Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Cytomegalovirus pp65- and Immediate Early 1 Antigen-Specific HLA Class I-Restricted Cytotoxic T Cell Responses Induced by Cross-Presentation of Viral Antigens1

Dendritic cells (DCs) play a pivotal role in the development of anti-viral CD8+ CTL responses. This is straightforward if they are directly infected with virus, but is less clear in response to viruses that cannot productively infect DCs. Human CMV (HCMV) shows strain-specific cell tropism: fibroblast (Fb)-adapted laboratory strains (AD169) and recent clinical isolates do not infect DCs, whereas endothelial cell-adapted strains (TB40/E) result in productive lytic DC infection. However, we show here that uninfected DCs induce CD8+ T cell cytotoxicity and IFN-γ production against HCMV pp65 and immediate early 1 Ags following in vitro coculture with HCMV-AD169-infected Fbs, regardless of the HLA type of these Fbs. CD8+ T cell stimulation was inhibited by pretreatment of DCs with cytochalasin B or brefeldin A, indicating a phagosome/endosome to cytosol pathway. HCMV-infected Fbs were not apoptotic as measured by annexin V binding, and induction of apoptosis of infected Fbs in vitro did not augment CTL induction by DCs, suggesting a mechanism other than apoptosis in the initiation of cross-presentation. Furthermore, HCMV-infected Fbs provided a maturation signal for immature DCs during coculture, as evidenced by increased CD83 and HLA class II expression. Cross-presentation of HCMV Ags by host DCs enables these professional APCs to bypass some of the evasion mechanisms HCMV has developed to avoid T cell recognition. It may also serve to explain the presence of immediate early 1 Ag-specific CTLs in the face of pp65-induced inhibition of Ag presentation at the level of the infected cell.
Discriminant Hyper-Laplacian projections with its application to face recognition

Discriminant Locality Preserving Projections (DLPP) is one of the most influential supervised subspace learning algorithms that considers both discriminative and geometric (manifold) information. There is an obvious drawback of DLPP that it only considers the pairwise geometric relationship of samples. However, in many real-world issues, relationships among the samples are often more complex than pairwise. Naively squeezing the complex into pairwise ones will inevitably lead to loss of some information, which are crucial for classification and clustering. We address this issue via using the Hyper-Laplacian instead of the regular Laplacian in DLPP, which only can depict the pairwise relationship. This new DLPP algorithm is exactly a generalization of DLPP and we name it Discriminant Hyper-Laplacian Projection (DHLP). Five popular face databases are adopted for validating our work. The results demonstrate the superiority of DHLP over DLPP, particularly in face recognition in the wild.
Fully automatic, real-time detection of facial gestures from generic video

A technique for the detection of facial gestures from low resolution video sequences is presented. The technique builds upon the automatic 3D head tracker formulation of [M. La Cascia et al., 2000]. The tracker is based on the registration of a texture-mapped cylindrical model. Facial gesture analysis is performed in the texture map by assuming that the residual registration error can be modeled as a linear combination of facial motion templates. Two formulations are proposed and tested. In one formulation, the head and facial motion are estimated in a single, combined linear system. In the other formulation, head motion and then facial motion are estimated in a two-step process. The two-step approach significantly yields better accuracy in facial gesture analysis. The system is demonstrated in detecting two types of facial gestures: "mouth opening" and "eyebrows raising. " On a dataset with lots of head motion, the two-step algorithm achieved a recognition accuracy of 70% for the "mouth opening" and an accuracy of 66% for "eyebrows raising" gestures. The algorithm can reliably track and classify facial gestures without any user intervention and runs in real-time.
Elevation-Dependent Temperature Trends in the Rocky Mountain Front Range: Changes over a 56- and 20-Year Record

Determining the magnitude of climate change patterns across elevational gradients is essential for an improved understanding of broader climate change patterns and for predicting hydrologic and ecosystem changes. We present temperature trends from five long-term weather stations along a 2077-meter elevational transect in the Rocky Mountain Front Range of Colorado, USA. These trends were measured over two time periods: a full 56-year record (1953–2008) and a shorter 20-year (1989–2008) record representing a period of widely reported accelerating change. The rate of change of biological indicators, season length and accumulated growing-degree days, were also measured over the 56 and 20-year records. Finally, we compared how well interpolated Parameter-elevation Regression on Independent Slopes Model (PRISM) datasets match the quality controlled and weather data from each station. Our results show that warming signals were strongest at mid-elevations over both temporal scales. Over the 56-year record, most sites show warming occurring largely through increases in maximum temperatures, while the 20-year record documents warming associated with increases in maximum temperatures at lower elevations and increases in minimum temperatures at higher elevations. Recent decades have also shown a shift from warming during springtime to warming in July and November. Warming along the gradient has contributed to increases in growing-degree days, although to differing degrees, over both temporal scales. However, the length of the growing season has remained unchanged. Finally, the actual and the PRISM interpolated yearly rates rarely showed strong correlations and suggest different warming and cooling trends at most sites. Interpretation of climate trends and their seasonal biases in the Rocky Mountain Front Range are dependent on both elevation and the temporal scale of analysis. Given mismatches between interpolated data and the directly measured station data, we caution against an over-reliance on interpolation methods for documenting local patterns of climatic change.
Biogeosciences Effects of free atmospheric CO 2 enrichment ( FACE ) , N fertilization and poplar genotype on the physical protection of carbon in the mineral soil of a polar plantation after five years

Free air CO2 enrichment (FACE) experiments in aggrading forests and plantations have demonstrated significant increases in net primary production (NPP) and C storage in forest vegetation. The extra C uptake may also be stored in forest floor litter and in forest soil. After five years of FACE treatment at the EuroFACE short rotation poplar plantation, the increase of total soil C% was larger under elevated than under ambient CO2. However, the fate of this additional C allocated belowground remains unclear. The stability of soil organic matter is controlled by the chemical structure of the organic matter and the formation of micro-aggregates (within macro-aggregates) in which organic matter is stabilized and protected. FACE and N-fertilization treatment did not affect the microand macro-aggregate weight, C or N fractions obtained by wet sieving. However, Populus euramericanaincreased the small macro-aggregate and free micro-aggregate weight and C fractions. The obtained macro-aggregates were broken up in order to isolate recently formed microaggregates within macro-aggregates (iM-micro-aggregates). FACE increased the iM-micro-aggregate weight and C fractions, although not significantly. This study reveals that FACE did not affect the formation of aggregates. We did, however, observe a trend of increased stabilization and protection of soil C in micro-aggregates formed within macroaggregates under FACE. Moreover, the largest effect on aggregate formation was due to differences in species, i.e. poplar genotype.P. euramericanaincreased the formation of free micro-aggregates which means that more newly inCorrespondence to: M. R. Hoosbeek (marcel.hoosbeek@wur.nl) corporated soil C was stabilized and protected. The choice of species in a plantation, or the effect of global change on species diversity, may therefore affect the stabilization and protection of C in soils.
Learning Social Networks from Web Documents Using Support Vector Classifiers

Automatic generation of a social network requires extracting pair-wise relations of the individuals. In this research, learning social network from incomplete relationship data is proposed. It is assumed that only a small subset of relations between the individuals is known. With this assumption, the social network extraction is translated into a text classification problem. The relations between two individuals are modeled by merging their document vectors and the given relations are used as labels of training data. By this transformation, a text classifier such as SVM is used for learning the unknown relations. We show that there is a link between the intrinsic sparsity of social networks and class distribution imbalance of the training data. In order to re-balance the unbalanced training data, a minority class down-sampling strategy is employed. The proposed framework is applied to a true FOAF (friend of a friend) database and evaluated by the macro-averaged F-measure
The Abscisic Acid-Responsive Kinase PKABA1 Interacts with a Seed-Specific Abscisic Acid Response Element-Binding Factor, TaABF, and Phosphorylates TaABF Peptide Sequences1

The abscisic acid (ABA)-induced protein kinase PKABA1 is present in dormant seeds and is a component of the signal transduction pathway leading to ABA-suppressed gene expression in cereal grains. We have identified a member of the ABA response element-binding factor (ABF) family of basic leucine zipper transcription factors from wheat (Triticum aestivum) that is specifically bound by PKABA1. This protein (TaABF) has highest sequence similarity to the Arabidopsis ABA response protein ABI5. In two-hybrid assays TaABF bound only to PKABA1, but not to a mutant version of PKABA1 lacking the nucleotide binding domain, suggesting that binding of TaABF requires prior binding of ATP as would be expected for binding of a protein substrate by a protein kinase. TaABF mRNA accumulated together with PKABA1 mRNA during wheat grain maturation and dormancy acquisition and TaABFtranscripts increased transiently during imbibition of dormant grains. In contrast to PKABA1 mRNA, TaABF mRNA is seed specific and did not accumulate in vegetative tissues in response to stress or ABA application. PKABA1 produced in transformed cell lines was able to phosphorylate synthetic peptides representing three specific regions of TaABF. These data suggest that TaABF may serve as a physiological substrate for PKABA1 in the ABA signal transduction pathway during grain maturation, dormancy expression, and ABA-suppressed gene expression.
Pectobacterium atrosepticum and Pectobacterium carotovorum Harbor Distinct, Independently Acquired Integrative and Conjugative Elements Encoding Coronafacic Acid that Enhance Virulence on Potato Stems

Integrative and conjugative elements (ICEs) play a central role in the evolution of bacterial virulence, their transmission between bacteria often leading to the acquisition of virulence factors that alter host range or aggressiveness. Much is known about the functions of the virulence determinants that ICEs harbor, but little is understood about the cryptic effects of ICEs on their host cell. In this study, the importance of horizontally acquired island 2 (HAI2), an ICE in the genome of Pectobacterium atrosepticum SCRI1043, was studied using a strain in which the entire ICE had been removed by CRISPR-Cas-mediated genome editing. HAI2 encodes coronafacic acid, a virulence factor that enhances blackleg disease of potato stems caused by P. atrosepticum SCRI1043. As expected, deletion of HAI2 resulted in reduced blackleg symptoms in potato stems. A subsequent screen for HAI2-related ICEs in other strains of the Pectobacterium genus revealed their ubiquitous nature in P. atrosepticum. Yet, HAI2-related ICEs were only detected in the genomes of a few P. carotovorum strains. These strains were notable as blackleg causing strains belonging to two different subspecies of P. carotovorum. Sequence analysis of the ICEs in different strains of both P. atrosepticum and P. carotovorum confirmed that they were diverse and were present in different locations on the genomes of their bacterial host, suggesting that the cfa cluster was probably acquired independently on a number of occasions via chromosomal insertion of related ICEs. Excision assays also demonstrated that the ICEs in both P. atrosepticum and P. carotovorum are mobilized from the host chromosome. Thus, the future spread of these ICEs via lateral gene transfer might contribute to an increase in the prevalence of blackleg-causing strains of P. carotovorum.
On Some Double Circulant Binary Extended Quadratic Residue Codes

Let p be a prime such that p = - 1 (mod 8). Let k = (p + 1)/2 and write k = 2<sup>m</sup>q, q odd. Let S -F<sub>2</sub>[x]/(1 + x<sup>k</sup>) where F<sub>2</sub> is the Galois field of two elements. We prove that the binary extended quadratic residue codes of length 2k have a double circulant presentation in the following cases: (1) q = 1, and (2) let X be the class of x in S, and alpha the algebra of automorphisms on S that sends X' to X<sup>-1</sup>. Factor 1 + x<sup>q</sup> over F<sub>2</sub> into irreducible factors. If the class of those factors in S is fixed by delta up to a unit, then the codes have a double circulant presentation.
Learning to Predict the Future using Web Knowledge and Dynamics

Mark Twain famously said that "the past does not repeat itself, but it rhymes. " In the spirit of this reflection, we present novel algorithms and methods for leveraging large-scale digital histories and human knowledge mined from the Web to make real-time predictions about the likelihoods of future human and natural events of interest. The Web is a dynamic being, with constantly updating content, which is entangled with sophisticated user behaviors and interactions. Some of these behaviors have the ability to convey current trends in the present, e.g., economical growth (predicting automobile sales based on query volume [6]), popular movies [4], and political unrest [1, 3, 5]. We mine the ever-changing Web content and user Web behavior. We show that, not only the dynamics itself can be predicted, but also that it can be used for future real-world event prediction. We mine decades of news reports (1851 - 2010) from the New York Times (NYT), and describe how we can learn to predict the future by generalizing sets of concrete transitions in sequences of reported news events. In addition to the news corpora, we leverage data from freely available Web resources, including Wikipedia, FreeBase, OpenCyc, and GeoNames, via the LinkedData platform [2]. The goal is to build predictive models that generalize from specific sets of sequences of events to provide likelihoods of future outcomes, based on patterns of evidence observed in near-term Web activities. We propose the methods as a means of generating actionable forecasts in advance of the occurrence of target events in the world. This thesis is one of the first works to demonstrate general, unrestricted artificial-intelligence prediction capacity. We present methods derived from heterogeneous Web sources to make knowledge-intensive reasoning about causality and future event prediction, using both automatic feature extraction and novel algorithms for generalizing over historical examples.
Spindle dynamics and cell cycle regulation of dynein in the budding yeast, Saccharomyces cerevisiae

We have used time-lapse digital- and video-enhanced differential interference contrast (DE-DIC, VE-DIC) microscopy to study the role of dynein in spindle and nuclear dynamics in the yeast Saccharomyces cerevisiae. The real-time analysis reveals six stages in the spindle cycle. Anaphase B onset appears marked by a rapid phase of spindle elongation, simultaneous with nuclear migration into the daughter cell. The onset and kinetics of rapid spindle elongation are identical in wild type and dynein mutants. In the absence of dynein the nucleus does not migrate as close to the neck as in wild-type cells and initial spindle elongation is confined primarily to the mother cell. Rapid oscillations of the elongating spindle between the mother and bud are observed in wild-type cells, followed by a slower growth phase until the spindle reaches its maximal length. This stage is protracted in the dynein mutants and devoid of oscillatory motion. Thus dynein is required for rapid penetration of the nucleus into the bud and anaphase B spindle dynamics. Genetic analysis reveals that in the absence of a functional central spindle (ndcl), dynein is essential for chromosome movement into the bud. Immunofluorescent localization of dynein-beta- galactosidase fusion proteins reveals that dynein is associated with spindle pole bodies and the cell cortex: with spindle pole body localization dependent on intact microtubules. A kinetic analysis of nuclear movement also revealed that cytokinesis is delayed until nuclear translocation is completed, indicative of a surveillance pathway monitoring nuclear transit into the bud.
SMRT-mediated co-shuttling enables export of class IIa HDACs independent of their CaM kinase phosphorylation sites

The Class IIa histone deacetylases (HDAC)4 and HDAC5 play a role in neuronal survival and behavioral adaptation in the CNS. Phosphorylation at 2/3 N‐terminal sites promote their nuclear export. We investigated whether non‐canonical signaling routes to Class IIa HDAC export exist because of their association with the co‐repressor Silencing Mediator Of Retinoic And Thyroid Hormone Receptors (SMRT). We found that, while HDAC5 and HDAC4 mutants lacking their N‐terminal phosphorylation sites (HDAC4MUT, HDAC5MUT) are constitutively nuclear, co‐expression with SMRT renders them exportable by signals that trigger SMRT export, such as synaptic activity, HDAC inhibition, and Brain Derived Neurotrophic Factor (BDNF) signaling. We found that SMRT's repression domain 3 (RD3) is critical for co‐shuttling of HDAC5MUT, consistent with the role for this domain in Class IIa HDAC association. In the context of BDNF signaling, we found that HDAC5WT, which was more cytoplasmic than HDAC5MUT, accumulated in the nucleus after BDNF treatment. However, co‐expression of SMRT blocked BDNF‐induced HDAC5WT import in a RD3‐dependent manner. In effect, SMRT‐mediated HDAC5WT export was opposing the BDNF‐induced HDAC5 nuclear accumulation observed in SMRT's absence. Thus, SMRT's presence may render Class IIa HDACs exportable by a wider range of signals than those which simply promote direct phosphorylation.
Query construction for related document search based on user annotations

We often use various services for creating bookmarks, tags, highlights and other types of annotations while surfing the Web or just reading electronic documents. These annotations represent additional information on particular information source. We proposed a method for query construction to search for related documents to currently studied document. We use the document content where we concentrate on user created annotations as indicators of user's interest in particular parts of the document. Our method for query construction is based on spreading activation in a graph created from the document content. We evaluated proposed method within a service called Annota, which allows users to insert various types of annotations into web pages and PDF documents displayed in the web browser. We analyzed properties of various types of annotations inserted by users of Annota into documents. Based on these properties, we also performed a simulation to determine optimal parameters and compare proposed method against commonly used tf-idf based method.
Engineered split in Pfu DNA polymerase fingers domain improves incorporation of nucleotide γ-phosphate derivative

Using compartmentalized self-replication (CSR), we evolved a version of Pyrococcus furiosus (Pfu) DNA polymerase that tolerates modification of the γ-phosphate of an incoming nucleotide. A Q484R mutation in α-helix P of the fingers domain, coupled with an unintended translational termination-reinitiation (split) near the finger tip, dramatically improve incorporation of a bulky γ-phosphate-O-linker-dabcyl substituent. Whether synthesized by coupled translation from a bicistronic (−1 frameshift) clone, or reconstituted from separately expressed and purified fragments, split Pfu mutant behaves identically to wild-type DNA polymerase with respect to chromatographic behavior, steady-state kinetic parameters (for dCTP), and PCR performance. Although naturally-occurring splits have been identified previously in the finger tip region of T4 gp43 variants, this is the first time a split (in combination with a point mutation) has been shown to broaden substrate utilization. Moreover, this latest example of a split hyperthermophilic archaeal DNA polymerase further illustrates the modular nature of the Family B DNA polymerase structure.
Convolution Kernel over Packed Parse Forest

This paper proposes a convolution forest kernel to effectively explore rich structured features embedded in a packed parse forest. As opposed to the convolution tree kernel, the proposed forest kernel does not have to commit to a single best parse tree, is thus able to explore very large object spaces and much more structured features embedded in a forest. This makes the proposed kernel more robust against parsing errors and data sparseness issues than the convolution tree kernel. The paper presents the formal definition of convolution forest kernel and also illustrates the computing algorithm to fast compute the proposed convolution forest kernel. Experimental results on two NLP applications, relation extraction and semantic role labeling, show that the proposed forest kernel significantly outperforms the baseline of the convolution tree kernel.
Home-field advantage or a matter of ambiguity aversion? Local bias among German individual investors

This paper investigates whether familiarity induced by ambiguity aversion can help explaining the local bias phenomenon among individual investors. Using geographic closeness as a proxy for investor familiarity, we find that investors pull out of (unfamiliar) remote stocks and pour into (familiar) local stocks during times of increased market uncertainty. Moreover, the magnitude of this ‘flight to familiarity’ increases in the spread of an investor's ambiguity (about expected returns) between local and remote stocks. Our results prove robust to a number of alternative explanations of local bias. Specifically, we rule out a ‘home-field advantage’, where investors are able to translate information advantages about nearby companies into excess returns on their local stockholdings. We conclude that individual investors’ local bias is induced by ambiguity aversion in the portfolio selection process rather than a trading strategy based on superior information about local companies.