Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome size diversity in orchids: consequences and evolution.

BACKGROUND The amount of DNA comprising the genome of an organism (its genome size) varies a remarkable 40 000-fold across eukaryotes, yet most groups are characterized by much narrower ranges (e.g. 14-fold in gymnosperms, 3- to 4-fold in mammals). Angiosperms stand out as one of the most variable groups with genome sizes varying nearly 2000-fold. Nevertheless within angiosperms the majority of families are characterized by genomes which are small and vary little. Species with large genomes are mostly restricted to a few monocots families including Orchidaceae. SCOPE A survey of the literature revealed that genome size data for Orchidaceae are comparatively rare representing just 327 species. Nevertheless they reveal that Orchidaceae are currently the most variable angiosperm family with genome sizes ranging 168-fold (1C = 0.33-55.4 pg). Analysing the data provided insights into the distribution, evolution and possible consequences to the plant of this genome size diversity. CONCLUSIONS Superimposing the data onto the increasingly robust phylogenetic tree of Orchidaceae revealed how different subfamilies were characterized by distinct genome size profiles. Epidendroideae possessed the greatest range of genome sizes, although the majority of species had small genomes. In contrast, the largest genomes were found in subfamilies Cypripedioideae and Vanilloideae. Genome size evolution within this subfamily was analysed as this is the only one with reasonable representation of data. This approach highlighted striking differences in genome size and karyotype evolution between the closely related Cypripedium, Paphiopedilum and Phragmipedium. As to the consequences of genome size diversity, various studies revealed that this has both practical (e.g. application of genetic fingerprinting techniques) and biological consequences (e.g. affecting where and when an orchid may grow) and emphasizes the importance of obtaining further genome size data given the considerable phylogenetic gaps which have been highlighted by the current study.
Relational Database Schema Design for Uncertain Data

We investigate the impact of uncertainty on relational data\-base schema design. Uncertainty is modeled qualitatively by assigning to tuples a degree of possibility with which they occur, and assigning to functional dependencies a degree of certainty which says to which tuples they apply. A design theory is developed for possibilistic functional dependencies, including efficient axiomatic and algorithmic characterizations of their implication problem. Naturally, the possibility degrees of tuples result in a scale of different degrees of data redundancy. Scaled versions of the classical syntactic Boyce-Codd and Third Normal Forms are established and semantically justified in terms of avoiding data redundancy of different degrees. Classical decomposition and synthesis techniques are scaled as well. Therefore, possibilistic functional dependencies do not just enable designers to control the levels of data integrity and losslessness targeted but also to balance the classical trade-off between query and update efficiency. Extensive experiments confirm the efficiency of our framework and provide original insight into relational schema design.
Tip-enhanced fluorescence microscopy of high-density samples

High-density samples of fluorescent quantum dots (QDs) were imaged using an apertureless near-field optical microscopy technique. QD fluorescence was modulated by oscillating a silicon atomic force microscope tip above an illuminated sample and a lock-in amplifier was used to suppress background from the excitation laser. Spatial resolution near 10nm and a peak signal-to-noise ratio (SNR) of ∼60 were achieved. Individual QDs within high-density ensembles were still easily resolved (SNR>5) at a density of 14QDs∕μm2. These results have favorable implications for the eventual nanoscale imaging of viable biological systems, such as cellular membranes.
Absorption features of high-redshift galactic winds

The environment of high-redshift galaxies is characterized by both wind-driven outflowing gas and gravitationally infalling streams. To investigate such galaxy-IGM interplay we have generated synthetic optical absorption line spectra piercing the volume surrounding a star-bursting analogue of a Lyman-break galaxy selected in a z ≈ 3 output from a smoothed particle hydrodynamics simulation, including a detailed treatment of mechanical feedback from winds. Distributions for several observable species (HI, CIII, CIV, Si II, Si III, Si iv, O VI, O VII and O VIII) have been derived by post-processing the simulation outputs. The hot-wind material is characterized by the presence of high-ionization species such as 0 vi, O VII and 0 VIII (the latter two observable only in X-ray bands); the colder (T < 10 5.5 K) infalling streams can be instead identified by the combined presence of Si II, Si III and C III optical absorption together with O VI that surrounds the cooler gas clumps. However, both line profile and pixel optical depth analysis of the synthetic spectra show that the intergalactic filament in which the wind-blowing galaxy is embedded produces absorption signatures that closely mimic those of the wind environment. We conclude that it may be difficult to clearly identify wind-blowing galaxies and their complex gaseous environment at high redshift in optical QSO absorption-line spectra based solely on the observed ion-absorption patterns.
Semantic labeling of digital photos by classification

The paper addresses the problem of annotating photographs with broad semantic labels. To cope with the great variety of photos available on the WEB we have designed a hierarchical classification strategy which first classifies images as pornographic or not-pornographic. Not-pornographic images are then classified as indoor, outdoor, or close-up. On a database of over 9000 images, mostly downloaded from the web, our method achieves an average accuracy of close to 90%.
Productivity of Software Projects by Business Sector An Empirical Analysis of Trends

Software organisations continuously adopt new technologies and improve their business processes to increase their productivity and hence, be abreast with or ahead of their competitors. This emphasises the importance of investigation into the results of such improvements over productivity over a period of time. In this paper we compare productivity of projects that commenced in and pre-1994 with those that commenced in and post-1997 (the latter a larger sample). Our results reveal very interesting trends in which companies within some business sectors have become very productive due to their past investments, while others are revamping their business processes to help increase productivity in the future. The analysis also reveals important features that play a crucial role in determining productivity within individual business sectors.
Bounded solutions of quadratic circulant difference equations

In this paper we develop some techniques to obtain global hyperbolicity for a certain class of endomorphisms of with This kind of endomorphisms are obtained from vectorial difference equations where the mapping defining these equations satisfy a circulant condition. In particular, we show that one-parameter families of these quadratic endomorphisms are hyperbolic for large values of the parameter.
An Empirical Verification of Coverage and Correctness for a General-Purpose Sentence Generator

This paper describes a general-purpose sentence generation system that can achieve both broad scale coverage and high quality while aiming to be suitable for a variety of generation tasks. We measure the coverage and correctness empirically using a section of the Penn Tree-bank corpus as a test set. We also describe novel features that help make the generator ﬂexible and easier to use for a variety of tasks. To our knowledge, this is the ﬁrst empirical measurement of coverage reported in the literature, and the highest reported measurements of correctness
Three-step-approach with validation for face hallucination

In this paper, we propose a novel face hallucination framework using validation based on three-step-approach. In order to improve the performance of facial image reconstruction, we included validation in our framework for correcting error. That is the final result should be more accurate than the result before the validation process. In this paper, the 2D framework is applied that means the image can directly process without requiring the vectorization. Moreover, the spatial information can be preserved. Our framework is based on a three-step-approach. In the first step, error of face image reconstruction is learnt from training data set by Bilateral Two Dimensional Principal Component Analysis (B2DPCA). In this step, the validation is obtained from the error of Low-Resolution (LR) and error of High-Resolution (HR). In the second step, the global image is reconstructed by using Maximum a Posteriori (MAP) estimator and the final step is using Regression Model for Tensor (RM-T) to learn from samples data set by applying error regression analysis. The experimental results on a well-known face database demonstrate that the proposed methods can improve the face reconstruction. The results show that our method enhances the resolution and improves the quality of the face hallucination in comparison with the conventional method.
Emotions and Incentives

We introduce a concept of emotions that emerge when workers compare their own performance with a given standard or with the performances of co-workers. Assuming heterogeneity among the workers the interplay of emotions and incentives is analyzed by focusing on three incentive schemes that are frequently used in practice: tournaments, bonuses and piece rates. We identify certain conditions under which emotions lead to additional incentives and under which the employer benefits from emotional workers. Furthermore, the concept of emotions is used to explain puzzling results from laboratory and field experiments. Finally, the results provide some insights on an employer's possible preferences in favor of heterogeneous instead of homogeneous work groups.
Debunking then Duplicating Ultracomputer Performance Claims by Debugging the Combining Switches

Memory system congestion due to serialization of hot spot accesses can adversely affect the performance of interprocess coordination algorithms. Hardware and software techniques have been proposed to reduce this congestion and thereby provide superior system performance. The combining networks of Gottlieb et al. automatically parallelize concurrent hot spot memory accesses, improving the performance of algorithms that poll a small number of shared variables. We begin by debunking one of the performance claims made for the NYU Ultracomputer. Specifically, a gap in its simulation coverage hid a design flaw in the combining switches that seriously impacts the performance of busy wait polling in centralized coordination algorithms. We then debug the system by correcting the design and closing the simulation gap, after which we are able to duplicate the original claims of excellent performance on busy wait polling. Specifically our simulations show that, with the revised design, the Ultracomputer readerswriters and barrier algorithms achieve performance comparable to the highly regarded MCS algorithms.
RFID Adoption: An Exploratory Study of Issues and Concerns

Radio frequency identification (RFID) systems have received increased attention from academicians and practitioners in the past few years. By implementing RFID, companies could achieve “process freedoms” and real-time visibility. Studies have discussed about opportunities, benefits, and challenges in deploying RFID. The issues discussed and insights offered in these studies were mostly of theoretical and conceptual significance due to the emergent nature of the phenomenon and difficulty in collecting data. The purpose of this paper is to get practical insights into organizations’ strategic issues in adapting to this new technological change. It examines the firm’s decision to adopt RFID from strategic perspective and aims to understand the transition process in doing so. The findings and conclusions reported are based on the data collected from organizations that have started the deployment process or have already deployed RFID.
Find Your Place: Simple Distributed Algorithms for Community Detection

Given an underlying graph, we consider the following \emph{dynamics}: Initially, each node locally chooses a value in $\{-1,1\}$, uniformly at random and independently of other nodes. Then, in each consecutive round, every node updates its local value to the average of the values held by its neighbors, at the same time applying an elementary, local clustering rule that only depends on the current and the previous values held by the node. We prove that the process resulting from this dynamics produces a clustering that exactly or approximately (depending on the graph) reflects the underlying cut in logarithmic time, under various graph models that exhibit a sparse balanced cut, including the stochastic block model. We also prove that a natural extension of this dynamics performs community detection on a regularized version of the stochastic block model with multiple communities. Rather surprisingly, our results provide rigorous evidence for the ability of an extremely simple and natural dynamics to address a computational problem that is non-trivial even in a centralized setting.
An Ontology of Form PF

Form PF, mandated by the 2010 Dodd-Frank Act, is financial regulators' primary source for supervisory data on the risk exposures of hedge funds. Investment advisers use the Securities and Exchange Commission's (SEC) Form ADV to register, and then submit Form PF to report on each of the funds that they advise. These forms embed significant internal structure that is amenable to knowledge representation via formal ontologies, which would facilitate key tasks, such as data integration and the assurance of data integrity. We argue that ontologies should be a core and integral component of information management for financial regulatory reporting. We have tested the approach by designing, developing, and integrating ontologies in OWL/RDF in prototype to consistently describe Form ADV and Form PF with precise semantics. Preliminary results indicate that this technique is feasible in practice for data search and analysis, and will yield useful functionality. We also outline directions for future research.
Influence of Human OATP1B1, OATP1B3, and OATP1A2 on the Pharmacokinetics of Methotrexate and Paclitaxel in Humanized Transgenic Mice

Purpose: Organic anion-transporting polypeptide (OATP) drug uptake transporters are thought to play an important role in drug pharmacokinetics and toxicokinetics. We aimed to determine the influence of the individual human OATP1B1, OATP1B3, and OATP1A2 transporters on the in vivo disposition of the anticancer drugs methotrexate and paclitaxel by using liver-specific humanized OATP1A/1B transgenic mice. Experimental Design: Wild-type, Slco1a/1b−/− (Oatp1a/1b knockout), Slco1a/1b−/−;1B1tg, Slco1a/1b−/−;1B3tg, and newly generated Slco1a/1b−/−;1A2tg (humanized OATP1B1, OATP1B3, and OATP1A2 transgenic) mice were characterized biochemically and physiologically, and subsequently intravenously dosed with methotrexate or paclitaxel (2 or 10 mg/kg each) for pharmacokinetic analyses. Results: Humanized OATP1B1, OATP1B3, and OATP1A2 transgenic mice all showed partial or complete rescue of increased plasma bilirubin levels, but also of the increased plasma levels and decreased liver and small intestinal accumulation of methotrexate observed in Slco1a/1b−/− mice. Furthermore, hepatic expression of OATP1B3 and OATP1A2, but not OATP1B1, resulted in increased liver uptake of paclitaxel (2 mg/kg). At 10 mg/kg, a modest effect of only OATP1A2 on paclitaxel liver uptake was observed. Conclusion: Human OATP1A/1B transporters play an important role in plasma and tissue distribution of the structurally diverse chemotherapeutics methotrexate (organic anion) and paclitaxel (hydrophobic, bulky). Variation in OATP1A/1B activity due to genetic variation and pharmacologic inhibition, or differences in tumor-specific expression levels might therefore affect plasma, tissue, and tumor levels of these drugs in patients, and hence their therapeutic efficacy. Humanized transgenic OATP1A/1B mice will provide excellent tools to further study these aspects in vivo for many (anticancer) drugs. Clin Cancer Res; 19(4); 821–32. ©2012 AACR.
Parallel Clustering of High-Dimensional Social Media Data Streams

We introduce Cloud DIKW (Data, Information, Knowledge, Wisdom) as an analysis environment supporting scientific discovery through integrated parallel batch and streaming processing, and apply it to one representative domain application: social media data stream clustering. In this context, recent work demonstrated that high-quality clusters can be generated by representing the data points using high-dimensional vectors that reflect textual content and social network information. However, due to the high cost of similarity computation, sequential implementations of even single-pass algorithms cannot keep up with the speed of real-world streams. This paper presents our efforts in meeting the constraints of realtimesocial media stream clustering through parallelization in Cloud DIKW. Specifically, we focus on two system-level issues. Firstly, most stream processing engines such as Apache Storm organize distributed workers in the form of a directed acyclic graph (DAG), which makes it difficult to dynamically synchronize the state of parallel clustering workers. We tackle this challenge by creating a separate synchronization channel using a pub-sub messaging system (ActiveMQ in our case). Secondly, due to the sparsity of the high-dimensional vectors, the size of cancroids grows quickly as new data points are assigned tithe clusters. As a result, traditional synchronization that directly broadcasts cluster cancroids becomes too expensive and limits the scalability of the parallel algorithm. We address this problem by communicating only dynamic changes of the clusters rather than the whole centred vectors. Our algorithm under Cloud DIKWcan process the Twitter 10% data stream ("gardenhose") in realtimewith 96-way parallelism. By natural improvements to CloudDIKW, including advanced collective communication techniques developed in our Harp project, we will be able to process the full Twitter data stream in real-time with 1000-way parallelism. Our use of powerful general software subsystems will enable many other applications that need integration of streaming and batch data analytics.
RECOURSE TO PRENATAL CARE IN TOGO. A COMPARATIVE ANALYSIS ON THE DETERMINANTS OF THE DEMAND IN RURAL AND URBAN AREAS

If from the supply side important investments have been made in order to put in place significant medical infrastructures, other economic and social factors not less important can influence the demand for reproductive health goods and services in its antenatal consultations component. The general objective of this study is to identify the economic and social factors that determine the probability of the choice of a type of antenatal healthcare and specifically to verify the effects of variables on the standard of living by using antenatal medical care. Based on a multinomial logit model, from the data of the MICS-3 survey conducted in 2006, the main response allow to bring out among others that (i) antenatal care consultations are less frequent among non-educated women than the educated ones; (ii) the proportion of antenatal care by a qualified personnel is all the more important that the sign of wealth is high; (iii) the education level of the mother, household size, the asset index, the number of children under five years, the price, and the quality have a statistically significant impact on woman’s decision to go or not for antenatal consultation by a qualified personnel.
Research on Architecture and Key Technology of a Medical Capsule Micro-robot in Intestinal Inspection

This paper presents a simple structure of the medical capsule micro-robot which achieves micro-image acquisition and wireless transmission. It has the characteristics of high integration, small size and low power consumption. The experimental results indicate that the capsule micro-robot can obtain a lot of clear images. It unifies observing, monitoring and safety diagnosis of the patient organically.
Differential Binding of Calmodulin to Group I Metabotropic Glutamate Receptors Regulates Receptor Trafficking and Signaling

Metabotropic glutamate receptors (mGluRs) are G-protein-coupled receptors that modulate excitatory neurotransmission and synaptic plasticity. The group I mGluRs (mGluR1 and mGluR5) have long intracellular C-terminal domains, which interact with many proteins. Our previous studies identified calmodulin (CaM) as a strong regulator of mGluR5 trafficking and mGluR5-induced calcium signaling. Although it has been accepted that both mGluR1 and mGluR5 interact with CaM, we now show that CaM specifically binds mGluR5 and not mGluR1. We have identified a single critical residue in mGluR5 (L896) that is required for CaM binding. In mGluR1, mutation of the corresponding residue, V909, to leucine is sufficient to confer CaM binding to mGluR1. To investigate the functional effects of CaM binding, we examined the surface expression of mGluR1 and mGluR5 in hippocampal neurons. The mutation in mGluR1 (V909L) that confers CaM binding dramatically increases mGluR1 surface expression, whereas the analogous mutation in mGluR5 that disrupts CaM binding (L896V) decreases mGluR5 surface expression. In addition, the critical residue that alters CaM binding regulates mGluR internalization. Furthermore, we find that mGluR-mediated AMPA receptor endocytosis is enhanced by CaM binding to group I mGluRs. Finally, we show that calcium responses evoked by group I mGluRs are modulated by these mutations, which regulate CaM binding. Our findings elucidate a critical mechanism that specifically affects mGluR5 trafficking and signaling, and distinguishes mGluR1 and mGluR5 regulation.
Dispersive Smoothing for the Euler-Korteweg Model

The Euler--Korteweg system consists of a quasi-linear, dispersive perturbation of the Euler equations. The Cauchy problem has been studied in any dimension $d\geq 1$ by Benzoni, Danchin, and Descombes, who obtained local well-posedness results when the velocity is in $H^s$ for $s>d/2+1$. They noticed that one may expect to find some smoothing effect due to the dispersive effects, but there was no proof so far. Our aim here is to give such results in any dimension under their local existence assumptions. In the simpler case of dimension $1$ we obtain unconditionnal Kato smoothing (local smoothing of $1/2$ derivative). In higher dimensions a few additional hypotheses must be made to get smoothing and we briefly discuss the pertinence of these restrictions.
What spelling tells us about the orthographic development and word study instruction with emergent bilingual secondary students

Abstract Educators need ways to assess orthographic knowledge and differentiate word study instruction for secondary, emergent bilingual learners. In this study, the spelling of 199 students in grades 7–12 across eight features and four spelling stages was examined to understand students' orthographic development; all but two were learning Spanish and English. Spelling data were collected three times over a nine-month period. There were significant changes across the time periods that show students progressing across four stages of spelling development, with a large effect size (partial eta squared = .498). Data from a standardized assessment of language proficiency were examined to study the relationship between students' orthographic knowledge and their language scores. This study suggests ways to use spelling assessments to plan differentiated vocabulary and word study instruction.