Miracle-dz/UniFAR-FTUs huggingface dataset:
Author ' s personal copy Anterior insular cortex anticipates impending stimulus signi fi cance

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o Touch is a fundamental, but complex, element of everyday interaction that impacts one's sensory and affective experience via interoceptive processing. The insular cortex is an integral component of the neural processes involved in interoception, i.e. the generation of an " emotional moment in time " through the sensing of the internal body state (Craig, A.D., 2002. How do you feel? Interoception: the sense of the physiological condition of the body. Nat. Rev. Neurosci 3, 655–666.). Here, we examine the contribution of different parts of the insular cortex in the representation of both affective and sensory aspects of touch. To that end, subjects were administered a cued application of touch during functional MRI. We find that stimulus-related activation occurs in the mid-to-posterior insula, whereas anticipatory related activation is seen mostly in anterior insula. Moreover, the degree of activation in anterior insula during anticipation is correlated with the degree of activation in the posterior insula and caudate during stimulus processing. Finally, the degree of activation in the anterior insula during anticipation is also correlated with experienced intensity of the touch. Taken together, these results are consistent with the hypothesis that the anterior insula is preparing for the sensory and affective impact of touch. This preparatory function has important implications for the understanding of both anxiety and addictive disorders because dysfunctions in anticipatory processing are a fundamental part of the psychopathology. Introduction Touch impacts both sensory and affective processes and, as such, acts as an important component of daily human interactions. In particular, human touch can attenuate stress-related activity in both the brain and body (Coan et al., 2006; Devries et al., 2003) and provides for supportive social behavior and. Moreover, touch by a human hand can produce pleasure and is often associated with significant reward value (Rolls, 2000). Finally, touch intensifies emotional displays from other modalities (Knapp and Hall, 1997) and is even able to convey distinct types of emotion (Hertenstein et al., 2006). Touch by an external object, including another human being, affects a number of subcutaneous receptors, which signal a change …
Scalable multi-relational association mining

We propose the RADAR technique for multirelational data mining. This permits the mining of very large collections and provides a technique for discovering multirelational associations. Results show that RADAR is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the Farmer and Warmr tools.
Herschel-ATLAS: VISTA VIKING near-infrared counterparts in the Phase 1 GAMA 9-h data

We identify near-infrared Ks-band counterparts to Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) submillimetre (submm) sources, using a preliminary object catalogue from the VISTA Kilo-degree Infrared Galaxy (VIKING) survey. The submm sources are selected from the H-ATLAS Phase 1 catalogue of the Galaxy and Mass Assembly 9-h field, which includes all objects detected at 250, 350 or inline image with the instrument. We apply and discuss a likelihood ratio method for VIKING candidates within a search radius of 10 arcsec of the 22 000 SPIRE sources with a 5σ detection at inline image. We estimate the fraction of SPIRE sources with a counterpart above the magnitude limit of the VIKING survey to be Q0≈ 0.73. We find that 11 294 (51 per cent) of the SPIRE sources have a best VIKING counterpart with a reliability R≥ 0.8, and the false identification rate of these is estimated to be 4.2 per cent. We expect to miss ∼5 per cent of true VIKING counterparts. There is evidence from Z−J and J−Ks colours that the reliable counterparts to SPIRE galaxies are marginally redder than the field population. We obtain photometric redshifts for ∼68 per cent of all (non-stellar) VIKING candidates with a median redshift of inline image. We have spectroscopic redshifts for 3147 (∼28 per cent) of the reliable counterparts from existing redshift surveys. Comparing to the results of the optical identifications supplied with the Phase 1 catalogue, we find that the use of medium-deep near-infrared data improves the identification rate of reliable counterparts from 36 to 51 per cent.
Inference of Stochastic Regular Grammars by Massively Parallel Genetic Algorithms

A Mathematical Analysis of Tournament Selection p. 9 On Decentralizing Selection Algorithms p. 17 Finding Multimodal Solutions Using Restricted Tournament Selection p. 24 Analysis of Genetic Algorithms Evolution under Pure Selection p. 32 A new class of the crossover operators for the numerical optimization p. 42 On Multi-Dimensional Encoding/Crossover p. 49 On the Adaptation of Arbitrary Normal Mutation Distributions in Evolution Strategies: The Generating Set Adaptation p. 57
Computer Aided Investigation: Visualization and Analysis of data from Mobile communication devices using Formal Concept Analysis

In this world of terrorism, it is very important to know the network of individual suspects. It is also important to analyze the attributes of members of a network and the relationships that exist between them either directly or indirectly. This will make it easy for concepts to be built in aiding criminal investigations. However traditional approaches cannot be used to visualize and analyze data collected on individuals. With this current day where information systems play critical role in everyday life of every individual, it is easier to depend on digital information in fighting crime.Effective computer tools and intelligent systems that are automated to analyze and interpret criminal data in real time effectively and efficiently are needed in fighting crime. These current computer systems should have the capability of providing intelligence from raw data and creating a visual graph which will make it easy for new concepts to be built and generated from crime data in order to solve understand and analyze crime patterns easily. This paper proposes a new method of computer aided investigation by visualizing and analyzing data of mobile communication devices using Formal Concept Analysis, or Galois Lattices, a data analysis technique grounded on Lattice Theory and Propositional Calculus. This method considered the set of common and distinct attributes of data in such a way that categorizations are done based on related data with respect to time and events. This will help in building a more defined and conceptual systems for analysis of crime data that can easily be visualized and intelligently analyzed by computer systems.
Early Oligocene partial melting via biotite dehydration melting and prolonged low-pressure–low-temperature metamorphism of the upper High Himalaya Crystalline Sequence in the far east of Nepal

Abstract Early Oligocene partial melting and prolonged low-pressure–low-temperature (low-P/T) metamorphism were investigated in migmatites and orthogneisses from the upper High Himalaya Crystalline Sequence (HHCS) in the far east of Nepal. The migmatites were formed by biotite dehydration melting at c. 800°C from 33 to 25 Ma. Cordierite was only produced at shallow crustal levels at pressures <6 kbar. After Early Oligocene partial melting, the low-P/T metamorphism continued until 17 Ma during exhumation of the cordierite-bearing migmatites. Early Oligocene biotite dehydration melting in the upper HHCS occurred at different times and locations from the Early Miocene muscovite dehydration melting in the underlying HHCS and the metamorphic discontinuity was accompanied by thrusting of the High Himalayan Discontinuity at c. 27–19 Ma. Pervasive partial melting and prolonged low-P/T metamorphism in the upper HHCS is more compatible with a lateral southwards channel flow of the upper HHCS along the High Himalayan Discontinuity, whereas current channel flow models explaining the exhumation of the HHCS as driven only by the coupled activity of the Main Central Thrust and South Tibetan Detachment have faced difficulties in explaining the timing of the low-P/T metamorphism observed in the upper HHCS. Supplementary material: The representative cordierite compositions from the cordierite migmatites, the far east of Nepal are available at https://doi.org/10.6084/m9.figshare. c.4068815
A Knowledge Level Approach to Collaborative Problem Solving

This paper proposes, characterizes and outlines the benefits of a new computer level specifically for multi-agent problem solvers. This level is called the cooperation knowledge level and involves describing and developing richer and more explicit models of common social phenomena. We then focus on one particular form of social interaction in which groups of agents decide they wish to work together, in a collaborative manner, to tackle a common problem. A domain independent model (called joint responsibility) is developed to describe how participants should behave during such problem solving. Particular emphasis is placed on the problem of ensuring coherent behaviour in the face of unpredictable and dynamic environments. The utility of this model is highlighted in the real-world environment of electricity transportation management. In this domain, agents have to make decisions using partial, imprecise views of the system and the inherent dynamics of the problem mean that team members have to continually evaluate the ongoing problem solving process. Joint responsibility provides the evaluation criteria and the causal link to behaviour upon which individual and social situation assessment is based.
Resuscitating students’ attitude toward mathematics via computer-based software package instruction

The poor attitude of students towards mathematics in Nigeria has constituted a threat to national development, considering the important of mathematics in all facet of life. This study determines the effect of computer-based software on student’s attitude towards mathematics-graph, using three groups taught with computer-based software, graphic organizers and conventional strategy (discussion method). Gender and computer self-efficacy were used as moderating variables to determine the existence gender disparity in attitude towards mathematics when computer-based software was used and to establish the effect of computer self-efficacy on students’ attitude towards mathematics when taught with computer-based software. The result shows that computer-based software was more effective in enhancing attitude towards graphs than graphic organizer and conventional strategy. There was also significant interaction effect of treatment and computer self-efficacy; treatment and gender; treatment, computer self-efficacy and gender on attitude towards graphs. computer-based software was found to significantly improve students’ attitude towards graphs than the conventional strategy. Therefore, computer-based software for use in teaching Mathematics in secondary schools in Nigeria. To this effect mathematics teachers should be trained on the design, development and use of computer assisted instruction package in teaching.
Non-heart-beating versus cadaveric and living-donor livers: differences in inflammatory markers before transplantation

Background. Liver transplantation from non–heart-beating donors (NHBD) has been reintroduced into clinical practice to increase the donor pool; however, little is known about the immune status of NHBD livers. The aim of this study was to assess intragraft cell populations and inflammatory markers in NHBD and to compare the findings with cadaveric and living-related donor (LRD) livers. Methods. Biopsy specimens were obtained from controlled NHBD (n=9), conventional cadaveric (n=22), and living-donor (n=10) livers at the end of cold storage. Cryostat sections were stained for monocytes-macrophages, T lymphocytes, and intercellular adhesion molecule (ICAM)-1. Results. The levels of leukocyte infiltration in NHBD reflected those found in conventional cadaver donors and were significantly higher than in LRD livers. Similar levels of CD68+ monocytes-macrophages were detected in cadaver (4.0±1.2%) and NHBD livers (4.6±1.2%) and were significantly greater than in the LRD livers (2.6±0.5%, P <0.01). Furthermore, the levels of T lymphocytes in NHBD (1.1±0.6%) and cadaver donors (1.5±0.8%) were similar, and were higher than in LRD (vs. 0.47±0.3%, P <0.05). Twelve of 22 (60%) cadaver livers had high levels of ICAM-1 expression (grade 3), compared with only 1 of 10 (10%) LRD livers (P =0.02). Four of nine (44%) controlled NHBD livers expressed high levels of ICAM-1. Conclusions. The results demonstrate that livers obtained from controlled NHBD before transplantation are similar to conventional cadaver donors regarding the level of leukocyte infiltration. Nevertheless, lower levels of ICAM-1 were detected in NHBD, suggesting less exposure to inflammatory mediators than conventional cadaver donor livers.
Model Predictive Torque Control for Enhanced SRM With Improving Drive Hardware Performance

Switched Reluctance Motor (SRM) is the choice of next-generation electric vehicle (EVs) traction motor applications, due to their simple rotor structure, power and torque characteristics. However, this SRM drive suffers from high torque ripples, which may cause severe vibration and acoustics. Therefore, torque ripple is effectively reduced by control techniques. This paper proposes an enhanced model predictive torque control (MPTC) that minimizes torque ripple and improves system efficiency. The active voltage vector (VVs) selection is obtained by removing flux linkage, eight sectors in the SRM electric cycle, and minimum VVs at each control period. As a result, a single cost function designed with the weighting factor reduces torque ripple by selecting optimal VVs. The enhanced SRM dynamic motor model and proposed MPTC control are verified through simulation studies and experiments based on a four-phase 8/6 pole SRM drive system.
Mining global frequent subtrees

Discovering global frequent subtrees from ordered labeled trees in distribute environment is an attractive research problem in data mining. In this paper, a new algorithm FAMDFS(Fast Algorithm for Mining Global Frequent Subtree) was proposed. This algorithm transfer local projected branch frequent nodes, can decrease network traffic, improve the efficiency of the algorithm. Theoretical analysis and experimental results show that FAMDFS algorithm is efficient and effective.
A probabilistic approach to high-confidence cleaning guarantees for low-cost cleaning robots

Cleaning is widely regarded as one of the most relevant applications of autonomous service robots. The goal of robotic cleaning is to achieve low dirt levels in the whole environment. Low cost consumer robots, however, are typically prone to high motion and sensor uncertainties. Additionally, their cleaning units do not always remove the dirt entirely. As a result, there is a substantial probability that some parts of the environment are not cleaned sufficiently. In this paper, we propose an approach to robotic cleaning that guarantees that in the whole environment, the dirt levels after cleaning are reduced below a user-defined threshold with high confidence. We introduce a novel probabilistic model for jointly estimating the trajectory of the robot and the current dirt distribution in the environment. Based on this estimate, we adapt the future cleaning path during operation such that the robot re-visits areas in which high dirt levels are still likely. We demonstrate the effectiveness of our approach in extensive experiments carried out both in simulation and with a real vacuum cleaning robot, also in comparison to previous approaches.
The Impaired Sustained Attention in Children with ADHD: Relevant Factors and Clinical Implications

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition that profoundly disrupts a child's capacity to maintain focus, impacting various aspects of their daily existence. This article delves into the intricate realm of compromised sustained attention in children diagnosed with ADHD, offering an exhaustive examination of the contributing factors and their clinical implications. Employing extensive research, this research delves into the multifaceted facets of attention deficits associated with ADHD, encompassing distinct attentional components, susceptibility to distractions, attention patterns, processing speed, autonomic regulation, and developmental considerations. By unraveling these discoveries, the exploration acquires valuable insights into the hurdles confronted by children grappling with ADHD when it comes to sustaining attention. Furthermore, emphasizing the significance of tailored interventions aimed at addressing specific attention-related elements. By shedding light on the complexity of impaired sustained attention in ADHD, this article advances researchers’ comprehension of this condition and lays the groundwork for more efficacious diagnostic and therapeutic approaches. This review can help improve the lives of children affected by ADHD by fostering a more nuanced understanding of the challenges they face in their daily lives.
Parameterized Inapproximability of Target Set Selection and Generalizations

In this paper, we consider the Target Set Selection problem: given a graph and a threshold value Open image in new window for each vertex v of the graph, find a minimum size vertex-subset to “activate” s.t. all the vertices of the graph are activated at the end of the propagation process. A vertex v is activated during the propagation process if at least Open image in new window of its neighbors are activated. This problem models several practical issues like faults in distributed networks or word-to-mouth recommendations in social networks. We show that for any functions f and ρ this problem cannot be approximated within a factor of ρ(k) in f(k) ·n O(1) time, unless FPT = W[P], even for restricted thresholds (namely constant and majority thresholds). We also study the cardinality constraint maximization and minimization versions of the problem for which we prove similar hardness results.
Image Denoising Via Learned Dictionaries and Sparse representation

We address the image denoising problem, where zeromean white and homogeneous Gaussian additive noise should be removed from a given image. The approach taken is based on sparse and redundant representations over a trained dictionary. The proposed algorithm denoises the image, while simultaneously trainining a dictionary on its (corrupted) content using the K-SVD algorithm. As the dictionary training algorithm is limited in handling small image patches, we extend its deployment to arbitrary image sizes by defining a global image prior that forces sparsity over patches in every location in the image. We show how such Bayesian treatment leads to a simple and effective denoising algorithm, with state-of-the-art performance, equivalent and sometimes surpassing recently published leading alternative denoising methods.
Pursue Shortest Mobility Model with Delay and Retransmission Attempts in MANET

-Mobile ad-hoc Network is consisting a network i.e. without any physically connection in which mobile nodes moving around the network area. These mobile nodes communicate with each other without any established or fixed infrastructure. Several routing protocols have been proposed by the researcher in MANET. Mobility models is an crucial part in testing the performance of various routing protocols in MANET. Here in this paper we have proposed a new mobility model i.e. pursue shortest mobility model and here evaluate the performance of various routing protocols(AODV,DSR,GRP) with respect to various Existing and new designed mobility model and performance matrices used i.e. Delay and retransmission attempts. Simulationhave been carried out with OPNET. Simulation results with different mobility models, routing protocols and their comparison gives the network performance Keyword:-Routing protocols, Mobility, Ad-hoc Network, Mobile nodes.
Algorithms for Matching and Predicting Trajectories

We consider the following two problems: Map Matching: Given a sequence of (imprecise) location measurements from a mobile user moving on a road network, determine the most likely path in the network this user has travelled along. Prediction of Trajectories: Given the path of where a mobile user has moved along in a road network up to now, predict where he will travel along in the near future. Our map matching algorithm is simple and efficient even in case of very imprecise measurements like GSM-localizations and allows for the real-time tracking of a large number of mobile users on modest hardware. Our proposed path prediction algorithm is equally simple but yields extremely accurate predictions at a very low computational cost.
PSO based UAV Localization for Interference Coordination in Cellular Network

Due to wide spread usage of smart phones, there is a rapid increase in the demand for high data rate services from users in a cellular network. With users undergoing multipath fading and shadowing, and base stations facing transmit power constraints, several users may face outage. In this paper, we deploy an unmanned aerial vehicle (UAV) as a decode-and-forward (DF) relay in a cellular system, which helps base stations (BSs) in providing desired rates to the users. Due to the channel reuse policy in a cellular network, the UAV while forwarding the information to a user, may interfere with other users of the same channel, leading to inter-cell interference (ICI). Considering the number of user equipments (UEs) in outage (UEiO) as the objective, we propose a particle swarm optimization (PSO) based solution to find the best location of the UAV which minimizes UEiO and keeps a check on ICI. For comparison, we evaluate the UEiO when the location of UAV is fixed and not optimized. Our simulation results demonstrate promising decrease in UEiO.