Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the number of PPG harmonics to assess Smartphone effectiveness

Smart technologies are increasing in popularity due to their current reduction in price and increased accessibility to the lay user. As a result, health monitoring for personalized healthcare is growing in importance. One problem for the current smart technologies is the poorer signal acquisition quality with respect to clinically validated devices. In this paper, we evaluate the minimal required sampling frequency to acquire the Photoplethysmography (PPG) by means of a Smartphone such that the PPG features remain sufficiently accurate. In particular, we show that a sampling frequency of 30 frames per second of the Smartphone camera is sufficient to extract the PPG signal.
Ground truth creation for handwriting recognition in historical documents

Handwriting recognition in historical documents is vital for the creation of digital libraries. The creation of readily available ground truth data plays a central role for the development of new recognition technologies. For historical documents, ground truth creation is more difficult and time-consuming when compared with modern documents. In this paper, we present a semi-automatic ground truth creation proceeding for historical documents that takes into account noisy background and transcription alignment. The proposed ground truth creation is demonstrated for the IAM Historical Handwriting Database (IAM-HistDB) that is currently under construction and will include several hundred Old German manuscripts. With a small set of algorithmic tools and few manual interactions, it is shown how laypersons can efficiently create a ground truth for handwriting recognition.
Supporting Knowledge Work with Knowledge Stance-Oriented Integrative Portals

Portals are an enabling technology for knowledge management (KM): They provide users with a consolidated interface that allows accessing various types of structured and semi-structured information. From the view of KM, their success depends not only on their ability to provide information and knowledge depending on the user’s tasks in business processes (exploitation of knowledge) but also on their ability to support unstructured, creative and learning-oriented actions of knowledge work (exploration of knowledge). However, knowledge management lacks concepts for integrated support of these orientations of knowledge work. The concept of knowledge stance is seen as a promising starting point. This paper presents the INWISS portal prototype that employs Semantic Web technologies for context-based integration of various information sources and applications on a semantic level and discusses extensions to this portal for the support of knowledge stances.
Coordination Mechanisms in Human-Robot Collaboration

—Robots are envisioned to collaborate with people in tasks that require physical manipulation such as a robot instructing a human in assembling household furniture, a human teaching a robot how to repair machinery, or a robot and a human collaboratively completing construction work. These scenarios characterize joint actions in which the robot and the human must effectively communicate and coordinate their actions with each other in order to successfully achieve task goals. Drawing on recent research in cognitive sciences on joint action, this paper discusses key mechanisms for effective coordination—joint attention, action observation, task-sharing, action coordination, and perception of agency—toward informing the design of communication and coordination mechanisms for robots. It presents two illustrative studies that explore how robot behavior might be designed to employ these mechanisms, particularly joint attention and action observation, to improve measures of task performance and perceptions of the robot in human-robot collaboration.
SURVEY AND SUMMARY Recent advances in the elucidation of the mechanisms of action of ribozymes

The cleavage of RNA can be accelerated by a number of factors. These factors include an acidic group (Lewis acid) or a basic group that aids in the deprotonation of the attacking nucleophile, in effect enhancing the nucleophilicity of the nucleophile; an acidic group that can neutralize and stabilize the leaving group; and any environment that can stabilize the pentavalent species that is either a transition state or a short-lived intermediate. The catalytic properties of ribozymes are due to factors that are derived from the complicated and specific structure of the ribozyme–substrate complex. It was postulated initially that nature had adopted a rather narrowly defined mechanism for the cleavage of RNA. However, recent findings have clearly demonstrated the diversity of the mechanisms of ribozyme-catalyzed reactions. Such mechanisms include the metalindependent cleavage that occurs in reactions catalyzed by hairpin ribozymes and the general double-metal-ion mechanism of catalysis in reactions catalyzed by the Tetrahymena group I ribozyme. Furthermore, the architecture of the complex between the substrate and the hepatitis delta virus ribozyme allows perturbation of the pKa of ring nitrogens of cytosine and adenine. The resultant perturbed ring nitrogens appear to be directly involved in acid/base catalysis. Moreover, while high concentrations of monovalent metal ions or polyamines can facilitate cleavage by hammerhead ribozymes, divalent metal ions are the most effective acid/base catalysts under physiological conditions.
Clinical evaluations for transfer of juveniles to criminal court: current practices and future research.

Completing clinical evaluations of juveniles considered for transfer to criminal court requires specialized expertise. However, there is little empirical foundation upon which they can be based. Within each of the three major evaluation domains (amenability to treatment, risk for future violence, and sophistication/maturity), we ask the following questions: a) Can forensic examiners properly assess this area, and if so using what tools? ; b) How can social science research clarify the transfer evaluation, particularly as it is impacted by systems issues? ; and c) How should the evaluation be structured? In doing so, we review clinical suggestions for completing these evaluations and identify pertinent research directions. A number of general issues specific to these evaluations are also discussed.
Quantum and braided linear algebra

Quantum matrices A(R) are known for every R matrix obeying the quantum Yang–Baxter equations. It is also known that these act on ‘‘vectors’’ given by the corresponding Zamalodchikov algebra. This interpretation is developed in detail, distinguishing between two forms of this algebra, V(R) (vectors) and V*(R) (covectors). A(R)→V(R21)⊗V*(R) is an algebra homomorphism (i.e., quantum matrices are realized by the tensor product of a quantum vector with a quantum covector), while the inner product of a quantum covector with a quantum vector transforms as a scaler. It is shown that if V(R) and V*(R) are endowed with the necessary braid statistics Ψ then their braided tensor‐product V(R)⊗_V*(R) is a realization of the braided matrices B(R) introduced previously, while their inner product leads to an invariant quantum trace. Introducing braid statistics in this way leads to a fully covariant quantum (braided) linear algebra. The braided groups obtained from B(R) act on themselves by conjugation in a way impossible.
A Robust Extraction Algorithm Based on a Specific Kurtosis Value Range

Independent component analysis (ICA), blind source separation (BSS) and related methods like blind source extraction (BSE) have been considered as a fundamental data analysis tool in the fields of neural network and signal processing. In this paper, we propose a robust algorithm based on a specific kurtosis value range that can extract a desired source signal as the first output signal with a specific kurtosis value range. That is to say, if we know that the kurtosis value of the desired signal generally lies in a specific range, while the values of other unwanted source signals do not belong to this range, we can use the proposed algorithm to extract the desired signal successfully. Moreover, the algorithm can work well in some poor situation (when the kurtosis values of some source signals are very close to each other). In addition, because of adopting an interior point penalty function method, the algorithm is robust to the estimation error of the kurtosis value range. Finally, we use the proposed algorithm to extract the accurate and reliable fetal electrocardiogram (FECG).
Selective Serotonin Reuptake Inhibitor Use Is Associated with Right Ventricular Structure and Function: The MESA-Right Ventricle Study

Purpose Serotonin and the serotonin transporter have been implicated in the development of pulmonary hypertension (PH). Selective serotonin reuptake inhibitors (SSRIs) may have a role in PH treatment, but the effects of SSRI use on right ventricular (RV) structure and function are unknown. We hypothesized that SSRI use would be associated with RV morphology in a large cohort without cardiovascular disease (N = 4114). Methods SSRI use was determined by medication inventory during the Multi-Ethnic Study of Atherosclerosis baseline examination. RV measures were assessed via cardiac magnetic resonance imaging. The cross-sectional relationship between SSRI use and each RV measure was assessed using multivariable linear regression; analyses for RV mass and end-diastolic volume (RVEDV) were stratified by sex. Results After adjustment for multiple covariates including depression and left ventricular measures, SSRI use was associated with larger RV stroke volume (RVSV) (2.75 mL, 95% confidence interval [CI] 0.48–5.02 mL, p = 0.02). Among men only, SSRI use was associated with greater RV mass (1.08 g, 95% CI 0.19–1.97 g, p = 0.02) and larger RVEDV (7.71 mL, 95% 3.02–12.40 mL, p = 0.001). SSRI use may have been associated with larger RVEDV among women and larger RV end-systolic volume in both sexes. Conclusions SSRI use was associated with higher RVSV in cardiovascular disease-free individuals and, among men, greater RV mass and larger RVEDV. The effects of SSRI use in patients with (or at risk for) RV dysfunction and the role of sex in modifying this relationship warrant further study.
DBLife: A Community Information Management Platform for the Database Research Community (Demo)

Community Information Management: There are many communities on the Web. Some are based on common interests, such as communities of movie goers, database researchers, and bioinformaticians, while others are based on a shared purpose, such as organization intranets and online technical support groups. Community members often want to discover, monitor, and query entities and relationships in their community. For example, database researchers might want to know if there is a connection between two given researchers, where a given paper has been cited in the past week, or what of interest has happened in the last 24 hours. Answering such questions often requires retrieving raw, largely unstructured data from multiple sources (e.g., home pages, DBLP, mailing lists), then inferring and monitoring semantic information. Examples of such inference and monitoring include recognizing entity mentions (e.g., “J. Gray”, “SIGMOD-04”), deciding if two mentions (e.g., “J. Gray” and “Jim Gray”) refer to the same real-world entity, recognizing that a relationship (e.g., co-authoring, advising, giving a talk) exists between two entities, detecting new entities (e.g., new workshops), and inferring that a relationship (e.g., affiliation with a university) has ceased to exist. The above inference and monitoring tasks are well known to be difficult [1, 2, 3, 7, 10]. As online communities proliferate, developing effective solutions to support their information needs becomes increasingly important. We call this problem community information management, or CIM for short.
Neuroimaging and social behavior in children after traumatic brain injury: findings from the Social Outcomes of Brain Injury in Kids (SOBIK) study.

BACKGROUND Neuroimaging studies identified either focal and/or non-specific frontotemporolimbic damage resulting from mild-complicated to severe traumatic brain injury (TBI) in a subset of 12 children 8-12 years of age who were part of the Social Outcomes of Brain Injury in Kids (SOBIK) study. The influence of identifiable damage on social behavior was examined. METHODS Magnetic resonance imaging was obtained on average 2.5 years post injury wherein cases with distinct abnormalities were selected. Various direct, performance-based measures of cognitive-social-emotional functioning were obtained along with data regarding peer relations and friendships in the classroom. RESULTS Overall, children with TBI were impaired on tasks of social-emotional processing compared to children with orthopedic injury (OI). Ten of the 12 children with TBI had multiple areas of impaired social-emotional functioning in comparison to OI controls. With regards to friendships, four of the nine children with TBI who had classroom data had no mutual friends, four also received low peer acceptance ratings, and two were perceived by peers as having high levels of rejection/victimization in the classroom. CONCLUSIONS Children with frontotemporolimbic or diffuse damage demonstrated variable social outcomes from their TBI. Results are discussed in terms of the heterogeneity of TBI-related abnormalities and their relationship to social behavior.
Experiences of overweight/obese adolescents in navigating their home food environment

Abstract Objective To explore perceived factors that impede or facilitate healthful eating within the home environment among overweight/obese adolescents. Design In the present qualitative photovoice study, participants were instructed to take photographs of things that made it easier or harder to make healthful food choices at home. Digital photographs were reviewed and semi-structured interviews were conducted to promote discussion of the photographs. Data were analysed using constant comparative analysis. Setting Vancouver, Canada, in 2012–2013. Subjects Twenty-two overweight/obese adolescents who completed a family-based lifestyle modification intervention. Results The mean age of participants was 14 (sd 1·9) years, 77 % were female and their mean BMI Z-score was 2·4 (sd 0·6). Adolescents talked about six aspects of the home environment that influenced their eating habits (in order of frequency): home cooking, availability and accessibility of foods/beverages, parenting practices, family modelling, celebrations and screen use/studying. In general, homes with availability of less healthful foods, where family members also liked to eat less healthful foods and where healthier foods were less abundant or inaccessible were described as barriers to healthful eating. Special occasions and time spent studying or in front of the screen were also conducive to less healthful food choices. Home cooked meals supported adolescents in making healthier food choices, while specific parenting strategies such as encouragement and restriction were helpful for some adolescents. Conclusions Adolescents struggled to make healthful choices in their home environment, but highlighted parenting strategies that were supportive. Targeting the home food environment is important to enable healthier food choices among overweight/obese adolescents.
Correction: Let-7, Mir-98 and Mir-181 as Biomarkers for Cancer and Schizophrenia

There is an error in the title of this article: “Mir-181” should be “Mir-183. ” The correct title is: Let-7, Mir-98 and Mir-183 as Biomarkers for Cancer and Schizophrenia. The correct citation is: Rizos E, Siafakas N, Katsantoni E, Skourti E, Salpeas V, Rizos I, et al. (2015) Let-7, Mir-98 and Mir-183 as Biomarkers for Cancer and Schizophrenia. PLoS ONE 10(4): e0123522. doi:10.1371/journal.pone. 0123522
Probabilistic Choice Operators as Constraint Combinators: Application to the Statistical Structural Testing Problem

Probabilistic Concurrent Constraint Programming (PCCP) extends concurrent constraint languages by providing probabilistic choice operators. These operators have proved to be useful in implementing randomized algorithms as well as stochastic processes. In this report, we present an instance of PCCP where probabilistic choice operators are modelled with constraint combinators. This modeling allow us to deal with a new kind of problems where the probabilistic choice is only partially known. An implementation under the form of a library of SICStus Prolog is in progress. The major practical application of our work is the statistical structural testing problem in software testing.
Numerical Simulation of Midlatitude Upper‐Level Zonal Wind Response to the Change of North Pacific Subtropical Front Strength

Using the Weather Research and Forecasting model, numerical experiments with reconstructed ideal zonally uniform sea surface temperatures were designed to discuss the midlatitude upper‐level zonal wind response to the change of subtropical front strength over the North Pacific in winter. The results show that the enhancement of the subtropical frontal zone (STFZ) of the North Pacific leads to the stronger upper zonal wind, without considering the lateral boundary barotropic and baroclinic disturbances in this regional model. The enhanced STFZ first results in positive meridional temperature gradient anomalies by affecting the sea surface sensible heat flux. Then the low‐level wind increases because of the increased thermal wind. In addition, the temperature gradient anomalies spread to middle and upper troposphere by baroclinic waves, causing the increase of Eady growth rate and enhanced storm tracks on the southern side of the STFZ and the decrease on the northern side. The strengthened storm tracks give rise to a stronger midlatitude westerly jet accompanied with a southward movement through wave‐mean flow interaction, including both barotropical energy conversion and the Rossby wave breaking.
State-based model slicing: A survey

Slicing is a technique, traditionally applied to programs, for extracting the parts of a program that affect the values computed at a statement of interest. In recent years authors have begun to consider slicing at model level. We present a detailed review of existing work on slicing at the level of finite-state-machine-based models. We focus on state-based modeling notations because these have received sufficient attention from the slicing community that there is now a coherent body of hitherto unsurveyed work. We also identify the challenges that state-based slicing presents and how the existing literature has addressed these. We conclude by identifying problems that remain open either because of the challenges involved in addressing them or because the community simply has yet to turn its attention to solving them.
Random Walks and Green's Function on Digraphs: A Framework for Estimating Wireless Transmission Costs

Various applications in wireless networks, such as routing and query processing, can be formulated as random walks on graphs. Many results have been obtained for such applications by utilizing the theory of random walks (or spectral graph theory), which is mostly developed for undirected graphs. However, this formalism neglects the fact that the underlying (wireless) networks in practice contain asymmetric links, which are best characterized by directed graphs (digraphs). Therefore, random walk on digraphs is a more appropriate model to consider for such networks. In this paper, by generalizing the random walk theory (or spectral graph theory) that has been primarily developed for undirected graphs to digraphs, we show how various transmission costs in wireless networks can be formulated in terms of hitting times and cover times of random walks on digraphs. Using these results, we develop a unified theoretical framework for estimating various transmission costs in wireless networks. Our framework can be applied to random walk query processing strategy and the three routing paradigms-best path routing, opportunistic routing, and stateless routing-to which nearly all existing routing protocols belong. Extensive simulations demonstrate that the proposed digraph-based analytical model can achieve more accurate transmission cost estimation over existing methods.
Survey on Semi-Supervised Feature Selection in Datamining

s: Data mining is one of the knowledge extraction process used to discover the knowledge from large datasets and convert it into useful information. Various techniques implemented for this extracting process. In machine learning, feature selection is most important one to extract the feature from large dataset. Feature selection involves subset generation, assessment and terminating technique for achieving relevant data. This survey shows various machine learning techniques for extracting relevant data. Extraction is not an easiest one, they where many problems occurred due to selection of irrelevant data and main problem in accuracy of the data. This survey shows the problems and challenges of machine learning techniques for achieving the better accuracy from supervised, unsupervised, and semi-supervised learning techniques.
Multitude in motion : re-readings on the political philosophy of Thomas Hobbes

Jakonen, Mikko Multitude in Motion: Re-Readings on the Political Philosophy of Thomas Hobbes Jyväskylä: University of Jyväskylä, 2013, 214 p. (Jyväskylä Studies in Education, Psychology and Social Research ISSN 0075-4625; 466) ISBN 978-951-39-5163-4 (nid.) ISBN 978-951-39-5164-1 (PDF) The present study examines the fundamentally intertwined relation of the concepts of motion and multitude in Thomas Hobbes’s political philosophy. The concept of motion was, as it has been widely recognized in previous research, a basis for Hobbes’s philosophy. Yet, its political nature has not been fully examined before. Furthermore, in recent decades the emphasis given to motion as a central concept in his political philosophy has diminished. On the other hand, the concept of multitude, which is usually understood as an apolitical concept, has been almost totally neglected in Hobbes scholarship. The aim of this research is to bring together these two concepts and show how the structure of Hobbes’s political philosophy depends on the interplay of these two. Thus, we claim that the most crucial problem that structured Hobbes’s political philosophy was the problem of multitude in motion. Hobbes saw that multitude, that is, the unorganized, incoherent, anarchic, and constantly moving and changing mass of human beings was the greatest obstacle for the peaceful and organized political life in the commonwealth. The political problem of the unpredictable behaviour of crowds was already familiar to classical philosophers. Hobbes was, however, dissatisfied with the solutions offered to this fundamental question. In his philosophy he proposed a totally new way of understanding the action of human masses based on the analysis on motion and geometrical method. Hence, to understand how Hobbes applied the new theory of motion introduced by the scientific revolution to his political philosophy, we must see how Hobbes analysed and used the concept of multitude. Through the analysis of Hobbes’s conception of multitude we enable critical re-readings of Hobbes’s political thought. We are interested in his conception of fear and its relation to the government of the state, in Hobbes’s contradictory relationship to democracy, in his distaste for revolution and finally in his vision of international relations. In general, the present research opens new ways of reading Hobbes’s political philosophy as a philosophy of motion.