Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a real-time algorithm for the detection of physiological arousal in the presence of motion among children with autism

Anxiety is a clinical concern among some children with autism, for whom such an emotional onset may exacerbate core symptoms. Current treatment options are challenged as many of these children are unaware of their emotional state, and due to autism some children also have difficulties with language and communication which further complicates anxiety diagnoses. In this thesis, we proposed a novel automated anxiety detection algorithm capable of interpreting heart rate arousal in the presence of physical movements , and intuitively notifying the user to engage in anxiety management techniques. The novelty of our proposed algorithm is based on its ability to detect anxiety in presence of motion; this is a challenge as motion and anxiety influence the heart rate similarly. This algorithm was able to account for the changes in heart rate due to motion and detection anxiety with an accuracy, specificity and sensitivity of 92.7% in children with autism.
SPECIFIC LANGUAGE IMPAIRMENT: NEUROPSYCHOLOGICAL AND NEUROLINGUISTIC ASPECTS

SUMMARY This paper discusses neuropsychological and neurolinguistic aspects of specific language impairment (SLI), classified among the developmental speech disorders. SLI constitutes one of the more important manifestations of irregularities in the development process and is among the earliest observed in children. SLI results from the uneven development of linguistic processes – phonological, semantic and/or syntactic – and is caused by hereditary and environmental factors with a negative impact on the activity of the brain. One can speak of SLI in a particular child if the retardation in the development of speech and language reaches 12 months in comparison to the average level of linguistic competence in children of the same calendar age. We do not diagnose SLI if there are other reasons for the observed speech and language symptoms, such as serious sensory and cognitive deficits, permanent developmental impairments (e.g. autism), massive brain injury, or the lack of adequate social and emotional conditions for the development of communication skills. According to WHO categories, SLI manifests itself as an impairment of individual language functions resulting in disturbed communication with other people, which, in turn, leads to a handicap resulting from social isolation, difficulties at school and consequent loss of the opportunity to adapt oneself to adult life in society. Even though the level of impairment in a given patient results from the pathology causing SLI, the handicap level depends on the patient's compensation ability, already available or learned in the rehabilitation process, while the level of limitation depends on the patient's adaptation to the existing situation. The problems of
Circulating testosterone levels and aggression in adolescent males: a causal analysis.

&NA; Empirical analyses conducted within a causal‐analytic framework (path analysis) on a sample of normal adolescent human males suggested that circulating levels of testosterone in the blood had a direct causal influence on provoked aggressive behavior (self‐reports): A high level of testosterone led to an increased readiness to respond vigorously and assertively to provocations and threats. Testosterone also had an indirect and weaker affect on another aggression dimension: High levels of testosterone made the boys more impatient and irritable, which in turn increased their propensity to engage in aggressive‐destructive behavior. Two somewhat parallel dimensions of behavior, intermale and irritable aggression, have been identified in animal research to be under testosterone control.
Clone Removal in Java Programs as a Process of Stepwise Unification

Cloned code is one of the most important obstacles against consistent software maintenance and evolution. Although today's clone detection tools find a variety of clones, they do not offer any advice how to remove such clones. We explain the problems involved in finding a sequence of changes for clone removal and suggest to view this problem as a process of stepwise unification of the clone instances. Consequently the problem can be solved by backtracking over the possible unification steps.
A Low-Cost Power Measuring Technique for Virtual Machine in Cloud Environments

With the development of cloud computing, high energy consumption issue has attracted more and more attentions recently. To achieve the goal of energy conservation, accurately measuring the power consumption of distributed resource is of significant importance. Conventional power models can only provide fine-grained power measurement for physical devices instead of virtualized resources. In this paper, we proposed a novel power measuring technique, which uses performance monitoring counters (PMC) as basic indicator of virtual machine’s power consumption. Meanwhile, we also designed a scheduling algorithm to reduce the measuring errors caused by recursive power consumption. Theoretical analysis indicates that the proposed algorithm can provide bounded error when metering virtual machine’s power. Massive experiments are conducted by using various benchmarks on different platforms, and the results shown the proposed technique is effective and low-cost for measuring the power consumption of virtualized resources in large-scale cloud systems.
Penguins in sweaters, or serendipitous entity search on user-generated content

In many cases, when browsing the Web users are searching for specific information or answers to concrete questions. Sometimes, though, users find unexpected, yet interesting and useful results, and are encouraged to explore further. What makes a result serendipitous? We propose to answer this question by exploring the potential of entities extracted from two sources of user-generated content -- Wikipedia, a user-curated online encyclopedia, and Yahoo! Answers, a more unconstrained question/answering forum -- in promoting serendipitous search. In this work, the content of each data source is represented as an entity network, which is further enriched with metadata about sentiment, writing quality, and topical category. We devise an algorithm based on lazy random walk with restart to retrieve entity recommendations from the networks. We show that our method provides novel results from both datasets, compared to standard web search engines. However, unlike previous research, we find that choosing highly emotional entities does not increase user interest for many categories of entities, suggesting a more complex relationship between topic matter and the desirable metadata attributes in serendipitous search.
On Reliable One-way Transmission of Data over Simple Wireless Channels

Standard protocols for reliable data transmission over unreliable channels are based on various ARQ (Automati c Repeat reQuest) schemes, whereby the sending node receives feedback from the receiver and retransmits the missing data . We discuss this issue in the context of one-way data transmissi on over simple (low-cost) wireless channels, characteristic of many sensing and monitoring applications. While in most of such applications occasional loss of data is acceptable, there e xist areas (notably medical monitoring), where the objective is to del iver all samples collected by the wireless device. Using a specifi application as an example, we demonstrate how the constrain ts of an embedded wireless system affect the problem and, in particular, preclude the use of popular schemes based on win dows and periodic acknowledgments. We also propose a family of solutions to the problem and demonstrate their advantage ov er the traditional protocols. keywords: wireless sensors, wireless communication, monitoring, protocols, reliability.
Primary Systemic Anaplastic Large Cell Lymphoma in Korean Adults: 11 Years' Experience at Asan Medical Center

Purpose Anaplastic large cell lymphoma (ALCL), a CD30+ T-cell non-Hodgkin's lymphoma, represents only 2 - 8% of lymphoma overall. Information on the clinical findings of primary systemic ALCL in Korea is limited. Our aims were to report the clinical features and outcomes of primary systemic ALCL. Patients and Methods We retrospectively reviewed the medical records of 36 adult patients diagnosed with primary systemic ALCL at Asan Medical Center from February 1995 through June 2006. Results Of 36 patients, 29 were male. The median age was 39 years (range, 17 - 67 years), and 26 (72%) presented with Ann Arbor stages III and IV. The most commonly involved extranodal sites were bone (n = 7) and soft tissue (n = 6). Thirty-two of all patients (89%) were treated with an anthracycline-based regimen including cyclophosphamide/doxorubicin/vincristine/prednisone (CHOP) as induction chemotherapy; 16 (50%) achieved complete remission (CR), and 13 (41%) achieved partial remission (PR). Median overall survival (OS) and event-free survival (EFS) were 49 and 17 months, respectively. Univariate analysis showed that performance status (p = 0.035), international prognostic index (IPI) (p = 0.025), and age-adjusted IPI (p = 0.034) were significant prognostic factors for OS, whereas anaplastic lymphoma kinase (ALK) expression did not affect OS (p = 0.483). Conclusion Our retrospective analysis of Korean primary systemic ALCL patients showed that median OS was 49 months and overall response to CHOP was 91%. Performance, IPI, and age-adjusted IPI were predictors of OS, whereas ALK expression did not have prognostic significance.
STRUCTURE AND TEXTURE SYNTHESIS

An approach for filling-in blocks of missing data in wireless image transmission is presented in this paper. When compression algorithms such as JPEG are used as part of the wireless transmission process, images are first tiled into blocks of 8x8 pixels. When such images are transmitted over fading channels, the effects of noise can destroy entire blocks of the image. Instead of using common retransmission query protocols, we aim to reconstruct the lost data using correlation between the lost block and its neighbours. If the lost block contained structure, it is reconstructed using an image inpainting algorithm, while texture synthesis is used for the textured blocks. The switch between the two schemes is done in a fully automatic fashion based on the surrounding available blocks. The performance of this method is tested for various images and combinations of lost blocks.
Towards Content-Oriented Integration for Process-Centric Knowledge Management Systems

Work¿ow Management System (WfMS) which focuses on controlling, monitoring, optimizing and supporting business processes management is extensively used in Knowledge Management Systems (KMS). But traditional WfMS only work with complete processes on the basis of process models and therefore fail to support a large class of knowledge intensive business processes such as content-oriented integration. In this paper, a service-oriented framework supporting effective content-oriented integration for process-centric KMS is proposed. This framework uses a hybrid process-driven navigation mechanism including content-oriented high-level process and content fragments-oriented micro process. Representational State Transfer (REST) based interface is used to interact with outer entities to increase flexibility and extensibility in constructing complex knowledge intensive applications. A content-oriented services activation and composition meta-data model is given to map relationships among processes, services and related content and its fragments which is used to activate corresponding processes and transform service context into message exchange objects transmitted in enterprise service bus. Finally, the overview, design and implementation of the prototype system are illustrated.
Local Spatial and Temporal Processes of Influenza in Pennsylvania, USA: 2003–2009

Background Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health's influenza surveillance system. Methodology and Findings We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003–2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic. Conclusions These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs.
FLEXIBLE GENERATION OF SEMANTIC 3D BUILDING MODELS

The paper presents a new 3D semantic building model dedicated to urban development. It provides the following special semantic features: storeys, passages, opening objects, and building variants, modelling different levels of detail and design respectively temporal variants. The model also includes a parametric part supporting easy generation of buildings and building variants in the urban design phase. In order to make the powerful tools of the CA(A)D world accessible to city modeling, a toolbox is being developed for transformation of IFC data. These extensions and addition facilitate multiple utilization of city models and thus enhance sustainability of modeling.
An Even Sterner Review: Introducing Relative Prices into the Discounting Debate

By estimating that the cost of unmitigated climate damages is an order of magnitude higher than most earlier estimates, the Stern Review on the Economics of Climate Change has had a major influence on the policy discussion on climate change. Not surprisingly, severe criticism has been levied against the report, especially by those who claim that the Stern Review's results hinge mainly on a discount rate that is too low. While we have no strong objections to the discounting assumptions adopted in the Stern Review, our main point in this article is that the conclusions reached in the Stern Review can be justified without using a low discount rate. We argue that nonmarket damages from climate change are probably underestimated and that future scarcities caused by the changing composition of the economy and climate change should lead to rising relative prices for certain goods and services. This will raise the estimated damage of climate change and modify as well as counteract the effect of discounting. We illustrate this effect using a slightly modified version of Nordhaus's DICE model and show that taking relative prices into account can have as large an effect on economically warranted abatement levels as a low discount rate.
An Analysis of the Methods Employed for Breast Cancer Diagnosis

Breast cancer research over the last decade has been tremendous. The ground breaking innovations and novel methods help in the early detection, in setting the stages of the therapy and in assessing the response of the patient to the treatment. The prediction of the recurrent cancer is also crucial for the survival of the patient. This paper studies various techniques used for the diagnosis of breast cancer. Different methods are explored for their merits and de-merits for the diagnosis of breast lesion. Some of the methods are yet unproven but the studies look very encouraging. It was found that the recent use of the combination of Artificial Neural Networks in most of the instances gives accurate results for the diagnosis of breast cancer and their use can also be extended to other diseases.
v-Glove: A 3D Virtual Touch Interface

Traditional interaction devices such as mouse and keyboard do not adapt very well to immersive environments, since they were not ergonomically designed for it. The user may be standing or in movement and these devices were projected to work on desks. Moreover, in the current interaction model for immersive environments, which is based on wands and 3D mice, a change of context is necessary every time to execute a non-immersive task. These constant context changes from immersive to 2D desktops introduce a rupture in the user interaction with the application. The objective of this work is to develop a device that maps a touch interface in a virtual reality immersive environment. In order to interact in 3D virtual reality immersive environments a wireless glove (v-Glove) was created, which has two main functionalities: tracking the position of the user's index finger and vibrate the fingertip when it reaches an area mapped in the interaction space to simulate a touch feeling. Quantitative and qualitative analysis were performed with users to evaluate the v-Glove, comparing it with a gyroscopic 3D mouse.
Neurodynamic non-invasive fetal electrocardiogram extraction

Fetal electrocardiography in contrary to adult is not that well represented in publications, yet circulatory system of the fetus is probably the most valuable and crucial biological infrastructure. Fetal heart ratio, form of QRS-wave and dynamics of cardiovascular system activity allow estimating fetus state, maturity, possibilities of heart abnormality occasion. This information can be received with guaranteed accuracy through Doppler-ultrasound procedure, however duration of such kind of monitoring is limited. Fetal electrocardiogram is an obvious source of information about fetal heart activity. However, because of low signal-to-noise ratio and prevailing of maternal component, non-invasive ways of acquiring this signal do not guarantee absolute accuracy. Problems of non-invasive electrocardiography demand complex mathematical approaches because maternal and fetal R-peaks overlap in time and frequency domains and have similar morphological structure of heart waves. In this paper we propose approach for extracting fetal electrocardiography from abdominal signal, which is based on dynamic neural network. The common problem for both dynamic and deep learning is caused by linearity of backpropagation and thus vanishing or exploding of gradients occurs. We proposed resilient propagation through time approach that unites training based on sign of derivative and parallel unfolding. We compared developed algorithm with blind source separation through independent component analysis and noted several important advantages that our model delivers - accuracy does not depend on: length of signal; amount of independent channels.
Analysis of recurrent gap time data using the weighted risk‐set method and the modified within‐cluster resampling method

The gap times between recurrent events are often of primary interest in medical and epidemiology studies. The observed gap times cannot be naively treated as clustered survival data in analysis because of the sequential structure of recurrent events. This paper introduces two important building blocks, the averaged counting process and the averaged at‐risk process, for the development of the weighted risk‐set (WRS) estimation methods. We demonstrate that with the use of these two empirical processes, existing risk‐set based methods for univariate survival time data can be easily extended to analyze recurrent gap times. Additionally, we propose a modified within‐cluster resampling (MWCR) method that can be easily implemented in standard software. We show that the MWCR estimators are asymptotically equivalent to the WRS estimators. An analysis of hospitalization data from the Danish Psychiatric Central Register is presented to illustrate the proposed methods. Copyright © 2010 John Wiley & Sons, Ltd.
Mississippi college students’ attitudes, willingness to intervene and legal knowledge toward sexual assault

ABSTRACT Sexual assault on college campuses has been a longstanding problem in the USA. Unfortunately, relatively little has been done to look at the characteristics of these attacks and how they might relate to knowledge of sexual assault policies, participation in sex education courses, beliefs toward sexual violence, and willingness to intervene if an attempted assault is observed. In response to this need, data were collected from college students from four universities in the state of Mississippi. A request to participate in an online, anonymous questionnaire was sent through email and listservs, and a total of 4,994 undergraduate students completed the survey. A significant relationship was found between men’s sexual attitudes and understanding of legal terms and their willingness to intervene if a sexual assault occurred; less legal knowledge and higher rape myth attitudes reduced their probability of being willing to intervene. Conversely, students who had received education at college on how to prevent a sexual assault from occurring were significantly to report being willing to intervene.
Intra-frame and Inter-frame Coding of Speech LSF Parameters Using A Trellis Structure

Linear Predictive Coding (LPC) parameters are widely used in various speech processing applications for representation of the spectral envelope of speech. Low bit-rate speech coding applications, require accurate quantization of these parameters using as few bits as possible. Line Spectral Frequency (LSF) representation is the most widely accepted representation of LPC parameters for quantization, since they posses a number of advantageous properties including lter stability preservation and spectral selectivity. The vector quantizers are more e cient than scalar quantizers in accurate quantization of these parameters, however, they are prohibitively complex. In this work, a low bit-rate Block-based Trellis Quantization (BTQ) scheme is introduced to overcome the complexity problem. The states in the trellis diagram corresponds to quantized LSF parameters and the branches correspond to the LSF di erence code-words. A weighted Euclidean distance is employed to incorporate the properties of human perception system. The search and design algorithms for the BTQ are presented and an e cient algorithm for the index generation ( nding the index of the path in the trellis) is introduced. The proposed BTQ achieves the transparent coding quality of speech at 23 bits/frame (1150 b/sec.) with a very low level of complexity. This refers to a gain of 3 b/frame (150 b/s) and signi cant reduction in complexity, compared to the Split-VQ of Paliwal and Atal [21]. In this work, an inter-frame BTQ scheme is also presented to exploit the redundancies between the adjacent frames. The inter-frame scheme is found to achieve an additional 50 bits/sec. reduction of the bit-rate, with slightly higher complexity.