Miracle-dz/UniFAR-FTUs huggingface dataset:
Antigenicity reduction contributes mostly to poor detectability of HBsAg by hepatitis B virus (HBV) S‐gene mutants isolated from individuals with occult HBV infection

Mutations in hepatitis B virus (HBV) S gene are one of factors contributing to occult HBV infection (OBI). The study aimed to uncover the impact of OBI‐related S‐gene mutations on the detectability of hepatitis B surface antigen (HBsAg). Nine representative mutations within the major hydrophilic region of the S region were investigated. These included six (M1‐M6) from an OBI patient with HBV‐related hepatocellular carcinoma, and three (M7‐M9) from three OBI blood donors. Recombinant plasmids on the basis of pTriEx‐mod‐1.1 HBV and pcDNA3.1(−)/myc‐His A vectors were constructed for each and transfected into HepG2 or Huh7 cells, respectively. Electrochemical luminescence, ELISA, Western blotting, and confocal immunofluorescence were used to examine HBsAg expression and antigenicity. In comparison to wild‐type strain, supernatant and intracellular HBsAg levels of the nine mutants were reduced by 56.39‐99.09% and 42.76‐99.77% upon Roche quantitative Elecsys assay, respectively. Confocal immunofluorescence showed that relative intensity ratios of HBsAg‐myc‐His fusion protein detected by anti‐HBs and anti‐His‐tag were lower by 11.87‐76.27% for the nine mutants compared to the wild‐type strain. Specifically, M1‐M5 mutants that we firstly found recently were 33.14%, 76.27%, 57.93%, 53.37%, and 40.88% lower, respectively. Consistent results were obtained using double‐antibody sandwich ELISA assays (anti‐myc + anti‐HBs vs anti‐myc + anti‐His). Antigenicity reduction played a major role for the poor detectability of HBsAg caused by the OBI‐related mutations, although decreased HBsAg expression of some mutants and anti‐HBs in samples might play coordinated roles. Taken together, antigenicity reduction contributes mostly to poor detectability of HBsAg caused by these OBI‐related mutations.
Estimating SE(3) elements using a dual quaternion based linear Kalman filter

Many applications in robotics such as registration, object tracking, sensor calibration, etc. use Kalman filters to estimate a time invariant SE(3) element by locally linearizing a non-linear measurement model. Linearization-based filters tend to suffer from inaccurate estimates, and in some cases divergence, in the presence of large initialization errors. In this work, we use a dual quaternion to represent the SE(3) element and use multiple measurements simultaneously to rewrite the measurement model in a truly linear form with state dependent measurement noise. Use of the linear measurement model bypasses the need for any linearization in prescribing the Kalman filter, resulting in accurate estimates while being less sensitive to initial estimation error. To show the broad applicability of this approach, we derive linear measurement models for applications that use either position measurements or pose measurements. A procedure to estimate the state dependent measurement uncertainty is also discussed. The efficacy of the formulation is illustrated using simulations and hardware experiments for two applications in robotics: rigid registration and sensor calibration.
Novel Fiber-Dependent Entry Mechanism for Adenovirus Serotype 5 in LacrimalAcini

ABSTRACT The established mechanism for infection of most cells with adenovirus serotype 5 (Ad5) involves fiber capsid protein binding to coxsackievirus-adenovirus receptor (CAR) at the cell surface, followed by penton base capsid protein binding to αv integrins, which triggers clathrin-mediated endocytosis of the virus. Here we determined the identity of the capsid proteins responsible for mediating Ad5 entry into the acinar epithelial cells of the lacrimal gland. Ad5 transduction of primary rabbit lacrimal acinar cells was inhibited by excess Ad5 fiber or knob (terminal region of the fiber) but not excess penton base. Investigation of the interactions of recombinant Ad5 penton base, fiber, and knob with lacrimal acini revealed that the penton base capsid protein remained surface associated, while the knob domain of the fiber capsid protein was rapidly internalized. Introduction of rabbit CAR-specific small interfering RNA (siRNA) into lacrimal acini under conditions that reduced intracellular CAR mRNA significantly inhibited Ad5 transduction, in contrast to a control (nonspecific) siRNA. Preincubation of Ad5 with excess heparin or pretreatment of acini with a heparinase cocktail each inhibited Ad5 transduction by a separate and apparently additive mechanism. Functional and imaging studies revealed that Ad5, fiber, and knob, but not penton base, stimulated macropinocytosis in acini and that inhibition of macropinocytosis significantly reduced Ad5 transduction of acini. However, inhibition of macropinocytosis did not reduce Ad5 uptake. We propose that internalization of Ad5 into lacrimal acini is through a novel fiber-dependent mechanism that includes CAR and heparan sulfate glycosaminoglycans and that the subsequent intracellular trafficking of Ad5 is enhanced by fiber-induced macropinocytosis.
Intensional associations in dataspaces

Dataspace applications necessitate the creation of associations among data items over time. For example, once information about people is extracted from sources on the Web, associations among them may emerge as a consequence of different criteria, such as their city of origin or their elected hobbies. In this paper, we advocate a declarative approach to specifying these associations. We propose that each set of associations be defined by an association trail. An association trail is a query-based definition of how items are connected by intensional (i.e., virtual) association edges to other items in the dataspace. We study the problem of processing neighborhood queries over such intensional association graphs. The naive approach to neighborhood query processing over intensional graphs is to materialize the whole graph and then apply previous work on dataspace graph indexing to answer queries. We present in this paper a novel indexing technique, the grouping-compressed index (GCI), that has better worst-case indexing cost than the naive approach. In our experiments, GCI is shown to provide an order of magnitude gain in indexing cost over the naive approach, while remaining competitive in query processing time.
Degenerate and critical Bloch branes

In the last few years a number of works reported the appearance of thick branes with internal structure, induced by the parameter which controls the interaction between two scalar fields coupled to gravity in (4,1) dimensions in warped space-time with one extra dimension. Here we show that one can implement the control over the brane thickness without needing to change the potential parameter. On the contrary, this is going to be done by means of the variation of a parameter associated with the domain wall degeneracy. We also report the existence of novel and qualitatively different solutions for a critical value of the degeneracy parameter, which could be called critical Bloch branes.
Review of Metaheuristics and Generalized Evolutionary Walk Algorithm

Metaheuristic algorithms are often nature-inspired, and they are becoming very powerful in solving global optimization problems. More than a dozen of major metaheuristic algorithms have been developed over the last three decades, and there exist even more variants and hybrid of metaheuristics. This paper intends to provide an overview of nature-inspired metaheuristic algorithms, from a brief history to their applications. We try to analyze the main components of these algorithms and how and why they works. Then, we intend to provide a unified view of metaheuristics by proposing a generalized evolutionary walk algorithm (GEWA). Finally, we discuss some of the important open questions.
ComposAR: An intuitive tool for authoring AR applications

This paper introduces ComposAR, a tool to allow a wide audience to author AR and MR applications. It is unique in that it supports both visual programming and interpretive scripting, and an immediate mode for runtime testing. ComposAR is written in Python which means the user interface and runtime behavior can be easily customized and third-party modules can be incorporated into the authoring environment. We describe the design philosophy and the resulting user interface, lessons learned and directions for future research.
Clathrin binding by the adaptor Ent5 promotes late stages of clathrin coat maturation

Clathrin adaptors link cargo to the clathrin coat. The clathrin adaptor Ent5 is also required for the maturation of clathrin coats at the trans-Golgi network or endosome, suggesting that it plays a key mechanistic role in coat formation. This function requires only the Ent5 clathrin-binding sites and not its interaction with other endosomal adaptors.
New Attacks on Timing-based Network Flow Watermarks

A network flow watermarking scheme attempts to manipulate the statistical properties of a flow of packets to insert a "mark" making it easier to detect the flow after passing through one or more relay hosts. Because an attacker that is willing to tolerate delay can (nearly) always eliminate such marks, recent schemes have concentrated on making the marks "invisible" so that a passive attacker cannot detect the presence of the mark. In this work, we argue that from a system's perspective, security against passive detection is insufficient for successful traffic analysis. We introduce a stronger, but feasible attack model (a known/chosen flow attacker) and a second security goal (security against copy attacks) and argue that security against both of these attacks is required for successful traffic analysis. We also demonstrate successful attacks against two recent watermarking schemes, RAINBOW and SWIRL, and show how considering these stronger attacks can aid in the design of passive detection attacks against each as well.
Saline: Improving Best-Effort Job Management in Grids

Virtualization technologies have recently gained a lot of interest in Grid computing as they allow flexible resource management. However, the most common way to exploit grids relies on dedicated services like resource management systems (RMSs) to get resources at a particular time. To improve resource usage, most of these systems provide a best-effort mode where lowest priority jobs can be executed when resources are idle. This particular mode does not provide any guarantee of service and jobs may be killed at any time by the RMS when the nodes they use are subject to higher priority reservations. This behaviour potentially leads to a huge waste of computation time or at least requires users to deal with checkpoints of their jobs. In this paper we present Saline, a generic and non-intrusive framework to manage best-effort jobs at grid level through virtual machines (VMs) usage. We discuss the main challenges concerning the design of such a grid system, focusing on VM snapshot management and network configuration. Results of experiments show our proposal ensures an efficient execution of best-effort jobs through the whole grid.
An Unusual Thioesterase Promotes Isochromanone Ring Formation in Ajudazol Biosynthesis

The ajudazols are antifungal secondary metabolites produced by a hybrid polyketide synthase (PKS)‐nonribosomal peptide synthetase (NRPS) multienzyme “assembly line” in the myxobacterium Chondromyces crocatus Cm c5. The most striking structural feature of these compounds is an isochromanone ring system; such an aromatic moiety is only known from two other complex polyketides, the electron transport inhibitor stigmatellin and the polyether lasalocid. The cyclization and aromatization reactions in the stigmatellin pathway are presumed to be catalyzed by a cyclase domain located at the end of the PKS, while the origin of the lasalocid benzenoid ring remains obscure. Notably, the ajudazol biosynthetic machinery does not incorporate a terminal cyclase, but instead a variant thioesterase (TE) domain. Here we present detailed phylogenetic and sequence analysis, coupled with experiments both in vitro and in vivo, that suggest that this TE promotes formation of the isochromanone ring, a novel reaction for this type of domain. As the ajudazol TE has homologues in several other secondary‐metabolite pathways, these results are likely to be generalizable.
Adapting Hybrid ANN/HMM to Speech Variations

A technique is proposed for the adaptation of automatic speech recognition systems using Hybrid models combining Artificial Neural Networks with Hidden Markov Models. We investigated in this paper the extension of the classical approach consisting in applying linear transformations not only to the input features, but also to the outputs of the internal layers. The motivation is that the outputs of an internal layer represent a projection of the input pattern into a space where it should be easier to learn the classification or transformation expected at the output of the network. To reduce the risk that the network focuses on new data only, loosing its generalization capability (catastrophic forgetting), an original solution, Conservative Training is proposed. We illustrate the problem of catastrophic forgetting using an artificial test-bed, and apply our techniques to a set of adaptation tasks in the domain of Automatic Speech Recognition (ASR) based on Artificial Neural Networks. We report on the adaptation potential of different techniques, and on the generalization capability of the adapted networks. The results show that the combination of the proposed approaches mitigates the catastrophic forgetting effects, and always outperforms the use of the classical linear transformation in the feature space.
Network Motif Analysis in Clouds - Subgraph Enumeration with Iterative Hadoop MapReduce

Finding network motifs in biological networks is a computationally intensive task as it involves traversing through a large network to enumerate all possible subgraphs of a given size, and then determining their statistical uniqueness by sampling subgraphs from a large number (more than 1,000) of random graph pools. There have been parallelization efforts in the past to mitigate the computational intensity for finding network motifs. However, they are either more for the frequent subgraphs in networks rather than network motifs, or require complex manipulations on message passing or designs. Additionally, most of the parallel algorithms are unavailable as tools for use. Here, we introduce a project of ‘complete network motif parallelization. ’ This project aims to improve performance of serial algorithms for finding all subgraph patterns with given size in PPI networks by parallelizing them using iterative Hadoop MapReduce on Google Cloud, and then determining their uniqueness through explicit or direct random graph generation to determine network motifs. In this paper, we describe the parallelization of subgraph enumeration and McKay’s canonical algorithms and present the experimental results with a significant improvement in performance, up to 37 times speedup. We are continuing to parallelize network motif significance as a next step, and expecting the completion of the project in near future.
Group sparse optimization via $\ell_{p,q}$ regularization

In this paper, we investigate a group sparse optimization problem via $\ell_{p,q}$ regularization in three aspects: theory, algorithm and application. In the theoretical aspect, by introducing a notion of group restricted eigenvalue condition, we establish some oracle property and a global recovery bound of order $O(\lambda^\frac{2}{2-q})$ for any point in a level set of the $\ell_{p,q}$ regularization problem, and by virtue of modern variational analysis techniques, we also provide a local analysis of recovery bound of order $O(\lambda^2)$ for a path of local minima. In the algorithmic aspect, we apply the well-known proximal gradient method to solve the $\ell_{p,q}$ regularization problems, either by analytically solving some specific $\ell_{p,q}$ regularization subproblems, or by using the Newton method to solve general $\ell_{p,q}$ regularization subproblems. In particular, we establish the linear convergence rate of the proximal gradient method for solving the $\ell_{1,q}$ regularization problem under some mild conditions. As a consequence, the linear convergence rate of proximal gradient method for solving the usual $\ell_{q}$ regularization problem ($0<q<1$) is obtained. Finally in the aspect of application, we present some numerical results on both the simulated data and the real data in gene transcriptional regulation.
Utilizing Symmetry of Planar Ultra-Wideband Antennas for Size Reduction and Enhanced Performance

With the increasingly new ultrawideband applications, antenna researchers face huge challenges in designing novel operational geometries. Monopole and quasi-monopole antennas are seen to be the most compact and easily incorporable solution for portable devices taking the advantages of printed circuit board techniques. Most antennas of such type have symmetrical structures. It is possible to attain wider operating bandwidths by meeting symmetry conditions while chopping the antenna into halves for a compact structure. However, there is no generalized way of applying such a technique. This paper addresses this issue by proposing a common feeding technique that can be applied to any antenna, which is miniaturized using its symmetrical structure. The proposed technique enables feeding the halved structure to achieve wider and better impedance matching than the reported full-size antennas. The theory of characteristic modes is applied to quasi-monopole structures to get an insight of the antennas-mechanism. The radiation patterns are also correlated with modal current distributions to understand the radiation characteristics of the modified structure. Finally, the method is implemented on some example antennas to illustrate its potential.
Self-Confidence in College Students: Conceptualization, Measurement, and Behavioral Implications

Self-confidence was conceptualized and a multidimensional measure, the Personal Evaluation Inventory, was developed which assesses college students' confidence in six areas most important to them. The measure's psychometric properties and relationships with other personality attributes were described. Three studies exploring behavioral correlates of confidence demonstrated the following: People's expressed self-confidence is consistent with others' appraisals of their confidence; when given a choice between two activities, people choose the one on which their confidence is higher; and less confident people perceive their futures, although not those of other people, less favorably than highly confident people. The importance of distinguishing and assessing both domain-specific and general confidence is discussed.
The Grammar Matrix: An Open-Source Starter-Kit for the Rapid Development of Cross-linguistically Consistent Broad-Coverage Precision Grammars

The grammar matrix is an open-source starter-kit for the development of broad-coverage HPSGs. By using a type hierarchy to represent cross-linguistic generalizations and providing compatibility with other open-source tools for grammar engineering, evaluation, parsing and generation, it facilitates not only quick start-up but also rapid growth towards the wide coverage necessary for robust natural language processing and the precision parses and semantic representations necessary for natural language understanding.
Response Rate and Nonresponse Bias - Impact of the Number of Contact Attempts on Data Quality in the European Social Survey

Increasing respondent contact problems and decreasing respondent willingness to cooperate have contributed to declining response rates in general population surveys, which has raised concerns of survey accuracy. To counteract nonresponse, several methods have been employed, including incentives, advanced letters, alternative survey modes for reluctant respondents, and increased field efforts to contact potential respondents. In particular, the number of contact attempts has been increased for many surveys. Even though more contact attempts increase survey costs, they are a reliable means for increasing response rates. However, the assumption that high response rates foster data quality and smaller nonresponse bias has been challenged. In this paper, we used contact data from the European Social Survey for Norway, Finland and Slovenia to see whether or not additional contact attempts resulting in a higher response rate can potentially reduce nonresponse bias.
Development of Computational Tools for the Inference of Protein Interaction Specificity Rules and Functional Annotation Using Structural Information

Relatively few protein structures are known, compared to the enormous amount of sequence data produced in the sequencing of different genomes, and relatively few protein complexes are deposited in the PDB with respect to the great amount of interaction data coming from high-throughput experiments (two-hybrid or affinity purification of protein complexes and mass spectrometry). Nevertheless, we can rely on computational techniques for the extraction of high-quality and information-rich data from the known structures and for their spreading in the protein sequence space. We describe here the ongoing research projects in our group: we analyse the protein complexes stored in the PDB and, for each complex involving one domain belonging to a family of interaction domains for which some interaction data are available, we can calculate its probability of interaction with any protein sequence. We analyse the structures of proteins encoding a function specified in a PROSITE pattern, which exhibits relatively low selectivity and specificity, and build extended patterns. To this aim, we consider residues that are well-conserved in the structure, even if their conservation cannot easily be recognized in the sequence alignment of the proteins holding the function. We also analyse protein surface regions and, through the annotation of the solvent-exposed residues, we annotate protein surface patches via a structural comparison performed with stringent parameters and independently of the residue order in the sequence. Local surface comparison may also help in identifying new sequence patterns, which could not be highlighted with other sequence-based methods.
An On Demand Interference Aware Routing Protocol for VANETS

Vehicular communication systems represent one of the most desirable technologies when the safety, efficiency and comfort of everyday road travel need to be improved. The main advantage is the absence of an infrastructure, typical of centralized networks, that makes them adequate for highly-variable network topologies. On the other hand, communication protocols become very complex and, sometimes, signaling overhead may waste bandwidth availability. Vehicular Ad-hoc NETworks (VANETs) are able to provide a wireless networking capability in situations where no fixed infrastructure exists: communication performance and Quality of Service (QoS) strongly depend on how the routing takes place in the network, on how protocol overhead affects the available bandwidth and on how different channels are selected in order to minimize interference levels. Attention is focused on the routing level of VANET and we propose an interference aware routing scheme for multi-radio vehicular networks, wherein each node is equipped with a multi-channel radio interface. In order to relieve the effects of the co-channel interference perceived by mobile nodes, transmission channels are switched on the basis of a periodical Signal-to-Interference Ratio (SIR) evaluation. A new metric is also proposed, based on the maximization of the average SIR level of the connection between source and destination. Our solution has been integrated with the Ad-Hoc On-Demand Distance Vector (AODV) routing protocol to design an enhanced Signal-to-Interference-Ratio-AODV (SIR-AODV). NS-2 has been used for implementing and testing the proposed idea, and significant performance enhancements were obtained, in terms of throughput, packet delivery and, obviously, interference.