Miracle-dz/UniFAR-FTUs huggingface dataset:
Behaviour coordination for navigation in office environments

Behaviour coordination is a notorious problem in mobile robotics. Behaviours are either in competition or collaborating to achieve the goals of a system, which leads to requirements for arbitration and/or fusion of control signals. In most systems the arbitration is specified in terms of "events" that denote positions or sensory input. The detection of these events allows discrete switching between groups of behaviours. In contrast, the fusion of behaviours is often achieved using potential fields, fuzzy rules, or superposition. In most cases, the underlying theoretical foundation is rather weak and the behaviour switching results in discrete changes in the overall system dynamics. In this paper, we present a scheme for behaviour coordination that is grounded in the dynamical systems approach. The methodology provides a solid theoretical basis for analysis and design of a behaviour coordination framework. This framework is demonstrated in the context of a domestic robot for fetch-and-carry type tasks. It is here shown that behaviour coordination can be analyzed as an integral part of the design to facilitate smooth transition and fusion between behaviours.
Sensitivity to Changing Contingencies Predicts Social Success

To adapt one’s behavior to suit changing social contingencies, it is necessary to be skillful at detecting such changing contingencies in the first place. As a consequence, the ability to detect changing contingencies (reversal learning) should predict social competence across both competitive and cooperative social settings. Consistent with this possibility, Study 1 revealed that better reversal learning predicted more effective conflict management and partner happiness within romantic relationships. Studies 2a and 2b found that better reversal learning predicted less satisfied negotiation partners, an effect mediated by the positive relationship between reversal-learning performance and value gained from the negotiation. In Study 3, better reversal learning predicted greater partner cooperation and more favorable outcomes in a multi-round prisoners’ dilemma game. These results suggest that the capacity to detect changing contingencies, and thereby modify one’s behavior in response to a socially dynamic world, facilitates interpersonal competence across a variety of social domains.
New genes that extend Caenorhabditis elegans’ lifespan in response to reproductive signals

In Caenorhabditis elegans and Drosophila, removing germline stem cells increases lifespan. In C. elegans, this lifespan extension requires DAF‐16, a FOXO transcription factor, and DAF‐12, a nuclear hormone receptor. To better understand the regulatory relationships between DAF‐16 and DAF‐12, we used microarray analysis to identify downstream genes. We found that these two transcription factors influence the expression of distinct but overlapping sets of genes in response to loss of the germline. In addition, we identified several new genes that are required for loss of the germline to increase lifespan. One, phi‐62, encodes a conserved, predicted RNA‐binding protein. PHI‐62 influences DAF‐16‐dependent transcription, possibly by collaborating with TCER‐1, a putative transcription elongation factor, and FTT‐2, a 14‐3‐3 protein known to bind DAF‐16. Three other genes encode proteins involved in lipid metabolism; one is a triacylglycerol lipase, and another is an acyl‐CoA reductase. These genes do not noticeably affect bulk fat storage levels; therefore, we propose a model in which they may influence production of a lifespan‐extending signal or metabolite.
Design of a robust receiver for chaotic switching maps of DC-DC power electronics transmitter converters for secure communication

This paper aims to open a new vista of research in the direction of possible application of power electronics DC-DC converters in analog chaotic communication. Most of the work reported on analog chaotic communication is based on the pioneer work of Pecora and Caroll, with synchronization between transmitter and receiver. Receiver based on synchronization, also known as coherent receiver, has a disadvantage of parameter mismatch and is sensitive to noise. In the present work, firstly, a secure transmitter using chaotic DC-DC converters is proposed that encrypts information using chaotic switching map technique. In chaotic switching map technique, the message is encrypted by randomly switching from one chaotic converter to another. The bifurcation parameter of the randomly switched chaotic converter is modulated by the message. Secondly, an attempt has been made to design a robust non-coherent receiver that is adaptable to the switching chaotic transmitters, even in the presence of noise. Once the receiver identifies the chaotic converter, it can decode the message as per the decryption algorithm. With the proposed non-coherent receiver, the disadvantages of coherent receivers can be overcome. We have also devised a prototype smart meter, used in smart distribution grid for implementing the proposed communication technique. Copyright © 2016 John Wiley & Sons, Ltd.
The notion of personality: historical and recent perspectives

To the scientist, personality is the complexity of psychological structures and processes that contribute to the unity and continuity of individual conduct and experience. Personality psychologists explore the mechanisms that mediate person–environment transactions and the ways in which these psychological mechanisms give rise to the uniqueness of each person. This paper reviews the history of the discipline of personality psychology and the current status of the field. It urges investigators to attend to the proactive, self-regulatory features of personality. People are self-organizing, proactive beings, not just reactive organisms. Self-reflective and self-regulatory capabilities enable people to shape the nature of their experiences and life paths. This potentialist view of personality enables one to identify and promote the social conditions required for the full realization of human capacities.
Morphological and atomic analytical studies on enamel and dentin irradiated by an erbium, chromium:YSGG laser.

OBJECTIVE The purposes of this study were to investigate the morphological and atomic analytical changes and to evaluate the cutting effect on dental hard tissues of this laser in vitro. BACKGROUND DATA There have been few reports on morphological and atomic analytical study of dental hard tissues after erbium,chromium:yttrium,scandium,gallium,garnet (Er,Cr:YSGG) laser irradiation. METHODS Eighteen extracted human molars were sectioned into 3-mm-thick slices, which were irradiated with water-air spray by an Er,Cr:YSGG laser at 6.0 W and 20 Hz for 5 sec for enamel and 5.0 W and 20 Hz for 5 sec for dentin. The samples were then morphologically observed and examined atomic-analytically. RESULTS Regular holes having sharp edges and smooth walls, but no melting or carbonization, were observed in both samples. An atomic analytical examination showed that the calcium ratio to phosphorus showed no significant changes between the lased areas and unlased areas (p > 0.01). CONCLUSION These results showed that the Er,Cr:YSGG laser has a good cutting effect on dental hard tissues and offers advantages of no burning or melting after laser irradiation.
Structure of the actin-depolymerizing factor homology domain in complex with actin

Actin dynamics provide the driving force for many cellular processes including motility and endocytosis. Among the central cytoskeletal regulators are actin-depolymerizing factor (ADF)/cofilin, which depolymerizes actin filaments, and twinfilin, which sequesters actin monomers and caps filament barbed ends. Both interact with actin through an ADF homology (ADF-H) domain, which is also found in several other actin-binding proteins. However, in the absence of an atomic structure for the ADF-H domain in complex with actin, the mechanism by which these proteins interact with actin has remained unknown. Here, we present the crystal structure of twinfilin's C-terminal ADF-H domain in complex with an actin monomer. This domain binds between actin subdomains 1 and 3 through an interface that is conserved among ADF-H domain proteins. Based on this structure, we suggest a mechanism by which ADF/cofilin and twinfilin inhibit nucleotide exchange of actin monomers and present a model for how ADF/cofilin induces filament depolymerization by weakening intrafilament interactions.
Face recognition using SVM decomposition methods

Support vector machines (SVM) decomposition methods were proposed to solve high dimensional and/or large data classification problems. Two major decomposition algorithms: Karush-kuhn-Tucker (KKT) condition based algorithm, and 'Joachims' decomposition algorithm are popularly adopted. In this paper, both these two decomposition methods are analyzed and applied into face recognition with three basic mapping kernels. Numerical results showed that: a) face recognition with SVM performs better accuracy than other existed methods; b) the decomposition methods can perform face recognition efficiently; c) Joachims' decomposition method has better accuracy than that of decomposition algorithm based on KKT condition; d) linear kernel can provide much higher recognition accuracy than polynomial and slightly better accuracy than Gaussian radial based function (RBF) kernel; Also due to the fact that the linear kernel method is much simpler than others, it is most suitable for face recognition.
Application of CO2 laser evaporation in locally advanced melanoma

Aim: This study aims to investigate the role of CO2 laser evaporation in the treatment of melanoma patients with satellite or in-transit metastases. Materials & methods: Patients who underwent CO2 laser evaporation were retrospectively included between November 2002 and August 2018. The Sharplan 40C CO2 laser was used with a high pulse wave mode. Data concerning patient and tumor characteristics, CO2 laser evaporation and subsequent therapies were collected. Results: A total of 26 patients were included. Median duration of local control was 5.5 months. The median number of lesions evaporated per treatment was three (1–16); patients received a median of three (1–19) treatments. Conclusion: In a selected group of melanoma patients with satellite or in-transit metastases, CO2 laser evaporation should be considered as treatment for local control.
Statistically-Enhanced Fine-Grained Diagnosis of Packet Losses

Packet losses are an important class of adverse events in Wireless Sensor Networks (WSNs), they can be caused by either a compromised or misbehaving node, or an attack focused on the wireless links of the network. Understanding the underlying cause is critical for the deployment of effective response measures aimed at restoring the network functionality. Shebaro et al. [9] proposed an initial approach for fine-grained analysis (FGA) of packet losses, and implemented and evaluated a tool based on it. Such approach profiles the wireless links between the nodes using resident metrics, such as the received signal strength indicator (RSSI) and the link quality indicator (LQI) for every packet, in order to achieve an accurate diagnosis of their root causes. The accuracy of their approach relies on the correct choice of some system parameters and thresholds, and empirically-determined values such as those proposed in their work might not always be optimal. Moreover, to reduce the burden on the network administrator, their approach uses a single threshold value set for the entire WSN, which can be suitable for some neighborhoods but not appropriate for others. In this work, we design an approach that builds a statistical model for determining optimal system thresholds by exploiting the variances of RSSI and LQI. Our model also has the advantage of allowing the setting of an individual threshold for each link. We have validated our approach through extensive MATLAB simulations based on real sensor data, showing that our model is accurate and its system parameters lead to an optimally-accurate fine-grained analysis of the underlying causes of packet losses.
Information measures quantifying aperiodic stochastic resonance.

Aperiodic stochastic resonance ~ASR! is a phenomenon in which the response of a nonlinear system to a subthreshold information-bearing signal is optimized by the presence of noise. We have previously characterized this effect by the use of cross-correlation-based measures. Here we apply a measure ~transinformation! that directly quantifies the rate of information transfer from stimulus to response and show that the presence of noise optimizes the information-transfer rate. By considering a nonlinear system ~the FitzHugh-Nagumo model! that captures the functional dynamics of neuronal firing, we demonstrate that sensory neurons could, in principle, harness ASR to optimize the detection and transmission of weak stimuli. @S1063-651X~96! 51309-7#
Opleiding Informatica Using Convolutional Autoencoders to Detect Anomalies in Sewer Images

The Dutch sewer system is currently inspected manually, which leads to inconsistent and subjective inspections. This is why the SewerSense project was started, which aims to automate the inspection process. In this thesis, a convolutional autoencoder (CAE) was designed to see if this method is a viable option for the use of anomaly detection. First, the proof of concept is illustrated using the MINST and CIFAR-10 image sets. The CAE proved to perform excellent on these sets. An experiment was conducted to analyse whether the CAE also performs well on the sewer pipe image sets. Two image sets were available: one with smooth concrete and one with coarse agglomerate. The CAE has an acceptable performance on the smooth concrete image set, but performs unsatisﬁable on the coarse agglomerate image set.
The H I Content of E+A Galaxies

We present deep single-dish H I observations of a sample of six nearby E+A galaxies (0.05 < z < 0.1). A nonnegligible fraction of a local sample of E+As are detected in H I. In four galaxies, we have detected up to a few times 109 M☉ of neutral gas. These E+A galaxies are almost as gas-rich as spiral galaxies with comparable luminosities. There appears to exist no direct correlation between the amount of H I present in an E+A galaxy and its star formation rate as traced by radio continuum emission. Moreover, the end of the starburst does not necessarily require the complete exhaustion of the neutral gas reservoir. Most likely, an intense burst of star formation consumed the dense molecular clouds, which are the sites of massive star formation. This effectively stops star formation, even though copious amounts of diffuse neutral gas remain. The remaining H I reservoir may eventually lead to further episodes of star formation. This may indicate that some E+As are observed in the inactive phase of the star formation duty cycle.
Photo rating of facial pictures based on image segmentation

A single glance at a face is enough to infer a first impression about someone. With the increasing amount of pictures available, selecting the most suitable picture for a given use is a difficult task. This work focuses on the estimation of the image quality of facial portraits. Some image quality features are extracted such as blur, color representation, illumination and it is shown that concerning facial picture rating, it is better to estimate each feature on the different picture parts (background and foreground). The performance of the proposed image quality estimator is evaluated and compared with a subjective facial picture quality estimation experiment.
A queue analytics system for taxi service using mobile crowd sensing

Passengers waiting queues and taxis waiting queues are commonly seen in many urban cities. Our poster presents a queue analytics system, which collaboratively uses the mobile data from taxis and smartphones, to detect both passenger queues and taxi queues. In particular, the system firstly determines the existence of taxi queues by analyzing the taxi data, and then make a soft inference on passenger queues. Meanwhile, the passenger side adopts the smartphone-based crowd sensing strategy to detect the personal-scale queuing activities. Lastly, the system aggregates the detection results and validates passenger queues. The extensive empirical experiments demonstrate our system can accurately and effectively achieve the design objectives. Moreover, the system envisions a novel crowd sensing way to perform online analysis using data from heterogeneous sources.
A Theory of Unsupervised Speedup Learning

Speedup learning seeks to improve the efficiency of search-based problem solvers. In this paper, we propose a new theoretical model of speedup learning which captures systems that improve problem solving performance by solving a user-given set of problems. We also use this model to motivate the notion of "batch problem solving," and argue that it is more congenial to learning than sequential problem solving. Our theoretical results are applicable to all serially decomposable domains. We empirically validate our results in the domain of Eight Puzzle.
An Exploratory Study of Child Molesters’ Relationship Patterns Using the Core Conflictual Relationship Theme Method

This study examined the relationship patterns of N = 20 child molesters (CM) using the Core Conflictual Relationship Theme (CCRT) method. The relationship patterns of the CMs were compared with those of a control group of N = 20 subjects from an out patient counseling service. Results showed that CMs had significantly less wish to be controlled, hurt, and not responsible than the control group. No significant difference was found between both groups for the CCRT response of other component (RO). For the response of self (RS) component, results indicated that CMs reported more relationship episodes in which they felt respected and accepted and self-controlled and self-confident. The authors suggest that these interactions could be indicators of the CMs’attempts to attribute blame to others andpresent themselves as victims. It is also suggested that CMs may have core issues involving autonomy and control.
Machine Translation by Pattern Matching

The best systems for machine translation of natural language are based on statistical models learned from data. Conventional representation of a statistical translation model requires substantial offline computation and representation in main memory. Therefore, the principal bottlenecks to the amount of data we can exploit and the complexity of models we can use are available memory and CPU time, and current state of the art already pushes these limits. With data size and model complexity continually increasing, a scalable solution to this problem is central to future improvement. Callison-Burch et al. (2005) and Zhang and Vogel (2005) proposed a solution that we call translation by pattern matching, which we bring to fruition in this dissertation. The training data itself serves as a proxy to the model; rules and parameters are computed on demand. It achieves our desiderata of minimal offline computation and compact representation, but is dependent on fast pattern matching algorithms on text. They demonstrated its application to a common model based on the translation of contiguous substrings, but leave some open problems. Among these is a question: can this approach match the performance of conventional methods despite unavoidable differences that it induces in the model? We show how to answer this question affirmatively. The main open problem we address is much harder. Many translation models are based on the translation of discontiguous substrings. The best pattern matching algorithm for these models is much too slow, taking several minutes per sentence. We develop new algorithms that reduce empirical computation time by two orders of magnitude for these models, making translation by pattern matching widely applicable. We use these algorithms to build a model that is two orders of magnitude larger than the current state of the art and substantially outperforms a strong competitor in Chinese-English translation. We show that a conventional representation of this model would be impractical. Our experiments shed light on some interesting properties of the underlying model. The dissertation also includes the most comprehensive contemporary survey of statistical machine translation.
Ret finger protein-like 3 promotes tumor cell growth by activating telomerase reverse transcriptase expression in human lung cancer cells

In this study, we identified ret finger protein-like 3 (RFPL3) as a hTERT promoter binding protein in lung cancer cells. The high hTERT promoter-binding activity of RFPL3 was detected in lung cancer cells compared to normal cells. Chromatin immunoprecipitation confirmed RFPL3 as a tumor-specific hTERT promoter binding protein. Overexpression of RFPL3 activated hTERT promoter and up-regulated hTERT expression and telomerase activity. Inhibition of RFPL3 expression by siRNA suppressed hTERT promoter activation and telomerase activity. Inhibition of RFPL3 by siRNA or shRNA also significantly inhibited tumor cell growth in vitro and in a xenograft mouse model in vivo. Immunohistochemical analysis of 181 human lung adenocarcinomas specimens showed a significant correlation between RFPL3 and hTERT expression. The overexpression of RFPL3 was also associated significantly with lymph node metastasis. Univariate and multivariate Cox model analyses of NSCLC clinical specimens revealed a strong correlation between RFPL3 expression and overall survival. These results demonstrate that RFPL3 is an important cellular factor which promotes lung cancer growth by activating hTERT expression and may be a potential novel therapeutic target for lung cancer.
The Effect of Frequency and Type of Internet Use on Perceived Social Support and Sense of Well-Being in Individuals With Spinal Cord Injury

This article examines the effect of frequency and type of Internet use on perceived social support and sense of well-being in persons with spinal cord injury. The results show that Internet use is not significantly related to perceived social support. Bivariate analysis indicates that there is a significant negative association between total Internet use and overall sense of well-being. Simultaneous regression further investigated the nature of this relationship by examining the contribution of 10 online activities to four scales measuring sense of well-being. Frequency of online gaming was negatively associated with each scale. Disability-related information seeking was also negatively associated with psychological and financial well-being, as well as perceived social support. These results suggest that Internet use as a whole should not be overlooked by rehabilitation counselors for its practical uses to increase independence and social connectedness in persons with disabilities; however, care should be used, particularly with online gaming.
Recursive soft morphological filters

We present properties of recursive soft morphological filters that use previously filtered outputs as their inputs, cascade combinations of these filters, and the idempotent recursive soft morphological filters. The development allows problems in the implementation of cascaded recursive soft morphological filters to be reduced to the equivalent problems of a single recursive standard morphological filter.