Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid participant embodiments in networked collaborative virtual environments

The authors present a novel approach to participant embodiment in networked collaborative virtual environments. The embodiment approach integrates live video into 3D objects for a hybrid participant representation. They implemented their ideas in a Networked Collaborative Virtual Environment system, VLNET and investigated network and rendering issues in comparison with virtual human participant embodiment. The paper presents two distinct case studies demonstrating their ideas. The first one is a tele-teaching application, in which they investigate a shared environment with virtual humans and hybrid embodiments. The second one presents a distributed augmented reality application, in which participants share a mixed environment with real and virtual elements.
O R I G I N a L a R T I C L E Open Access

Fungal strain matters: colony growth and bioactivity of the European medicinal polypores Fomes fomentarius, Fomitopsis pinicola and Piptoporus betulinus Abstract Polypores have been applied in traditional Chinese medicine up to the present day, and are becoming more and more popular worldwide. They show a wide range of bioactivities including anti-cancer, anti-inflammatory, antiviral and immuno-enhancing effects. Their secondary metabolites have been the focus of many studies, but the importance of fungal strain for bioactivity and metabolite production has not been investigated so far for these Basidiomycetes. Therefore, we screened several strains from three medicinal polypore species from traditional European medicine: Fomes fomentarius, Fomitopsis pinicola and Piptoporus betulinus. A total of 22 strains were compared concerning their growth rates, optimum growth temperatures, as well as antimicrobial and antifungal properties of ethanolic fruit body extracts. The morphological identification of strains was confirmed based on rDNA ITS phylogenetic analyses. Our results showed that species delimitation is critical due to the presence of several distinct lineages, e.g. within the Fomes fomentarius species complex. Fungal strains within one lineage showed distinct differences in optimum growth temperatures, in secondary metabolite production, and accordingly, in their bioactivities. In general, F. pinicola and P. betulinus extracts exerted distinct antibiotic activities against Bacillus subtilis and Staphylococcus aureus at minimum inhibitory concentrations (MIC) ranging from 31-125 μg mL −1 ; The antifungal activities of all three polypores against Aspergillus flavus, A. fumigatus, Absidia orchidis and Candida krusei were often strain-specific, ranging from 125-1000 μg mL −1. Our results highlight that a reliable species identification, followed by an extensive screening for a 'best strain' is an essential prerequisite for the proper identification of bioactive material.
Judging Models in Legal Fact-Finding

Scientific, statistical, and economic models are often crucial in legal fact-finding. Competing models yielding different inferences may represent the same phenomenon. This article studies the judgment of models in legal fact-finding, in particular where competing models and inferences must be judged. Three categories of the use of models are identified: formal models provided by experts, formal models not scrutinized as expert knowledge, and the use of models more informally to aid storytelling. In the first case, the nature of expert knowledge makes it difficult for non-expert fact-finders to judge the conclusions, which emphasizes the importance of judging the reliability of the methods used to reach the conclusions, both on their own terms and in conjunction with the specific circumstances of the case. In the second case, the challenge is to benefit from the logic of models, but avoid tautologies disguised as expert knowledge. In the latter situation, the methods applied may not be transparent, which emphasizes the need to judge the conclusions on the basis of explanatory power. It is argued that it is important to judge models according to the appropriate standard dependent on their use. The study mainly draws on examples from antitrust, regulation, and torts.
Automatic Word Categorization: An Information-theoretic Approach

This paper presents a novel approach to the automatic categorization of words from raw data. We count occurrences of word pairs in text and use a hierarchical clustering technique on this frequency data to obtain a classification of words into linguistic categories. As a distance criterion in the clustering process, we use the loss of mutual information caused by combining two clusters into a single new cluster. With this method, words are not only classified on the basis of their syntactic categories, but also with respect to aspects that are related to their meanings. The method can form the basis of a system that uses a much finer categorization of words than is feasible using traditional grammar-based approaches. We plan to use it in a layered system of artificial neural networks that are trained to recognize higher-level constituents.
Towards the Composition of Web Services and the Role of the Query Optimization

Recently, the technology of Web Services emerge in the main focus as a new way to develop distributed service- oriented or resource-oriented application. This paper studies the architecture of web services which is built on internet standards that simplify the exchange and integration of large amounts of data over the Internet, and as such they make it easier to conduct work across organizations regardless of the types of programming platform, operating systems, hardware/ software, and database management systems that are being used. To better understand the architecture of Web Services, we will provide analysis of the core protocols and the process of modeling the Orchestration of web services in a specific case study. Composition is the process of defining the communication actions and the internal actions in which a service engages. To integrate data exchanged by web services, the interconnection of web services with databases is needed, with intention to provide backup and better management of data. While we execute a query we need to analyze the performance and estimation of the SQL operations. One of the best methods is to view the query execution plan, which provides information on how a specific DBMS query optimizer runs a specific query. This information is very valuable when we want to find out why a specific query is running slow and determine the cost estimations. The section of the Query Optimizer will help readers to improve the performance of the databases and applications, meaning that they can write better queries, provide the Query Optimizer with the information it requires to produce high execution plans.
Secure Beamforming via Amplify-and-Forward Relays in Machine-to-Machine Communications

We consider the collaborative use of amplify-and-forward relays to form a beamforming system and provide physical layer security for a wireless machine-to-machine (M2M) communication network. We investigate two objectives: (i) the achievable secrecy rate maximization subject to the relay power constraint and (ii) the relay transmit power minimization under a secrecy rate constraint. For the first objective, we propose a secrecy rate maximization (SRM) beamforming scheme. The secrecy rate maximization problem can be formed into a two-level optimization problem and we solve it using semidefinite relaxation (SDR) techniques. To reduce the complexity of the SRM beamforming scheme, a virtual eavesdropper-based SRM (VE-SRM) beamforming scheme is proposed, in which we hypothesize a virtual eavesdropper instead of all eavesdroppers and maximize the secrecy rate according to the virtual eavesdropper. In addition, for the second objective, we design a relay power minimization (RPM) beamforming scheme, in which an iterative algorithm combining the SDR technology and the gradient-based method is devised by studying the convexity of the RPM problem. By relaxing the constraints of the RPM beamforming scheme, we propose a virtual eavesdropper-based RPM (VERPM) beamforming scheme, which reduces the multivariate RPM problem to a problem of a single variable, and thus an analytical solution is obtained. Our proposed beamforming designs can work well even if the number of eavesdroppers is larger than that of relays, while the existing schemes, for example, the null-space beamforming schemes, cannot work under this condition. Simulation results are presented to demonstrate the significance of performance improvements with the SRM and RPM beamforming schemes. It is also shown that the virtual eavesdropper approaches significantly reduce the complexity with acceptable performance degradation.
Making Recommender Systems Work for Organizations

For the past two years, we have been investigating the use of recom m nder systems as a technology in support of knowledge sharing in organizations. Recommender sy st m are a way of extending the natural process of recommendation by word-of-mouth to netw rk d groups of people. They are able to provide personalized recommendations that take in o account similarities between people based on their user profiles. The comm unity around recommender systems that has emerged in the past five or so years has focus ed on methods for constructing and learning user profiles, the exploration and testing of various recomme ndation algorithms, and the design of user interfaces, with applications primarily in the domai ns of electronic commerce and leisure/entertainment. Thus far, we have focused our research in two areas: adapting recomm ndation algorithms and user profile construction methods to take into account prior information re garding the existing organizational social network; and addressing the incentive issues sur rounding the use of a recommender system for knowledge sharing in an organization. In this paper, we describe principally the incentive issues that we have identified and how we ha v attempted to alleviate them. We also report and analyze results from an internal yearlong trial of our recommender tool, the Knowledge Pump.
Halo effect suppression for single image haze removal method

Haze is mainly occurred by atmospheric phenomena. Recently, many researchers in haze removal algorithm area are using single image. At the single image, we can't use depth information. To estimate the thickness of haze without depth information is not easy. As a result, single image haze removal method includes halo effect. In this paper, we propose halo effect suppression for single image haze removal method. Conventional halo removal method required a lot of time, but the proposed method is to lower the computational complexity.
Model-based 2D&3D dominant motion estimation for mosaicing and video representation

It is fairly common in video sequences that a mostly fixed background (scene) is imaged with or without objects. The dominant background changes in the image plane mostly due to camera operations and motion (zoom, pan, tilt, track etc.). We address the problem of computation of the dominant image transformation over time and demonstrate how this can be effectively used for efficient video representation through video mosaicing and image registration. We formulate the problem of dominant component estimation as that of model based robust estimation using M estimators with direct, multi resolution methods. In addition to 2D affine and plane projective models, that have been used in the past for describing image motion using direct methods, we also employ a true 3D model of motion and scene structure imaged with uncalibrated cameras. This model parameterizes the image motion as that due to a planar component and a parallax component. For rigid 3D scenes imaged under camera motion only, least squares (LS) methods with the plane and parallax parameterization are also presented. Furthermore, in the context of robust estimation, in contrast with previous approaches for similar problems, our algorithm employs an automatic computation of a scale parameter that is crucial in rejecting the non dominant components as outliers. <<ETX>>
Eeciently Executing Information Gathering Plans

The most costly aspect of gathering information over the Internet is that of transferring data over the network to answer the user's query. We make two contributions in this paper that alleviate this problem. First, we present an algorithm for reducing the number of information sources in an information gathering (IG) plan by reasoning with localized closed world (LCW) statements. In contrast to previous work on this problem, our algorithm can handle recursive information gathering plans that arise commonly in practice. Second, we present a method for reducing the amount of network tra c generated while executing an information gathering plan by reordering the sequence in which queries are sent to remote information sources. We will explain why a direct application of traditional distributed database methods to this problem does not work, and present a novel and cheap way of adorning source descriptions to assist in ordering the queries.
Effects of Adolescent Violent Victimization on Adult Depression

Many studies have associated adolescent violence exposure with later mental health outcomes, but because violence cannot be randomly assigned, few have established causality. Additionally, few have directly tested whether violence affects boys’ and girls’ psychological health differently. The author hypothesizes that (1) violence has a negative causal effect on depression and (2) the effects of violence on depression are worse for women than for men. Using National Longitudinal Study of Adolescent Health data, the author builds multilevel propensity score models with wave 1 predictors in a cross-lagged two-level hierarchical linear model estimating the effects of wave 2 violence on wave 3 outcomes. The results (1) confirm that women have higher depression scores than men net of other factors, (2) show that violence exposure raises average depression scores for both sexes, and (3) uncover no significant sex differences in effect size of violence on depression.
Recent Applications of Aerosol Sealing in Buildings

Abstract This paper describes two recent applications of aerosol sealing techniques in buildings for improving indoor air quality and reducing energy required for heating, cooling, and ventilation. One application applies a commercially-available duct sealing technology, which has typically been used in single-family applications, to large-building exhaust systems. The initial leakage rates, percent leakage sealed, and issues encountered are presented for several large buildings. The reasons for having this leakage sealed are presented, as are some of the techniques applied when conducting this type of sealing. The average duct leakage for these buildings was 28% of fan flow and the aerosol process sealed over 90% of that leakage. The second application is the use of aerosol sealing techniques for building envelope leaks. The process is similar to that used for sealing leaks in ducts; however it does not depend on injection of the sealant into a carrier flow to transport the sealant to the leaks, and therefore has to address the likelihood of particles settling to the ground, as well as the possibility of particles depositing on vertical surfaces. Laboratory tests investigating the impacts of pressure and particle size on the sealing process are described, as are the results of selected field tests showing how well the process performed when applied at two different stages of new multifamily construction. These tests suggest that the process should be able to achieve better levels of air tightness as compared to manual sealing methods, while including the added benefit of automated air-tightness verification.
The effects of injection modes on instantaneous particle deposition in a realistic human nasal cavity

To understand the instantaneous particle deposition in nasal cavity, effects of two injection models on particle deposition characteristic were discussed in this paper. Based on a realistic human nasal cavity geometry obtained from CT scans, a comparison of deposition pattern in the nasal cavity between single injection and continuous injection was investigated through the Lagrangian approach. The instantaneous airflow field was simulated with the tidal volume of 159 and 318 mL by two sine wave curves at inlet. For the case of single injection, particles have finished deposition in the first half of inhalation, and a negative correlation between the tidal volumes and deposition can be observed when the particle diameter was larger than 10 µm. Moreover, particles were mainly deposited in the turbinate area that was beneficial for aerosol therapy. The inertial parameter was not suitable to predict the particle deposition in the case of single injection. With respect to continuous injection, a reduction in total deposition caused by the deceleration process of inhalation can be observed after 1.5 s. The deposition was closely associated with the time‐varying flow field, and particles were mainly deposited in the anterior region and turbinate area. Besides, the particle deposition increased with the inertial parameter for continuous injection. The results indicated that the injection modes had an influence on both the total deposition and local deposition pattern in the nasal cavity. Copyright © 2016 John Wiley & Sons, Ltd.
Bayes and Empirical Bayes Estimators of Abundance and Density from Spatial Capture-Recapture Data

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.
Use It Too Much and Lose It? The Effect of Working Hours on Cognitive Ability

Using data from Wave 12 of the Household, Income and Labour Dynamics in Australia (HILDA) Survey, we examine the impact of working hours on the cognitive ability of people living in Australia aged 40 years and older. Three measures of cognitive ability are employed: the Backward Digit Span; the Symbol Digits Modalities; and a 25-item version of the National Adult Reading Test. In order to capture the potential non-linear dependence of cognitive ability on working hours, the model for cognitive ability includes working hours and its square. We deal with the potential endogeneity of the decision of how many hours to work by using the instrumental variable estimation technique. Our findings show that there is a non-linearity in the effect of working hours on cognitive functioning. For working hours up to around 25 hours a week, an increase in working hours has a positive impact on cognitive functioning. However, when working hours exceed 25 hours per week, an increase in working hours has a negative impact on cognition. Interestingly, there is no statistical difference in the effects of working hours on cognitive functioning between men and women.
Genomic organisation and regulation of murine alpha haemoglobin stabilising protein by erythroid Kruppel‐like factor

Alpha haemoglobin stabilising protein (AHSP) binds free α‐globin chains and plays an important role in the protection of red cells, particularly during β‐thalassaemia. Murine ASHP was discovered as a GATA‐1 target gene and human AHSP is directly regulated by GATA‐1. More recently, AHSP was rediscovered as a highly erythroid Kruppel‐like factor (EKLF) ‐dependent transcript. We have determined the organisation of the murine AHSP gene and compared it to orthologs. There are two CACC box elements in the proximal promoter. The proximal element is absolutely conserved, but does not bind EKLF as it is not a canonical binding site. In rodents, the distal element contains a 3 bp insertion that disrupts the typical EKLF binding consensus region. Nevertheless, EKLF binds this atypical site by gel mobility shift assay, specifically occupies the AHSP promoter in vivo in a chromatin immunoprecipitation assay, and transactivates AHSP through this CACC site in promoter–reporter assays. Our results suggest EKLF can occupy CACC elements in vivo that are not predictable from the consensus binding site inferred from structural studies. We also propose that absence of AHSP in EKLF‐null red cells exacerbates the toxicity of free α‐globin chains, which exist because of the defect in β‐globin gene activation.
PDE Transforms and Edge Detection

In this paper, we propose the use of partial differential equation (PDE) based novel PDE transforms for determining jump discontinuity locations in piecewise smooth data containting potential isolated jump discontinuities. The PDE transform method involves evolving coupled PDEs under different time scales to extract edge information. Multiscale edge detection is done by varying the parameters and edges of different scales (kinds) are recovered. The focus is on linear PDEs and their implementation using fast fourier transforms (FFTs). We show that PDE tansforms with linear PDEs act as very high order exponential filters. The use of FFTs adapts the PDE transforms for edge detection in spectral data. Experiments are presented in one and two dimensions for detecting edges in signals and images. For giving some background to the use of PDEs in image processing, in general, and edge detection, in particular, we also present a brief discussion of the topic in the beginning sections.
In Vitro Antibacterial Activity of Essential Oils against Streptococcus pyogenes

Streptococcus pyogenes plays an important role in the pathogenesis of tonsillitis. The present study was conducted to evaluate the in vitro antibacterial activities of 18 essential oils chemotypes from aromatic medicinal plants against S. pyogenes. Antibacterial activity of essential oils was investigated using disc diffusion method. Minimum Inhibitory Concentration of essential oils showing an important antibacterial activity was measured using broth dilution method. Out of 18 essential oils tested, 14 showed antibacterial activity against S. pyogenes. Among them Cinnamomum verum, Cymbopogon citratus, Thymus vulgaris CT thymol, Origanum compactum, and Satureja montana essential oils exhibited significant antibacterial activity. The in vitro results reported here suggest that, for patients suffering from bacterial throat infections, if aromatherapy is used, these essential oils, considered as potential antimicrobial agents, should be preferred.