Miracle-dz/UniFAR-FTUs huggingface dataset:
REAL-TIME PATH PLANNING IN UNKNOWN ENVIRONMENTS USING A VIRTUAL HILL

Abstract The artificial potential field based path planning has been most wisely used for local path planning because it provides simple and efficient motion planners for practical purposes. However, this approach has a local minimum problem which can trap a robot before reaching its goal. The local minimum problem is sometimes inevitable when a mobile robot moves in unknown environments, because the robot cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planning. In this study, we propose a new concept using a virtual hill to escape local minima that occur in local path planning for a mobile robot. A virtual hill is located around local minimum to repel a robot from local minimum.
Condition-specific target prediction from motifs and expression

MOTIVATION It is commonplace to predict targets of transcription factors (TFs) by sequence matching with their binding motifs. However, this ignores the particular condition of the cells. Gene expression data can provide condition-specific information, as is, e.g. exploited in Motif Enrichment Analysis. RESULTS Here, we introduce a novel tool named condition-specific target prediction (CSTP) to predict condition-specific targets for TFs from expression data measured by either microarray or RNA-seq. Based on the philosophy of guilt by association, CSTP infers the regulators of each studied gene by recovering the regulators of its co-expressed genes. In contrast to the currently used methods, CSTP does not insist on binding sites of TFs in the promoter of the target genes. CSTP was applied to three independent biological processes for evaluation purposes. By analyzing the predictions for the same TF in three biological processes, we confirm that predictions with CSTP are condition-specific. Predictions were further compared with true TF binding sites as determined by ChIP-seq/chip. We find that CSTP predictions overlap with true binding sites to a degree comparable with motif-based predictions, although the two target sets do not coincide. AVAILABILITY AND IMPLEMENTATION CSTP is available via a web-based interface at http://cstp.molgen. mpg.de.
Diverging towards the common good: heterogeneous self-organisation in decentralised recommenders

Decentralised social networks promise to deliver highly personalised, privacy-preserving, scalable and robust implementations of key social network features, such as search, query extensions, and recommendations. Such systems go beyond traditional online social networks by leveraging implicit social ties to implement personalised services. Yet, current decentralised social systems usually treat all users uniformly, when different sub-communities of users might in fact work best with different mechanisms. In this paper, we look at the specific case of decentralised social networks seeking to cluster users exhibiting similar behaviours to provide decentralised recommendations. These decentralised recommendation systems typically rely on a single metric applied uniformly to all users to extract similarities, while it seems natural that there is no such one-size-fits-all approach. More specifically we show in this paper, using a real Twitter trace, that (i) individual users can benefit from a personalised strategy in the context of decentralised recommendation systems, and that (ii) overall system performance is improved when the system accounts for the varying needs of its users i.e. when each user is allowed to diverge and use its optimal strategy.
Supervised mid-level features for word image representation

This paper addresses the problem of learning word image representations: given the cropped image of a word, we are interested in finding a descriptive, robust, and compact fixed-length representation. Machine learning techniques can then be supplied with these representations to produce models useful for word retrieval or recognition tasks. Although many works have focused on the machine learning aspect once a global representation has been produced, little work has been devoted to the construction of those base image representations: most works use standard coding and aggregation techniques directly on top of standard computer vision features such as SIFT or HOG. We propose to learn local mid-level features suitable for building word image representations. These features are learnt by leveraging character bounding box annotations on a small set of training images. However, contrary to other approaches that use character bounding box information, our approach does not rely on detecting the individual characters explicitly at testing time. Our local midlevel features can then be aggregated to produce a global word image signature. When pairing these features with the recent word attributes framework of [4], we obtain results comparable with or better than the state-of-the-art on matching and recognition tasks using global descriptors of only 96 dimensions.
Strong Ties in a Small World

This paper examines the celebrated strength of weak ties theory of Granovetter (1973). We examine two hypotheses implied by the theory: one, for any three players with two links present, the probability of a third link being present is increasing in the strength of the two ties, and two, the removal of a weak tie breaks more shortest paths than the removal of a strong tie. This paper tests these hypotheses using data on co-authorship among economists. Our data supports the hypothesis of transitivity of strong ties, but it rejects the hypothesis that weak ties are more crucial than strong ties. We then propose an explanation for the strength of strong ties which builds on two properties of the network: one, significant inequality in the distribution of connections across individuals, and two, stronger ties among highly connected individuals.
Field Evaluation of a Multiplex Real-Time Reverse Transcription Polymerase Chain Reaction Assay for Detection of Vesicular Stomatitis Virus

Sporadic outbreaks of vesicular stomatitis (VS) in the United States result in significant economic losses for the U.S. livestock industries because VS is a reportable disease that clinically mimics foot-and-mouth disease. Rapid and accurate differentiation of these 2 diseases is critical because their consequences and control strategies differ radically. The objective of the current study was to field validate a 1-tube multiplexed real-time reverse transcription polymerase chain reaction (real-time RT-PCR) assay for the rapid detection of Vesicular stomatitis New Jersey virus and Vesicular stomatitis Indiana virus strains occurring in Mexico and North and Central America. A comprehensive collection of 622 vesicular lesion samples obtained from cattle, horses, and swine from throughout Mexico and Central America was tested by the real-time RT-PCR assay and virus isolation. Overall, clinical sensitivity and specificity of the real-time RT-PCR were 83% and 99%, respectively. Interestingly, VS virus isolates originating from a specific region of Costa Rica were not detected by real-time RT-PCR. Sequence comparisons of these viruses with the real-time RT-PCR probe and primers showed mismatches in the probe and forward and reverse primer regions. Additional lineage-specific primers and a probe corrected the lack of detection of the missing genetic lineage. Thus, this assay reliably identified existing Mexican and Central American VS viruses and proved readily adaptable as new VS viruses were encountered. An important secondary result of this research was the collection of hundreds of new VS virus isolates that provide a foundation from which many additional studies can arise.
A Visual Representation of Wittgenstein’s Tractatus Logico-Philosophicus

In this paper we will discuss a method for data visualization together with its potential usefulness in digital humanities and philosophy of language. We compiled a multilingual parallel corpus from different versions of Wittgenstein’s Tractatus Logico-philosophicus, including the original in German and translations into English, Spanish, French, and Russian. Using this corpus, we compute a similarity measure between propositions and render a visual network of relations for different languages.
Palette-Based Coding in the Screen Content Coding Extension of the HEVC Standard

This paper provides a technical overview of palette-based coding that was adopted into the test model for the screen content coding (SCC) extension of High Efficiency Video Coding (HEVC) standard at the 18th JCT-VC meeting. Key techniques that enable the palette mode to deliver significant coding gains for screen contents are highlighted, including palette table generation, palette table coding, and the coding methods for palette indices and escape colors. Proposed and adopted techniques up to the first version of the working draft of HEVC SCC extension and test model SCM-2.0 are presented. Experimental results are provided to evaluate the performance of the palette mode in the SCC extension of HEVC.
Spatial Knowledge Discovery through an Integration of Visual Data Exploration with Data Mining

The use of multi-dimensional abductive inference has been a challenge for geographers who are interested in discovering research hypotheses from data. This and other exploratory data mining techniques have attracted much attention and hype as spatial analysis tools for scouring large databases in search of interesting spatial data patterns. Progress in data mining, spatial statistics, and visualization algorithms has also created a challenge in choosing the right set of techniques and tools for data analysis. In this paper we describe one approach to choosing abductive inference techniques dealing with the real-world problem of discovering transboundary migration patterns. The approach is based on the integration of visual data exploration with data mining algorithms. Data visualization leads to clues about data patterns, and the clues guide data mining searches. The results of data mining are then visualized, leading to additional clues and more tangible research hypotheses. We present the application of the approach and discuss its potential for guiding the selection of data mining and visualization techniques for effective spatial knowledge discovery.
Test of Effect from Future in Large Hadron Collider:. a Proposal

We have previously proposed the idea of performing a card-drawing experiment of which the outcome potentially decides whether the Large Hadron Collider (LHC) should be closed or not. The purpose is to test theoretical models such as our own model that have an action with an imaginary part that has a similar form to the real part. The imaginary part affects the initial conditions not only in the past but even from the future. It was speculated that all the accelerators producing large amounts of Higgs particles such as the Superconducting Super Collider (SSC) would mean that the initial conditions must have been arranged so as not to allow these accelerators to work. If such effects existed, we could perhaps cause a very clear-cut "miracle" by having the effect of a drawn card to be the closure of the LHC. Here we shall, however, argue that the closure of an accelerator is hardly needed to demonstrate such an effect and seek to calculate how one could perform a verification experiment for the proposed type of effect from the future in the statistically least disturbing and least harmful way. We shall also discuss how to extract the maximum amount of information about such as effect or model in the unlikely case that a card preventing the running of the LHC or the Tevatron is drawn, by estimating the relative importance of high beam energy or high luminosity for the purpose of our effect.
CTL model checking based on forward state traversal

We present a CTL model checking algorithm based mainly on forward state traversal, which can check many realistic CTL properties without doing backward state traversal. This algorithm is effective in many situations where backward state traversal is more expensive than forward state traversal. We combine it with BDD-based state traversal techniques using partitioned transition relations. Experimental results show that our method can verify actual CTL properties of large industrial models which cannot be handled by conventional model checkers.
Boosting Evolutionary Support Vector Machine for Designing Tumor Classifiers from Microarray Data

Since there are multiple sets of relevant genes having the same high accuracy in fitting training data called model uncertainty, to identify a small set of informative genes from microarray data for designing an accurate tumor classifier for unknown samples is intractable. Support vector machine (SVM), a supervised machine learning technique, is one of the methods successfully applied to cancer diagnosis problems. This study proposes an SVM-based classifier with automatic feature selection associated with a boosting strategy. The proposed boosting evolutionary support vector machine (named BESVM) hybridizes the advantages of SVM, boosting using a majority-voting ensemble and an intelligent genetic algorithm for gene selection. The merits of the BESVM-based classifier are threefold: 1) a small set of used genes, 2) accurate test classification using leave-one-out cross-validation, and 3) robust performance by avoiding overfitting training data. Five benchmark datasets were used to evaluate the BESVM-based classifier. Simulation results reveal that BESVM performs well having a mean accuracy 94.26% using only 10.1 genes averagely, compared with the existing SVM and non-SVM based classifiers
New approach of authentication method based on profiles

The exponential raise in traffic across network has obliged the need to distinguish unauthorized access. The process of identifying an individual usually based on a user name and password, which is the process of giving individuals access to system objects based on their identity. Authentication can involve highly complex and secure methods. This paper proposes an innovative algorithm based on neural networks and fuzzy logic that can be used for easy identification of unauthorized users in a network. The algorithm has been tested and validated and the results have been discussed. The result analysis shows that the algorithm is successful in intrusion detection.
The effects of dried root aqueous extract of Salvia miltiorrhiza and its major ingredient in acceleration of orthodontic tooth movement in rat

Objective(s): Salvia miltiorrhiza (SM) is a popular and classic herb in traditional Chineses medicines. The objective is to confirm the effects of aqueous extract of S. miltiorrhiza (ESM) and its main ingredient on the promotion of orthodontic tooth movement and healing of periodontal ligament in rat. Materials and Methods: Male Sprague-Dawley rats (n= 150) were divided into five groups: model control group (0.5 ml/kg phosphate-buffered saline (PBS) injection), ESM group (0.75 g/kg/day of crude drugs) and Danshensu subgroups (250, 500, 750 mg/kg/day of body weight). All rats were administered intramuscularly into the buccal vestibular mucosa of first molar of left maxillary. The indicators such as the moving distance of orthodontic tooth, nuclear factor κB ligand (RANKL) and osteoprotegerin (OPG) expression and osteoclasts were tested. Results: The expressions of RANKL and OPG in the treatment groups were obviously enhanced compared with control group (P<0.05). The increase rate of OPG expression was slower than that of RANKL. But, RANKL decreased conspicuously after no orthodontic pressure was applied, especially in the treatment groups (Danshengsu high dose group at day 30: 2.17 versus 3.47 of control, P<0.01). ESM groups promoted osteoclasts proliferation in the first 20 days. Conclusion: There is a relationship between RANKL/OPG ratio and the number of osteoclasts. ESM might accelerate periodontal alteration of rat orthodontic tooth via producing more osteoclasts.
Continuities and Discontinuities in the Development of Moral Judgments

Prior research has outlined developmental changes within the conventional and personal domains. Research thus far has provided only limited understanding of age-related changes within the moral domain. That research indicates that there are continuities and discontinuities across ages in moral judgments. The aims of the research presented here were to examine moral judgments in childhood and adolescence, taking into account applications of moral judgments in contexts and the coordination of different considerations in evaluations and decisions. Participants were 167 children and adolescents drawn from two regions of the United States, from diverse ethnic and SES backgrounds, distributed across four age groups from 8 to 17 years. Moral judgments were assessed through interviews around issues of direct harm (hitting), indirect harm (returning dropped money), and helping. Each situation was presented within three conditions: unconflicted situations; situations of conflict with needs of self; and conflicts with needs of another. Situations varied in terms of characteristics of the person who was the object of moral decisions: a generic other, vulnerable other, or antagonistic other. Participants made two types of judgments: whether the action was right or wrong; and whether the actor would have a right to engage in the action if that was the actor's choice. Justifications were elicited for judgments. Cross-age continuities in moral judgments were observed in judgments of acts as wrong in the unconflicted contexts. In contrast, a U-shaped age-related pattern was revealed in judgments of acts as well as the right to engage in acts in the conflicted situations with 8- and 16-year-olds judging acts as wrong and 10- to 14-year-olds more likely to judge acts as right and the actor as having a right to engage in the action. This U-shaped pattern was accompanied by three age-related levels in the coordination of moral and nonmoral elements of situations.
Network Resilience through Multiple Routing Configurations

We propose the use of multi-topology (MT) routing for network resilience against link and node failures. We describe the multi-topologies by an n-dimensional vector of different link costs for all links in the network. It is the base for the calculation of n shortest path trees from any node to all other destinations, i.e. for n virtual routing topologies. We define the link costs in such a way that the routing topologies complement each other in the sense that at least one valid route remains in a single link or node failure scenario for each pair of nodes in at least one routing topology. In such a failure case, packets are rather deviated over the intact routing topology than discarded. The recovery speed of the presented mechanism is very fast and can be compared to fast rerouting mechanisms in MPLS, which reduce packet, drops to a minimum. In contrast to MPLS, MT routing is still a pure IP-based solution that retains the scalability and the robustness of IP routing. As the Internet takes an increasingly central role in our communications infrastructure, the slow convergence of routing protocols after a network failure becomes a growing problem. To assure fast recovery from link and node failures in IP networks, we present a new recovery scheme called Multiple Routing Configurations (MRC). Our proposed scheme guarantees recovery in all single failure scenarios, using a single mechanism to handle both link and node failures, and without knowing the root cause of the failure. MRC is strictly connectionless, and assumes only destination based hop-by-hop forwarding. MRC is based on keeping additional routing information in the routers, and allows packet forwarding to continue on an alternative output link immediately after the detection of a failure. It can be implemented with only minor changes to existing solutions.
The Reproduction of Specular Highlights on High Dynamic Range Displays

Recent advances in the design of high dynamic range (HDR) monitors enable the display of images having a large dynamic range, close to that encountered in the real world. As their usage will increase, we will be confronted with the problem of rerendering images that have been mapped to standard dynamic range (SDR) displays so that they look natural on HDR monitors. We address this issue for SDR images representing original HDR scenes. We propose a tone scale function that takes advantage of the increase in dynamic range of HDR monitors to recreate the brightness of specular highlights, which were clipped or compressed by the capturing and rendering process to SDR. We validate the use of such functions with a psychovisual experiment conducted on an HDR display, where the observers’ task was to judge pairs of tone-scaled images. The result of the experiment shows that using part of the extension of dynamic range provided by HDR displays to enhance the brightness of specular highlights leads to more natural looking images.
Simultaneous Humoral and Cellular Immune Response against Cancer–Testis Antigen NY-ESO-1: Definition of Human Histocompatibility Leukocyte Antigen (HLA)-A2–binding Peptide Epitopes

A growing number of human tumor antigens have been described that can be recognized by cytotoxic T lymphocytes (CTLs) in a major histocompatibility complex (MHC) class I–restricted fashion. Serological screening of cDNA expression libraries, SEREX, has recently been shown to provide another route for defining immunogenic human tumor antigens. The detection of antibody responses against known CTL-defined tumor antigens, e.g., MAGE-1 and tyrosinase, raised the question whether antibody and CTL responses against a defined tumor antigen can occur simultaneously in a single patient. In this paper, we report on a melanoma patient with a high-titer antibody response against the “cancer–testis” antigen NY-ESO-1. Concurrently, a strong MHC class I–restricted CTL reactivity against the autologous NY-ESO-1–positive tumor cell line was found. A stable CTL line (NW38-IVS-1) was established from this patient that reacted with autologous melanoma cells and with allogeneic human histocompatibility leukocyte antigen (HLA)-A2−, NY-ESO-1–positive, but not NY-ESO-1–negative, melanoma cells. Screening of NY-ESO-1 transfectants with NW38-IVS-1 revealed NY-ESO-1 as the relevant CTL target presented by HLA-A2. Computer calculation identified 26 peptides with HLA-A2–binding motifs encoded by NY-ESO-1. Of these, three peptides were efficiently recognized by NW38-IVS-1. Thus, we show that antigen-specific humoral and cellular immune responses against human tumor antigens may occur simultaneously. In addition, our analysis provides a general strategy for identifying the CTL-recognizing peptides of tumor antigens initially defined by autologous antibody.
CASS: A Context-Aware Simulation System for Smart Home

Ubiquitous computing (ubicomp) environments provide access to information and computing resources for users at any time and anywhere. In the approaching ubiquitous ear, many self-adaptive applications are emerging. These can be made to adapt to the environment within which the application operates. Context information is the key to producing self-adaptive applications in ubicomp environments. However, the supporting infrastructure that generates context information can be made dynamically responsive to the environment. Therefore, for the development of self-adaptive applications, it is necessary to demonstrate that valid context information can be created by virtual sensors instead of physical sensors. In this paper we present a context aware simulation system called CASS. In particular, it generates the context information associated with virtual sensors and virtual devices in a smart home domain. By using CASS, the self-adaptive application developer can immediately detect rule conflict in context information and determine optimal sensors and devices in a smart home.