Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Linked Data is Not Enough for Scientists

Scientific data stands to represent a significant portion of the linked open data cloud and science itself stands to benefit from the data fusion capability that this will afford. However, simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Publishing has requirements of provenance, quality, credit, attribution, methods in order to provide the \emph{reproducibility} that allows validation of results. In this paper we make the case for a scientific data publication model on top of linked data and introduce the notion of \emph{Research Objects} as first class citizens for sharing and publishing.
Involvement of Endocytosis and Alternative Splicing in the Formation of the Pathological Process in the Early Stages of Parkinson's Disease

Parkinson's disease (PD) is the one of most widespread neurodegenerative pathologies. Because of the impossibility of studying the endogenous processes that occur in the brain of patients with PD in the presymptomatic stage, the mechanisms that trigger the disease remain unknown. Thus, the identification of the processes that play an important role in the early stages of the disease in these patients is extremely difficult. In this context, we performed a whole-transcriptome analysis of the peripheral blood of untreated patients with stage 1 PD (Hoehn-Yahr scale). We demonstrated a significant change in the levels of transcripts included in the large groups of processes associated with the functioning of the immune system and cellular transport. Moreover, a significant change in the splicing of genes involved in cellular-transport processes was shown in our study.
Design and Evaluation of Four AR Navigation Tools Using Scene and Viewpoint Handling

In an Augmented Reality (AR) system using a brick-based tangible user interface, we present and evaluate alternative techniques for scene navigation. Going from two-dimensional brick-based input to three- dimensional navigation presents design issues. There are two fundamental methods for scene control: scene handling or viewpoint handling. The system has two views (plan and side), presenting action-perception spaces which are coincident and separate. Four tools were developed to explore design solutions, testing the alternative methods in each view. In a quantitative user experiment with a search-and-position task, we evaluated the four tools, measuring performance by trial completion time. Results showed that scene and viewpoint handling performed equally well in the plan view. In the side view, scene handling performed better. Subjective ranking showed that scene handling was always preferred to viewpoint handling. Results indicate that when action- perception spaces are coincident, the choice of handling method is less critical than when separate.
EXOFLY: A FLAPPING WINGED AEROBOT FOR AUTONOMOUS FLIGHT IN MARS ATMOSPHERE

Flapping winged flight is well suited to the low density and highly viscous Martian atmosphere. The ExoFly demonstrator and mission concept illustrates the feasibility and usefulness of a mission to mars utilising such a rover mobility concept. Such a system would be capable of autonomous, efficient and robust flight in the lower Mars atmosphere, offering novel opportunities for 3D surface feature analysis from outcrop-scale visual data collection using this stable mobile platform. A demonstrator has been implemented for use in Earth atmosphere, capable of autonomous, stable and robust straightline flight and hovering, as well as take-off and landing capabilities. While adaptation to Mars conditions would require different physical characteristics, initial studies have found that this should not be an impediment to feasibility. The demonstrator has a total weight of 17 grams and is able to fly for 12 minutes with onboard energy storage and a pinhole camera payload. In Mars conditions, initial studies have identified a potential mission with ExoFly mass of 20 grams and range of 10-15 km with onboard solar cell recharging of the energy storage subsystem and a similar scientific payload. Further development could envisage additional equipment for, for example, aerial magnetic survey given availability of sufficiently miniaturized payload options. In addition, the design may be optimised for differing mission profiles emphasizing, for instance, range or hovering flight. Autonomous control using optical flow is envisaged, building on capability already implemented in the demonstrator. The use of this mission concept, allowing slow and stable airborne movement could provide previously unavailable capability in terms of 3D imaging of surface features in analysis of Aeolian and chemical erosion or study of the rock record through analysis of sedimentary structures or volcanic flow features. In addition to its particular suitability for use on Mars, ExoFly might be considered for use in any extraterrestrial atmosphere. This paper will explore the feasibility and potential scientific value of a mission concept using this technology.
Solving fuzzy combined-emission dispatch by using differential evolution immunized Ant Colony Optimization technique

Emission dispatch deals with the process of determining the emission level produced by thermal power plants. Since the concerns toward environmental health paramount, emission dispatch has become a crucial consideration during energy dispatch planning. Different fuel types produce different types of pollutant and thus the total emission level may vary. However, the fluctuation of future load demand and fuel cost causes emission dispatch problems in dynamic system. Therefore, this paper proposes the implementation of fuzzy logic in solving the combined emission dispatch and termed as Fuzzy Combined-Emission Dispatch (FCED). A newly developed optimization technique termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique is employed to optimize FCED. DEIANT is compared with Evolutionary Programming (EP) and Ant Colony Optimization (ACO) techniques in order to evaluate its performance. Results indicate that the proposed FCED technique outperformed EP and PSO in terms of achieving lower minimal emission level and reduce operating cost.
Seasonal Effects of Water Quality on Infant and Child Health in India

This paper examines the impact of fertilizer agrichemicals in water on infant and child health using data on water quality combined with data on the health outcomes of infants and children from the 1992-93, 1998-99, and 2005-06 Demographic and Health Surveys of India. Because fertilizers are applied at specific times in the growing season, the concentrations of agrichemicals in water vary seasonally and by cropped area as some Indian states plant predominantly summer crops while others plant winter crops. Our identification strategy exploits the differing timing of the planting seasons across regions and differing seasonal prenatal exposure to agrichemicals to identify the impact of agrichemical contamination on various measures of child health. The results indicate that children exposed to higher concentrations of agrichemicals during their first month experience worse health outcomes on a variety of measures (infant mortality, neo-natal mortality, height-for-age z scores and weight-for-age z-scores). Disaggregated runs reveal that effects are largest amongst the most vulnerable groups – children of uneducated poor women living in rural India.
The Acquisition and Use of Context-Dependent Grammars for English

This paper introduces a paradigm of context-dependent grammar (CDG) and an acquisition system that, through interactive teaching sessions, accumulates the CDG rules. The resulting context-sensitive rules are used by a stack-based, shift/reduce parser to compute unambiguous syntactic structures of sentences. The acquisition system and parser have been applied to the phrase structure and case analyses of 345 sentences, mainly from newswire stories, with 99% accuracy. Extrapolation from our current grammar predicts that about 25 thousand CDG rule examples will be sufficient to train the system in phrase structure analysis of most news stories. Overall, this research concludes that CDG is a computationally and conceptually tractable approach for the construction of sentence grammar for large subsets of natural language text.
Normal sparse Deep Belief Network

Nowadays this is very popular to use deep architectures in machine learning. Deep Belief Networks (DBNs) have deep architectures to create a powerful generative model using training data. Deep Belief Networks can be used in classification and feature learning. A DBN can be learnt unsupervised and then the learnt features are suitable for a simple classifier (like a linear classifier) with a few labeled data. According to researches, training of DBN can be improved to produce features with more interpretability and discrimination ability. One of these improvements is sparsity in learnt features in DBN. By using sparsity we can learn useful low-level feature representations for unlabeled data. In sparse representation we benefit from this property that the learnt features can be interpreted, i.e. they correspond to meaningful aspects of the input, and capture factors of variation in the data. Different methods have been proposed to build sparse RBMs. In this paper we propose a new method namely nsDBN that has different behaviors according to deviation of the activation of the hidden units from a (low) fixed value. Also our proposed method has a variance parameter that can control the force degree of sparseness. According to the results, our new method compared to the state of the art methods including PCA, RBM, qsRBM, and rdsRBM always achieves the best recognition accuracy on the MNIST hand written digit recognition test set even when only 10 to 20 labeled samples per class are used as training data.
Migratie 'Out of Africa': krachten en tegenkrachten

* De auteurs zijn verbonden aan het NIDI, Den Haag, en de eerste auteur is tevens verbonden aan het OCFEB van de Erasmus Universiteit Rotterdam en het Tinbergen Instituut. Contactadres per email: dalen@nidi.nl. Zij danken Jeannette Schoorl en twee referenten voor hun commentaar op het artikel in een eerder stadium. Economische prikkels en sociale netwerken zijn de drijvende krachten achter emigratie vanuit ontwikkelingslanden. In dit artikel worden een aantal Afrikaanse landen onder de loep genomen omdat dit continent gezien wordt als het continent bij uitstek dat nu en in de toekomst gekarakteriseerd wordt door een sterke en toenemende emigratiedruk. Grote verschillen in levensstandaarden en bevolkingsstructuren tussen Afrika en het westen maken dat emigratie ‘out of Africa’ een reëel en langdurig fenomeen zal zijn.
The Serendipitous Extragalactic X-ray Source Identification (sexsi) Program. Iii. Optical Spectroscopy

We present the catalog of 477 spectra from the Serendipitous Extragalactic X-ray Source Identification (SEXSI)program, a survey designed to probe the dominant contributo rs to the 2 – 10 keV cosmic X-ray background. Our survey covers 1 deg 2 of sky to 2 – 10 keV fluxes of 1 ×10−14erg cm−2 s−1, and 2 deg2 for fluxes of 3×10−14erg cm−2 s−1. Our spectra reach to R-band magnitudes of ∼< 24 and have produced identifications and redshifts for 438 hard X-ray sources. Typical completen ss levels in the 27 Chandrafields studied are 40 – 70%. The vast majority of the 2 – 10 keV-selected sample are a ctive galactic nuclei (AGN) with redshifts between 0.1 and 3; our highest-redshift source lies at z = 4.33. We find that few sources at z< 1 have high X-ray luminosities, reflecting a dearth of high-mass, highaccretion-rate sources at low redshift, a result consistent with other recent wide-area surveys. We find that hal f of our sources show significant obscuration, with NH> 1022 cm−2, independent of unobscured luminosity. We classify 168 sou rces as emission-line galaxies; all are X-ray luminous ( Lx > 1041erg s−1) objects with optical spectra lacking both high-ionizatio n lines and evidence of a non-stellar continuum. The redshift distribu ion of these emission-line galaxies peaks at a significantly lower redshift than does that of the sources we spe ctroscopically identify as AGN. We conclude that few of these sources, even at the low-luminosity end, can be p owered by starburst activity. Stacking spectra for a subset of these sources in a similar redshift range, we d etect [NeV] λ3426 emission, a clear signature of AGN activity, confirming that the majority of these objects a re Seyfert 2 galaxies in which the high-ionization lines are diluted by stellar emission. We find a total of 33 obj ects lacking broad lines in their optical spectra which have quasar X-ray luminosities ( Lx > 1044 erg s−1), the largest sample of such objects identified to date. In addition, we explore seventeen AGN associated with galax y clusters and find that the cluster-member AGN sample has a lower fraction of broad-line AGN than does the ba ckground sample. Subject headings: catalogs – surveys – X-rays: galaxies – galaxies: active – Xrays: general – X-rays: galaxies: clusters
S. pombe meiotic linear elements contain proteins related to synaptonemal complex components

The fission yeast Schizosaccharomyces pombe does not form synaptonemal complexes (SCs) in meiotic prophase nuclei. Instead, thin threads, the so-called linear elements (LEs), are observed at the corresponding stages by electron microscopy. Here, we demonstrate that S. pombe Rec10 is a protein related to the Saccharomyces cerevisiae SC protein Red1 and that it localizes to LEs. Moreover, a homologue to S. cerevisiae Hop1 does exist in S. pombe and we show by in situ immunostaining that it, and the kinase Mek1 (a homologue of which is also known to be associated with SCs), localizes to LEs. These observations indicate the evolutionary relationship of LEs with the lateral elements of SCs and suggest that these structures might exert similar functions in S. cerevisiae and S. pombe.
Traffic sign recognition with VG-RAM Weightless Neural Networks

Virtual Generalizing Random Access Memory Weightless Neural Networks (VG-RAM WNN) is an effective machine learning technique that offers simple implementation and fast training and test. In this paper, we present a new approach for traffic sign recognition based on VG-RAM WNN. We evaluate its performance using the German Traffic Sign Recognition Benchmark (GTSRB), a large multi-class classification benchmark. Our experimental results showed that our VG-RAM WNN architecture for traffic sign recognition was able to rank at 4th position in the GTSRB evaluation system, with a recognition rate of 98.73%, and was overcome by only one automatic approach.
Optimal cost traffic shaping with self-similar input sources

We address the problem of determining the parameters of a traffic shaper modeled as a single server queue with finite buffer size and deterministic service rate. In our scheme, the user wishes to gain access to the network with cell loss probability guarantees when the input traffic is self-similar. We assume that the mean rate, the variance and the degree of self-similarity are known. The network is able to provide a connection if the user voluntarily shapes the traffic and if sufficient resources are available to accommodate the shaped traffic stream. We formulate a minimization problem to determine the optimal parameters for the traffic shaper and use techniques of non-linear programming to obtain a solution.
Specification of the Stringmol chemical programming language version 0 . 2 Technical Report Number YCS-2010-458

This report describes in detail version 0.2 of a specification for a nonstandard computational model that emulates the reactivity of enzymes in bacterial cells. The model is an artificial chemistry in which the unique properties of each molecular species is encoded as a sequence of symbols. The model has a very simple cell-level representation consisting of a mixing volume and mixing equation. There is no distinction between genotype and phenotype, or data and program. Randomly selected molecules are subject to a stochastic binding test, in which their identifying sequences are subjected to a complementary alignment process. If the bind is successful, the molecules are combined to form a computational entity to run the reaction between them. At this point the sequence acts as a microprogram. These microprograms can perform a range of tasks, much as a chemical reaction can. Our first chemistry within this model solves the problem of designing a chemical “replicase”, capable of creating copies of itself such that it can replenish a population of molecules that are subject to a decay process. This report gives detail to the model, describes the replicase molecule and its function, and shows an “invasion when rare” experiment.
Predicting Dissolved Lignin Phenol Concentrations in the Coastal Ocean from Chromophoric Dissolved Organic Matter (CDOM) Absorption Coefficients

Dissolved lignin is a well-established biomarker of terrigenous dissolved organic matter (DOM) in the ocean, and a chromophoric component of DOM. Although evidence suggests there is a strong linkage between lignin concentrations and chromophoric DOM (CDOM) absorption coefficients in coastal waters, the characteristics of this linkage and the existence of a relationship that is applicable across coastal oceans remain unclear. Here, 421 paired measurements of dissolved lignin concentrations (sum of 9 lignin phenols) and CDOM absorption coefficients (ag(λ)) were used to examine their relationship along the river-ocean continuum (0-37 salinity) and across contrasting coastal oceans (sub-tropical, temperate, high-latitude). Overall, lignin concentrations spanned four orders of magnitude and revealed a strong, non-linear relationship with ag(λ). The characteristics of the relationship (shape, wavelength dependency, lignin-composition dependency) and evidence from degradation indicators were all consistent with lignin being an important driver of CDOM variability in coastal oceans, and suggested physical mixing and long-term photodegradation were important in shaping the relationship. These observations were used to develop two simple empirical models for estimating lignin concentrations from ag(λ) with a +/- 20% error relative to measured values. The models are expected to be applicable in most coastal oceans influenced by terrigenous inputs.
Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature

Researchers from a number of disciplines have long sought the ability to estimate the functional attributes of plant canopies, such as photosynthetic capacity, using remotely sensed data. To date, however, this goal has not been fully realized. In this study, fresh-leaf reflectance spectroscopy (λ=450–2500 nm) and a partial least-squares regression (PLSR) analysis were used to estimate key determinants of photosynthetic capacity—namely the maximum rates of RuBP carboxylation (Vcmax) and regeneration (Jmax)—measured with standard gas exchange techniques on leaves of trembling aspen and eastern cottonwood trees. The trees were grown across an array of glasshouse temperature regimes. The PLSR models yielded accurate and precise estimates of Vcmax and Jmax within and across species and glasshouse temperatures. These predictions were developed using unique contributions from different spectral regions. Most of the wavelengths selected were correlated with known absorption features related to leaf water content, nitrogen concentration, internal structure, and/or photosynthetic enzymes. In a field application of our PLSR models, spectral reflectance data effectively captured the short-term temperature sensitivities of Vcmax and Jmax in aspen foliage. These findings highlight a promising strategy for developing remote sensing methods to characterize dynamic, environmentally sensitive aspects of canopy photosynthetic metabolism at broad scales.
Mean of the Typical Decoding Rates: A New Translation Efficiency Index Based on the Analysis of Ribosome Profiling Data

Gene translation modeling and prediction is a fundamental problem that has numerous biomedical implementations. In this work we present a novel, user-friendly tool/index for calculating the mean of the typical decoding rates that enables predicting translation elongation efficiency of protein coding genes for different tissue types, developmental stages, and experimental conditions. The suggested translation efficiency index is based on the analysis of the organism’s ribosome profiling data. This index could be used for example to predict changes in translation elongation efficiency of lowly expressed genes that usually have relatively low and/or biased ribosomal densities and protein levels measurements, or can be used for example for predicting translation efficiency of new genetically engineered genes. We demonstrate the usability of this index via the analysis of six organisms in different tissues and developmental stages. Distributable cross platform application and guideline are available for download at: http://www.cs. tau.ac. il/~tamirtul/MTDR/MTDR_Install. html
Running title page a ) Running title : DDI via Inhibition of UGTs by Erlotinib and Gefitinib b )

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A Mixed Approach Toward an Efficient Logical Structure Recognition from Document Images

SUMMARY This paper presents our efforts to improve the efficiency of a document structure analysis system, which intends to analyse the complete logical structure of a document. The usage of fuzzy logic improves the system robustness; however, the problem of system efficiency was revealed to be critical. Different techniques have been studied to overcome this problem. Dynamic programming, heuristics, and dynamic threshold are used for parsing, which achieves a linear complexity. A new concept of key step, based on the principle of sub-goals, is incorporated with a multi-pass and mixed top-down analysis strategy, which avoids the combinatorial explosion of the number of search paths. Finally, the paper shows that the error-tolerating parser based on an analysis graph seems more realistic and efficient than an error-correcting parser.