Miracle-dz/UniFAR-FTUs huggingface dataset:
DHR3 is required for the prepupal-pupal transition and differentiation of adult structures during Drosophila metamorphosis.

Pulses of the steroid hormone ecdysone activate genetic regulatory hierarchies that coordinate the developmental changes associated with Drosophila metamorphosis. A high-titer ecdysone pulse at the end of larval development triggers puparium formation and induces expression of the DHR3 orphan nuclear receptor. Here we use both a heat-inducible DHR3 rescue construct and clonal analysis to define DHR3 functions during metamorphosis. Clonal analysis reveals requirements for DHR3 in the development of adult bristles, wings, and cuticle, and no apparent function in eye or leg development. DHR3 mutants rescued to the third larval instar also reveal essential functions during the onset of metamorphosis, leading to lethality during prepupal and early pupal stages. The phenotypes associated with these lethal phases are consistent with the effects of DHR3 mutations on ecdysone-regulated gene expression. Although DHR3 has been shown to be sufficient for early gene repression at puparium formation, it is not necessary for this response, indicating that other negative regulators may contribute to this pathway. In contrast, DHR3 is required for maximal expression of the midprepupal regulatory genes, EcR, E74B, and betaFTZ-1. Reductions in EcR and betaFTZ-F1 expression, in turn, lead to submaximal early gene induction in response to the prepupal ecdysone pulse and corresponding defects in adult head eversion and salivary gland cell death. These studies demonstrate that DHR3 is an essential regulator of the betaFTZ-F1 midprepupal competence factor, providing a functional link between the late larval and prepupal responses to ecdysone. Induction of DHR3 in early prepupae ensures that responses to the prepupal ecdysone pulse will be distinct from responses to the late larval pulse and thus that the animal progresses in an appropriate manner through the early stages of metamorphosis.
Factors Affecting Mongolian Online Game Players' Satisfaction and Loyalty

Mongolia is an emerging market for the online game industry. The study surveyed 302 valid samples of online game players in Mongolia. The results show that the challenge of an online game is positively related to interdependence with other gamers, loyalty to the game, and its experiential value, respectively. Among them, interdependence mediates the influence of challenges on loyalty and satisfaction mediates the relationship between experiential value and loyalty. Online game companies which want to enter and compete in Mongolia can examine themselves from these findings.
El efecto de la estrategia de innovación tecnológica y de la estrategia exportadora en el desempeño internacional de la empresa

espanolEn este trabajo se examina la influencia que la estrategia de innovacion tecnologica de la empresa, expresada en terminos de sus capacidades innovadoras, tiene sobre el resultado de su actividad internacional y se plantea que la relacion anterior se ve moderada por la estrategia exportadora de la empresa. El estudio empirico se ha desarrollado a partir de una muestra de 88 empresas pertenecientes al sector espanol de baldosas ceramicas. Los resultados obtenidos confirman el efecto positivo sobre el desempeno exportador de la inversion en actividades innovadoras, pero unicamente de aquellas diferentes a la I+D, de las capacidades de produccion relacionadas con la habilidad para mejorar e imitar productos y procesos, y de la cooperacion con centros de investigacion. Asimismo, queda confirmado el efecto moderador de la estrategia exportadora sobre la relacion entre los diferentes tipos de capacidades innovadoras de la empresa y el resultado internacional EnglishIn this work we study the effects that technological capabilities of firms, as an expression of their technological innovation strategy, have on their international competitiveness and suggest that the above relationship is moderated by their export strategy. Empirical work is carried out on a sample of 88 Spanish exporting firms belonging to the ceramic tiles industry. Our findings show a positive impact of technological innovation capabilities on export performance. Specifically, results show that investment in internal non-R&D innovative activities, production capabilities linked to both improvement and imitation of products and processes and capabilities linked to co-operation with universities and research institutes exert a positive influence on export performance. The moderating effect of firms export strategy on the relationship between the different sets of technological capabilities and export performance is also verified
Changes in migration phenology and biometrical traits of Reed, Marsh and Sedge Warblers

Global environmental processes like climate change could severely affect population level migratory behaviour of long range migrant birds. We analyzed changes in migration phenology and biometrics of three closely-related long-distance migrant Acrocephalus species. We used the records of 12 063 Sedge, 12 913 Reed, and 5 409 Marsh Warblers caught and ringed between 1989–2009, at a Hungarian stopover site. Quantile regressions were used to analyse the changes in spring and autumn migration phenology. Median spring arrival date of Sedge and Reed Warblers shifted 6.5 and 7.5 days earlier, respectively. Autumn arrival of all species shifted one (Reed and Marsh Warblers) or two (Sedge Warbler) weeks later. Mean body mass of adult Reed and Marsh Warblers decreased in spring (by 0.3 and 0.2 grams, respectively) and in autumn (by 0.8 and 0.2 grams, respectively) while body mass of adult Sedge Warblers decreased only in autumn (by 0.4 grams). Mean wing length of all species increased significantly (range of change: 0.6–1 mm). Despite the fact that the studied species are closely related, all three have remarkably different migration strategies. However, similar patterns can be observed in the studied parameters, indicating that global processes may have general effects on these species, albeit through markedly different mechanisms.
Supraphysiologic glucocorticoid administration increased biomechanical bone strength of rats' vertebral body

The aim of this study is to assess the effects of different glucocorticoid administration protocols on biomechanical properties of the first lumbar vertebral body in rats. We divided 40 male rats into the following groups: control, dexamethasone (7 mg/week), dexamethasone (0.7 mg/week), methylprednisolone (7 mg/kg/week), methylprednisolone (5 mg/kg twice weekly), dexamethasone (7 mg/kg three times per week), dexamethasone (0.7 mg/kg three times per week, and low-level laser treated rats. Lumbar vertebrae in rats were exposed to the pulsed laser. We conducted a biomechanical test to examine the mechanical properties of vertebral body in rats' lumbar bone. Supraphysiologic glucocorticoid administration protocols did not impair the biomechanical properties of rats' vertebral bodies compared to control and laser-treated rats. Supraphysiologic glucocorticoid administration caused an anabolic effect on the vertebral bodies.
Galaxy Evolution, Deep Galaxy Counts, and the Near-Infrared Cosmic Infrared Background

Accurate synthetic models of stellar populations are constructed and used in evolutionary models of stellar populations in forming galaxies. Following their formation, the late-type galaxies are assumed to follow the Schmidt law for star formation, while early-type galaxies are normalized to the present-day fundamental plane relations assumed to mimic the metallicity variations along their luminosity sequence. The stars in disks of galaxies are distributed with the Scalo IMF and in spheroids with the Salpeter IMF. We show that these assumptions reproduce extremely well the recent observations for the evolution of the rate of star formation with redshift. We then compute predictions of these models for the observational data at early epochs for various cosmological parameters Ω, ΩΛ, and H0. We find good match to the metallicity data from the damped Lyα systems and the evolution of the luminosity density out to z≃1. Likewise, our models produce good fits for low values of Ω to the deep number counts of galaxies in all bands where data are available; this is done without assuming existence of extra populations of galaxies at high z. Our models also match the data on the redshift distribution of galaxy counts in B and K bands. They also provide good fits to the observed colors. We compute the predicted mean levels and angular distribution of the cosmic infrared background produced from the early evolution of galaxies. The predicted fluxes and fluctuations are still below the current observational limits, but not by a large factor. Finally, we find that the recent detection of the diffuse extragalactic light in the visible bands requires for our models a high redshift of galaxy formation, zf≥(3-4); otherwise, the produced flux of the extragalactic light at optical bands exceeds the current observational limits.
Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons

This paper explores the preference-based top-$K$ rank aggregation problem. Suppose that a collection of items is repeatedly compared in pairs, and one wishes to recover a consistent ordering that emphasizes the top-$K$ ranked items, based on partially revealed preferences. We focus on the Bradley-Terry-Luce (BTL) model that postulates a set of latent preference scores underlying all items, where the odds of paired comparisons depend only on the relative scores of the items involved. We characterize the minimax limits on identifiability of top-$K$ ranked items, in the presence of random and non-adaptive sampling. Our results highlight a separation measure that quantifies the gap of preference scores between the $K^{\text{th}}$ and $(K+1)^{\text{th}}$ ranked items. The minimum sample complexity required for reliable top-$K$ ranking scales inversely with the separation measure irrespective of other preference distribution metrics. To approach this minimax limit, we propose a nearly linear-time ranking scheme, called \emph{Spectral MLE}, that returns the indices of the top-$K$ items in accordance to a careful score estimate. In a nutshell, Spectral MLE starts with an initial score estimate with minimal squared loss (obtained via a spectral method), and then successively refines each component with the assistance of coordinate-wise MLEs. Encouragingly, Spectral MLE allows perfect top-$K$ item identification under minimal sample complexity. The practical applicability of Spectral MLE is further corroborated by numerical experiments.
A FULLY BAYESIAN METHOD FOR JOINTLY FITTING INSTRUMENTAL CALIBRATION AND X-RAY SPECTRAL MODELS

Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is “pragmatic” in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use a principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.
An Agile Development Cycle of a Web-Based Memory Intervention Program for Healthy Older Adults

The Memory and Aging Program is an in-person psychoeducation intervention for healthy older adults provided at Baycrest Health Sciences. The program has been shown to significantly increase participants' memory knowledge, strategy use, and satisfaction with their memory, promote healthier lifestyle behaviors, and decrease intentions to seek unnecessary medical attention. To increase outreach, a web-based version of the program was created through an agile development cycle: an iterative process involving end-users’ feedback. The current thesis outlines this process according to the four translational (T) phases of the Clinical and Translational Research Spectrum. First, an overview of the design phase (T1) is provided. In the T2 phase, 26 older adults participated in piloting of individual modules. Additionally, 20 older adults completed the program in its entirety from their homes (T3). Qualitative feedback, results of memory measures, lessons learned for tailoring the e-learning experience to older adults, and next steps (T4) are discussed.
ProteusTM: Abstraction Meets Performance in Transactional Memory

The Transactional Memory (TM) paradigm promises to greatly simplify the development of concurrent applications. This led, over the years, to the creation of a plethora of TM implementations delivering wide ranges of performance across workloads. Yet, no universal implementation fits each and every workload. In fact, the best TM in a given workload can reveal to be disastrous for another one. This forces developers to face the complex task of tuning TM implementations, which significantly hampers their wide adoption. In this paper, we address the challenge of automatically identifying the best TM implementation for a given workload. Our proposed system, ProteusTM, hides behind the TM interface a large library of implementations. Underneath, it leverages a novel multi-dimensional online optimization scheme, combining two popular learning techniques: Collaborative Filtering and Bayesian Optimization. We integrated ProteusTM in GCC and demonstrate its ability to switch between TMs and adapt several configuration parameters (e.g., number of threads). We extensively evaluated ProteusTM, obtaining average performance <3% from optimal, and gains up to 100x over static alternatives.
On packing R-trees

We propose new R-tree packing techniques for static databases. Given a collection of rect-angles, we sort them and we build the R-tree bottom-up. There are several ways to sort the rectangles; the innovation of this work is the use of fractals, and speci(cid:12)cally the hilbert curve, to achieve better ordering of the rectangles and eventually better packing. We proposed and implemented several variations and performed experiments on synthetic, as well as real data (TIGER (cid:12)les from the U.S. Bureau of Census). The winning variation (`2D-c') was the one that sorts the rectangles according to the hilbert value of the center. This variation consistently outperforms the packing method of Roussopoulos and Leifker [24], as well as other R-tree variants. The performance gain of the our method seems to increase with the skeweness of the data distribution; speci(cid:12)cally, on the (highly skewed) TIGER dataset, it achieves up to 58% improvement in response time over the older packing algorithm and 36% over the best known R-tree variant. We also, introduce an analytical formula to compute the average response time of a range query as a function of the geometric characteristics of the R-tree.
Transcriptional Profiling of MEq-Dependent Genes in Marek’s Disease Resistant and Susceptible Inbred Chicken Lines

Marek’s disease (MD) is an economically significant disease in chickens caused by the highly oncogenic Marek’s disease virus (MDV). Understanding the genes and biological pathways that confer MD genetic resistance should lead towards the development of more disease resistant commercial poultry flocks or improved MD vaccines. MDV mEq, a bZIP transcription factor, is largely attributed to viral oncogenicity though only a few host target genes have been described, which has impeded our understanding of MDV-induced tumorigenesis. Given the importance of mEq in MDV-induced pathogenesis, we explored the role of mEq in genetic resistance to MDV. Using global transcriptome analysis and cells from MD resistant or susceptible birds, we compared the response to infection with either wild type MDV or a nononcogenic recombinant lacking mEq. As a result, we identified a number of specific genes and pathways associated with either MD resistance or susceptibility. Additionally, integrating prior information from ChIP-seq, microarray analysis, and SNPs exhibiting allele-specific expression (ASE) in response to MDV infection, we were able to provide evidence for 24 genes that are polymorphic within mEq binding sites are likely to account for gene expression in an allele-specific manner and potentially for the underlying genetic differences in MD incidence.
ESO imaging survey - Deep public survey: Multi-color optical data for the Chandra Deep Field South

This paper presents multi-passband optical data obtained from observations of the Chandra Deep Field South (CDF-S), located at 3 h 32 m , 2748 0 . The observations were conducted at the ESO/MPG 2.2 m telescope at La Silla using the 8k 8k Wide-Field Imager (WFI). This data set, taken over a period of one year, represents the rst eld to be completed by the ongoing Deep Public Survey (DPS) being carried out as a part of the ESO Imaging Survey (EIS) project. This paper describes the optical observations, the techniques employed for un-supervised pipeline processing and the general characteristics of the nal data set. Image processing has been performed using multi-resolution image decomposition techniques adapted to the EIS pipeline. The automatic processing steps include standard de-bias and flat-eld, automatic removal of satellite tracks, de-fringing/sky-subtraction, image stacking/mosaicking and astrometry. Stacking of dithered images is carried out using pixel-based astrometry which enables the ecient removal of cosmic rays and image defects, yielding remarkably clean nal images. The nal astrometric calibration is based on a pre-release of the GSC-II catalog and has an estimated intrinsic accuracy of <0.10 arcsec, with all passbands sharing the same solution. The paper includes data taken in six dierent lters (U 0 UBVRI). The data cover an area of about 0.25 square degrees reaching 5 limiting magnitudes of U 0 AB =2 6:0, UAB =2 5:7, BAB =2 6:4, VAB =2 5:4;RAB =2 5: 5a nd IAB = 24.7 mag, as measured within a 2FWHM aperture. The optical data covers an area of 0.1 square degrees for which moderately deep observations in two near-infrared bands are also available, reaching 5 limiting magnitudes of JAB 23: 4a ndKAB 22:6. The current optical/infrared data also fully encompass the region of the deep X-ray observations recently completed by the Chandra telescope. The optical data presented here, as well as the infrared data released earlier, are publicly available world-wide in the form of fully calibrated pixel and associated weight maps and source lists extracted in each passband. These data can be requested through the URL \http://www.eso. org/eis".
Prevalence and gender differences in symptomatology of posttraumatic stress disorder and depression among Iraqi Yazidis displaced into Turkey

Background Posttraumatic stress disorder (PTSD) and depression are common among populations displaced due to large-scale political conflicts and war. Objective The aim of this study is to investigate the prevalence and gender-based differences in symptoms of PTSD and depression among Iraqi Yazidis displaced into Turkey. Method The study was conducted on 238 individuals who were evaluated using the Structured Clinical Interview for DSM-IV (SCID-I) and the Stressful Life Events Screening Questionnaire. Results Of the participants, 42.9% met the DSM-IV diagnostic criteria for PTSD, 39.5% for major depression, and 26.4% for both disorders. More women than men suffered from PTSD and major depression. More women than men with PTSD or depression reported having experienced or witnessed the death of a spouse or child. Women with PTSD reported flashbacks, hypervigilance, and intense psychological distress due to reminders of trauma more frequently than men. Men with PTSD reported feelings of detachment or estrangement from others more frequently than women. More depressive women than men reported feelings of guilt or worthlessness. Conclusions PTSD and major depression affected women more frequently than men. While women tended to respond to traumatic stress by undermodulation of emotions and low self-esteem, men tended to respond by overmodulation of emotions. Rather than being a derivative of sex differences, this complementary diversity in response types between genders seems to be shaped by social factors in consideration of survival under extreme threat.