infrared colors consistent with reddened starlight. In addition, the cold ULIG UGC 5101 (and possibly three others) have near-infrared colors suggesting additional active galactic nucleus–like near-infrared components in their nuclei. In a 2 kpc diameter aperture measurement, the global colors of all of the cold galaxies except UGC 5101 are consistent with starlight with a few magnitudes of visual extinction. The general dichotomy of the near-infrared properties of the warm and the cold galaxies are further supported by the light distributions: seven of the eight warm galaxies have unresolved nuclear emission that contributes significantly (i.e., ≥30%–40%) to the total near-infrared luminosity. The smooth, more extended light observed in all of the galaxies is most likely composed of giant and supergiant stars, but evidence at longer wavelengths suggests that these stars contribute little to the high 8–1000 μm luminosity of these galaxies. Finally, light profiles of nine of the 24 systems were fitted well by an r1/4 law (and not so well by an exponential disk profile). Whether these star systems eventually become massive central bulges or giant elliptical galaxies will depend on how efficiently the present ISM is converted into stars.