Miracle-dz/UniFAR-FTUs huggingface dataset:
Turning Residual Stresses in Functionally Graded Steel Components

Introduction Metallic components with graded materials properties are of particular importance for the realization of lightweight design. The scientific basis of such concepts was provided by the Collaborative Research Centre TRR 30, funded by the German Research Foundation DFG between 2006 and 2015. As part of the project, thermo-mechanically graded components were manufactured by hot metal forming processes [1, 2]. Their characteristic properties are to a large extent determined by final machining operations. In this context, residual stresses play an important role for strength and lifetime of the produced parts. A survey about near surface residual stress states after hard turning of differently heat treated quenched and tempered steel AISI 6150 (51CrV4) is given in [3]. In the present paper, results of similar investigations carried out of Jominy end quench samples are reported and compared with results of samples with homogeneous microstructures.
Long D3-cycles in graphs with large minimum degree

It is shown that if G is a 2-connected graph on n vertices, with minimum degree such that n≤4δ−6, and with a maximum independent set of cardinality , then G contains a cycle of length at least min {n,n+2δ−2α−2g or G e F, where F denotes a well-known class of nonhamiltonian graphs of connectivity 2.
Load Model Based on Integrative K-means Clustering For Reliability Evaluation in Operational Planning

Aiming the deficiency of traditional load model used for reliability assessment, this paper proposes a new integrative K-means clustering algorithm incorporating load characteristics information. Based on the clustering algorithm, this model adopts multi-dimension correlation sampling technique considering bus load correlation load forecasting uncertainty to determine the bus load in evaluation period. At last, the effects of number of clustering, bus load correlation, and load forecast uncertainty are discussed and compared by case studies. The feasibility and reasonableness of the proposed algorithm are proved.
Bayesian sampling of genomic rearrangement scenarios via double cut and join

MOTIVATION When comparing the organization of two genomes, it is important not to draw conclusions on their modes of evolution from a single most parsimonious scenario explaining their differences. Better estimations can be obtained by sampling many different genomic rearrangement scenarios. For this problem, the Double Cut and Join (DCJ) model, while less relevant, is computationally easier than the Hannenhalli-Pevzner (HP) model. Indeed, in some special cases, the total number of DCJ sorting scenarios can be analytically calculated, and uniformly distributed random DCJ scenarios can be drawn in polynomial running time, while the complexity of counting the number of HP scenarios and sampling from the uniform distribution of their space is unknown, and conjectured to be #P-complete. Statistical methods, like Markov chain Monte Carlo (MCMC) for sampling from the uniform distribution of the most parsimonious or the Bayesian distribution of all possible HP scenarios are required. RESULTS We use the computational facilities of the DCJ model to draw a sampling of HP scenarios. It is based on a parallel MCMC method that cools down DCJ scenarios to HP scenarios. We introduce two theorems underlying the theoretical mixing properties of this parallel MCMC method. The method was tested on yeast and mammalian genomic data, and allowed us to provide estimates of the different modes of evolution in diverse lineages. AVAILABILITY The program implemented in Java 1.5 programming language is available from http://www.renyi. hu/~miklosi/DCJ2HP/.
A Music Emotion Recognition Algorithm with Hierarchical SVM Based Classifiers

This paper proposes a music emotion recognition algorithm consisting of a kernel-based class separability (KBCS) feature selection method, a nonparametric weighted feature extraction (NWFE) feature extraction method, and a hierarchical support vector machines (SVMs) classifier to recognize four types of music emotion. For each music sample, a total of 35 features from dynamic, rhythm, pitch, and timbre of music were generated from music audio recordings. With the extracted features via feature selection and extraction methods, hierarchical SVM-based classifiers are then utilized to recognize four types of music emotion including happy, tensional, sad and peaceful. The performance of the proposed algorithm was evaluated by two datasets with a total of 219 classical music samples. In the first dataset, music emotion of each sample was annotated by recruited subjects, while the second dataset was labelled by music therapists. The two datasets were used to verify the perceived emotions from normal audience and music expert, respectively. The average accuracy of the proposed algorithm achieved at 86.94% and 92.33% for these two music datasets, respectively. The experimental results have successfully validated the effectiveness of the proposed music emotion recognition algorithm with hierarchical SVM-based classifiers.
The insertion of ISAR targets into pre-existing SAR scenes

For the training of automatic target recognition algorithms, and of scene understanding in image intelligence, it is important to have the largest possible data base. This can be achieved by inserting targets that were measured in a tower/turntable configuration, into pre-existing SAR scenes. The blending has to be performed in exactly that stage of the SAR processing chain that produces a result corresponding to that as if the target had been present in the scene during the SAR overflight.
Functional connectivity in the thalamus and hippocampus studied with functional MR imaging.

BACKGROUND AND PURPOSE With functional connectivity functional MR imaging, co-variance in signal intensity has been shown in functionally related regions of brain in participants instructed to perform no cognitive task. These changes are thought to represent synchronous fluctuations in blood flow, which imply neuronal connections between the regions. The purpose of this study was to map functional connectivity in subcortical nuclei with functional connectivity functional MR imaging. METHODS Imaging data were acquired with an echo-planar sequence from six volunteers who performed no specific cognitive task. For functional connectivity functional MR imaging, a "seed" voxel or group of voxels was selected from the resting data set in the thalamus or in the hippocampus. Control voxels in gray matter presumed not to be eloquent cortex were also chosen. The correlation coefficient of the seed voxels and the control voxels with every other voxel in the resting data set was calculated. The voxels with correlation coefficients greater than or equal to 0.5 were mapped onto anatomic images for the functional connectivity functional MR images. The anatomic location of these voxels was determined by conventional parcellation methods. RESULTS For each participant, functional connectivity functional MR imaging maps based on four seed voxels in the thalamus or hippocampus showed clusters of voxels in the ipsilateral and contralateral thalamus or hippocampus. For control voxels, few voxels in the hippocampus or thalamus showed significant correlation. Significantly more pixels in the ipsilateral hippocampus correlated with the seed voxel than in the contralateral hippocampus. The differences between numbers of functionally connected voxels in ipsilateral thalamus and those in contralateral thalamus were not significant. CONCLUSIONS The thalamus and hippocampus show functional connectivity, presumably representing synchronous changes in blood flow.
De Novo Transcriptome Assembly in Chili Pepper (Capsicum frutescens) to Identify Genes Involved in the Biosynthesis of Capsaicinoids

The capsaicinoids are a group of compounds produced by chili pepper fruits and are used widely in many fields, especially in medical purposes. The capsaicinoid biosynthetic pathway has not yet been established clearly. To understand more knowledge in biosynthesis of capsaicinoids, we applied RNA-seq for the mixture of placenta and pericarp of pungent pepper (Capsicum frutescens L.). We have assessed the effect of various assembly parameters using different assembly software, and obtained one of the best strategies for de novo assembly of transcriptome data. We obtained a total 54,045 high-quality unigenes (transcripts) using Trinity software. About 92.65% of unigenes showed similarity to the public protein sequences, genome of potato and tomato and pepper (C. annuum) ESTs databases. Our results predicted 3 new structural genes (DHAD, TD, PAT), which filled gaps of the capsaicinoid biosynthetic pathway predicted by Mazourek, and revealed new candidate genes involved in capsaicinoid biosynthesis based on KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. A significant number of SSR (Simple Sequence Repeat) and SNP (Single Nucleotide Polymorphism) markers were predicted in C. frutescens and C. annuum sequences, which will be helpful in the identification of polymorphisms within chili pepper populations. These data will provide new insights to the pathway of capsaicinoid biosynthesis and subsequent research of chili peppers. In addition, our strategy of de novo transcriptome assembly is applicable to a wide range of similar studies.
Enhancing Presence in Head-Mounted Display Environments by Visual Body Feedback Using Head-Mounted Cameras

A fully-articulated visual representation of a user in an immersive virtual environment (IVE) can enhance the user's subjective sense of feeling present in the virtual world. Usually this requires the user to wear a full-body motion capture suit to track real-world body movements and to map them to a virtual body model. In this paper we present an augmented virtuality approach that allows to incorporate a realistic view of oneself in virtual environments using cameras attached to head mounted displays. The described system can easily be integrated into typical virtual reality setups. Egocentric camera images captured by a video-see-through system are segmented in real-time into foreground, showing parts of the user's body, e. g. , her hands or feet, and background. The segmented foreground is then displayed as inset in the user's current view of the virtual world. Thus the user is able to see her physical body in an arbitrary virtual world, including individual characteristics such as skin pigmentation and hairiness.
Selective activation of central subtypes of the nicotinic acetylcholine receptor has opposite effects on neonatal excitotoxic brain injuries

The incidence of neurological disabilities ascribable to perinatal injury is rising in Western countries, raising ethical and financial problems. No curative treatments are available. The pathophysiology of brain lesions of hypoxic‐ischemic or inflammatory origin involves various neurotransmitters or neuromodulators. Among these, glutamate plays a key role. By overactivating V‐methyl‐d‐aspartate receptors, it triggers the excitotoxic cascade. Although addictive, nicotine prevents excitotoxic neuronal death in adult animals. Its potential neuroprotective effects have not been evaluated in neonates. We found that nicotine is neuroprotective in vivo, in a murine model of neonatal excitotoxic brain injury, and in vitro, in primary cultures of cortical neurons. We investigated the respective roles in nicotine‐related neuroprotection of the two dominant nicotinic acetylcholine receptor (nAChR) isoforms, namely, α4β2 (heteropentameric) and α7 (homopentameric). Inhibition of α4β2, either pharmacological (i.e., an α4β2 nAChR antagonist) or molecular (β2‐/‐ knockout mice), abolished the protective effect of nicotine in vivo and in vitro, suggesting the involvement of α4β2 nAChR in neonatal nicotine‐related neuroprotection. In contrast, activation of α7 nAChR, which is protective in adult animals, was deleterious in our neonatal model, whereas its blockade, either pharmacological or molecular (α7‐/‐ knockout mice) provided neuroprotection. Neuroprotective strategies must consider these opposite properties of distinct nAChR isoforms in neonates.
Application of Analog Network Coding to MIMO Two-Way Relay Channel in Cellular Systems

An efficient analog network coding transmission protocol is proposed in this letter for a MIMO two way cellular network. Block signal alignment is first proposed to null the inter-user interference for multi-antenna users, which makes the dimensions of aligned space larger compared with the existing signal alignment. Two algorithms are developed to jointly design the precoding matrices at the relay and BS for outage optimization. The performance of this transmission protocol is also verified by simulations.
Structural Properties of Buyback Contracts for Price-Setting Newsvendors

This paper studies a buyback contract in the Stackelberg framework of a manufacturer (leader) selling to a price-setting newsvendor retailer (follower). Using an analytical model that focuses on a multiplicative demand form, we generalize previous results and produce new structural insights. A novel transformation technique first enables us to establish the unimodality of the profit functions for both channel partners, under relatively mild assumptions. Further analysis identifies the necessary and sufficient condition under which the optimal contract for the manufacturer (wholesale and buyback prices) is distribution free, i.e., independent of the uncertainty in customer demand. A specific instance of the above condition is also necessary and sufficient for a no-buyback contract to be optimal from the manufacturer's perspective. We then prove that the optimal performance of the decentralized channel for distribution-free buyback contracts depends only on the curvature of the deterministic demand part. In addition, some of the optimal decisions and relevant profit ratios for buyback contracts in our setting are shown to be identical to those for their deterministic price-only counterparts.
On search decision and the efficiency of polynomial-time algorithms

Recent advances in well-partial-order theory, especially the seminal contributions of Robertson and Seymour, have troubling consequences for those who would equate tractability with polynomial-time decidability. Specifically:many problems are now known to be decidable in low-degree polynomial time, but only by decision algorithms with overwhelmingly astronomical constants of proportionality, the existence of such a polynomial-time decision algorithm alone does not ensure that a corresponding search problem can be solved efficiently, and even if both a decision problem and a corresponding search problem can be shown to be polynomial-time computable, there is no guarantee that correct algorithms can be found or even recognized within any bounded amount of time. In this paper, we present a number of techniques for dealing with these remarkable features of algorithms based on well-partially-ordered sets. Our main results include a general strategy with which such algorithms can be made constructive. With the aid of this method, we demonstrate that low-degree polynomial-time algorithms are now known for almost all of the catalogued applications of RS posets. We also prove that, despite the nonconstructive nature of the well-partial-order theory on which this line of research is based, no RS poset application can settle P @@@@ N P non-constructively by any established method of argument.
THE IDENTIFICATION OF DATA PRIMITIVES TO SEPARATE THE CONCEPTS AND SEMANTICS OF LAND COVER AND LAND USE : THE EXAMPLE OF ‘FOREST’

This paper is concerned with data and classifications that confuse the concepts of land cover and land use. Conceptual confusion is problematic for data integration and modelling. This has resulted in calls for the separation of land use and land cover from the global land monitoring community. Text mining approaches are combined with social network analyses as a method for unravelling the different concepts embedded in land cover and land use semantics and applied to descriptions of forest cover and use. Whilst the results show the distinct biological dimension to land cover descriptions and the socio-economic character of land use, they reveal the deep degree of semantic confusion embedded in land cover and land use descriptions. The implications for this lack of internal semantic accuracy and consistency in land resource inventories are discussed and the case made for separating the concepts of land cover from land use.
Learning to Coordinate Behaviours for Robot Navigation

Past approaches to navigating behavior-based robots have relied on apriori determined arbitration schemes to control the total behaviour of a robot. Such arbitrators can only resolve deadlocks between competing behaviours by introducing randomness. Without monitoring its self-behaviour and using state information a robot can not improve its performance. We show that by continually monitoring it's actions (the output of behaviours) a robot can discover the deadlocking features (local minima) in the environment that cause failure. The robot can determine the correct arbitration sequence between its behaviours that is needed to resolve the conflict. We present experimental results of a Nomad robot discovering and then using environment features to escape local minima while navigating in unknown environments.
How “Social” is the social Simon effect?

In the standard Simon task, participants carry out spatially defined responses to non-spatial stimulus attributes. Responses are typically faster when stimulus location and response location correspond. This effect disappears when a participant responds to only one of the two stimuli and reappears when another person carries out the other response. This social Simon effect (SSE) has been considered as providing an index for action co-representation. Here, we investigated whether joint-action effects in a social Simon task involve mechanisms of action co-representation, as measured by the amount of incorporation of another person's action. We combined an auditory social Simon task with a manipulation of the sense of ownership of another person's hand (rubber hand illusion). If the SSE is established by action co-representation, then the incorporation of the other person's hand into one's own body representation should increase the SSE (synchronous > asynchronous stroking). However, we found the SSE to be smaller in the synchronous as compared to the asynchronous stroking condition (Experiment 1), suggesting that the SSE reflects the separation of spatial action events rather than the integration of the other person's action. This effect is independent of the active involvement (Experiment 2) and the presence of another person (Experiment 3). These findings suggest that the “social” Simon effect is not really social in nature but is established when an interaction partner produces events that serve as a spatial reference for one's own actions.
Subspace anytime stream clustering

Clustering of high dimensional streaming data is an emerging field of research. A real life data stream imposes many challenges on the clustering task, as an endless amount of data arrives constantly. A lot of research has been done in the full space stream clustering. To handle the varying speeds of the data stream, "anytime" algorithms are proposed but so far only in full space stream clustering. However, data streams from many application domains contain abundance of dimensions; the clusters often exist only in specific subspaces (subset of dimensions) and do not show up in the full feature space. In this paper, the first algorithm that considers both the high dimensionality and the varying speeds of streaming data, is proposed. The algorithm, called SubClusTree, can flexibly adapt to the different stream speeds and makes the best use of available time to provide a high quality subspace clustering. The experimental results prove the effectiveness of our anytime subspace concept.
Kinetic bounding volume hierarchies for collision detection of deformable objects

We present novel algorithms for updating bounding volume hierarchies of objects undergoing arbitrary deformations. Therefore, we introduce two new data structures, the kinetic AABB tree and the kinetic BoxTree. The event-based approach of the kinetic data structures framework enables us to show that our algorithms are optimal in the number of updates. Moreover, we show a lower bound for the total number of BV updates, which is independent of the number of frames. Furthermore, we present a kinetic data structures which uses the kinetic AABB tree for collision detection and show that this structure can be easily extended for continuous collision detection of deformable objects. We performed a comparison of our kinetic approaches with the classical bottom-up update method. The results show that our algorithms perform up to ten times faster in practically relevant scenarios.
Check list of ground-dwelling ant diversity (Hymenoptera: Formicidae) of the Iguazú National Park with a comparison at regional scale

We describe the ant fauna of Iguazu National Park (INP), a region of high biodiversity and endemism in northeastern Argentina that includes the southernmost protected area of the Atlantic Forest (AF). Ants were sampled over seven periods from 1998 to 2011 using a variety of techniques. We also surveyed museum collections and the scientific literature to obtain additional records of ants from INP. In addition to providing a species list, we compare ant composition of INP to other sites in the Upper Parana, Serra do Mar Coastal Forest and Araucaria eco-regions. A total of 165 ant species belonging to 57 genera are reported; 67 species are new records for Misiones Province and 48 species are reported from Argentina for the first time. Alto Parana and Canindeyu departments in Paraguay present the most similar ant fauna to INP. Serra da Bodoquena in Brazil showed higher similarity with the Upper Parana AF eco-region, despite that Serra da Bodoquena is composed of a mix of eco-regions. Ant diversity was lower in Upper Parana than in Serra do Mar Coastal Forest eco-region. This difference may result from higher primary productivity and a greater altitudinal variation in the coastal region.
ReviveNet: A Self-Adaptive Architecture for Improving Lifetime Reliability via Localized Timing Adaptation

The aggressive technology scaling poses serious challenges to lifetime reliability. A parament challenge comes from a variety of aging mechanisms that can cause gradual performance degradation of circuits. Prior work shows that such progressive degradation can be reliably detected by dedicated aging sensors, which provides a good foundation for proposing a new scheme to improve lifetime reliability. In this paper, we propose ReviveNet, a hardware-implemented aging-aware and self-adaptive architecture. Aging awareness is realized by deploying dedicated aging sensors, and self-adaptation is achieved by employing a group of synergistic agents. Each agent implements a localized timing adaptation mechanism to tolerate aging-induced delay on critical paths. On the evaluation, a reliability model based on widely used weibull distribution is presented. Experimental results show that, without compromising with any nominal architectural performance, ReviveNet can improve the Mean-Time-To-Failure by up to 48.7 percent, at the expense of 9.5 percent area overhead and small power increase.
Fish eye OLSR scaling properties

Scalability is one of the toughest challenges in ad hoc networking. Recent work outlines theoretical bounds on how well routing protocols could scale in this environment. However, none of the popular routing solutions really scales to large networks, by coming close enough to these bounds. In this paper, we study the case of link state routing and OLSR, one of the strongest candidates for standardization. We analyze how these bounds are not reached in this case, and we study how much the scalability is enhanced with the use of Fish eye techniques in addition to the link state routing framework. We show that with this enhancement, the theoretical scalability bounds are reached.