Miracle-dz/UniFAR-FTUs huggingface dataset:
Cerebellar and basal ganglia motor network predicts trait depression and hyperactivity

In the human brain, the cerebellum (CB) and basal ganglia (BG) are implicated in cognition-, emotion-, and motor-related cortical processes and are highly interconnected, both to cortical regions via separate, trans-thalamic pathways and to each other via subcortical disynaptic pathways. We previously demonstrated a distinction between cognitive and motor CB-BG networks (CCBN, MCBN, respectively) as it relates to cortical network integration in healthy young adults, suggesting the subcortical networks separately support cortical networks. The CB and BG are also implicated in the pathophysiology of schizophrenia, Parkinson's, and compulsive behavior; thus, integration within subcortical CB-BG networks may be related to transdiagnostic symptomology. Here, we asked whether CCBN or MCBN integration predicted Achenbach Self-Report scores for anxiety, depression, intrusive thoughts, hyperactivity and inactivity, and cognitive performance in a community sample of young adults. We computed global efficiency for each CB-BG network and 7 canonical resting-state networks for all right-handed participants in the Human Connectome Project 1200 release with a complete set of preprocessed resting-state functional MRI data (N = 783). We used multivariate regression to control for substance abuse and age, and permutation testing with exchangeability blocks to control for family relationships. MCBN integration negatively predicted depression and hyperactivity, and positively predicted cortical network integration. CCBN integration predicted cortical network integration (except for the emotional network) and marginally predicted a positive relationship with hyperactivity, indicating a potential dichotomy between cognitive and motor CB-BG networks and hyperactivity. These results highlight the importance of CB-BG interactions as they relate to motivation and symptoms of depression.
SEMANTIC ADAPTATION APPROACH FOR ADAPTIVE WEB-BASED SYSTEMS

The principles of the WWW used today rely solely on links and on content presented through simple HTML tags. The drawback of the above mentioned modus operandi is that it is purely syntactic with no clear emphasis on meaning about data. The Semantic Web approach tries to bridge that gap by providing additional information, mainly conceptual to the data at hand. In this paper we are focusing on extension of the adaptation methods with semantic adaptation dedicated to Adaptive Web-Based Systems. The approach is consisted of five steps based on querying RDF resources through SPARQL every time the user is visiting a particular resource. It is worth mentioning that the retrieved resources represent similar resources relevant to the currently visited resource which guides the user towards the desired information while browsing.
Maintaining Both Local and Global Coherence

In 2 experiments we investigated whether readers experience comprehension difficulty when they read texts in which local coherence is maintained but global incoherence is introduced. Ss read passages containing an elaborate description of a main character presented early in the text that was inconsistent with actions carried out by the main character later in the text. In Experiment 1, reading times for critical sentences were significantly longer when the earlier description and the critical sentences were inconsistent. In Experiment 2, resolution of global inconsistencies improved memory for the regions of the text that involved the inconsistencies. The results are discussed within a mental model approach to comprehension in which readers attempt to maintain both local and global coherence.
New seismic modelling facilities in Matlab

The seismic modelling capabilities available in the CREWES Matlab toolbox have been substantially upgraded. These capabilities expand an already strong interactive facility to bring a large variety of useful tools to the explorationist or researcher. The v(z) raytracing facility has a fast ray-shooting algorithm that allows an efficient, iterative solution to the two-point raytracing problem. Specialty routines are available to trace P-P and P-S primary reflections for any acquisition geometry (including source gathers, receiver gathers, VSPs, and OBC). Traveltimes and ray parameters are determined but not amplitudes. A general-purpose interface is available to trace arbitrary multi-modes that have any number of mode conversions and up or down legs. A v(x,z) raytracing capability has been developed that solves the ray tracing differential equation on a 2D grid. This method uses a 4 th order Runge-Kutta solver to create a very general ray-shooting algorithm. Normal incidence raytrace migration and modelling capabilities have been developed using this raytracer. The acoustic finite-difference facility has been improved and many bugs were fixed. Based on the 2D variable-velocity scalar-wave equation, this modelling facility uses time-stepping to advance a wavefield. Both 2 nd and 4 th order Laplacians are available and Clayton-Engquist absorbing boundaries have been implemented. Any 2D source or receiver geometry can be simulated including such effects as arrays, VSPs, and topography. An exploding reflector option also has been created to allow simple modelling of stacked sections. An interactive picking facility has been built into the basic seismic viewer. This facility allows interactive normal-incidence raytrace modelling and migration to be done interactively. Picks can be made on depth or time sections and the corresponding raypaths are drawn in depth.
XIII—Metaphor: Ad Hoc Concepts, Literal Meaning and Mental Images

I propose that an account of metaphor understanding which covers the full range of cases has to allow for two routes or modes of processing. One is a process of rapid, local, on-line concept construction that applies quite generally to the recovery of word meaning in utterance comprehension. The other requires a greater focus on the literal meaning of sentences or texts, which is metarepresented as a whole and subjected to more global, reflective pragmatic inference. The questions whether metaphors convey a propositional content and what role imagistic representation plays receive somewhat different answers depending on the processing route.
Towards using DBpedia for building user identities

Internet offers a number of various services that to maximise the user experience apply different personalisation techniques. An important resource of every personalisation method is a user profile. The more information on the user is available in such profile, the better. Therefore, together with maturing of these mechanisms, the notion of identity emerged. The identity exceeds the user profile with information that is more detailed or enables benefiting from additional functionalities. The information stored within an identity needs to be understandable for different services to be easily reused. This can be achieved using the DBpedia. The goal of the article is to describe the design of a method that potentially enables providing data to build the user identity, based on his behaviour on the Web. The method is elaborated as well as an example of application is presented.
A Survey of Decision Fusion and Feature Fusion Strategies for Pattern Classification

Abstract For any pattern classification task, an increase in data size, number of classes, dimension of the feature space, and interclass separability affect the performance of any classifier. A single classifier is generally unable to handle the wide variability and scalability of the data in any problem domain. Most modern techniques of pattern classification use a combination of classifiers and fuse the decisions provided by the same, often using only a selected set of appropriate features for the task. The problem of selection of a useful set of features and discarding the ones which do not provide class separability are addressed in feature selection and fusion tasks. This paper presents a review of the different techniques and algorithms used in decision fusion and feature fusion strategies, for the task of pattern classification. A survey of the prominent techniques used for decision fusion, feature selection, and fusion techniques has been discussed separately. The different techniques used for fusion have been categorized based on the applicability and methodology adopted for classification. A novel framework has been proposed by us, combining both the concepts of decision fusion and feature fusion to increase the performance of classification. Experiments have been done on three benchmark datasets to prove the robustness of combining feature fusion and decision fusion techniques.
The Implementation of a Hierarchical Hybrid Navigation System for a Mobile Robotic Vehicle

One of the challenges of robotics is to develop a robot control system capable of obtaining intelligent, suitable responses to dynamic environments. The basic requirements for accomplishing this is a robot control architecture and a hardware platform that can adapt the software and hardware to the current state of the environment. This has led researchers to design control architectures composed of distributed, independent and asynchronous behaviours. In line with this research, this thesis details the development of a control system which adopts a hierarchical hybrid navigation architecture designed at Victoria University of Wellington. The implementation of the control system is aimed towards one of Victoria University of Wellington’s fleet of mobile robotic platforms called MARVIN. MARVIN is a differential drive robot and the sensory equipment on the device includes infrared sensors and odometry. The control system has been implemented in C# . NET programming language adopting a Service- Oriented Architecture. This software framework provides several services along with a graphical user interface to configure the control system. Several experiments have been carried out to test the control system and the results indicate that the features of the navigation architecture have been accomplished
Student perceptions of various hint features while solving coding exercises

Drill and practice systems provide students with an informal learning environment to learn programming languages. In a traditional classroom setting, while feedback is personalized for each individual, it is a time consuming process. These online environments possess the ability to provide instantaneous feedback and can be accessed from any location. However, while these are conveniences, there is still an issue with the quantity and quality of feedback that is provided to each user by the system, and whether it is helpful towards helping them solve the exercise with a large understanding of the concept being tested. In this thesis we investigate how students perceive additional feedback would help them in completing coding exercises in CodeWorkout. We conducted these investigations through user studies, across two focus groups, with Computer Science students from various years. The study was conducted over one semester with a total of seventeen participants. A discussion based frequently asked questions (FAQ) tool, the ability to request a hint during submissions and the option to provide a hint to other users, to encourage active learning, were all options presented to participants during these focus groups. The information gathered though these group discussions formed the basis of our conclusion and implications. The overall feedback on all three tools was both positive and constructive. The idea of having a less traditional FAQ tool, complete anonymity in responses, as well as the ability to vote on hints provided were strong emergent themes through the study. The majority of Participants felt that they would utilize all these tools in some fashion, were they provided, and would find them helpful in completing a coding exercise if they were stuck. Lastly, we conclude with suggestions for potential design and feature options for the system.
Block-based Atomicity in Message-passing Distributed Programs

In this paper, we have studied the notion of atomicity in message-passing distributed programs. The difference between the notion of atomicity in shared memory programs and messagepassing programs has been discussed in detail. Due to the nature of communication in messagepassing programs, the atomicity requirement in shared memory programs (serializability) does not guarantee the same level of atomicity in message-passing programs. We have referred to the atomicity level guaranteed by the serializability requirement in message-passing programs as the weak atomicity. We have defined the requirements that guarantee a level of atomicity in message-passing programs similar to that in shared memory programs. We have referred to it as the strong atomicity requirement. Both of weak and strong atomicity have been formally defined. The notion of atomicity can be employed to significantly reduce the state space to be considered in verification. Moreover, atomicity violations in a run typically indicate the presence of program bugs. Consequently, the concepts presented in this paper can be exploited to reduce the cost of the verification of message-passing distributed programs.
Measurement of resting energy expenditure in healthy children.

BACKGROUND The role that the components of energy expenditure play in the etiology of childhood obesity has highlighted the need for greater accuracy and standardized protocols for the measurement of resting energy expenditure (REE). However, protocols used to assess REE in children are varied, and consensus on a suitable method for measuring REE in children has not been reached. This study was undertaken to determine the effect of measurement time and measurement device (mask or mouthpiece) on REE in healthy children. DESIGN Following a 12-hour fast and abstinence from exercise, 23 children (age, 7-12 years) completed two 35-minute protocols: one with a face mask and the other with a mouthpiece/noseclip. Energy expenditure was measured continuously via indirect calorimetry, while device acceptability was assessed using a 6-point comfort rating scale. RESULTS Repeated measures ANOVA indicated that there was no significant difference in REE when measured after 10, 15, 20, or 25 minutes of rest compared to 30 minutes for either the mask or mouthpiece/noseclip (REE range, 1371-1460 kcal/d). Examination of the percentage coefficient of varia tion (CV) in energy expenditure for each time period by device showed that the least variation existed after 20 minutes of measurement using the mask (CV 6%). Paired t test analysis indicated significantly less discomfort when wearing the mask compared to the mouthpiece/noseclip. CONCLUSION It would appear that a 20-minute protocol using a mask may increase compliance and prove to be a more practical protocol for measuring REE in children.
LINGUISTIC AND PROGRAM TOOLS FOR DEBUGGING AND TESTING OF SIMULATION MODELS OF COMPUTER NETWORKS

This paper focuses on the problem of validation and verification of computer network simulation models. Authors propose to use special linguistic and program tools of CAD system TriadNS in this case. First of all it should be noted that TRiadNS is a computer system which was developed for computer network design. Simulation is the main method for investigation of designed computer networks. But it is very important to have a credible simulation result. It is necessary for target users to have sufficient confidence that results generated by a simulation run reflect real world operation to a large degree. Authors observe the specifications of the simulation model in TriadNS.Net, consider the program tools for simulation model analysis (information procedures and conditions of simulation) and propose to use them for simulation model validation and verification, debugging and testing. Besides, the authors suggest program tools including the intellectual agents and ontology for localization of mistakes determined during verification and validation processes. Moreover the authors show how the specific features of hierarchical simulation models in TRIADNS make the process of testing and debugging of simulation models flexible.
DYNAMIC VOLTAGE RESTORER WITH REPETITIVE CONTROLLER FOR POWER QUALITY IMPROVEMENT

The Dynamic Voltage Restorer (DVR) has become popular as a cost effective solution for the protection of sensitive loads from voltage sag. By providing proper control scheme the DVR can also be utilized for eliminating other power quality problem such as voltage unbalance and voltage as well as current harmonics This paper presents control system based on repetitive controller to compensate voltage sag, voltage unbalance and voltage harmonics and current harmonics The well –developed graphical facilities available in PSCAD/EMTDC are used to carry out all modeling aspects of repetitive controller. KeywordsDynamic Voltage Restorer (DVR), Power Quality, repetitive control, voltage sag, harmonic distortion.
Paper and Pen Interaction with Structured Speech

This paper addresses the problem that a listener experiences when attempting to capture information presented during a lecture, meeting, or interview. Listeners must divide their attention between the talker and their notetaking activity. We propose a new device—the Audio Notebook—for taking notes and interacting with a speech recording. The Audio Notebook is a combination of a digital audio recorder and paper notebook, all in one device. Audio recordings are structured using two techniques: user structuring based on notetaking activity, and acoustic structuring based on a talker’s changes in pitch, pausing, and energy. A field study showed that the interaction techniques enabled a range of usage styles, from detailed review to high speed skimming. The study motivated the addition of phrase detection and topic suggestions to improve access to the audio recordings. Through these audio interaction techniques, the Audio Notebook defines a new approach for navigation in the audio domain.
Why Are Computational Neuroscience and Systems Biology So Separate?

Despite similar computational approaches, there is surprisingly little interaction between the computational neuroscience and the systems biology research communities. In this review I reconstruct the history of the two disciplines and show that this may explain why they grew up apart. The separation is a pity, as both fields can learn quite a bit from each other. Several examples are given, covering sociological, software technical, and methodological aspects. Systems biology is a better organized community which is very effective at sharing resources, while computational neuroscience has more experience in multiscale modeling and the analysis of information processing by biological systems. Finally, I speculate about how the relationship between the two fields may evolve in the near future.
A Study of Learning Effects on E-Learning with Interactive Thematic Video

This study implemented and examined the effects of a self-paced learning environment-interactive thematic video (ITV) designed to enhance learner's achievement and motivation on e-learning. We integrated the thematic instructional strategy into interactive video-based instruction and investigated the participant's reflection and learning performance through post-test, IMMS and the experimental teaching activities. Participants were divided into experimental group and control group. The comparison of learning achievement and motivation between two groups were also presented. The findings suggested that the proposed ITV could offer a better learning performance on e-learning environment.
CRISPRTarget

The bacterial and archaeal CRISPR/Cas adaptive immune system targets specific protospacer nucleotide sequences in invading organisms. This requires base pairing between processed CRISPR RNA and the target protospacer. For type I and II CRISPR/Cas systems, protospacer adjacent motifs (PAM) are essential for target recognition, and for type III, mismatches in the flanking sequences are important in the antiviral response. In this study, we examine the properties of each class of CRISPR. We use this information to provide a tool (CRISPRTarget) that predicts the most likely targets of CRISPR RNAs (http://bioanalysis.otago.ac.nz/CRISPRTarget). This can be used to discover targets in newly sequenced genomic or metagenomic data. To test its utility, we discover features and targets of well-characterized Streptococcus thermophilus and Sulfolobus solfataricus type II and III CRISPR/Cas systems. Finally, in Pectobacterium species, we identify new CRISPR targets and propose a model of temperate phage exposure and subsequent inhibition by the type I CRISPR/Cas systems.
Establishing object-state representation in language comprehension : evidence from picture verification, eye-tracking and ERPs

In a set of behavioral, eye tracking, and ERP experiments, this thesis explored when and how object-state representation is established, maintained, and retrieved in language comprehension. We firstly examined whether different object-state representations could be established under two contrasting linguistic contexts (e.g., no change – “choose the ice cream” vs. change – “drop the ice cream”). Our findings showed that when linguistic context was provided, the representation that matched the consequences of described events was verified faster than the one that mismatched the expected outcome. Then, we studied the time course of establishing object-state representations with the visual world paradigm. Our results suggested that: a) the difference in looks towards the depicted versions of the situationally appropriate target object (an intact vs. a dropped ice cream) often manifested at the reference to the object but not prior to it; b) eye movements were primarily driven by semantic overlap between the visual display and the described object-state representation. Moreover, we found ERP evidence that was consistent with the need to keep track of, and retrieve object-state representations from episodic memory. We conclude that object-state representations were activated and retrieved during language processing. The work reported in this thesis highlights the need to take account of dynamics of event representation to capture the interplay between general semantic knowledge about objects and the episodic knowledge introduced by the sentential context in language comprehension.
Search Results Improvement Through Ranking Approach

Recommender systems provide plenty of benefits to both users and the businesses. Due to Web related applications, user-generated information is more freestyle and less ordered, which increases the difficulties in mining helpful information from these data sources. Innumerable dissimilar types of recommendations are ready on the Web daily, with movies, music, images, books recommendations, query suggestions, and tags recommendations, etc. It is not concerned about types of data sources old for the recommendations, basically these data sources can be constructed in the type of dissimilar types of graphs. Then it illustrates to generalize different recommendation problems into graph diffusion framework. The existing system does not focus on improving search results. In order to suit the information needs of Web users and recover the user practice in many web applications, Recommender Systems. The proposed framework can be using in many recommendation errands on the World Wide Web (WWW). The search results are improved by heat diffusion based ranking. By using this process we can satisfy the user needs in web application. ABSTRACT