Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of PA-N terminal domain of Influenza A polymerase reveals sequence specific RNA cleavage

Influenza virus uses a unique cap-snatching mechanism characterized by hijacking and cleavage of host capped pre-mRNAs, resulting in short capped RNAs, which are used as primers for viral mRNA synthesis. The PA subunit of influenza polymerase carries the endonuclease activity that catalyzes the host mRNA cleavage reaction. Here, we show that PA is a sequence selective endonuclease with distinct preference to cleave at the 3′ end of a guanine (G) base in RNA. The G specificity is exhibited by the native influenza polymerase complex associated with viral ribonucleoprotein particles and is conferred by an intrinsic G specificity of the isolated PA endonuclease domain PA-Nter. In addition, RNA cleavage site choice by the full polymerase is also guided by cap binding to the PB2 subunit, from which RNA cleavage preferentially occurs at the 12th nt downstream of the cap. However, if a G residue is present in the region of 10–13 nucleotides from the cap, cleavage preferentially occurs at G. This is the first biochemical evidence of influenza polymerase PA showing intrinsic sequence selective endonuclease activity.
Treatment of Adolescent and Young Adults with Acute Lymphoblastic Leukemia

The primary objective of this review was to update and discuss the current concepts and the results of the treatment of acute lymphoblastic leukemia (ALL) in adolescents and young adults (AYA). After a brief consideration of the epidemiologic and clinicobiologic characteristics of ALL in the AYA population, the main retrospective comparative studies stating the superiority of pediatric over adult-based protocols were reviewed. The most important prospective studies in young adults using pediatric inspired or pediatric unmodified protocols were also reviewed emphasizing their feasibility at least up to the age of 40 yr and their promising results, with event-free survival rates of 60–65% or greater. Results of trials from pediatric groups have shown that the unfavourable prognosis of adolescents is no more adequate. The majority of the older adolescents with ALL can be cured with risk-adjusted and minimal residual disease-guided intensive chemotherapy, without stem cell transplantation. However, some specific subgroups, which are more frequent in adolescents than in children (e.g., early pre-T, iAMP21, and BCR-ABL-like), deserve particular attention. In summary, the advances in treatment of ALL in adolescents have been translated to young adults, and that explains the significant improvement in survival of these patients in recent years.
Morphological Development of Larvae and Juveniles of Acanthopagrus schlegeli

ABSTRACT Newly hatched black porgy larvae (Acanthopagrus schlegeli) swam to the surface, with the mouth and anus still closed and were 1.90–2.11 mm (mean, 2.0 mm) in total length (TL). The larvae were 2.71–2.94 mm TL (mean, 2.82 mm) on day 2 after hatching. At this time, about two-thirds of the yolk was absorbed, the bladder and intestines had formed, and the mouth and anus were open. Total length was 4.32–4.66 mm (mean, 4.45 mm) at the post-larval stage on days 5–6 after hatching, and the yolk and oil globule were almost absorbed. The end of the notochord began to flex, and 6–8 caudal fin rays were visible. The larvae were 15.37–16.1 mm TL (mean, 15.83 mm) at the juvenile stage on days 30–32 after hatching, and the number of rays in all fins was completely revealed.
Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes

Identification and comparison of nonlinear dynamical system models using noisy and sparse experimental data is a vital task in many fields, however current methods are computationally expensive and prone to error due in part to the nonlinear nature of the likelihood surfaces induced. We present an accelerated sampling procedure which enables Bayesian inference of parameters in nonlinear ordinary and delay differential equations via the novel use of Gaussian processes (GP). Our method involves GP regression over time-series data, and the resulting derivative and time delay estimates make parameter inference possible without solving the dynamical system explicitly, resulting in dramatic savings of computational time. We demonstrate the speed and statistical accuracy of our approach using examples of both ordinary and delay differential equations, and provide a comprehensive comparison with current state of the art methods.
Pre-vocational education in the curriculum: the case of Norwegian lower secondary education

ABSTRACT This article investigates the composition of the Norwegian lower secondary school curriculum with a special emphasis on pre-vocational education from a contemporary perspective. The data consist of four official national curricula enacted from the 1970s until the present. Despite differences between the curricula, the main structure of school subjects has remained stable over time. Norwegian lower secondary school curricula mainly include academic subjects, even though pre-vocational education is, to varying degrees, present in all curricula, especially amongst elective subjects. This consolidated position of academic subjects results in a consistency in the composition of the curriculum. Curriculum change is most likely to happen amongst electives and is related to changes in policy making and societal changes. Pre-vocational education is mainly included in the first and current curriculum contrary to the second and third curriculum. These findings indicate that the international policy agenda and its emphasis on the relevance of education through stressing the linkage between education and the world of work only has a minor impact on Norwegian curricula. Further, the allocation of teaching hours shows that the status of pre-vocational subjects is low compared to that of academic subjects. International policies emphasizing basic skills strengthen the academic subjects even further.
An Analysis of the Server Characteristics and Resource Utilization in Google Cloud

Understanding the resource utilization and server characteristics of large-scale systems is crucial if service providers are to optimize their operations whilst maintaining Quality of Service. For large-scale data enters, identifying the characteristics of resource demand and the current availability of such resources, allows system managers to design and deploy mechanisms to improve data enter utilization and meet Service Level Agreements with their customers, as well as facilitating business expansion. In this paper, we present a large-scale analysis of server resource utilization and a characterization of a production Cloud data enter using the most recent data enter trace logs made available by Google. We present their statistical properties, and a comprehensive coarse-grain analysis of the data, including submission rates, server classification, and server resource utilization. Additionally, we perform a fine-grained analysis to quantify the resource utilization of servers wasted due to the early termination of tasks. Our results show that data enter resource utilization remains relatively stable at between 40 - 60%, that the degree of correlation between server utilization and Cloud workload environment varies by server architecture, and that the amount of resource utilization wasted varies between 4.53 - 14.22% for different server architectures. This provides invaluable real-world empirical data for Cloud researchers in many subject areas.
Does Consumer Empathy Influence Consumer Responses to Strategic Corporate Social Responsibility? The Dual Mediation of Moral Identity

The present study examined consumer responses to strategic corporate social responsibility (CSR) from the perspectives of consumer moral emotions (empathy) and cognition (moral identity), and investigated charitable activities conducted by convenience stores in Taiwan from theoretical and practical perspectives. The research method involved a comparison between two actual charitable activities conducted by convenience stores, namely “donation platform services” and “cause-related marketing”. A questionnaire was distributed into four regions spanning southern to northern Taiwan by using a convenient sampling method, and 332 valid responses were collected. The present study employed structural equation modelling to verify its hypotheses. In terms of theoretical contributions, the present study constructed two theoretical models and subsequently verified that empathy influences moral identity; this constitutes a major contribution to investigations of the causal relationship between moral emotions and cognitive theory. In practice, the present study recommends that convenience stores implement more cause-related marketing to reduce consumer suspicions that firms are motivated purely by profit and increase consumer trust in firms. Subsequent studies are recommended to conduct in-depth investigations of the underlying causes of moral identity internalization and symbolization generating different responses in consumers, as well as other possible situational variables.
A Possible Bias Model for Quasars

We propose that the majority of quasars at redshift z~1-5 formed in the environment of newborn collapsed halos with one-dimensional velocity dispersion σ1dv~400 km s-1. The harboring coefficient f of quasars per halo and the lifetime of quasars depend only on local processes; they are not modulated by the density inhomogeneities on scales larger than the size of the halos. Thus, the bias of quasars on scales larger than the size of these halos is mainly determined by the parameter σv, which is used for quasar environment identification. With this model, the popular structure formation models, like the standard cold dark matter (SCDM) and the low-velocity CDM, can be fairly well reconciled with the data of quasars, including (1) observed features of the environment for quasars, (2) the redshift evolution of quasar abundance, and (3) the two-point correlation functions of quasars. This bias model predicts that the correlation function of quasars does not significantly evolve or only slightly increases with redshift.
A subject-independent pattern-based Brain-Computer Interface

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.
Revisiting the viability to allow dual-class share structure companies to list in the financial market of Hong Kong

The request of Alibaba, China’s largest e-commerce company, to allow a self-selected group of its past and present management known as the ‘partners’ the right to nominate a majority of the directors in its negotiation with the Hong Kong Stock Exchange (HKEx) for an initial public offering (IPO) in 2013 reignited a new round of debate over the one share, one vote policy, which has survived for three decades in Hong Kong. Alibaba’s IPO application to list on the HKEx was eventually rejected which ultimately led to the company’s decision to list on the New York Stock Exchange. In late 2017, the debate on whether companies with dual-class share (DCS) structure should be allowed to list in Hong Kong re-emerged as the HKEx has announced that it would amend its listing rules to enable companies with DCS structure to list on its exchange, subject to certain safeguards and restrictions. This article examines what measures Hong Kong could adopt to allow companies with DCS structure to list on its exchange despite legal and institutional shortcomings of its financial market. In doing so, it will also make reference to other major financial markets in the world and examine how other jurisdictions have handled the issue of DCS structure companies.
Event-related potentials to schematic faces in social phobia

Social phobia has been associated with an attentional bias for angry faces. This study aimed at further characterising this attentional bias by investigating reaction times, heart rates, and ERPs while social phobics, spider phobics, and controls identified either the colour or the emotional quality of angry, happy, or neutral schematic faces. The emotional expression of angry faces did not interfere with the processing of their colour in social phobics, and heart rate, N170 amplitude and parietal late positive potentials (LPPs) of these subjects were also no different from those of non-phobic subjects. However, social phobics showed generally larger P1 amplitudes than non-phobic controls with spider phobic subjects in between. No general threat advantage for angry faces was found. All groups identified neutral schematic faces faster and showed larger late positive amplitudes to neutral than to emotional faces. Furthermore, in all groups the N170 was modulated by the emotional quality of faces. This effect was most pronounced in the emotion identification task.
Reconstruction of primordial density fields

The Monge–Ampere–Kantorovich (MAK) reconstruction is tested against cosmological N-body simulations. Using only the present mass distribution sampled with particles, and the assumption of homogeneity of the primordial distribution, MAK recovers for each particle the non-linear displacement field between its present position and its Lagrangian position on a primordial uniform grid. To test the method, we examine a standard Lambda cold dark matter (ΛCDM) N-body simulation with Gaussian initial conditions and six models with non-Gaussian initial conditions: a χ2 model, a model with primordial voids and four weakly non-Gaussian models. Our extensive analyses of the Gaussian simulation show that the level of accuracy of the reconstruction of the non-linear displacement field achieved by MAK is unprecedented, at scales as small as ∼3 h−1 Mpc. In particular, it captures in a non-trivial way the non-linear contribution from gravitational instability, well beyond the Zel'dovich approximation. This is also confirmed by our analyses of the non-Gaussian samples. Applying the spherical collapse model to the probability distribution function of the divergence of the displacement field, we also show that from a well-reconstructed displacement field, such as that given by MAK, it is possible to accurately disentangle dynamical contributions induced by gravitational clustering from possible initial non-Gaussianities, allowing one to efficiently test the non-Gaussian nature of the primordial fluctuations. In addition, we test successfully a simple application of MAK using the Zel'dovich approximation to recover in real space the present-day peculiar velocity field on scales of 8 h−1 Mpc. Although non-trivial observational issues yet remain to be addressed, our numerical investigations suggest that MAK reconstruction represents a very promising tool to be applied to three-dimensional Galaxy catalogues.
Optical flow estimation using learned sparse model

Optical flow estimation is a fundamental and ill-posed problem in computer vision. To recover a dense flow field, appropriate spatial constraints have to be enforced. Recent advances exploit higher order spatial regularization, and achieve the top performance on the Middlebury benchmark. In this work, we revisit learning-based approach, and propose a learned sparse model to patch-wisely regularize the flow field. In particular, our method is based on multi-scale spatial regularization, which benefits from first-order spatial regularity and our learned, higher order sparse model. To obtain accurate flow estimation, we propose a sequential optimization scheme to solve the corresponding energy minimization problem. Moreover, as the errors in intermediate flow estimates are usually dense with large variations, we further propose flow-driven and image-driven approaches to address the problem of outliers. Experiments on the Middlebury benchmark show that our method is competitive with the state-of-the-art.
Dynamic Association of NUP98 with the Human Genome

Faithful execution of developmental gene expression programs occurs at multiple levels and involves many different components such as transcription factors, histone-modification enzymes, and mRNA processing proteins. Recent evidence suggests that nucleoporins, well known components that control nucleo-cytoplasmic trafficking, have wide-ranging functions in developmental gene regulation that potentially extend beyond their role in nuclear transport. Whether the unexpected role of nuclear pore proteins in transcription regulation, which initially has been described in fungi and flies, also applies to human cells is unknown. Here we show at a genome-wide level that the nuclear pore protein NUP98 associates with developmentally regulated genes active during human embryonic stem cell differentiation. Overexpression of a dominant negative fragment of NUP98 levels decreases expression levels of NUP98-bound genes. In addition, we identify two modes of developmental gene regulation by NUP98 that are differentiated by the spatial localization of NUP98 target genes. Genes in the initial stage of developmental induction can associate with NUP98 that is embedded in the nuclear pores at the nuclear periphery. Alternatively, genes that are highly induced can interact with NUP98 in the nuclear interior, away from the nuclear pores. This work demonstrates for the first time that NUP98 dynamically associates with the human genome during differentiation, revealing a role of a nuclear pore protein in regulating developmental gene expression programs.
Anatomy of the eye of the sperm whale ( Physeter macrocephalus L.)

Eyes of e ve sperm whales ( Physeter macrocephalus ) were investigated macro- and microscopically. The general anatomy corresponded well with previous reports on other cetacean species, as well as previous reports on the sperm whale eye. The sperm whale eye does not di Ver in any great respect from other odontocete eyes, except for the obvious larger size. The most prominent structures were a very thick sclera encapsulating the bulbus, a large, vascularized rete ophthalmica surrounding the optic nerve, and a massive musculus retractor bulbi . Lack of ciliary muscles was also noted as well as the presence of a choroid tapetum and giant ganglion cells in the retina. It is suggested that the anatomy of the sclera, ophthalmic rete and retractor muscle is linked to the ability of cetaceans to protrude and retract their eyes. The eye is retracted into the orbit by the retractor muscle with the thick sclera providing a e rm basis for attachment as well as protection from deformation. Space for the eye in the orbit is provided by drainage of the rete for blood. Protrusion could be facilitated by relaxation of the retractor and eyelid muscles and a ree lling of the rete with blood.
PEER-EFFECTS IN OBESITY AMONG PUBLIC SCHOOL CHILDREN: A GRADE-LEVEL ANALYSIS

We examine the role of peer effects in childhood obesity outcomes by investigating whether obesity rates among the highest graders in a public school has an effect on obesity rates among younger grades. We use a panel dataset with obesity prevalence measured at the grade level. Our data are from Arkansas public schools. Results provide evidence that changes in the obesity prevalence at the highest grade are associated with changes in obesity prevalence at younger grades. The magnitude of the peer effect depends on the type of school, and we find statistically significant peer effects in both elementary and high schools but not in middle schools. These effects are also larger in high schools than in elementary schools. We use falsification tests to provide evidence that these peer effects are more than just a statistical correlation or an association.
Prediction during statistical learning, and implications for the implicit/explicit divide

Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.
City users' classification with mobile phone data

Nowadays mobile phone data are an actual proxy for studying the users' social life and urban dynamics. In this paper we present the Sociometer, and analytical framework aimed at classifying mobile phone users into behavioral categories by means of their call habits. The analytical process starts from spatio-temporal profiles, learns the different behaviors, and returns annotated profiles. After the description of the methodology and its evaluation, we present an application of the Sociometer for studying city users of one small and one big city, evaluating the impact of big events in these cities.