Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing the ability of cognitive and affective Theory of Mind in adolescent onset schizophrenia

Background Evidence in the literature suggests that there is an impairment of social cognition in schizophrenia. Theory of Mind (ToM) is defined as one’s ability to understand others’ wishes, beliefs, intentions, and other psychological states and thereby to judge others’ behavior, as an essential component of social cognition. However, there have been limited studies on social cognition, especially ToM in adolescent onset schizophrenia (AOS). The current study aims to investigate ToM abilities in adolescent schizophrenia according to various ToM subcomponents (cognitive ToM and affective ToM) and various ToM orders (first order and second order). Methods This study examines ToM in 35 adolescent schizophrenic patients and 35 healthy adolescents using the “Yoni task” and “Faux Pas Recognition test” to assess their affective and cognitive ToM abilities. Results In the Yoni task, patients with AOS showed differences in ToM abilities either on a different order or under different conditions. The Faux Pas Recognition task results revealed that AOS patients were not always able to recognize a faux pas or understand complicated emotions under the faux pas scenario. Furthermore, as indicated by the correlation analysis, neither cognitive ToM nor affective ToM was related to the patients’ symptoms, disease duration, dose of medication, or intelligence quotient (IQ). Conclusion Our findings showed AOS impairment in the performance of ToM tasks. It seemed that impairment in second-order-ToM is more serious. Moreover, these deficits are largely independent of symptom clusters, disease duration, dose of medication, and IQ. It can be speculated that ToM dysfunction may be a hallmark of adolescent schizophrenia.
Foetus Ultrasound Medical Image Segmentation via Variational Level Set Algorithm

There is a challenge to segment the medical image which is often blurred and consists of noise. The objects to be segmented are always changing shape. Thus, there is a need to apply a method to automated segment well the objects for future analysis without any assumptions about the object's topology are made. In general, when performing pregnancy ultrasound scanning, obstetrician needs to find out the best position or angle of the foetus and freeze the scene. The obstetrician will click on the crown and the rump of the foetus to get the foetus length. The segmentation technique applied is level set method. A variational level set algorithm has been successfully implemented in medical image segmentation (Xray image, MRI image and ultrasound image). The results showed the level set contour evolved well on the low contrast and noise consisting medical image, especially the ultrasound image.
An automatic method for identifying TE-derived miRNAs

MicroRNAs and transposable elements (TEs) share numerous characteristics: size, stable secondary structure, maturation into shorter sequence and regulation of binding target genes. TE-derived miRNAs are microRNAs that are generated from transposable elements. TE-derived miRNAs and TEs have a similar distribution of their occurrences that is distinct from ’classical’ miRNAs: a TE-derived miRNA have many occurrences spread in many chromosomes, and a ’classical’ miRNA has generally one occurrence of few ones appearing in a cluster. We developed an automatic method called miRNAcheck to distinguish a TE-derived miRNA from a ’classical’ miRNA. Given a miRNA candidate, miRNAcheck calculates in a first step the number of occurrences of the candidate in the genome. The ten occurrences the most similar to the candidate sequence are then extended and a consensus sequence is created. Finally, the consensus sequence is compared to TE sequences in RepBase, a database of TEs. From the 1048 human miRNAs of miRBase, we selected the miRNAs that have at least 5 similar occurrences in the genome. We get only 67 candidates. Among them, 59 are identified by miRNAcheck as TE-derived miRNAs. miRNAcheck is available at the Web site: http://EvryRNA.ibisc. univ-evry.fr/
An Ethnographic Study of Is Investment Appraisal

Both academics and practitioners have invested considerably in the information systems evaluation arena, yet rewards remain elusive. The aim of this article is to provide rich insights into some particular political and social aspects of evaluation processes. An ethnographic study of a large international financial institution is used to compare the experience of observed practice with the rhetoric of company policy, and also to contrast these observations with the process of IS evaluation as portrayed within the literature. Our study shows that despite increasing acknowledgement within the IS evaluation literature of the limitations and flaws of the positivist approach, typified by quantitative, â€˜objectiveâ€™ assessments, this shift in focus towards understanding social and organisational issues has had little impact on organisational practice. In addition, our observations within the research site reveal that the veneer of rationality offered by formalised evaluation processes merely obscures issues of power and politics that are enmeshed within these processes.
Topological Structure Matching Measure between Two Graphs

There have been a plethora of algorithms and techniques for the one‐to‐one correspondence matching between two small graphs at the element level. However, it is a daunting task for large graphs. It is necessary to design an aggregate statistical measurement to measure the degree of matching at the coarse grained level between two large graphs. This work presents a novel contribution with the proposal of an aggregate statistical measurement of the matching between two large networks at the macro topological structure level. In the viewpoint of strategic planning application, decision makers want to know whether the road infrastructure network meets the traffic flow network at the macro level rather than the micro level. The macro topological structure of the graph is described by a partition of all the vertices by the singular value decomposition based on the weighted vertex‐path incidence matrix. The topological structure matching measurement (TSMM) of the two graphs is defined as the degree of similarity between two partitions. As a case study, the TSMM is considered between the road network and the traffic flow network for Shanghai. The result is 0.2129, which shows that the two networks mismatch to a certain degree. This, agreeing with the current situation of the traffic congestion in Shanghai, suggests the improvement in the urban traffic.
Parallel simulation of beam-beam interaction in high energy accelerators

In this paper, we present a self-consistent simulation model of beam-beam interaction in high energy accelerators. Using a parallel particle-in-cell approach, we have calculated the electromagnetic fields between two colliding beams. Dynamic load balance is implemented to improve the parallel efficiency. A preliminary performance test on IBM SP Power3, Cray T3E and PC cluster is presented. As an application, we studied the coherent beam-beam oscillation in the proposed Large Hadron Collider.
Maslov asymptotic extension of generalized Radon transform inversion in anisotropic elastic media: a least-squares approach

Linearized asymptotic inversion of seismic data is carried out in general anisotropic media. In an anisotropic medium, even if it is homogeneous, the shear waves form (instantaneous) caustics. In the absence of caustics, we formulated the seismic inverse scattering problem via the generalized Radon transform. In the presence of caustics, which are associated with multi-pathing, we have to re-derive the inversion procedure which is now based on the weak formulation of the inverse problem. The key ingredients are the Maslov canonical operators describing the transmission from the image point to the sources and the receivers, and delicate high-dimensional stationary phase analyses. The importance of caustics in practical applications becomes apparent in the analysis of mode converted wave constituents in sedimentary basins.
Cooperative simultaneous localization and synchronization: A distributed hybrid message passing algorithm

Localization and synchronization in wireless networks are strongly related when they are based on internode time measurements. We leverage this relation by presenting a message passing algorithm for cooperative simultaneous localization and synchronization (CoSLAS). The proposed algorithm jointly estimates the locations and clock parameters of the network nodes in a fully decentralized manner while requiring time measurements and communications only between neighboring nodes and making only minimal assumptions about the network topology. Low computation and communication requirements are achieved by a hybrid use of sample-based and Gaussian belief propagation. Our simulations demonstrate performance advantages of the proposed CoSLAS algorithm over separate state-of-the-art localization and synchronization algorithms.
ARTEMIS: Real-Time Detection and Automatic Mitigation for BGP Prefix Hijacking

Prefix hijacking is a common phenomenon in the Internet that often causes routing problems and economic losses. In this demo, we propose ARTEMIS, a tool that enables network administrators to detect and mitigate prefix hijacking incidents, against their own prefixes. ARTEMIS is based on the real-time monitoring of BGP data in the Internet, and software-defined networking (SDN) principles, and can completely mitigate a prefix hijacking within a few minutes (e.g., 5-6mins in our experiments) after it has been~launched.
Improving the performance of out-of-order sigma-point Kalman filters for joint localization by multiple UAVs

In search and surveillance operations, a team of small Unmanned Aerial Vehicles (UAVs) can provide a robust solution that outperforms what can be achieved by a single aircraft with comparatively superior mobility and sensors. Three key challenges can be identified in this field: (1) optimizing the UAV trajectories to place them at desired locations at desired times to capture target locations, (2) cooperative sensor scheduling, and (3) intelligent fusing of multiple sensor measurements to accurately estimate the position and velocity of a target. The focus of this paper is the sensor-fusion task, in particular with the goal of providing accurate localization of a ground target from coarse azimuth angle-of-arrival information captured by multiple cameras onboard flying platforms. One might consider addressing this problem using some form of Kalman filter. However, the estimation system is nonlinear and, in practical implementation, sensor readings can arrive out-ofsequence to the sensor fusion process. For example, there is non-deterministic latency in the inter- and intra-UAV communication channels. We have previously addressed both issues by developing an out-of-order sigma-point Kalman filter (O3SPKF) [1], and in this paper we seek to improve on its localization performance by coupling O3SPKF with the triangulation of the azimuth angles simultaneously registered by the cameras in multiple UAVs.
Lexical Disambiguation Using Constraint Handling In Prolog (CHIP)

Automatic sense disambiguation has been recognised by the research community as very important for a number of natural language processing applications like information retrieval, machine translation, or speech recognition. This paper describes experiments with an algorithm for lexieal sense disambiguation, that is, predicting which of many possible senses of a word is intended in a given sentence. The definitions of senses of a given word are those used in LDOCE, the Longman Dictionary of Contemporary English [Procter et al., 1978]. The algorithm first assigns a set of meanings or senses drawn from LDOCE to each word in the given sentence, and then chooses the combination of word-senses (one for each word in the sentence), yielding the maximum semantic overlap. The metric of semantic overlap is based on the fact that LDOCE sense definitions are made in terms of the Longman Defining Vocabulary, effectively a (large) set of semantic primitives. Since the problem of finding the word-sense-chain with maximum overlap can be viewed as a specialised example of the class of constraint-based optimisation problems for which Constraint Handling In Prolog (CHIP) was designed, we have chosen to implement our algorithm in CHIP.
Pharmacologic treatment of cancer pain.

Pain from cancer is a major health care problem.1–3 Thirty percent of patients with cancer have pain at the time of diagnosis, and 65 to 85 percent have pain when their disease is advanced.2,4–6 The impact of cancer pain is magnified by the interaction of pain and its treatments with other common cancer symptoms: fatigue, weakness, dyspnea, nausea, constipation, and impaired cognition.4,6 Cancer pain can be effectively treated in 85 to 95 percent of patients with an integrated program of systemic, pharmacologic, and anticancer therapy.7,8 Many of the remaining patients can be helped by the .
Reactive NUCA: near-optimal block placement and replication in distributed caches

Increases in on-chip communication delay and the large working sets of server and scientific workloads complicate the design of the on-chip last-level cache for multicore processors. The large working sets favor a shared cache design that maximizes the aggregate cache capacity and minimizes off-chip memory requests. At the same time, the growing on-chip communication delay favors core-private caches that replicate data to minimize delays on global wires. Recent hybrid proposals offer lower average latency than conventional designs, but they address the placement requirements of only a subset of the data accessed by the application, require complex lookup and coherence mechanisms that increase latency, or fail to scale to high core counts. In this work, we observe that the cache access patterns of a range of server and scientific workloads can be classified into distinct classes, where each class is amenable to different block placement policies. Based on this observation, we propose Reactive NUCA (R-NUCA), a distributed cache design which reacts to the class of each cache access and places blocks at the appropriate location in the cache. R-NUCA cooperates with the operating system to support intelligent placement, migration, and replication without the overhead of an explicit coherence mechanism for the on-chip last-level cache. In a range of server, scientific, and multiprogrammed workloads, R-NUCA matches the performance of the best cache design for each workload, improving performance by 14% on average over competing designs and by 32% at best, while achieving performance within 5% of an ideal cache design.
Diagnostic techniques for spoken keyword discovery

Keyword discovery is an unsupervised technology that can help to process collections of speech and capture repeated patterns. This technology becomes useful and provides solution for un-supervised content analysis tasks, especially when the acoustic and lexical characteristics are not known in advance or there is little or no data to model these characteristics via statistical models. In these situations, keyword discovery can ﬁnd potentially important words for further analysis using minimal resources. Unfortunately, keyword discovery performance heavily depends on the quality of the features used to characterize the raw signal and the alignment algorithm used to ﬁnd similar feature subsequences. It is not yet fully understood which features and alignment algorithms work well in different scenarios and for different tasks, and there are very few diagnostic techniques for improving our understanding. In this paper, we present two diagnostic measurements that can be used to directly assess the quality of alignments between sequences of features independently of the intended use of the alignments downstream. We argue that such diagnostic techniques are valuable for intrinsically assessing speech features and alignment algorithms for keyword detection.
Design of a high-linearity RF front-end with IP2 calibration for SAW-less WCDMA receivers

A fully integrated receiver RF front-end designed in 0. 13µm CMOS that meets the WCDMA system requirements is presented. The receiver RF front-end requires no interstage SAW filter. To handle the stringent linearity requirements in terms of both IP3 and IP2 set for the RF front-end, a current-mode passive mixer constructing a built-in high-Q bandpass filter is adopted to suppress blockers including the transmitter leakage, and an IP2 calibration circuit is applied to the mixer. A new start-up circuit is proposed for the operational amplifier in the transimpedance amplifier. To generate the quadrature clocks, a three-stage RC polyphase filter is used. The measurement results show that, owing to this high-linearity RF front-end, the receiver achieves −15dBm IIP3 and +72dBm IIP2, which satisfies the WCDMA SAW-less requirements.
Effective rule induction from labeled graphs

Labeled graphs provide a natural way of representing objects and the way they are connected. They have various applications in different fields, such as for example in computational chemistry. They can be represented by relational structures and thus stored in relational databases. Acyclic conjunctive queries form a practically relevant fragment of database queries that can be evaluated in polynomial time. We propose a top-down induction algorithm for learning acyclic conjunctive queries from labeled graphs represented by relational structures. The algorithm allows the use of building blocks which depend on the particular application considered. To compensate for the reduced expressive power of the hypothesis language and thus the potential loss in predictive performance, we combine acyclic conjunctive queries with confidence-rated boosting. In the empirical evaluation of the method we show that it leads to excellent prediction accuracy on the domain of mutagenicity.
Evaluating the Effectiveness of Mental Health First Aid Program for Chinese People in Hong Kong

Purpose: Chinese people generally lack knowledge of mental illness. Such phenomenon may lead to a delay in seeking psychiatric treatments. This study evaluated the effectiveness of Mental Health First Aid (MHFA) program in improving mental health knowledge of the general public in Hong Kong. Methods: A quasi-experimental design was adopted whereby 138 participants received MHFA training and 139 partook in seminars on general health, respectively. All participants filled out a standardized questionnaire before, at the end, and 6-month after the training. Results: Findings demonstrated that MHFA training might be effective in enhancing participants’ knowledge of mental disorders, reducing stigma, and improving perceived confidence in providing help to people with mental illness. Effect size statistics revealed mostly modest to moderate improvements in major variables in the experimental group. Conclusion: It is recommended that culturally attuned MHFA program can be used as prevention strategy to promote good mental health in Chinese communities.
Distributed communications resource management for tracking and surveillance networks

We present a market-like method for distributed communications resource management in the context of networked tracking and surveillance systems. This method divides communication resources according to the expected utility provided by information of particular types. By formulating the problem as an optimization of the joint utility of information flow rates, the dual of the problem can be understood to provide a price for particular routes. Distributed rate control can be accomplished using primal-dual iteration in combination with communication of these route prices. We extend the previous work on the subject in a few important ways. First, we consider utility functions that are jointly-dependent on flow rates, to properly account for geometric synergy that can occur in sensor fusion problems. Second, we do not require that the rate-update algorithms have explicit knowledge of utility functions. Instead, our update algorithms involve transmitting marginal utility values. We present simulation results to demonstrate the effectiveness of the technique.
Adaptive multi-resource end-to-end reservations for component-based distributed real-time systems

Complexity in the real-time embedded software domain has been growing rapidly. The component-based software development approach facilitates the development process of such software systems by dividing a complex system into a number of simpler components. Resource reservation techniques have been widely used for providing resources to real-time software components. In this paper we target real-time components operating on a distributed resource infrastructure. Furthermore, we target a class of software components which demonstrate dynamic resource consumption behavior. A prime example of such components is a multimedia software component. In the paper, we present a framework supporting multi-resource endto- end resource reservations. We reserve resource bandwidths on both processor resources as well as on the network resources. The proposed framework utilizes a Multiple Input Multiple Output (MIMO) controller which adjusts the sizes of reservations tracking the dynamic resource demands of the software components. Finally, we present a case study using a multimedia component to demonstrate the performance and efficiency of our framework.
An Active Head Tracking System for Distance Education and Videoconferencing Applications

We present a system for automatic head tracking with a single pan-tilt-zoom (PTZ) camera. In distance education the PTZ tracking system developed can be used to follow a teacher actively when s/he moves in the classroom. In other videoconferencing applications the system can be utilized to provide a close-up view of the person all the time. Since the color features used in tracking are selected and updated online, the system can adapt to changes rapidly. The information received from the tracking module is used to actively control the PTZ camera in order to keep the person in the camera view. In addition, the system implemented is able to recover from erroneous situations. Preliminary experiments indicate that the PTZ system can perform well under different lighting conditions and large scale changes.
The North Lewisham Telepsychiatry Project: Beyond the Pilot Phase

The integration of a telepsychiatry application into an inner-city community mental health service was evaluated over 10 months. ISDN videoconferencing at 128 kbit/s was employed for psychiatric consultation between a primary care centre and a community mental health centre. A convenience sample of patients and referrals seen by videoconferencing was compared with a sample seen face to face. During the study period 19 patients were managed by videoconferencing and 12 face to face. There were 162 consultations, comprising 81 prearranged teleconsultations and 81 prearranged face-to-face consultations. There was no significant difference in attendance between videoconferencing and face-to-face consultations. Nine of the videoconferencing new referrals had not completed their treatment at the end of the study period, compared with only three in the face-to-face group. This implies that it takes longer to complete treatment for new referrals managed by videoconferencing.
Clustering time series, subspace identification and cepstral distances

In this paper a methodology to cluster time series based on measurement data is described. In particular, we propose a distance for stochastic models based on the concept of sub- space angles within a model and between two models. This distance is used to obtain a clustering over the set of time series. We show how it is related to the mutual information of the past and the future output processes, and to a previously defined cepstral distance. Finally, the methodol- ogy is applied to the clustering of time series of power consumption within the Belgian electricity grid.