Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Human Motion Detecting Device for Human-Machine Interface

This paper presents the development of a human-robot interface and a modified impedance controller, which generate robot motion which is appropriate for a human-robot interaction. The proposed control system enables a human operator to interact with the robot intuitively and stably. The proposed interface can simultaneously detect relative motion data as well as force data between the human operator and the robot during a human-robot interaction. The modified impedance controller, which is designed to handle not only the relative motion data but force data as well, generates familiar and intuitive motion for the human operator. In addition, the proposed interface mechanism, which provides an adequate stiffness, improves the stability of the control system. In order to confirm that the effectiveness of the proposed system, a supporting human operator's forearm experiment is carried out. Experimental results illustrate that the proposed interface and the proposed controller are effective for the human-robot interaction.
Ieee Transactions on Affective Computing Bridging the Gap between Social Animal and Unsocial Machine: a Survey of Social Signal Processing

—Social Signal Processing is the research domain aimed at bridging the social intelligence gap between humans and machines. This article is the first survey of the domain that jointly considers its three major aspects, namely modeling, analysis and synthesis of social behaviour. Modeling investigates laws and principles underlying social interaction, analysis explores approaches for automatic understanding of social exchanges recorded with different sensors, and synthesis studies techniques for the generation of social behaviour via various forms of embodiment. For each of the above aspects, the paper includes an extensive survey of the literature, points to the most important publicly available resources, and outlines the most fundamental challenges ahead.
Practice patterns for architecture reconstruction

Architecture reconstruction embodies benefits for commercial organizations. Reconstructing or recovering the architecture of software systems is primarily driven by the increased awareness of software architectures as a blueprint for systems and the resulting central role of architectures in development paradigms, like software product lines and component-based systems. This is especially the case for organizations that consciously want to migrate towards software architectures paradigms and enforce them in their software development life-cycle. This paper introduces practice patterns for architecture reconstruction, which offer common, problem/solution pairs to strategically apply architecture reconstruction at commercial organizations. Based on an. investigation of already developed and presented reconstruction approaches, the paper describes deficiencies that have been uncovered in several practice pattern's solution space and proposes improvements.
A 3D Neuronal Morphology Classification Approach Based on Convolutional Neural Networks

Since biological neurons have complex and diverse spatial geometric structures, classifying neurons according to their geometries has been an important issue. At present, the main approaches of neuron classification generally extract the structural features of neurons by the specified methods, and then use such features for classification. However, there are mainly two problems for these approaches. One is that there is no feature extraction standard of neuronal morphology, and the other is that a lot of useful information for neuron classification may be lost. Therefore, using the convolutional neural network model, this paper proposes a new three-dimensional (3D) neuronal morphology classification approach without geometric feature extraction. This approach first converts SWC format data of neuron into the scaled 3D neuronal graphics, and obtains the voxel data of neuronal morphology, and then uses convolutional neural network for training and classification. The experimental results show that this approach can classify the brain region cholinergic neurons of drosophila melanogaster, and obtains better classification accuracy.
4D-SETL - A Semantic Data Integration Framework

Although successfully employed as the foundation for a number of large-scale government and energy industry projects, foundational ontologies have not been widely adopted within mainstream Enterprise Systems (ES) data integration practice. However, as the closed-worlds of ES are opened to Internet scale data sources, there is an emerging need to better understand the semantics of such data and how they can be integrated. Foundational ontologies can help establish this understanding and therefore, there is a need to investigate how such ontologies can be applied to underpin practical ES integration solutions. This paper describes research undertaken to assess the effectiveness of such an approach through the development and application of the 4D-Semantic Extract Transform Load (4D-SETL) framework. 4D-SETL was employed to integrate a number of large scale datasets and to persist the resultant ontology within a prototype warehouse based on a graph database. The advantages of the approach included the ability to combine foundational, domain and instance level ontological objects within a single coherent system. Furthermore, the approach provided a clear means of establishing and maintaining the identity of domain objects as their constituent spatiotemporal parts unfolded over time, enabling process and static data to be combined within a single model.
The multiple faces of proteinkinase R in antiviral defense

Various pattern recognition receptors (PRRs) have been implicated in the detection of viral RNA and subsequent interferon (IFN) gene expression, including the double-stranded RNA-dependent proteinkinase R (PKR). Now, a novel role of PKR has been unveiled, as it was shown that, upon the infection with certain viruses, PKR is crucial for the integrity of newly synthesized IFN mRNA, thereby generating an optimal host antiviral immune response. There is a need of future studies to investigate additional roles of PKR in innate immunity and the molecular understanding of this novel function of PKR.
Persistent Activation of Nuclear Factor-&kgr;B by Interleukin-1&bgr; and Subsequent Inducible NO Synthase Expression Requires Extracellular Signal-Regulated Kinase

The role of extracellular signal-regulated kinase (ERK) was studied in the signaling pathway by which interleukin-1&bgr; (IL-1&bgr;) increases the expression of inducible NO synthase (iNOS) in rat vascular smooth muscle cells. IL-1&bgr; induced a rapid and transient activation of nuclear factor-&kgr;B (NF-&kgr;B), followed by a prolonged activation of NF-&kgr;B that was required to induce iNOS expression. Either PD98059 or U0126, selective inhibitors of ERK activation, did not influence IL-1&bgr;-induced early activation but effectively reduced the prolonged activation of NF-&kgr;B and significantly reduced IL-1&bgr; induction of iNOS. Transfection with antisense, but not sense, phosphorothioate-modified oligodeoxynucleotides directed toward ERK also reduced IL-1&bgr;-induced prolonged NF-&kgr;B activation and iNOS expression. I&kgr;B&bgr;, but not I&kgr;B&agr; degradation, induced by IL-1&bgr; was markedly attenuated when ERK activation was inhibited and could be partially responsible for the persistent NF-&kgr;B activation. These data suggest that ERK activity is required for persistent NF-&kgr;B activation by IL-1&bgr; that is necessary for iNOS gene expression.
Detection of facial areas in thermal images

This article deals with non-contact measurement of temperature in a human faces and describes program for the evaluation of temperature changes. It describes the algorithm of the program, the possibility of using and further deals with the possibilities of the segmentation of thermal images. Variety of image processing methods were used to design this algorithm including registration of images, segmentation using k-means clustering, Hough transformation, thresholding and others. The aim is to distinguish a human face from the hair and background. It also describes the possibility of detection of individual facial details. The functionality of those procedures was tested on experimental data.
Using twitter to recommend real-time topical news

Recommending news stories to users, based on their preferences, has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach to news recommendation that harnesses real-time micro-blogging activity, from a service such as Twitter, as the basis for promoting news stories from a user's favourite RSS feeds. A preliminary evaluation is carried out on an implementation of this technique that shows promising results.
An Information Foraging Approach to Determining the Number of Relevant Features

For many types of high-dimensional data, such as natural language corpora, the vast majority of extracted variables or features are essentially noise. Culling such features can not only reveal important patterns, but also improve the performance of supervised and unsupervised machine algorithms. Most research on feature selection has focused on the statistical measures used to rank features. Meanwhile, little work has been done developing techniques for identifying the optimal subset of features without repeatedly training models. However, developing such techniques is important, as they can signiﬁcantly decrease computation time while providing a way to determine the features that characterize the classes within a data set, independent of how the data may be clas-siﬁed in the future. Here we introduce a novel method based on information foraging that works in conjunction with existing feature ranking methods to automatically determine a subset of important features. The method is demonstrated on simulated and linguistic data from psychiatric interviews. We show that the method is able to accurately determine the features that characterize the classes within both data sets. The method is fast, simple, and independent of any method of classifying the data, and can be extended to any high-dimensional data set.
Combining Computational and Social Effort for Collaborative Problem Solving

Rather than replacing human labor, there is growing evidence that networked computers create opportunities for collaborations of people and algorithms to solve problems beyond either of them. In this study, we demonstrate the conditions under which such synergy can arise. We show that, for a design task, three elements are sufficient: humans apply intuitions to the problem, algorithms automatically determine and report back on the quality of designs, and humans observe and innovate on others’ designs to focus creative and computational effort on good designs. This study suggests how such collaborations should be composed for other domains, as well as how social and computational dynamics mutually influence one another during collaborative problem solving.
Iron and phosphorus cycling under ferruginous conditions

Considering the entirety of Earth’s history, the ocean has dominantly been in an anoxic, non-sulphidic state, with the water column containing dissolved iron (termed ‘ferruginous’). Despite the significance of such conditions, the cycling of nutrients in ferruginous settings remains poorly understood. Phosphorus (P) is thought to be the ultimate limiting nutrient on geological timescales. Therefore it is essential to constrain the behaviour of P under ferruginous conditions in order to evaluate feedback mechanisms associated with P stimulation of primary productivity, organic carbon burial and ultimately oxygen production. This study aims to further our understanding of iron (Fe) and P cycling under ferruginous conditions, through the investigation of a modern ferruginous lake and ancient sedimentary rocks deposited under ferruginous conditions. Modifications are made to the SEDEX P sequential extraction method to make it suitable for use with ancient sedimentary rocks and Fe-rich sediments. Using this newly revised method, the previously unidentified magnetite-bound pool of P is shown to have constituted a significant proportion of reactive P in many ancient ferruginous environments, indicating that magnetite may require further consideration when modelling P cycling under ferruginous conditions. Detailed investigation of the water column and sediments of the ferruginous Lake La Cruz reveals that whilst a substantial amount of P is released from the sediments, the formation of reduced Fe phosphates in the water column exerts a strong control on the vertical extent of the benthic P flux, a process that is most likely enhanced over the deeper water column depths of ancient ferruginous oceans. P partitioning in ancient sedimentary rocks from the ~1.8 billion year old Animikie Basin reveals that under stable redox environments, ferruginous conditions cause significant drawdown and burial of P, most likely resulting in a P limited water column. Whilst the majority of this P is now present as authigenic calcium phosphates, the presence of magnetite-bound P and observations of the modern ferruginous Lake La Cruz suggest this was most likely initially drawn down in association with Fe minerals.
Calibrating Satellite-Based Vegetation Indices to Estimate Evapotranspiration and Crop Coefficients

This paper presents a procedure to estimate actual evapotranspiration (ET) using a satellite-derived vegetation index. Actual ET is computed in a traditional manner using the crop coefficient (Kc) and reference ET (ETref) procedure (i.e., ET = Kc x ETref) with Kc estimated from the satellite-based NDVI. This study calibrated relationships between Kc and NDVI using satellite-based ET determined by surface energy balance. This unique approach enables calibration of the Kc vs NDVI equations using large numbers of sampled fields (in this case, more than 3000). Thus the calibration represents a regional average Kc estimate. The study was conducted for alfalfa, beans, sugar beet, corn, potatoes, and small grain crops, which are the major crops in southern Idaho. Estimation accuracy for ET was statistically evaluated. Average error of seasonal ET was within 5 percent of the energy balance (EB) determined ET for most crop types. Error in seasonal ET from individual fields is expected to be within 10 percent. NDVI based ET was compared with lysimeter measurements of ET from grass and sugar beets. The seasonal error of the NDVI based method was only 2 percent for grass and 6 percent for the sugar beets, as compared to lysimeter measurements. Statistical accuracy assessments suggest that NDVI based ET estimation can be a robust, simple and inexpensive tool to estimate ET from irrigated agricultural crops with reasonable good accuracy.
Double effort: Parental behavior of wild Azara's owl monkeys in the face of twins

In species of mammals that habitually bear single offspring, like most anthropoid primates, the occurrence of twins is expected to impose considerable energetic costs on the caretakers. The question then arises of how caregivers cope with the potentially increased costs of raising twins. These increased costs should lead to differing developmental rates in twins when compared to singletons, and/or to changes in the caregivers' behavior. Likewise, time budgets of parents of singletons are expected to differ from those of adults without offspring. Additionally, if twinning was an adaptive response to favorable ecological conditions, it should be more likely in years with high food abundance. Following the birth in 2011 of two sets of twins in a wild population of pair‐living Azara's owl monkeys (Aotus azarae) in Northern Argentina, we used long‐term demographic, behavioral, and phenological data to compare (a) the proportion of time that singleton and twin infants were carried by either parent; (b) adult time budgets and ranging behavior in groups with zero, one, or two infants; and (c) the availability of food in 2011 with food availability in other years. Twins, like singletons, were carried nearly exclusively by the male, and they were carried slightly more than singletons, suggesting a relatively inflexible pattern of infant care in the species. Time budgets showed that twin parents foraged more and moved less than singleton parents or groups without infants, despite the fact that phenological data indicate that fruit availability in 2011 was not substantially higher than in some of the other years. Overall, twinning thus presumably increased costs to breeders, especially males, but its effect on animals' long‐term reproductive success remains unclear. Am. J. Primatol. 76:629–639, 2014. © 2014 Wiley Periodicals, Inc.
Distress among Indigenous North Americans

Stress process and life-course models of mental distress emphasize sociocultural and historical processes that influence stress exposure and the impact of stress on mental health outcomes. Drawing from these theoretical orientations as well as concepts from the historical trauma literature, the authors examine the effects of culturally relevant and more generalized sources of stress on distress among North American Indigenous adults and test for the potential cumulative and interactive effects of stress on distress across the life course via self-reported early childhood and adult and contemporary stressors. Results of ordinary least squares regression analyses reveal positive, significant associations between general stressors and distress as well as culturally meaningful stressors and distress. In addition, the authors found evidence of the accumulating and interactive impact of stress on psychological distress.
Game theoretic analysis for MIMO radars with multiple targets

This paper considers a distributed beamforming and resource allocation technique for a radar system in the presence of multiple targets. The primary objective of each radar is to minimize its transmission power while attaining an optimal beamforming strategy and satisfying a certain detection criterion for each of the targets. Therefore, we use convex optimization methods together with noncooperative and partially cooperative game theoretic approaches. Initially, we consider a strategic noncooperative game (SNG), where there is no communication between the various radars of the system. Hence each radar selfishly determines its optimal beamforming and power allocation. Subsequently, we assume a more coordinated game theoretic approach incorporating a pricing mechanism. Introducing a price in the utility function of each radar/player enforces beamformers to minimize the interference induced to other radars and to increase the social fairness of the system. Furthermore, we formulate a Stackelberg game by adding a surveillance radar to the system model, which will play the role of the leader, and hence the remaining radars will be the followers. The leader applies a pricing policy of interference charged to the followers aiming at maximizing his profit while keeping the incoming interference under a certain threshold.We also present a proof of the existence and uniqueness of the Nash equilibrium (NE) in both the partially cooperative and non cooperative games. Finally, the simulation results confirm the convergence of the algorithm in all three cases.
Statistical Planetary Period Oscillation Signatures in Saturn's UV Auroral Intensity

Saturn's auroral emissions are a good measure of field‐aligned current (FAC) systems in the planet's magnetospheric environment. Previous studies based on magnetic field data have identified current systems rotating with the planetary period oscillations (PPOs) in both hemispheres, superimposed onto the local time‐invariant current system producing the main auroral emission. In this study we analyze the statistical behavior of Saturn's ultraviolet auroral emissions over the full Cassini mission using all suitable Cassini‐UVIS images acquired between 2007 and 2017. We examine auroral intensities by organizing the data by the two PPO coordinate systems. Strong statistical intensifications are observed close to the expected locations of upward FACs in both hemispheres, clearly supporting the main assumptions of the present theoretical model. We furthermore find clear signatures of modulation due to interhemispheric current closure from the PPO system in the opposite hemisphere, although with a weaker modulation amplitude. The auroral intensity in the northern hemisphere is shown to be modulated by a superposition of the FACs associated with both PPO systems, as the modulation phase and amplitude varies as expected for different relative orientations (beat phases) of the two PPO systems.
P2P shared-caching model: using P2P to improve client-server application performance

Client-server application model has several drawbacks such as server bottleneck and weak scalability. Peer-to-Peer (P2P) model resolves these problems by distributing tasks on the nodes participating in the system. P2P application development and protocol designing are much more difficult than client-server model. This paper proposes an approach to take the advantages of both models: the scalability of the P2P model and the simplicity of the client-server model. This paper presents a hybrid P2P and client-server model to achieve both goals based on caching mechanism which allows using cache content not only on a single client, but for all clients in the system. The proposed model has been applied to implement a Web application.
Considerations on the Measurement of the Stability of Oscillators with Frequency Counters

The most common time-domain measure of frequency stability, the Allan variance, is typically estimated using a frequency counter. Close examination of the operation of modern high-resolution frequency counters shows that they do not make measurements in the way commonly assumed. The consequence is that the results typically reported by many laboratories using these counters are not, in fact, the Allan variance, but a distorted representation. We elucidate the action of these counters by consideration of their operation in the Fourier domain, and demonstrate that the difference between the actual Allan variance and that delivered by these counters can be very significant for some types of oscillators. We also discuss ways to avoid, or account for, a distorted estimation of Allan variance.
How Musical are Images? From sound Representation to Image Sonification: an Eco Systemic Approach

Although sound visualization and image sonification have been extensively used for scientific and artistic purposes, their combined effect is rarely considered. In this paper, we propose the use of an iterative visualization/sonification approach as a sound generation mechanism. In particular, we visualize sounds using a textural self-similarity representation, which is then analysed to generate control data for a granular synthesizer. Following an eco-systemic approach, the output of the synthesizer is then fed back into the system, thus generating a loop designed for the creation of novel time-evolving sounds. All the process is real-time, implemented in Max/MSP using the FTM library. A qualitative analysis of the approach is presented and complemented with a discussion about visualization and sonification issues in the context of sound design.