Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Analysis of the Synonymous Codon Usage Patterns in Riemerella anatipestifer

Riemerella anatipestifer (RA) belongs to the Flavobacteriaceae family and can cause a septicemia disease in poultry. The synonymous codon usage patterns of bacteria reflect a series of evolutionary changes that enable bacteria to improve tolerance of the various environments. We detailed the codon usage patterns of RA isolates from the available 12 sequenced genomes by multiple codon and statistical analysis. Nucleotide compositions and relative synonymous codon usage (RSCU) analysis revealed that A or U ending codons are predominant in RA. Neutrality analysis found no significant correlation between GC12 and GC3 (p > 0.05). Correspondence analysis and ENc-plot results showed that natural selection dominated over mutation in the codon usage bias. The tree of cluster analysis based on RSCU was concordant with dendrogram based on genomic BLAST by neighbor-joining method. By comparative analysis, about 50 highly expressed genes that were orthologs across all 12 strains were found in the top 5% of high CAI value. Based on these CAI values, we infer that RA contains a number of predicted highly expressed coding sequences, involved in transcriptional regulation and metabolism, reflecting their requirement for dealing with diverse environmental conditions. These results provide some useful information on the mechanisms that contribute to codon usage bias and evolution of RA.
"Seeing is believing: the quest for multimodal knowledge" by Gerard de Melo and Niket Tandon, with Martin Vesely as coordinator

There is a growing conviction that the future of computing will crucially depend on our ability to better exploit data to produce more intelligent systems. Increasingly, this will involve drawing simultaneously on multiple heterogeneous modalities, to take full advantage of the vast quantities of images and videos now available on the Web and elsewhere. We give several examples of methods that leverage prior knowledge for better, more semantically informed visual analytics, as well as methods that use multimodal data for better textual analytics. Important progress may come from approaches specifically geared towards harvesting rich multimodal knowledge. For example, our Knowlywood system relies on Hollywood movies to learn about human activities. Once acquired, knowledge of this sort can then be re-used across different tasks, much like humans draw on their accumulated knowledge when making sense of the world.
One Step Forward, Two Steps Back; Xeno-MicroRNAs Reported in Breast Milk Are Artifacts

Background MicroRNAs (miRNAs) are short RNA sequences that guide post-transcriptional regulation of gene expression via complementarity to their target mRNAs. Discovered only recently, miRNAs have drawn a lot of attention. Multiple protein complexes interact to first cleave a hairpin from nascent RNA, export it into the cytosol, trim its loop, and incorporate it into the RISC complex which is important for binding its target mRNA. This process works within one cell, but circulating miRNAs have been described suggesting a role in cell-cell communication. Motivation Viruses and intracellular parasites like Toxoplasma gondii use miRNAs to manipulate host gene expression from within the cellular environment. However, recent research has claimed that a rice miRNA may regulate human gene expression. Despite ongoing debates about these findings and general reluctance to accept them, a recent report claimed that foodborne plant miRNAs pass through the digestive tract, travel through blood to be incorporated by alveolar cells excreting milk. The miRNAs are then said to have some immune-related function in the newborn. Principal Findings We acquired the data that supports their claim and performed further analyses. In addition to the reported miRNAs, we were able to detect almost complete mRNAs and found that the foreign RNA expression profiles among samples are exceedingly similar. Inspecting the source of the data helped understand how RNAs could contaminate the samples. Conclusion Viewing these findings in context with the difficulties foreign RNAs face on their route into breast milk and the fact that many identified foodborne miRNAs are not from actual food sources, we can conclude beyond reasonable doubt that the original claims and evidence presented may be due to artifacts. We report that the study claiming their existence is more likely to have detected RNA contamination than miRNAs.
Ldr2Hdr: on-the-fly reverse tone mapping of legacy video and photographs

New generations of display devices promise to provide significantly improved dynamic range over conventional display technology. In the long run, evolving camera technology and file formats will provide high fidelity content for these display devices. In the near term, however, the vast majority of images and video will only be available in low dynamic range formats. In this paper we describe a method for boosting the dynamic range of legacy video and photographs for viewing on high dynamic range displays. Our emphasis is on real-time processing of video streams, such as web streams or the signal from a DVD player. We place particular emphasis on robustness of the method, and its ability to deal with a wide range of content without user adjusted parameters or visible artifacts. The method can be implemented on both graphics hardware and on signal processors that are directly integrated in the HDR displays.
Quantum Sphere-Packing Bounds With Polynomial Prefactors

We study lower bounds on the optimal error probability in classical coding over classical-quantum channels at rates below the capacity, commonly termed quantum sphere-packing bounds. Winter and Dalai have derived such bounds for classical-quantum channels; however, the exponents in their bounds only coincide when the channel is classical. In this paper, we show that these two exponents admit a variational representation and are related by the Golden–Thompson inequality, reaffirming that Dalai’s expression is stronger in general classical-quantum channels. Second, we establish a finite blocklength sphere-packing bound for classical-quantum channels, which significantly improves Dalai’s prefactor from the order of subexponential to polynomial. Furthermore, the gap between the obtained error exponent for constant composition codes and the best known classical random coding exponent vanishes in the order of $o(\log n / n)$ , indicating our sphere-packing bound is almost exact in the high rate regime. Finally, for a special class of symmetric classical-quantum channels, we can completely characterize its optimal error probability without the constant composition code assumption. The main technical contributions are two converse Hoeffding bounds for quantum hypothesis testing and the saddle-point properties of error exponent functions.
Attenuation of antigen-specific T helper 1 immunity by Neolitsea hiiranensis and its derived terpenoids

Background T cells play a pivotal role in the adaptive immunity that participates in a wide range of immune responses through a complicated cytokine network. Imbalance of T-cell responses is involved in several immune disorders. Neolitsea species, one of the biggest genera in the family Lauraceae, have been employed widely as folk medicines for a long time in Asia. Previous phytochemical investigations revealed the abundance of terpenes in the leaves of N. hiiranensis, an endemic Neolitsea in Taiwan, and demonstrated anti-inflammatory activities. However, the effect of N. hiiranensis on the functionality of immune cells, especially T cells, is still unclear. In this study, we utilize in vitro and in vivo approaches to characterize the effects of leaves of N. hiiranensis and its terpenoids on adaptive immune responses. Methods Dried leaves of N. hiiranensis were extracted three times with cold methanol to prepare crude extracts and to isolate its secondary metabolites. The ovalbumin (OVA)-sensitized BALB/c mice were administrated with N. hiiranensis extracts (5–20 mg/kg). The serum and splenocytes of treated mice were collected to evaluate the immunomodulatory effects of N. hiiranensis on the production of OVA-specific antibodies and cytokines. To further identify the N. hiiranensis-derived compounds with immunomodulatory potentials, OVA-primed splenocytes were treated with compounds isolated from N. hiiranensis by determining the cell viability, cytokine productions, and mRNA expression in the presence of OVA in vitro. Results Crude extracts of leaves of N. hiiranensis significantly inhibited IL-12, IFN-γ, and IL-2 cytokine productions as well as the serum levels of antigen-specific IgM and IgG2a in vivo. Two of fourteen selected terpenoids and one diterpenoid derived from the leaves of N. hiiranensis suppressed IFN-γ in vitro. In addition, β-caryophyllene oxide attenuated the expression of IFN-γ, T-bet, and IL-12Rβ2 in a dose-dependent manner. N. hiiranensis-derived β-caryophyllene oxide inhibited several aspects of adaptive immune responses, including T-cell differentiation, IFN-γ production, and Th1-assocaited genes. Conclusion As IFN-γ is the key cytokine secreted by T helper-1 cells and plays a pivotal role in Th1 immune responses, our results suggested that the N. hiiranensis and its terpenoids may possess potential therapeutic effects on Th1-mediated immune disorders.
Evaluation of the Valve Academic Research Consortium-2 Criteria for Myocardial Infarction in Transcatheter Aortic Valve Implantation: A Prospective Observational Study

Objective To evaluate the relevance of the individual components of the Valve Academic Research Consortium (VARC)-2 criteria for periprocedural myocardial infarction (MI) in transcatheter aortic valve implantation (TAVI). The association between biomarkers and adverse procedural outcome has been established. However, the additive prognostic importance of signs and symptoms are more uncertain. Methods A total of 125 consecutive TAVI patients were prospectively included in this study. Biomarkers for MI were analyzed and signs and symptoms according to VARC-2 criteria were collected from clinical records. Results The criteria of elevated biomarkers and of signs or symptoms were found in 27 (22%) and 32 (26%) of the patients, respectively. According to VARC-2 definition, 12 (10%) had MI. VARC-2 definition of MI, Troponin T (TnT) > 600 ng/L, and presence of signs or symptoms correlated with 6 months mortality, prolonged ICU stay, elevation of N-terminal prohormone brain natriuretic peptide, and renal impairment. No signs or symptoms were found in 7 (44%) of the patients who fulfilled the criterion of elevated TnT > 600 ng/L. In the group with positive TnT criterion, there were no significant differences between those with and without signs or symptoms in respect to levels of TnT (1014 [585–1720] ng/L versus 704 [515–905] ng/L, p = 0.17) or creatine kinase-MB (36 [25–52] μg/L versus 29 [25–39] μg/L, p = 0.32). In the multivariate Cox regression analysis, TnT > 600 ng/L was the only significant independent variable associated with 6-months postprocedural mortality. Conclusions Myocardial injury in TAVI, measured with biomarkers, correlates well with adverse procedural outcome. In this study it is also the strongest predictor for early postprocedural mortality. The additional requirement of signs or symptoms for the diagnosis of MI results in omission of a considerable number of clinically significant MI.
Stroke: Highlights of Selected Articles

In this interesting prospective longitudinal study of the natural history of cerebral amyloid angiopathy (CAA), Reijmer et al explore the progression of white matter pathology over time and its correlation with cognitive decline. The authors quantified the efficiency of global white matter connections network by analysis of diffusion tensor imaging; CAA was dichotomized as moderate or severe based on the number of cerebral microbleeds, and a detailed battery of neurocognitive testing was performed in all 33 patients included in their final analysis. The authors found an unequivocal decline of the global network efficiency during a mean follow-up time of 1.3 years, to an extent significantly higher than previous studies in healthy adults. This decline was driven by the subgroup with severe CAA. A similar pattern was noted in the posterior–frontal and frontal–frontal connections, whereas the posterior–posterior connections were affected across the whole study. The decline in network connectivity was correlated with a parallel decline in executive functioning; no relationship was found with processing speed and memory. White matter hyperintensity volume also increased over time, but it was not associated with concurrent decline in cognitive performance. Overall, despite its small sample size, this study offers unique insight into the biology of CAA: It reveals a structural, measurable decline in the quality of white matter connections, commensurate to the severity of the disease and at a faster rate than what naturally occurs as part of normal ageing. In addition, it reveals a unique posterior–anterior gradient, suggesting that although CAA predominantly affects posterior cerebral regions, in more severe forms and over time, it becomes more diffuse, affecting more anterior regions as well. Future studies examining the disease progression in larger patient samples and over longer periods of time are expected to deepen our understanding of this complex disease even more. See p 2470.
Multiple Ionic Conductances of the Human Dopamine Transporter: The Actions of Dopamine and Psychostimulants

Electrophysiological and pharmacological studies of a cloned human dopamine transporter (hDAT) were undertaken to investigate the mechanisms of transporter function and the actions of drugs at this target. Using two-electrode voltage-clamp techniques with hDAT-expressing Xenopus laevis oocytes, we show that hDAT can be considered electrogenic by two criteria. (1) Uptake of hDAT substrates gives rise to a pharmacologically appropriate “transport-associated” current. (2) The velocity of DA uptake measured in oocytes clamped at various membrane potentials was voltage-dependent, increasing with hyperpolarization. Concurrent measurement of transport-associated current and substrate flux in individual oocytes revealed that charge movement during substrate translocation was greater than would be expected for a transport mechanism with fixed stoichiometry of 2 Na+ and 1 Cl− per DA+ molecule. In addition to the transport-associated current, hDAT also mediates a constitutive leak current, the voltage and ionic dependencies of which differ markedly from those of the transport-associated current. Ion substitution experiments suggest that alkali cations and protons are carried by the hDAT leak conductance. In contrast to the transport-associated functions, the leak does not require Na+ or Cl−, and DAT ligands readily interact with the transporter even in the absence of these ions. The currents that hDAT mediates provide a functional assay that readily distinguishes the modes of action of amphetamine-like “DA-releasing” drugs from cocaine-like translocation blockers. In addition, the voltage dependence of DA uptake suggests a mechanism through which presynaptic DA autoreceptor activation may accelerate the termination of dopaminergic neurotransmission in vivo.
Optimal Sensor Trajectories in Bearings-Only Tracking

We consider the problem of determining sen- sor trajectories in the bearings-only tracking of an uncer- tain target. This work differs from previous research in tha t we allow the target dynamics to be both uncertain and ran- dom; and also consider multi-sensor scenarios. The basis of our technique is to control a measure of estimation error based on the Posterior Cram´ er-Rao lower bound (PCRLB), and we present both single-step and multi-step planning ap- proaches. We also introduce an efficient search technique that allows us to quickly perform the necessary optimisa- tion(s). Sensor trajectories are shown to be almost identi- cal to those obtained by performing an enumerative search, but the computational load is reduced by several orders of magnitude. Simulation results are presented for 1, 2 and 3 sensor scenarios, and compare the single-step and two- step approaches. The performance (in terms of both the PCRLB and particle filter estimation errors) improves both with two-step planning and as sensor numbers increase, as one would expect.
A generic audio classification and segmentation approach for multimedia indexing and retrieval

We focus the attention on the area of generic and automatic audio classification and segmentation for audio-based multimedia indexing and retrieval applications. In particular, we present a fuzzy approach toward hierarchic audio classification and global segmentation framework based on automatic audio analysis providing robust, bi-modal, efficient and parameter invariant classification over global audio segments. The input audio is split into segments, which are classified as speech, music, fuzzy or silent. The proposed method minimizes critical errors of misclassification by fuzzy region modeling, thus increasing the efficiency of both pure and fuzzy classification. The experimental results show that the critical errors are minimized and the proposed framework significantly increases the efficiency and the accuracy of audio-based retrieval especially in large multimedia databases.
Using Machine Learning to Explore Human Multimodal Clarification Strategies

We investigate the use of machine learning in combination with feature engineering techniques to explore human multimodal clarification strategies and the use of those strategies for dialogue systems. We learn from data collected in a Wizard-of-Oz study where different wizards could decide whether to ask a clarification request in a multimodal manner or else use speech alone. We show that there is a uniform strategy across wizards which is based on multiple features in the context. These are generic runtime features which can be implemented in dialogue systems. Our prediction models achieve a weighted f-score of 85.3% (which is a 25.5% improvement over a one-rule baseline). To assess the effects of models, feature discretisation, and selection, we also conduct a regression analysis. We then interpret and discuss the use of the learnt strategy for dialogue systems. Throughout the investigation we discuss the issues arising from using small initial Wizard-of-Oz data sets, and we show that feature engineering is an essential step when learning from such limited data.
Variational principles in grid generation and geometric modelling: theoretical justifications and open problems

The paper is devoted to analysis of variational principles for construction of mappings with prescribed properties in grid generation and geometric modelling. An attempt is made to formulate general requirements which should be satisfied by the variational principle. Theoretical justification is considered along with review of unsolved problems and fundamental mathematical difficulties. Copyright © 2004 John Wiley & Sons, Ltd.
Job Insecurity and Children's Emancipation

The age at which children leave the parental home differs considerably across countries. We present a theoretical model predicting that higher job security of parents and lower job security of children may delay emancipation. We then provide aggregate evidence which supports this hypothesis for 12 European countries. We also give microeconometric evidence for Italy, the single country for which we have access to household-specific information on job security and coresidence. It is a very interesting case to study since, in the late 1990s, approximately 75% of young Italians aged 18 to 35 were living at home and they had only a 4% probability of emancipation in the subsequent 3 years. We show that this probability would have increased by 4 to 10 percentage points if their fathers had gone from having a fully secure job to becoming unemployed for sure.
Bayesian modeling and analysis for gradients in spatiotemporal processes

Stochastic process models are widely employed for analyzing spatiotemporal datasets in various scientific disciplines including, but not limited to, environmental monitoring, ecological systems, forestry, hydrology, meteorology, and public health. After inferring on a spatiotemporal process for a given dataset, inferential interest may turn to estimating rates of change, or gradients, over space and time. This manuscript develops fully model‐based inference on spatiotemporal gradients under continuous space, continuous time settings. Our contribution is to offer, within a flexible spatiotemporal process model setting, a framework to estimate arbitrary directional gradients over space at any given timepoint, temporal derivatives at any given spatial location and, finally, mixed spatiotemporal gradients that reflect rapid change in spatial gradients over time and vice‐versa. We achieve such inference without compromising on rich and flexible spatiotemporal process models and use nonseparable covariance structures. We illustrate our methodology using a simulated data example and subsequently apply it to a dataset of daily PM2.5 concentrations in California, where the spatiotemporal gradient process reveals the effects of California's unique topography on pollution and detects the aftermath of a devastating series of wildfires.
Analysing Micro- and Macro-Structures in Textures

Analysing micro- and macro-structures within images confers ability to include scale in texture analysis. Filtering allows for selection of texture structures at different scales, revealing the micro- and macro-structures which would otherwise be concealed. The new approach to texture segmentation uses low- and high-pass filters to achieve this scale-based analysis. Segmentation is performed using Local Binary Patterns as an example of the type of feature vector that can be used with the new process. These are generated for the original image and each of the filtered images. A two stage training process is used to learn the optimum filter sizes and to produce model histograms for each known texture class. These are used in the supervised segmentation of texture mosaics generated from the VisTex database. The results demonstrate the superiority of the new combined approach compared to the best multi-resolution LBP configuration and analysis only using low pass filters. Noise analysis has also confirmed the advantageous properties of low- and high-pass filtering, and confirms that it is optimal to combine the two forms in texture segmentation.
Computer animation for articulated 3D characters

We present a review of the computer animation literature, mainly concentrating on articulated characters and at least some degree of interactivity or real time simulation. Advances in dierent techniques such as key-frame, motion capture (also known as mocap), dynamics, inverse kinematics (IK), controller systems, and even neural networks are discussed. We try to analyze these methods from dierent aspects: semantics, data input, animation types, generating the animations, combining animations, animation varying, target type, and even the path planning perspective is taken into account for the reviewed animation systems.
Modified Intervastus Approach to the Knee

Abstract The modified intervastus approach to the anterior knee is an approach that may be used in the majority of patients undergoing total knee arthroplasty. This article presents the first description of this approach. The advantages of this approach include its extensile nature, similar to a medial parapatellar approach, and preservation of the extensor mechanism and the vastus medialis, leading to a more rapid return to active knee extension than is traditionally observed. The approach is also simple to perform, easy to close, and is compatible with more extensile approaches such as a quadriceps snip if required in revision scenarios.